1 
 

 

BUSINESS MODEL INNOVATION:  

A BLUEPRINT FOR STRATEGIC CHANGE  

 

 

 

 

 

 

Chander Velu 

Department of Engineering and Selwyn College 

University of Cambridge 

 

 

 

Published by Cambridge University Press 

2024 

  



2 
 

CONTENTS 

 

PREFACE  

ACKNOWLEDGEMENTS  

LIST OF FIGURES  

 

CHAPTER 1: THE IMPERATIVE FOR BUSINESS MODEL INNOVATION 

CHAPTER 2: BUSINESS MODELS AND CREATING MARKETS  

CHAPTER 3: ORGANISATIONAL STRUCTURE AND LEADERSHIP  

CHAPTER 4: DIGITAL TECHNOLOGIES AND TRANSFORMATION  

CHAPTER 5: DIGITAL PLATFORMS AND ECOSYSTEMS 

CHAPTER 6: SMALL AND MEDIUM-SIZED ENTERPRISES AND START-UP 

BUSINESS MODELS  

CHAPTER 7: SUSTAINABILITY AND BUSINESS MODELS  

CHAPTER 8: BUSINESS MODELS FOR SOCIO-ECONOMIC DEVELOPMENT  

CHAPTER 9: CONDUCT RISK AND BUSINESS MODELS 

CHAPTER 10: CONCLUSION 

INDEX 

 

 

 



3 
 

Chander Velu is Professor of Innovation and Economics in the Institute  for Manufacturing 

(IfM) at the Department of Engineering, University  of Cambridge. He heads the Business 

Model Innovation Research Group  at the IfM. Professor Velu is Fellow at Selwyn College, 

Cambridge and Fellow of the Institute of Chartered Accountants in England and Wales. Prior 

to joining the IfM, he was a member of the faculty at  Cambridge Judge Business School. He 

has worked as a consultant with PricewaterhouseCoopers and Booz Allen & Hamilton in 

London. 

  



4 
 

 

Preface 

A plethora of new start-ups were launched to disrupt incumbent firms across a range of 

industries in the late 1990s and early 2000s, during what has come to be known as the era of 

the dot.com bubble. Often, people left secure employment to harness the opportunities provided 

by the Internet to launch new businesses that would disrupt their loyal employers or other 

incumbent firms that relied on the inefficiencies of the market to sustain their superior 

competitive advantage. During this exciting period, I joined one of the major global strategy 

consulting firms at the time, Booz Allen & Hamilton. My very first assignment at the firm was 

a strategy-evaluation project for a major global news and information service provider whose 

share price had declined rapidly, as the market felt it did not have a coherent e-commerce 

strategy. A team was assembled in London to work on this assignment in record time. After 

several weeks of intense work, our proposed e-commerce strategy was received with 

enthusiasm by the senior management; however, the firm found it challenging to implement 

the strategy because each department had an urgent current operational issue to address. There 

was a lack of common ownership of the business model, which made it difficult to coordinate 

the response internally to develop new business models. This resulted in a lethargic response 

by our client, with the consequence that they missed the opportunity to become a pioneer in 

leveraging the business opportunities provided by the Internet.  

This experience sowed the seeds of my interest in business model innovation. I worked 

on several high-profile strategy-formulation assignments with major blue-chip firms, which 

demonstrated a similar inability on the part of management to innovate business models despite 

having a great deal of knowledge about Internet-based technologies. I could not fully 

understand the dynamics of the decision-making process and the resource-allocation issues to 

drive strategic business model innovation from the vantage point of a management consultant, 



5 
 

as the demands of the next assignment did not allow for such reflection. Hence, I decided with 

great trepidation to pursue my doctoral studies at the Cambridge Judge Business School to 

develop a deeper theoretical understanding of business model innovation resulting from new 

digital technologies. I initially studied the global financial services market before pursuing my 

interest across other manufacturing and service-driven industries when I joined the Institute for 

Manufacturing at the Cambridge University Engineering Department. I quickly realised that 

many of the grand challenges of society, such as the productivity paradox and economic 

growth, climate change, poverty alleviation, health and biodiversity, among others, require 

innovative business models. Moreover, novel business models are often the catalyst to enable 

digital and other emerging technologies such as quantum technologies to provide benefits to 

society. In fact, as I learnt about business model innovation through research and discussions 

with senior executives, more questions arose in my mind – reminding me of Charles Darwin’s 

insightful quote, “The pleasure of knowing things always goes on increasing the more one 

knows”.  

This book is an attempt to pause and take stock of the knowledge in the area of business 

model innovation and to highlight what we know and the topics we need to explore further. I 

hope this book will provide the scaffolding to enable scholars, managers and policy-makers to 

ask the right questions in a truly collaborative effort to discover and shape our understanding 

of business model innovation in order to build a better world for us all as we face the next 

generation of grand societal challenges. 

 

Chander Velu 
Cambridge 
 

  



6 
 

Acknowledgements 

Although I have been fortunate to be given the opportunity to hold the pen in writing this book, 

it has been a collaborative effort, with contributions from many people. Several individuals 

have helped to shape my thinking and the contents of this book. I would like to thank my 

students and researchers at the Cambridge Business Model Innovation Research Group. In 

particular, my current and former PhD students and Research Associates have performed a 

crucial role in teaching me patience and the ability to learn from their insights. It has been 

delightful to learn from all of you equally. Stuart Madnick at the Massachusetts Institute for 

Technology has been a mentor and a great role model and inspiration for my academic work 

ever since I visited his research group back in 2004. His enduring support provided me with 

the confidence to pursue an academic career. I would also like to thank Sir Mike Gregory, Tim 

Minshall, Duncan McFarlane and Andy Neely. Sir Mike was crucial in encouraging me to be 

bold in my ambition to build a research group on business model innovation when I joined the 

Institute for Manufacturing (IfM) at the Cambridge University Engineering Department. Tim, 

Duncan and Andy have been great mentors ever since I joined the IfM. They have helped me 

to embrace and complement the strengths of the Engineering Department and have been 

extremely supportive in my research and personal development by encouraging me to go 

beyond my comfort zone to explore new areas of research at the crossroads of engineering, 

economics and management.  

I would also like to thank Geoff Meeks for providing the intellectual partnership to 

develop some challenging issues on conduct risk and business models. Thanks also go to my 

collaborators, colleagues and friends who have provided stimulating discussions and stretched 

my thinking on this topic – Sergei Savin, Jonathan Gair, Philip Stiles, Marshall Van Alstyne, 

Jan Heidi, John Deighton, Wayne Hoyer, Michael Pollitt, Gishan Dissanaike, John Metseelar, 

Rita Shor, Ataman Ozyildirim, Anne Greer, Roger McKinlay, Golnar Pooya, Philip Daslzell-



7 
 

Payne, Toni Vidal-Puig, Andi Smart, Mike Jones, Sir Charlie Mayfield, Arun Jacob, Evert 

Geurtsen, Dominic O’Brien, Chris Noble, Keith Norman, Charles Popper, Jamie Cattell, Andy 

Page, Mahima Khanna, Jeff Alstott, Abdul Mumit, Rob Glew, Stefan Kurpjuweit, Stephan 

Wagner, Maximilian Klöckner, Mark Phillips, Charles Baden-Fuller, John Nicholson, Steven 

Pattinson, Michael Ehret, Paul Ryan, Dan Friedman, Hyunkyu Park, Liz Salter, Janet Hao, 

Arnoud De Meyer, Adam Brandenburger and Youngjin Yoo. I am also very grateful to various 

students and Research Associates, whose excellent research work contributed to various 

chapters of this book – Fathiro Putra, Myungun Kim, Philip Chen, Sudhir Rama Murthy, 

Jiashun Huang, Nikolai Kazantsev, Zurina Mokhtar, Ghanim Al-Sulaiti, Philipp Koebnick, 

Chen Ye, Julius Bock, Luka Gebel, Pengbo Qi, Yuzhen Zhu and Wit Wannakrairoj. Selwyn 

College has provided me with a stimulating inter-disciplinary intellectual environment, while 

also offering a sanctuary for my mind. Thank you to the Fellows of Selwyn College, and I am 

particularly grateful to the Master, Roger Mosey, for his friendship and encouragement. I 

would like to express my grateful thanks to Valerie Appleby, my Editor at Cambridge 

University Press, for her guidance and advice, which are much appreciated. Thank you to 

Carrie Parkinson from Cambridge University Press and Alice Gregory for their help and 

editorial assistance. And thank you to Amanda George for painstakingly copy-editing the drafts 

of the chapters with such care and professionalism.  

I would also like to thank the Engineering and Physical Sciences Research Council 

(EPSRC) and the Economic and Social Research Council (ESRC) for providing the funding 

for my research. In particular, the EPSRC Digital Economy Fellowship allowed me to pursue 

the broad area of productivity, digital technologies and business model innovation. The 

Fellowship has also given me the time to pursue new and exciting areas of research in quantum 

technologies and the implications for business model innovation. And it allowed me to take 

time out from normal teaching and administrative duties and to focus on writing the book. 



8 
 

Thank you also to my colleagues at the IfM, in particular, Florian Urmetzer and Judith 

Plummer, for taking on a substantial part of my teaching and administrative responsibilities 

during the Fellowship. The ESRC also provided funding through The Productivity Institute – 

my very grateful thanks to Bart Van Ark and Tony Venables for their leadership and 

encouragement.  

I would like to thank my family for their continuous support and encouragement 

throughout. My father, the late Mr Kathir Velu, and Mrs Thanam Velu laid the foundations for 

being ambitious in whatever I do and for teaching me the merits of contributing to society. My 

father, with the enduring support of my mother, played a crucial role in encouraging me to 

apply to Cambridge based on reading an advertisement in the local newspaper in Malaysia for 

a British Council Scholarship to study for a Master’s course. This was the start of my academic 

career – many thanks are due to my parents for their wholehearted love, prayers and the 

foresight to guide me. I would also like to thank my brother, Ramani, for his brotherly advice 

and support over the years. Thank you also to my parents-in-law, Srilata and S.R. Iyer, Soumya 

and Mukund, for their prayers, blessings and love.  

Finally, I would like to dedicate this book to my wife, Sriya Iyer, for her undivided love 

and support. You have provided me with the wind beneath my wings when I needed to fly and 

the breeze to relax and reflect when I needed to think. You have been a most gracious and 

elegant intellectual and life partner, making our lives truly enjoyable and meaningful. This 

book was made possible through your inspiration and encouragement – My Most Grateful 

Thanks. 

Chander Velu 
Cambridge 
 
 

 



9 
 

List of Figures 

Figure 1.1: Components of the Business Model 

Figure 1.2: Strategy, Business Models and Tactics 

Figure 1.3: Share Price of Netflix and Blockbuster 

Figure 1.4: Profitability of Netflix and Blockbuster 

Figure 2.1: Changing the Meaning of Markets 

Figure 2.2: A Frame for Deframing 

Figure 3.1: Dual Business Model Strategies 

Figure 3.2: BMCS Coherence Matrix 

Figure 5.1: Layered Modular Architecture 

Figure 7.1: Sustainable Business Model Archetypes 

Figure 7.2: Four Sources of Value Creation for Circularity 

Figure 8.1: Social Business Versus Other Types of Business 

Figure 8.2: Grameen and Telenor – Creating the Supply Chain 

Figure 8.3: Map Agro and Waste Concern – Creating Demand 

Figure 8.4: Weather Risk for Farmers 

Figure 8.5: Horn of Africa Risk Transfer for Adaptation (HARITA) Programme 

Figure 9.1: Subprime Mortgage Supply Chain 

Figure 9.2: Leverage of US Investments Banks 

Figure 10.1: Belvedere House 

 

List of Tables 

Table 3.1: Innovation Readiness Level Methodology 

Table 3.2: Revenue and Cost Coherence Analysis Report 

Table 9.1: Income Statement of Lehman Brothers 

Table 9.2: Balance Sheet of Lehman Brothers 

 

 

 

 

 



10 
 

CHAPTER 1: THE IMPERATIVE FOR BUSINESS MODEL INNOVATION 

 

Nothing is so practical as a good theory. 

(Kurt Lewin) 

 

1. Introduction 

The concept of the business model has become especially prominent in recent times, even 

though it has been in use among business practitioners and academic scholars for a long time 

(Massa and Tucci, 2017; Teece, 2010). Alfred Chandler, the prominent Harvard business 

historian, outlined eloquently that American firms transformed themselves via vertical and 

horizontal integration from 1840 onwards following the emergence of the railroad for 

transportation, telegraph for communication and coal as a major source of energy (Chandler, 

1977). Moreover, Joan Robinson, the distinguished Cambridge economist – in her famous 

article discussing the production function and the theory of capital – posited that each 

production technique might display different degrees of mechanisation involving its own 

specific blueprints, and there may be no recognisable items in common between one and any 

other (Robinson, 1953–4). Although Chandler and Robinson did not explicitly use the term 

“business model”, the spirit of their analysis describes the architecture of firms that contribute 

to performance differences.  

The more recent prominence of business models was predominantly fuelled by the 

Internet and by digital technologies. Amazon.com, Uber, Airbnb, Google, Netflix and 

Southwest Airlines are firms that are founded on business model innovations; that is, 

innovations1 that involve changes to a business's value proposition combined with changes to 

 
1 Joseph Schumpeter had proposed that the process of technological change in a free market consists of three 
phases: invention whereby a new idea or process is conceived, innovation whereby arranging the economic 
and social processes for implementing an invention and diffusion whereby stakeholders adopt the new 
discovery adopt or imitate it (Schumpeter 1939, 1942). 



11 
 

how the value is created and captured by the firm and the network of partners required to do 

so. Moreover, competitive pressures have pushed business model innovation high up the 

priority list of firms worldwide (Global Innovation Barometer, 2013; Hao, Hicks, Popper, and 

Velu, 2020). Perhaps unsurprisingly, not a day seems to go by without some new prescription 

in the popular press advising managers on how to deal with the challenges and opportunities 

posed by such innovation. Business model innovation can create huge opportunities, while 

threatening traditional means of generating revenue (Zott and Amit, 2008). As a consequence, 

business model innovations can create the fortunes of some firms, while killing the market 

positions of others (Velu, 2015). Incumbent firms, who may not have implemented such 

innovations, are forced to wrestle with decisions that can profoundly affect their future. New 

firms need to grapple with decisions about how best to design new business models that disrupt 

existing industries or create new markets for their propositions.  

One indicator of the importance of business models is the surge in prominence of the 

number of articles in the Financial Times using the term “business model”: this number grew 

from 10 in 1995 to over 2,027 in 2021. A similar trend is evident in other major business 

newspapers around the world, including The Wall Street Journal in the United States and The 

Economic Times in India. Surveys of CEOs suggest that firms that emphasise business model 

innovation have grown their operating margins faster than their competitors (Hao, Hicks, 

Popper, and Velu, 2020). Moreover, a survey of senior executives in 25 countries found that 

business model innovation is at the top of all forms of innovation on their priority lists (Global 

Innovation Barometer, 2013).  

Business model innovation is also a critical enabler of productivity improvements. 

Productivity growth has slowed down in the last decade in major economies, as well as in 

emerging markets, despite the prevalence of digital technologies (Bean, 2016). This 



12 
 

phenomenon is widely known as the productivity paradox (Syverson, 2011).2 Moreover, 

industries that are the most intensive users of information and communication technologies 

(ICT)3 appear to have contributed most to the slowdown in productivity (Van Ark, 2016). There 

could be many reasons for the productivity paradox, including: the skills’ mismatch due to 

changes in product market structures driven by digitalisation; the slowdown in technological 

diffusion between firms at the front of the technological frontier and others; and the legacy of 

the financial crisis causing dislocated markets and mismeasurement as a result of the digital 

economy providing significant propositions for free. However, studies on the history of new 

technologies have shown that productivity improvements might be hampered by the limited 

redesign of business models following the adoption of new technologies by firms. For example, 

in the US, productivity gains were very limited when electric motors first replaced the steam 

engine on an industrial scale in the late nineteenth century. It was only when firms completely 

changed their business processes and corresponding business models that technology had a 

significant impact – and that took over forty years (David, 1990). 

A business model can be seen as a complex organisational system that aims to transform 

input into valuable propositions for customers. Business models often act as the bridge between 

technology and the ability to deliver a compelling customer value proposition. Hence, the 

ability to experiment with new technologies, and to develop associated business models, is 

potentially a major source of productivity gains and growth for both new and established firms 

(OECD, 2015). Although new technologies often act as the catalyst for business model 

innovation, they are not necessary for the emergence of new business models. For example, 

the emergence of the Metro as one of the leading newspapers in the world was not due to any 

 
2 Global labour productivity (output per worker) growth slowed down from 2.4% to 2.1% between 1996 and 
2006 and between 2007 and 2014. Total factor productivity growth displayed an even larger slowdown from 
1.3% to 0.3% during the same period (Van Ark, 2016). 
3 Measured by purchases of ICT assets and services relative to GDP. 



13 
 

particular new technology; its free-sheet business model is based on distributing the paper free 

of charge to commuters in busy cities. The Metro earns its revenue from advertisements, which 

represents a major difference when compared to conventional newspapers that earn revenue 

from subscriptions or sales at news-stands.  

Business model innovations can be disruptive when they change the bases of 

competition by altering the performance metrics along which firms compete (Markides and 

Oyon, 2010). Such disruptive business models can manifest themselves through acquiring the 

customers and beneficiaries of the dominant business model by improving their efficiency in 

the provision of the existing customer value proposition or by creating a new market for an 

improved value proposition. The implications of disruptive business models are evident across 

many industries, including: low-cost airlines, for example, Southwest Airlines; the retail book 

industry, for example, Amazon; and Google, with its search engine and related services; and, 

more recently, the taxi and hotel industries, with the emergence of firms such as Uber and 

Airbnb, respectively. However, how these business models emerge and disrupt industries, and 

the leadership and organisational design challenges inherent in managing them, are among the 

issues that scholars and managers are trying to understand better. This book aims to address 

some of these issues by bringing together the research on business model innovation and 

identifying areas for future research while highlighting the implications for management. 

1.1. Strategy, Business Models and Tactics 

Scholars have provided various definitions of a business model. These definitions vary from 

the stories that explain how enterprises work (Magretta, 2002), the resources and processes that 

are put together to create and capture value (Johnson, Christensen, and Kagermann, 2008) or 

the structural template of how the focal firm connects to factor and product markets (Zott and 

Amit, 2008). The common theme in these definitions rests on how the revenue model and the 



14 
 

underlying cost structure, as a result of the operations, create and deliver the customer value 

proposition.  

Business models are a form of activity system that connects the internal aspects of the 

firm, such as resources and routines, with the external aspect, such as partners, markets and 

customers, and hence articulates how the firm goes to market to implement the strategy (Baden-

Fuller and Haefliger, 2013; Zott and Amit, 2010; Zott, Amit, and Massa, 2011). The business 

model as an activity system has three key design parameters, namely, content, structure and 

governance. Content outlines which activities are part of the business model. Structure is about 

how these activities are linked to one another. Finally, governance relates to who can make 

decisions about them. The business model acts as a mechanism for actors to collectively form 

a shared understanding based on rules, norms and beliefs in order to guide their choices 

(Chesbrough and Rosenbloom, 2002b; Doganova and Eyquem-Renault, 2009). In this sense, 

business models are the “architecture” that provides the bridge between the value created for 

customers and the value captured by the business in terms of profit.4 A business model can be 

viewed as a complex system with components that connect the customer value proposition, 

how value is created, the means of value capture and the partners in the value network (Velu, 

2017). Management’s objective is to manage the dynamic consistency by maintaining 

congruence between the components of the business model in order to ensure efficiency, while 

enabling innovation of the business model (Velu, 2020).  

We propose the 4Vs of the business model: value proposition, value creation, value 

capture and value network (Velu, 2018). Business models define the organisation’s customer 

value proposition, and its approach to value creation, and the means of value capture and the 

partners in the value network. This is illustrated in Figure 1. Business model innovation 

 
4 This includes a holistic perspective covering value for all stakeholders. 



15 
 

involves the discovery and adoption of fundamentally different modes of value proposition, 

value capture and/or value creation and the value network from an existing business – so 

business model innovation redefines what an existing product or service is, and how it is 

provided to the customer, by seeking to identify unique configurations of business model 

attributes (Velu and Jacob, 2016).  

Business models can be defined both objectively and subjectively (Doz and Kosonen, 

2010). The objective definition encapsulates the economic manifestation in terms of the 

structure of the firm’s relationships and procedures (Teece, 2010). The economic manifestation 

captures the financial viability of the business proposition in relation to value creation and 

value capture. In this sense, the objective perspective corresponds to the components and the 

relationship between components in order to have an economic outcome. The subjective 

definition encapsulates the cognitive manifestation that shapes managerial choices (Baden-

Fuller and Mangematin, 2013). The cognitive manifestation captures how senior management 

conceptualise the business model as a model-like device as the basis for their actions in order 

to create and capture value.  

 

 

 

 

 

 

 



16 
 

Figure 1.1: Components of the Business Model 

 

Source: Velu (2018) 

A firm’s business model is different to its business strategy, although the two constructs have 

some overlapping characteristics (Zott and Amit, 2008). In particular, a business model relates 

to the overall system that drives revenue and costs to deliver the customer value proposition, 

while business strategy refers to the generic choices that firms make to compete effectively in 

the marketplace (e.g. creating competitive advantage via differentiation, cost leadership and 

focus (McGahan and Porter, 1997)). The business model represents how the activities of the 

firm work together to execute its strategy5 (Casadesus-Masanell and Ricart, 2010); hence, 

choosing a particular business model means choosing a particular way to compete.  

Strategy relates to the contingency plan regarding which business model to adopt. 

Hence, strategy can be seen as an action plan that responds to a high-stakes challenge and 

requires diagnosis, guiding policies and coherent action (Rumelt, 2011). On the other hand, the 

 
5 Strategy formulation and implementation are an integral part of business model design and evolution (Foss et 
al., 2015). Strategy is determined by answering three questions: What is the offer, who constitutes the target 
market and how is the offer delivered to the customer? Business model selection constitutes the realised 
strategy that principally resides within the “how” question. 

Value 
Creation

Value Capture

Value 
Proposition

Business 
Model

Value Network



17 
 

business model is the underlying business logic of the go-to-market strategy. Tactics relate to 

how to optimise the performance of the business model once a strategy is chosen – the operating 

model. Figure 2 illustrates the relationship between strategy, business models and tactics. The 

constructs of business models and strategy are related because the understanding of how a 

business model works is important when formulating an effective business strategy. For 

example, a firm could execute a cost leadership strategy by more effectively training its staff 

to use state-of-the-art technology. Such a cost leadership strategy might be implemented based 

on the existing business model. On the other hand, a firm that intends to develop a 

differentiation strategy, such as going into low-cost air travel, might require a reinvention of 

the business model. For example, in the early 1990s the Ryan brothers changed their full-

service regular airline business into a low-cost, no-frills airline to save the firm from 

bankruptcy. Such a strategic change to create differentiation requires innovation to the business 

model. The business model innovation that created Ryanair was not only instrumental in saving 

the firm from bankruptcy but also contributed to the re-emergence of the firm as a profitable 

airline (Casadesus-Masanell and Ricart, 2010). 

 

 

 

 

 

 

 

 



18 
 

Figure 1.2: Strategy, Business Models and Tactics 

 

 
Source: Adapted from Casadesus-Masanell and Ricart (2010) 

1.2. Business Model Innovation and Performance 

The design of new business models has been shown to affect performance (Zott and Amit, 

2008). The design of the business model encompasses how the activities are configured, their 

relationship with one another and the actions taken by management to maintain the congruence 

of the link between the customer value proposition of the external market environment and 

how value is monetised. For example, some business model configurations in Formula 1 racing 

have a superior performance to others (Aversa, Furnari, and Haefliger, 2015), and certain 

service-based business models among manufacturing firms have been shown to improve 

performance (Visnjic, Wiengarten, and Neely, 2014).  

Such a positive relationship between business model innovation is evident not only in 

larger firms but also in small and medium-sized firms (Cucculelli and Bettinelli, 2015). 

However, research shows that there are contingency factors affecting the relationship between 

business model innovation and performance. Zott and Amit (2008) studied the relationship 

Firm

Business model A

Business model B 

Business model C

Business model D

Tactical set A

Tactical set B

Tactical set C

Tactical set D

Strategy stage
(contingency plan 
of which business 
model to adopt)

Operating Model
(tactical optimisation)

Business model
(underlying 
business logic of 
the go-to-market 
strategy)



19 
 

between strategic positioning and business model design in relation to performance by 

examining relatively new firms that conducted parts of their business over the Internet. They 

classified these businesses based on the degree of novelty (novelty-centred business model) – 

new ways of conducting economic exchanges – and degree of efficiency (efficiency-centred 

business model) – reducing transaction costs for all transaction participants. They showed that, 

as firms pursued a differentiation strategy, there was a positive relationship between the degree 

of novelty-centred and efficiency-centred business model design in relation to firm 

performance in terms of market value. However, high design novelty has a stronger positive 

relationship than efficiency-centred business model design. This is because firms that pursue a 

differentiation strategy need to make their customer value proposition different to that of their 

competitors, which might entail new ways of doing business through radically different 

business models rather than merely reducing the transaction for the customer. On the other 

hand, when firms try to design business models with both high design efficiency and novelty 

in their business model, the performance tends to decline as a result of experiencing 

diseconomies of scale. This is in line with the positioning school of strategy that argues that 

firms seeking to be cost leaders, and also to differentiate, can ultimately become stuck in the 

middle and hence fail to create superior competitive advantage.  

Building on this early work on business model design and performance, Velu (2015) 

addressed the question of how the degree of business model innovation affects the survival of 

new firms. The research analysed new firms that launched electronic trading platforms in the 

US bond market between 1995 and 2004 following the advent of Internet technology. The 

study showed that new firms with a high or low degree of business model innovation are more 

likely to survive for longer than new firms with a moderate degree of business model 

innovation. The study also showed that partnering with third-party firms with complementary 

assets reduces the survival of new firms as the degree of business model innovation increases. 



20 
 

This might be because such complementary assets derived from partnering might be most 

effective when the business model is not altered radically, as it creates significant complexity 

and coordination costs. Research has also shown that the relationship between business model 

innovation and performance might be related to the types of skill set held by the managers 

(Patzelt, Knyphausen-aufse, and Nikol, 2008). For example, in the biotechnology industry, 

founder-based firm-specific experience contributes more positively to performance in the case 

of platform firms focusing on the commercialisation of research services or enabling 

technologies compared to biotherapeutic firms that continuously need to come up with new 

drugs. This is because such platform-based firms are not radically altering the core proposition 

over time. However, founder-based firm-specific experience has a negative impact on 

performance in therapeutics firms that focus on biotherapeutic products (drugs) because new 

drug development requires new knowledge and skill sets. 

1.3. Challenges to Business Model Innovation  

Incumbent firms often find it extremely challenging to innovate their business models 

effectively despite ample evidence of the positive effects on performance of such innovations. 

Business model innovation can occur when there are changes in the components, or 

interdependencies between the components, in order to serve an existing, or new, market (Amit 

and Zott, 2012; Casadesus-Masanell and Zhu, 2013). Such business model innovation might 

require, among other things, reactivating – changing the set of activities; relinking – changing 

the linkage between activities; repartitioning – changing the boundaries of the focal firm; or 

relocating – changing the location in which activities are performed (Foss, Saebi, and Santos, 

2015). Such decisions need to be made in order to maintain congruence between the different 

components of the business model to ensure that the positive reinforcing factors are harvested, 

while managing the conflicts arising from the negative mitigating factors. There are two 

principal reasons for the difficulty that incumbent firms face in innovating their business 



21 
 

models. First, senior management tend to get locked into a cognitive frame with a dominant 

business model design that it is unable to reframe appropriately in a timely manner – the 

cognitive challenge. Second, incumbent firms tend to find it difficult to reconfigure their 

activities and processes from an architectural perspective to change the business model – the 

reconfiguration challenge. We review these challenges next. 

1.3.1. The Cognitive Challenge 

The importance of the cognitive framework and the influence of the dominant design of the 

business model have significant implications for the ability of incumbent firms to innovate 

their business models. For example, Xerox was one of the major firms in terms of the number 

of patents held in the 1960s and 1970s. In fact, Xerox PARC (Xerox’s Palo Alto Research 

Centre) was responsible for many science-based technological inventions, such as the mouse, 

word-processing software, the personal computer and the graphical user interface. However, 

Xerox did not commercialise these inventions (Chesbrough and Rosenbloom, 2002a); the  

firm’s success in the past was partly responsible for such a missed opportunity. In order to 

understand why this is the case, it is instructive to review the history of Xerox.  

Xerox was originally known as the Haloid Company, which developed the first dry 

photocopier technology. Xerox launched the 914 dry copier in 1959 when the prevalent 

technology was wet copiers.6 The 914 copier would have retailed at over $2,000, which was 

close to seven times the price of a regular wet photocopier, at $300. Since wet copiers were 

cumbersome to use, as one needed to wait for the ink to dry upon photocopying, clients only 

photocopied very important documents. In order to make the 914 copier attractive to clients, 

Xerox decided to encourage leasing of the machines at $95 per month, with the first 2,000 

copies free, although at the time most clients did not photocopy more than 2,000 copies per 

 
6 This was called the 914 copier because the photocopier used paper that was 9 by 14 inches. 



22 
 

month so they felt that the 914 copier was good value for money. However, once they started 

using the 914 copier, they soon began copying more than 2,000 copies per month and paying 

Xerox four cents per copy above the 2,000 copies. The success of the leasing model prompted 

Xerox to vertically integrate into the paper business in order to make additional profits from 

supplying the paper to clients for photocopying. The 914 copier soon became a bestseller and 

accounted for two-thirds of Xerox’s revenue.  

The success of the photocopying business for Xerox prompted its senior management 

team to develop a vision for transforming how the office would work in the future, with Xerox 

machines central to that vision. This vision was also driven by the fear of Xerox becoming 

redundant following the emergence of the paperless office enabled by digital technologies such 

as the digital computer. Hence, Xerox set up Xerox PARC and hired some of the most brilliant 

scientists to work on the latest technologies, which resulted in some of the major inventions 

listed above. However, the new propositions from Xerox PARC did not fare well in the annual 

budgeting process because they did not conform to Xerox’s business model. In particular, when 

the inventions (such as the Star workstation, the Ethernet, etc.) from Xerox PARC were 

presented to the senior management at Xerox, the latter asked a simple question: “How would 

these technologies help speed up photocopying?” This was because the volume and speed of 

copying were central to the success of the 914 copier, and hence to Xerox’s growth. Since the 

scientists did not have a clear answer to the question, the inventions were not funded for further 

development and therefore not commercialised by Xerox. In fact, several of the key 

technologies and patents were sold to the founders, Steve Jobs and Bill Gates, to form Apple 

and Microsoft, respectively.  

Another example of the cognitive framing and dominant design affecting the decisions 

of firms is the failure of the Polaroid Corporation to commercialise digital cameras (Tripsas, 

2010). Polaroid introduced the first instant camera in 1948. The leading firm was Kodak, which 



23 
 

had transformed the camera industry by introducing the Brownie chemical-based film camera 

in 1901, and the technology was still dominant in the market. However, Kodak cameras were 

still cumbersome to use, as the films needed to be processed separately in a lab. In 1965 

Polaroid introduced the “Swinger” instant camera model. In order to encourage sales, it 

dropped the price of the camera to stimulate demand for the film and hence increased the price 

of the films. This was the “razor and blade” business model, with the razor (the camera, in the 

case of Polaroid) sold at a loss in order to stimulate demand for the blades (the films, in the 

case of Polaroid), which are sold at a premium. In 1972 Polaroid invented the SX-70, with the 

lab for development essentially embedded in the camera: the SX-70 provided one-step 

developing following the photo being taken, with no waste. The success of the Polaroid 

Corporation was a source of great envy for other firms. Between 1948 and 1978 Polaroid 

showed annual growth rates of 23 per cent in sales, 17 per cent in profit and 17 per cent in share 

price.  

The success of Polaroid enabled it to invest heavily in research and development. The 

spirit of the high-risk radical invention in the firm was captured in a quote from the 1980 annual 

report to shareholders: “Do not undertake the program unless the goal is manifestly important 

and its achievement nearly impossible.” Such a focused effort in R&D at Polaroid enabled the 

firm to file some of the early patents in digital camera technology. However, it was slow to 

realise the potential of commercialising digital photography because of the dominant design of 

the razor and blade business model of Polaroid, which influenced the cognitive framing of the 

senior management team in the evaluation of new technologies. This is evident in a quote from 

the CEO of Polaroid at that time: “...in the photographic business all the money is in the 

software, none of it’s in the hardware… so the fundamental objective in these things was to 

find ways to advance products but that would be useful for improving the software sales.” Since 

digital photography essentially eliminates the distinction between the camera (razor) and the 



24 
 

film (blade), the senior management team rejected commercialising digital photography 

despite having in-depth knowledge of the technology from its own patents. Xerox and Polaroid 

were leaders of not only the existing technology but also the new technologies in their 

respective fields. However, they struggled to leverage these new technologies in order to 

commercialise them. The challenge for Xerox and Polaroid was not technological know-how 

but overcoming the cognitive framing of their respective business models that made them world 

leaders. In order to enable business model innovation there needs to be a means of 

systematically changing the cognitive framing of the business model by managers. How this 

can be done will be the subject of later chapters. Next, we look at how firms are able to 

overcome the reconfiguration challenge. 

1.3.2. The Reconfiguration Challenge 

In this section we discuss why managers, even when they are able to overcome the dominant 

logic of their previous business model as a result of cognitive framing, might still respond in a 

sub-optimal way. We call this the reconfiguration challenge. There are three broad reasons why 

firms might respond sub-optimally when trying to innovate their business model, namely, 

tactical responses, organisational design issues and leadership challenges. Let us examine these 

in turn.  

The first reason is the result of firms using tactical responses that might destroy the 

economics of the business model. This is because firms change the value proposition of an 

existing business model via a tactical response through their operating model without altering 

the underlying business model. An example of this can be seen in the rental car industry (Hart, 

Roberts, and Stevens, 2005). Zipcar is a car rental business that was launched in Boston, the 

United States, in June 2000. Zipcar’s business model was different to the major incumbent car 

rental firms in the United States at that time, such as Hertz, Avis and Enterprise. Specifically, 



25 
 

Zipcar enabled car rental by the hour, whereas the major incumbents only allowed rental by 

the day. Zipcar stationed its cars around cities and near residential neighbourhoods in pre-paid 

public parking spots where customers could pick up their cars and return them. The pick-up 

and drop-off processes were made very simple for the customer. Specifically, the car keys were 

left in the cars and members of Zipcar could unlock a car that they had booked by waving their 

Zipcar membership card – a unique proximity card called Zipcard – on the front windscreen 

during pick-up or drop-off.7 The cars were booked via the Zipcar website when one became a 

member and paid the annual subscription of $75; the cars were charged by the hour directly to 

customers’ credit or debit cards. The Zipcar model was cheaper than renting from the 

incumbent car rental firms, as the former included gas and insurance. Moreover, the incumbent 

car rental firms allowed rental by the full day but not by the hour. 

The initial reaction of the incumbent car rental firms such as Hertz was to downplay the 

potential impact of Zipcar on their business. Indeed, Hertz did not initially respond to the 

launch of Zipcar but began to see a slowdown in its revenue growth from 12.5 per cent in 2004 

to 7.9 per cent in 2007. Moreover, when Hertz observed the successful expansion of Zipcar 

across various cities in the United States, it decided to respond with a business model that 

leveraged its fleet of cars and brand reputation. Hertz allowed rental by the hour in the 

Manhattan area of New York City in 2007: customers would pick up and drop off the cars in 

one of the Hertz depots. It soon became apparent to Hertz that this was destroying the 

economics of its business model, for two reasons. First, the systems and processes of Hertz 

were not designed to manage the new customer value proposition of renting cars by the hour. 

Hence, management of the inventory of cars required a separate process, which increased the 

costs involved. Second, the randomness of customer renting by the hour added complexity to 

 
7 Zipcar extended this to a mobile phone application, whereby customers can unlock their cars using their mobile 
phone. 



26 
 

managing the car fleet for regular customers who rented by the day. Therefore, the service 

levels decreased as a result of the firm not being able to match the customer booking 

preferences exactly. Hertz therefore decided to abandon its business model experiment of 

adding a new customer value proposition of car rental by the hour and focus on the existing 

business model that was designed to deliver car rental by the day. Eventually, in 2008, Hertz 

launched Connect as a separate business that enabled rental by the hour with a separate car 

fleet to the conventional Hertz business model.   

The second reason for a sub-optimal response is the organisational design and its 

implications for how the business model is launched. This might be because the firm launches 

a new business model to deliver the new value proposition and tactically integrates it with the 

existing business model. Such an approach could create conflict among the components of the 

business model. An example of this is the development of a new business model that retrofits 

the existing business model, as seen in the response of Blockbuster to the emergence of Netflix 

(Shih, Kaufmann, and Spinola, 2007). Figure 3 shows the stark contrast of the share price 

performance of Netflix and Blockbuster, respectively, between 2002 and 2010.8 Netflix was 

created in 1997 and quickly evolved a business model of renting DVDs based on membership 

subscription. Netflix, an online business, also pioneered the delivery of DVDs by post rather 

than through retail stores. Blockbuster, which had more than 5,000 video rental stores across 

the United States, initially did not respond to the threat posed by Netflix. However, when it did 

respond in 2004, Blockbuster launched an online proposition, Blockbuster.com, to replicate the 

business model of Netflix, which was run in tandem with the Blockbuster store model. 

Blockbuster felt that its customer value proposition was better than that of Netflix because the 

customer could rent movies either online or through the store network seamlessly. This is 

encapsulated by a quote from the CEO of Blockbuster in 2008, Jim Keyes: “I’ve been frankly 

 
8 Netflix was listed in 2002. 



27 
 

confused by this fascination that everybody has with Netflix … Netflix doesn’t really have or 

do anything that we can’t or don’t already do ourselves.”  

 

 

 

 

 

Figure 1.3: Share Price of Netflix and Blockbuster 

 

Source: Yahoo Finance 

Two aspects of the response are worth noting, the first being the elimination of late return fees 

by Blockbuster. Blockbuster had a policy of charging fees for late returns; the late fees 

generated approximately $600 million, which was roughly 10 per cent of the company’s 

revenue. In addition to the revenue, late fees enabled Blockbuster to manage its inventory, as 

customers had an incentive to return the rentals in a timely manner. Since Netflix and 

Blockbuster.com were subscription models with no late fees, Blockbuster decided to drop its 

late fees for stores in 2005. Second, in order to provide an even better value proposition for its 

0

10

20

30

40

50

60

70

80

90

Netflix

Netflix

Share price (US$)

Month/Year

0

2

4

6

8

10

12

14

16

18

20

Blockbuster

Blockbuster

Share price (US$)

Month/Year



28 
 

customers compared to Netflix, it allowed customers to return DVDs received by post via 

Blockbuster.com to Blockbuster stores. This added complexity to its inventory management 

system and increased costs further. Both the loss in revenue from dropping late fees and the 

added costs of complexity from inventory management resulted in a poor performance at 

Blockbuster. The cost/income ratio of Blockbuster in 2003 prior to the year it launched 

Blockbuster.com was 0.72, and this had grown to 1.11 by 2009. In contrast, Netflix’s 

cost/income ratio in 2003 was 0.80, and this came down to 0.74 by 2009. Figure 4 shows the 

profitability performance of Blockbuster and Netflix, respectively, between 2000 and 2009.9 

These factors, together with the high cost of its branch network, resulted in Blockbuster filing 

for Chapter 11 bankruptcy in September 2010. It is clear that the response of Blockbuster in 

launching a new business model, and trying to integrate new customer propositions into the 

existing business model, created a mismatch between the components of its business model.  

Figure 1.4: Profitability of Netflix and Blockbuster 

 

Source: Financial statements of Netflix and Blockbuster 

The third reason for a sub-optimal response is a lack of leadership in transforming the business 

model. An example of this is the case of Nokia (Doz and Keeley, 2017), the leading firm in the 

 
9 The last annual report available for Blockbuster was for 2009. 

(USD m) (USD m)(USD m) (USD m)



29 
 

mobile phone industry in the early 2000s. However, the firm could not transform its business 

model fast enough to be a leader in the smartphone industry. In 2003 Nokia had two business 

divisions, Nokia Mobile Phones (NMP) and Nokia Networks (NET). NMP focused on selling 

handsets to distributors and operators, while NET focused on selling bundled handset deals to 

operators. Nokia decided, in September 2003, to adopt the matrix organisational structure to 

enable strategic differentiation between mobile phones, multimedia and enterprise solutions. 

Such a structure would also enable the sharing of common marketing, sales, logistics and 

technology platforms for these businesses. However, the benefits of the matrix organisational 

structure did not materialise because of the lack of a clear “strategic vision” by the senior 

management team. This resulted in middle managers negotiating resource allocation via 

committees, which slowed down decision-making, with a lack of overall responsibilities for a 

technology roadmapping strategy. Moreover, during this period, mobile phone evolution from 

voice and text to smartphones meant a shift from focusing on market segmentation to mass 

customisation driven by software applications rather than the hardware of the phone. However, 

Nokia was slow to make the shift from traditional mobile phones to smartphones because of 

the lack of leadership, coupled with short-term quarterly sales targets, and a cap of 10 per cent 

on R&D over sales meant that the focus was on improving the existing mobile phones.  

The above examples illustrate the importance of business model innovation in 

sustaining superior performance. The effectiveness of the business model in contributing to 

performance is based on the alignment and congruence between the value proposition, value 

creation, value capture and value network. As discussed earlier, there are several components 

to the value proposition, value creation, value capture and value network. Therefore, “fit” here 

refers to the internal consistency of the various components of the business model. Drazin’s 

and Van de Ven’s (1985) systems approach to fit is relevant here, whereby fit is defined as the 

degree of internal consistency of multiple contingencies, structural and performance 



30 
 

characteristics. The cases provide vivid illustrations of how the lack of congruence could arise 

from activity and organisational design elements and, if not managed appropriately, could have 

detrimental consequences. Therefore, developing a business model where there is fit among 

the components of the business model, and continuing to maintain such congruence as tactical 

elements are changed, are among the biggest challenges that firms face.10 This calls for 

measuring and managing such congruence of the business model components via a Business 

Model Coherence Scorecard (Velu, 2020).  

1.4. Discussion and Outline of the Book 

The cases show that the relationship between customer value propositions and business model 

design is crucial in order to create and sustain competitive advantage. In particular, 

understanding the relationship between strategy, business models and tactics is key. This is 

captured well by a quote from Ronald de Jong, former CEO of Philips CL, Germany, who said: 

“When the business model is innovative, operations and the product will follow automatically.” 

However, because of the functional nature of organisational design many firms tend to respond 

tactically to changes in the market environment by assuming that the business model is a given. 

Often, the product, price, promotion and distribution channels are leveraged individually and 

not collectively as the basis for a tactical response to changes in the strategic environment. 

Hence, this piecemeal response raises the question of who should be responsible for the 

business model. Often, in large organisations, as a result of the functional specialisation in 

order to drive efficiency, ownership of the business model is either dissipated or neglected 

altogether. Hence, firms often struggle when there are changes in the environment that call for 

 
10 Drazin and Van de Ven (1985) assume that there are various ideal types that might give a superior 

performance. In that sense, there is equifinality among the various combinations of options to configure the 
tactical choices.  

 



31 
 

innovation to the business model in order to serve a new market, or to serve an existing market 

with a different value proposition.  

Management needs to overcome the cognitive and reconfiguration challenges in order 

to innovate the business model effectively. The challenge arises as there are always market and 

technological uncertainties affecting firms. Firms need some simple rules or metaphors, as 

managers are rationally bounded and can therefore only process so much information. Hence, 

management faces the cognitive challenge of refreshing the dominant logic of the business 

from time to time as the market environment or the technology changes (Martins et al., 2015). 

Moreover, as management attempts to innovate the business model through reactivating, 

relinking, repartitioning or relocating, it is important to maintain dynamic consistency or fit 

between the components of the business model. This often calls for a deep understanding of 

the architecture of business models; therefore, management often faces the reconfiguration 

challenge, which is to execute the required change in the business model. This entails 

reconfiguring processes and competencies within the organisation, as well as its relationship 

with the external network of stakeholders.  

We propose a holistic, systems-based perspective to better understand and manage these 

challenges in order to enable business model innovation (Velu, 2017). Such a holistic 

perspective highlights the hierarchical nature of business models, whereby the combination of 

activities comprises subsystems, which, in turn, can be connected to other subsystems. 

However, the interconnections imply that a change in one component, for example, due to the 

adoption of a new technology, could result in knock-on changes throughout the system before 

it settles into a new stable pattern or business model (Goldstein, 1999). Such patterned 

interconnections often harbour core processes that are crucial to how the business model 

evolves (Siggelkow, 2011; Velu, 2017). Identifying these core processes as part of the strategic 

objectives, and designing suitable business models, are often challenging tasks for management 



32 
 

(Chaterjee, 2005). Such a holistic-systems-based approach to business model innovation will 

be required to leverage the benefits of new digital technologies and address some of the grand 

challenges of society. The innovation economy requires upstream activities in research and 

invention through to downstream experiments to leverage the new economic spaces opened up 

by innovation – and this requires new business models (Janeway, 2012; Schumpeter, 1942; 

Massa and Tucci, 2017). The remainder of the book will examine the opportunities that 

business model innovation creates and how management needs to go about overcoming the 

challenges in order to benefit from them. The chapters of the book are as follows. 

CHAPTER 2: BUSINESS MODELS AND CREATING MARKETS  

How do we think creatively about creating markets with new business models? This chapter 

will examine the role that business models play in the development of new markets. The chapter 

will also address how senior management could refresh the cognitive framing of the dominant 

design in order to identify and enable business model innovation. 

CHAPTER 3: ORGANISATIONAL STRUCTURE AND LEADERSHIP  

What are the key principles of designing organisational structures and leadership challenges 

for business model innovation? This chapter will examine the leadership challenges, as well as 

the organisational design issues, for business model innovation. In particular, it will discuss 

how senior management could lead the business model innovation process and the 

organisational design issues to consider driving change within the firm. The chapter will also 

consider the design principles for management information systems to enable business model 

innovation. The chapter will introduce the Business Model Coherence Scorecard (BMCS) as a 

means to manage the congruence of the components of the business model in order to achieve 

efficiency and effectiveness.  

 



33 
 

CHAPTER 4: DIGITAL TECHNOLOGIES AND TRANSFORMATION  

What are the key digital technologies affecting business model innovation? This chapter will 

examine the new digital technologies, such as additive manufacturing, blockchains, the Internet 

of Things (IoT) and artificial intelligence, and their potential to reshape industries. The chapter 

will also highlight an early-stage emerging technology, quantum technology, as it promises 

major business model innovation opportunities, as well as challenges, to provide benefits to 

society that would not be possible with existing digital technologies. It will examine the 

conceptual underpinnings to better understand the kinds of new business model that might 

emerge.  

CHAPTER 5: DIGITAL PLATFORMS AND ECOSYSTEMS 

Why are digital platforms becoming ubiquitous and what are the business model implications? 

This chapter will examine the benefits and challenges inherent in managing platform-based 

business models. It will introduce the concept of layered modular architecture (LMA) and how 

platform business models evolve over time. In addition, the chapter will discuss the strategic 

issues of managing platforms within a business to consumer (B2C), compared to a business to 

business (B2B), setting. 

CHAPTER 6: SMALL AND MEDIUM-SIZED ENTERPRISES AND START-UP 

BUSINESS MODELS  

What are the business model challenges for small/medium-sized enterprises (SMEs) and start-

up firms trying to commercialise new technologies? This chapter will explore the challenges 

of SMEs, which are part of major supply chains, to innovate their business model and improve 

performance. In addition, it will explore the process that entrepreneurs go through when 

developing new business models as part of commercialising new technologies such as spin-

outs from university labs. In particular, the chapter will examine the challenge that start-up 



34 
 

firms face when designing new business models to help create markets and subsequently to 

evolve the business model to a profitable proposition.  

 

CHAPTER 7: SUSTAINABILITY AND BUSINESS MODELS  

What are the benefits and challenges inherent in designing business models to address the 

major global sustainability challenges? This chapter will examine the challenges related to 

climate change and the sustainability agenda, as well as the benefits of maintaining 

biodiversity. In particular, it will look at the different challenges involved in value creation and 

value capture from a multiple stakeholder perspective. It will examine how to internalise 

externalities and design business models that encompass economic, social and environmental 

goals. 

CHAPTER 8: BUSINESS MODELS FOR SOCIO-ECONOMIC DEVELOPMENT  

What are the principles of designing business models to address socio-economic challenges? 

This chapter will examine business model design to address issues related to healthcare, 

poverty, education and general well-being. In particular, it will address novel business model 

design, where market solutions and government intervention alone might not be sufficient to 

address the issues. 

CHAPTER 9: CONDUCT RISK AND BUSINESS MODELS 

What are the principles of designing business models to ensure fair customer and market 

outcomes? This chapter will explore how the global financial crisis highlighted the need to 

design business models in financial institutions that are profitable, while ensuring fair customer 

outcomes and the integrity of markets. It will introduce the concept of conduct risk and its 

relevance for sectors more generally beyond financial services. The principles of designing 

business models to manage conduct risk, and the implications, will be discussed.  



35 
 

CHAPTER 10: CONCLUSION 

This chapter will review the role of new technologies in fostering business model innovation 

to enable industrial revolutions by glancing into business history. It will also revisit some of 

the general principles of the design of economic systems and the role of government in 

influencing the design of business models. This chapter will provide some concluding thoughts, 

from a theoretical and practical perspective, for fruitful and impactful research opportunities 

on business model innovation in the future. 

Chapter 1 has provided an overview of the importance of understanding business model 

innovation and its relationship with strategy formulation and tactical choice, including its 

impact on performance. It also provided an overview of the cognitive and reconfiguration 

challenges. These aspects provided the basis for an overview of the following chapter. 

  



36 
 

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Zott, C., Amit, R., and Massa, L. (2011). The Business Model: Recent Developments and 
Future Research. Journal of Management 37(4): 1019–1042.  
 
 
  



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CHAPTER 2: BUSINESS MODELS AND CREATING MARKETS 

  



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CHAPTER 2: BUSINESS MODELS AND CREATING MARKETS 

 

We cannot solve the problems we have created with the thinking that created them. 

(Albert Einstein) 

 

2. Introduction 

Reconstructing market boundaries is a major source of business model innovation (Geroski, 

1998). Such reconstruction of the market boundary might involve identifying new customer 

needs that an existing proposition does not meet or the development of a new proposition that 

meets existing needs in a fundamentally different way. Therefore, defining a firm's market is 

important, as it defines the identity of the firm, the skills and expertise needed and the 

appropriate organisational structure.  

The market for potato crisps provides an illustration of the importance of market 

boundaries for business model innovation (Geroski, 1998). In the 1960s potato crisps made by 

Smith’s – a firm with the largest market share for such snacks – used to be sold as individual 

packs to complement drinks in pubs in the United Kingdom. The target market was 

predominantly working men, who went to the pub for a relaxing drink after work. Golden 

Wonder, a relative newcomer, redefined the market for crisps as a children’s snack as part of 

their school lunchbox. Hence, they were positioned as family-size packs sold in supermarkets 

and targeted at mums, who often made the decision about their children’s school lunchbox 

items. Golden Wonder promoted the new family-size offering in a major national advertising 

campaign targeted at mothers and children. The advertising proved to be very successful in 

creating a new market for crisps for Golden Wonder. The expansion of this market contributed 

to Smith’s continued growth in annual sales. Smith’s then made an incorrect inference that its 

market was growing despite the activities of Golden Wonder. However, because of the much 

larger size of the market for family-size crisps as snacks for children and for consumption by 



42 
 

families at home, Golden Wonder overtook Smith’s and became the market leader in a very 

short period of time. Only after new management had been installed did Smith’s respond with 

successive innovations, which then grew the market substantially. This case shows that one 

way to enter a market that is well protected is by redefining the market. Hence, identifying 

market boundaries almost always tops the hierarchy of strategic decisions and other decisions 

follow. 

This chapter provides an overview of the theory of market creation, and the logics of 

competition, and discusses some of the appropriate frameworks in the context of business 

model innovation. We examine the implications for both firms and the value network. 

2.1 The Theory of Market Creation 

Studies have focused on the business model as a description of the company’s logic of value 

creation (Ghaziani and Ventresca, 2005). This conceptualisation essentially focuses on the 

economic and financial aspects of how value is created and captured. Such a definition is an 

essentialist view of a description or representation of reality that exists beyond the firm 

(Doganova and Eyquem-Renault, 2009). The essentialist view is problematic when considering 

new propositions that require new markets to be created, and, as such, the reality beyond the 

model has not materialised. Doganova and Eyquem-Renault (2009) introduce the notion of 

business models as “market devices”, which have both material and discursive elements that 

intervene to construct markets. In such a role, the business model can be seen as a “boundary 

object”, which connects and mediates the relationship between various stakeholders and 

coordinates their actions (Garud and Karnoe, 2003; Star and Griesemer, 1989). Business 

models have been argued to have agency to shape actions and, in turn, influence the actions of 

constituent stakeholders, both with and across the networks of firms, which shapes the business 

model (Mason and Spring, 2011). In essence, the business model as a market device acts to 



43 
 

provide a mix of storytelling and financial logic (Magretta, 2002). Baden-Fuller and 

Magematin (2013) argue that business models can be seen as a set of cognitive configurations 

that are “manipulable instruments”, which can be used either by managers of established firms 

or entrepreneurs to categorise the business world and better explore cause and effect. Therefore, 

it is important to understand the interplay between the cognitive and economic aspects of 

business models in order to help create the market. 

Markets refer to situations in which some good or service is exchanged for a price. 

Factors for development of the market include latent demand, the state of the economy, 

competitive pressure from related markets and relevant skills, among others. However, markets 

might not develop, even when such factors are favourable. There are two views about how 

markets might come about, namely, the discovery process and the creative process (see Alvarez 

and Barney, 2007; Buchanan and Vanberg, 1991). In the discovery process the market is always 

in a transitory state (disequilibrium) and there is asymmetric information among stakeholders. 

In such a context access to information is critical and therefore the market comes about from a 

search and selection process of all the possible opportunities that exist. In the creative process 

of market creation, opportunities do not pre-exist to be recognised or discovered. On the other 

hand, values and meaning emerge endogenously and the market is created as a residual process 

of interactions, resulting from a series of transformations of the extant reality (Sarasvathy and 

Dew, 2005). In this sense, creation opportunities are social constructions that do not exist 

independently of the perceptions of the entrepreneur or manager (Aldrich and Kenworthy, 

1999). The creation of opportunities is in line with effectuation theory, which takes a set of 

means as a given and focuses on selecting between possible effects that can be created with 

that set of means (Sarasvathy, 2001, 2008). This is in contrast to causation processes, where a 

particular effect is given and the focus is on selecting between the means to create that effect. 

http://philpapers.org/s/James%20M.%20Buchanan
http://philpapers.org/s/Viktor%20J.%20Vanberg


44 
 

The market develops “causally” (has the nature of cause and effect) in the discovery process, 

while it develops “effectually’ (capable of producing the effect) in the creative process.  

 There are several key implications of discovery and creation processes (Alvarez, 

Barney, and Anderson, 2013). First, in the case of the discovery process, objective 

opportunities exist because of exogenous shocks to existing markets, such as technological, 

regulatory or consumer preference changes. In the case of the creation process, opportunities 

are enacted and formed endogenously by entrepreneurs seeking to exploit them. Second, there 

are differences in the information and decision-making setting. In the case of the discovery 

process information exists objectively in physical and social artefacts in such things as 

technologies, routine operating procedures and processes. This enables data collection for risk-

based decision-making. By contrast, in the case of the creation process, information does not 

yet exist and hence the creation of opportunities forms new context-specific information. 

Therefore, decision-making is incremental and inductive. 

 Alvarez and Barney (2007) argue that it will always be possible after an opportunity is 

formed to describe the actions of a particular entrepreneur or manager in both “discovery” and 

“creation” terms. Recent studies show that the early stages of a venture appear to place greater 

emphasis on the creative process than the discovery process (Berends, Jelinek, Reymen, and 

Stulteins, 2014). The balance between these two processes reverses over time, with greater 

emphasis on the discovery process and less on the creative process, as the opportunity is 

articulated more precisely.  

 The emergence of casinos as a legitimate business proposition in the United States 

provides an example of the creation of markets as a social process (Humphreys, 2010). 

Although casinos had been in existence in the US for a long time, they were often perceived as 

crime-laden. In order to make casinos a viable business, the stakeholders – regulators, public 



45 
 

policy activists and financial investors involved in the industry – had to change the perception 

of casinos to become a legitimate leisure activity. The concerted efforts of these stakeholders 

through social, cultural and legal frameworks enabled the transformation of casinos from being 

perceived as related to crime to a financially viable entertainment business. Humphreys (2010) 

was able to demonstrate the evolution of casinos by analysing the content of the major 

newspapers in the United States – The New York Times, The Wall Street Journal and USA 

Today – to show how this positive framing took place, with an increasing number of articles 

discussing casinos as business enterprises for entertainment, and less emphasis on crime, over 

the period between 1980 and 2006. Hence, the number of casinos grew from fewer than 10 in 

the early 1980s to close to 150 by 2006.  

Religious views and spirituality could have a significant effect on institutions and 

markets (Iyer et al., 2014; Iyer, 2016; Yin and Mahrous, 2022). This is exemplified by the time 

it took for the life insurance industry in the United States to take off. America was largely an 

agricultural economy during the 18th century (Zelizer, 1978). The mortality rates among bread-

winners in the farming community were relatively high as a result of the poor health conditions 

in rural areas. The insurance industry saw this high mortality rate as an opportunity to provide 

life insurance cover for the families of farmers. However, the product did not take off, as 

widows and orphans were provided with assistance to overcome economic hardship by 

neighbours and relatives and mutual aid groups. Moreover, the farmland provided security in 

terms of a subsistence level of food and other income.  

From the early 19th century America started to industrialise, which provided 

opportunities for people to work in factories located in cities. The increasing urbanisation 

encouraged the population to migrate to the cities for jobs, which resulted in the fragmentation 

of the close-knit family ties that had existed before in the farmlands. As a result, the risk of 

economic hardship was high for families that had migrated to the cities in the event that the 



46 
 

bread-winner passed away. The insurance industry again saw this as an opportunity to provide 

life insurance cover for these families, who no longer had neighbours and relatives or the 

farmland to protect them from hardship. However, the life insurance industry still struggled to 

take off despite the evident need for it. In fact, the reason for the lack of demand for life 

insurance was the prevailing religious view that planning for one’s death through the purchase 

of life insurance could hasten one’s death, as it profanes the sanctity of death. The insurance 

industry had to overcome this religious and moral view by working with the pastoral 

community through the Sunday church service to change the view of the public by saying that 

a good death equates to wise and generous provision for dependents. This is exemplified by 

the quote below:  

The necessity that exists for every head of family to make proper provision for the sustenance 

of those dear to him after his death is freely acknowledged and there is no contingency whereby 

a man stands excused from making such a provision. (Life Insurance, Journal of the Manhattan 

Life Insurance Company, 1852) (Zelizer, 1978, p. 603) 

The examples from the casino and life insurance industries show that markets need to be 

created in order for firms to develop a viable business. It is widely accepted that both discovery 

and creation processes are critical for market creation. Scholars have emphasised the 

importance of examining the role of the business model in the creation of new markets (see 

Doganova and Eyquem-Renault, 2009; Santos and Eisenhardt, 2009). Next, we discuss the 

concept of business model innovation requiring creative thinking about markets through 

changing the meaning of the proposition (products/services), analogical reasoning and 

conceptual combinations (Martins et al., 2015; Verganti, 2009).  

 

 



47 
 

2.2 Changing the Meaning of the Proposition 

The meaning of a particular artefact could change depending on the problem it is trying to 

solve. Let us consider the development of the bicycle (Pinch and Bijker, 1987). Early forms of 

the bicycle had a large front wheel, such as the Penny Farthing. The attractiveness of the larger 

front wheel lay in the fact that for a fixed angular velocity one way of getting a higher 

translational velocity over the ground was to enlarge the radius of the wheels. However, this 

created a hazard for the rider, as the disparity in the size of the wheels and location of the rider’s 

position over the centre of the wheel meant that a hitting a stone on the road could easily throw 

the rider over the handle bar. Hence, bicycles with a smaller wheel base were developed with 

safety considerations in mind. These low-wheeled bicycles resulted in bumpy rides. In order to 

address this issue, firms such as Dunlop introduced pneumatic tyres, which had air pumped 

into the types to mitigate the vibrations from the road. Initially, this was ridiculed, as they were 

prone to slipping on muddy roads and did not have a particularly aesthetic look. Moreover, 

when air tyres were first introduced in a bicycle race, they were met with derision. However, 

the laughter was silenced when, to everyone’s astonishment, the air-tyre-based bicycle 

achieved high speeds and left its rivals in its wake. The proponents had reformulated the 

meaning of air tyres – from an artefact meant to solve the vibration problem – to achieve speed. 

Such a redefinition of the problem gave air tyres prominence and acceptability, resulting in the 

development of business models to make and sell them. 

Changing the meaning of the key customer value proposition could result in the 

emergence of new markets and hence business models. Let us consider the evolution of the 

watch market (Verganti, 2009). Watches were predominantly seen as a luxury item, and Swiss 

watchmakers had a global market share of over 40 per cent up until the mid-1970s. The Swiss 

watch manufacturers invented the Quartz movement but did not adopt it as a core technology 

for their watches, as they felt that it did not fit their core competencies of precision mechanics 



48 
 

and assembly. The Japanese company, Seiko, was the first to adopt the Quartz technology and 

develop a watch with LED (light-emitting diode) and LCD (liquid crystal display) technologies 

in the early 1970s. These cheaper watches were positioned not as luxury items but as time-

keeping pieces that customers were socialised to wear on their wrists every day. In response, 

Swiss watchmakers made their watches even more luxurious in order to avoid competition 

from the Japanese watchmakers. However, as a result of the emergence of the Japanese 

watchmakers with their low-end time-keeping pieces, the Swiss watch industry market share 

dropped to less than 3 per cent by the end of the 1970s, with the closure of more than 1,000 

watchmakers among the 1,600 in business at that time.  

In the early 1980s a consultant for Swiss bankers, Nicholas Hayek, came across the 

crisis unfolding in the Swiss watch industry and suggested that two of the major Swiss 

watchmakers, SSIH and ASUAG, combine to form Swatch. Swatch aimed to change the 

meaning of the watch industry again to make watches a fashion item. In order to do this, Swatch 

had to change the nature of watch manufacturing. They used the latest Quartz technology but 

with analogue displays, which allowed the firm to change the process whereby traditional 

Swiss watches were made in their entirety and assembled inside the casing. However, Swatch 

made all of the components separately and bonded them to the lower part of the casing, which 

allowed them to use more automated technology, to make the watches thinner and also, 

importantly, to change the casing depending on the fashion without altering the core watch. 

Swatch was then able to position the watches as fashion items, which was a major success, 

enabling the firm to grow exponentially in the 1980s. Hence, the evolution of the watch 

industry was enabled by changes in its meaning from its initial beginnings as a luxury item, to 

a time-keeping piece, and then to a fashion item supported, in turn, by the development of new 

business models. Figure 1 provides a summary of the watch industry and changing the meaning 

of markets. 



49 
 

Figure 2.1: Changing the Meaning of Markets 

 

Source: Verganti, R., Design-Driven Innovation (2009) 

The meanings of a proposition to support the development of markets are often based on 

schemas. Schemas are the knowledge structures that contain categories of information and their 

relationships (DiMaggio, 1997). One needs to understand how schemas emerge in order to 

understand how meanings change and hence new markets develop. Bingham and Kahl (2013) 

discuss the three stages of the emergence of a new schema: assimilation, deconstruction and 

unitisation. Their study shows that the insurance industry was one of the first to adopt 

computers after they were developed for business use following the Second World War. The 

insurance industry identified two opposing schemas, namely, “machine” and “brain” analogies, 

respectively, to describe the computer. The “machine” schema was adopted first, as it related 

more closely to the automation of routine processes in the insurance industry. This is the 

assimilation process. The machine schema did not significantly emphasise the novel features 

of the computer. However, as the technology improved and the insurance industry became 

more accustomed to the use of computers, the industry started to adopt the “brain” analogy, 

Adaption to the 
evolution of 

socio-cultural models

Generation of new meanings

Incremental 
improvement

Radical
improvement

Performance
(Technology)

Meaning
(Language)

High-end Swiss 
manufacturers

Quartz movements
LED and LCD

displays

Casio and other
Asian 

manufacturers

Swatch

Quartz movements
component-in-case

architecture

Watches as jewels
Watches as 
instruments

Watches as 
fashion accessories



50 
 

which was aided by the computer’s ability to be programmed and provide support to 

management in decision-making. This is the deconstruction process. Hence, computers were 

adopted for their novel features rather than merely for automation of existing processes. This 

process eventually resulted in the emergence of a new schema for business computers, which 

is termed the unitisation process.  

2.3 Analogical Reasoning 

An important aspect of business model innovation happens through changing its schema. The 

schema is defined as cognitive structures that represent knowledge about the business model 

attributes and the relations among attributes (Martins et al., 2015). One approach for enabling 

business model innovation is through analogical reasoning, which uses the knowledge content 

in one domain, the source, to interpret information in another domain, the target. Analogical 

reasoning involves leveraging similarities through the use of knowledge involved in one 

schema to interpret information in the new domain. This entails selecting an analogue and 

mapping the attributes of the analogue to the target business model and working out the unique 

properties of the target.  

 An example of the application of this type of analogical reasoning is the development 

of Tesla. There are four principal stages in the analogical reasoning approach. The first is 

selecting an analogue relational structure that could potentially be used to organise the target 

concept. For example, Tesla found Apple computers to be a helpful analogue in seeking to 

differentiate its electric car technology from internal combustion engine cars. It is important 

that managers look outside the immediate domain in which they are operating to find such 

analogues. The key is to find industry contexts that have been trying to solve a similar problem 

to the ones currently being addressed. For example, the Tesla model’s founder, Elon musk, 

refers to Model S as his Apple Macintosh, which acts as the target analogue for the design of 



51 
 

Tesla cars. The second stage involves mapping the relational structures and similarities. Often, 

managers focus on the attributes that are similar between the source and the target. Although 

this is helpful, the more important concept is to identify the relationship between attributes and 

the underlying structures in order to inform the activity system of the target business model 

scheme. For example, there is a need to compete on high-end design, with Tesla having some 

very Apple-like design characteristics, including attention to detail, in order to make the Tesla 

Model S as distinctive as possible. 

 Third, one needs to determine which elements of the analogue to incorporate. For 

example, Tesla was emulating the Apple model by placing all stores in high-end malls and 

shopping centres instead of relying on dealer franchises, which is the common mode of sales 

for conventional cars. This approach enables sales staff to help configure their cars using giant 

touchscreens for potential customers. Moreover, these salespeople do not receive commission, 

as would be the case with regular car dealerships. Such a distribution system, owned by Tesla, 

allows the firm to launch new models in luxurious surroundings with invitation-only events. 

The design of such a system requires managers to have a deep understanding of the overall 

architecture of the activity system of the source domain, and the types of problem it is trying 

to solve, in order to be able to have an impact on the new business model. In the fourth stage 

one needs to identify how to modify elements borrowed from the analogue. In the case of Tesla 

the delivery of cars to high-end malls occurred later than was conventionally the case for Apple 

Macintosh as a result of the high costs of holding inventory of cars in showrooms. Managers 

need to have a good understanding of not only the similarities but also the principal differences 

between the source and the target in order to be able to design appropriate business models. 

 

 



52 
 

2.4 Conceptual Combination 

An alternative way of creating new business models through changing the schema is the use of 

conceptual combinations (Martins et al., 2015). Unlike analogical reasoning, conceptual 

combinations leverage the differences between the source schema and the target. The use of 

conceptual combinations involves four steps. For example, we can illustrate the development 

of the Starbucks business model, a major global coffee chain, in using conceptual 

combinations. First, managers need to select a modifier concept. In the case of Starbucks the 

firm selected bars as the modifier concept; in doing this, conceptual combinations allowed 

multiple modifiers to be used. For example, Starbucks used not only the bar as a modifier 

concept but also the concept of a gallery in terms of store design. Choosing a modifier concept 

could be purposeful or accidental. For example, Best Buy came up with the idea of the fire sale 

as a result of one of its stores being damaged by a tornado; the subsequent creation of temporary 

tents in order to dispose of the inventory helped the firm to come up with the idea of creating 

a carnival-like atmosphere in its regular stores.  

Second, managers need to compare the modifier concept of the target business model 

schema to identify differences. For example, in the case of Starbucks, there is usually a 

difference in the role of the bartender, in the case of the bar, and the barista, in the case of the 

coffee shop. The bartender tends to know his or her regular customers well and has 

conversations with them, while the coffee retailer might have a more impersonal relationship 

with the customer. Moreover, in the bar the drinks are customisable, whereas in traditional 

coffee outlets there are standard coffee options. The idea is to identify the key differences 

between the modifier and the target in such a way as to be able to select prototypical concepts 

so that their meaning can be transferred from the modifier to the new concept (Wisniewski, 

1997). This process would enable managers to understand the true differences between the 

target and the modifier. For example, the founder of Starbucks, Howard Schultz, started to 



53 
 

question the initial business model of Starbucks when he visited Italy and discovered how 

emotionally attached the Italians were to their coffee, which prompted Starbucks to embrace 

the more personal-connection-based model. 

The third step involves the ability to integrate selected values, fillers of the modifier 

concept, to the slots that need to be filled in the target concept. For example, in the case of 

Starbucks, baristas provide a customisable menu of drinks and develop a more personalised 

relationship with their regular customers. Moreover, values from the schemas of an office are 

used to attract business people for prolonged use, while the gallery-like atmosphere enables 

Starbucks to increase the aesthetic value of the coffee-drinking experience. Fourth, there is the 

ability to adapt new fillers in the new business model schema to make it fit the characteristics 

of the target business model and its context. For example, in the case of Starbucks there are no 

barstools and customers do not chat with the baristas while consuming their coffee. It is 

possible that the combination of new fillers borrowed from the modifier concept might create 

the opportunity for new combinations of value and hence possible new business models. This 

is a major difference between conceptual combination and analogical reasoning. In the case of 

analogical reasoning the concepts are borrowed at systems level, while in conceptual 

combinations the concepts are identified at each element. Therefore, in the case of conceptual 

combinations, there is the potential to combine unrelated elements and hence create new 

dimensions of value for the possible emergence of new business models.  

The different ways that schemas or logics are combined to enable innovation and create 

new markets are also called recombinant strategies. Different approaches are used by firms to 

implement these recombinant strategies (Dalpiaz, Rindova, and Ravasi, 2016). For example, 

Alessi, an Italian manufacturer of consumer utensils for the kitchen, combined the logics of art 

with industrial manufacturing to create a new market for artistic kitchenware. Alessi’s early 

attempts to combine the two schemas were based on getting artists such as sculptors to suggest 



54 
 

designs for the kitchenware. This approach ran into technical difficulties, as the sculptors 

proposed designs that were not compatible with large-volume manufacturing processes. Alessi 

subsequently revised its approach by following an enrichment approach to its recombinant 

strategy. Alessi proposed that the functional value of the product needed to be retained while 

being enhanced by using arts and culture. This approach would maintain the industrial 

manufacturing logic while being enhanced by the art and cultural logic. Alessi worked with 

external designers with an artistic background who appreciated industrial design challenges. 

This process created several new designs that were appealing to hotels and bars, which made 

it a major success.  

Alessi leveraged lessons from this stage to make new products that were simultaneously 

tools with functionality while also being art. For example, it introduced tea and coffee sets 

designed by artisan workshops by making them in silver first, which overcame the constraints 

imposed by steel-based manufacturing. These became a major success and were purchased by 

museums around the world. Once the products received positive acclaim as a result of being 

purchased by museums, less radical versions were designed to conform to the large-scale 

manufacturing processes. Hence, Alessi was able to adopt innovation in organisational 

practices, resulting in fundamental changes to its design and manufacturing processes, which 

provided the basis for creating the new art-based kitchenware market. 

3. The Logics of Competition and Strategy 

The logics of competition are an important aspect of understanding the development of markets 

(Barnett, 2017). The logics of competition determine the principles of who can compete, how 

they compete, on what criteria they compete for success or failure and what outcomes they 

compete on in order to determine the consequences of success or failure. Such principles are 

determined by the notion of meta-competition. The conventional notion of competition 



55 
 

involves firms trying to learn to be better than their competitors. Once a firm is able to pull 

away from its competitors, the competing firms often try to outdo the lead firm, and when this 

succeeds the process begins again. Such competition is seen as the “Red Queen” effect 

(Barnett, 2008), an analogy from Lewis Carroll’s Through the Looking Glass, where Alice 

needs to run as fast as possible only to stay still. The concept of trying to continuously be better 

than the competition has limitations, for several reasons. First, there are limits to learning and 

managers also tend to forget, which implies that firms often react to the latest competitive 

effects. Second, firms tend not to respond to just one competitor but rather co-evolve their 

strategies with the requirements to replicate different rivals. This approach to competition 

makes it challenging to manage resources and is potentially risky. Third, firms have limited 

cognitive capacity and tend to display myopic learning from within a small context.  

Studies have also shown that firms often do not learn from failures because there is a 

“success bias” in learning. In order to overcome the “Red Queen” effect, firms need to engage 

in wider meta-competition by setting the logics of competition themselves. This might involve 

indirect or direct meta-competition. Indirect meta-competition arises when there are multiple 

possible logics for an industry and the competition revolves around establishing one of them 

as the dominant paradigm. The leaders within an organisation try to establish the framing by 

influencing the social acceptance by working with the relevant stakeholders, such as customers, 

employees and governments, among others. For example, Uber is trying to position itself as a 

technology firm, and not a taxi firm, in order to treat its drivers not as employees but as casual 

workers.11 Direct meta-competition arises when the broad contours of the industry have been 

set. The competition is based on different firms competing based on different logics. The issue 

is whether a firm is playing the right game, as opposed to playing the game well. For example, 

 
11 The UK Supreme Court ruled in 2021 that Uber needs to treat its drives as employees rather than self-
employed workers (The Guardian, 2021). 



56 
 

in the IT industry firms that offer “off-premises” IT services compete on the basis of scale and 

utilisation, which is alien to traditional enterprise IT firms providing “on-premises” services.  

Barnett (2017) provides an illustration of such meta-competition in the music 

distribution business. Three distinct business models co-existed in the digital music distribution 

industry in 2003, namely, the free music downloading service, the commercial music 

downloading service and the commercial subscription streaming service. Although large firms 

and musicians consider free downloading to be illegal, there was an alternative discourse that 

claimed that major music labels were seeking exorbitant returns. Moreover, firms such as 

Apple were initially committed to commercial music downloading services and were opposed 

to streaming services. For example, Steve Jobs, the CEO of Apple, at the time claimed that 

people should own their music album, as they had done with LPs and CDs, and therefore they 

should not subscribe to downloading services. However, the increasing popularity of streaming 

services due to companies such as Pandora and Spotify convinced Apple to reframe its digital 

music proposition based on the streaming service.  

Barnett (2008) emphasised that technology, regulation and the sociopolitical 

environment could influence the logics of competition. New technologies offer firms the ability 

to propose new logics of competition. For example, with the advent of the Internet, WR 

Hambrecht + Co, a new firm formed in 1998 and staffed by outsiders to the industry, came up 

with an idea whereby initial public offerings (IPOs) would be done via Dutch auctioning 

technology rather than by building a book through contacts, which was the traditional form 

practised by investment banks at the time. The auctioning approach was positioned to firms 

that tended towards IPOs as providing a more accurate valuation of the firm compared to 

investors getting the benefit through a large increase in share price immediacy after the listing, 

partly driven by under-pricing the IPOs. Moreover, Hambrecht promoted accessible research 

through the Internet rather than roadshows, which was the traditional method at the time to 



57 
 

promote the IPO. This new logic of competition attracted significant attention when firms such 

as Google used Hambrecht for its IPO. Moreover, regulation and the sociopolitical climate 

could affect the logics of competition, as was the case in early 20th-century America.  

During the early years of the US telephone industry, the Bell System was growing and 

acquiring other smaller independent telephone companies. The independent telephone 

companies responded by cooperating with one another to fend off the threat posed by the Bell 

System. Legal changes and the political system at the time mandated protection to the 

independent companies. Counter-intuitively, such a change in regulatory setting removed the 

threat of the common enemy, resulting in the independents competing with one another. In 

essence, the legal changes due to the sociopolitical pressures at the time changed the landscape 

of the industry from a collective to an individualistic logic. Sometimes, firms also use the logic 

of predation, whereby mergers and acquisitions are used as the basis for eliminating rivals and 

hence maintaining the logics of competition. For example, during the early 2000s more than a 

hundred electronic trading platforms were launched in the US bond trading market (Velu, 2016; 

Velu and Jacob, 2016). Many of these were start-up firms trying to disintermediate the market-

making role of the investment banks that were dominant in the secondary trading of bonds. 

Some of the investment banks acquired these start-up electronic trading firms in order to help 

maintain the status quo of their lucrative bond trading business. 

Brandenburger (2018, 2019) proposed a major question that was at the heart of 

competitive strategy and key to understanding market creation: “Where do strategies come 

from?” The study proposed an analytical framework for the creative process of strategy 

formulation that has four elements, namely, contrast, combination, constraint and context. 

Contrast comes from being able to make an assumption that underlies conventional thinking in 

an industry and challenging it. PayPal, a global online money-transfer firm, had initially taken 

a widely held but untested assumption in banking – namely, that transferring money between 



58 
 

institutions, but not individuals, was fine – and then disproved it. The combination comes from 

connecting products and services that have traditionally been separate. For example, Apple and 

Nike joined forces by enabling Nike shoes to communicate with an iPod or Apple Watch to 

track steps. A constraint is turning a limitation or conventional liabilities into an advantage. 

For example, Audi converted the disadvantage that its cars could not go faster than its 

competitors in the Le Mans race into an advantage. It decided to build diesel-powered racers, 

which required fewer fuel stops than gasoline cars, and it subsequently won Le Mans three 

years in succession between 2004 and 2006. Context is the ability to bring ideas that at first 

seem disconnected to shed light on pressing problems. Intel borrowed from the notion that 

branded ingredients such as Teflon and Nutrasweet are important drivers of brands. Intel used 

this insight to develop the Intel Inside marketing strategy as a way to brand the invisible 

computer component, the microprocessor, to help grow the PC industry. 

4. Discussion and Frameworks 

Scholars have suggested that market boundaries, and hence the conception of strategic 

boundaries, are based on two dimensions. The first is based on schemas, which are people’s 

interpretational-based theories and concepts of the world. The second is based on resources, 

which are materially tangible and observable (Pontikes and Rindova, 2020). Structure comes 

about when there is an appropriate pairing between schemas and resources. Such schema–

resource pairings are dynamic but stabilised when there is a consistent pattern in the use of 

resources that is defined by the schema; in turn, the allocation of resources is validated by the 

schemas. However, it is instructive to note that structure is not objectively determined, as 

structures can often intersect with one another at different social levels. Schema are often 

transposable from one area of application to another, and resources can take on different 

meanings depending on the context. Market structure can be seen as a schema–resource pairing 

that is driven by routines, technologies and business models, among others. Hence, on the one 



59 
 

hand, markets display stability, and on the other hand, there is scope for agentic 

transformations.  

Successful business model innovation requires the creation of new markets by changing 

the cultural, social and legal framework (Fligstein, 1996; Humphreys, 2010). There are three 

reasons for this. First, the demand for the proposition might not exist. Second, we need to 

understand how consumer needs themselves come about. Third, institutions such as property 

rights, governance structures and rules of exchange are required. In particular, social 

institutions are necessary for the existence of markets. Institutions refer to shared rules, which 

can be laws or collective understanding (custom, explicit and tacit agreement), which covers 

property rights, governance structures, conceptions of control among stakeholders and, finally, 

the rules of exchange. Property rights refer to the residual claimants of assets and profits. 

Governance structures refer to rules that define competition, cooperation and the structure of 

firms. Conceptions of control refer to the structure of perceptions of how the markets work, 

which allows the actors to interpret the actions of others and also to control situations. The 

rules of exchange define who can transact with whom and the conditions for transactions 

between parties to take place. These sets of principles that define institutions require agency 

from stakeholders in order to be created, maintained and changed.  

 Stakeholders in the marketplace need to exercise their agency in order to influence the 

development of markets. Scholars have proposed three forms of agency: constructive, temporal 

and interactive (Pontikes and Rindova, 2020). Constructive agency involves the ability of 

agents to apply new schemas to the endowed resources. Therefore, constructive agency enables 

stakeholders to apply new schema–resource combinations in order to improve their position 

and transform the market structures. Moreover, such constructive agency also influences the 

resource accessibility of other stakeholders. Temporal agency involves the ability of agents to 

individualise their position by integrating their unique past and present experiences with their 



60 
 

view of the future in order to derive their vision. Such a vision acts as the cornerstone for agents 

to transform the structure, which is enacted through constructive agency. Temporal agency 

involves interaction with others in order to learn, as well as shape their experiences of the 

world, which contributes to reimagining possibilities. Hence, temporal agency contributes to 

either enhancing or changing the vision provided by temporal agency through harmonisation 

or conflict with other agents. Interactive agency involves persuasive activities to influence 

other market actors, which involves coordinating one’s actions to persuade or coerce 

heterogeneous market actors in order to align incentives and form a collective common 

purpose.   

Often, there are challenges inherent in overcoming existing institutional structures for 

new markets to develop. These are due to practices that have created legitimacy as accepted 

norms by the stakeholders. In order for new markets to emerge, this accepted legitimacy of 

practices needs to change. In particular, studies have shown that cognitive and sociopolitical 

legitimacy are key aspects to consider in developing new markets (Aldrich and Fiol, 1994). 

Cognitive legitimacy relates to the extent to which a new form is taken for granted, the 

knowledge about a new activity and, finally, what is needed to succeed in an industry. 

Sociopolitical legitimacy relates to the extent to which a new form conforms to recognised 

principles or accepted rules and standards, the value placed on an activity by cultural norms 

and political authorities, and the process by which key stakeholders (the public, opinion 

leaders, government officials) accept a venture as appropriate and right. Changes to the 

cognitive and sociopolitical legitimacy need to be made across organisational, inter-industry 

and intra-industry levels. Research shows that, at organisational level, the use of inclusive 

language with the relevant stakeholders is key to obtaining buy-in and trust. In addition, at 

intra-industry level, the building of new markets calls for convergence around a dominant 

design by positioning the new proposition close to the existing design and encouraging 



61 
 

collective action among stakeholders. For example, when the electric light was developed to 

replace oil lamps, the industry pioneer at the time positioned the lights to be similar to the 

design of oil lamps in order to conform to the brightness of the existing technology; they also 

worked with road developers to help bury the wiring below ground level (Hargadon and 

Douglas, 2001). At inter-industry level, the recognition that often the success of a new industry 

is dependent on another industry is a key factor. Hence, the ability to develop new activities by 

negotiating and compromising with other industries is a crucial step to enabling cooperation 

and building the market. For example, the development of a new healthcare provision would 

require the cooperation of the insurance industry.  

One of the main challenges in business model innovation is the prevalence and 

embeddedness of the dominant logic or mental models. The dominant logic is important 

because management often display bounded rationality, where there is limited ability to process 

all of the information. In addition, scholars have emphasised the importance of formulating 

strategy using simple rules or metaphors. The benefit of using simple rules is that it provides a 

clear and concise set of criteria for making decisions and communicating to employees. On the 

one hand, strategy formulation using simple rules is a powerful proposition when markets are 

relatively stable. However, when there is significant market and technological uncertainty, and 

hence there is a need to develop new markets, the use of simple rules or metaphors can be 

detrimental (Dunbar, Garud, and Raghuram, 1996). This is because the existing dominant logic 

in most firms is based on the principles of deductive logic, which has an underlying premise 

that the world we operate in has an objective reality, and therefore any variance from the 

expected outcomes can be explained through a set of deductive propositions.  

Much of the financial management system within organisations is based on periodic 

budgets and variance reporting that have a strong bias towards deductive reasoning. Such 

financial management practices underpinning strategy formulation are premised on explaining 



62 
 

the variance based on a particular expected outcome and the reasons for either not achieving 

or overachieving the outcome. The budget-variance approach to financial management is 

important for improving the efficiency of the existing business model. However, this approach 

based on deductive reasoning is less appropriate for the creation of new markets – in terms of 

effectiveness in delivering the right value proposition. Often, new markets are socially 

constructed, which requires the use of inductive reasoning, whereby schemas from other 

sectors are used to creatively construct the new market through analogical reasoning or 

conceptual combinations. Therefore, it is important that there is diversity in the senior 

management team in order to be able to use deductive reasoning to improve the efficiency of 

the existing business model, while enabling the emergence of new business models through 

inductive reasoning.  

Figure 2 summarises the framework for deframing these two aspects, whereby firms 

need to leverage the existing dominant logic while fostering the development of the new 

dominant logic. These two modes of thinking need to be managed and balanced in 

organisations in order to achieve the optimal balance between executing well on the current 

business model and facilitating renewal of the business model. This calls for abductive 

informed reasoning, whereby there is iteration between deductive and inductive reasoning in 

order to achieve the optimal outcome. For example, the CEO of Future Group, a major retailer 

in India, appointed a chief mythological officer (CMO), who often plays a major role in senior 

management strategy away days.12 Based on the proposed strategic and business model 

innovation discussion, the CMO is often tasked with designing the first-day discussion based 

on a mythological story that might be connected, but not directly related, to the new business 

model being proposed. The objective of the first-day discussion is to try to help senior 

managers to deframe their dominant logic of the existing business model and to begin to 

 
12 Based on an interview with the founder of Future Group, Kishore Biyani. 



63 
 

consider alternative propositions. On the second day the key strategic issues and the proposed 

new business models are discussed. This approach helps managers to give thoughtful 

consideration to any new business model proposition without dismissing it based on the metrics 

and success criteria of the existing business model of the firm. 

Figure 2.2: A Frame for Deframing 

 

Source: Adapted from Dunbar, Garud and Raghuram (1996); Prahalad and Bettis (1985, 1996) 

5. Conclusion 

Markets are social constructions that enable the exchange of goods and services. 

Reconstructing market boundaries to enable the development of new markets is a major source 

of business model innovation. Business models can be seen as market devices with 

characteristics of boundary objects that connect and mediate the relationship between various 

stakeholders and coordinate their actions. In doing this, business models help the functioning 

of markets but they also need markets in order to operate effectively. Therefore, firms need to 

pay adequate attention to how markets come about and strategies to influence the development 

of new markets as they consider business model innovation. The development of new markets 

Inductive Mode
(Questioning)

Deductive Mode
(Explaining)

Enacted WorldObjective World Socially Constructed
World

Existing 
Dominant 
Logic

New
Dominant 
Logic

Ex
am

in
in

g 
pr

em
is

es

Fo
cu

s 
on

 u
ni

qu
e 

ev
en

tsUnderstand reality construction Influence reality through creative process  



64 
 

is a creative process. Studies have highlighted the three approaches to thinking creatively about 

market creation. The first is by changing the meaning of the proposition of products or services. 

The second is through the use of analogical reasoning by leveraging similarities through the 

use of knowledge involved in one schema to interpret information in the new domain in order 

to help create new markets. The third approach involves the use of conceptual combination 

leveraging the differences between the source schema and the target to help develop new 

schemas.  

One of the major issues that the development of new markets creates is the notion of 

meta-competition, whereby the logic of competition determines the principles of who can 

complete, how they compete, on what criteria they compete for success or failure, and what 

outcomes they compete on in order to determine the consequences of success or failure. Firms 

need to ask not only how to play the game effectively but also the rules by which the new game 

of competition is created. Firms that are able to influence the development of such rules will 

become gatekeepers of the new markets and help to define the design of business models that 

are likely to be effective. One key element of such meta-competition and the creation of new 

markets and business models is to understand where strategies come from. Strategies could 

come from being able to make contrasting observations, combining initially unrelated 

elements, imposing constraints and making them advantageous and, finally, understanding the 

context of other innovative ventures and learning how to graft them. In developing new 

markets, firms need to overcome existing institutional structures that have created legitimacy 

as accepted norms by the stakeholders. Firms need to actively seek to change the cognitive and 

sociopolitical legitimacies.  

Often, there are challenges inherent in overcoming existing institutional structures for 

new markets to develop. These are due to practices that have created legitimacy as accepted 

norms by the stakeholders. In order for new markets to emerge, this accepted legitimacy of 



65 
 

practices needs to change. In particular, studies have shown that both cognitive and 

sociopolitical legitimacy are key aspects to consider in developing new markets. Finally, it is 

important for firms to understand the balance required between the deductive approaches to 

decision-making within firms, which is often needed to improve efficiency, and inductive logic 

to create new markets and improve the effectiveness of business models. Firms need to have 

senior management teams with the skills to do both of these things and to manage the 

contractions that this might entail in order to create and capture value effectively. 

There are several areas in market creation and business models that require further study 

covering the role of senior management, engagement of the ecosystem and the decision-making 

processes within firms. First, how do we develop a senior management team that has the ability 

to play the game of meta-competition and strategy formation to help create and shape markets? 

Senior management might be rooted in being in the business where the rules of the game have 

been predominantly defined. In such a market marginal improvement might be fairly limited, 

with competition often copying innovations that provide competitive advantage. Senior 

management needs to develop the skills and acumen to think about how to play the larger 

competition game. Defining the skills needed in the senior management team, and how they 

should interact with one another, is an important and relatively understudied area in top 

management team (TMT) composition.  

Second, there is the question of what kind of decision-making processes would be 

needed to enable schema changes and facilitate new market development. The decision-making 

system in firms needs to strike a balance between improving the operational efficiency of 

existing business models and thinking about new business models and creating new markets. 

Defining the principles of the governance model to enable the right balance between these two 

complementary, yet conflicting, processes also requires further investigation. Moreover, does 

such a governance model differ between the type of industries or the rate of technological 



66 
 

change being experienced? The third area requiring further study encompasses the question of 

how to engage with an ecosystem of firms to enable schema changes and business model 

innovation. Often, there are conflicting objectives among stakeholders about what the 

appropriate schema change needs to be. Therefore, the notion of the interactive agency of 

persuading other stakeholders on the new schema – and hence the market to create – is not well 

understood. In particular, strategies of persuasion and coercion work better than others. 

Moreover, there are some powerful players in the marketplace. Hence, are there different 

strategies for the different players depending on their power relations in the marketplace? These 

are some of the research issues that require more systematic study. 

This chapter has provided an overview of the principles of market creation for business 

model innovation and some of the outstanding research issues on this topic.  

 

 

 

  



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CHAPTER 3: ORGANISATIONAL STRUCTURE AND LEADERSHIP 

  



71 
 

CHAPTER 3: ORGANISATIONAL STRUCTURE AND LEADERSHIP 

 

Whether you believe you can, or whether you believe you can’t, you are absolutely right. 
(Henry Ford) 

 

3. Introduction 

Firms are often reluctant to cannibalise an existing business until the new business model is 

shown to be viable. The challenge for the top management team is to implement a new business 

model alongside an existing one and to manage the contradictions between the two (Velu and 

Stiles, 2013). For example, Kodak did not shrink the volume of chemical-based film, even 

when sales were declining as a result of digital cameras becoming prevalent. The continued 

production of colour films was driven by the incentives provided by the costing system that 

allocated the overhead costs of the capital equipment (Shih, 2016). Hence, Kodak could not 

reduce the volume of films to match the sales decline, as this would have increased the costs 

of producing the films and accelerated the decline in sales. The reluctance to reduce the volume 

of chemical films delayed the adoption of digital cameras and was ultimately fatal for Kodak.  

 Moreover, studies have shown that the type of leadership required to enable business 

model innovation might vary depending on the degree of systemic change that needs to be 

managed (Stock, 2016; Stacey, 1995; Van der Hoven, 2021). The more radical and architectural 

business model innovation would need top management to be actively involved (Stieglitz and 

Foss, 2015). We often see leadership changes when firms want to develop a new business 

model or reorient their existing one. For example, Tetra Pak, one of the largest and most 

successful packaging companies, appointed a new CEO to lead the new business, Tetra Recart, 

which produced retortable cartons as an alternative to cans for food packaging (Deschamps, 

2008). Moreover, Tetra Recart was set up as a separate organisation through a fully owned 

subsidiary company.  



72 
 

This chapter will provide an understanding of the leadership challenges that 

management face when implementing business model innovation and the types of 

organisational issue that need to be considered. In particular, it will focus on how management 

makes decisions to implement business model innovations. The chapter will also explore how 

the organisational structure and performance metrics used can influence the design and success 

of new business models.  

3.1 Theory of Leadership and Business Model Innovation  

Business model innovation is not straightforward because changes in one element of the 

business model often entail changes in another (Velu, 2017). Maintaining coherence of the 

business model as a system is important, and often such interdependencies between different 

elements of the business model might not be apparent (Velu, 2020). Hence, a sequence of 

substitutions or additions to the activities would change the business model from being one 

complex system to another, with possible unintended consequences (Schoemaker, Heaton, and 

Teece, 2016).  

Business model innovation requires organisational adaptability to manage such 

complexity and ambiguity. Studies have shown that leadership for organisational adaptability 

requires organisations to be flexible, agile and adaptive in response to a volatile and often 

unpredictable world (Miller and Lin, 2015; Uhl-Bien and Arena, 2018). Leadership in such a 

setting is a multi-faceted concept that uses a systems-level approach to foster collaboration 

through building social capital, as well as individual performance, by emphasising human and 

intellectual capital. Organisational adaptability involves managing the tension between the 

need to innovate and the need to produce. This requires the delicate balance of organisations 

as semi-structures that are not over-structured, and hence mechanistic, but which are not under-

structured and chaotic either. New ideas for a business model often conflict with the existing 



73 
 

business model. Leadership involves managing such tensions by enabling adaptive space by 

creating the conditions for conflicting and connecting to enable the emergence of new business 

models (Uhl-Bien and Arena, 2018). Conflicting involves engaging the tension between 

innovation and production. Such tensions can be created internally by injecting tension into the 

system or externally by the environment. However, such conflicts need to be balanced by 

connecting, linking the conflicting areas in such a way as to scale up the innovative ideas into 

some form of beneficial order to enable the new business model to emerge. Such leadership for 

organisational adaptability requires both ambidexterity and dynamic capabilities (Teece, 

2007).  

Firms need to exhibit ambidexterity by managing exploitation and exploration activities 

(March, 1991; Tushman and O’Reilly, 1996). This requires a high-performance behavioural 

context that enables employees to use their own judgement, while the leadership provided by 

the top management team acts as an integrative unit in making strategically important decisions 

(Hambrick, 1998; Neely, 2005).   

Research has shown that business model change requires dynamic capabilities, 

whereby leaders are able to sense, seize and transform opportunities (Schoemaker, Heaton, and 

Teece, 2016; Teece, 2007). Sensing is the ability to scan the environment and develop 

peripheral vision about what is around the corner; it requires the ability to anticipate and 

challenge the conventional wisdom. Seizing is the ability to innovate and implement new 

systems to take advantage of the external changes; it requires leaders who are able to synthesise 

information from different perspectives and balance speed with rigour to reach a decision. 

Finally, transforming is the ability to reshape the firm and the ecosystem to take full advantage 

of the new business models; it involves the ability to align conflicting viewpoints to reach a 

decision and also to view success and failure as critical sources of learning.  



74 
 

The above principles of leadership require three mega-capabilities to manage the 

strategic discontinuity brought about by changes to the business model: strategic agility, 

leadership unity and resource fluidity (Doz and Kosonen, 2010). Strategic agility is the ability 

to display anticipation and experimentation – to gain insights through experiments; distancing 

and abstracting – nurturing an “outside-in” perspective; and reframing – encouraging reframing 

of the business (Doz and Kosonen, 2010). The key is not merely to increase the lead time to 

enable transformation as a result of better forecasting. Forecasting tools work best when there 

are known uncertainties to manage the continuity of existing business models. When firms face 

discontinuous change, such forecasting methods need to be enhanced, for example, by 

technology roadmapping of radical new possibilities. For example, the investment of IBM and 

Google (and other firms) anticipates the development of quantum computing to complement 

classical computing because of its ability to do significantly more complex tasks efficiently 

despite the technology’s commercial value being future-based.  

Building leadership unity involves dialoguing: sharing assumptions among the senior 

team; integrating and aligning – a common agenda and interest; and caring – personal safety 

and compassion for trying/failing (Doz and Kosonen, 2010). Such leadership unity requires not 

only that incentives be aligned but, more importantly, the creation of a compelling mission to 

serve the customer. SAP reorganised itself from vertical business units by product application 

domains to a platform business with a more open application suite, by allocating 

responsibilities to board members for different phases or activities, with the mission of creating 

an integrated customer value proposition. This is part of providing a culture of personal safety, 

which is important to encourage trial and error learning. Resource fluidity involves: decoupling 

and modularising – it is easy to assemble/disassemble the activities; switching – trying different 

models in parallel; and grafting – importing business models from the outside (Doz and 

Kosonen, 2010). Business models evolve because the pressure to change in one element creates 



75 
 

tension for other elements, which then need to adapt and change as well. Thompson (1967) 

suggested that this requires firms to build a technical core but also to have a more adaptable 

periphery that is more modular. Such modularity creates semi-structures to move resources 

freely (Baldwin and Clark, 2000). 

3.2. Cases on Leadership and Decision-Making  

The adoption of a radical business model in the US bond trading market illustrates some of the 

senior management decision tensions (Velu and Stiles, 2013). The US bond market is the 

largest securities market in the world – at the end of 2000, over US$17 trillion in bonds were 

outstanding, with over US$2 trillion being issued in that year alone. The US corporate bond 

market is highly concentrated, with 12 dealer banks having a total market share of over 90 per 

cent between them. Bond trading was traditionally carried out by dealer banks via a telephone-

based business model. They act as intermediaries, matching buyers with sellers, and so they 

are able to price these securities, generating their revenue from the spread between the purchase 

and sale prices. The dealer banks often buy securities and hold them in inventory before selling 

them to other investors, during which time they assume the risk of price fluctuations, which 

requires economic risk capital. The advent of the Internet enabled new entrants to propose 

business models to allow direct trading between buyers and sellers and potentially to 

disintermediate the banks (Velu, 2016). In response, the smaller banks moved first to adopt an 

incremental business model innovation whereby trading still took place, with the banks acting 

as intermediaries, but over the Internet rather than the telephone. In response to the smaller 

banks, some of the larger dealer banks later formed a consortium to adopt the radical direct 

trading model via the Internet, as this contributed to lower costs by helping banks to avoid 

holding inventories of securities. 



76 
 

Strategic decision-making is typically classified into three phases: intelligence – 

involving the identification of opportunities, perhaps highlighted as a result of problems; design 

– which relates to the development of solutions; and choice – choosing between possible 

alternatives (Mintzberg et al., 1976). Senior management needs to be aware of both procedural 

rationality and politics in enabling the adoption of the radical business model while running 

the existing business model. On the one hand, procedural rationality is about the decision-

making process reflecting the intention to make the best decision possible for the organisation 

under the given conditions (Dean and Sharfman, 1993). On the other hand, politics is about the 

impact of individuals or groups who try to influence decision-making to enhance or protect 

their interests above those of the organisation (Pettigrew, 1973).  

In the case of the large banks launching the radical direct trading business model in the 

bond trading market, senior management needed to bridge the tension that arose at each stage 

of these decision-making processes by combining procedural rationality and politics (Velu and 

Stiles, 2013). In the intelligence phase, management consulted widely before deciding to adopt. 

From a rational perspective this made sense as, on average, one makes fewer mistakes, as 

different points of view are taken into account. From a politics perspective it provides buy-in 

via engagement by encouraging the expression of conflicting views and debate. Hence, the 

tension is manged via transcendence – by reframing a tension within a different perspective. In 

the design phase, management highlighted the business model innovation in terms of small 

changes. Rationally, this enables management to buy an option to execute business model 

innovation later, for example, to equities trading, only if the first is successful, while being 

politically astute in presenting the adoption of the new business model as incremental change, 

which makes it palatable. Hence, the tension is managed via separation – keeping apart the 

tension through a temporal process. In the choice phase, management leveraged different 

beliefs by putting forward additional strategic considerations, even if these were not the 



77 
 

preferred choice for the radical business model. Rationally, this enables managers to see the 

contrasts between the business models more clearly, and hence the benefits of the radical 

business model. Politically, it helps to reduce conflict and encourages “give and take”. Hence, 

the tension is managed via integration – neutralisation – whereby the opposing parties 

compromise to resolve the tension. 

Moreover, it is important to ensure in fast-changing environments such as high-

technology markets that the leadership team maintains a strategic focus within a defined 

framework. This strategic focus needs to be complemented with a technological focus whereby 

both radical and incremental technologies need to be aligned with the strategic objectives. 

Three firms – GE Medical Systems (GEMS), Motorola and Corning – who developed business 

models to become leaders in the 1990s in their respective high-technology markets, provide 

exemplary cases (Morone, 1993). GEMS was in the medical diagnostic imaging equipment 

business and one of its key products in the early 1970s was X-ray equipment, with a declining 

market share; it was the leading provider of X-ray equipment but its product was seen to be of 

lower quality than its competitors, Siemens and Philips. Initially, GEMS started to diversify 

into other areas of medical equipment before deciding to focus on X-ray machines in 1973. 

The GEMS senior management team decided to focus more specifically on computerised 

tomography (CT), which uses X-rays to provide detailed images of the cross-section of the 

anatomy. Although initially slow to adopt, GEMS developed a superior CT scanner using fan 

beam technology rather than a pencil beam, which allowed for faster computerised 

reconstruction of the body part being scanned and was extremely beneficial to medical 

practitioners and patients. This enabled GEMS to build its leadership in CT scans with the 

policy of “continuum”, whereby each new CT product enhancement would be compatible with 

the previous system so that customers could upgrade seamlessly. The firm’s success in CT 

scanners induced its competitors to move into a new technology, magnetic resonance imaging 



78 
 

(MRI), a non-invasive technology using a combination of magnetic fields and radio frequency 

technology that provides superior images of organs. GEMS reoriented its strategic positioning 

from an X-ray equipment business to a diagnostic imaging business. Initially, it was developing 

magnetic resonance technology, magnetic spectroscopy for biochemical analysis as a 

complement to its CT imaging and hence to protect its CT business. MR spectroscopy needed 

a more powerful superconducting magnet than MRI. However, this stronger superconducting 

was within the capability of the parent company, General Electric (GE), because its R&D 

department had developed the capability in its electrical power business. This superior ability 

to develop and produce a powerful superconducting magnet enabled higher-resolution brain 

images when using MRI, which enabled GEMS to develop superior MRI equipment to become 

the leader in the market. However, it positioned itself as a world-leading supplier of diagnostic 

imaging equipment in computerised tomography (CT) and magnetic resonance imaging (MR) 

systems. In this way, the leadership team’s ability to set targets of continuous improvement for 

quality and cost through learning by doing helped the firm to think about the next “big idea”.  

Having a strategic framework is important when creating focus but the leadership team 

should not be ruled by it. Motorola’s move to become a leader in the mobile and portable 

communications market by the 1990s, despite heavy competition from Japanese giants such as 

Matsushita and NEC, is an example of this. George Fisher of Motorola (CEO in 1988 and CEO 

and Chairman from 1990) said, in Morone (1993, p. 119):13 

So we have a strategic framework within which we make a lot of these decisions... We don't 

totally focus within the framework, but if it fits there, it gets a better chance of being funded 

than if it doesn't. So we have a strategic framework, but at the same time, there is a lot if 

Babylonian thinking, as opposed to Euclidean thinking, that goes into the process. 

 
13 Babylonian thinking is akin to inductive logic, as the Babylonians often learnt to develop theorems by solving 
many mathematical problems. Euclidean thinking is more akin to deductive logic, whereby mathematical 
theorems are derived logically from axioms (Feynman, 1964). 



79 
 

Often, the decision-making has to be bold and the financial analysis should act as the constraint 

on the pace of investment and not the determinant. Corning, a leader in an array of speciality 

glass and ceramic products, which transformed itself to become a leader in the optical fibre 

market, had such a philosophy. Tom MacAvoy, President of Corning (Morone, 1993, p. 185), 

said: 

The organisation has the desire to allocate resources in a rational and democratic process. 

Ultimately though, [to bring a big-hitting candidate to fruition], something irrational has to be 

done, and by irrational I mean ... requires resources that transcend the normal allocation 

process. 

Dave Duke, Chief Technology Officer (Morone, 1993, p. 191), explains that Corning used 

discounted cashflow analysis to get a feel for how much it would cost and what the market 

shares would be but experiments and intuition were needed to make the necessary assumptions 

for the analysis.  

3.3. Dual Business Model 

Strategic renewal often involves sub-processes such as competence definition, deployment and 

modification and affects different levels of management (Floyd and Lane, 2000).14 One of the 

major challenges of such strategic renewals faced by firms is how to adopt a new business 

model while running the existing business model effectively. These firms face a dilemma. On 

the one hand, the new business model might be able to provide great growth opportunities. On 

the other hand, the new business model might conflict with the existing business model and 

hence destroy value for both. For example, in 1998 British Airways launched a low-cost airline, 

Go. The idea was for British Airways to get a share of the growing low-cost airline market to 

cater for travellers flying to destinations in Europe. British Airways expected new passengers 

 
14 Within these sub-processes the roles of the different layers of management might vary across the time 
horizon, information requirements and core values, which results in conflicts that need to be managed (Floyd 
and Lane, 2000). 



80 
 

who had never flown before to travel with Go to European destinations. It replicated many of 

the processes of its regular passenger business for its Go subsidiary to ensure that capabilities 

were leveraged appropriately. For example, Go leased its aircrafts, which was easier but more 

expensive in the long run compared to Ryanair, another low-cost European carrier that bought 

its fleet at that time (Michaels, 2001). However, this replication of processes meant that British 

Airways never fully appreciated the differences between the business model of low-cost 

airlines (Boon, 2018). Hence, it decided to sell Go to a management buy-out backed by a 

private equity firm called i3, which in turn sold the airline in 2002 to EasyJet, a major 

competitor in low-cost airlines (Odell, 2001). This example shows that it is appropriate for 

firms to manage how best to leverage the existing capabilities when launching new business 

models. 

 Markides and Charitou (2004) proposed a framework to think about managing such 

dual business models. The principles of the framework consider two primary factors: the first 

is the similarities between the established business and the new business; and the second is the 

nature of the conflicts between the established business and the new business. The nature of 

the conflicts could arise as a result of location, brand, equity, value chain activities and 

organisational factors, among others. The proposed framework implies four broad strategies to 

manage dual business models, as shown in Figure 1 (below).  

 

 

 

 

 



81 
 

Figure 3.1: Dual Business Model Strategies 

 

Source: Adapted from Markides and Charitou (2004) 

At the two extremes are full separation or full integration strategies. Full separation, by 

launching the new business model within a separate organisation, is optimal when the new 

business model aims to serve a different market with low strategic relatedness to the existing 

market. For example, Nestle was a world leader in instant coffee through its Nescafe brand 

(Deschamps, 2008). However, when Nestle launched Nespresso, it launched it as a separate 

subsidiary with its own brand name. Nestle had initially tried to sell the premium coffee system, 

Nespresso, to the institutional coffee market and the hotels, restaurants and cafe market but 

was not successful. Hence, Nestle repositioned Nespresso by targeting wealthy young urban 

professions as an upmarket brand. Although Nestle sold Nescafe through supermarkets, it 

decided to market Nespresso through an exclusive Internet-based consumer club and its own 

speciality stores. Hence, as Nespresso was targeted at a new market segment and it was 

cannibalising the sales of the traditional business of Nestle in instant coffee, it decided to adopt 

a separation strategy of forming a separate unit to manufacture and sell Nespresso.  

Separation Strategy
(Nestle and Nespresso)

Phased Integration
(Charles Schwab and 

eSchwab)

Phased Separation
(Tesco and Tesco.com)

Integration Strategy
(Barclays and 

Barclays Online)

Low Strategic Relatedness
(Different markets)

High Strategic Relatedness
(Similar markets)

Nature of conflicts 
between

the established 
business 

and innovation

Serious

Minor

Similarities between established business and innovation 

Dual Business Model Strategies



82 
 

The integration strategy, on the other hand, involves launching the new business model 

within the existing organisational structure. Barclays, for example, when it launched Internet 

banking in the 1990s, decided that the proposition was targeted at its existing customers and 

that online banking would be complementary to branch-based banking. As there was very little 

conflict with the activities of its branch banking, it decided to launch Barclays online as an 

integrated business model within the existing business. This is in contrast to some of the 

building societies, such as Abbey National,15 which launched a separate unit for its online 

banking, namely, cahoot; it was aiming for a new cohort of more wealthy customers compared 

to its current customer base and felt there would be more conflicts with the existing branch-

based business model. 

At the other two extremes are phased separation or phased integration strategies. Tesco, 

a large supermarket chain in the UK, adopted a phased separation model when it launched its 

online business, Tesco.com (Enders and Jelassi, 2009). Initially, in order to leverage the 

benefits of its extensive store network, Tesco.com fulfilled its online customer orders by asking 

its stores that were nearest to the homes of its customers to fulfil the orders. This involved a 

store worker visiting the stores and filling the orders from the shelves of the supermarket, an 

approach that initially worked well. However, as the online business started to increase, the 

business of fulfilling online orders using the physical stores started to affect the experience of 

customers who came in to shop in these stores, as the number of workers moving around the 

store with a trolley increased dramatically. Tesco realised that it needed to develop separate 

fulfilment centres for its Tesco.com customers to avoid and reduce these conflicts with the in-

store customer experience. It even started to launch dark stores, which might resemble a regular 

 
15 Currently part of the Santander Group. 



83 
 

store but with no customers, and these stores were used exclusively for fulfilling online orders. 

Tesco has moved to using robotics to fulfil orders in these dark stores.  

The phased integration strategy involves launching the new business model as a 

separate business first and then integrating it within the existing organisational structure over 

time. For example, Charles Schwab, a major financial services firm in the US, launched 

eSchwab, its online retail broking business, as a separate entity (Markides and Charitou, 2004). 

eSchwab was meant to cater for new customers, and therefore the business model was launched 

as a separate entity with a different brand name to avoid conflict with the existing brokerage 

business. However, over time, the regular customers of Charles Schwab’s brokerage business 

became more sophisticated and were using the online brokerage services; Charles Schwab 

therefore decided to integrate eSchwab into its core business model. 

The original organisational design might have to change as the product category 

evolves; hence, the business model required to support it needs to be redesigned. IBM’s 

development of the PC is a case in point. IBM dominated enterprise computing and was the 

leader in mainframe computers (Bresnahan, Greenstein, and Henderson, 2012). Initially, IBM 

ignored developments in the PC market as being niche for individuals and not corporate clients. 

However, IBM observed that PCs started to be sold to IBM customers in the 1970s. IBM’s 

Boca Raton Group, which monitors small developments and proposes responses, prepared a 

presentation for IBM’s Corporate Management Committee (CMC) in the late 1970s. IBM had 

a policy that any employee could write a note to the CMC if they disagreed with any strategic 

decisions made by the senior team. However, the PC was deemed to be an important strategic 

investment for IBM so it adopted a “no complaints” policy to the CMC. 16 

 
16 IBM had a policy whereby any employee could write a note to the CMC to complain about any new policy 
decisions. This policy was frozen for the PC business. 



84 
 

The lab director of the Boca Raton facilities was given the opportunity to build the PC 

business as a separate unit with independent decision-making authority to the mainframe 

business. Initial studies had shown that PC adoption was slow as a result of the lack of software 

applications. Executives at IBM felt they could develop a PC quickly and the Boca Raton team 

was given the authority to come up with a PC in less than a year. As a result of the limited time 

frame, the group’s PC development team decided to use tested vendor technologies, a 

standardised one-model product and open systems architecture. Hence, IBM decided to build 

the first PC by sourcing parts from outside suppliers, which was unconventional in terms of its 

vertically integrated model for the mainframes. IBM chose Intel’s microprocessor and 

operating system from a little-known company at the time, Microsoft, to enable others to 

participate in the open-architecture-based PC business (Bradley, 2011). Moreover, the firm 

decided not to use IBM’s distribution network but to use third-party sales channels for getting 

the product to the consumer quickly. IBM’s first PC, the IBM 5150, was launched in August 

1981, a year after it was given the go ahead by the management committee. The company’s 

PCs were very successful until the advent of the PC-jr, a small PC for home users, which was 

a failure because of keyboard and other issues, which were sourced externally when building 

the PC. The incident with the PC-jr damaged the reputation of IBM in other business areas, 

including the core mainframe business, because of conflict and diseconomies of scope. First, 

there was distribution channel conflict because sales did not generate commissions for PCs, 

which were sold via retailers, unlike mainframes, which were sold directly by the IBM sales 

team. Moreover, there were increasing overlaps in customers as corporate customers started 

buying PCs. Therefore, IBM decided to bring back the PC business into the main business. 

3.4. Metrics and Incentives  

Business model innovation requires the appropriate alignment of incentives and metrics in the 

firm. Intel’s transformation from a memory business to a world-leading microprocessor 



85 
 

illustrates this. Intel was founded in the late 1960s and became a leader in the memory business 

– dynamic random access memory (DRAM) – by the mid-1970s, with over 80 per cent of the 

global market share (Burgelman, 1994). Intel’s initial investment in microprocessors came 

about because a Japanese calculator company, Busicom, wanted a chipset designed for its 

calculators. This is encapsulated in a quote from Intel’s VP for sales, Ed Gelbach (Burgelman, 

1994, p. 37): “Originally, I think we saw it (microprocessor) as a way to seek more memories 

and we were willing to make the investment on that basis.” These advanced chipsets for 

calculators later became known as microprocessors. However, Busicom initially owned the 

rights to the chip design. One of Intel’s technologists realised that these chipsets could be used 

as a general-purpose solution to other applications and persuaded the senior management of 

Intel to renegotiate the rights to the chip design. Busicom eventually sold the rights of the 

chipset back to Intel for all non-calculator applications.  

During the same period PCs were becoming important and beginning to be widely used. 

PCs required microprocessors; however, the enormous importance of personal computers was 

not evident to Intel’s senior management. Intel’s list of top 50 priorities for the 80286 

microprocessor did not include personal computers. However, its ability to provide 

development tools for its customers and demonstrate the upward compatibility path for its next-

generation products convinced IBM to choose Intel’s 8088 microprocessor as the central 

processing unit (CPU) for its PCs. However, there was still significant emotional attachment 

to the memory business, as it had made Intel successful. The memory business was 

commoditising rapidly, with many competitors by the 1970s having thinning margins. This is 

encapsulated in the quote from Andy Grove, who eventually became Intel’s CEO, replacing 

Gordon Moore, Intel’s founder and CEO at the time (Burgelman, 1994, p. 43): “I recall going 

to see Gordon (Moore) and asking him what a new management would do if we were replaced. 

The answer was clear: get out of DRAMs. So, I suggested to Gordon that we go through the 



86 
 

revolving door, come back in, and do it ourselves.” Intel therefore decided to transform itself 

from a memory firm into a microprocessor firm. 

The memory and semiconductor business shared fabrication plants. The senior 

management gave the local fabrication plant managers the responsibility to choose how many 

memory chips and microprocessors to manufacture. The monthly load to the factories was 

based on maximising “margin-per-wafer-start”, which did not maximise immediate profits but 

selected niche over commodity markets. Since microprocessors had a higher margin, the 

managers gradually provided more resources in factories to manufacture them, resulting in an 

exit from DRAM. The key performance metrics, and hence resource allocation method, 

provided alignment between internal and external conditions to match the competitive reality 

in order to help transform Intel from a leading memory firm into a global leader in 

microprocessors. 

In designing business models and appropriate metrics, scholars have suggested that the 

strategy of the firms be translated into some simple rules (Morris, Schindehutte, and Allen, 

2005). Such a process involves three steps. The first step is to define the foundational premise 

of the business in terms of what the business will be, and what it is not, and to ensure that such 

decisions are internally consistent. The foundational elements cover the core value creation and 

value capture mechanism, including the competitive positioning of the firm. Second is the 

proprietary level, which encompasses the development of unique combinations of activities 

and processes that result in marketplace advantage. Finally, the foundational and proprietary 

levels need to be translated into some simple rules that provide guidance and discipline to the 

business operations. Rules delineate guiding principles governing execution of the 

foundational and proprietary elements. For example, in the case of the low-cost airline, 

Southwest, the key foundational premise related to the offering was a standardised and narrow 

service offering. The proprietary level was based on designing the activity and processes for a 



87 
 

short-haul, high-frequency point-to-point service with direct sales to customers. The 

foundational and proprietary levels were translated into simple rules such as a maximum one-

way fare per passenger of less than a certain dollar value. Eisenhardt and Sull (2001) proposed 

the use of simple rules as key operational measures to help translate strategy into action. The 

authors suggested that firms should have between two and seven simple rules. These rules 

could include: how-to rules – spelling out the key features of how a process is executed; 

boundary rules – which opportunities to pursue and which are outside the scope; priority rules 

– helping to rank opportunities or options; timing rules – helping to synchronise the firm’s 

operations to speed and timing to get things done; and exit rules – helping to decide when to 

pull out of an opportunity.  

Several leading firms have also adopted the Hoshin Kanri (HK) policy deployment 

matrix as a means to translate strategy objectives into operational targets and to manage 

continuous improvements (Da Silveira et al., 2017; Jolayemi, 2008). HK has been defined as 

the process of developing plans, targets and controls and identifying areas for improvement 

based on previous levels of policy and an assessment of previous performance. Although 

originally developed in Japan, the HK policy deployment matrix has been used extensively by 

western corporations, including Texas Instruments, Lucent technologies, AT&T, Xerox and 

Hewlett Packard (Witcher and Butterworth, 2000). The HK approach has been given various 

names, such as management by policy, policy deployment and planning for results. The HK 

planning methodology essentially identifies medium-term breakthrough objectives and 

translates them into annual objectives. Once the annual objectives have been agreed, a set of 

top-level improvement priorities are identified and operationalised into targets for 

improvement with the appropriate allocation of responsibilities for them (Tortorella et al., 

2018). The annual planning table (APT) is used to document and deploy items and activities 

that constitute the annual plan. At each level of the organisation, the strategy and objectives 



88 
 

from the APT from the level above are used to develop an APT for that level based on its 

expertise and technical strengths. Hence, at each succeeding level, strategies are owned, 

expanded and converted into implementation plans in order to contribute to achieving the 

overall strategic objectives of the firm (Mulligan et al., 1996). One of the key aspects of the 

HK planning methodology is to achieve both horizontal and vertical alignment across the firm 

(Mannix et al., 1996). This alignment is achieved through a process called “crossball” to 

encourage dialogue between the different levels of the organisation during the deployment 

process. 

3.5. Tools and Frameworks 

Identifying a new business model and managing business model innovation is often a 

challenging and risky venture for organisations. We discuss two tools and frameworks that are 

helpful in managing the change process from one business model to another: the innovation 

readiness level (IRL); and the business model coherence scorecard (BMCS). 

3.5.1 Innovation Readiness Level (IRL) 

Lockheed Martin, a US-based aerospace and defence firm, developed a tool to manage the 

risk–return trade-off related to business model innovation (Evans and Johnson, 2013). The firm 

set out to answer two questions related to its investment decision on new business models. 

First, if the new business model goes to plan, will it be financially material to the business? 

Second, what are the risks of implementing the new business model? The first question is 

answered using various measures of return on investment and net present value based on the 

best available estimates. In answer to the second question, the risks typically increase, as the 

new business model differs from the existing business model. Hence, one way of estimating 

risk is to develop a metric that quantifies the difference between the existing business model 

and the new one. An alternative approach adopted by Lockheed Martin is to measure the 



89 
 

innovation readiness level of its various functions with respect to the proposed new business 

model. Such a measure of readiness provides a proxy for the degree of “stretch” that the firm 

needs to go through in order to adopt the new business model. This is called the innovation 

readiness level (IRL). 

Table 3.1: Technology Readiness Levels and Innovation Readiness Levels  

 

Source: Adapted from Evans and Johnson (2013) 

The concept of the IRL is borrowed from NASA’s technology readiness levels (TRLs). Under 

the TRL, readiness levels vary from 1 to 9, where 1 refers to basic principles that have been 

observed and reported and 9 refers to an actual system that is proven in successful mission 

operations. A similar concept can be developed for IRLs, as shown in Figure 2 (above). The 

IRLs are measured at functional level, say, manufacturing readiness level (MRL), human 

resources readiness level (HRL), and others. IRLs are not a measure of maturity or goodness 

but are intended to capture the degree to which the function has demonstrated the capabilities 

needed to migrate from the existing business model to the new business model. The IRL scale 

can be seen as logarithmic, whereby taking a function from 4 to 6 might require considerably 

more resources than taking it from 2 to 4. Once the evaluation is done at a functional level, 

Level Technology Readiness Level Innovation Readiness Level

1 Basic principles observed and reported General specification of capabilities required by
function to execute business model generated

2 Technology concept and/or application formulated Detailed specification of capability requirements
generated for each function

3 Analytical and experimental critical function 
and/or
characteristic proof of concept

Active development of capability begun

4 Component and/or breadboard validation in 
laboratory environment

First general demonstration of capability achieved

5 Component and/or breadboard validation in 
relevant environment

Good demonstration of capability achieved

6 System/subsystem model or prototype 
demonstration
in relevant environment

First demonstration of capability in the market
(e.g., sale of beta product)

7 System prototype demonstration in operational 
environment

First transaction involving full product in final form

8 Actual system completed and qualified through 
test and demonstration

Capability successfully used in business (generally
in cash-positive operation)

9 Actual system proven in successful mission 
operations

Capability in routine use to support full-scale
production



90 
 

IRLs can be plotted on a radar diagram with scales from 1 to 9 in order to obtain a picture of 

the readiness levels of the different functions, which enables a dialogue about how the 

capabilities of the different functions can be enhanced to adopt the envisioned business model. 

Moreover, IRLs for the different functions can be summed, perhaps weighted according to their 

criticalness and plotted against the financial returns for the different proposed new business 

models. In this way, the management team is able to consider the return and risk profile, which 

helps when making informed decisions about de-risking the decision to adopt business model 

innovation.  

3.5.2 Business Model Coherence Scorecard (BMCS) 

Understanding and managing business model innovation requires “big picture” systems 

thinking (Velu, 2017). The systems thinking approach of a business model conceptualises the 

difference between the components with reference to the whole and its constituent parts, the 

relationship between components, and the perspectives of the agents who are part of the 

system17 (Cabrera, Cabrera, and Powers, 2015; Midgley and Wilby, 2015). The objective of 

management is to manage the dynamic consistency by maintaining coherence between the 

components of the business model in order to ensure the efficiency of the existing model while 

enabling business model innovation (Demil and Lecocq, 2010). Therefore, a systems thinking 

approach of business models is beneficial when new technologies are implemented to enhance 

the efficiency, and effectiveness, of the business model. 

As discussed earlier, most large firms are organised by function. In this context, no one 

“owns” the business model. It is often seen as a “given”, something that each function needs 

to optimise but which no one questions. One of the dangers of such organisational silos is that 

it may make sense for one part of a firm to adopt a new technology in order to make a particular 

 
17 The notion of perspectives or viewpoints encompasses the subjective beliefs held by agents, which can then 
influence the evolution of the system. 



91 
 

process more efficient. However, if the system is not looked at in its entirety, this can be 

problematic and create conflicts with other processes. As a result, the cohesiveness of the 

business model as a system and the associated information to manage are often overlooked.  

The “balanced scorecard” is an established method of augmenting financial reporting 

with other key measures, such as how the business is creating value for its customers, what 

internal processes it has for satisfying customer and shareholder needs, and how it is developing 

its people, systems and culture to achieve growth (Kaplan and Norton, 1996). More recently, 

the approach has been extended to emphasise the alignment needed to capture synergies across 

the business through mechanisms such as having a clear business strategy. While this more 

nuanced approach is a significant improvement on financial reporting, it still does not give 

managers the information they need to understand and manage the evolution of the business 

model. 

Another inhibitor of business model innovation is that many firms rely on profitability 

from management information systems (MIS) as their principal indicator of success.18 

Furthermore, most accounting systems tend to look at the profitability of different parts of the 

business independently, without taking into account the value they might be generating 

elsewhere in the organisation or ecosystem. Profitability is based on the accounting principle 

of matching revenue and costs during a reporting period (Hergert and Morris, 1989). 

Profitability might be measured at a product, business-unit or geographical level within the 

organisation. Profitability reporting is necessary to understand the economic and financial 

viability of a business and hence for capital allocation and decisions about business growth. 

However, profitability reports tend to supress the information on the interactions of the activity 

system that constitutes the business model and therefore the dynamic consistency of the 

 
18 MIS encompasses business information systems that provide financial and non-financial information to help 
senior management make decisions.  



92 
 

components of the business model. Systems dynamics thinking could be valuable for 

understanding the interactions of the activities (Sterman, 1984; Sterman et al., 1997). 

Measuring the interactions of the activity system in a way that identifies both the enhancing 

and mitigating effects of a change of activity following the adoption of new technologies is 

essential in order to help identify opportunities for business model innovation. Studies have 

emphasised that managing linkages across the value chain, business models and ecosystems is 

one of the most challenging and complex tasks for management and is a major source of 

competitive advantage (Demil and Lecocq, 2010; Porter, 1985). Therefore, profitability reports 

that are complemented with a business model coherence scorecard (BMCS), which provides 

information on interlinkages – both within and across the value chain of firms – and hence 

measures the cohesiveness of the system, would enable senior management to better identify 

opportunities for business model innovation (Velu, 2020).  

The BMCS uses systems dynamics thinking to model the behaviour of the system as a 

whole rather than piecemeal. It aims to measure the alignment between the different 

components of the business model, from four perspectives: 

(1) Physical flow: Are the raw materials and finished products and services delivered at the 

right time and in the right place? 

(2) Information flow: Is the information for decision-making delivered to the right people 

or systems at the right time? 

(3) Decision rights: Do the right people or systems have the authority to make decisions? 

(4) Incentives system: Are people appropriately incentivised to make timely and joined-up 

decisions? 

By asking these questions of all the elements in the business model, it is possible to see if the 

firm is delivering on its customer value propositions while making a satisfactory return. In 

doing so, the BMCS complements traditional financial reporting in enabling business model 



93 
 

innovation while evaluating its financial viability. 

To help us think about the complexities of business model innovation, let us look at 

the following scenario with a consumer durable product such as a washing machine. The same 

principle could be applied to a more complex product such as the spare part for an aeroplane 

engine. Typically, for a washing machine, there are a number of key players such as the 

consumer, the retail store that sells and repairs the machine, and the manufacturer of the 

washing machine. If, for example, a component in a washing machine were to become faulty 

beyond repair, the consumer might have to contact the retailer, which then contacts the 

manufacturer – which has to hold a large number of spares in stock – asking for that specific 

component to be sent out from its storehouse located elsewhere. The entire process may take 

several weeks to complete, causing substantial inconvenience for the consumer during the 

wait. Now, in an integrated additive manufacturing network of the future, the appliance may 

be embedded with sensors capable of diagnosing the machine’s integrity, making notifications 

about failure or upcoming potential failure of parts. This information can be connected with 

manufacturers in real time, which then share data files with a third-party 3D printing firm in 

the local vicinity to punctually produce, deliver and install the parts. Once the work has been 

completed, payment can be automatically deducted via a smart contract. The entire network 

can be managed using distributed ledger technology, which permits accurate recording of the 

contracts and various procedures, ensuring security via encryption. The inter-connectivity 

between different parties requires advanced digital connectivity infrastructure such as 5G, 

which also enables the functioning of cloud computing to provide the computational resources 

needed by AI algorithms for the purpose of predictive maintenance, and to optimise various 

processes. Distributed ledger technology combined with additive manufacturing could lay the 

groundwork for new business models such as shared factories and secure design marketplaces 

(Klöckner, Kurpjuweit, Velu, and Wagner, 2020). The above example illustrates how a range 



94 
 

of digital technologies are brought into play via the additive manufacturing network. In order 

to take advantage of the opportunities, firms in the relevant sectors need to collectively seek 

to adopt new business models around the new technologies. 

This is an example of a whole-system innovation that could result in more agile 

customer service, greater efficiency for the manufacturer and less waste, thanks to a better 

repair service. However, if only parts of the process are adopted piecemeal – for example, if 

the manufacturer uses 3D printing to make new parts and hold them in stock – then the 

benefits of business model innovation will not be realised. 

Figure 3.2: BMCS Coherence Matrix 

 

 

  Source: Adapted from Velu (2020) 

We need a structured way to evaluate the pros and cons of changes to the business model. 

Design and Product Development
Procurement
Manufacturing
Assembly
Sales and Marketing
Distribution
Customer Service
HR and Training
IT Development and SupportInter-relationships effects

Enhancing effect

Mitigating effect

Internal Coherence Analysis

R
etail Store

R
epair Specialist

Logistics Firm

External Coherence 
Analysis



95 
 

The first step is to examine its potential impact on the firm’s coherence internally, across all 

functions (product design, procurement, manufacture, sales, distribution, customer service, 

HR and IT), and then externally, to include ecosystem partners such as the logistics firms, 

repair specialists and retail stores. 

Internally, the effects could be both positive (better customer service and opportunities 

for product innovation, for example) and negative (challenges for IT in supporting a new, 

standalone machine, which may take longer to get the part to the customer). Similarly, there 

are pros and cons for ecosystem partners. Providing a bespoke service for customers needs to 

be traded off against the complexity of managing, for example, the logistics of delivery when 

the logistics firm might not know when the part is going to be ready. Such analysis could be 

done using a BMCS coherence matrix, as illustrated in Figure 3 (above). 

Having assessed the possible impacts of the new business model on the firm and its 

ecosystem, the next step is to look at how it would generate revenue while delivering the value 

proposition to the customer. 

Table 3.2: Revenue and Cost Coherence Analysis Report 

  

Source: Adapted from Velu (2020) 

Value Creation Value Network
Revenue/Value
Proposition

Increased flexibility
Increased time to delivery

Cost Reduced inventory
Uncertainty from printing 

on demand

Due to uncertainty from 
printing on demand

Resource Velocity Could increase or decrease depending on the net effect 
of flexibility and time to deliver for the customer 

Margins/Profits Potentially increased 
margins/profits depending 
on the trade-off between 
revenue and costs and 
resource velocity

Potentially decreased 
margins/profits from higher 
costs depending on impact 
of revenue and resource 
velocity



96 
 

In our example, the greater flexibility for product design could increase revenue but the 

increased delivery times could negate the benefits to the customer and decrease revenue. For 

the manufacturer, holding less inventory could lower costs but the uncertainty and complexity 

of printing on-demand could increase them. Combining an analysis of revenue and costs with 

the rate at which assets are turned over to make a profit – the resource velocity – will indicate 

the likely impact of margins and profit. Such analysis could be captured with a revenue and 

cost coherence analysis report, as shown in Figure 4 (above). 

Applying this value lens in conjunction with an analysis of the aspects of business 

models discussed earlier (physical and information flows, decision rights and incentive 

systems) is likely to highlight some of the problems with the proposed business model and 

catalyse discussions for improvements, such as moving the printing nearer to the customer, in 

partnership with the retailer or a repair firm. 

The benefit of the BMCS is that it gives the management team a mechanism for 

discussing the cohesiveness of a complex system and a method for evaluating its effectiveness. 

It is important to stress that it is not designed to be a one-off but a tool to enable continuous 

dialogue among managers, both within and across the firm, to identify and enable business 

model innovation. 

3.6. Conclusion 

One of the key insights from the work of Alfred Chandler in studying the American enterprise 

is that organisational structure follows strategy (Chandler, 1962, 1977).  For example, changes 

in strategy, such as product market diversification, require subsequent alterations in structure, 

such as divisionalisation. However, scholars have also shown that the organisational structure 

might influence the strategy (Miller, 1986). This is because the design of an organisation 

implies certain activities and process architecture and information flows that might make it 



97 
 

difficult for it to change its strategy. For example, strategies of differentiation and innovation 

might be difficult to implement in organisations that have fairly mechanistic structures that 

place significant emphasis on cost control and standardised repetitive processes. Similarly, 

organisations that have fairly organic and dynamic structures might be too flexible and 

inefficient to serve as cost leaders. The formulation of strategy is the contingent plan about 

which business model to choose. Hence, strategy formulation influences the design of the 

business model. However, the design of the business model, in turn, might determine the 

architecture of the activities and the information flow to influence the cognitive aspects, as well 

as the capability of the management team to alter their strategy.  

 Studies have argued that one of the challenges for management is to maintain the 

congruence between the external environment, such as new technologies and customer 

preferences, and internal processes. Often, firms need to make a trade-off between the need to 

alter the activities on a piecemeal basis, to match the changing environment, and the need to 

keep the business model as a system coherent (Miller and Friesen, 1978, 1982). There might 

be hidden costs in making frequent piecemeal changes to the organisational structure to cope 

with a changing environment because of the disharmony that it creates in the business model 

functioning as a system (Burns and Stalker, 1961; Miller, 1982, 1987). Hence, there might be 

performance benefits of delaying change and making a more quantum or multifaceted 

revolutionary change. Such a decision and management of the trade-off would depend on 

uncertainty and the rate of change of the environment and the design of the business model in 

terms of modularity (Baldwin and Clark, 2000).  

 Thompson (1967) provides the context for different forms of leadership style to deal 

with uncertainty and preferences. The study articulates the uncertainty relating to the inability 

to establish cause and effect (Spender and Kessler, 1995). Preferences relate to different 

outcomes preferred by managers. When both preferences and cause and effect are clear, the 



98 
 

decision-making style of the leader becomes computational and often deals with fairly 

unambiguous short-term situations. When the outcome preferences are clear but the cause and 

effect are uncertain, the decision-making of the leader will be based on judgement. When the 

cause and effect are fairly well established but the preferences among managers are uncertain, 

the decision-making style will be based on compromise between different groups. Hence, there 

would be political coalitions and the leadership style would need to focus on negotiating and 

bargaining among the groups. Finally, when both preferences and cause and effect are 

uncertain, the leadership style needs to be inspirational and charismatic to bring people along. 

Often, when there are significant technological shifts and changes in consumer preferences, 

there will be uncertainty in both preferences and cause and effect. This is when radically new 

business models are needed, which calls for a charismatic leadership style. 

 The challenge for leaders is to keep the rewards system aligned with the objectives of 

the firm in enabling business model innovation. Given that business models are complex 

organisational systems requiring coordinated change across many functions, the senior 

management team needs to work as a coherent team in order to implement business model 

innovation. In most management by objective systems, goals in areas where quantification is 

difficult go unspecified (Kerr, 1975). Hence, often the softer aspects of intangible capital, such 

as working collectively as a team, ensuring that information is shared and empowered decision-

making are less well measured and rewarded (Kaplan and Norton, 2006). The more 

individualistic measures at activity, process or functional level are easier to measure and are 

rewarded. Such a tendency to measure and reward individualism over collectivism (Morris, 

Davis, and Allen, 1994) could result in firms focusing on efficiency improvement rather than 

rethinking the business model to focus on effectiveness.  

 There are several areas in organisational structure and leadership that require further 

study, covering aspects of business model design, strategic decision-making and leadership 



99 
 

styles. First, when and how should senior management adopt evolutionary business model 

innovation compared to revolutionary business model innovation? On the one hand, when the 

environment in which the firm operates changes, one can make incremental changes to the 

activities and processes in order to better fit the environment. However, this causes the internal 

coherence of the business model to be altered and could make the firm less efficient and 

effective. On the one hand, waiting to make a radical business model innovation later, while 

not making any incremental changes, could be more beneficial, albeit riskier. How the 

leadership of a firm should think about this trade-off, in terms of both theoretical framework 

and practical implications, requires further research.  

Second, how senior management should manage the potential conflicts between a new 

and an existing business model requires further exploration. The issues to consider here are the 

optimal organisational design, the governance structure that needs to be put in place and the 

process of conflict resolution. Related to this is a better understanding of the composition and 

governance models of the top management team that would enable business model innovation. 

Third, the interplay between business model design and strategic choices, and vice versa, 

requires further elaboration. In particular, do particular business models provide management 

with certain types of information and hence make it more difficult to change business models 

in the future? In this context, the frameworks that would enable managers to make better 

decisions about future business model innovation opportunities that are less certain and riskier 

than the existing business model require further study.  

This chapter has provided an overview of the principles of organisational design and 

leadership for business model innovation and proposed some outstanding research issues on 

this topic.  

 



100 
 

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CHAPTER 4: DIGITAL TECHNOLOGIES AND TRANSFORMATION 

  



106 
 

CHAPTER 4: DIGITAL TECHNOLOGIES AND TRANSFORMATION 

 

Computers are useless. They can only give you answers. 

(Pablo Picasso) 

 

4. Introduction 

It is common knowledge that a number of major firms such as Amazon, Google and Uber have 

transformed industries using digital technologies. All of these firms are founded on business 

model innovations: offerings that involve systemic changes to how value is created and 

captured (Appio et al., 2021; Bharadwaj et al., 2013). There are many newspaper articles and 

blog posts providing advice to managers on how to deal with the opportunities and challenges 

created by digital technologies. Digital technologies can offer new forms of value creation 

while posing a threat to conventional means of customer value propositions (Aversa et al., 

2020; Bresciani et al., 2021; Velu, 2016). Digital technologies can help to transform 

organisations, opening up possibilities for new firms to emerge while destroying the viability 

of others (Velu, Pooya, and Dalzell-Payne, 2019; Berman et al., 2019; Broekhuizen et al., 

2020). Established firms who are considering implementing digital technologies need to decide 

how to do so, as it can profoundly alter their prospects for the future.  

Today, several digital technologies and critical infrastructures, such as AI, cloud 

computing, additive manufacturing and 5G, are developing rapidly and may transform the 

economic landscape on which firms compete. The transformation may be compared to several 

general-purpose technologies (GPT) from the past, including steam and electricity (David, 

1990; Rosenberg and Trajtenberg, 2004; Velu, 2020; Dosi, 1982).19 Electric motors were 

 
19 General-purpose technologies tend to display the characteristic of general applicability, whereby it performs 
some generic function that is vital to the functioning of a large number of products or production systems 
(Rosenberg and Trajtenberg, 2004). 



107 
 

introduced around 1879 to replace steam engines, yet productivity initially declined slightly up 

to 1920, before beginning to rise rapidly (David, 1990). The rapid productivity growth in US 

manufacturing may be attributed to new organisational structures and business models that only 

emerged in the 1920s. The new business models involved putting multiple electric motors 

where they are needed and leasing them from external firms with specialist support services. 

This enabled productivity growth through lower energy consumption, improved production 

flows and greater resilience. 

Studies suggest that there are multiple stages or phases to digital change, ranging from 

relatively simple to comprehensive changes (Verhoef et al., 2021). These phases can be 

classified into three broad categories: digitisation, digitalisation and digital transformation. 

Digitisation is the encoding of analogue information into a digital format (i.e. into zeros and 

ones) such that they can be stored, processed and transmitted by electronic means (Yoo, 

Hendfridsson, and Lyytinen, 2010). Digitalisation refers to how digital technologies can be 

used to alter existing business processes (Pagani and Pardo, 2017). Digital transformation 

refers to a more comprehensive change across the firm that contributes to new business models 

(Iansiti and Lakhani, 2014).  

Digital technologies enable products and services to be delivered electronically and 

hence provide new value propositions to customers (Andal-Ancion et al., 2003). Moreover, 

digitally enhanced products and services encode much more information and are significantly 

more customisable. Hence, firms could better engage with customers and also obtain 

information about their processes on a real-time – or near real-time – basis. Digital technologies 

enable a more integrated set-up, both within and across firms. This enables the 

disintermediation of some existing firms but reintermediation with different roles, depending 

on the flow of material and information required to develop and deliver propositions to 

customers. Such an integrated approach implies that firms need to change their business models 



108 
 

from primarily “make and sell” products and services to “sense and act” based on the 

information flow between the customer and firms across the network (Koebnick, Velu, and 

McFarlane, 2020). Hence, digital transformation can be challenging for firms. In this chapter 

we provide an overview of the theory behind digital technologies and the implications for 

digital transformation. We then discuss some of the recent developments in digital technologies 

based on developments in artificial intelligence. Following that, we preview a new and 

emerging general-purpose technology based on quantum mechanics that is likely to change the 

landscape of computing and the Internet in years to come, as well as providing a basis for major 

digital transformation opportunities. Finally, the conclusion section provides some of the 

societal challenges related to business model innovation in the digital economy.  

4.1 The Evolution to Digital Technologies and Transformation Challenges 

Information-technology-driven competition that has shaped strategy can be classified into three 

waves (Porter and Hepplemann, 2015). The first wave, in the 1960–80s, involved the 

automation and digitisation of individual activities across the value chain, such as order 

processing, procurement and manufacturing resource planning. This involved standardising 

processes, and the challenge for firms was how to differentiate effectively. The second wave 

came with the rise of the Internet in the 1990s and 2000s, which enabled the integration of 

activities across suppliers, customers, channels and geography, enabling more globally 

distributed supply chains. In the third wave, which is happening today, IT is being embedded 

into products and hence changing the nature of products and services. Products with embedded 

sensors, increased connectivity and cloud-based data storage and analysis enable new product 

features and service functionalities. This could potentially reshape the value chain dramatically. 

There is a good example of this from the agricultural context (Porter and Hepplemann, 2014). 

Imagine a tractor that is used on a farm to move earth and cultivate crops. Such a tractor could 

be embedded with sensors, which inform the farmer about its performance and how to optimise 



109 
 

its use. In the next stage the tractor could be connected to other farm equipment such as tillers, 

planters and combine harvesters. This would make it a product system; hence, the basis of 

competition shifts away from being a product to a product system. The manufacturer of the 

tractor could alter its business model from being a farm equipment manufacturer to farm 

equipment optimisation as a service proposition. The next stage could be expanding beyond a 

product system to a system of systems proposition, whereby the connection is not only to farm 

machinery but to irrigation systems, weather, crop prices and seed-management systems. 

Moreover, the connected processes enable increased granularity in segmenting customer needs 

and require enhanced flexibility of value-adding activities to meet these needs. Such features 

will require firms to transform their business models from the traditional “make-and-sell” into 

a “sense-and-act” business model (Koebnick, Velu, and McFarlane, 2020). Such a connected 

system of systems proposition blurs industry borders and throws up major challenges for firms 

in designing the appropriate business models to create competitive advantage.  

Smart products could change how consumers consume the product from buying 

outright to pay-per-use. Alternatively, the firm could go into a hybrid model, whereby product 

ownership is transferred to the user but there is a performance-based service contract to ensure 

that the product performs to a certain specification, such as uptime (Martinez et al., 2017). This 

fundamentally changes the incentive structure of firms. For example, Rolls-Royce traditionally 

might have had a business that gains from selling spare parts and service contracts on its aircraft 

engines (Grubic and Jennions, 2018). However, such a business model might lessen the 

incentives to design engines that are reliable and durable. Hence, following pressure from its 

customers, the firm decided to include sensors in its aircraft engines and to sell a service 

contract by the hour, known as power-by-the hour, which pays based on the hours that the 

engine is in the air (Smith, 2013). This is often known as servitisation (Baines and Lightfoot, 

2013; Martinez et al., 2017; Smith et al. 2011; Neely, 2008; Neely et al., 2005). Such a trend 



110 
 

is happening in many industries, from personal home and office space to personal and public 

transportation systems. For example, automotive firms such as Scania, a Swedish commercial 

vehicles manufacturer, has connected 500,000 vehicles on the road to manage the optimisation 

of routes, predictive maintenance and more efficient staffing of trucks as a service (Bjorkdahl, 

2020). However, the generation of technological shifts from product systems to systems of 

systems might prove challenging for truck companies. The truck industry is facing a 

technological shift from diesel engine powertrains to electric road system (ERS) powertrains, 

whereby there is continuous electric power transfer to trucks via the road surface (Tongur and 

Engwall, 2014). Although, from the customers’ perspective, there might be little change, this 

represents a radical change from the truck manufacturers’ perspective. Such ERS powertrain 

systems will be more integrated to other subsystems, such as roads, fuel supply and billing 

system, than the diesel-engine-based powertrain system. Truck manufacturers’ core 

capabilities need to be transformed from engine technology to knowledge of customer 

behaviour, logistics and fleet-management services as customers adapt to wanting 

transportation services. Hence, the challenge for firms is to decide the scope of the firm, what 

core competency it would need and who it needs to partner with to enable complementary 

assets to come together to provide the product and service offering to the customer (Leonard-

Barton, 1992).  

4.2 Theory of Digital Technologies 

Digital technologies are increasingly prevalent in enabling new sources of value. The Von 

Neumann architecture of digital technologies enables the instructions to manipulate the data 

and the data itself to be stored in the same format and location, which enables 

reprogrammability (Langlois, 2007). Digital technologies enable the decoupling of information 

from its related physical form or device, which has been termed resource liquification 

(Normann, 2001). This enables digital technologies to have two features. First, there is the 



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separation of content from the medium (Yoo et al., 2010; Faulkner and Runde, 2013). For 

example, in the physical world, the content of a book in terms of, say, its story is tied to the 

physical copy of the book. However, with the digital medium, the content of the book can be 

read or listened to in various ways, such as the phone, computer or tablet, among others. The 

second feature is the separation of form and function. For example, a private car has often been 

used as a personal vehicle, and hence the form and function are relatively fixed. However, with 

the advent of Uber, the personal car is being used as a taxi and reverting back to being used for 

private purposes. Hence, digital technologies enable the procrastinated binding of form and 

function, whereby new capabilities can be added to a proposition once they have been designed 

and created (Zittrain, 2006). These, in turn, provide new ways to recombine resources and 

enable generativity, the capacity to produce unprompted change and innovation from 

uncoordinated and heterogenous audiences (Yoo et al., 2010).  

Moreover, digital technologies can create and shape physical reality, a phenomenon 

called ontological reality (Baskerville et al., 2020). Typically, the physical reality takes 

precedence over the digital reality. For example, as one drives, the blue dot representing the 

location of the car on Google Maps follows the physical location of the car. Ontological 

reversal happens when the digital version of an object is created first, before the physical 

version. For example, in the case of autonomous cars, the blue dot that represents the car is 

created first and is computed to move from point A to point B on Google Maps. The real car 

then moves based on the movement in the non-material digital blue dot. Hence, the non-

material digital object,20 the blue dot, comes before the material real object, the autonomous 

car. In this way, digital reality takes precedence over physical reality and the ontology is 

reversed. This ontological reversal could have profound implications for human experiences 

 
20 Digital objects have the properties of a binary system, are editable and display replicability (Faulkner and 
Runde, 2013). 



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and how value is created and captured. The vertical and horizontal scope of the firm, in terms 

of the activities within its hierarchy, as well as across the network of the value chain, will 

determine the boundary of the firm. These features of digital technologies enable new 

combinations of digital and physical assets to redefine the boundary of the firm.  

The transaction costs theory of the firm helps to provide an initial framework to 

understand the boundary of the firm. Transaction costs theory suggests that each actor will 

require payment of its resources’ marginal productivity in order to provide incentives to 

recombine resources (Townsend and Busenitz, 2008). The transaction costs theory of the firm 

focuses on the balance between the costs of transacting in the market compared to the firm. 

Coase (1937) argued that firms exist when the transaction costs of using the markets are higher 

than those within the hierarchical structure of a firm. Transaction costs in markets can arise 

because of uncertainty; asset specificity – how specific the assets are to the required 

transactions; and the degree of opportunism (Williamson, 1985). Economists start with the 

premise that markets are an efficient way of coordinating economic activity in cases in which 

a pure exchange economy exists (e.g. spot contracts) (Williamson, 1985). Markets, however, 

prove to be inefficient if business dealings require coordinated investment where the 

composition of the assets is very specific to the transactions, and if the business dealings are of 

a non-contractable nature as a result of uncertainty (Grossman and Hart, 1986). Non-

contractability can arise from asymmetric information between trading partners, bounded 

rationality and difficulty specifying and measuring output (Gibbons, 2005). Non-

contractability is also an issue in team-based production, which faces challenges measuring the 

input of each party precisely, making it difficult to apportion the value created (Hart and Moore, 

1990). This gives rise to the metering problem, which is caused by shirking by the parties in 

the team, which is a form of moral hazard (Alchian and Demsetz, 1975). Organising team-



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based production is often therefore more efficient within the hierarchical structures of firms 

than markets. 

Modularity is important in understanding how transaction costs determine the boundary 

of the firm (Baldwin, 2007). Transactions are defined as mutually agreed transfers between 

actors with compensation. The costs of the output being transacted need to be defined and 

measured, which are called mundane transaction costs. The mundane transaction costs are 

minimised at the thin crossing points of the task network, which creates module boundaries. 

Tasks within such a boundary are called transaction-free zones, and transactions occur between 

modules. Therefore, tasks that correspond to problem-solving, as well as routine activities 

where transfers are dense, need to be located within these modules. These modules are called 

transaction-free zones, where the cost of the transactions is less than the value of the transfer. 

Transactions need to be located at module boundaries where mundane transaction costs are 

minimised; this corresponds to the thin crossing points of the task network and where the 

boundary of the firm lies. Hence, transaction costs theory explains how tasks are bundled into 

modules in such a way that transactions occur across modules, known as thin crossing points, 

in order to minimise costs (Baldwin, 2007). An alternative methodology to the transactions 

costs approach to determining the boundary of the firm is to examine the capabilities and 

resources that maximise the resource portfolio of the firm, as well as the market demand for 

new customer value propositions (Jacobides and Billinger, 2006; Priem et al., 2018).  

A valuable way to understand how such organisation of activities and tasks might be 

affected by digital technologies is to consider the firm as a multi-agent system with an 

identifiable boundary and goal, in which an individual agent’s efforts are expected to make a 

contribution (Puranam, Alexy, and Reitzig, 2014; Kretschmer and Khasabhi, 2020). In this 

context any functioning organisation involves solving two fundamental and inter-linked 

problems, namely, the division of labour and integration of efforts. The division of labour 



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involves how to divide the task – task division – and how to allocate the tasks to individuals or 

teams – task allocation. The integration of efforts involves the provision of appropriate 

incentives and motivation to complete the tasks – the provision of rewards – and what 

information needs to be provided in order to execute the tasks and coordinate the actions – the 

provision of information.  

Digital technologies fundamentally alter the four elements that constitute the division 

and integration activities. First, digital technologies can provide significantly more information 

as a result of the liquification process that we outlined earlier. Moreover, digital technologies 

could create a new wave of critical elements for creating customer value, and hence certain 

new activities might need to be added while others are eliminated. For example, Cemex, a 

Mexican-based global cement firm, was able to eliminate a substantial proportion of its human-

based inspection tasks for cement supply because it could monitor inventory levels in real time 

at client sites using sensors (Kretschmer and Khasabhi, 2020). Such a process requires the 

regrouping of tasks, not only in how they are to be divided but also in the integration process. 

The regrouping of tasks needs to be done by putting tasks that are complementary together in 

order to augment their combined value, as well as optimising coordination (Milgrom and 

Roberts, 1990). Such complementarities might arise by working with other firms. For example, 

Vodafone, a UK-based telecommunications firm, worked with Microsoft to provide the 

underlying technology infrastructure for its digital transformation efforts (Correani et al., 

2020). Vodafone adopted Microsoft’s conversational autonomous interface using neural 

networks processing natural language when redesigning its customer care services. Vodafone 

is able to interact with its customers through multiple channels such as voice, social networks 

and home assistance, in order to listen, understand and assist customers.  

Digital technologies also affect information flow for communication, monitoring and 

coordination. Research shows that information technologies and communication technologies 



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have a different impact on autonomy and control (Bloom et al., 2014). On the one hand, 

information technologies, such as enterprise resource planning (ERP) systems, increase the 

autonomy of employees and hence enable decentralisation. On the other hand, technologies 

that improve communications, such as data intranets and electronic communications systems, 

could potentially decrease the autonomy of employees and encourage centralisation. Hence, 

these two forces could impact how organisations divide and integrate activities, both within 

and across firms. Such division and integration as a result of digital technologies will affect the 

design of business models.  

4.3 Realising the Full Potential of Digital Transformation  

A report by the Conference Board titled “Realizing the Full Potential of Digital 

Transformation” noted that firms that have successfully executed digital transformation share 

two common characteristics (Hao, Hicks, Popper, and Velu, 2020). First, these firms have the 

discipline to undertake digital initiatives only if they are aligned with the overarching corporate 

or business unit strategy. Second, they can enable business model innovation through new 

value propositions for their customers through the adoption of digital technologies. The 

research study was based on interviews with executives such as chief digital officers, chief IT 

officers and R&D directors from 14 companies across 10 industries in the US and Europe. The 

study provides three insights on digital transformation: first, digital transformation must be 

integrated within the business strategy; second, business model innovation is often a key part 

of digital transformation and leads to creating competitive advantage for firms; and, third, firms 

measure and manage digital transformation using a multifaceted approach. We discuss these 

insights from the Conference Board research report below.  

One of the biggest challenges that firms face is ensuring that their digital adoption fits 

the overall corporate strategy. Often firms might be tempted to adopt a new digital strategy, 



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such as blockchain, sensors or additive manufacturing technology, because it is a novel 

technology, without necessarily thinking through how it will improve customer solutions. 

Digital technology adoption often requires continuous adjustment of activities and processes 

that needs to be closely aligned with the strategic planning process. Moreover, the adoption of 

digital technologies might inspire a pivot in an existing strategy or a shift to an entirely new 

one. However, the continuous alignment between digital technology adoption and corporate 

strategy needs to be maintained by the firm. This is especially challenging when firms are 

organised across functions and geographies where there could be a disconnect between digital 

technology adoption and the corporate strategy as a result of the misalignment of interests and 

rewards.  

A US-based car-rental firm was able to learn from the acquisition of a new car-rental 

firm that rents cars by the hour and which had superior on-board electronics monitoring 

systems in order to manage the car-rental system. The firm learnt that having on-board 

electronics car technology on its regular longer-term rentals would be helpful in monitoring 

the performance of its cars and replacing vehicles if the system predicted a possible breakdown. 

The rented vehicle is normally replaced by exchanging another car with the faulty vehicle 

wherever the rental vehicle has been taken, for example, to a holiday destination. The firm 

learnt that this increases service quality and contributes to customer loyalty. With the 

increasing possibility of autonomous vehicles, the car-rental firm is looking to develop a 

business for fleet-management services as the result of on-board digital technology 

management systems – digital transformation that inspires a new business model. 

There are several ways that firms can align their corporate strategy with digital 

technology adoption. The first approach involves the definition of a major customer solution 

outcome based on the technology trend. A large European personal care company has a strategy 

of helping customers to visualise and personalise their beauty products. Once this has been 



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done, using cross-functional teams, IT develops feasible, cost-effective digital solutions. De 

Beers defined the need to have end-to-end traceability of its diamonds, because of the risk 

posed by lab-manufactured diamonds, and, with partners, it developed a blockchain system to 

do this, from the digital exploration of diamonds to omni-channel sales and distribution. The 

second approach involves organising by cross-functional teams to develop the capabilities to 

achieve major strategic goals. At a major US-based semiconductor manufacturer, the firm 

identified 13 competencies such as demand creation, product information management and 

order fulfilment to grow the market share and profitability of the firm. These major competency 

areas are then organised and led by a cross-functional team consisting of senior management 

from the various divisions of the firm, which reports to the executive leadership team. A third 

approach is followed by BBVA, the Spanish multinational financial services firm, which 

established a corporate venture fund to observe and invest in promising fintech start-ups that 

could be integrated into the bank’s business strategy. The fourth approach is to develop trends 

from the bottom up. For example, at 3M, a multinational conglomerate based in the US, 

business units are encouraged to draw up strategic plans that address megatrends in technology 

and how they are likely to impact the business. Through a recursive process these are aligned 

with the corporate strategy and the strategy is refreshed when required. 

 Digital technology adoption is also most beneficial when firms re-examine how they 

create and capture value (Christensen et al., 2016; Cennamo et al., 2020). For example, a 

leading US publishing company has transformed the delivery of books from a physical to a 

digital format, which enables it to collect information on usage patterns, which can be used to 

provide additional services such as tutorials to improve students’ exam performance. 

Moreover, the digital model has also allowed the company to explore new approaches to 

developing value, such as selling products directly to consumers and disintermediating 

distributors and developing subscription models for students, professors and institutions.  



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 Two major challenges that firms face when leveraging digital technologies to change 

their business models are the piecemeal syndrome and incentive misalignment (Velu, 2020). 

The piecemeal syndrome arises from the fact that managers are typically risk-averse, according 

to prospect theory, whereby disutility from failure is higher than the utility from gain. Hence, 

in most firms the incentives are typically aligned to conduct incremental changes at process or 

functional level, with less regard for the systemic changes needed for business model 

innovation, as the latter is often riskier than the former. This piecemeal adoption effect was 

seen with the introduction of PCs to replace mainframe computers (Steinmueller, 2000). Many 

firms treated PCs similarly to mainframes, with users continuing to procure services from the 

IT department as a centralised function while not fully benefiting from the more customisable 

opportunities provided by the PC. Hence, PCs took a long time to benefit firms, and they only 

did so when they facilitated the growth of more generic software, for word processing and 

manufacturing operations control, which was more customisable and could be upgraded, thus 

quickly displacing dedicated computers.  

The second challenge relates to incentive structures that are misaligned with the new 

business model. For example, 3M sold furnace filters that keep air filtered and clean in 

buildings. The emergence of sensor-based technologies enabled 3M to develop a servitised 

business model based on selling “clean air” to its customers on a subscription basis; the 

company operates on the basis of promising a certain quality of clean air and is responsible for 

monitoring and cleaning – or replacing – the filters when necessary. The new subscription-

based business model demands the minimisation of filter changes. However, the older business 

model requires maximising product sales and manufacturing large volumes to get the benefit 

of economies of scale to reduce the costs of production per filter. These conflicts often prevent 

firms from adopting new business models enabled by digital technologies.  



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The third element of the digital transformation highlighted by the Conference Board 

report relates to how firms measure and manage digital transformation using a multifaceted 

approach consisting of input, throughput and output. Input involves measuring the capability 

and readiness of the organisation for digital transformation. For example, some organisations 

measure the digital capability of their staff in both soft and hard skills and ensure sufficient 

diversity among others between the sciences and the humanities. Gurbaxani and Dunkel (2019) 

proposed a six-dimension framework to measure firms that are gearing up for digital 

transformation. These six dimensions are: clarity of the strategic vision; the degree of 

alignment of the vision with investments; the suitability of the culture of innovation; the 

possession of sufficient intellectual property assets and know-how; the strength of digital 

capabilities; and the use of digital technologies. Firms can benchmark themselves on these 

dimensions against other firms in four broad categories: behind, on par, slightly ahead, and 

significantly ahead. Throughput requires organisations to systematically report on how 

effectively and efficiently their business model delivers the right customer value. The business 

model coherence scorecard (BMCS) discussed in Chapter 3 might provide a useful framework 

to identify and manage the efficiency and effectiveness of business models as part of the digital 

transformation effort. Finally, digital transformation success should be measured against 

achieving the business strategy. Such output measures call for a balance between financial and 

non-financial measures (Kaplan and Norton, 2004; Velu, 2020). Firms should use digital 

technologies to have real-time scorecard systems with customer-centric metrics across the 

different levels of the organisation that need to be fully aligned with the overall strategy of the 

firm. 

4.4 The Age of Data and Artificial Intelligence 

An increasing number of firms rely less on traditional business processes operated by customer 

service representatives, engineers and managers and more on algorithms to make decisions 



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(Iansiti and Lakhani, 2020; Bader et al., 2019: Brock et al., 2019). Artificial intelligence (AI) 

based algorithms set the prices for Amazon, recommend songs on Spotify, suggest films on 

Netflix, match cars with passengers on Uber and approve loans on Ant Group. These AI-based 

algorithms are able to learn and update in order to improve the decisions being made over time 

(Brynjolfsson et al., 2017). Many traditional firms are also beginning to embrace the use of AI 

to transform their business models (Cappa et al., 2021; Del Giudice et al., 2020). 

One of the implications of liquification, the ability of digital technologies to decouple 

information from its related physical form or device, is the abundance of data that becomes 

available (Normann, 2001). Data has been defined as sign tokens or marks used to describe, 

represent or perform reality or index other marks (Alaimo et al., 2020). Studies have claimed 

that data as sign tokens or marks operates at a far more granular level of reality than higher-

order functional entities such as components (Von Krogh, 2018). These sign tokens or marks 

in the form of data are a key resource used in the digital economy to create value; the value is 

created from both recombination and reinterpreting through a process of encoding, aggregation 

and computation of data (Alaimo et al., 2020).  

Since John McCarthy coined the term AI (artificial intelligence) in 1956 at a conference 

in Dartmouth, there has been steady improvement in the techniques used to analyse and 

compute data. The ability to collect large amounts of data resulting from an increase in 

computer power has given rise to this era of AI advances. Artificial intelligence describes a set 

of advanced general-purpose technologies that enable machines to perform highly complex 

tasks effectively (Hall and Pesenti, 2017; Ransbotham, 2019). AI technologies aim to 

reproduce or surpass abilities (in computational systems) that would require “intelligence” if 

humans were to perform them – the science and engineering of intelligent machines 

(McCarthy, 1999). Machine learning is a type of AI in which a machine approaches a problem 

not by being explicitly programmed but by learning from data; it tackles a task by making data-



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driven decisions and predictions (Ghahramani, 2015). There are broadly three ways in which 

machines can learn: supervised learning, unsupervised learning, and reinforcement learning. In 

the case of supervised learning, algorithms learn to predict the output from the input data where 

all the observations in the data set are labelled.21 Unsupervised learning involves observations 

in the data set that are unlabelled, and the algorithms learn the inherent structure from the input 

data. Reinforcement learning is based on interactions with the environment whereby the 

algorithm learns how to optimise based on the presence or absence of some reward.22 

The application of AI may be classified into a hierarchy of analytical tasks, namely, 

descriptive, diagnostic, predictive and prescriptive (Davenport and Harris, 2007). Descriptive 

AI involves the process of gathering and interpreting data to describe what has occurred. 

Diagnostic AI involves the process of gathering and interpreting data sets to detect patterns and 

anomalies and determine relationships in order to explain why something has happened. 

Predictive AI involves the use of descriptive and predictive analysis from the past and 

identifying the likelihood of particular outcomes in the future. Finally, prescriptive AI involves 

using descriptive analysis for what has happened, diagnostic analysis for why, predictive 

analysis for timing and a form of reoccurrence in order to infer actions to influence future 

desired outcomes. For example, in the case of Uber, descriptive relates to understanding the 

customer profile and the rides that customers have taken in each car. Diagnostic involves 

understanding why customers have taken those rides, for example, as a result of weather 

conditions. Predictive involves using historical data to predict which customers are going to 

need cars, when and for which destinations. Finally, prescriptive informs drivers about which 

passengers are likely to need cars, and when, and informing drivers to wait at the right time 

 
21 Data labelling is the process of identifying raw data (images, text files, videos, etc.) and adding one or more 
meaningful and informative identifiers in order to provide context. 
22 Deep learning is a term used with neural networks where multiple layers (deep) are used to represent the 
data structures that can be used by structured, unstructured or reinforcement learning-based algorithms.   



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and in the right place for passengers. This could also involve suggesting to passengers that they 

might want to take an Uber for a particular ride. In the case of industrial application, such as 

the use of sensors in manufacturing operations, descriptive might involve understanding the 

breakdown of machines in terms of type and timing. Diagnostic would include an 

understanding of why they broke down. Was it due to overheating, stress on the rotating parts 

or other factors? Predictive involves an analysis of which machines are likely to break down, 

and when, based on the past pattern of usage. Finally, prescriptive provides information for 

making suggestions about what should be done to minimise or avoid losses. Most applications 

of AI are predominantly descriptive, diagnostic and predictive, while the use of prescriptive is 

still in its infancy. 

Many studies have highlighted the notion that AI should be used for augmentation 

rather than pure automation. Automation implies that machines take over a human task, 

whereas augmentation implies that humans collaborate closely with machines to perform tasks. 

However, Raisch and Krakowski (2021), in their review paper, mentioned that augmentation 

cannot be neatly separated from automation because these dual AI applications are 

interdependent across time and space, creating a paradoxical tension. They provide two use 

cases of AI to illustrate their point about time and space. Let us consider the time element first, 

whereby the use of automation will have an impact on augmentation in the future and there 

will be continuous interaction between them. JP Morgan Chase is increasingly using AI to help 

set the criteria for the selection of candidates to hire. By removing the human element, the idea 

is to make the system fairer and more efficient in choosing candidates for interview. However, 

over time it is likely that digitalisation might require employees to have data science skills, 

which do not play a major role in the extant criteria for selecting candidates. Hence, the initial 

use of AI for automation would require subsequent human involvement, with a focus on 



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augmentation, which allows humans and machines to work together by altering the context and 

adjusting their models accordingly.  

Let us consider the space element next, whereby the use of automation will have an 

impact on augmentation in adjacent processes. For example, Symrise, a major global fragrance 

company, adopted an augmentation approach to generate ideas for new fragrances using a 

database of 1.7 million fragrances based on customer requirements. This model was reached 

through a combination of master perfumers’ knowledge and customer purchases. The system 

initially consisted of automated searches for new novel fragrance formulas faster than humans 

were able to do. However, this use of AI to automate the idea-generation stage has an impact 

on the preceding objective-setting stage, whereby master perfumers must identify and input 

customer objectives and constraints in order to allow the automated generation of fragrance 

formulas matching these requirements in the idea-generation stage. This continuous iterative 

process of AI for automation and augmentation will enable new business models. 

As machines become more intelligent using AI methods, they tend to have feedback 

systems to continuously improve performance, which in turn affects the organisational design 

(Galbraith, 1974). This feedback is likely to affect business model design through the content 

of activities of the organisation, the structure in terms of the relationship between activities, 

and the governance with respect to the responsibility for decision-making. Studies have 

highlighted that AI today is particularly focused on machine intelligence, which tries to solve 

well-defined problems. AI is less suited to defining the problem, as this requires a sense of self, 

motivation and purpose (Raisch and Krakowski, 2021; Von Krogh, 2018). However, one of 

the challenges in redesigning the business model, as machines become more intelligent, is to 

identify the appropriate problems that need to be solved to enable the business model to evolve. 

Such types of problem identification might require more general or human intelligence 

(Davenport and Kirby, 2016; Shevlin et al., 2019). Hence, cooperative methods for managers 



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to use AI to enhance general intelligence would be needed for the business model to evolve 

appropriately to act as a complementary asset to intelligent machines in order to fully benefit 

from AI. Moreover, AI increases connectivity across the value chain. For example, AI is being 

used to develop digital twins, the generation or collection of digital data representing a physical 

object, which enables closer linking of product development, production, distribution and 

aftersales performance in the automotive industry, which calls for co-evolution of the business 

models of firms across the ecosystem. Hence, the business model needs to be seen as a complex 

system that co-evolves with the entire business ecosystem in which the firm is embedded as 

machines become more intelligent and connected (Burström et al., 2021). 

4.5 Next-Generation Digital Technologies – Quantum Technologies 

One of the key issues of digital technologies for firms is not just considering digital 

technologies that have been commercialised but also looking into the future at emerging 

technologies. History shows us that the benefits of new technologies can take many years, if 

not decades, to materialise, as this requires new social, legal and organisational approaches 

(Geels, 2002). Hence, it is appropriate to look forward in time to see forthcoming technologies 

that might have a profound effect on productivity and economic growth. One such technology 

is based on quantum mechanics, which is beginning to show incredible promise as a general-

purpose technology that might have profound implications for all walks of life and in the design 

of business models in years to come (Knight and Walmsley, 2019; van Dam, 2020; MacQuarrie 

et al., 2020; Vedral, 2011). 

In the early 1980s Nobel-prize-winning physicist Richard Feynman challenged 

computer scientists to develop a quantum computer (Cusumano, 2018). Feynman’s challenge 

was based on his intuition that one could not solve problems in physics using classical digital 

computers with bits or binary digits, which are always either 0 or 1. This is problematic for 



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physicists when representing a particle that could be in multiple states. For example, a particle 

(e.g., electron or photon) such as a qubit could simultaneously be in two states, both 0 and 1. 

It would be relatively straightforward to simulate with a single qubit, as it is in state 0 or 1. 

With two qubits, we have the possibility of having both in state 0, both in 1, one in 0 and the 

other in 1, or vice versa, which results in a total of four probabilities. This implies that N qubits 

could be in 2n states. Therefore, with 10 qubits, 1,024 probabilities are needed, and with 20 

qubits, 1,048,576 are needed. The information states required for over 300 qubits would soon 

surpass the number of particles in the universe. However, the systems that scientists investigate 

may have a number of particles that is many orders of magnitude larger, and hence the number 

of probabilities becomes unimaginably large – for example, simulating molecules for drug 

discovery. Feynman published a paper in 1982, Simulating Physics with Computers, where he 

postulated that to simulate quantum systems one needs to build quantum computers, as the 

problem cannot be solved by simply scaling or applying principles of parallel processing with 

classical computers (Feynman, 1982). Feynman went on to remark (1982, p. 486): “Nature 

isn’t classical, dammit, and if you want to make a simulation of nature, you'd better make it 

quantum mechanical, and by golly it's a wonderful problem, because it doesn't look so easy.” 

 Physicists, computer scientists and engineers have come a long way since 1982 in trying 

to harness the power of quantum technologies (Pirandola and Braunstein, 2016; Wehner et al., 

2018). In particular, there are three properties of quantum technologies that have significant 

implications for solving some of the most intractable problems of the world and significant 

societal challenges, such as the need for better medicines and therapies, understanding nitrogen 

fixation for making ammonia, discovering low-carbon technologies to address climate change 

and greater security around information, among others (Ball 2018; Government Office of 

Science, 2016). First, quantum technologies display superposition, where a particle can be in 

two or more states at once. Second, when two particles could be remotely connected – the 



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entanglement principle – their state needs to be described jointly as a system and not according 

to the components separately which results in correlation of between spatially separated 

particles. Hence, when a measurement of the state is made on one particle, the outcome of the 

other entangled particle is known, regardless of the distance between them. Third, there is the 

uncertainty principle, whereby it is not possible to know the state of the particle until it is 

measured, when it will collapse to one state or the other; nor can an arbitrary quantum state be 

copied exactly (the “no-cloning principle”). These properties of quantum technologies have 

significant implications for how they might offer new solutions to problems that existing 

classical computers will be unable to solve. We discuss below each of these properties and their 

implications for business model innovation. 

4.5.1. Quantum Computing and Simulation 

Quantum superposition, as a result of qubits being able to be in many states at once and 

entanglement enables complex calculations to be done much faster than classical computers23 

(Cusumano, 2018). Hence, a quantum computer can process many inputs simultaneously 

instead of going through them one at a time, like a classical computer that can only be in binary 

states of 0 or 1. For certain classes of problem, this can mean a much faster solution – solving 

complex combinatorial problems or simulating material at the atomic or molecular structure 

(Sodhi and Tayur, 2022; Ruane et al., 2022). In order to harness the benefits of quantum 

computers, the qubits need to be realised and manipulated, which is not easy, as they are not 

stable. Qubits can be realised and manipulated using several classes of technology, such as 

superconductors, silicon spins or trapped ions among others, all of which are being developed 

as possible underlying technologies for quantum computers. Recently, there has been progress 

in achieving quantum supremacy, whereby a quantum system was able to do a calculation faster 

 
23 The complex calculations use the properties of quantum entanglement and quantum superposition.  



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than a classical system (Ball, 2020). For example, Google claimed in 2019 that its quantum 

computer carried out a specific calculation that would have taken a classical supercomputer 

10,000 years to compute (Gibney, 2019).24 A group of scientists based in China were 

subsequently able to demonstrate this using beams of laser light to perform computations that 

have been shown to be mathematically impossible for normal computers (Ball, 2020). These 

are still the very early stages for comprehensive quantum computers. Nonetheless, although 

quantum computing is unlikely to replace classical computers, it might be very helpful in 

complementing them to tackle complex problems. The current state of art quantum computing 

are called noisy intermediate-scale quantum (NISQ) computers, as they experience errors for a 

particular number of operations and hence are not yet advanced enough for fault-tolerance.  

The vision is to build a fully fault tolerant quantum computer sometime in the future.  

Quantum computers will have an enormous advantage in addressing two major classes 

of problem, namely, factoring large numbers and optimisation or simulation. We discuss the 

impact of factoring in the section on communications. Many commercial activities rely on 

optimisation or simulation; for example, complex products in aeroplanes are optimised using 

computer models before any real parts are manufactured, drugs are discovered by simulating 

new molecule combinations, new materials are created for batteries, financial portfolios are 

optimised, and routing is managed for logistics operations, among others. Moreover, many of 

the solutions using artificial intelligence use ever-larger data sets, where quantum computing 

might play an increasingly critical role in the future in speeding up machine learning 

capabilities. These optimisation- and simulation-based problems would result in more dynamic 

personalisation, for example, in the delivery of goods using logistics, where there is a much 

 
24 This claim was later challenged by IBM, which claimed that its supercomputers could have done the same 
calculation in just over two days using a different classical technique (Gibney, 2019). 



128 
 

faster sense of responding to new requirements that are specific to individual preferences or in 

personalised medicine.  

4.5.2. Sensing and Imaging 

Quantum entanglement enables particles to be connected to one another, whereby the state of 

one of them provides information on the other (National Science and Technology Council, 

2016). This unique property, which has no classical equivalent, together with the very sensitive 

nature of quantum mechanical systems can be used for various imaging and sensing 

applications.  

Most cameras and imaging technology today are restricted to visible light and capturing 

images in two dimensions. However, the real world is three-dimensional and has multiple light 

spectrums going from radio waves and ultraviolet to infrared. Quantum technologies can 

leverage these multi-spectrums of light to capture images. Conventional cameras rely on 

recoding light that bounces back from an illuminated object, which requires the wavelengths 

of the illuminating object and the light captured by the camera to be the same. However, 

quantum imaging enables the illumination of an object with one type of light, such as infrared, 

but recording of the image using visible light. This is possible because the two types of light 

emitted by, say, an ultraviolet laser are entangled. Hence, the camera can build an image of an 

object based on the visible light, but it is the non-visible light that is projected onto the image 

because these two types of light are entangled. This type of quantum imaging is called ghost 

imaging and it is particularly useful for gas-emission detection in hazardous areas or for 

analysing chemical compositions.  

Quantum sensors are being developed to provide more effective and non-invasive 

health and medical imaging such as brain tumours and cancer detection using entanglement 

principles. Quantum sensing is also very valuable for surveying hazardous environments such 



129 
 

as mineshafts and also more efficient in the maintenance of infrastructure such as rail networks 

(Stray et al., 2022). Moreover, the use of quantum sensors can improve position, navigation 

and timing (PNT) systems to much-improved levels of accuracy compared to global 

positioning systems (GPS) or global navigation satellite systems (GNSS). These quantum 

sensors are particularly helpful for positioning and route navigation for autonomous cars, trains 

and other vehicles, especially in densely built environments, underwater, underground and in 

tunnels. Moreover, these PNT applications of quantum technology provides more accurate 

timing for energy management or financial transactions recording that calls for very fine-

grained time stamping. 

4.5.3 Communications 

One of the most important areas of the application of quantum technologies is in 

communications (Cacciapuoti et al., 2020; Wehner et al., 2018). The first application relates to 

security of communications and the second to the development of the quantum enabled 

Internet. Networking digital computers to create the original internet helped to transform 

business models and accelerate growth across many industries, and we believe that a quantum 

enabled internet will spur such new developments. 

 In order to ensure secure communications, cryptography is built into many 

communication systems, including commonly used web browsers and mobile phones. 

Cryptographic keys are analogous to keys in the physical world – they are used to encrypt and 

decrypt data from sender to receiver. Factoring is very important because it is behind the most 

common form of cryptography, which is used to protect private and sensitive data. The 

encryption commonly used today relies on factoring large prime numbers, which a classical 

computer is unable to do sufficiently quickly. However, a quantum computer could easily break 

this kind of cryptography, solving large prime number factoring, which could render global 



130 
 

communications systems vulnerable to hacking. One possible solution is to use quantum key 

distribution (QKD), where it would not be possible to effectively intercept the message because 

any tampering would be detected through the principle of uncertainty. This ensures security of 

communications.   

The quantum-enabled Internet, a network connecting devices through quantum links 

together with classical ones, is often envisioned as the final stage of the quantum revolution 

(Cacciapuoti et al., 2020), which could open fundamentally new communications and 

computing capabilities such as blind quantum computing which allows fully private 

computation. The quantum-enabled Internet would need to produce entanglement on demand 

between any two users. This might involve sending photons through both fibre-optic networks 

and satellite links that can extend the reach of entanglement by relaying it from one user to 

another along intermediate points. This would require routers and repeaters to transport 

quantum information to enable communication between distant quantum computers – a 

phenomenon called quantum teleportation. 

Overcoming the class of problems outlined above by leveraging the properties of 

quantum technologies in the case of computers, sensing and imaging and communications 

could create new customer value propositions. Making such customer value propositions 

valuable to society calls for new means of organising the value creation, value capture and 

value network, and hence the development of new business models. Firms in some industries, 

such as financial services and healthcare, are already beginning to experiment with quantum 

technologies to solve problems that existing classical computers are unable to address 

effectively. The development of new business models to fully benefit from an emerging digital 

technology, such as quantum technologies, will require new cognitive models and leadership 

from both start-ups and established firms. 



131 
 

4.6 Conclusion 

Organisations adopt different approaches to their digital transformation journeys (Hao, Hicks, 

Popper, and Velu, 2020). For example, in the financial services industry, with a vibrant fintech 

market and with start-ups disrupting the established ways of banking, some banks, such as 

Barclays and BBVA, have taken venture capital and incubation approaches to observe 

promising start-ups and drive innovation from an outside-in perspective. In the healthcare 

sector, health service providers have been trying to consolidate client data at each point of the 

life cycle and health journey to enable digital technologies to provide a holistic service and 

enable new business models. In other sectors, a performance-target-driven approach has been 

adopted. For example, a target of achieving 80 per cent deployability of aircrafts, which is often 

achieved by commercial airlines, enabled the military service to implement digital 

transformation by adopting more data-driven analytical approaches for aircraft utilisation and 

maintenance.  

Studies on digital transformation show that it is important to maintain customer-

centricity and to keep the transformation journey agile by building cross-functional teams, 

working with external partners and ensuring the development of data proficiency among staff 

(Hao, Hicks, Popper, and Velu, 2020). Another area that has been emphasised as important in 

enabling digital transformation is the notion of the digital mindset. The digital mindset relates 

to employees having the perception that digital technologies are a strategic pillar of the 

organisation, and hence the firm having structures and processes in place for knowledge 

sharing, experimentation, continuous improvement, innovation and flexibility (Solberg et al., 

2020). Studies show that there could be two major considerations in shaping the digital mindset 

(Solberg et al., 2020). The first relates to individual personal resources, where individuals see 

themselves as having either a fixed or a growth mindset. A fixed mindset relates to individuals 

who believe that their competencies are relatively fixed and who tend less towards embracing 



132 
 

new opportunities to learn and grow. A growth mindset relates to individuals who believe that 

intelligence and ability can grow and hence look for ways to learn and grow. The adoption of 

digital technologies provides opportunities to experiment, learn and grow and might therefore 

be conducive to the growth mindset.  

The second consideration relates to situational resources and whether people believe 

that resources are finite or expandable. On the one hand, when resources are finite, gains for 

one party correspond to losses for others. On the other hand, when resources are expandable, 

gains are possible for all parties. Therefore, it is important for management to understand the 

digital mindset of employees across these two dimensions when proposing digital 

transformation projects in order to position the opportunities and address the challenges 

appropriately. For example, when the Royal Bank of Scotland (RBS), a major British bank, 

was adopting an advanced data analytics system that could take over the core duties of financial 

advisors (primarily to sell ad hoc financial products), the bank created a new position of 

“journey manager” for advisors to take up a new format of customer service. The role entailed 

facilitating customers’ journeys through their major financial moments with the help of data 

analytics (Solberg et al., 2020). This approach enabled the change to be accepted and the digital 

transformation to be implemented more efficiently. 

The emergence of digital technologies also creates a challenge for firms designing 

business models that does not provide firms with an unfair advantage over their competitors.  

Digital technologies could result in unfair practices. For example, there is a practice known as 

the “last look” in foreign exchange (FX) markets (Anderson 2005). This is where banks have 

the option to pull prices that they have offered on an electronic trading platform in order to 

protect them against toxic trade, with faster electronic trading venues being able to trade 

milliseconds faster because of the latent advantage, to the detriment of the banks. However, it 

has been known for banks to use this ‘“last look” facility to pull a trade even when the trade is 



133 
 

less profitable as a result of regular market price movements, to the detriment of customers. 

Such a practice could become prevalent in other fast-moving markets that are using ever-more 

sophisticated artificial intelligence and machine learning algorithms. These practices could 

result in business model designs that embed unfair advantage for certain firms over others and 

hence threaten the integrity of the marketplace.  

There are several areas in the field of digital technologies and business model 

innovation that require further study, covering the identification of opportunities, phases of 

digital transformation and measuring the success of the transformation. First, what processes 

do firms have in place to identify digital transformation opportunities? We have discussed 

various ways in which firms seem to identify digital transformation opportunities. The question 

of whether or not there are certain ways of organising to identify new digital transformation 

opportunities that work under certain conditions compared to others requires further 

investigation. Second, do firms need to follow a phased approach to digitisation, and then 

digitalisation, followed by digital transformation? When does such a phased approach become 

effective and what should firms do to ensure that they are able to migrate seamlessly from one 

phase to the next? Third, how should firms measure the success of their digital transformation 

efforts? Whether or not there are particular metrics that are dependent on the type of digital 

transformation is an area that could be further explored as part of a research study.  

This chapter has provided an overview of the opportunities and challenges of digital 

technology adoption and business model innovation and proposed some outstanding research 

issues on this topic.  

 

 

 



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CHAPTER 5: DIGITAL PLATFORMS AND ECOSYSTEMS 

 

  



141 
 

CHAPTER 5: DIGITAL PLATFORMS AND ECOSYSTEMS 

 

It is by logic that we prove, but by intuition that we discover.  

 (Poincairé) 

 

5. Introduction 

IBM’s System 360 was seen as the first platform-based business model in the computer 

industry, whereby a bundle of standard components enabled users, buyers, developers or sellers 

to coordinate their efforts, providing IBM with a dominant position in the mainframe segment 

from the mid-1960s onwards (Bresnahan and Greenstein, 1999). More recently, there has been 

a proliferation of platform business models such as Amazon, Uber, Apple iOS, Google Android 

and Airbnb in the consumer market, as well as Siemens MindSphere and GE Predix in the 

business-to-business markets. Established firms such as Philips have also adopted platform-

based business models for their healthcare proposition. Philips was founded in 1891 as a 

carbon-filament lamp manufacturer (Lal and Johnson, 2019). From its foundation in lamps, 

Philips went into X-ray tubes, radios, electric razors, televisions, compact cassette players, 

video cassette players (VCR) and compact discs, among others. Philips’ expansion into this 

array of products and services was based on its technological know-how being applied in 

adjacent markets.  

However, in the early 2000s Philips realised that, in the digital world, competitive 

advantage comes from having a holistic understanding of customer needs in a particular sector 

and addressing their needs (Quelch and Rodriguez, 2015). In 2013 Philips, under the leadership 

of the CEO, Frans van Houten, decided to focus exclusively on healthtech – based on its 

strength in healthcare technology – and to exit all other sectors. However, serving customer 

needs in healthcare required the launch of a healthcare platform, meaning Philips would have 

a holistic understanding of customer needs and be able to be innovative in the provision of 



142 
 

services across the consumer health journey, from healthy living to prevention, diagnosis, 

treatment and recovery. In 2014 Philips launched its HealthSuite digital platform in order to 

support the secure collection and exchange of consumers’ health and lifestyle data. Philips 

partnered with firms such as Salesforce and Amazon Web Services (AWS) to build HealthSuite 

as an open, cloud-based platform that would enable third parties to develop applications for 

health systems, care providers and individuals to access data and provide personalised and 

empowered healthcare services. 

The platform-based business model makes it easier for parties to transact between 

themselves and enables innovations to happen more efficiently. The platform business model 

facilitates an increase in the variety of the offering and is able to customise the offering to 

specific customers. This is exemplified by the objective of achieving personalised healthcare 

for the Philips HealthSuite. However, such platform business models require an ecosystem of 

partners in order to provide variety on the supply side and a broad set of customers to engage 

on the demand side (Helfat and Raubitschek, 2018; Gawer, 2021). There are several strategic 

issues to consider in designing platform-based business models.  

The first issue is how to encourage the participation of partners and the design of 

suitable governance of such models. There need to be sufficient incentives for partner firms to 

engage, whereby they see the participation of other partners as an asset to help create and 

capture value. Second, the platform needs to attract enough customers to use the platform, 

which typically displays demand-side network effects, where customers get value from the 

participation of other customers on the platform. Third, the product and service proposition are 

not complete with digital platforms and it therefore evolves continuously. Hence, the platform 

needs to decide how open to be to enable third-party firms to provide applications that will 

increase the variety offered to customers (Hilbolling et al., 2021). The platform faces a trade-

off in that the more open it becomes, the more value it creates, but it also makes it less likely 



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to be able to capture that value. Hence, there is an optimal openness for each platform 

depending on its market and technological characteristics. Related to this is when the 

integration of the components as part of the product or service should take place: Should it be 

done by the platform firm or by the customers themselves with a more modular systems-based 

architecture? This chapter provides an overview of these strategic questions when designing 

platform-based business models. We first discuss the theory of platforms, which will provide 

the underlying conceptual framework. We then discuss a number of challenges that firms face 

when designing and scaling up such digital platforms. In the conclusion section the chapter 

provides some of the challenges with respect to the power that platform firms wield and the 

implications for business model design. 

5.1 The Types, Theory and Strategic Issues of Digital Platforms 

This section outlines the principal types, theories and strategic issues of digital platform 

business models.  

5.1.1 The Types of Digital Platform 

The term “platform” has been used in a number of different ways. First, the organisational 

perspective views a platform as organisational capabilities that enable superior performance; 

the product family perspective views a platform as a stable centre of a family of products to 

enable derivative products; the market intermediary perspective views a platform as an 

intermediary between parties to a market-based exchange; and, lastly, the platform ecosystems 

perspective views a platform as a system that supports a collection of complementary assets 

(Thomas, Autio, and Gann, 2014).  

In order to reconcile these different perspectives, it would be helpful to review the 

origins of the use of the term in management literature. One of the early scholars used the term 

“platform” in the context of manufacturing firms providing a product or service that meets the 



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core group of customer needs but which can be modified through the addition, substitution and 

removal of features (Wheelright and Clark, 1992). Some scholars have highlighted that a 

platform consists of common elements or assets across a product that enable the development 

of new products and services (Robertson and Ulrich, 1998). Gawer (2014) highlights that the 

commonality across these definitions is the systemic reuse of components across a family of 

products. Early studies of platforms were observed in manufacturing within firms, then across 

firms within supply chains, and more recently across a network of firms where there is no 

specific “buyer–supplier” relationship. The latter has often been called the “innovation 

ecosystem”, with firms bringing together assets that can be used to develop complementary 

products, technologies or services (Gawer, 2014). Innovation ecosystems enable a collection 

of assets to be leveraged jointly by member firms in order to help stimulate innovation that 

allows for economies of scope in production, whereby the cost of joint production is less than 

the cost of producing each output separately (Thomas, Autio, and Gann, 2014). 

Two primary literature streams have focused on the economics and management of 

digital platforms: the economics literature; and the design engineering literature (Gawer, 2014). 

The economics literature has primarily focused on the demand-side network externalities by 

emphasising pricing and competition. Demand-side network externalities arise from increasing 

returns from the number of users of a product or service. These consist of direct network effects, 

whereby the benefit to users of the proposition depends positively on the number of other users. 

Indirect network effects arise when the benefit to users in one group depends positively on 

another group, and vice versa. The economics literature on platforms focuses on connecting 

two or more groups though the platform and implementing an appropriate pricing strategy to 

maximise the value, hence outlining the competitive dynamics of platforms (Rochet and Tirole, 

2003). The emphasis of the economics literature stream is on the economies of scope in 

demand. This could entail studying the cross-price elasticity of demand in determining optimal 



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pricing. Cross-price elasticity captures the extent to which the demand for products on one side 

of the market increases as a result of cutting the price of the product on the other side, and vice 

versa. At the limit, it is possible to charge a price of zero or to give away the product or service 

for free because the increase in demand and corresponding profits on the other side more than 

compensate for the loss of profits from the free proposition (Parker and Van Alstyne, 2006). 

Sometimes platforms, such as Taobao, allow free sign-ups for sellers and charge for providing 

complementary services such as obtaining better ranking in its internal search engine 

(Cusumano, Gawer, and Yoffie, 2019). The design engineering literature, on the other hand, 

has focused primarily on the modularity of the platform (Baldwin and Clark, 2000). The focus 

is on the design of the platform into a stable core and a variable peripheral component to 

stimulate innovation and hence the evolution of the platform (Baldwin and Woodard, 2009). 

The emphasis of the design engineering literature stream is on economies of scope in supply 

through innovation. 

Platforms deliver products and services by bringing together two or more stakeholders, 

and they are often referred to as multi-sided (Cusumano, Gawer, and Yoffie, 2019; Yoffie and 

Cusumano 2015). For example, Facebook began in 2004 by connecting Harvard College 

students to their classmates; it then added advertisers to its platform as more students and their 

acquaintances joined. Following this, Facebook opened its platform to a third side – application 

software developers and game developers – to provide additional services. Finally, it added 

content providers such as newspapers and magazines, among others. Studies have shown that 

there are broadly two types of platform. The first are transaction platforms, which are market 

intermediaries that make it possible for people and organisations to share and transact goods 

and services between themselves (Gawer, 2021). Transaction platforms include Alibaba and 

Amazon Marketplace, which aim to improve the transaction efficiency of the market. Platforms 

capture value or monetise the platform by collecting transaction fees or charging for 



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advertisements, or both. The second is innovation platforms, which have a common 

technological building block to enable the creation of new complementary products and 

services that add functionality or access to resources, which make the platform increasingly 

valuable (Gawer, 2021). Innovation platforms include Appel iOS, Amazon Webservices and 

Microsoft Azure, which promote innovation efficiency. Firms capture value by directly selling 

or renting the product or giving the core proposition for free and earning revenue elsewhere, 

for example, through advertisements. A number of major platforms are a hybrid of both 

transaction and innovation platforms, as they combine the characteristics of market 

intermediary and innovation. Examples of such platforms include Salesforce, Apple and 

Amazon, among others. 

Innovation platforms add transaction capabilities in order to facilitate and maintain 

control over the distribution channel for complements (Cusumano, Gawer, and Yoffie, 2019). 

Transaction capabilities create value for complementors such as application developers, as they 

offer access to a wider customer base. In addition, platform firms are able to capture value from 

additional revenue from distribution. For example, Apple added the App Store about eight 

months after launching the iPhone; similarly, Google added the Google Store about a year after 

it started licensing Android. Transaction platforms tend to add innovation platforms to their 

business model design to stimulate innovation by third parties (Cusumano, Gawer, and Yoffie, 

2019). This makes it attractive to both users, as it broadens the products and services, as well 

as the platform provider, providing additional sources of revenue such as transaction fees or 

advertisement revenue. For example, Expedia, the travel marketplace, opened a set of APIs in 

order to allow third-party firms to build applications for payments, hotels, cars, flights and 

other travel-related services.  

 



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5.1.2 The Theory of Digital Platforms 

Digital platforms benefit from the liquification and reprogrammability characteristics of digital 

technology (Yoo, Henfridsson, and Lyytinen, 2010; Yoo, 2020, You et al., 2012). Liquification 

implies data homogenisation, which enables different digital and physical objects that have 

been digitised to be processed using the same machine, such as a computer. Reprogrammability 

enables the separation of logical functions from the executing physical components, thus 

allowing the creation of different kinds of data and functions that permit multiple uses. 

Moreover, platforms have a layered modular architecture (LMA) (Yoo, Henfridsson, and 

Lyytinen, 2010). The LMA is a set of loosely coupled digital resources brought together in real 

time through algorithms at, or near, the point of use across multiple layers on a common digital 

infrastructure. The LMA typically consists of four layers, as shown in Figure 1: contents, 

service, network and hardware layers. The contents layer contains data from various sources; 

the service layer contains the software used to access and interact with the data; the network 

layer refers to connectivity to the device, such as the communication protocols; and the 

hardware layer consists of the physical components of the device. 

 

 

 

 

 

 

 



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Figure 5.1: Layered Modular Architecture 

 

Source: Adapted from Yoo, Henfridsson and Lyytinen (2010) 

The combination of data homogeneity and reprogrammability enables recombinations to create 

new value propositions that are unprompted and not predictable, driven by large, varied and 

uncoordinated audiences – often called generativity (Zittrain, 2006). The ability of the platform 

to create new value propositions enables the fine segmentation of customers’ unique 

requirements. Some feature of the product or service proposition is demanded by most 

customers and needs to be combined with the core platform. However, other features that bring 

different types of value to the customer need to be tailored to each customer requirement. Such 

peripheral propositions that provide value of variety need to be combined differently for each 

customer and hence brought together later, as and when the customer needs them. For example, 

Apple’s iPhone has certain features embedded as part of the core phone offering, such as the 

email application. However, there are numerous other applications developed by third-party 

developers and available to iPhone users for free or by paid download, which enables each 

Contents Layer

Service Layer

Network Layer

Device Layer



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phone to be configured differently. The value of variety that is provided creates dynamic 

complementarity, whereby two assets complement each other with a feedback effect – they 

display economies of scope in demand. However, the increased variety could contribute to 

increased costs of complexity in the production and delivery of the proposition. Hence, the 

objective is to minimise costs by modularising the supply side and standardising as far as 

possible so that the component parts are compatible. The need to achieve compatibility could 

result in incurring higher fixed costs though standardisation via the platform. Since the process 

of generativity to create such value propositions is unpredictable and the value of variety will 

influence the costs, firms need to make two strategic decisions. The first is to decide how much 

to open the platform in order to choose what to integrate within the platform across the layers 

of the LMA: vertical integration. The second is to decide whether to integrate the peripheral 

components with the core platform: horizontal integration.  

Firms need to balance creating and capturing value through their decisions about the 

two strategic choices regarding the degree of horizontal and vertical integration. Such strategic 

alternatives will be determined by the appropriate business model design. For example, Apple 

iOS and Google Android are both operating systems for phones but based on very different 

platform-based business models. Apple iOS is reliant predominantly on the sales of iPhones, 

which is in contrast to Google Android phones, with Google dependent predominantly on 

advertising revenue. On the one hand, Apple has a relatively closed architecture with controlled 

development of applications; it does integrate some hardware and services to the iPhone, such 

as Apple Music. On the other hand, Google Android uses open-source architecture with less 

controlled application development; Google does integrate some hardware and services to the 

Android-based phones, such as Gmail and Google Chrome. As of April 2021, Android users 

were able to choose from over 3.1 million applications from the Google Play store, while Apple 



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users could choose from around 2.1 million applications for Apple iOS on the Apple Store 

(Statista Research, 2021).  

In April 2021 Apple removed automatic consent from users of iPhones with iOS 14.5 

to provide access to personal information such as location, what other apps are used, the timing 

of logging into an app, an encrypted version of email addresses, phone numbers and a unique 

number that identifies iPhones for advertisers: the IDFA (identifier for advertisers) (Financial 

Times, 2021). Such information is critical for advertisers to be able to provide personalised 

advertisements and generate revenue. The logic is that Apple charges 15–30 per cent 

commission on all application purchases and subscriptions through its App Store. Hence, Apple 

is banking on apps turning to charging customers higher fees, as they will lose some of the 

revenue from targeted advertising. Google, on the other hand, decided to stop using IDFA 

altogether. Although it is disadvantageous to Google to lose access to data from other apps, it 

already has a large amount of data from its own suite of apps that it can rely upon. For example, 

when phone owners use Google Search, Maps, Chrome, Gmail or YouTube, Google can still 

use that data to build advertising profiles. These examples show how business models need to 

be carefully designed, as they influence the degree of vertical and horizontal integration, which 

determines the value-creation and value-capture opportunities of the platform. 

The degree of openness across the vertical and horizontal activities is also relevant in 

the context of business-to-business platforms. We compare and contrast the GE Predix and 

Siemens MindSphere platforms (Immelt, 2017; IMD, 2019, Case Study no: IMD-7-2011). 

General Electric (GE) launched Predix as an ingestion and processing platform for industrial 

operations data; it was developed to provide a standardised way for firms to utilise the 

information coming from their sensor-equipped industrial machinery. Predix focused initially 

on a pre-packaged software as a service (SaaS) solution; it was an integrated solution and less 

developer-friendly. Predix supported many of the vertical businesses of GE, such as aerospace, 



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power and renewable energy, among others. GE initially built its own cloud data centre, which 

resulted in low take-up because clients were reluctant to have their data on GE servers. For this 

reason, GE later decided to use Amazon AWS and Microsoft Azure. GE’s initial strategy was 

to target Predix at organisations that were deeply invested in GE products and services. The 

sales compensation strategy was very different, which created tensions between the industrial 

vertical sales teams that sold machines and the Predix sales teams that sold intangible digital 

offerings.  

Siemens managed to overcome some of these challenges in launching the MindSphere 

Internet of Things Industrial Platform, which followed an open architecture model, whereby 

third parties can bring variety by developing applications – Siemens bought Mendix, a low-

code software platform company that provides tools to build, test, deploy and iterate 

applications. MindSphere was geared not only towards organisations invested in Siemens 

products and services but also others. Customers own their data, develop their own apps and 

do not have to have Siemens machines. Hence, the MindSphere platform was much more open, 

both vertically and horizontally, than the GE Predix platform, at least initially. This gave 

MindSphere a more successful start compared to the challenges in scaling up faced by GE’s 

Predix. 

Gawer (2021) developed these notions of the boundary of the platform further by 

examining three interrelated choices. The first relates to the platform scope in terms of what is 

owned and performed in-house. In the digital economy, assets can be enabled without 

necessarily owning them because of digital connectivity. The second relates to the platform 

sides in terms of which distinct group of stakeholders have access to the platform. The third 

choice relates to digital interfaces, namely, the degree of openness and flow of information 

between different sides of the platform. Studies have argued that platforms need to balance 

minimising transaction costs, on the one hand, and enabling generativity, on the other. The 



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boundary decisions across these three elements may vary depending on whether it is a 

transaction platform or an innovation platform and also whether the platform is in a launch or 

a maturity phase. For example, a transaction platform might be narrow in scope in the launch 

stage and only have a few sides, while being fairly open to enable increasing transaction and 

monitoring. However, as the platform matures, it might broaden its scope to exploit the 

asymmetric data flows between parties and add sides, but it might close its interfaces to prevent 

competitors from accessing data. Innovation platforms might start with a broad scope and have 

open interfaces with a few sides. When the innovation platform matures, it might broaden 

further as it incorporates complements into its core proposition, be more selective about adding 

sides and start to close its interfaces to prevent competitors from accessing data. 

5.1.3 Ecosystem Platform Governance 

A digital platform often requires an ecosystem of firms to create and capture value. Jacobides 

et al. (2018) argued that ecosystems are a different form of governance compared to markets 

and hierarchically managed organisations such as firms. Platform ecosystems are seen as 

“semi-regulated marketplaces” that foster interdependence between platform sponsors and 

their complementors to make it valuable to consumers (Wareham, Fox, and Giner, 2014). 

Ecosystems help to coordinate interrelated organisations that display autonomy. Autonomous 

organisations arise from the existence of thin crossing points, where transactions costs are 

minimised by having a boundary between tasks (Baldwin, 2007); these boundaries create the 

modular architecture of the ecosystem. Some firms have been able to rearchitect their 

conventional business to become more modular. For example, Intel took the lead in investing 

in a new peripheral component interconnect (PCI) architecture to be able to better connect the 

main subsystems and the Universal Serial Bus (USB) standard, which enabled innovation to 

connected devices such as microphones, keyboards, printers and cameras, among others. This, 



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in turn, increased the value of Intel’s microprocessors, as their performance doubled over time 

(Cusumano and Gawer, 2002).  

Modular architecture needs to display complementarity that is non-generic and where 

the complements are either unique or have the property of supermodularity.25 The combination 

of modularity and non-generic complementarity gives rise to the emergence of ecosystems. In 

the context of platforms, there are benefits to group-level coordination of production and joint 

consumption of the complements, as it results in higher utility. Hence, ecosystem members 

retain residual claims over their assets and no one party can set all of the terms of operations. 

Therefore, ecosystems need to be both de jure and de facto, whereby some of the decision-

making needs to be distributed (Jacobides et al., 2018).26  

The question naturally arises about the optimal governance structure, and hence the 

degree of centralisation of the decision-making. On the one hand, fully centralised governance 

can be beneficial when making decisions, but it might not take into account the perspectives of 

the different ecosystem members. On the other hand, a fully decentralised model reduces the 

likelihood of collective action and slows down decision-making, but it might allow the benefits 

of federated information to be brought together. Chen et al. (2021) demonstrated that the value 

of the platform is maximised when there is semi-decentralised governance, whereby members 

are given freedom and rights to participate in the platform while having some key members 

sponsor and shape the platform governance.  

The acquisition, sharing and utilisation of knowledge is key to stimulating innovation 

within the platform ecosystem. The role of the lead firm in creating the governance mechanism 

 
25 Unique complementarity is where A needs B, and vice versa, to work effectively, where A and B are products, 
assets or activities. Supermodular complementarity is where A makes B more valuable, and vice versa. Both 
unique and supermodular complementarities can be applied to production and consumption. 
26 De facto means practices that exist even though they are not officially recognised by laws or rules, and de jure 
means recognised by the law or rules. 



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for platforms is key to an efficient and effective knowledge-management system. By making 

an analogy of the platform ecosystem as a team (Gebert, Boerner, and Kearney, 2010), Velu 

(2015) showed that the use of open and closed action strategies to foster innovation highlights 

three salient forms of tension that need to be managed in ecosystem governance (Wareham, 

Fox, and Giner, 2014). The three tensions are autonomy–control, dissent–consent and 

uncertainty–certainty. In the case of autonomy–control, autonomy provides decentralisation 

and empowerment in order to expand the range of possibilities, which – when combined with 

the need to curtail freedom based on time and budget constraints, centralised control and 

frequent feedback – provides the right balance in terms of knowledge acquisition. In the case 

of dissent–consent open communication, debate and disagreement necessitate a variety of 

views, which – when combined with promoting informal communication, collectivist culture 

and team homogenising in order to enhance consensus potential – provides the right balance in 

terms of knowledge sharing. In the case of the uncertainty–certainty tension, fostering 

knowledge exchange with external entities generates new knowledge and might create 

uncertainty, which – when combined with promoting internal team communication and 

utilising existing knowledge – consolidates new and existing knowledge and promotes 

certainty, hence providing the right balance in terms of knowledge utilisation. In addition, 

scholars have emphasised the importance of integrative capabilities among lead firms in a 

platform ecosystem (Helfat and Raubitscheck, 2018). Integrative capability refers to the 

capability for effective communication and the coordination of activities, knowledge and 

objectives of firms within the ecosystem in order to achieve alignment across the 

complementary assets and enhance innovation.  

The conventional wisdom is that firms need to own physical assets in order to capture 

value. However, in the digital economy such conventional wisdom needs to be enhanced to 

incorporate the notion of orchestrating external assets to help create and capture value (Hagiu 



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and Wright, 2018; Parker, Van Alstyne, and Choudary, 2016). On the one hand, we have seen 

value being created by delinking assets fully, such as Airbnb and Uber, in sharing-economy 

business models. On the other hand, firms can orchestrate the right combination of 

complementary assets within the ecosystem to create and capture value. Such orchestration of 

the ecosystem implies that platform business models are likely to not only disintermediate or 

eliminate middlemen, or intermediate layers, but also to reintermediate with new middlemen. 

For example, in the travel business, TripAdvisor has created a new intermediation role by 

enabling certification of the quality of product and service providers.  

Orchestrating external assets within an ecosystem would naturally result in the tension 

of when and how to provide products and services in such a way as to encourage partners to 

join the ecosystem while enhancing the value of the core platform. When Taobao – the Chinese 

online marketplace – started, it wanted to provide all products and services (Zeng, 2015). As a 

result of the company’s rapid growth, many services were provided. However, Taobao opened 

itself up to an “ecosystem” mindset because of its inability to provide all of the services itself. 

However, the ecosystem mindset took time to embed, as there was still a desire by employees 

to be in control. For example, Taobao had introduced a standard software for store design, 

which not only could not serve the variety of sellers’ requirements but also cannibalised the 

business for the store-design service providers. Hence, Taobao decided to provide a simple 

basic module for free and left the premium version to be provided by partner firms.  

Governance of platforms becomes challenging when the platform competitors are also 

complementors. There are occasions when the application or service becomes mainstream and 

hence the firm embeds it within the core offering (Cusumano, Gawer, and Yoffie, 2019). For 

example, Google Maps was displayed prominently on the first Apple iPhones. However, by 

2012, Apple viewed Google as a competitor and therefore developed a competing product, 

Apple Maps, which was preloaded on iPhones instead of Google Maps, which are available 



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separately via Apple’s App Store. Platforms also try to prevent multi-homing among users, as 

this makes it difficult to create and capture value. Multi-homing occurs when users or service 

providers use multiple platforms for similar types of interaction. For example, passengers and 

drivers use both Uber and Lyft. Apple avoided multi-homing by excluding Adobe Flash Player 

from its iPhone operating system. Apple’s claim was that Flash was an inferior option to similar 

tools provided by Apple; however, the principal reason could be because Flash developer tools 

would allow content and program porting from Apple iOS to Google Android. Such portability 

between platforms would have enabled multi-homing and hence made iPhone less distinct 

(Parker, Van Alstyne, and Choudary, 2016).  

Firms also tend to use platform envelopment as a strategy to overcome competitive 

threats posed by adjacent platforms providing new features that might enable multi-homing. 

Platform envelopment is the strategy of one platform absorbing the functions and user base of 

another adjacent platform. For example, in 1995 RealNetworks invented the streaming audio 

product, Real Audio. Microsoft wanted to capture this market but was left behind by the initial 

success of Real Audio. Most of the users of the Real Audio streaming service were probably 

also users of the MS Windows operating system provided by Microsoft. Hence, Microsoft 

decided to compete with RealNetworks by developing its own audio streaming application and 

embedding it within Windows, which then enveloped the platform created by Real Audio, 

although the latter’s software had superior performance (Parker, Van Alstyne, and Choudary, 

2016).  

5.2. Opportunities and Challenges in Transitioning to Digital Platforms 

Traditional firms in value chains have scaled in two ways. The first is to integrate vertically by 

owning a larger proportion of the value creation and delivery chain of activities. The second is 

to integrate horizontally by expanding the scope of products and services produced and 



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distributed. Platforms provide a new means by which traditional firms can integrate vertically 

and horizontally: Philips developing a healthcare platform; and GE and Siemens connecting 

their machines to the Internet of Things to create industrial platforms. Nike is continuing to 

build fitness-based application platforms that connect to its shoes and sportswear. However, 

what are the challenges for traditional firms in developing such platform-based business 

models? Let us examine digital platform business model adoption across various industries to 

highlight some of the key issues. 

Volvo, the leading Swedish car company, made connected cars a strategic focus area 

in 2010 (Svahn, Mathiassen, and Lindgren, 2017). Volvo outlined a vision that would “give 

life” to cars beyond the time of production. The idea is to have an enhanced customer 

experience while opening new revenue streams for the firm. This initiative involved creating a 

platform business model that could provide additional connectivity and services to the car. 

Volvo created a transient initiative, the Connectivity Hub, as a forum for taking forward the 

Volvo Connected cars initiative. Volvo faced four competing concerns in adopting the digital 

platform business model (Svahn, Mathiassen, and Lindgren, 2017). The first involved 

developing the appropriate innovation capability without jeopardising existing product 

innovation practices. Volvo Cars was used to selecting the technology and functionality early 

for its next generation of products. However, the features of the connected car required ongoing 

interplay between the different stakeholders, such as the auto-makers, end-users, developers 

and public authorities. This required Volvo to develop skills and to be comfortable with delayed 

decision-making, which is a new type of capability of the firm. The second concern was related 

to the innovation focus between product and process innovation. The connected car initiative 

requires Volvo to work with its ecosystem of partners to guide the emergence of new designs 

and features. Hence, the focus shifts from product to process innovation, which is a new 

capability for Volvo Cars.  



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Volvo’s third concern relates to the innovation collaboration model, which requires the 

balancing of internal and external collaboration. Volvo increasingly recognised that the 

connected car, unlike the traditional car, is not complete when it leaves the plant and will never 

be complete until it is taken in for scrapping. Hence, the capability of Volvo was predominantly 

developing new cars with its internal capabilities rather than the aftermarket, which requires 

collaboration with external partners. This required Volvo to reassign responsibility for business 

functions such as information technology (IT); the IT department was traditionally seen as a 

support function without product responsibility. However, to keep pace with the non-linear 

cloud-based innovation cycle, the IT department was given a new responsibility for end-user 

functions. Fourth, Volvo needed to consider innovation governance when dealing with partners 

that were not suppliers in the traditional sense of being contracted to deliver to a specified 

quality, time and price. Many of the new ecosystem partners for the in-car applications such as 

Spotify or TuneIn did not consider Volvo to be a customer, as their revenue was generated by 

selling to the end-user directly or to advertisers. Hence, Volvo needed to balance traditional 

cost control and requirement validation in a supplier contract with the need to incentivise 

partners to stimulate innovation.  

LEGO, the Danish-based toy production company, shifted its strategy in 2008 from 

stabilising the organisation, after some challenging years, to focusing on growth under the 

leadership of the CEO, Jorgen Vig Knudstorp. As part of this growth strategy, LEGO 

emphasised the need to focus on digitalisation by purposefully evolving its business model to 

integrate digital into everything that it does. LEGO was looking to build on its digital platform 

to embrace digitalisation more holistically across the organisation. It used three lenses to 

leverage digitalisation: products, marketing, and enterprise (El Sawy et al., 2016). First, the 

product lens centred around product innovation and the product ecosystem. LEGO had already 

built a robotics platform, Mindstorms, in 1998 in order to combine the digital and physical 



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experience. It embraced a more open architecture for its Mindstorms platform after its 

proprietary operating system was hacked by LEGO fans. The company then launched 

numerous digital platforms to strengthen its connection to large user communities. These 

include, among others, LEGO Dimensions, a video game for popular consoles such as Sony 

PlayStation, Nintendo Wii and Microsoft Xbox, combining the digital and physical by enabling 

the player to have LEGO figures and a toy pad that can be played within the game itself. LEGO 

Club and My LEGO Networks allow children to share LEGO creations and to be creative. 

Second, LEGO shifted its marketing to become a pull activity to engage and interact with 

customer communities rather than a push activity to deliver product information. Third, it 

extended its IT skills and architecture in order to build its engagement platform to complement 

its strength in enterprise platforms.  

Traditional enterprise platforms such as ERP and the supply chain management 

integration paradigm focus on transaction recording and reporting. However, the increased 

intensive interactive digital connectivity to the outside required integration between outside 

and within the enterprise; for this reason, LEGO built the engagement platform capability. This 

requires the IT team to be solution-takers, partners and integrators though a joint collaboration 

model with the business units rather than the traditional “plan–build–run” requirement-focused 

approach of the systems development model. This also required staff to have a higher digital 

quotient, with appropriate digital skills and training provided by LEGO. 

One of the major challenges for incumbent firms is to develop a potentially competing 

digital platform while being involved with an existing platform ecosystem. Cisco, the 

multinational technology firm based in the US, faced such a challenge (Khanagha et al., 2022). 

Cisco develops, manufactures and sells networking hardware, software and other related 

telecommunications equipment. Cisco was part of a cloud platform ecosystem based on 

centralised computing architecture using the cloud; it provided complementary products and 



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services to the cloud platform ecosystem. The rapid emergence of the “Internet of Things” 

created the demand for decentralised data processing closer to machines or devices where the 

sensors are embedded. Hardware companies spotted an opportunity to lead this fundamental 

shift in the computing paradigm and to provide a range of services based on edge computing 

architecture. Cisco leveraged this opportunity to create a decentralised technology platform, 

where data is managed near the physical devices but between the so-called edge computing 

and the cloud. Cisco called this fog computing in 2014; fog is a viable complementor to cloud 

computing, while also being a potential competitor. The firm had to balance between 

positioning the fog platform as a symbiotic proposition to the cloud computing platform in 

order to attract the right type of partner in the early stages. Moreover, this approach enabled 

Cisco to neutralise resistance by powerful players in the existing platform. It then switched to 

positioning the fog platform in partial competition to the cloud computing platform once it had 

gathered sufficient momentum. In the initial stage Cisco combined appropriate symbolic 

action, such as framing fog computing as a complement to cloud computing, by developing 

exclusivity. In the subsequent stage Cisco started to relinquish exclusivity by positioning the 

fog platform in competition to cloud computing by fostering its own compatibility standards 

and forming appropriate partners to do so.   

Digital platforms often require coopetition, whereby firms compete and cooperate at 

the same time to create and capture value. Customer adoption dynamics in network markets 

will influence how and when firms engage in coopetition (Brandenburger and Nalebuff, 1996; 

Velu, 2016). Demand-side network effects could affect incumbent firms differently as a result 

of the effect of their installed base of customers. This is because the resource base of the 

incumbent firms diminishes as customers dis-adopt an existing product or service proposition 

in order to adopt a new proposition provided by another firm, such as a new entrant. The 

diminishing customer base of the incumbent firms might provide the incentive for them to 



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cooperate with their competitors. This cooperation with competitors enables incumbent firms 

to defend and regain market share in order to innovate their business models as a means to 

retain their leadership position in the industry. For example, in the US corporate bond trading 

market, it was observed that, with trading volumes exceeding US$400 billion per day in the 

early 2000s, incumbent firms chose to engage in coopetition in light of the competitive threat 

and adopted a defensive or offensive strategy when adopting electronic trading platforms to 

trade corporate bonds (Velu, 2016).  

The less dominant firms engaged in coopetition by forming a consortium to innovate 

their platform business model in an evolutionary manner before the dominant firms; this was a 

defensive strategy to protect their existing business model. The evolutionary platform business 

model took the form of replicating the existing telephone-based trading systems but merely 

migrated the processes to an Internet-based interface, whereby the banks continue to act as 

market-making intermediaries. On the other hand, the dominant firms engaged in coopetition 

by forming a separate consortium to innovate their platform business model in a revolutionary 

manner after the less dominant firms, as an offensive strategy, as they saw their market share 

eroding fast following the move by the less dominant firms. The revolutionary platform 

business model took the form of radically altering the existing business model by eliminating 

the role of the banks as market-making intermediaries and enabled direct trading by buyers and 

sellers, with the banks acting as credit guarantors.  

Amazon also adopted a coopetition-based platform business model (Velu, 2018), 

launching Amazon Marketplace in 2001 in response to a loss in investor confidence that 

Amazon would be suitable with its online business model; this was reflected in its share price 

declining by 80 per cent by the end of 2000. Amazon Marketplace enabled the firm to offset 

operating expenses while increasing sales. Competitors could list and sell their books and other 

products alongside Amazon’s own propositions by leveraging Amazon’s e-commerce platform 



162 
 

and customer base. This platform business model enabled the firm to implement its “single 

store strategy”, whereby it becomes the place of choice for customers to buy either new or used 

books from Amazon or its competitors by comparing them on a single page. In addition, 

Amazon provided automated tools to third-party retailers to migrate their catalogues of new 

and used books to the Amazon web page. The economic logic was the marginal cost of enabling 

competitors to list their products on Amazon.com, which was relatively small compared to the 

commissions and subscription fees earned. In addition, Amazon needed to hold less inventory 

of its own. In summary, Amazon built a platform-based business model by linking competitors’ 

activities with its own in order to leverage the combined resources and provide a compelling 

customer value proposition. 

5.3. Sharing-Economy Business Models 

The emergence of Uber in transportation and Airbnb in the accommodation rental market have 

brought to the fore the notion of sharing-economy business models. Sharing is the act and 

process of distributing what is ours to others, and vice versa (Belk, 2014). A sharing economy 

is defined as the socio-economic ecosystem that commonly uses information technology to 

connect different stakeholders to share products and services in order to facilitate collaborative 

consumption (Belk, 2014; Laamanen et al., 2018). Sharing-economy models could be business 

to consumer (B2C), such as Zipcar, consumer to consumer (C2C), such as BlaBlaCar, or 

business to business (B2B), such as Yard Club, owned by Caterpillar, which enables equipment 

sharing among construction contractors (Chasin et al., 2018; Munoz and Cohen, 2018). The 

Internet has created new ways of sharing and also widened the access and scale of existing 

ways of sharing. An example of sharing material goods between consumers facilitated by the 

Internet is Sharehood, which was started in Melbourne by Michael Green, who knew that there 

were many washing machines between where he lived and the nearest laundromat that were 

often idle but which he could not access to do his laundry. Michael started an online sharing 



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service, whereby neighbours could list things that were available (power tools, sewing 

machines, washing machines, etc.), which others could reserve and use at no cost. This created 

not only a more efficient use of machines and other items but also a greater sense of community 

among neighbours. Moreover, studies have shown that the average car in North America and 

Western Europe is used 8 per cent of the time and the average electric drill is used for between 

6 and 13 minutes over its lifetime (Belk, 2014; Sacks, 2011).  

A number of trends are encouraging firms to consider looking at sharing-economy-

based business models (Kathan, 2016). First, Internet technology and other digital 

technologies, such as distributed ledger, enable ways to secure trust via screening people, 

feedback loops and online payment systems. For example, increased peer-based self-regulation 

and ratings systems provide a check on possible dishonest behaviour. Second is the shift in 

values, especially among the younger generation, whereby ownership of tangible goods is less 

central to their identities and they have an increased focus on intangible attributes such as 

knowledge and reputation. Moreover, the economic pressures arising from uncertainties in the 

economy make the popularity of ownership less easily attainable, making sharing a viable 

alternative. Studies have shown that sharing-economy markets are likely to expand 

consumption as a result of the more efficient allocation of unused capacity in goods and 

services (Filippas et al., 2020). For example, a study comparing utilisation rates in Los Angeles 

and Seattle show that Uber taxis are utilised over 55 per cent of the time compared to regular 

taxis, which are utilised approximately 40 per cent of the time (Cramer and Krueger, 2016).  

The rapid growth of the sharing economy has attracted scholars to examine the 

performance implications of sharing platforms (Jiang et al., 2021). Studies have shown that up 

to a quarter of sharing platforms fail fewer than three years after their launch (Chasin et al., 

2018). A configurational approach to studying the performance of business models has merit 

because of the causal complexity of the activity system within business models (Misangyi et 



164 
 

al., 2016). This is the result of three features of business models, the first being the conjunction, 

where outcomes are often the result of interdependence of multiple conditions. The second 

feature is equifinality, where there could be more than one pathway for a given outcome. And 

the third is asymmetry, where attributes found to be causally related in one configuration may 

be less so – or even reversed – in another configuration (Misangyi et al., 2016).  

Jiang et al. (2021) use a configurational approach to identify six design elements that 

are most salient in the sharing economy: (1) the degree of asset lightness, which describes the 

extent to which the products or services belong to the focal sharing platform itself; (2) the 

frequency of recurring transactions within a certain amount of time; (3) anonymity, which 

describes whether or not the actors that transact are anonymous; (4) transferability, which refers 

to the extent to which the assets being transacted or used on the platform are portable to other 

locations for use by a different set of users; (5) modularity, which refers to services provided 

by the platform that can be divided into a set of sequenced activities to be separated or 

recombined; and (6) the product category, which refers to customers’ ability to judge the 

quality of the products or services before purchasing, which might vary according to the type 

of goods, such as search goods, experience goods or credence goods. Search goods enable 

customers to search for product quality before buying (e.g. watches, mobile phones). 

Experience goods are products for which product evaluation and consumption takes place 

simultaneously (e.g. restaurants, hairdressers). Credence goods are products where evaluation 

is difficult even after consumption (e.g. management consulting services).  

The study identifies four business model configurations that result in high performance. 

The first is the product-based sharing economy (PNSE) exemplified by the platform Poshmark, 

the social commerce marketplace where individuals can curate looks for their shoppers in order 

to buy and sell used clothing, shoes and accessories. The idea is to buy, sell and share personal 

style. The high performance of Poshmark is the result of it being asset-light, high frequency 



165 
 

and having high transferability in terms of fashion goods that might ordinarily be credence 

goods in order to make them search goods. The second configuration is the rental-based sharing 

economy (RBSE) exemplified by Zipcar, the car-rental company that enables a business-to-

customer sharing network. High performance is associated with it being asset-heavy, high 

frequency, high anonymity and high modularity in terms of how the service is designed: 

becoming a member, booking, obtaining and returning the car. Third is the knowledge-based 

sharing economy (KBSE) exemplified by the Khan Academy, the free peer-to-peer education 

platform. The Khan Academy considers education to be a credence good: it makes video clips 

in digestible 5–20-minute sessions available so that students can learn at their own pace in a 

modular and interactive way rather than a rigidly timetabled format. Hence, high performance 

is associated with low frequency, low anonymity and high transferability for credence goods. 

The fourth configuration is the labour-based sharing economy (LBSE) exemplified by Fiverr, 

an online marketplace for freelance digital services such as graphic design translation and video 

production, among others. Fiverr is a streamline service model creating a demand and supply 

marketplace for these online services, similar to buying goods via Amazon. The high 

performance of Fiverr is associated with it being asset-light, high frequency, low anonymity 

and having low transferability and high modularity. 

5.4.  Conclusion 

IBM’s System 360 platform-based business changed the basis of competition in the computer 

industry from firms to ecosystems (Bresnahan and Greenstein, 1999). Since then, platform-

based business models have become prevalent across many industries and have grown to be 

very popular and topical in recent years. However, platform business models are not without 

their challenges, from both theoretical and practical points of view. From a theoretical point of 

view, one of the main challenges is the conceptualisation of an ecosystem for digital platforms. 

The literature on ecosystems can be grouped into the structure view and the co-evolution view 



166 
 

(Hou and Shi, 2020). On the one hand, the structure view emphasises the modular architecture 

of multilateral dependencies (Adner, 2017; Jacobides et al., 2018). The structure view focuses 

on facilitating value co-creation and coordination among actors in order to explain the 

uniqueness and when and why ecosystems emerge (Hou and Shi, 2020). Such a view pays 

attention to the role-based dynamics of the ecosystem. On the other hand, the co-evolution 

view emphasises the community-affiliated and interacting actors that keep an open exchange 

with the environment (Moore, 2006). The co-evolution view focuses on both the emergence 

and evolution of the ecosystem, paying attention to the actor-based dynamics of the ecosystem. 

This process of actor-based dynamics highlights the importance of lead firms developing 

integrative capabilities to enable the alignment of activities, products, resources, investments 

and objectives with partners and to facilitate internal coordination within the firm to enable 

platform evolution (Helfat and Raubitschek, 2018).   

One of the other major challenges in platform business models is the ability of platforms 

to garner massive amounts of data, and hence to create a monopoly – and often an uneven 

playing field – as a result of the benefits of increasing returns from information. We have seen 

numerous cases against the major platform businesses, such as Google, Amazon, Airbnb and 

Uber, around issues ranging from market access and data privacy to pricing and classification 

of service providers. Google processes around 90 per cent of all online searches in the US, 

which is coupled with a massive advertising business that generates a significant portion of its 

revenue (The United States Department of Justice, 2020). Moreover, Google pays Apple ad 

revenue to make Google search the default on Apple devices. The data that Google is able to 

garner from its dominant position in searches and advertisements, and creating exclusive 

agreements for its services, makes it the focus of anti-trust investigations (The United States 

Department of Justice, 2020). This dominance is also prevalent in sharing-economy business 

models. For example, in 2020 the UK Supreme Court decided to classify Uber drivers in the 



167 
 

UK as employees rather than contractors (or “gig” economy workers), contrary to the position 

taken by the firm. This means that Uber’s drivers will get certain employment benefits in the 

UK. The ability of platform business models to gain significant monopoly power through the 

design of their business models raises questions around welfare and societal issues, which 

requires further consideration, from an ethics and regulation perspective.  

Moreover, the literature so far has focused predominantly on the indirect network 

effects from the quantity of complements. However, the quality of complements is equally 

important, as generativity enables the variety of products and services to proliferate on the 

platform (Hilbolling et al., 2021). As platforms grow, changes to the platform core, the 

ecosystem elements and the idiosyncrasies of how users connect to the platform could increase 

the chances of glitches and also contribute to obsolescence (Hilbolling et al., 2021). Therefore, 

platform owners, complementors and users need to work together to maintain the quality of the 

platform as it grows. In summary, the operating model of the platform that enables scale, scope 

and learning effects needs to enhance the variety while maintaining the quality (Iansiti and 

Lakhani, 2020). 

There a number of areas on platform business models and the sharing economy that 

require further study, covering aspects of the evolution of platforms, societal and welfare 

implications and maintaining quality. First, how do platforms evolve over time? We 

highlighted the role of the focal firm in curating and providing leadership for the platform. One 

of the key open areas from a theoretical perspective is how the structural characteristics of the 

ecosystem influence its evolution, and vice versa. The second relates to the societal and welfare 

implications of platform business model design. Platform business models can gain enormous 

power through mobilisation of their ecosystem and the accumulation of data. The principles of 

designing platform business models in order to balance the benefits to society, while not over-

penalising some aspects of society, is an important area for further research. The third area that 



168 
 

requires further consideration relates to how to maintain quality as platforms scale up, which 

could result in externalities. For example, when Uber is used extensively in a major city it could 

result in large traffic jams that reduce the welfare of other residents. In addition, as noted 

earlier, the increase in volume of complementary assets on a platform could contribute to 

glitches and obsolescence. The challenge of how we internalise such externalities in order to 

build platform business models that maintain quality as they scale up calls for further research. 

This chapter has provided an overview of the opportunities and challenges of platform 

and sharing-economy business models and proposed some outstanding research issues on this 

topic.  

 

 

 

 

 

 

 

 

 

 

 

 



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CHAPTER 6: SMALL AND MEDIUM SIZED ENTERPRISES AND START-UP 
BUSINESS MODELS 

  



174 
 

CHAPTER 6: SMALL AND MEDIUM SIZED ENTERPRISES AND START-UP 
BUSINESS MODELS 

 

When the time comes in which one could, the time has passed in which one can.   

(Marie Ebner Eschenbach) 

 

6. Introduction 

Small and medium-sized enterprises (SMEs) play a key role in most national economies around 

the world by generating significant employment and value added (OECD, 2017a). SMEs 

contribute to over 70 and 45 per cent of jobs in OECD countries and emerging economies, 

respectively. In addition, they contribute to up to 50–60 and 33 per cent of GDP in OECD and 

emerging economies, respectively. Hence, improving the productivity of the SME sector could 

enhance economic growth and create jobs. However, there is ample evidence that productivity 

growth among SMEs lags behind large firms across major economies (OECD, 2017a; OECD, 

2017b; Llinas and Abad, 2020). Such productivity differences could be gleaned from the lack 

of adoption of digital technologies and opportunities to reshape business models. For instance, 

across OECD countries, enterprise resource planning (ERP) software applications to manage 

business information flows are popular among large firms, with a more than 75 per cent 

adoption rate, but less than 20 per cent by SMEs (OECD, 2017a). Despite the prevalence of 

digital technologies, SMEs face challenges in adopting these technologies as a result of the 

lack of investment in complementary assets, particularly knowledge assets and organisational 

changes such as process innovation and business models. This might be due to limited 

management and leadership capabilities, a narrow focus on specialised products and services, 

with a dependence on a small number of customers, limited opportunities for scale economies, 

constraints in terms of internal and external knowledge capabilities, and resource limitations 

such as finance (Miller et al., 2021).  



175 
 

Studies have shown that for large firms the main challenge regarding innovation is 

reducing inertia, while for SMEs the challenge is to increase cooperative capacity (see Cosenz 

and Bivona, 2021; Miller and Friesen, 1980). However, start-up firms might also face a form 

of inertia because of the influence of their founding members. For example, in biotechnology, 

where firms need to continuously come up with new drugs, the experience of a firm’s founder 

can be detrimental to performance in terms of growth, perhaps as a result of the lack of new 

knowledge (Patzelt, Knyphausen-Aufseb, and Nikol, 2008). Research also shows that 

partnering with third-party firms with complementary assets reduces the survival of new firms 

as the degree of business model innovation increases (Velu, 2015). The conjecture is that, as 

the degree of business model innovation increases, relying on partners for appropriability via 

complementary assets increases the new firm's exposure to coordination costs and asset-

specific investments, which prevents the benefits of collaboration from materialising (Bock et 

al., 2012). 

Start-up firms face enormous challenges in overcoming the liability of newness. This 

is particularly evident in science-based start-up firms in the early stages of product 

development, where the market for the product might not exist; hence, there are significant 

technological and market uncertainties to overcome (Bigdeli et al., 2016; Coombes and 

Nicholson, 2013; Lubik and Garnsey, 2016). The business model design of such science-based 

start-ups is challenging because of the long lead time between scientific development and 

technology commercialisation (Mason et al., 2019). 

This chapter provides an overview of the opportunities and challenges of business 

model innovation among SMEs and science-based start-ups. We first discuss SMEs within 

complex supply chains, followed by a discussion of some of the challenges inherent in the 

adoption of digital technologies among SMEs in order to innovate their business models. We 

then discuss the challenges of business model innovation among family-owned SMEs, 



176 
 

followed by an exploration of some of the frameworks for the development of SME business 

models. Next, we look at the challenges for science-based start-ups in designing and innovating 

their business models to enable the commercialisation of new technologies. In the conclusion 

section the chapter looks at some of the opportunities and challenges faced by SMEs and start-

ups when innovating their business models in order to enhance productivity and stimulate 

economic growth. 

6.1 Supply Chains and SMEs 

Small and medium-sized enterprises can be part of a supply chain to manufacture and deliver 

products and services to customers, as in the aerospace industry (Greenwood and Hinings, 

1993; Smith and Tranfield, 2005). Some of these supply chains are tiered, with a large firm 

often the prime contractor or the original equipment manufacturer (OEM), which outsources 

part of the manufacturing and assembly of the product to other firms, which then sub-contract 

to SMEs (Lee et al., 2020; Godsell et al., 2010). We examine below the business model 

implications of SMEs in these supply chains. 

Firms that supply customised high-volume products, such as automobiles, electronics 

and clothing, will be incentivised to push finished goods into the market in order to cover their 

high production and operating costs (Holweg and Pil, 2001). Such a made-to-stock (MTS) 

model needs to forecast demand and manufacture products, holding them in inventory ahead 

of sales. Often the MTS model results in a mismatch between the forecast demand and the 

actual sales. For example, in the automobile industry, dealers might need to give discounts to 

sell the inventory of cars in their showrooms. Customers might be persuaded to buy a pink 

Chevrolet, as a result of the discount offered by the dealer, rather than the blue one that they 

were keen to acquire. However, if the family does not like the pink Chevrolet, the car is then 

sold in the second-hand market after less than a year. The demand forecasting system in the 



177 
 

meantime has predicted the demand for pink Chevrolets; hence, more of them are made under 

the MTS model. Moreover, firms need to increase volume because of the eroding margins 

created by the discounts. Hence, the MTS model could result in an inadequate supply of the 

desired product and an oversupply of undesired variants (Holweg and Pil, 2001). The US car 

market was particularly prone to low profitability in the late 1990s and early 2000s; for the 

average 17 million vehicles sold, up to 2 million vehicles were held in inventory for between 

40 and 60 days. Such high inventory results in significant costs in terms of interest and logistics, 

among others. In order to overcome some of these challenges and meet customer requirements, 

European car manufacturers, followed by American car manufacturers, moved to a made-to-

order (MTO) model, which helped them to improve their profitability significantly. This is a 

result of the MTO model enabling process, product and volume flexibility to meet customer 

requirements.  

Dell is well known for pioneering a variant of the MTO model, the assemble-to-order 

model, to customise personal computers (Gunasekaran and Ngai, 2005). Moreover, in the retail 

clothing industry, Zara, which is owned by Inditex, has adopted a “sense and respond” model 

known as “pronto moda” or “rapid fire fulfilment”, where the aim is to turn over its inventory 

every two weeks, as opposed to the much longer lead times based on forecasting sales among 

other major retailers such as H&M (Martinez, Errasti, and Rudberg, 2015).  

Most clothes retail chains sell fashion items where stock is held for several weeks or 

months. Prices are generally set higher when the items are first brought out for sale. These 

clothing retail chains often provide discounts to clear inventory of slow-moving items when 

the season is over or coming to an end. Most clothes retailers do not have their own 

manufacturing facilities but tend to outsource manufacturing, some of which are SMEs, to help 

reduce costs. In addition, retailers hold a large inventory of items, as the design and delivery 

of stock from manufacturers involve time lags of several months. The clothes are transported 



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to retail outlets from low-cost countries, where the outsourced manufacturers are typically 

located. 

The Zara model effectively tries to come closer to mimicking the MTO model by 

reducing the time between detecting fashion trends and bringing products to market. Zara has 

fast stock rotation: it rotates its stock every two weeks, enticing customers to make frequent 

visits and purchases. It has a more vertically integrated supply chain with respect to designers 

and manufacturers of its clothing, where more of the activities are done in-house than externally 

sourced, in the case of conventional clothing retailers. Zara manufactures most of its lines in 

Europe, using fully owned or closely controlled plants. Therefore, it has higher manufacturing 

costs for equivalent products than its other retail clothing competitors. However, Zara is able 

to adjust quickly to fashion trends, reduce mark-downs and cut inventory costs, which has 

significant implications for SMEs, who are often involved in supplying material and products 

to the major retail firms in the supply chain.   

SMEs across the manufacturing continuum between MTS and MTO need to have 

different business models to serve the supply chain efficiently and effectively. The MTS system 

is based on building to forecast, while the MTO system is based on building after receiving the 

customer order.27 The customer order point (COP) is the point in the manufacturing system 

where the product is assigned to a customer order. In MTS the COP is at the finished inventory, 

while in MTO it could be earlier, at the material inventory stage (Olhager and Ostlund, 1990). 

Hence, MTS is a push system, while MTO is a pull system, with materials and production being 

pulled through the system based on customer orders (Gunasekaran and Ngai, 2005). MTS 

meets customer requirements from stock and relies on a stable production schedule with a 

 
27 There are variations to the MTO such as build-to-order (BTO), assemble-to-order (ATO) or engineer-to-order 
(ETO), which are principally based on manufacturing or assembling the product after the customer order has 
been received (Gunasekaran and Ngai, 2005). 



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relatively deterministic demand. MTO relies on supply chain flexibility to meet customised 

product requirements. The MTO system relies on tight integration of the supply chain with the 

upstream supplier of materials, midstream manufacturer and assembly of components and 

downstream distributor of finished goods. Demand management techniques such as marketing 

and promotions, as well as flexible arrangements with suppliers, are often adopted to balance 

supply and demand.  

SMEs need to design their business models to determine the scope of the firm in terms 

of the degree of vertical integration across the supply chain. In particular, firms that have access 

to key information and material flow control the bottlenecks in the supply chain, which 

determines the competitive advantage – and therefore profitability (Jacobides and Tae, 2015).  

Hence, the industry architecture and the role of SME business models could determine their 

competitive position and performance, respectively. For example, OEMs in the automotive 

sector in the late 1990s and early 2000s decided to vertically unbundle and adopt a modular 

architecture based on an analogy from the evolution of the computer sector. However, once the 

OEMs began to outsource their production to SMEs in the supply chain, they realised that the 

computer sector – where outsourcing led to vertical unbundling and the creation of modular 

open access components – is different to the automobile sector. In particular, in the automobile 

sector the components are proprietary in nature; hence, outsourcing still required a degree of 

hierarchical control in order for the OEMs to create and capture value and not lose control to 

the tier 1 supplier and SMEs that provide specialised components (Jacobides, MacDuffie, and 

Tae, 2016). Therefore, the OEMs changed course in the mid-2000s onwards to maintain the 

outsourcing but regain control of the design element. This approach was adopted to retain the 

systems integration role in order to maintain differentiation and hence guarantee the quality of 

the automobiles. This, in turn, contributes to the changes needed among the SMEs in the supply 

chain to adapt their respective business models. 



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The creation and development of complex products and systems (CoPS), such as 

aircraft carriers, battleships and nuclear power plants, often require supply chains to consist of 

both large firms and SMEs. The complexity of products can be defined by some principal 

features such as the novelty of the technology, the quantity of subsystems, the degree of 

customisation and the intensity of regulatory involvement, among others (Hobday, 1998). As 

the complexity of products increases, so does the number of feedback loops in the design and 

production process from the later to the earlier stages of production. There has been a 

continuous increase in specialisation and production artefacts and knowledge, coupled with 

advances in information and communications technology (ICT). Such developments provide 

the impetus for the continued disintegration of the value chain for product development and 

manufacturing of CoPS (Hobday et al., 2005). This results in increasing outsourcing of the 

development and manufacturing function. For example, Airbus, a major civil aircraft 

manufacturer, has increased the outsourcing of its planes from around 30 to 70 per cent over 

several years. Firms that outsource also need the capability to provide systems integration, 

which is the ability to define and combine the necessary input for a system and agree on a path 

for future development (Hobday et al., 2005).  

These trends in CoPS result in SME firms adopting a “made-to-print” (MTP) business 

model, which requires SMEs to deliver the parts to the design specification provided by the 

firm above them in the supply chain or the OEM. Studies show that SMEs might under-invest 

in intangible capital, such as human, information and organisational capital, as these are less 

measurable, and over time they become less able to innovate their products and processes and 

their business models (Said et al., 2022). This might partly explain the increasing disparity in 

the productivity of large firms and SMEs. On the one hand, vertical disintegration contributes 

to specialisation that might improve productivity; and, on the other hand, effective systems 

integration also leads to productivity improvements. SMEs need to develop dynamic 



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capabilities to reinvent their business models so as not to be caught between the specialisation 

and systems integration roles of changing technological systems. 

6.2 Industrial Digital Technologies and SMEs 

Small and medium-sized enterprises tend to digitise general administration and marketing 

functions first (Ehret and Wirtz, 2017; OECD, 2021). Therefore, the gap between SMEs and 

larger firms tends to be smaller in terms of online government interactions, social media, selling 

online and electronic invoicing. However, the gap increases when the digital technology 

becomes more sophisticated, such as data analytics, ERP, cloud computing and other 

production technologies. Government-funded technology extension programmes have 

expanded across the world to help SMEs adopt digital technologies and enable digital 

transformation (OECD, 2021; Shapira, Youtie, and Kay, 2011). These include financial and 

non-financial support in consultancy and advice, for example, the Industry 4.0 Voucher 

(Portugal), SME Digital (Denmark), Capital Investment for Revolutionising SME Productivity 

(Japan), Digital Economy Corporation (Malaysia), Robo-Lift (Sweden), Digital India (India) 

and the Manufacturing Extension Partnership28 programme (USA), among others. 

The Made Smarter Review (2017) identified poor levels of adoption of industrial digital 

technologies (IDT)29 in the UK among SMEs and under-leveraged innovation assets to help 

support start-ups and scaling up. These factors – together with the lack of effective leadership 

on a clear narrative about the opportunities of adopting IDT – hamper productivity growth in 

the UK. One of the Made Smarter Review (2017) recommendations was to set up a pilot 

 
28 The Manufacturing Extension Partnership (MEP) programme was initially established with the goal of 
transferring technology developed in federal laboratories to SMEs in the manufacturing sector. However, MEP 
changed its strategic focus in the early 1990s to respond to needs identified by SMEs, including off-the-shelf 
technologies and business advice, which includes digital transformation (Voytek, Lellock, and Schmit, 2004). 
29 The Made Smarter Review (2017) defines IDT, which includes the application of digital tools and technologies 
to the value chain of businesses involved in the production of things or which are operationally asset-intensive, 
such as power grids and wind farms. These include technologies at different levels of maturity, such as robotics, 
additive manufacturing, the Internet of Things (IoT) and artificial intelligence (AI), among others. 



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programme to help SMEs in the North West of England to adopt IDTs. The Made Smarter 

Pilot Report highlighted that, although 75 per cent of SME manufacturers in the North West 

of England had invested in new technologies in the last three years, most were larger SMEs, 

with one in eight smaller SMEs never having invested in new technologies over that period 

(Made Smarter, 2019). Moreover, most of the SMEs that have invested in new technologies 

have done so without a clear plan for implementation, resulting in disparate and disconnected 

equipment. Therefore, many of the IDT pilot programmes have focused on data and systems 

integration to ensure a more holistic view of operations and performance before adopting other 

digital technologies. The pilot report also identified that the major barriers to the adoption of 

IDTs among SMEs were insufficient capital, gaps in skills and knowledge and the need for 

guidance. 

There are four reasons for a lack of digitalisation among SMEs: (a) less need resulting 

from specific foci; (b) a lack of resources and managerial vision; (c) taking a gradual approach 

compared to larger firms; and (d) heavily relying on financial performance and therefore having 

limited resources in this area (Suppatvech et al., 2019; Gruber, 2018). SMEs tend to perform 

better in digital transformation if they allocate more resources for business model 

implementation and also engage more in strategy implementation (Bouwman et al., 2019). 

Moreover, research shows that SMEs that adopt the notion of the self-tuning model are better 

able to execute on digital innovation (Del Giudice et al., 2021). Such self-tuning organisations 

display the following: agility – the dynamic capability to integrate new processes and expertise 

using advanced technologies; adaptation – which refers to the learning curve of the enterprise 

due to change in the business model brought about by the transfer of organisational capabilities; 

and ambidexterity – which comprises exploration and exploitation in new forms of advanced 

technologies. Moreover, it is managers’ lack of perceiving Industry 4.0 drivers, and not their 

perceptions of high Industry 4.0 barriers, that obstructs SMEs’ development of digital readiness 



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and their application of digital technologies (Stentoft et al., 2021). The study shows that among 

SMEs the main drivers of digital technology adoption are cost reduction and speed to market, 

while the main barriers are a lack of knowledge, as well as operational applications. The case 

studies based on four Danish SMEs show that the combination of digital technologies such as 

robotics with technologies that provide better systems integration between the shopfloor and 

business intelligence enables cost reduction and improves time to market.  

The internationalisation of SMEs has been shown to affect business models and hence 

performance, as these firms need to compete for business in a more globalised setting with 

increased competition (Rissanen et al., 2020). Moreover, internationalisation could also act as 

an impetus for the adoption of digital technologies. For example, Li et al. (2018) showed how 

SME firms based in China, with little experience in international e-commerce, were able to do 

business internationally. This was because Alibaba, the major Chinese e-commerce platform, 

provided mentoring, facilitating and rule-making to help SMEs build managerial and 

organisational capabilities to facilitate digital transformation, thereby enabling business to be 

conducted on their platform for international e-commerce. 

6.3 Family Firms 

Family firms account for 85 per cent of firms worldwide (Chirico et al., 2011). For example, 

in the US it is estimated that family firms employ more than 80 per cent of the workforce, 

producing more than 50 per cent of the output and contributing to a significant level of 

innovation (Chirico et al., 2011). Family firms differ in their approach to product and process 

innovation, and therefore business model innovation, compared to non-family firms, because 

of the resources and non-financial goals of family firms (Soluk et al., 2021). The difference 

between family and non-family firms results from the strong attachment between the family 

and the business, distinct knowledge management capabilities and the concentration of the 

family’s wealth in the business, which can lead to risk aversion (Chirico et al., 2011). Family 



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involvement often means business decisions can be overlaid with complex emotional 

relationships such as sibling rivalry or discord among family members (Jones and Girodano, 

2021).  

For example, ECessori is an electronic trading company that buys and sells goods on 

an e-commerce platform, which was started by two brothers (Jones and Girodano, 2021). The 

brothers started the business based on their activities selling sweets and pens to schoolmates, 

which eventually grew to be a successful e-commerce trading business that bought and sold 

goods from China to the UK and other European markets. The business model was initially 

based on trading in its own avenue but it expanded to include Amazon Marketplace. One of 

the reasons for scaling up their hobby business was that the brothers wanted to generate enough 

revenue for their father – who normally travelled for work – to work from home. The business 

grew from selling various third-party accessories, such as smartphone accessories and memory 

cards, until a new business model was launched by one of the brothers and the business became 

very successful, selling own-brand e-cigarettes, Ez Cig, via Amazon Marketplace. However, 

Amazon then decided to ban the sale of these e-cigarettes, which created significant tension 

among the brothers, with the one who had started Ez Cig wanting to continue this line of 

business and the other brother having misgivings. The sibling rivalry had to be mediated by the 

boys’ parents, who were intimately involved with the family business, in order to ensure its 

continued growth and success. 

Family ownership has been shown to positively influence the ability to innovate 

business models using digital technologies (Soluk et al., 2021). Moreover, this positive 

relationship is mediated by dynamic capabilities such as knowledge exploitation, risk 

management and marketing capabilities. Family ownership might result in building specific 

capabilities in how knowledge is shared because of strong family ties. However, there is a 

management risk because of the stake of family members and their marketing capabilities that 



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could be prone to being selective in customer partnerships to protect the family reputation. 

Family involvement can be both a favourable influence and a liability if there is a tendency to 

avoid risk or delay change. Hence, the involvement of families across generations in a 

participatory manner has been shown to positively influence family firms’ performance 

(Chirico et al., 2011).   

Family businesses often face two opposing forces: the first drives them to grow and 

expand beyond traditional markets; and the second encourages stability and the development 

of low-risk avenues in traditional markets (Casillas et al., 2010). Hence, internationalisation of 

the business model of family firms is one way to seek growth, which requires risk-taking. 

Studies have shown that family businesses that are able to develop the know-how, desire and 

commitment for internationalisation are able to demonstrate profitable growth. This is because 

exposure to global competition enables these firms to innovate their business models and hence 

introduce competitive products at low cost (Calia et al., 2007).  

For example, a Brazilian metal company, Metallurgy, was a leading provider of metallic 

chrome powder for the Brazilian market using a process called aluminothermy (Calia et al., 

2007). This was a successful business between its founding in 1978 and 1986, serving the 

growing maritime platform of the Brazilian oil company when the Brazilian market was 

protected from international competition. However, after 1986 Metallurgy faced stiff 

international competition and a period of challenging financial conditions. The founder passed 

the baton to the second generation, consisting of his son and daughter, respectively. The firm 

decided to build a new product line by relying on recycled iron and aluminium alloys as raw 

materials and a new atomisation process to obtain metal powder. This desire to internationalise 

required the acquisition of know-how by partnering with a local institute for technological 

research in order to do the requisite R&D together. The innovation was required based on 

technological development, procurement via a joint venture with an aluminium recycling 



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company and also partnership for operational development of the atomisation technology. The 

combination of these capabilities and transformation of the business model enabled Metallurgy 

to thrive and compete in a global market.  

Family ownership and management have been shown to have a negative impact on 

innovation input but a positive effect on innovation output (Matzler et al., 2014). Innovation 

input relates to a firm’s investment in research and development. Innovation output relates to 

a firm’s different strategic considerations, activities and capabilities, including intellectual 

property. On the one hand, based on the principles of agency theory, there is a tendency for 

family firms to be more risk-averse than non-family firms, as there is often less separation 

between principal and agent. Since the family’s wealth is at stake, in terms of investment in 

risky innovation-related input, family firms tend to display risk aversion to protect their 

personal investment value. On the other hand, human and relational capital are rich among 

family members and constitute important intangible capital. Family-owned firms are less 

concerned with short-term returns and more concerned with long-term performance. This 

longer-term orientation puts the family firm in a better position to more easily make 

adjustments to the structures and processes and strategic orientation of the firm.  

An example of this was evident in the case of Cimber, a Denmark-based family-owned 

airline (Bogers et al., 2015). Initially, the founder–owner set up the airline business as a partner 

to other airline firms such as SAS and Lufthansa because of the close relationship with their 

senior executives. The focus was on serving a small set of business customers. However, later 

on, bringing external members into the business meant that its complexity increased through 

the adoption of a hybrid model, that is, by moving into the consumer and holiday market space, 

while still serving the business customer market. This created complexities in the business, 

which the family members had to reverse in order to become a more simplified customer-based 

business model while relying on the relationship with SAS to bail them out of financial trouble.  



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6.4 Early-Stage Science-Based Start-Ups 

Early-stage technologies often face the challenge of novel applications for markets that do not 

yet exist and which therefore need to be created (George and Bock, 2011; Pisano, 2006; Shane, 

2004). In such early-stage technologies, there is significant market ambiguity. The focus of 

start-ups in avoiding such ambiguity by primarily focusing downstream on end-users might 

lead to technology commercialisation failure (Molner, Prabu, and Yadav, 2019). This market 

ambiguity calls for a wide search for the application of technology across different domains. 

In such settings partnering firms that are willing to jointly learn and explore the possible 

landscape of applications of the technology is more important than a focus on any immediate 

end product (Molner, Prabhu, and Yadav, 2019). Hence, the creation of such markets, with the 

development of appropriate business models, is often the challenge for science-based start-ups, 

where the market for the product is not readily available (Pisano, 2010).  

During the 20th century, large-scale incumbent firms such as DuPont, GE, 

Westinghouse, IBM, Kodak, Xerox (PARC) and AT&T (Bell Laboratories) created in-house 

labs to perform scientific research in order to commercialise products (Pisano, 2010). More 

recently, the connection between science and business has begun to change as a result of the 

highly risky nature of some of the scientific research and the increasingly long time needed to 

convert this into viable products, often between five to ten years or more. The investment in 

in-house scientific labs declined among incumbent firms and was replaced by new “science-

based businesses”; start-ups in sectors such as biotech, nanotech and energy emerged, with an 

increasing role played by universities in enabling such technology transfer from their labs 

(Gumusay and Bohne, 2018; Pisano, 2010). It is becoming increasingly common for incumbent 

firms to acquire these science-based start-ups. For example, Japanese incumbent Sumitomo 

Chemical acquired Cambridge Display Technology (CDT), which had developed the P-OLED 

(polymer-organic light-emitting diode) technology for over a decade; and Medigene AG 



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acquired Oxford biotech spit-out Avidex, which went on to integrate Avidex T-cell protein 

technology with Medigene’s own offering (Lubik and Garnsey, 2016).  

Science-based start-ups need to be considered in relation to whether the technology has 

a clear market where they are targeted to help solve a problem. This depends on the technology. 

Often in areas such as biotechnology and pharmaceuticals the breakthroughs are targeted at 

solving specific problems (Lubik and Garnsey, 2016). However, in other areas, such as new 

energy or material, the technology is often generic and could be used for a wide variety of 

applications. Such generic technologies are often known as general-purpose technologies, 

which display general applicability across a number of products or production systems, display 

technological dynamism with continual innovation, and prompt innovation in complementary 

technologies in the application sectors (Rosenberg and Trantenberg, 2004; Goldfarb, 2005). 

These properties of generic technologies make it challenging for start-up firms to develop their 

business models. Two case examples of start-ups – Cambridge Display Technology (CDT) and 

Metalysis in the advanced materials sector – illustrate these challenges.  

CDT was founded in 1992 following 10 years of science-based research at the 

Cavendish Laboratory, the University of Cambridge, following the invention of polymer 

transistors (Maine and Garnsey, 2006).30 Light-emitting polymers (LEP) were seen as having 

the potential to replace cathode ray technologies, which was still the standard for electronic 

display applications. CDT created intellectual property on LEP technology platforms, as well 

as the production process for the flat-panel organic light-emitting diode (OLED). LEP and 

OLED technologies had new attributes for display design such as flexible screens, efficiency 

and weight compared to existing technologies such as cathode ray display and LCD displays. 

Initially, CDT licensed its technology to incumbent firms involved in materials supplies, as 

well as displaying manufacturers such as Philips, Hoechst and Uniax as a means to develop the 

 
30 This case study is from Maine and Garnsey (2006). 



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market through manufacturing partnerships. Moreover, a joint venture partnership was formed 

with Seiko Epson Corporation, resulting in the first video display LEP. However, CDT needed 

more funds to conduct R&D for materials and devices surrounding its OLED patents: it sold 

out to a New York private equity fund, Kelso and Hillman, in 2000. In order to increase the 

value of the licensing agreements, CDT decided to re-enter small-scale manufacturing to 

demonstrate the viability of its pioneering technology. To this end, it developed its own 

manufacturing facilities in Cambridge. CDT’s first commercial product was the OLED 

electronic shaver display, which was launched in 2002. Following this, CDT’s LEP display 

was incorporated into mobile phones through various partnership agreements. However, the 

cost of manufacturing was too high, as the volume was still relatively low; hence, CDT decided 

to scale back its manufacturing by selling its facilities. Despite the slow growth, CDT 

positioned itself at the centre of the network of companies developing technologies using LEP 

displays and was successful in listing on Nasdaq in December 2004. As mentioned earlier, 

CDT was acquired by the Japanese firm Sumitomo Capital in 2007.  

CDT faced significant market and technological uncertainties, the latter because its 

technology was competing with existing technologies. For this reason, it needed to invest in 

reducing costs in the upstream, as well as downstream, process to enable component suppliers 

and OEM manufacturers to utilise the products in existing product applications. CDT focused 

exclusively on the consumer electronics market but examined several applications. It faced the 

challenge of acquiring an accurate picture of consumer needs because it did not have direct 

contact with consumers. Hence, CDT initially decided to pursue in-house manufacturing in 

order to demonstrate the benefits of its technology. However, the combination of market and 

technological uncertainty resulted in CDT iterating between manufacturing and licensing 

business models before finally settling on licensing as its core business model. 



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Metalysis (called FCC Ltd until 2003) was a spin-out of the University of Cambridge 

whose aim was to commercialise the Cambridge FCC process, which is an electrochemical 

method of producing metals from metal oxides through electrolysis in molten calcium salts 

(Lubik and Garnsey, 2016).31 The process could be applied to various metals such as 

chromium, tungsten, cobalt, tantalum and titanium. The Cambridge FCC process has 

significant benefits, as it allows for the production of metal powders directly from metal oxides, 

lowers processing costs and removes the need for machining, among others. Moreover, the 

technology was seen to be green, as it significantly reduces environmental impact by lowering 

temperature and using fewer toxic chemicals. The founders approached Cambridge Enterprise, 

the technology-transfer office of the University of Cambridge, in order to license the patent to 

a number of firms. Metalysis built a small-scale pilot plant in one of the science parks in 

Cambridge to develop the process further. It originally targeted tantalum, which was costly to 

produce, but the tantalum market did not prove to be a success.  

In 2006 Metalysis decided to focus on titanium as a result of a partnership with Rolls-

Royce, which provided funding for R&D activities and scale-up facilities as part of its tax off-

set programme in Malaysia. Initially, the rights for the use of titanium were licensed to another 

firm but this was overcome through a transfer of the licensing rights by Cambridge Enterprise, 

which was followed by a legal battle. Moreover, BHP Billiton joined Metalysis to jointly 

develop the method for processing titanium. Initially, Metalysis adopted the pure licensing 

model and demonstrated the benefits of the technology using tantalum. However, it needed a 

market with a high-value-added metal with a sufficient market size; for this reason, it split to 

enter scale-up production in the titanium market despite the existence of large dominant 

players. Metalysis was able to collaborate to produce metal powders, which were very valuable 

to this segment. This strategy overturns the conventional wisdom of serving the niche market 

 
31 This case study is from Lubik and Garnsey (2016). 



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first, as it protects start-ups from stiff competition and enables them to build a bridge for future 

growth. As this case illustrates, Metalysis began by focusing on the high-end segment of a large 

market such as titanium and added value to the existing players by reducing the costs for them.   

Ambos and Birkinshaw (2010) discussed the process of the evolution of new science-

based ventures. The authors highlighted three distinct venture archetypes. The first is a 

capability-driven venture, in which the primary driver of action is the development of an 

internal technology or capability. The second is a market-driven venture, where the primary 

driver is the development of sales and the relationship with customers or alliance partners. The 

third archetype is the aspiration-driven venture, where the primary driver of action is the growth 

aspiration of the venture’s leaders and legitimising the business among stakeholders. The study 

shows that often new science-based ventures start with one of these three types of focus and 

over time transition to another focus. For example, a venture could start with an aspiration-

driven venture, with the founder wanting to build a company almost for its own sake. The 

aspiration-driven orientation shifts to capability orientation when the technology needs to be 

developed and then a market-driven orientation when the emphasis shifts to finding a customer 

for the proposition. 

This idea draws upon the cognitive view of strategy that emphasises what preoccupies 

the senior management team the most, whereby strategy is defined as an “enabler of action”, 

as the viewpoint about the future, which people cluster in order to mobilise a set of actions 

(Weick, 1987). In science-based ventures the focus often shifts between the three archetypes, 

which defines the focus of management or founders on one set of issues, while keeping the 

other two on the backburner. This is often a result of the highly constrained resources of 

science-based new ventures, unlike large firms, where there are often functional heads to 

manage different areas and priorities. Often, the emphasis shifts from one archetype to another 

because of the cognitive dissonance between management’s understanding of one cognitive 



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schema and another because of changes triggered by internal events, such as a change in 

personnel or new technological breakthroughs, or external events such as regulatory changes 

or customer needs. Such transitions could be either sustaining, building on existing capabilities, 

or disruptive, which requires dropping some capabilities and building new ones. Therefore, the 

chances of success are as much a function of decisive and committed action to pivot between 

the different archetypes as they are about identifying objective actions. Such intrinsic 

ambiguity means that the importance of ensuring the shared interpretive scheme can act as an 

enabler or an inhibitor of action, which could eventually determine the design of appropriate 

business models, contributing to success or failure, respectively (Leonard-Barton, 1992).  

6.5 Business Model Design of Start-up Ventures 

One of the major challenges for start-up firms during the early stages of the venture is designing 

their business models. Various studies have proposed principles for founders and managers of 

start-up firms facing significant uncertainty in designing and evolving their business models. 

We review some of the principles in this section. 

Amit and Zott (2015) highlighted the design thinking approach in crafting the business 

model architecture. They proposed goals, templates, stakeholder activities and environmental 

constraints as the antecedents for business model design. They highlighted how these 

antecedents affect business model design themes of novelty – the provision of new value 

propositions; lock-in – the ability to lock in customers and partners; complementarity – the 

bundling of activities to promote synergies; and efficiency – linking activities to reduce costs. 

The first antecedent is for the start-up to identify its goals to create and capture value in broad 

open-ended terms rather than being too specific. This approach allows the design of the 

business model to evolve and create value for various stakeholders. The objectives of the 

stakeholders will not all be aligned; hence, there is a need to balance managing the tension with 

appropriate judgement that arises from conflicting objectives in creating and capturing value. 



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Such a process creates and captures value for the new venture while enhancing the lock-in of 

the stakeholders. For example, in designing person-to-person (P2P) lending the objectives are 

defined as overcoming social injustice as a result of the lack of transparency of the existing 

lending model (Amit and Zott, 2015).  

The second antecedent is the use of the template from other existing businesses in 

designing the business model of the new venture. Here, being mindful of the similarities and 

differences is important in terms of the ability to graft the relevant aspects to the new start-up 

firm. Mindless copying could result in a sub-optimally designed business model. For example, 

in the P2P lending market one of the start-ups combined the template from the corporate bond 

market and the match-making model of eBay. The idea of the servicing-type match-making 

platform was built on the principles of people having the power and democracy to decide on 

borrowing and lending rather than institutionalised players dictating the terms.  

The third antecedent is based on the design concept of collaboration among partners to 

bring complementary assets together, to create either novelty or efficiency of both, and hence 

create appropriate lock-ins. The idea of the highly reputable anchor partner is important in 

terms of enhancing the attractiveness of less committed stakeholders. Partners can help to 

increase revenue or reduce costs (Kesting et al., 2015). An example of increasing revenue is 

Google in its early days adding Google AdWords, a pay-per-click advertising service; the 

founders of Google realised that appearing high on search results holds tremendous value for 

stakeholders with a willingness to pay for this service. An example of engaging with partners 

in reducing costs is TripAdvisor utilising social media to collect and display user evaluations. 

The final antecedent is the environmental constraint, which can serve as a stimulus for 

the invention of new approaches to adopting practices from other domains. These constraints 

can be external or internal. External constraints are imposed on the business from the outside, 

such as regulation, culture or socio-politics, while internal constraints are due to limited 



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resources and capabilities within the firm. Therefore, focusing on constraints can enable 

creativity and hence the design of novelty in the business model of the new firm. For example, 

in the case of the P2P business model design, one of the firms felt that, if they pooled risks, the 

regulators would consider them a collection investment scheme with a significant regulatory 

burden. Hence, the start-up firm decided to set up individual contracts directly between 

borrower and lender, which resulted in further novel business model designs.  

Studies have also emphasised the need for start-up firms to adopt the principles of 

parallel play or simultaneous experiments to overcome business model development challenges 

due to uncertainty. McDonald and Eisenhardt (2020) borrowed from the child development 

literature, whereby pre-schoolers play near one another but not together, taking an interest in 

what their peers are doing and often mimicking them. They tend to build objects and might 

even pause and consider their progress before continuing. Parallel play refers to children 

playing in a space, borrowing from peers, testing assumptions and pausing before elaborating 

on the activity system. Such a process of parallel play among start-up firms might enable them 

to achieve “optimal distinctiveness”, where there are similarities that enable them to conform 

to the established rules in the market but enough differences to highlight their differentiation 

(Zhao et al., 2017). The study observes that entrepreneurs often borrow from their peers. In 

addition, similar to pre-schoolers, these entrepreneurs tend to test major assumptions to reduce 

uncertainty about which template to choose. Finally, entrepreneurs who design effective 

business models tend to pause and reflect before completing their activity system.  

Andries et al. (2013) highlight the need for start-up firms to conduct simultaneous 

experiments as a learning strategy. They contrast simultaneous experiments with focused 

commitments, which might be instrumental in acquiring dedicated resources but reduce the 

ability to conduct experiments to learn, and hence they might be detrimental to long-term 

survival. The authors borrow from the effectuation literature to make an analogy to causation 



195 
 

and effectuation (Sarasvathy, 2001). Causation is where entrepreneurs choose specific means, 

such as technology and employee skills, to create a desired effect, such as a specific business 

model design. Effectuation implies that the venture draws upon their knowledge and networks 

and selects between possible effects that can be created with this set of means. Simultaneous 

experimentation is seen as representing effectual logic, as it takes a set of means as a given; for 

example, investment decisions involve a commitment limit in terms of affordable loss, in order 

to focus on selecting between possible effects that can be created from this set of means. 

Focused commitment follows causal logic, where the venture chooses a specific means to 

create a desired effect, such as an ex ante chosen business model.  

6.6 Conclusion 

Small- and medium-sized enterprises are a significant part of most developed and developing 

economies in terms of their contribution to both output and employment; however, their 

productivity often lags behind larger incumbent firms. Therefore, SMEs are a major source of 

opportunities to increase jobs and stimulate economic growth. Nonetheless, they do face major 

hurdles in innovating their business models as the result of a combination of a lack of resources, 

knowledge and capabilities (Masood and Sonntag, 2020). Recent studies also show that, 

because of such constraints, SMEs might want to adopt a “shoestring” approach to off-the-

shelf simple digital technology solutions rather than complex industrial solutions, which are 

often designed for larger firms (Hawkridge et al., 2021). Moreover, when SMEs are part of 

larger, more complex supply chains, they are often tied to the requirements of larger prime 

firms, which can result in a lack of incentives to invest in the intangible capital that is often 

required to innovate business models, especially when new technologies come on board (Made 

Smarter Review, 2017; Said et al., 2022).  

The above issues are particularly challenging, as the evolution of digital technologies 

enables more distributed production architecture, which will call upon SMEs to be more 



196 
 

involved in local production and distribution (Klockner et al., 2020). In addition, the emergence 

of platform architecture business models increasingly relies on generative principles to create 

new products and services, which might rely on a plethora of SMEs to develop such a 

proposition (De Marco et al., 2019). Moreover, it is possible that the emergence of radically 

new general-purpose technologies will rely on start-ups and SMEs to develop the new 

propositions, which might be less interesting to established firms that do not want to cannibalise 

the status quo.   

Governments around the world have instituted various programmes to overcome some 

of these challenges. For example, in the United States the Manufacturing Extension Partnership 

(MEP) programme helps SMEs to improve their performance by providing a combination of 

advice and help on various aspects of business, including the adoption of digital technologies. 

In the United Kingdom the Sharing in Growth (SiG) programme is designed to help SME firms 

in the aerospace sector address the shortcoming of not being able to invest sufficiently in 

intangible capital, as this is the less measurable part of the business (Said et al., 2022). The 

immediate objective of the SIG programme is to help SMEs navigate the challenges posed by 

an increasingly competitive global aerospace supply chain. However, the resulting improved 

performance helps SME firms to innovate their business model as a result of the changing 

market and technological conditions in the aerospace sector. Moreover, there are also initiatives 

to help educate SMEs on the benefits of digital technologies by building demonstrators or 

model factories using the latest digital technologies, such as the ModelFactory@SIMTech in 

Singapore (Tay, Ng, and Tan, 2021). These initiatives help SME firms not only to learn about 

the benefits – and hence be able to de-risk investment in new technologies – but also to build 

capabilities to transform their business models through a sense and response manufacturing 

approach. Studies show that start-ups and SMEs need to play their part by being open to such 



197 
 

learning, being able to partner other firms to acquire skills and capabilities, and also keeping 

their business models agile in order to pivot to new opportunities as they arise.  

There are a number of areas for further investigation of business model design among 

start-ups and SMEs. The first major area of research is to better understand how intangible 

capital plays a role in the digital transformation of SMEs. The resources, knowledge and 

capabilities constraints of SMEs might tilt them towards low-cost digital technology solutions 

to improve efficiency and productivity. More in-depth research is needed to better understand 

how to provide a systematic roadmap for SMEs to transition from low-cost digital solutions to 

digital transformation of their business models as their industrial ecosystem transforms as a 

result of new digital technologies.  

The second major area of research is to better understand how the dynamics of family 

businesses influence the decision-making and implementation of business model innovation. 

The complex interplay of family relations and senior management decision-making needs to 

be better understood to enable family businesses to transition from niche players to more major 

firms in the national and international landscape. Such growth and ability to compete on a 

global scale require business model innovation. However, the right balance needs to be struck 

between family involvement and professional management, which requires further research 

and in-depth understanding.  

The third key area concerns how new markets come about in science-based start-up 

propositions. An increasing amount of work has been done in understanding the emergence of 

new markets. However, more insights are needed to understand the links between technology 

transition (TT) literature that highlights the socio-technical changes and the incentives provided 

by business models. Studies in technological transitions have emphasised the importance of 

examining different levels, such as the multi-level perspective, which have argued that 

technological breakthrough and replacing an existing technological regime arise from 



198 
 

dynamics across different levels; or they have emphasised how system builders are key to 

enabling alignment across technical and non-technical (such as laws and regulations) artefacts 

that create unity among the actors to enable technological transitions (Bolton and Hanan, 2016; 

Hughes, 1979). These approaches to TT highlight the socio-technical nature of change but de-

emphasise the activity system inherent in the BM approach, which comprises transactions 

between firms. Hence, further work is needed to understand the role of the business model 

designs of start-ups in science-based ventures in order to enable major technological 

transitions.  

This chapter has provided an overview of the opportunities and challenges of SMEs and 

start-up firms in transforming their business models; it has also proposed some outstanding 

research issues on this topic.  

 

 

 

 

 

 

 

 

 

 

 

 

 

 



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CHAPTER 7: SUSTAINABILITY AND BUSINESS MODELS 

  



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CHAPTER 7: SUSTAINABILITY AND BUSINESS MODELS 

 

Earth provides enough to satisfy every man’s needs but not every man’s greed. 

(Mahatma Gandhi) 

 

7. Introduction 

Business as usual is not an option for a sustainable future because of the rising global 

population, accelerating global development, and increasing resource use and environmental 

impact (Bocken et al., 2014; Crowley et al., 2017). The world is using the equivalent of 1.5 

planets to support human activities (WWF, 2012). In other words, the world will take 1.5 years 

to regenerate the renewable resources consumed in one year, which is an unsustainable rate of 

consumption. Firms have a role to play in achieving sustainability by designing sustainable 

business models. Sustainable business models need to value natural assets that are often “free”, 

internalise externalities and encompass the triple bottom line of economic, social and 

environmental goals (Bocken et al., 2014). Scholars have called for a more critical assessment 

of the purpose of the organisation beyond merely profit maximisation, which requires a radical 

rethink of innovation and industrial systems to address the sustainability challenges facing our 

world today (Ciulli et al., 2019; Lehoux et al., 2021; Henderson, 2021).  

The need for a sustainable world is not new but has built momentum as a result of its 

urgency in recent years (Rendtorff, 2019). The Brutland Commission report in 1987 was the 

original report on sustainability, which was then extended by the Sustainable Development 

Goals (SDGs) of the United Nations (United Nations, 2015, 2018). The SDGs aim to combine 

economic development, environmental development and social inclusion (Sachs, 2012, 2015).  

They were meant to be a follow-up from the Millennium Development Goals (MDGs), which 

focused primarily on poverty, hunger, disease, unmet schooling, gender inequality and 

environmental degradation. The MDGs, which ran for 15 years, from 2000 to 2015, were seen 



206 
 

to be achieved by some countries and not others (Sachs, 2012). Hence, policy-makers and civil 

society felt the need to continue the poverty reduction goals of the MDGs and enhance them 

with challenges around climate change and other environmental ills (Sachs, 2012). There was 

a recognition that human activity might push the global ecosystem past a threshold, which 

might have devasting and non-linear outcomes for human well-being. Hence, under the 

leadership of the UN Secretary General, in June 2012 a high-level global sustainability panel 

issued a report recommending the adoption of SDGs following the MDGs. The MDG targets 

were mainly for poor countries, with rich countries helping to provide finance and technology. 

However, the SDGs pose challenges for all countries, rich and poor; moreover, they embrace 

a wider set of goals for sustainability by adding prosperity, peace and partnership to people, 

the planet and profit (Rendtorff, 2019). 

Achieving the SDGs would require good governance at all levels within the public and 

private sectors. These include appropriate economic institutions and firms acting responsibly 

to a wide range of stakeholders. Private-sector firms are often the main driver of the productive 

sector of the economy and own many of the advanced technologies and management systems 

(Sachs, 2012). Therefore, firms in the private sector need to embrace new business models by 

adopting new technologies, enabling new ways of organising human activities in order to 

contribute to achieving the SDGs.  

There are continued pressures from human activity on different crucial earth systems, 

including carbon, nitrogen and water cycles (Sachs, 2012), and there are anthropogenic 

challenges due to climate change and biodiversity.32 The challenges to climate change are a 

result of human-created emissions of greenhouse gases, such as carbon dioxide and methane; 

and increased acidification of the oceans, caused by a greater concentration of atmospheric 

 
32 Anthropogenic is used to refer to environmental changes that are caused or influenced, either directly or 
indirectly, by humans (Chakrabarty, 2020). 



207 
 

carbon dioxide. Moreover, there is a growing loss of biodiversity from unsustainable demands 

on forests and significant environmental pollution from run-off of nitrogen and phosphorus-

based fertilisers, among others.   

Governments agreed to develop voluntary action plans to cut greenhouse-gas emissions 

under the terms of the Paris Agreement, or COP 21 summit, which was signed by 197 countries 

in 2015 (IPCC, 2018).33 The objective of the voluntary cutting of greenhouse-gas emissions 

was to keep the world’s average temperature well below rising to 2 °C above what it was before 

the Industrial Revolution – and preferably keeping it below 1.5 °C (IPCC, 2018). Moreover, 

during the COP26 summit in Glasgow, in 2021, some countries made collective commitments 

to curb methane emissions, to halt and reverse forest loss, and to encourage the finance sector 

with a net-zero target by 2050, including the end of international financing of fossil fuels and 

accelerating the phasing out of coal (The Economist, 2021c). Addressing these targets and 

challenges calls for innovative solutions such as a circular economy to create a closed-loop 

system that minimises the use of resource input and the creation of waste and pollution. Such 

a closed-loop system calls for the design of new business models – the focus of this chapter – 

which provides an overview of the opportunities and challenges associated with addressing one 

of society’s greatest challenges – sustainability issues related to climate change – as well as 

biodiversity, through business model innovation. 

7.1 Sustainable Business Models for a Circular Economy 

Sustainability based on a circular economy would be built on some core principles (Bocken et 

al., 2019). First, it would include a system that encourages the minimisation of consumption or 

which imposes personal and institutional caps or quotas on energy, goods, water, and so on. 

 
33 The UNFCCC is the United Nations Framework Convention on Climate Change. In the 1990s the UNFCCC was 
agreed upon by virtually every nation in the world in order to stabilise greenhouse-gas concentrations that 
would prevent dangerous human-induced causes of change to the climate system. COP21 means the Conference 
of the Parties that were signatories to the UNFCCC meeting for the 21st time.  



208 
 

Second, the system would be designed to maximise societal and environmental benefit, rather 

than prioritising economic growth. Third, it would be a closed-loop system where nothing is 

allowed to be wasted or discarded into the environment, which reuses, repairs and remakes in 

preference to recycling. Fourth, the system would emphasise the delivery of functionality rather 

than product ownership; and, fifth, it would provide fulfilling, rewarding work experiences for 

all that enhances human creativity/skills. Finally, it would be a system built on collaboration 

and sharing rather than aggressive competition.34 

The types of business model design for sustainability could be classified using three 

broad groupings, namely, technological, social and organisational (Bocken et al., 2014). First, 

the technological grouping could be due to technical innovations such as manufacturing 

processes or new materials. Technological-grouping-based business model innovation includes 

maximising material and energy efficiency, creating value from waste and substituting with 

renewables and natural processes. Maximising material and energy efficiency involves 

deploying products or services that deliver similar levels of functionality but use fewer 

resources and generate less waste and emissions, such as dematerialisation, low-carbon 

solutions and lean manufacturing processes. Creating value from waste involves thinking 

creatively about transforming existing waste products into valuable input for other processes.  

For example, the British Sugar factory in Norfolk, in the United Kingdom, is one of the 

major producers of tomatoes in the UK because much of the carbon dioxide produced as part 

of its beet-based sugar production is recycled for growing its tomatoes in controlled 

greenhouses (Short et al., 2014). Another example of a holistic waste management system is 

the Kalundborg Industrial Symbiosis System (KISS) in Denmark, which is the world’s first 

working industrial symbiosis ecosystem. The KISS production firms are located close to one 

 
34 Although these principles seem reasonable, as we will see later there are conditions whereby some of them 
could create adverse incentives. 



209 
 

another so as to be able to transfer by-products between parties via a network of pipes and by 

road to make them useful. The results are impressive, with yearly CO2 emissions reduced by 

240,000 tonnes, 3 million m3 of water saved through recycling and reuse, 30,000 tonnes of 

straw converted to 5.4 million litres of ethanol, 150,000 tons of yeast replacing 70 per cent of 

soy protein in traditional feed mix for more than 800,000 pigs, and recycling of 150,000 tonnes 

of gypsum from the desulphurisation of flue gas (SO2), which replaces the importation of 

natural gypsum (CaSO4) (Chopra and Khanna, 2014; Team Gemini, 2015). Substituting with 

renewable energy solutions and natural processes, such as hydrogen and wind energy, involves 

reducing the environmental impact associated with non-renewable resources.  

Second, the social grouping is due to changes driven predominantly by social 

innovation, such as changes in consumer behaviour. Social-grouping-based business model 

innovation includes delivering functionality rather than ownership, adopting a stewardship role 

and encouraging sufficiency. Delivering functionality rather than ownership involves 

providing services to customers such as pay-per-use-based product–service systems, without 

customers necessarily owning the product, which might reduce the number of products that 

need to be manufactured. Adopting a stewardship role involves stewarding assets in such a way 

as to engage with stakeholders to ensure that their long-term well-being and productive assets 

are protected, such as ethical fair-trade initiatives. Encouraging sufficiency involves changing 

demand patterns by, say, educating customers to reduce consumption. This could be achieved, 

for example, by energy companies providing transparent and clear data on usage patterns in 

order to encourage savings from reducing consumption.  

Third, the organisational grouping is driven primarily by an organisational design 

change component, such as changing the fiduciary responsibility of the firm. Organisational-

grouping-based business model innovation includes repurposing for society and the 

environment and also developing scale-up solutions. Repurposing for society includes 



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reorganising businesses in such a way as to prioritise the delivery of social and environmental 

benefits rather than being purely profit-driven. Developing scale-up solutions involves scaling 

sustainability initiatives to benefit society, which can take a myriad of forms, such as 

standardising processes and other business practices, including licensing, franchising and 

openly sharing appropriate knowledge and business processes (Bigdeli et al., 2015). A 

summary of the grouping of the different business model archetypes is listed in Figure 1. 

Figure 7.1: Sustainable Business Model Archetypes 

 

Source: Adapted from Bocken et al. (2014) 

7.2 Circular Business Models and Product–Service Systems 

The literature on sustainable business models has emphasised the “what” question that outlines 

what sustainable business models look like. The next step is to better understand the “how” 

questions of how managers need to enable the change that is required for firms to contribute to 

sustainability (Roome and Louche, 2016). Business models for sustainable development 

require an understanding of both value creation and value destruction across the ecosystem of 

actors (Batista et al., 2018; Hawken, Lovins, and Lovins, 1999; Parry et al., 2016). Hence, the 

design and implementation of sustainable business models call for both a system- and firm-

level perspective on value creation and an avoidance of value destruction. Research has shown 

that the process model of change might consist of four phases: identifying the need for change; 

translating, which involves how the firm adapts new concepts to the organisation; embedding, 

Technological Social Organisational

Maximise 
material and 

energy 
efficiency

Creative 
value from 

waste

Substitute 
with 

renewables 
and natural 
processes

Deliver 
functionality 
rather than 
ownership

Adopt a 
stewardship 

role

Encourage 
sufficiency

Repurpose 
for 

society/envir
onment

Develop 
scale up 
solutions

Ar
ch

et
yp

es



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which focuses on the way the firm adopts new concepts and develops internal routines; and, 

finally, sharing, which outlines the learning process that goes beyond the boundary of the firm 

to the ecosystem of partners. We examine some of the enablers and barriers of the process 

model of change in firms adopting circular business models and product–service systems 

(PSS). 

The aim of sustainability is to benefit the environment, the economy and society at 

large (Elkington, 1997). More recently, scholars have emphasised the concept of the circular 

economy, the aim of which is a closed-loop system of eliminating resource input, waste and 

emissions. This was influenced by Boulding (1966), who described the earth as a closed and 

circular system with limited assimilative capacity – hence, the need for the economy and the 

environment to co-exist. A circular economy can be seen as one means of achieving 

sustainability by emphasising how resources can be better used and waste emissions reduced 

with a circular, rather than linear, make–use–dispose system35 (Bounding 1945, 1949; 

Geissdoefer et al., 2017). An industrial system that is restorative and regenerative by intention 

and design is called a circular economy (Ellen MacArthur Foundation, 2013, 2015). The Ellen 

MacArthur Foundation circularity analysis focuses on five key areas of economic and 

environmental impact: material input, labour input, energy input, carbon emissions and balance 

of trade (Ellen MacArthur Foundation, 2013). The traditional economy is based on the “take, 

make and dispose” industrial model, which increases the demand for raw materials. For 

example, the prices of raw materials increased from the turn of the century and there has been 

an increase in price volatility in recent decades (Ellen Macarthur Foundation, 2013). Hence, 

 
35 Germany was a pioneer in introducing the concept of the circular economy into national law in 1996 with the 
“Closed substance cycle and waste management act”, which was followed by other countries, for example, 
Japan’s 2002 “Basic Law of Establishing a Recycling-Based Society”, China’s 2009 “Circular Economy Promotion 
Law of the People’s Republic of China” and the EU’s 2015 “Circular Economy Strategy” (Geissdoefer et al., 2017). 



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firms face higher supply disruptions and higher prices, prompting them to look at circular-

economy-based industrial systems with sustainable business models.  

The circular economy works on three principles (Ellen MacArthur Foundation, 2013). 

The first principle needs to design out waste in the system, while the second is to manage the 

distinction between consumables and durables. Consumables are largely made up of biological 

nutrients and are non-toxic: the biological nutrients cycle is designed to re-enter the biosphere 

safely. Durables are made up of technical nutrients and are unsuitable for the biosphere: the 

technical cycle is designed to circulate without entering the biosphere through end-of-life. 

Third, the energy required to fuel the cycle needs to be renewable by nature. These principles 

drive the value-creation opportunities of material through the following: the power of the inner 

circle – minimising material use; the power of circling longer – maximising the number of 

consecutive cycles; the power of cascade use – diversifying reuse along the value chain for 

different purposes as the material changes properties; and the power of pure circles – the use 

of uncontaminated materials to increase the efficiency of material productivity. A summary of 

the four sources of value creation for circularity are shown in Figure 2.  

 

 

 

 

 

 

 



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Figure 7.2: Four Sources of Value Creation for Circularity 

 

Source: Adapted from Ellen McArthur Foundation (2013) 

An example of a change in business model from such circular principles was evident in the 

case of Rohner, a successful manufacturer of high-end upholstery fabrics based in Switzerland 

(Roome and Louche, 2016). Between 1981 and 2004 Rohner transformed itself from selling 

textile products that resulted in a high risk of pollution and generated waste to adopting a 

closed-loop production–consumption-based circular economy for textiles (Roome and Louche, 

2016). Rohner’s senior management first identified the need to change when they faced intense 

competition from non-European textile manufacturers, combined with increased regulation of 

environmental issues. The regulatory issue was particularly compelling, as Rohner was located 

near the source of the Rhine River and Lake Constance, where pollution was a major issue.  

Hence, the CEO and the management team decided to develop a vision for Rohner for 

high-quality, well-designed products and manufacturing processes encompassing the highest 

standards of environmental and social responsibility. The company decided to work closely 

with Michael Braungart, the founder of the German Greenpeace Chemical Division, and the 

Power in inner circle Power for circulating longer

Power of cascade use Power of pure circles



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American architect William McDonough, who were known for the cradle-to-cradle concept, 

which challenged the way things were made in order to be sustainable (McDonough and 

Braungart, 2002). This required the firm to work with its employees and suppliers of, for 

example, dyestuffs to develop and test ideas related to sustainable production. The first period 

was a process redesign in the textile mill, followed by product innovation and then a product–

process redesign. The next stage involved embedding the new concepts within the firm by 

building appropriate management information systems and tools to support employees by 

providing information and performance guidelines to reinforce the new products and processes.  

Next, they worked with external partners and regulators to transfer knowledge to the 

agricultural sector, which, for example, provided the wool used in the textiles. Rohner had to 

radically change its products and production processes, and hence its business model, which 

resulted in a significant change in the way the firm was governed, organised and managed. In 

fact, Rohner first developed a vision to contribute to its economic success, while also 

contributing to sustainable development by reducing the damage to resources from its 

activities. This vision preceded the development of the new business model; therefore, the 

revised business model was the outcome of the process. Such a transformation required a move 

away from a focus on products to the higher level of the system to better understand the sources 

of value creation and destruction. This required both a problematic and an aspirational search 

(Cyert and March, 1963).36  

The closed-loop value chain comprises the production stage, the consumption stage and 

the subsequent circulation stage (Kortmann and Piller, 2016). The production stage can be 

conceptualised as what is produced by the firm or its ecosystem. The consumption stage is in 

the domain of the consumer in terms of how the product is used. Finally, the circulation stage 

 
36 Firms are likely to search for solutions and change when they are either facing problems or have an excess of 
resources, which could result in a problematic search or an aspirational search (Cyert and March, 1963) 



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involves the product’s end-of-life stage. There are two major forces that focus firms’ attention 

on the circular economy. First, there is an increased cost of product returns such as electronic 

goods. Second, stakeholders are increasingly willing to participate in firm activities with 

regards to the circular economy, especially when enabled by emerging information and 

communications technologies (Kortmann and Piller, 2016). These two developments 

fundamentally redefine the relationship between the firm and the customer, and hence the 

business models, by changing the traditionally separated tasks into new forms of horizontal 

collaboration. Firms are increasingly opening their business models to enable third-party 

organisations to participate in the end-to-end life cycle of the product. For example, Dell is 

increasingly cooperating with asset resale and recycling partners to develop products with the 

end in mind (Kortmann and Piller, 2006). This involves emphasising the use of recyclable and 

renewable materials, standardising components, replacing glues with adhesives and snapfits, 

as well as new types of paint and coating. These initiatives require more open business models 

through alliances or engagement with firms with platform-based business models that enable 

multi-parties to transact efficiently to achieve the closed-loop objectives.  

Ricoh, a provider of production, printing and office solutions, developed “GreenLine” 

as part of its Green Office Solutions Programme. Copiers and printers returning from its leasing 

programme were refurbished and updated with new software and rented to the market under a 

similar warranty scheme to its new products (Ellen MacArthur Foundation, 2013). Ricoh was 

able to launch the GreenLine label because of its adoption of the “Comet Circle” programme, 

whereby the firm builds its products on the basis that all product parts should be recycled or 

reused. Moreover, the transition to a circular economy shows that adopting a circular economy 

business model requires not only manufacturing and operations but also marketing to do its 

share in changing the culture of consumers and business users (Hopkinson et al., 2018). 



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The closed-loop principle requires firms to extend their value-added services to not only 

the consultation stage but also developing propositions around product returns. The consumer 

becomes more engaged in the activities traditionally associated with the firm. Moreover, 

external stakeholders increase their participation in the creation and capture of value. Because 

of the possibility of returning products and exchanging them for state-of-the-art devices, 

consumers may become less prone to product ownership and more willing to lease or rent, 

which might include complementary services (Kortmann and Piller, 2006). Hence, there could 

be increased use of product–service system (PSS) business models. For example, Moovel, a 

subsidiary of Daimler Benz, is a platform app that fully integrates various service providers, 

such as car2go and MyTaxi, railway firms, public transport authorities, as well as bike rental 

firms, to enable customers to find – and then book – the best way to get from one place to 

another. In launching the Moovel platform, Daimler has essentially created a mobility service 

by working closely with an alliance of partners within an ecosystem in order to jointly create 

and capture value by providing a service based on systems of products (Kortmann and Piller, 

2006). 

PSS could be product-oriented, where the product is still owned by the customer; use-

oriented, where the product is owned by a third party and the customer pays for specific use; 

and outcome-oriented, where the customer pays for a particular outcome37 (Pardo et al., 2012; 

Yang and Evans, 2019). PSS could combine different elements of product, use and outcome-

oriented mechanisms to create the customer offering. Pay-per-use business models could 

contribute to sustainable consumption; for example, in the case of washing-machine 

 
37 Cusumano et al. (2015) classified product-related services into three types, namely, smoothing, adapting and 
substituting services. Smoothing relates to services that do not change the product’s functionality, such as 
maintenance and financing. Adapting relates to changing the functionality of the product, such as making it more 
customised. Substituting services relates to services that replace the purchases of the product, such as leasing 
or renting. One can posit that adapting and smoothing are related to product-oriented PSS, and substituting 
relates to use-oriented and result-oriented services (Yang et al., 2018).  



217 
 

implementation, when customers started paying after a period of free consumption, the total 

number of washes and the washing temperatures reduced significantly (Bocken et al., 2018).  

Recent studies have shown that, although PSS that provide a service from a set of product 

offerings could contribute to sustainable initiatives, they are not inherently sustainable 

(Amasawa et al., 2020; Yang and Evans, 2019). For example, the ownership balance might 

influence the degree to which the customer uses the product with care. Customers might use 

products less carefully when they do not own them, and hence they could contribute to a 

decrease in product life (Yang and Evans, 2019). In addition, there are transportation costs in 

moving the product to where the customer is in the case of peer-to-peer sharing of products 

such as books, bicycles and automobiles, among others, which might contribute to greenhouse-

gas emissions (Amasawa et al., 2020).  

Moreover, there are barriers to adopting a PSS business model because of conflicts 

between sales and service, for example, in terms of compensation systems, pricing of services 

and balancing performance with social/ecological issues (Pacheo et al., 2013). For example, 

research shows that, with PSS, business models tend to focus primarily on value that brings 

economic benefits in terms of profits and financial returns (Yang and Evans, 2019). The 

environmental or social value might be created only because it was combined with economic 

value. For example, in the case of a firm selling gas-generation services, energy consumption 

was the main cost for air-separation units in the generation of gases. Hence, the firm was 

incentivised to reduce energy consumption in order to reduce costs, but this also reduced carbon 

emissions. This need to balance economic with environmental and social issues makes it 

challenging for firms, especially SMEs, to transition to sustainable business models. Moreover, 

ownership of the underlying equipment could influence the type of source of value creation for 

sustainability (Yang et al., 2018).  



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Yang et al. (2018) studied the case of power generation of a firm across three business 

model archetypes – product, use and results, or outcome-oriented business models – in order 

to better understand the emphasis of different sources of value. In the case of use and outcome-

oriented business models, the firm owns the product and might therefore be incentivised to 

adopt the inner circle by minimising material use and circling longer by maximising the number 

of consecutive cycles more than the product-oriented business model. This is because the firm 

owns the product in the case of use and outcome-oriented business models, which incentivises 

the firm to create value from the whole product life cycle. The firm has the economic incentive 

to reduce the environmental impact of products that are in use. In the product-oriented business 

model the customer owns the product and the firm might have less detailed information about 

use patterns. Moreover, in the case of the outcome-oriented business model, the firm might 

also be more incentivised to adopt the power of cascades through the use of co-products and 

by-products in other value chains – for example, the application of co-produced gases for new 

applications. In addition, outcome-oriented business models might also be more prone to using 

the power of pure circles by, for example, the use of uncontaminated materials to increase 

efficiency of material productivity. 

7.3 Net Zero and Energy Transition 

The energy sector accounted for approximately three-quarters of greenhouse-gas emissions in 

2021, which means it is important in terms of helping to avoid the negative consequences of 

climate change38 (IEA, 2021). Efforts to limit the long-term increase in average global 

temperatures to 1.5 °C are consistent with the initiative to reduce cardon-dioxide emissions to 

 
38 Moreover, there are health benefits from reducing greenhouse gases, as they contribute to energy-related 
emissions of major air pollutants such as sulphur dioxide, nitrogen dioxides and fine particulate matter (IEA, 
2021). More than 90 per cent of people around the world are exposed to air pollution, which led to around 5.4 
million premature deaths in 2020, mostly in developing countries, which undermines productivity and puts an 
enormous burden on the healthcare system.  



219 
 

net zero39 by 2050 (IPCC, 2018).40 This will require significant transformation of how energy 

is produced, transported and consumed, which will have major implications for the design of 

new business models. Such a transformation will require the use of different energy sources 

and carbon capture, as well as behavioural changes. The estimated global emission of CO2 was 

around 33 billion tonnes in 2021. The International Energy Agency (IEA, 2021) believes that 

most of the reduction of CO2 emissions through to 2030 could be achieved by technologies that 

are ready – or almost ready – today, but in 2050 almost half of the reductions will need to come 

from technologies that are in the demonstration phase or yet to be discovered. Some of the most 

promising technologies include advanced batteries, hydrogen electrolysers and direct air 

capture and storage. For example, low-carbon hydrogen could be produced via electrolysis 

using surplus renewable energy, sometimes termed “green hydrogen”; alternatively, it could 

be obtained from natural gas, with the carbon emissions reduced via the use of carbon capture 

utilisation and storage (CCUS) facilities, termed “blue hydrogen”41 (Nuttall and Bakenne, 

2019). Such CCUS facilities demand new business model solutions based on the degree of 

vertical integration with the generation facilities and the type of services being delivered.  

Moreover, one of the major challenges is being able to design business models to 

overcome the cost gap between the deployment of low-carbon hydrogen supply and higher-

carbon fuels. This involves addressing the market price – the price for hydrogen is lower than 

 
39 Net zero implies that the fossil-fuel usage that will remain in 2050 will be in products where the carbon is 
embodied in the product, such as plastics, which does not imply emissions; where the fuel is not combusted, 
such as lubricants; or in sectors where low-emission technologies are limited, such as aviation. 
40 Some countries have made meeting their net-zero target a legal obligation, while others have made pledges 
in official documents (Branca et al., 2021). For example, the European Green Deal is a combination of policy 
initiatives and laws to make the economy and the EU climate-neutral by 2050. Moreover, a net-zero pledge 
could be achieved in the energy sector, where energy-related emissions could be offset by the absorption of 
emissions from forestry or negative emissions from bioenergy or the direct capture of CO2.  
41 Carbon capture, utilisation and storage (CCUS) includes methods and technologies to remove CO2 from fossil 
fuels and the atmosphere, followed by recycling the CO2 for possible utilisation in other valuable substances or 
products and determining safe and permanent storage options. Demand for CCUS facilities could increase, which 
requires major shared investments by industry in pipeline and shipping infrastructure to link the facilities where 
CO2 is captured and the storage sites (IEA, 2021). 



220 
 

the cost of production and volume risk – with the risk that sales fall below the economically 

viable level for producers to recover their production costs (BEIS, 2021). Some countries, such 

as the UK, are considering policy interventions to provide price and volume support 

mechanisms to enable the transition to a hydrogen-based economy (BEIS, 2021). Moreover, a 

range of policy interventions might be needed across the hydrogen value chain to help 

overcome other related barriers such as the high capital costs of investments, a lack of 

distribution and storage facilities, demand uncertainty, and policy and regulatory uncertainties 

around standards for low-carbon hydrogen (BEIS, 2021). 

The energy sector consists of a large number of long-lived and capital-intensive assets 

such as pipelines, refineries and coal-powered power plants with lifespans of over fifty years.42 

The key principles for decarbonisation of the global energy system are energy efficiency, 

behavioural changes, electrification,43 renewables, hydrogen-based fuels and bioenergy, as 

well as the use of CCUS facilities, which can enable the transition to net-zero emissions by 

providing a cost-effective pathway to scale up hydrogen production rapidly and also address 

CO2 emissions from some of the challenging sectors, such as cement manufacturing.44 Modern 

bioenergy will come from sustainable sources and avoid a negative impact on biodiversity, 

freshwater systems and processes of agricultural produce for food. An advantage of bioenergy 

is the ability to use the existing infrastructure; for example, biomethane could use existing 

natural gas pipelines and end-user equipment (IEA, 2021).  

The electricity sector alone accounts for more than 50 per cent of emissions from 

existing assets, industrial sectors such as chemical, steel and cement account for around 30 per 

cent, transport accounts for 10 per cent and the building sector just under 5 per cent (IEA, 

 
42 Advanced economies tend to have older capital stock compared to emerging economies (IEA, 2021). 
43 The rapid electrification of all sectors could put electricity at the cornerstone of energy security globally, as 
electricity infrastructure is more vulnerable to extreme weather events, compared to pipelines and underground 
storage facilities, and could also be subject to cyber-security risks (IEA, 2021). 
44 The current technology for the production of one tonne of cement creates around 0.6 tonnes of CO2. 



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2021). In 2020 oil provided 30 per cent of the total energy supply, followed by 26 per cent 

from coal and 23 per cent from natural gas (IEA, 2021). Renewables are likely to provide a 

significant proportion of energy use in the future, such as hydrogen, bioenergy, wind, solar, 

hydroelectricity and geothermal. Transportation relied on 90 per cent of carbon-based fuel use 

in 2020. This is likely to change to electricity for low-duty transportation, hydrogen for long-

haul heavy-duty trucks, advanced biofuels and hydrogen-based fuels such as ammonia for 

shipping and synthetic liquids, and advanced biofuels for aviation. Moreover, buildings need 

to increasingly decarbonise by using renewable energy, electricity or district heat, which 

provides heat to homes and businesses generated at a local energy centre. 

Renewables such as hydropower, wind and solar will increasingly contribute to energy 

production in the future.45 Innovative business models based on electrical energy storage (EES) 

would be needed to help balance the demand and supply of these less controllable renewable-

based power sources in order to help decarbonise the market (Anaya and Pollitt, 2019). Anaya 

and Pollitt (2019) provided an analysis comparing the storage business models of cloud data 

storage, frozen food storage and natural gas storage, as they display increasing maturity in the 

product life cycle, in order to draw lessons for business model design for the emerging 

electrical-energy storage (EES) market. These include considerations such as regulation, the 

ability to share capacity via consolidation, product bundling, response times, accessibility and 

green initiatives, among others. Moreover, start-up firms such as Highview Power are 

developing new technologies for energy storage, for example, the CRYOBattery, whereby low-

cost electricity is used to cool air to reduce it to liquid form (The Sunday Times, 2022). The 

liquid form is then expanded again using turbines to generate electricity when needed, with the 

resultant process being free of combustion and emissions or the use of rare minerals.  

 
45 There could be major demand for critical minerals such as copper, lithium, nickel, cobalt and rare earth 
elements that are essential for many clean-energy technologies (IEA, 2021).  



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There is also an increasing move towards distributed generation, whereby customers 

produce their own electricity, for example, with solar panels. Hence, there is a trend to shift 

away from centralised conventional electricity generation towards decentralisation that enables 

customers to generate, store, share and sell energy to the grid (Bryant et al., 2019). Such a trend 

presents a competitive threat to the business models of electric utilities operating under the 

traditional structure of selling electricity to customers.46 There has been increasing interest in 

analysing future energy utility business models to become energy-solutions providers, 

including: the provision of services beyond energy sales, such as installation, financing, 

operations, maintenance and warranty for a fee; energy as a service – the customer pays a flat 

fee for a certain amount of energy and avoids peak-load pricing uncertainty, which incentivises 

the utility to promote energy efficiency; and building a platform model – to connect the 

distributed generation capacity with consumers (Bryant et al., 2019). However, these digitally 

based smart decentralised energy systems could contribute to the business models of incumbent 

utility firms being challenged by new entrants trying to disintermediate them using digital 

platforms to aggregate demand and enabling trading among consumers or providing energy-

saving-based demand management propositions (Nillesen and Pollitt, 2016). Hence, utility 

firms need to rethink “where to play”, “how to play” and “how to win” in the emerging net-

zero energy industry (Nillesen and Pollitt, 2016). 

7.4 Biodiversity and Crafting Business Models 

Nature provides us with food, water and shelter, which contributes to our health and well-being. 

Therefore, nature should be treated as an asset, just like produced capital (such as building and 

machinery) and human capital (such as knowledge and skills). There has been increasing 

 
46 Customers under the decentralised model could potentially avoid the joint grid costs of maintaining the 
network. Some countries are introducing tariffs for their own consumption of domestically generated electricity 
(Nillesen and Pollitt, 2016). 



223 
 

attention by firms on acknowledging their dependence on nature; the cost to firms from the 

loss of biodiversity could be enormous. For example, Unilever, a global consumer goods 

company, faced significantly higher prices for cod in the 1990s as a result of overfishing in the 

western North Atlantic. Cod is the main fish species, used for its fish stick, a premium frozen 

food product. The replacement of cod with New Zealand hoki fish was not accepted by UK 

consumers because of its taste and quality, and hence it was delisted as a product by a number 

of retailers through 2004 (Winn et al., 2013).   

Just as diversity within a portfolio of financial assets reduces risks and uncertainty, 

biodiversity – the diversity within a portfolio of natural assets – increases nature’s resilience to 

shocks and hence maintains the ability to continue to provide services to humankind and other 

species47 (Dasgupta, 2021). Biodiversity enables nature to be productive, resilient and 

adaptable. In doing so, nature’s ecosystem provides two types of service (Cardinale et al., 

2012): provisioning services that enable the production of renewable resources (e.g. food); and 

regulating services (e.g. pest and disease control). Biodiversity is defined as the variety of life 

forms, including variation among species and their functional traits (Cardinale et al., 2012). 

The concept of biodiversity is a multi-level construct that captures more than just the variation 

in species (Cardinale et al., 2012; Winn et al., 2013). Biodiversity also includes functional 

diversity and response diversity: functional diversity refers to the number of species that can 

perform different ecological functions in an ecosystem (e.g. pollination); and response diversity 

refers to the number of ways in which a specific function, such as pollination, can be performed 

(e.g. bees or birds).  

 
47 There are instances where increasing biodiversity might be detrimental (Cardinale et al., 2012). For example, 
diverse assemblage of natural enemies (such as predators, pathogens, etc.) can be beneficial in the control of 
herbivorous pests, but this can also inhibit biocontrol because the enemies attack one another. Another example 
relates to human health, where a more diverse pathogen population could increase infectious disease (for 
example, variants of SARS-CoV-2 or COVID-19).  



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The Dasgupta Review (Dasgupta, 2021) highlights that, collectively, we have failed to 

manage the global portfolio of natural assets in a sustainable manner. This is evidenced by 

estimates showing that, between 1992 and 2014, the capital produced per person globally 

increased by about 13 per cent, while the stock of natural capital per person declined by 14 per 

cent. Biodiversity loss is due to a combination of factors such as climate change, pollution, 

human exploitation of natural resources and the displacement of some species into new 

territories away from their natural habitat, which causes instability in the existing ecosystem 

(The Economist, 2021a). Firms are increasingly addressing biodiversity as part of their overall 

strategic initiatives (Bishop et al., 2009; Winn et al., 2013). For example, ArcelorMittal, a 

leading firm in the steel and mining industry, has implemented a biodiversity compensation 

programme to minimise the impact of iron mining activities in Liberia’s Nimba mountains. 

Another example is Sygenta, a Swiss agribusiness in the seeds and pesticide market, which 

launched an initiative to increase farm productivity, with the goal of restoring native pollinators 

in the agricultural landscape in some major European countries and the United States.   

The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem 

Services (IPBES), a body created to bridge the gap between biodiversity science and policy, 

stated in its 2020 report that the health of natural ecosystems is deteriorating rapidly. This was 

further supported by the Living Planet Report 2020, produced by the World Wildlife Fund 

(WWF) and the Zoological Society of London, two conservation and research groups, who 

stated that the loss of populations of animals such as mammals, birds and fish is accelerating 

(The Economist, 2021b). Moreover, significant deforestation – for example, of the Amazon – 

beyond a certain point could cause an abrupt transformation of the landscape into a savannah 

and make it irreversible.  

There has been a significant loss of animals that perform important functions within the 

natural ecosystem. Nearly three billion birds have been lost in North America since 1970 



225 
 

(Paulson, 2021). More than 75 per cent of the global food crop, including coffee, cocoa and 

almonds, is pollinated by animals (The Economist, 2021a). Hence, the loss of birds affects the 

efficiency of food-crop pollination. Moreover, climate change and biodiversity loss are locked 

in tandem in a cycle of destruction. For example, scientists predict that 70 to 90 per cent of 

coral reefs will disappear over the next 20 years as a result of warming sea temperatures, acidic 

water and pollution (Paulson, 2021). This will affect 4,000 species of fish, and approximately 

half a billion people dependent on these coral reef ecosystems for food and employment. There 

has been an increasing call to finance initiatives to protect the most important biodiversity, and 

the services it provides, through initiatives such as the UN Convention on Biodiversity. It is 

likely that low-income countries, which are more dependent than high-income countries on 

nature’s goods and services, will be most affected, contributing to increased inequality.  

The goods and services that nature provides to society, and hence its worth or value, 

are often not reflected in market prices, as many of them are freely available.48 This pricing 

distortion leads to underinvestment and overconsumption relative to other forms of capital such 

as produced capital (Dasgupta, 2021). This is a market failure and an institutional failure, with 

institutions incentivised to exploit, rather than protect, nature. The Dasgupta Review 

(Dasgupta, 2021) recommends three broad transitions to address these issues. The first is to 

ensure that our demands on nature do not exceed supply. This could take the form of pricing 

for the use of natural resources, as well as quantity restrictions on the use of such resources. 

The second suggested transition is the need to change the measure of economic activity in terms 

of simply output, such as GDP, to a wider concept that incorporates depreciation of the stock 

 
48 Estimating the value of biodiversity loss is not trivial, as it requires a better understanding of the complexity 
of the ecosystem, which often delivers multiple services and involves trade-offs (Cardinale et al., 2012). For 
example, carbon sequestration through afforestation might increase the production of timber but reduce the 
supply of water. Hence, the value of biodiversity needs to factor in both the marginal benefit in terms of services 
gained and the marginal costs in terms of services lost. A systems thinking approach would be needed to address 
these types of complexity in valuing nature’s services (Lovins et al., 1999). 



226 
 

of natural assets. This could include natural capital in national accounting systems, as well as 

at firm level (Haskel and Westlake, 2018). For example, the Integrated Reporting Framework 

(IRF) might be a broad step in that direction, with members’ firms encouraged to report the 

impact of natural capital and other forms of intangible capital together with the manufactured 

capital (Flower, 2015; Thomson, 2015).49 The third recommendation is to reform the 

institutions and governance system to support the management of such diversity. Such 

institutions need to be polycentric by consolidating knowledge and perspectives at global, 

national and local levels. These institutions need to include business and financial institutions 

by incorporating the impact of their activities on biodiversity. This calls for new business 

models.  

Some firms have taken the opportunity to reinvent their business models, whose core 

value proposition is, in essence, a contribution to the management of a given environmental 

problem. For example, Lyonnaise des Eaux transformed itself from a “small water-cycle” firm 

to an “extended water-cycle’ firm (Feger and Merhmet, 2020). A small water cycle involves 

providing services for water-treatment plants, pipes and other man-made infrastructures. 

However, the emergence of digital technologies with sensors enabled Lyonnaise des Eaux to 

provide extended water-cycle services that cover water-related ecosystem management such as 

flood risks, green infrastructure for rainwater management, groundwater protection and 

wetland and ecosystem services, and related biodiversity protection. This was partly driven by 

the change in perception of the “concessions” management system of public services in France, 

which was developed in the 19th century. The concession-based approach allowed public 

authorities in France to delegate the financing, construction and management of public services 

and utilities to private operators while still owning the infrastructure.  

 
49 However, studies have criticised the IRF for focusing on reporting and not going far enough with the changes 
needed in terms of the power structure of stakeholders (Flower, 2015; Thomson, 2015). 



227 
 

In the l990s and early 2000s, there was a change in perception that this concession-

based approach was seen to accelerate the privatisation and commodification of common 

goods. In particular, there were increasing concerns about the costs of managing environmental 

and water-resource preservation issues such as less water availability due to climate change 

and more pollution caused by farming, and so on. Moreover, there was a reduction in the 

amount of water sold although the billing was based on volume. This caused Lyonnaise des 

Eaux to rethink its customer value proposition based on the extended water-cycle business 

model. These extended water-cycle services include management of the inland water body as 

a natural bathing pool, pollution-reduction plans for groundwater, and quality monitoring of 

nearby water streams for construction firms in order to alert them in advance of any damage to 

fish populations.  

There were several challenges that Lyonnaise des Eaux had to overcome in transitioning 

its business model to incorporate extended water-cycle management. First, there was no 

predefined customer for the wider ecosystem management of the water system. Second, there 

was resistance from managers attached to the small water-cycle culture, where there was 

certainty in terms of billing based on the volume of consumption compared to the less certain, 

but potentially lucrative, service model. The third challenge was the need to gain legitimacy to 

intervene in biodiversity management, where there was no single metric to demonstrate 

ecological performance. These are the types of challenge that firms will need to manage as the 

maintenance of biodiversity objectives is incorporated into business model design. 

7.5 Methane Abatement and Business Model Design 

Methane emissions from human activities are the second largest contributor to global warming 

after carbon dioxide (McKinsey, 2021). Human activity emits less methane than carbon 

dioxide, which stays in the atmosphere for a long time – often centuries – making it hard to 



228 
 

reduce its atmospheric concentrations. In contrast, methane has a half-life of roughly a decade, 

which implies that it degrades quickly. However, methane has a larger impact on global 

warming. Over the course of a 20-year period, a tonne of methane (CH4) will warm the 

atmosphere 86 times more than carbon dioxide (CO2). Hence, methane is said to be responsible 

for 23 per cent of the rise in temperatures since pre-industrial times. The main reasons for the 

rise in methane emissions are livestock farming, where animals such as cows belch it, rice 

cultivation, where soggy environments could harbour micro-organisms that produce it, and the 

fossil-fuel industry, whereby pipelines and rigs could leak methane (The Economist, 2021a).  

Methane emissions and their contribution to climate change have been discussed less 

frequently among policy-makers, corporate decision-makers and society because of the more 

sporadic nature of its emission compared to carbon dioxide (McKinsey, 2021). These sporadic 

emissions create a number of problems. First, they are difficult to quantify, making it difficult 

to take abatement actions. Second, abatement costs vary significantly between one type of asset 

and another (methane recovery in coal mining has higher costs than gas leaks in the oil and gas 

industry). Third, often there are trade-offs in the solutions; for example, dry seeding in rice 

farming might reduce emissions from flooding but increase emissions from nitrous oxide, 

another greenhouse gas (McKinsey, 2021).  

Five industries are responsible for 98 per cent of human emissions of methane, namely, 

agriculture, oil and gas, coal mining, solid waste management, and wastewater management 

(McKinsey, 2021). Agriculture accounts for 40 to 50 per cent of anthropogenic methane 

emissions. Ruminant animals such as cows and sheep create methane during digestion, among 

other gasses such as carbon dioxide. Moreover, the mechanical flooding of rice farms to 

manage pests is also responsible for methane emissions (The Economist, 2021b). Firms are 

already commercialising feed additives for cattle that reduce methane production, while new 

approaches to water, soil-carbon, nitrogen and land-management systems for rice production 



229 
 

are reducing methane emissions. Leakage from the oil and gas industry, for example, from 

natural gas, accounts for around 20–25 per cent of methane emissions (McKinsey, 2021). 

Similarly, the leakage from methane trapped in coal that is emitted when the coal is mined 

accounts for 10–15 per cent of emissions. For example, some countries are beginning to 

mandate requirements to monitor the intensity of natural gas leakage using more sophisticated 

sensing equipment. Such extra-sensitive sensing equipment might be provided by quantum-

technology-based firms with the opportunity for new business model development. The solid 

waste and wastewater management industries account for about 7–10 per cent of methane 

emissions (McKinsey, 2021). Anaerobic organic material, or the breakdown of organic 

material in wastewater streams, generates methane. There might be opportunities to capture 

these methane emissions and sell them as renewable natural gas or use them in the production 

of fertiliser. Alternatively, there are opportunities for the application of microalgae to prevent 

methane formation (McKinsey, 2021). The above-mentioned management of methane 

emissions in the relevant key industries requires new business models in order to deliver the 

solutions effectively and efficiently. 

7.6 Discussion 

An increasing number of firms are creating purpose-driven strategies to take into account 

sustainability objectives alongside commercial objectives (Henderson, 2021; Rozentale and 

van Baalen, 2021). Pursuing conflicting goals inevitably creates ongoing tactical conflicts 

within the business model when deciding which objective to prioritise and hence which 

stakeholders to satisfy. Firms need to be cognisant of these tensions and accommodate them 

when pursuing sustainability goals. This is one of the key challenges in defining value when 

pursuing multiple objectives. The notion of value based on philosophical pragmatism is neither 

purely objective nor subjective but rather the result of the social process of action (Painter et 

al., 2019). In this context, value can be seen as prizing and appraising that comes about from 



230 
 

the continuous design and engineering of social activity (Dewey, 1944). Hence, if a sustainable 

future is prized, valuation should enact and serve this objective. This value is achieved by 

examining the past problem, for example, environmental degradation, and generating a new 

imagination of the future to test, amend and modify previous beliefs though a process of 

participatory involvement by the relevant stakeholders.  

Cafédirect, a farmer-owned social enterprise, experienced this tension in defining value 

and responding to changes and challenges in the market and societal environment with different 

business models, with varying degrees of success (Davies and Doherty, 2019). The firm 

initially started with the objective of the core economic activity of selling coffee and tea as a 

means to serve the social goals of empowering smallholder farmers and pulling them out of 

poverty. Farmers are not just suppliers but partners in the Cafédirect venture. Cafédirect tried 

to guarantee a minimum price for coffee to the farmers following the significant reduction in 

prices that came about after the dismantling of the International Coffee Agreement in 1989; it 

also tried to provide farmers with welfare protection to promote poverty alleviation. Cafédirect 

was focused on marketing and sales of the products to consumers and had an agreement with 

an NGO, Twin Trading, to provide producer-support and development initiatives. By the early 

2000s, the fair-trade coffee that it sold had become a commodity, with many suppliers selling 

to supermarkets at lower prices. Cafédirect’s unique position was therefore eroded. Moreover, 

the period coincided with concerns about the environment such as climate change, and crop 

dependence was becoming increasingly important. Hence, Cafédirect started to reposition its 

brand from being a fair-trade producer to a sustainable coffee and producer-advocacy 

organisation.  

In order to achieve this new strategic positioning, the company decided to bring the 

producer-support and development activities in-house rather than relying on Twin Trading. 

Such a move required a more complex set of activities to be managed internally around 



231 
 

logistics, supply chain management and the related producer-support and development 

activities. These added complexity and tensions – such as the value proposition, workers, 

customer communication and branding – to Cafédirect’s business model, and this conflict 

resulted in a poor financial performance. Eventually, from around 2011, a separate entity, the 

Cafédirect Producers’ Foundation (CPF), was set up, which was run independently in order to 

manage the producer-support and development activities. This model enabled Cafédirect to 

refocus on its sustainable enterprise business model without creating an overly complex 

bureaucratic organisation to manage the tensions arising from hybrid business objectives.  

7.6.1 Sustainability Transition Challenges 

Sustainability initiatives often require the adoption of new technologies and transformation of 

the socio-technical systems (Köhler et al., 2017). Studies have been critical of the view that 

transition challenges are merely about overcoming market failure with appropriate pricing of 

externalities (Rosenbloom et al., 2020). The market failure approach underestimates the 

fundamental systems problem and focuses on efficiency as opposed to effectiveness, hence 

stimulating optimisation of the existing system rather than transformation. To envisage how 

green technologies transform our socio-technical system, one may refer to the research on 

technological transitions, whereby scholars have aimed to understand the phenomena of 

technological transitions and their impact on industry and society. In particular, the literature 

on socio-technology transitions has described how technological transitions come about. 

Studies of the multi-level perspective (MLP) have argued that technological breakthrough and 

replacing an existing technological regime arise as a result of dynamics across three levels: the 

micro level, which involves niche experimentation by firms; the meso level, where regimes 

maintain stability through a semi-coherent set of rules that orient and coordinate the activities 

of social groups and determine the institutional interaction; and the macro level, where the 

external landscape, such as deep structural trends, social values and worldviews, largely 



232 
 

beyond the control of the system actors, take place, for example, policies on climate change 

(Geels and Schot, 2007; Elzen, Geels, and Green, 2004).  

Given the right landscape conditions, radical niche innovations can overthrow dominant 

regimes to enable transition pathways for new technologies. The focus of the multi-level 

perspective is on the evolutionary mechanism of change and less explicit recognition of the 

agency and politics of change. The large technical systems (LTS) literature has studied the 

transition of electricity infrastructure. In LTS, system builders are key to enabling alignment 

across technical and non-technical (such as laws and regulations) artefacts that create unity 

among the actors to enable technological transitions (Hughes, 1983). Such alignment is often 

achieved by system builders, who construct the system by breaking down demarcated 

boundaries between scientific knowledge, technologies, institutions and users, among others, 

to create a seamless web. Such system builders could be inventor–entrepreneurs, financiers and 

managers, who might play different roles during the phases of the technical system transition. 

These approaches to technological transitions highlight the socio-technical nature of change 

but de-emphasise the activity system inherent in the business model approach, which is 

composed of transactions between firms (Bolton and Hannon, 2016).  

Moreover, recent research suggests that business models can both facilitate and hamper 

technological transitions (Bidmon and Knab, 2018). For example, DuPont (of the United 

States) and Imperial Chemical Industries (ICI) (of the United Kingdom) were both major 

multinationals whose business models were dependent on chlorofluorocarbon (CFC) 

production. For this reason, they both played an important role in influencing their respective 

governments on their initial positions in the 1970s, which entailed a reluctance to support 

policies to ban CFCs (Rajan, 1997). Subsequently, in the 1980s, the European firm alleged that 

the US wanted to ban CFCs to open up vast markets for Du Pont, which had a head start in 

developing CFC substitutes. Therefore, existing theories lack the business model perspective, 



233 
 

despite firms being regarded as key performative actors in technology transitions (Sarasini and 

Linder, 2018). During the transition, firms need to align the content, structure and governance 

of their business models with the evolving socio-technological context (Bolton and Hannona, 

2016).  

For example, there were multiple approaches in the transition to combined power and 

heat (CHP) systems with district-level localised heating in the UK. In the first approach the 

local authority owns part of a start-up energy service firm and promotes the council’s 

sustainability objectives. The energy service firm might compete with other incumbents in 

providing energy services based on decentralised energy solutions. The second model consists 

of the local authority contracting to buy energy services from third-party incumbent energy 

firms and providing the anchor loads, such as large municipal buildings and residential 

schemes, as the principal customer. The local authority enters into a long-term contract with 

the incumbent energy service provider to encourage the large capital investment needed for the 

local CHP schemes. These two models might be driven by different political considerations, 

such as whether a local authority should own an energy service firm. In addition, the transition 

could be driven by a start-up or an incumbent firm. Moreover, these two models of transition 

to a sustainable energy supply framework show that the business model design needs to be 

incorporated within the technology transition systems.  

It is helpful to contextualise the business model design space to describe the options 

available for new business model designs and hence how actors need to either “fit and conform” 

or try to “stretch and transform” the space (Wesseling et al., 2020). The design spaces that 

firms need to consider include: regulatory – rules and regulations; science and technology – 

the technology and knowledge to create and capture value; industry – the presence and 

willingness of firms in the ecosystem to collaborate or compete; cultural – the cultural value of 

the stakeholders; and the market dimension – which determines user preferences (Wesseling et 



234 
 

al., 2020). Stakeholder firms would need to assess which are the softer dimensions, which are 

malleable, and the order in which to adopt a “fit and conform” or “stretch and transform” 

strategy. Thus, understanding the firm-level dynamics with a business model lens can shed 

light on the drivers and barriers of transitioning to a new socio-technical system.  

An in-depth examination of firm-level dynamics and their business models can provide 

deeper insights on the adoption challenges of green technologies and their impact on the 

systemic process of technological transition to enable sustainability. Both the large technical 

systems and business model approaches forefront the agency of actors in building systems, 

while the multi-level perspective emphasises the evolutionary aspects across different levels 

(Bolton and Hannon, 2016). The large technical systems approach emphasises system builders 

engaging in political processes, and the business model approach emphasises entrepreneurs 

and managers entering market transactions to shape the content, structure and governance of 

business models to drive economic value. All three approaches of technology transition are 

needed to better understand how green technologies can move towards a sustainable economy 

and the role that business model design plays. Moreover, the economic system is important, 

whereby the relationship between the state and the private sector could drive how such 

technological transitions unfold and the associated policy implications. For example, liberal 

market economies, whereby the state limits its role to rule setting and conflict settlement (e.g. 

the United States), coordinated market economies, enabling state arbitration among economic 

actors to facilitate cooperative relationships (e.g. Germany), state-influenced market 

economies, where the state plays an active interventionist role (e.g. France, Japan, South 

Korea), and state capitalism (e.g. China and Russia), where the state or state-owned enterprises 

undertake commercial activities, could influence the policy and business model design 

implications (Geels, 2018).  

7.6.2. Degrowth Economics 



235 
 

The conventional paradigm in economics and politics is the green growth model to address the 

issue of climate change. The green growth model assumes that the economy can continue to 

grow while addressing the threat of climate change through market-led action and 

technological innovation (Paulson, 2021; Bokat-Lindell, 2021). An alternative perspective is 

the degrowth paradigm, whereby humanity does not have the capacity to reduce the use of 

fossil fuels and meet the ever-growing demand for economic growth (Hickel, 2017; Ripple, 

2020). Hence, the proponents of degrowth emphasise the need to curtail consumption and 

accept a reduction in the growth rate of the economy to address climate change (Keyber and 

Lenzen, 2021).  

The degrowth paradigm is based on two main premises (Hickel, 2017): the first is that 

GDP growth cannot be decoupled from material resource use; and the second is that GDP can 

be decoupled from greenhouse-gas emissions by replacing fossil fuel with renewal energy, but 

this replacement is not taking place quickly enough. This might be the result of technological 

advances not being able to cope with such rapid change or the challenge of technological 

transitions. Therefore, the degrowth proponents argue that the solution is to reduce resource 

and energy consumption, which will make it easier to transition to renewable energy. Some 

have argued that the responsibility to reduce consumption should lie disproportionately with 

the richer countries in order to allow the poorer countries to catch up and their population to be 

brought out of poverty (Hickel, 2017). The proponents of such economies that are regenerative 

and distributive by design have argued that the objective is to find ways to achieve tempered 

economic growth as a means to reach social goals within ecological limits – and not a goal in 

itself (Raworth, 2018).  

There are proponents of the green growth paradigm that reject calls for a degrowth 

strategy, as they believe that GDP growth is already being decoupled from material resource 

use. For example, some richer countries have grown while using fewer of the planet’s most 



236 
 

important resources. For example, the US has seen a decline in the use of freshwater 

withdrawals per day, various metals and trade-adjusted carbon emissions (Smith, 2021). 

Moreover, they argue that technological developments will enable a faster transition to 

renewable energy. In addition, the degrowth recommendation of tempered growth might not 

be politically or socially palatable – and hence less acceptable in practice. In any case, even a 

partial adoption of the degrowth model could imply significant changes in production and 

consumption activities. For example, the model could entail a substantial reduction in the use 

of carbon-based fuel, which might have implications for global transportation such as shipping 

and air transport. In addition, the reduced use of cement-based mortar or concrete, which is 

heavy in carbon emissions, could mean changes to the construction industry. The reduction of 

ruminant meat-based products to curtail methane emissions could imply a greater demand for 

vegan or vegetarian diets, which has significant implications for the food industry. These 

factors could change business models in industries such as transportation, construction and 

food, among others, and hence the ecosystems of firms supplying to these industries. Such a 

business model change requires firms to internalise negative externalities and generate positive 

externalities such as securing stable employment, social capital, food security and non-market 

capital in order to embrace the idea of operating within the carry capacity of the environment 

and equitable distribution of wealth (Khmara and Kroneberg, 2018).  

7.7 Conclusion 

Firms in the private sector need to embrace new business models by adopting new technologies 

that enable novel ways to organise human activities in order to contribute to achieving the 

Sustainable Development Goals. The pressure on crucial earth systems such as carbon, nitrogen 

and water cycles is creating anthropogenic-driven challenges as a result of climate change and 

the impact on biodiversity. However, in order for firms to innovate their business models, major 

technological transitions are required that call for public policy interventions, as purely market-



237 
 

based systems might fail to achieve such changes quickly enough (Bryant et al., 2019). Modern 

governments need to think about not just fixing market failures but also acting as transformers 

and shapers to address societal issues (Rosenbloom et al., 2020). This would include policy 

initiatives that identify the type of business models needed to achieve the desired outcome 

– and also the barriers to achieve the outcome. The policy stance of governments could be 

driven by their political and economic orientations, respectively (Dryzek and Stevenson, 2009). 

On the political dimension, they could be either conservative – strategies will be executed 

within existing institutions and power structures; or progressive – where existing institutions 

and power structures are seen to be inadequate and in need of reform. On the economic 

orientation, they could be either reformist – they accept that the existing economic objectives 

and values are sufficient to address the changes needed; or radical – where the existing 

economic objectives and values are implicated in the problem and require radical change. Most 

of the policy agenda on climate-change initiatives has focused on the economic orientation, 

with little emphasis on changing the political dimension, such as institutions or power 

structures (Bryant et al., 2019).  

Studies show that merely focusing on the technological aspects of the transition 

challenges involved in addressing climate-change issues might not be adequate. Some of the 

barriers to transition might be related to institutional aspects (Bakker and Konnings, 2018). 

Hence, these institutional barriers need to be addressed concurrently with the technological 

issues, such as high component costs and systems integration challenges. For example, in the 

case of the transition to the use of zero-emission buses (ZEBs), such as electric and hydrogen 

fuel-cell buses to replace diesel buses in the Netherlands, the institutional barriers were an 

important hurdle to overcome in order to enable new business models to emerge (Bakker and 

Konnings, 2018). In order to incentivise new actors to provide refuelling and recharging 

infrastructure for the ZEBs, it might be necessary to build these facilities to cater not only for 



238 
 

buses but also for other users such as rubbish trucks and taxis. Hence, the installation of 

refuelling and recharging infrastructure in strategic locations that are not necessarily optimised 

for ZEBs could affect the punctuality of buses. The locations of such infrastructure, together 

with the longer time required for ZEB recharging, call for a different approach to schedule 

planning. Moreover, the longer time period needed to depreciate ZEB assets could mean that 

the local authorities need either to buy the buses and lease them to the operators or to provide 

a guaranteed residual value for the ZEBs. These measures shift the risks to the local authorities, 

which requires new institutional arrangements and governance structures in order to stimulate 

ZEB adoption. Moreover, the conventional approach of focusing on the costs and timeliness of 

the schedules as the basis for offering contracts might need to be altered to explicitly include 

ZEBs and provide concessions to overcome the higher initial costs. This case illustrates the 

need for institutional changes to calibrate the economic incentives for new business models to 

complement technological developments in order to encourage technological transition to 

address sustainability issues. 

There are a number of areas where further investigation of business model innovation 

for sustainability could take place. The first major area of research is how to position 

sustainability issues as gains rather than losses (Solberg et al., 2020). Sustainability can often 

be seen as a cost to doing business to address climate or biodiversity issues if viewed with a 

short-term lens. However, from a longer-term perspective, addressing sustainability issues 

maintains the natural environment upon which firms rely in order to conduct business. 

Therefore, further research needs to explore the cognitive dimension of how to position 

sustainability issues as gains. One promising avenue is the development of sustainability 

measures for different business model design configurations that internalise externalities 

related to sustainability. The second major area of research is to address the design of business 

models to enable, and be congruent with, the institutional changes that are needed to address 



239 
 

sustainability issues. As discussed, addressing major sustainability issues involves technology-

transition challenges. Hence, understanding business model design, and how they interact with 

institutional changes, is an important aspect of better understanding how to enable such 

technology-transition challenges to address sustainability issues.  

The third major area of research is how to conceptualise business model design to 

address both climate change and biodiversity simultaneously. As we have discussed, there are 

some instances where addressing climate change might exacerbate biodiversity issues, and 

perhaps vice versa. Hence, more research on how business model design and innovation can 

help to address these two challenges simultaneously, as opposed to individually, is an important 

area of further research. The fourth area of research is to better understand financial business 

models to enable sustainability transitions, particularly how the business models of financial 

institutions need to change and to what extent firms in other sectors in the process of 

transitioning to sustainable business models might need to internalise the financing of such 

transitions within existing business models.  

This chapter has provided an overview of the opportunities and challenges involved in 

addressing sustainability issues related to climate change, as well as biodiversity through 

business model innovation. Sustainability issues address one of the major challenges of our 

generation, and business model innovation could act as a crucial lever to align the interests of 

various stakeholders to make a significant change to the status quo. In this context, we propose 

some outstanding research issues on this topic.  

 

 

 

 



240 
 

 

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CHAPTER 8: BUSINESS MODELS FOR SOCIO-ECONOMIC DEVELOPMENT 

 

  



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CHAPTER 8: BUSINESS MODELS FOR SOCIO-ECONOMIC DEVELOPMENT 

 

Service to others is the rent you pay for your room here on earth. 

(Muhammad Ali) 

 

8. Introduction 

The increasing environmental, social and economic challenges faced by the world led to 193 

of the United Nations (UN) member countries agreeing, at the beginning of 2016, upon 17 

Sustainable Development Goals (SDGs) as a common global agenda to be achieved by the year 

2030 (United Nations, 2020). The SDGs relate to social targets, the eradication of poverty, zero 

hunger, good health and well-being, quality education, gender equality and reduced inequalities 

(Raith and Seabold, 2018). Achieving these targets requires transformation of the financial, 

economic and political systems that govern our societies (United Nations, 2020). Moreover, 

the COVID-19 pandemic has exposed and exacerbated existing inequalities and injustice, as 

the effects have adversely affected the marginalised groups. This calls for even more urgent 

attention to the 2030 SDG agenda. 

The share of the world’s workers living in extreme poverty on less than $1.90 a day 

declined from 14.3 per cent in 2010 to 7.1 per cent in 2019 but the pace of progress has slowed 

down since 2013. The global prevalence of undernourishment (chronic food insecurity) has 

remained almost unchanged, at slightly below 9 per cent, but given the growth in population, 

this translated into 690 million people in 2019, which was up by about 60 million since 2014. 

Universal health coverage, whereby all people have access to suitable healthcare without 

unnecessary financial hardship, was about 30–50 per cent of the global population, but only 

between 12 and 27 per cent in low-income countries. Although the proportion of children out 

of primary and secondary schools declined from 19 per cent in 2010 to 17 per cent in 2018, 

there were still over 258 million people out of school in 2018, with three-quarters of these 



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living in sub-Saharan Africa or Southern Asia. Although there have been advances in gender 

equality in some areas, inequality persists. For example, there are 28 per cent more girls than 

boys out of school in Africa. Moreover, according to estimates in over 89 countries between 

2001 and 2018, women spend about three times as many hours in unpaid domestic and care 

work as men. Between 2010 and 2017, income inequality, although improving in many 

countries, increased in 25 of the 89 countries with available data.50 The existing structures and 

policies are inadequate to solve such major issues and market solutions, and government 

interventions alone might not be sufficient to address these challenges. A major part of such a 

transformation is the need to design innovative business models to act as the architecture with 

a social purpose (Raith and Seabold, 2018). 

This chapter focuses on the concept of social business models to address some of the 

challenges of socio-economic development, including open innovation systems and the design 

of business models to address market failures. The chapter also discusses the often-

unquestioned assumptions of the benefits of value creation and delivery for addressing socio-

economic development, which might have unintended consequences in terms of winners and 

parts of society that might be left behind. The chapter makes the case for a more holistic 

approach to business model design in order to address some of these socio-economic issues.  

8.1 Social Business Models 

The Aravind Eye Hospital in India provides an example of a social business model, having 

adopted a mission to cure blindness through a combination of a market-oriented approach and 

a social purpose (Aravind Eye Care System, 2011; Rangan, 2009). There are 24 million blind 

people in the world and one-third of these cases are curable. Asia has two-thirds of the blind 

 
50 Income inequality is often measured using the Gini coefficient, which ranges between 0 and 100, where 0 
indicates that income is shared equally among all people and 100 indicates that income is concentrated on one 
individual. 



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population in the world, with approximately three-quarters living in India. Dr Venkataswamy 

(also affectionately known as “Dr V”) and David Green, an entrepreneur in the US, came 

together to revolutionise the eye-care delivery system. Dr V had a vision of delivering eye care 

with the efficiency and scale of McDonald’s fast-food chains. In 1976 the Aravind Eye Care 

System was formed as a hybrid business with hospitals, education and training programmes 

and a research foundation. David Green partnered with Aravind through Aurolab, which 

manufactures intraocular lenses at around $4 each in India, compared to $100 in the USA, 

meaning it was able to supply affordable lenses and related services. This partnership meant 

that Aravind was able to perform a high volume of eye surgery at a low cost.  

This high volume provides surgeons with the training and experience to perform eye 

surgery with effectiveness rates that match many of the best eye hospitals in the world. 

Surgeons at Aravind perform over 2,000 surgeries a year, compared to a normal average of 

around 250–400, by adopting standardised processes and systems. Increasingly, telemedicine 

technologies are being used to reach remote areas. About 70 per cent of the surgeries are 

performed for free or below cost, while the remaining 30 per cent of patients are charged above 

cost. This allows the hospital to maintain a 50 per cent profit margin, which results in profits 

being ploughed back into the business to build capability and capacity. Aravind trains nurses 

for two years by recruiting students with the requisite education from local villages; all of the 

doctors work full-time. Moreover, the doctors and nurses are encouraged to adopt a culture of 

service called the “Arvind Way of Life”.  

 

 

 

 



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Figure 8.1: Social Business Versus Other Types of Business 

 

Source: Yunus et al. (2010) 

The Aravind Eye Hospital adopts a social business model design. As shown in Figure 1, a 

social business model can be distinguished from other forms of business. On the one hand, as 

shown in the top-right quadrant of Figure 1, organisations can be seen as profit maximising, 

whereby their objective is to maximise financial return with a view to providing a return on the 

capital to shareholders. The second type of organisation, as shown in the bottom left of Figure 

1, is a not-for-profit organisation, where the objective is to provide some social purpose (social 

profit maximisation), but not with a view to recovering the invested capital. Social businesses, 

as shown in the bottom-right quadrant, maximise social objectives while making a return on 

the capital investment, with a view to reinvesting in the business (Yunus et al., 2010). Hence, 

social business can be self-sustaining while the benefits are passed on to the target group of 

social undertaking in the form of lower prices, better service or greater accessibility (Yunus et 

al., 2010).  

Another example of a social business model is Danone, a multinational food-product 

corporation based in Paris (Danone 2012). In 2006 Danone partnered with Grameen 

Financial profit maximisation

Social profit maximisation

Repayment of
invested capital

(self sustainability)

No recovery
of invested 

capital

Profit-maximising
businesses

Not-for-profit 
organisations

SOCIAL BUSINESSES

N/A



251 
 

(microcredit) Bank in Bangladesh to form Grameen Danone Foods Ltd (GDFL) in Dhaka. 

Franck Riboud (then chairman and CEO of Danone) formed the social business model of 

GDFL following a discussion with Muhammad Yunus, the founder of Grameen Bank and 

subsequently a Nobel Peace Prize winner (Yunus et al., 2010). The mission of GDFL was to 

fight poverty and malnutrition in Bangladesh and to create a positive social impact. This vision 

is reflected in the statement by Muhammad Yunus (Danone Communities, 2020): 

Grameen Danone Foods is a unique opportunity to create a company with a strong social 

dimension, a business whose goal is not to maximise profits but to serve the interests of the 

population, yet without sustaining losses. This small-scale project may be the start of a whole 

new type of market that will change the economic foundations of the world.  

Franck Riboud went on to articulate the strategic imperative for Danone to create a new type 

of business model (Emerging Markets Daily News, 2006). 

I strongly believe that our future depends on our ability to explore and invent new business 

models and new types of enterprise. For Danone, this partnership with a company as iconic 

and visionary as Grameen Bank is a great opportunity to make progress in that direction and 

take another huge step towards fulfilling our mission: to bring health through food to as many 

people as possible. 

Grameen Danone Foods Ltd works on the principles of social business for profit-making, 

where the profits are ploughed back into the business. GDFL’s main product is Shokti Doi, a 

type of yogurt aimed at children. Children in Bangladesh suffer from malnutrition and are 

underweight; it is estimated that 54 per cent of preschool-aged children, approximately 9.5 

million youngsters, are malnourished and 56 per cent are underweight (Danone Communities, 

2020). In addition, Bangladeshi children also suffer from high rates of micronutrient 

deficiencies, particularly vitamin A, iron, iodine and zinc; these deficiencies have an impact on 

the child’s physical and cognitive development. The aim with Shokti Doi is to deliver 30 per 



252 
 

cent of the daily requirement for iron, zinc, vitamin A and iodine at an affordable price through 

a distribution system based on – primarily women – entrepreneurs, called “Grameen ladies”, 

who sell the yogurts in cooler bags door to door in both urban and rural populations. Grameen 

Bank provides the microcredit to the women entrepreneurs to enable them to conduct the 

business of distributing Shokti Doi. GDFL initially built a factory in Bogra, Bangladesh, to 

produce the yogurt. The Bogra factory is built to local specification and uses locally sourced 

milk products, thereby supporting local farmers by educating and training them to produce milk 

to the required specification. GDFL has provided a broad positive social impact to 300,000 

children in Bangladesh while creating sustainable revenue for over 500 farmers and 200 

Grameen ladies (Danone Communities, 2020). 

 Social business models often operate by serving less affluent communities (Seelos and 

Mair, 2007). There are many challenges inherent in serving such communities, as the market 

might not exist or consumers might not be in a position to consume. The market might be 

constrained by availability, whereby the supply chain, governance and institution might not be 

in existence – also called institutional voids (Khanna et al., 2010). Moreover, there could be an 

awareness issue, where customers might not have the knowledge to recognise the benefits of 

the product or service offering. In addition, from the point of view of the consumer, there is a 

challenge of affordability – consumers not being able to pay; and production, acceptability – 

whether consumers are willing to buy given the other demands on their resources. A social 

business model design has to address these market and consumer challenges, as illustrated in 

the case vignettes on Grameen and Telenor – in terms of creating the supply chain; and Map 

Agro and Waste Concern – in terms of creating demand. 

During the 1990s Telenor, the incumbent telecoms operator in Norway, was facing a 

growth challenge as a result of the saturation of its home market (Seelos and Mair, 2007). The 

CEO of Telenor at the time, Tormod Hermansen, received a call from the ambassador of 



253 
 

Bangladesh in Norway to help develop the mobile phone market in Bangladesh. After some 

due diligence and learning more about Bangladesh, Telenor decided to partner with Grameen 

Bank. In 1997 the firms formalised their partnership via a joint venture by forming two sperate 

organisations, Grameen Phone and Grameen Telecoms, as shown in Figure 2 (Seelos and Mair, 

2007). Grameen Phone was run by experienced telecoms managers from Telenor as a profit-

making organisation focusing on the urban market. Grameen Telecoms partnered with a 

Grameen microfinance initiative to create jobs for millions of poor people in over 60,000 

villages across Bangladesh. Many people in rural Bangladesh did not have easy access to 

telephones services at that time and would often have to travel for more than eight hours, 

incurring the equivalent cost of over US$10 to make a phone call. This was partly due to 

Bangladesh having one of the lowest teledensities in the world – less than 1 phone per 100 

people in the country; and even less accessibility – 1 phone per 1,000 people – in rural areas 

(GSMA, 2021). On the other hand, in providing microcredit, Grameen Bank needed to create 

entrepreneurial opportunities for the women it lent to in order to make a return on the loans to 

make a living and repay the borrowings. Hence, the women borrowers were encouraged to take 

up the microcredit loans, purchase the mobile phones from Grameen Telecoms and provide 

access to phone calls to rural communities. In this way everyone gains, as employment is 

created and the rural community saves money by not having to travel and incur inordinate 

expenses to make a call.  

Grameen Phone has been able to build up the middle-class community across villages 

in Bangladesh, becoming profitable and self-sustaining financially and having over 79 million 

subscribers in 2020 (Grameenphone Annual Report, 2020). Grameen Telecoms focused on 

providing a profit-driven telecoms service to the urban community but also built up the 

telecoms infrastructure throughout Bangladesh, which in turn helped to reinforce the business 

of Grameen Phone. The positive feedback loop between Grameen Phone and Grameen 



254 
 

Telecoms helped to build the supply chain for telecoms services in Bangladesh and eventually 

enabled the joint ventures to become one of the largest taxpayers in the country. They did so 

by emphasising income-generation activities by gaining preferential access to the high-income 

segment in urban areas by serving the rural areas. 

Figure 8.2: Grameen and Telenor – Creating the Supply Chain 

 

Source: Adapted from Seelos and Mair (2007) 

In the mid-1990s the 10 million citizens of Dhaka produced over 4,500 tonnes of waste per 

year (IESE Insights, 2006). The city municipality could only collect and dispose of less than 

40 per cent of the total solid debris generated, and much of the waste was not disposed of in a 

sanitary way. This left a considerable amount of uncollected rubbish, and during monsoon 

periods the waste contaminated the groundwater, leading to public health hazards. The city 

authorities had neither the budget nor the resources to address this challenge. In 1995 two 

entrepreneurs, Iftekhar Enayetullah and Maqsood Sinha, studied Dhaka's unacceptable 

conditions and set up Waste Concern (Seelos and Mair, 2007). The budding social 

entrepreneurs discovered that 76 per cent of the waste produced by the residential sector in 

Dhaka had 76 per cent organic content, which was suitable for transformation into compost for 

farmers (IESE Insights, 2006). It turns out that soil in Bangladesh suffered from intense 

Strategic Objectives Interfaces
Strategic Objectives
(Local BOP partner)

Urban 
areas

Economic 
returns

Telenor
Create supply

Connectivity

Revenues,
resources

Grameen Bank Jobs Rural 
poor

GrameenPhone GrameenTelecomCapability
Replication



255 
 

chemical fertiliser use, which could reduce the crop yield in the long run despite the increased 

demand for agricultural produce to feed the growing population. Waste Concern collects waste 

from households at a nominal charge using rickshaw vans.  

Despite Waste Concern initially having issues in terms of land use, it managed to obtain 

preferential access to land through donations made by the local government. The waste is 

composted in small, decentralised composting plants near residential areas. The firm uses an 

aerobic composting technique known as the Indonesian Windrow technique, which produces 

excellent compost material with little odour. Waste Concern also formed a partnership with 

local chemical fertiliser producer MAP Agro, which invested in a nutrient-enrichment plant in 

order to enrich the compost acquired from Waste Concern and used the vast distribution 

network of its parent group, ALPHA Agro, to sell to farmers. Waste Concern calls the business 

model “urban–rural symbiosis”, with food transported from farmlands to urban areas and its 

remains constituting waste that is converted into compost for use in rural agricultural 

businesses – as shown in Figure 3. MAP Agro, in turn, is able to mark up and sell the enriched 

compost to farmers, which contributes to increased productivity of the farmlands. In addition, 

Waste Concern has also increased public awareness of the hazards of dumping waste, while 

valuing its organic waste, and public agencies are able to reduce landfill use.  

 

 

 

 

 

 



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Figure 8.3: Map Agro and Waste Concern – Creating Demand 

 

Source: Adapted from Seelos and Mair (2007) 

One of the key lessons from both Grameen/Telenor and Map Agro/Waste Concern is the ability 

to create new business models by not combining too many elements simultaneously and 

assembling via existing subsystems (Simon, 1962). The second lesson is the ability to keep 

alliance objectives separate by maintaining the process, culture and norms and maximising the 

private benefits (Seelos and Mair, 2007). In their study of two pioneering microfinance 

organisations in Bolivia – Banco Solidario and Caja de Ahorro y Prestamo Los Andes – 

Battilana and Dorado (2010) demonstrated that their success is based on the ability to create 

and maintain a common organisational identity that strikes a balance between the logics that 

they combine: a development logic that guides their mission to help the poor; and a banking 

logic that maintains profitability and their fiduciary duty to make a financial return. In doing 

so, it is important for the social business to actively develop spaces for negotiation, where the 

tensions that naturally arise between managers with a profit objective can be discussed and the 

differences negotiated (Battilana et al., 2019). The hiring and socialisation policies are 

important in maintaining this balance between the logics. In terms of hiring, the focus on 

socialisation over-ability is an important driver. Socialisation allows the organisation to recruit 

Strategic Objectives Interfaces
Strategic Objectives
(Local BOP partner)

Rural
farmers

Economic 
returns

Map Agro
Create demand

Resources

Inexpensive 
compost

Waste 
Concern

Jobs;
clean

environment

Urban
poor

Capability
redeployment



257 
 

people with no experience of either banking or development, enabling the firm to develop a 

culture of serving both objectives more effectively. Moreover, the compensation and promotion 

system was developed based on the joint objectives of approving loans targeted at the poor, as 

well as managing delinquent rates of these loans to ensure appropriate financial returns.  

In contrast, Aspire – a British firm that employed homeless people in a door-to-door 

catalogue business selling fair-trade products – failed as a result of its inability to manage these 

competing logics effectively (Tracey and Jarvis, 2006). First, Aspire adopted the franchising 

model early, which created conflict among franchisees with a need to balance making a 

sufficient financial return and the overall social objectives. Second, the firm employed many 

homeless people with little work experience and often troubles of their own, which could make 

it more difficult for them to focus their efforts on achieving the mission. Aligning business 

models and organisational design for social businesses requires an understanding of two 

principal dimensions (Santos et al., 2015). The first dimension is the extent to which the value 

created automatically spills over to the relevant parties and communities compared to being 

contingent upon interventions. For example, the provision of microcredit to women might 

create employment, which is direct, but the indirect benefits in terms of the surplus spillovers 

could be beneficial for society in terms of better healthcare and education for families.  

The second dimension is whether the clients are the same as the beneficiaries. There 

may be segments of the population that are unable to pay or gain access or who do not 

sufficiently value the benefits, which creates a dichotomy between clients and beneficiaries. 

On the one hand, mission drift is lowest in the case where the clients are the beneficiaries and 

the benefits spill over automatically. On the other hand, mission drift is highest when clients 

are not the beneficiaries and the benefits are contingent upon specific interventions, which 

might require close management of operational and impact KPIs.  



258 
 

In order to address some of these organisational challenges, a number of countries have 

developed legal structures for social businesses. For example, in the UK there are community 

interest companies (CICs), sociétés à mission in France, social enterprises in South Korea and 

benefit corporations in certain states in the United States. The legal structures are the first step, 

but social businesses need a change in mindset among corporate leaders, as well as creating a 

new norm that will evaluate the performance of firms based on financial results, and social and 

environmental impacts (Battilana, 2021). This will require appropriate metrics to be developed 

to measure the social and environmental impact, as well as the right funding opportunities for 

these social businesses. This also requires a change in mindset among not only corporate 

leaders but also investors and public authorities. And, to facilitate this change, we need to create 

a new norm, one that will dictate that we assess the performance of a firm based on not only 

its financial results but also its social and environmental impacts. 

Moreover, managing social business models requires the careful management of 

tensions, including: performing tensions – managing the differing valuations of goals and 

achievements; organising tensions – managing the organisational cultures, priority-setting and 

resource allocation; belonging tensions – managing identity-related issues; and, finally, 

learning tensions – managing the tension between short-term financial and longer-term social 

outcomes (Smith et al., 2013). Balancing these tensions results in multiple ways in which social 

business models could be configured as activity systems with different configuration logics 

that could experience various ways of evolving over time (Tykkylainen and Ritala, 2021). 

8.2 Open Innovation and Social Business Models 

Open innovation is an approach to designing products and services to leverage knowledge from 

a variety of sources to develop and exploit innovation (Chesbrough, 2003; Ahn et al., 2018). 

Openness has been shown to increase the rate of innovation (Murray et al., 2016)). For 



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example, in 1988 Harvard University granted a patent for the “OncoMouse”, a genetically 

engineered mouse. Du Pont funded research by Professor Phil Leder at Harvard Medical 

School and was given an exclusive licence to patent and hence control openness. Du Pont paid 

a fee to Harvard for the latter to disclose experimental progress, with the rights to follow-on 

commercial applications. In 1999 the restriction was lifted by Du Pont following pressure from 

the academic community. There were two effects of this openness. First, there was an increase 

in follow-on research (new researchers and new institutions); and, second, there was an 

increase in entirely new research lines (diversity of both horizontal explorations and vertical 

exploitation). Firms have adopted the concept of open innovation to increase the speed of 

product and service innovation. This is driven by increased globalisation, resulting in higher 

mobility of capital and labour coupled with higher technology intensity with a shorter product 

life cycle and complexity of R&D initiatives. These forces have led firms to innovate their 

business models using open innovation as a result of shifting industry borders from technology 

fusion across traditionally defined industry sectors. Studies have shown that there is a trade-off 

between the increased benefits of discovery and the costs of divergence in managing a large 

pool of stakeholders and the associated coordination costs (Boudreau, 2010; Laursen and 

Slater, 2006).  

For example, in 2000 P&G set a target to source more ideas from outside the 

organisation as a result of the stagnation of its R&D productivity (Huston and Sakkab, 2006).  

A. G. Lafley, the CEO of P&G, made it a goal to source 50 per cent of innovations from outside 

the firm as part of its Connect and Develop (C&D) Strategy. When P&G wanted to develop 

Pringles potato crisps with trivia jokes printed on them, it discovered from its European 

network that a small bakery in Bolgna (Italy), run a by a university professor, had already 

developed the edible ink. Ordinarily, it would have taken P&G over two years to develop such 

an ink, but, through the process of C&D, it was able to leverage the edible ink technology – 



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with the Bologna bakery compensated appropriately – and develop a successful product 

quickly. There are two forms of open innovation: inbound open innovation; and outbound open 

innovation (Chesbrough, 2003). Inbound open innovation involves leveraging the discovery of 

others, while in outbound open innovation an external organisation’s business model might be 

better suited to commercialising the innovation compared to the focal firm.  

The concept of open innovation has been studied extensively in relation to firms’ 

economic performance and resilience (Ahn et al., 2018). These include, among others, GE’s 

First Build – an open innovation platform for designers and engineers to share ideas with other 

members to create new home appliances; and LEGO Idea – where customers can create their 

own LEGO sets, which are voted upon by other users before being selected for production 

(Chesbrough, Vanhaverbeke, and West, 2017).  More recently, scholars and practitioners have 

become increasingly interested in how open innovation could be used to develop innovative 

business models to address society’s grand challenges by leveraging the diverse set of 

collaborative partners (Ahn et al., 2019). For example, governments have increasingly been 

using open social innovation initiatives to address public needs (Mair and Gegenhuber, 2021). 

Governments worldwide typically have data sets that could be turned into applications to serve 

citizens’ needs. Governments in Malaysia, India and Poland have created portals that allow 

data sets to be used free of charge. The city of Toronto organised a hackathon in 2015 by 

encouraging the public to delve into open data to fix Toronto’s traffic troubles. The city 

governments in Denmark and Austria have created open government labs to stimulate social 

innovation by creating spaces for experimenting and developing propositions to address social 

problems via crowdsourcing ideas. 

Crowdsourcing for social innovation has also led to innovative business model design 

(Kohler and Chesbrough, 2019), for example, Travel to Change (T2C). T2C was initially 

developed as an integrator platform to organise week-long volunteer trips. Creators would 



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submit ideas, which would be voted upon; a jury would then select the travel idea to develop 

and a travel partner would develop the trip. The first iteration did not succeed, as it was based 

on volunteer trips to contribute to social change. The pivot is where participants pay for hours-

long (within the day) and impactful activities. Participants can create a list of activities that 

they want to undertake, which is then vetted by T2C and provided by local communities via a 

matching process on a multi-sided platform. The participants pay for the service, which covers 

the cost of the T2C platform. Activities include cleaning up beaches that have marine debris or 

supporting the craft of growing chocolate among cocoa farmers in Hawaii.  

Another example of an open innovation business model for social purposes is the 

OpenMRS initiative, which was used for different forms of inbound and outbound open 

innovation as it grew from a local to a global provider of healthcare software. The OpenMRS 

mission was to “Write Code, Save Lives” and it was founded by doctors. It is a free open-

source software initially created to address the burdensome administrative procedures needed 

to handle data for treating AIDS patients in Kenya following the increased financial 

commitment provided by the US president’s Emergency Plan for AIDS Relief (PEPFAR) and 

a non-profit organisation for distribution of the ART drug. OpenMRS can be adopted and 

modified based on open-source principles, is suitable for use in resource-poor environments 

and can be modified easily without programming through the addition of new data items, forms 

and reports.  

There are four major challenges in open-innovation-based social business model 

development: (a) causality identification – it is often not clear what impact can be attributed to 

which cause; (b) attribution – it is difficult to attribute impact, as it can be diffuse, complex and 

contingent; and (c) evaluation timescale – premature impact measurement may result in 

policies that overemphasise the short-term results (Ahn et al., 2019). There are tools being 

developed such as Corporate Social Performance, which provides a qualitative measurement 



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of the environment, governance and social performance of firms. Although still focused on the 

organisation, these frameworks will need to be developed further in light of the various case 

experiences in order to more comprehensively develop and measure the performance of the 

social business models.  

8.3 Market Failures and Corrective Business Model Design  

There are instances where the market is unable to serve recognised or unrecognised needs that 

could significantly improve the welfare of society. An example of this is the case of agricultural 

output. In India two-thirds of the population are dependent on agriculture for a livelihood; 

however, agriculture is a risky business that is subject to price, climate, geological and 

biological risks (Banerjee and Bhattacharya, 2011). Moreover, many farmers have small 

landholdings of less than one hectare, with a growing share of small landholdings over time 

(Banerjee and Bhattacharya, 2011). One of the consequences of this is that farmers do not 

plough the full acreage of their farms in order to hedge against various risks, depending on the 

type of crops, resulting in severe economic hardship. The incomplete utilisation of the land 

implies a loss of agricultural output, and hence productivity, and the market forces do not 

necessarily have a mechanism to correct such challenges in resource utilisation.  

Indian agriculture production and income suffers from large year-to-year fluctuations 

because of the variability in distribution and timeliness and variations in rainfall, prices and 

availability input that are necessary for each crop (Banerjee and Bhattacharya, 2011; Rathore 

et al., 2011). To address these risks, the Indian government introduced various crop insurance 

schemes, such as the one by the General Insurance Corporation of India (GICI) in 1972, which 

was modified and remodified as the Comprehensive Crop Insurance Scheme (CCIS) in 1985 

and the Experimental Crop Insurance Scheme (ECIS) in 1997. These programmes required 

farmers to pay a premium, with a certain insured sum for the loans they were taking, with pay-



263 
 

out contingent upon risks such as adverse weather conditions, cyclones and floods. The 

programmes were not scalable, as they were run for specific crops in certain geographical 

regions. The National Agricultural Insurance Scheme (NAIS), or “Rashtriya Krishi Bima 

Yojna”, was introduced in 1999–2000 in order to scale up the previous CCIS and ECIS 

programmes (The World Bank 2012). It was taken over by the Agricultural Insurance Company 

of India (AICL) in 2003. All of these types of crop insurance protected farmers against crop-

yield fluctuations. In the case of NAIS, the farmers’ premium was subsidised and aggregate 

claims over the farmers’ premium were jointly funded by the national and state governments, 

respectively. Although various schemes have been tried, their success has been mixed – with 

low take-up due to a lack of awareness, a lack of full coverage across states, and the selection 

of coverage for larger farmers, among others.  

New business models might be required to overcome such challenges in providing 

agriculture insurance schemes (Shah et. al., 2008). One example of such a scheme considered 

ways to enhance the take-up of weather-related insurance products without increasing the cost 

for farmers, as illustrated in Figure 4. A large proportion of fertilisers is purchased via the 

Farmers’ Fertiliser Cooperative. Farmers are automatically insured for their crops based on the 

amount of fertiliser purchased each season – assuming that a farmer with a larger landholding 

will buy greater amounts of fertiliser. The pay-out for farmers is based on certain rainfall 

thresholds and dependent on the fertiliser purchased. The protection of downside risk for 

farmers without incurring additional costs would most likely incentivise them to increase the 

acreage planted in their land. Part of the increased revenue received from the increased volume 

of fertiliser purchases by the Farmers’ Fertiliser Cooperative is channelled into an insurance 

company as the insurance premium that is used for the pay-outs, depending on the weather 

outcomes. This is an innovative business model design that is, in principle, able to increase 

insurance coverage for all farmers purchasing fertilisers without increasing their costs, which 



264 
 

could contribute to increased agricultural output while protecting farmers against adverse 

economic conditions. The success of such a venture will principally be dependent on the 

elasticities of increased fertiliser purchase, in addition to the actuarial risks related to the 

weather. 

Figure 8.4: Weather Risk for Farmers 

  

Source: Adapted from Shah et al. (2008) 

A variation of such a business model innovation that aligns incentives to solve agricultural risk 

is through leveraging under-utilised resources. Farmers often face risks but are unable to pay 

the premiums for weather-related insurance policies, and climate change is driving an increase 

in the frequency and intensity of such weather-related risks. Oxfam, a global charitable 

organisation, and Swiss Re, a global reinsurance company and its partners, addressed this 

through a novel solution in the drought-prone northern state of Tigray in Ethiopia through 

improved risk reduction, risk transfer and managed risk-taking via resource management, 

insurance and microcredit, respectively (Oxfam, 2009). The programme was called the Horn 

of Africa Risk Transfer for Adaptation (HARITA). The farmers came up with the suggestion 

of using their labour time to contribute to building irrigation systems, compost-making and soil 

Farmers 
Fertilisers Cooperative

Insurance 
Premium

Rupees

Fertiliser

Premium

Payout based triggers 
on amount of land/fertilisers purchased



265 
 

management, which contributes to a reduction of risk from the unpredictable weather. In turn, 

funds donated via charitable agencies such as the Rockefeller Foundation are donated to a risk-

transfer company such as Swiss Re, which pays out to farmers if there is a drought and the 

rainfall drops below a certain predetermined threshold. Such a scheme, which has a unique 

business model combining a charitable and a profit-making organisation, protects farmers from 

having to sell productive assets and enables them to buy the seeds needed to plant the following 

year’s crops.  

Figure 8.5: Horn of Africa Risk Transfer for Adaptation (HARITA) Programme 

  

Source: Adapted from Oxfam (2009) 

Market price fluctuations constitute another risk that farmers face. For example, in India 

farmers often have poor access to information that could help them with cultivation, as well as 

selling their produce. Often, farmers have to take their produce to nearby markets that might 

be several miles away; sometimes markets have an oversupply, resulting in a significant 

reduction in market prices, and sometimes there is insufficient supply, with prices tending to 

increase significantly. Moreover, there are often middlemen who take advantage of the lack of 

market price information to take an extraordinarily high proportion of the final customer price, 

Risk-reduction programmes
(irrigation, compost making, 

agroforestry, etc)

Insurance and 
credit Institutions 
(e.g., Swiss Re)

Labour

Weather insurance

Premium

Payout based triggers 
such as rainfall (uses satellite data)

Oxfam, World Food programme



266 
 

leaving farmers with subsistence-level incomes. In order to overcome such a challenge, in 

October 2007 Thomson Reuters set up Reuters Market Light (RML), a mobile-based 

information service for farmers (Velu and Prakash, 2010). RML provided a personalised 

professional information service to the farming community ($5 per quarter), including spot 

crop prices, localised weather forecasts, crop advisory and commodity news and information. 

The service was initially delivered by mobile phone subscriptions in local languages to more 

than 1 million farmers in over 35,000 villages, and to a selected number of states, before rolling 

out nationally. The advantages of RML have been significant, with benefits within five years 

of $2–3 billion in income for farmers, while over 50 per cent of them reduced their spending 

on agricultural input. This is exemplified by the following quote by a farmer on the benefits of 

having market prices: “Knowledge of market prices has made it easier to sell produce at good 

rates.” And on the benefits of weather forecasts: “RML’s weather forecasts have made it much 

easier to protect my crops. [And] RML’s crop advisories are excellent. I have learnt a lot. My 

tomato plants are lasting longer now because I know the right fertilisers and medicines for 

them (Velu and Prakash, 2010, pp. 80–1).  

A related concept that fosters business model innovation is frugal innovation, which is 

characterised by a low-cost, flexible and inclusive approach. There are various related 

innovation concepts that encapsulate “do-it-yourself” improvisation, including jugaad 

innovation in the Indian context, gambiarra or jeitinho in Brazil, kanju in parts of Africa, 

juakali in Kenya and jiejian chuangxin in China (Prabhu and Jain, 2015; Radjou, Prabhu, and 

Ahuja, 2012). An example of frugal innovation is the business model developed by SELCO, a 

rural energy service company in India (Prabhu and Jain, 2015). SELCO’s mission was to 

provide solar lighting solutions to Indians living in rural areas who do not have access to 

electricity and who use kerosene lamps to light their homes. SELCO needed to make solar 

lamps as cheap as kerosene lamps in order to make them affordable for the rural community, 



267 
 

so it devised an innovative business model. The company trains local people in rural villages 

to manage and maintain solar panels and batteries; and an arrangement is made with a bank for 

local people to take out a loan guaranteed by SELCO. The local person becomes an 

entrepreneur by setting up shop with solar panels, which are used to charge lamps supplied by 

SELCO at an affordable price. The lamps are rented to local villagers at a cost per lamp that is 

equivalent to kerosene lamps; the villagers are therefore incentivised to rent the lamps and the 

local entrepreneur makes enough returns to be able to pay back the loan. In this innovative 

approach, SELCO, a profit-making entity, is able to deliver solar lighting to the rural 

community, which has the benefit of being more economical, healthy, not a fire hazard and 

brighter than kerosene lamps.  

The concept of frugal innovation has also been adopted by large multinational firms, 

such as Tatas, with Tata Nano and GE’s Mac 400 ECG machine. Tata Nano was a compact 

city car priced affordably for Indian consumers.51 GE’s Mac 400 electrocardiograph (ECG) 

low-cost handheld machine was developed in the Indian market to enable examinations to be 

carried out at the homes of patients who would otherwise have had to travel long distances to 

medical centres to receive treatment. The portable ECG machine first developed in India 

enabled GE to adopt a reverse innovation process to take the product to developed countries 

(Immelt, Govindarajan, and Trimble, 2009). Frugal innovation propositions in the healthcare 

sector have also been shown to create value for the entire healthcare system by generating 

overall efficiency gains (Winterhalter et al., 2017). This is achieved by allowing basic 

examinations to be done outside hospitals, which frees up specialists in hospitals to focus on 

 
51 Tata Nano was loss-making for Tatas and was closed for production in 2018. There are various analyses for 
why Tata Nano did not take off, among them technical faults and being less than comfortable. In addition, 
prospective Indian consumers did not want to be seen to acquire the “cheapest” car, which denotes a lowly 
status. Instead, Tata Nano was seen to have niche appeal among the wealthy, being seen as cute and funky (The 
Wire, 2018). 



268 
 

severe health cases, enabling the efficient distribution of scare resources in the local healthcare 

system.  

8.4 Discussion 

Organisations that work with the world’s poor need to measure their success to ensure that they 

provide the feel-good factor that is needed to continue to drive the success of their initiatives 

(London, 2009). VisionSpring provides a case vignette for how to measure the success of these 

social development initiatives. VisionSpring sells reading glasses through a microfranchising 

programme, hiring poor people, training them to become vision entrepreneurs and providing 

them with a business in a backpack, which contains reading glasses. The vision entrepreneur 

goes to a village and sets up “camp” for three days in order to test the eyesight of the villagers. 

Many of the villagers are tailors, mechanics and artisans, meaning clear sight is needed to 

continue their livelihoods and support their families. The mission of VisionSpring is to provide 

vision to these villagers in order to reduce poverty through the sale of affordable glasses. Its 

success can be measured broadly in three main areas: changes in economics; changes in 

capabilities; and changes in relationships across the key stakeholders such as sellers, buyers 

and communities.  

For example, for sellers, measures of success include increased income to be able to 

support their families, which in turn might improve communication skills and an improved role 

in the family, as there will be less financial stress. For buyers, it could contribute to increased 

productivity from their jobs, improved contentment due to better vision and, finally, a better 

professional reputation. Finally, from a community perspective, there could be increased 

interest from other businesses due to the improved productivity of the artisans, in addition to 

high aspirations of the women in the community, which could lead to greater gender inequality. 

Therefore, tracking such performance indicators must cover both quantitative and qualitative 



269 
 

indicators to be able to share the positive results and hence motivate the immediate stakeholders 

and the wider community.   

Studies have also highlighted the stance taken by both managers and scholars to address 

the challenging aspects of designing business models for social economic development. The 

book Fortune at the Bottom of the Pyramid (BOP)52 by C. K. Prahalad highlighted that large 

multinational companies should not view people who live on less than $2 a day as marginal to 

the process of globalisation, rather embracing them as resilient entrepreneurs and value-

conscious customers (Prahalad, 2006). Gupta (2020) provides a reasoned critique of such a 

view of reification of consumers at the bottom of the pyramid as having “entrepreneurial” traits 

that need to be harnessed for the betterment of society given the right incentives. Such a view 

might overly attribute the locus of social problems such as poverty and joblessness to 

individuals themselves, as opposed to institutional, social, political and economic dysfunctions; 

hence, unwittingly it might desensitise poverty and normalise economic upheavals and life at 

the BOP. This, in turn, might limit the field of possible actions that can be initiated by the 

vulnerable people at the bottom of the pyramid. Therefore, it is important for managers to think 

reflexively when designing social business models about the implications of the power balance 

between partners in order to ensure that there is a fair outcome for society as a whole.  

Studies have highlighted the need to examine business models that might cause 

oppression (human stakeholders) or depletion (non-human stakeholders) exclusion in certain 

communities (Marti, 2018). For example, new business models able to respond appropriately 

to a scarcity of minerals and metals with complex business models might not fully appreciate 

how they translate into practices of child labour, low salaries or hazardous working conditions 

at the end of the complex supply chain. Moreover, some microfinance initiatives might exclude 

 
52 Also known as the base of the pyramid.  



270 
 

certain strata of society based on gender and other communal strictures and practices, which 

reinforces some of the deprivation that the programme set out to address. To address these 

concerns, business models designed to address the grand challenges53 of society need to have 

four elements: participatory forms of architecture – whereby there are structures and rules to 

enable diverse and heterogenous actors to interact constructively; multivocal inscription – 

capturing the need to combine all opposing perspectives to get a better idea of the main 

problems; scaffolding – unlocking entrenched social norms and building alternative social 

orders; and proximity – building the ethics of care and concern for others as neighbours in a 

moral sense (Marti, 2018).    

Scholars have also highlighted that BOP initiatives need to focus on capability 

development and social capital-building as part of poverty alleviation and the role of business 

in empowering communities (Ansari, Munir, and Gregg, 2012). The focus of the traditional 

welfare approaches of choice and desire fulfilment might be inadequate (Sen, 1985; Putnam, 

1995). For example, Hindustan Unilever’s “Fair and Lovely” skin-whitening face cream, a 

profitable brand, may have reinforced beauty stereotyping in India based on the premium 

placed on fair skin compared to dark skin. In this context, business models targeting the BOP 

need to be evaluated on the basis of how well they advance capability transfer, diffusion and 

retention by preserving and enhancing social capital within the community, as well as other 

resource-rich networks.54  

8.5 Conclusion 

 
53 Grand challenges are complex problems with significant implications and no clearly defined solutions (Ferraro 
et al., 2015).  
54 These include structural social capital – the ties and network configuration of the society; relational social 
capital – pertaining to trust and the type of relationship; and cognitive social capital – covering shared language, 
identities, beliefs and norms (Ansari, Munir, and Gregg, 2012). 



271 
 

Market solutions and government interventions alone are inadequate to solve major global 

issues such as healthcare, poverty, education and general well-being (George et al., 2012); and 

such problems are more complex in countries with limited resources. A major part of 

addressing these challenges is the need to design innovative business models to build markets 

where there could be institutional voids, whereby certain institutions that typically provide the 

legal structure and set the rules of exchange might not exist (Khanna et al., 2010). In addition, 

these markets could display a lack of knowledge from both the supply and demand perspectives 

(Seelos and Mair, 2007). Business models need to be interactive by functioning with, and 

within, the ecosystem in order to help develop the resources and institutions by working with 

partners and even competitors (Howell et al., 2018).  

The Trans-African Hydro-Meteorological Observatory (TAHMO) illustrates the 

importance of designing business models by developing markets to overcome institutional 

voids and working with an ecosystem of partners (Howell et al., 2018; Van de Giesen, 2014). 

TAHMO stepped in to provide a public good, as the governments in Africa were cutting down 

on their provision of reliable weather data, which is crucial for the productivity of farmers in 

Africa, having over 65 per cent of the world’s arable land (African Development Bank, 2016). 

TAHMO was started by Delft University of Technology and Oregon State University in order 

to improve the poor weather-monitoring practices on the African continent through the 

deployment of low-cost, simple and robust ground-weather stations. TAHMO uses high-

technology sensors through frugal engineering to monitor weather using ground stations. 

Ground stations use solar panels and mobile networks and have integrated sensors that measure 

rainfall, shortwave radiation, wind speed, wind direction, barometric pressure, air temperature 

and relative humidity; they have no moving parts and are low maintenance.  

Formally, TAHMO is a registered international NGO but it adopts a commercial 

approach to the diffusion of weather stations by combining education for schools with the sale 



272 
 

of data to different service providers across various African countries. The weather data from 

the local stations needed to be enhanced with specific niche requirements and hence needed 

different ecosystems of partners. TAHMO started with a “buy-one, pay-two” programme, 

whereby schools in a developed country pay for the cost of two schools, with the second school 

located in Africa, which hosts the ground station. The programme allows schools to enrich their 

curriculum with lessons about the environment, weather, electronics and computer science. For 

example, the data collected by the ground stations is then sold to an IT start-up in Rwanda that 

provides simple SMS-based weather-prediction information to small farmers. In East Africa 

the data is sold to Acre, a micro crop insurance company that uses more accurate weather data 

to reduce the premiums on weather insurance for farmers. The weather data typically allows 

the insurance of crops with a value that is multiple times the cost of the station. TAHMO aims 

to resolve the major issue of a lack of weather forecasting for farmers in Africa to manage 

climate mitigation and adaptation. However, the distribution of data requires access to the 

Internet, which not all farmers have. This could promote less inclusion, which is a major 

problem that needs to be addressed.  

There are a number of areas for further investigation of business model innovation for 

socio-economic development, with the first being how frugal innovation business models for 

socio-economic development could affect the mental models of the population. For example, 

there have been claims that the low-cost and low-resource nature of jugaad innovation, which 

focuses on improvisation, might instil a mental model of “making do” (Nelson, 2018). 

However, the case of TAHMO shows that frugal innovation can be based on the most advanced 

technology coupled with innovative business models. The second area is how business models 

developed for socio-economic development might create inequality as a result of exclusion. 

The additional complication for socio-economic business models needs to factor in the lack of 

knowledge and resources, which could have unintended negative consequences or even 



273 
 

reinforce certain cultural norms and practices, thereby worsening the existing socio-economic 

development issues. Hence, entrepreneurs and established firms need to recognise these issues 

when designing and managing business models for socio-economic development purposes. 

The third issue is how better to manage the tension between the business and social objectives 

in start-ups compared to established firms. What are the leadership and organisational issues 

to enable such paradoxes to be managed efficiently? Are the mechanisms different or similar 

among start-ups and established firms? Is there a basis for theorising the management of the 

paradoxes as a duality in such a way as to enhance the value creation and value capture from 

such socio-economic business models?  

This chapter has provided an overview of the opportunities and challenges of addressing 

socio-economic development issues such as healthcare, education and poverty through 

business model innovation. These issues need to be addressed to ensure an inclusive growth 

agenda for the world to maintain economic growth and well-being within a peaceful 

environment. We propose a number of key research issues on this topic.  

 

 

 

 

 

 

  



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CHAPTER 9: CONDUCT RISK AND BUSINESS MODELS 

 

  



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CHAPTER 9: CONDUCT RISK AND BUSINESS MODELS 

 

It is better to be roughly right than precisely wrong. 

(John Maynard Keynes) 

 

9. Introduction 

The global financial crisis (GFC) of 2008 had a significant impact on the operation of both 

financial and other markets around the world (Bernanke et al., 2019). The collapse of Lehman 

Brothers on 15 September 2008 sent shock waves around the world, resulting in a significant 

decline in the stock markets globally. The GFC was extremely detrimental to borrowers, 

investors and other stakeholders, including the freezing of financial markets through 

misinformation and conflicts of interest (Meeks and Velu, 2018).55 One of the major 

developments following the crisis has been the focus on the notion of conduct risk, which is 

broadly defined as any action of a regulated firm or individual that leads to customer detriment 

or which has an adverse effect on market stability or effective competition (FCA Handbook, 

2021). Customer detriment occurs when customers are damaged or harmed, financially or non-

financially. It is important to emphasise that non-financial detriment includes psychological 

effects, including distress and inconvenience, and that customers need not necessarily be aware 

that they have suffered detriment. The UK regulatory authority, the Financial Conduct 

Authority (FCA), were the pioneers in developing the framework for regulating conduct risk 

(Financial Times, 2012).  

Conduct risk can be seen as different to the conventional risk that financial services 

firm usually manage, such as market risk, credit risk and operational risk, which are internally 

 
55 This chapter is based on research and executive education courses on conduct risk delivered together with 
Professor Geoff Meeks to some of the major global financial institutions. I would like to express my grateful 
thanks to Professor Meeks for sharing his wealth of knowledge and insights on this topic.    



280 
 

focused and have an immediate effect on the profits of the bank from a failure to manage them 

well. Conduct risk, unlike the other types, relates to the external risk to protect consumers, 

financial markets and competition. Conduct risk arises as a result of information asymmetry 

and conflicts of interest; hence, it has significant implications for the design of business models 

(Meeks and Velu, 2018). This chapter provides an overview of how information asymmetry 

and conflicts of interest arose in the subprime mortgage supply chain. We then look at the 

business model design of the major investment banks and other firms within the supply chain 

in order to examine the business model design underpinning some of the conduct-related issues. 

We draw lessons from other industries in order to overcome such conflicts of interest with a 

view to designing appropriate business models. The next section reviews the subprime 

mortgage market and goes on to discuss how conflicts of interest arose from the design of 

business models. The subsequent section discusses the implications for business model design 

to manage conduct risk before the chapter concludes. 

9.1 Subprime Mortgage Supply Chain 

Financial institutions play an important part in the intermediation between borrowers and 

savers of funds by managing the appropriate transformation of the various risks, such as 

liquidity, market prices and credit, among others. In doing so, they provide an important service 

to the economy in order to ensure the appropriate returns to savings and to fund economic 

growth and development. However, the very act of financial intermediation could contribute 

to information asymmetry and conflicts of interest. Information asymmetry arises when 

information is distorted or withheld by the bank from the client and/or the market; and conflicts 

of interest arise as a result of the interests of the bank and employees – or the bank and clients 

– being in conflict (Meeks and Velu, 2018). Let us examine the subprime mortgage supply 

chain to see how such information asymmetry and conflicts of interest might arise.  



281 
 

Let us assume that Betty wants to buy a house and does not have enough savings to do 

so. Lucy, on the other hand, has funds to save and wants a good return on her savings. Lucy 

could lend directly to Betty but would not want to do so, as this would expose Lucy to the risk 

of default by Betty. Hence, the banks and other related financial institutions act as 

intermediaries in order to transform such direct lending risks. In 2001 the George Bush 

administration pushed hard to expand home ownership, especially among minority groups in 

the United States. This quote from President George Bush in 2002 encapsulates this policy 

(New York Times, 2008): 

We can put light where there's darkness, and hope where there's despondency in this country. 

And part of it is working together as a nation to encourage folks to own their own home.  

Almost every case of detriment actually begins with good intentions – a product or service 

designed to benefit the customer. However, in the process of intermediation, various 

information asymmetries and conflicts of interest cause detriment to customers and markets.  

Returning to our case, Betty embraces the Bush administration’s policy of home 

ownership and borrows money from New Century, a major mortgage provider in the United 

States. New Century originates Betty’s mortgage and bundles it with some 5,000 others. 

Citigroup buys the bundle of mortgages and issues securities backed by the mortgages, called 

mortgage-backed securities (MBS). Citigroup asks Moody’s, the credit rating agency, to rate 

the mortgages. Strategos, an investment advisory firm in the real-estate securities market, then 

buys a portion of a lower-rated tranche of Citigroup securities, bundles them with similar 

tranches of low-rated MBS and funds the collateralised debt obligations (CDOs) with bonds. 

Strategos similarly asks Moody’s to rate these CDO securities. Lucy then buys some of the 

CDOs as an investment vehicle for her savings in order to get a healthy return. In doing so, 

Lucy has, through the intermediation enabled by the mortgage supply chain, indirectly lent her 

savings to Betty to buy a house. The mortgage value chain is summarised in Figure 1. 



282 
 

Figure 9.1: Subprime Mortgage Supply Chain 

  

Source: Adapted from FCIC Report (2011) 

The mortgage originators had developed a product called option adjustable-rate mortgages 

(option ARMs), where borrowers had a reduced interest rate to pay in the initial years, which 

made them affordable, and were then charged above the average rate thereafter. In fact, 

borrowers could choose how much to pay each month as part of the “Pick a Pay” scheme. Any 

shortfall was added to the principal through a negative amortisation scheme. The option ARM 

was a widely used product among mortgage originators such as New Century, Washington 

Mutual and other firms in the United States ahead of the crisis in subprime mortgages. When 

the low initial interest rates increased, borrowers could: (1) refinance with another initial rate 

mortgage; (2) sell their homes and repay their mortgage; or (3) default – and the lender would 

sell the house to recoup the lending. The mortgage originators earned substantial origination 

fees, which were often added to the principal being borrowed. In addition, there were 

substantial interest rate margins once the teaser period had elapsed. Finally, there were capital 

gains if the home was repossessed and sold at a profit in a rising market. Hence, the mortgage 

originators provided substantial incentives for sales staff to sell option ARMs, as they were 

very profitable. For example, Countrywide option ARMs retained on the balance sheet grew 

Mortgage 
Borrower

(Betty)

Mortgage 
Originator Bank

Credit 
Rating 
Agency

Bank
Credit 
Rating 
Agency

Lender buys 
bonds
(Lucy)

New Century 
originates 

Betty’s mortgage and 
bundles it with some 

5,000 others

Citigroup buys the 
bundle of mortgages 
and issues securities 

backed by the 
mortgages

Moody’s rates the 
securities

Strategos buys a 
portion of a lower-rated 
tranche of the Citigroup 
securities, bundles with 
similar tranches of low 
rated MBS, and funds 
the CDO with bonds

Moody’s rates the 
securities

Making loans 
accessible to 

previously 
excluded 
groups

Expanding the 
supply of funds for 

home loans

MBS –Mortgage-Backed Securities
CDO – Collateralised Debt Obligations



283 
 

from $5 billion in 2004 to $26 billion in 2005 and $33 billion in 2006. The CEO of 

Countrywide, Angelo Mozilo, said (Financial Crisis Inquiry Commission Report, 2010, p. 

105): 

Countrywide was one of the greatest companies in the history of this country and probably 

made more difference to society, to the integrity of our society, than any company in the history 

of America.  

The mortgage originators, in turn, had an incentive to sell these mortgages to banks such as 

Citibank to free up their balance sheets to obtain new funds in order to originate even more 

mortgages.  

Credit-rating agencies, such as Moody’s, played a role in enabling this securitisation of 

mortgages to take place across the mortgage supply chain. The central role of the rating 

agencies was to mitigate information asymmetry. Banks, in turn, needed their ratings to 

determine what amount of capital to hold, as BBB-rated securities required five times as much 

capital as AAA- and AA-rated securities. Many investors relied on these credit ratings because 

they had neither access to the same data nor the capacity and analytical ability to assess the 

securities they were purchasing (Financial Crisis Inquiry Commission (FCIC) Report, 2011, 

pp. 118–22). The lower-rated mortgage-backed securities were more difficult to sell given the 

restrictions placed on some institutional investors, such as pension funds, to hold only A-rated 

securities and above.  

Collateralised debt obligations (CDOs) are structured financial instruments that pool 

these lower-rated mortgage-backed securities. The CDO manager buys lower-rated mortgage-

backed securities and bundles them together to get diversification benefits. CDO securities 

were sold in tranches, with risk-tolerant investors securing a higher yield but taking the first hit 

should the underlying investments perform badly, with the risk-averse investors getting a lower 



284 
 

yield but taking the last hit. These CDOs were then rated again by Moody’s. For example, 88 

per cent of one of the CDOs, Kleros III bonds, were being AAA-rated when they were 

composed of mortgage-related securities, of which 45 per cent were rated as BBB or lower and 

16 per cent as A. Moody’s reasoned that pooling many BBB-rated mortgage-backed securities 

would lead to additional diversification benefits: if one security went bad, the second had only 

a very small chance of going bad at the same time. Only those investors at the bottom would 

lose money (and were compensated by a higher yield). It was reasoned that there would be few 

defaults at any one time. Moody’s model “had put little weight on the possibility that prices 

would fall nationwide”. “Even as housing prices rose to unprecedented levels, Moody’s never 

adjusted the scenarios to put greater weight on the possibility of a decline”. “Moody’s position 

was that there was not a … national housing bubble” (FCIC Report, 2011, pp. 120–21). This 

was because, in the preceding 50 years, there had never been an instance where all parts of the 

United States had exhibited a fall in house prices simultaneously. Moody’s model and data 

were based on this assumption and did not factor in the possibility of falling house prices 

simultaneously across the United States, which is what happened during the global financial 

crisis. Of all mortgage-backed securities that it had rated triple A in 2006, Moody’s 

(subsequently in the crash) downgraded 73 per cent to junk (FCIC Report, 2011, p. 122).  

Moody’s income was driven by rating MBS. The fee for rating MBS was as much as 

three times the fee for rating corporate bonds; half of Moody’s ratings income in 2007 came 

from rating MBS. Hence, it was conflicted in its business model by relying heavily on the 

income being paid by the issuers of the securities. The investment banks threatened to withdraw 

their business if they did not get their desired rating. This was encapsulated in a comment from 

Gary Witt, Moody’s former team managing director covering US derivatives (FCIC Report, 

2011, p. 210): 



285 
 

Oh God, are you kidding? All the time. I mean that’s routine. I mean they would threaten you 

all of the time … It’s like, “Well, next time, we’re just going to go with Fitch and S&P”.   

Richard Malek, former Moody’s vice president and senior credit officer, said:  

The threat of losing business to a competitor, even if not realised, absolutely tilted the balance 

away from an independent arbiter of risk towards a captive facilitator of risk transfer.  

Moreover, there was evidence that the investment banks were selling securities to investors as 

agents and trading in them as principals, as noted in the quote below from Senator Carl Lewin 

questioning the CEO of Goldman Sachs, Lloyd Blankfein (Louis and Zinkin, 2019, p. 30): 

Goldman was selling securities to people and not telling them that they were taking and 

intending to maintain a short position against those same securities. 

There was evidence that the conflict of interest was showing up among some of the more 

sophisticated clients in Bear Sterns’ Structured Credit Fund, which made good returns when 

the credit market was booming between 2004 and 2006. However, in early 2007 the sub-prime 

mortgage market started to turn down and the price of mortgage securities began to decline. 

Investors were demanding their money back as the value of the funds started to decline rapidly. 

Employees of Bear Sterns tried to soothe them by saying that the funds offered an “… awesome 

opportunity …” and that “… we’re very comfortable with where we are …”. However, in 

private emails to colleagues, they expressed their concerns: “… I’m fearful of these markets 

…” and “… It’s either a meltdown or the greatest buying opportunity ever. I’m leaning more 

towards the former …” (Mintz, 2008). The next section seeks to better understand how 

information asymmetry and the design of the business model resulted in such conflicts of 

interest and hence contributed to the increase in conduct risk, with the consequence of being 

detrimental to clients and markets, respectively. 

 



286 
 

9.2 Business Models and Conflicts of Interest 

In a written testimony dated 7 December 2011 by Professor Arthur E. Wilmarth Jr (Professor 

of Law, George Washington University Law School, Washington DC) to the Subcommittee on 

Financial Institutions and Consumer Protection on Banking, Housing and Urban Affairs, 

United States Senate, the professor said: 

The financial crisis has also proven, beyond any reasonable doubt, that large financial 

conglomerates operate based on a hazardous business model that is riddled with conflicts of 

interest and prone to speculative risk-taking. 

Financial conglomerates have never demonstrated that they can provide beneficial services to 

their customers and attractive returns to their investors without relying on safety net subsidies 

during good times and massive taxpayer-funded bailouts during crises. It is long past time for 

LCFIs (Large, Complex Financial Institutions) to prove – based on a true market test – that 

their claimed synergies and their supposedly superior business models are real and not 

mythical. 

Arguably, there is some merit in Professor Wilmarth’s statement about the business models 

among the LCFIs, as there could be a tendency to take excessive risks during good times if 

firms believe that they will be bailed out using taxpayers’ money during less sanguine times. 

This is what economists term the moral hazard problem, whereby firms might lack the incentive 

to guard against risk when they are effectively protected from its consequences by a form of 

government insurance (Pauly, 1968). In order to examine this phenomenon, it is worth 

exploring in more depth the failure of Lehman Brothers and the other associated firms during 

the global financial crisis.  

 The excerpts from Management’s Discussion and Analysis of Financial Condition and 

Results of Operations from the 2007 Annual Report of Lehman Brothers, which was the last 

report before the Chapter 11 bankruptcy protection, mentions: 



287 
 

On the basis of a record first half and a reasonably successful navigation of difficult market 

conditions in the second half, we achieved our fourth consecutive year of record net revenues, 

net income and diluted earnings per common share in 2007.  

The statement in the Management Discussion appears to be consistent with the results reported 

by Lehman Brothers, as shown in Figure 2. 

Table 9.1: Income Statement of Lehman Brothers 

 

Source: Annual Report of Lehman Brothers 

In addition, the Auditor’s Report by Ernst & Young LLP from the 2007 Annual Report stated: 

We also have audited, in accordance with the standards of the Public Company Accounting 

Oversight Board (United States), the consolidated statement of financial condition of the 

Company as of November 30, 2007 and 2006, and the related consolidated statements of 

income, changes in stockholders’ equity, and cash flows for each of the three years in the period 

ended November 30, 2007 of the Company and our report dated January 28, 2008 expressed 

an unqualified opinion thereon.  

The auditors, Ernst & Young, had provided an unqualified opinion on the last financial 

statement of Lehman Brothers, implying that the figures showed a true and fair view of the 

business performance of Lehman Brothers and that there were no material misstatements. It is 

therefore puzzling that Lehman Brothers collapsed a few months after such a positive financial 

Lehman Brothers

Income Statement

in US$ million 2005 2006 2007

Net revenues 14,630 17,583 19,527

Net income 3,260 4,007 4,192



288 
 

performance. To explore this, let us get a better understanding of its business model. There was 

a significant shift in the business model of Lehman Brothers before the GFC from agent to 

principal. This is encapsulated in the statement below (FCIC Report, 2011, p. 177): 

Then, in its March 2006 “Global Strategy Offsite,” CEO Richard Fuld and other executives 

explained to their colleagues a new move toward an aggressive growth strategy, including 

greater risk and more leverage. They described the change as a shift from a “moving” or 

securitization business to a “storage” business, in which Lehman would make and hold longer-

term investments. 

In order to see the implications of this shift in strategy, and hence business model, we need to 

examine closely the balance sheet of the firm, which is shown in Figure 3.  

Table 9.2: Balance Sheet of Lehman Brothers 

 

Source: Annual Report of Lehman Brothers 

The balance sheet shows that Lehman Brothers was increasingly holding assets for its own 

position – as the principal – as opposed to being a broker, namely, as an agent. This was a 

deliberate strategy, as noted above in the shift from a “moving” to a “storage” business. In 

Lehman Brothers
Balance Sheet
in US$ billion 2005 2006 2007

Assets 410 503 691

(of which Financial Instruments and other Inventory position owned) 177 227 313
Liabilities and Equity
ST Debt 339 403 546
LT Debt 54 81 123
Total Debt 393 484 669
Shareholders' equity 17 19 22

Total Liab & SE 410 503 691

Debt/equity 23.1 25.5 30.4



289 
 

order to better understand the difference, it might be worth examining an analogy in the real-

estate market. Imagine Ann wants to buy a house similar to the one that Tom lives in. 

Incidentally, Tom wants to sell his house in the process of moving to a larger one to 

accommodate his growing family. Typically, Ann might not know that Tom wants to sell his 

house and approaches a real-estate agent to indicate her preference for the type of house she is 

looking for. Equally, Tom does not know that Ann is looking to buy a house similar to the one 

he lives in and approaches the real-estate agent to put his house up for sale on the market. The 

real-estate agent advertises that Tom’s house is up for sale. Ann approaches the real-estate 

agent to view the property, happens to like the property and agrees to buy the house. The agent 

then matches the buyer, Ann, with the seller, Tom, and makes a commission from the sale of 

the house, charging the buyer, the seller, or both, depending on the practice in each country.  

Let us assume that the real-estate agent observes that the price of houses is generally 

going up. Moreover, it is often the case as the business grows that the real-estate agent might 

not be able to find a buyer immediately when a seller wants to sell their house. Hence, the 

estate agent reasons that it might not be a bad idea to buy the house from the seller and hold it 

on its own books, selling it when a buyer comes along sometime in the future. In this way, the 

estate agent makes a return twice, first on the commission and second on the difference between 

the buying and selling price of the house as the prices rise. However, the estate agent does not 

have the funds to buy the house and borrows from the bank to do so, in the process leveraging 

themselves up. The real-estate agent has effectively transformed its business model from agent 

to principal, investing in houses and hoping to make a handsome return. The new business 

model works as long as house prices continue to increase. However, when house prices start to 

tumble, the estate agent makes a loss from its inventory of houses, which might not be easy to 

dispose of; hence, the agent might get into a liquidity crisis with the bank by breaking the terms 

of the loan covenant. This could result in the bankruptcy of the estate agent. 



290 
 

This is essentially what happened to Lehman Brothers. Figure 3 shows us that Lehman 

Brothers increased the assets held on its own account as inventory from US$177 billion in 2005 

to US$313 billion in 2007, an increase of US$136 billion. There was a large holding of MBS 

and CDOs. Much of this increase was funded with short-term loans, which increased by 

US$207 billion in the same period, from US$339 billion in 2005 to US$546 billion in 2007. 

These short-term funds were often borrowed from the inter-bank market for periods of up to 

one day. As a result, Lehman Brothers’ leverage ratio, indicated by the debt-to-equity ratio, 

increased from 23.1 to 30.4 between 2005 and 2007, respectively. The highly leveraged 

position was partly responsible for the stellar performance of Lehman Brothers for the few 

years preceding its bankruptcy. However, when the housing market stated to decline, with the 

corresponding value of securities, including declines in the value of MBS and CDOs, Lehman 

Brothers were caught holding these declining assets, which could not be sold easily. Banks 

such as JP Morgan, which had lent the short-term funds to Lehman Brothers, called in their 

loans one Friday afternoon, on 12 September 2008, which left Lehman in a liquidity crisis and 

having to file for Chapter 11 bankruptcy on Monday 15 September 2008.  

The change in the business model of Lehman Brothers, which was riddled with conduct 

risk and caused significant detriment to customers and markets, was exacerbated by a number 

of practices. First, there was an opportunity to arbitrage the capital requirements, as noted in 

the FCIC Report (p. 100): 

Banks could reduce the capital they were required to hold for a pool of mortgages simply by 

securitizing them, rather than holding them on their books as whole loans. If a bank kept $100 

in mortgages on its books, it might have to set aside about $5, including $4 in capital against 

unexpected losses and $1 in reserves against expected losses. But if the bank created a $100 

mortgage-backed security, sold that security in tranches, and then bought all the tranches, the 

capital requirement would be about $4.10. 



291 
 

Second, Lehman Brothers understated its leverage at the end of each reporting season by 

merely selling and repurchasing the securities held in order to temporarily remove assets from 

its balance sheet under an accounting gimmick called “Repo 105” (FCIC Report, 2011, p. 177). 

Third, Lehman Brothers relied on credit default swaps, which were a type of insurance contract 

meant to pay out in the case of default. These credit default swaps were sold by an insurance 

company, AIG, which had to be bailed out by the US government. It turns out that AIG’s 

business model was also based on unsound foundations, as noted below (FCIC Report, 2011, 

p. 140), namely, leveraging the parent’s strong credit rating of AAA in order to provide credit 

insurance relatively cheaply:  

Relying on the guarantee of its parent, AIG [which had a AAA rating], AIG Financial Products 

became a major over-the counter derivatives dealer, eventually having a portfolio of $2.7 

trillion in notional amount.  

AIG Financial Products issued credit default swaps guaranteeing debt obligations held by 

financial institutions and other investors. Because credit default swaps were not regulated 

insurance contracts, no reserve requirement was applicable. 

AIG FP predicted with 99.85% confidence that there would be no realized economic loss on 

the supposedly safest portions of the CDOs on which they wrote CDS protection, and failed to 

make any provisions whatsoever for declines in value—or unrealized losses—a decision that 

would prove fatal to AIG in 2008. 

The practice of increased financial leverage through short-term borrowing and changing the 

business model from principal to agent created a conflict of interest. Moreover, asymmetric 

information played a part too – the superior information of the bank acting as dealers in the 

market gave them an advantage in taking security positions that were contrary to customers’ 



292 
 

interests.56 However, this practice was prevalent among all of the major US investment banks, 

as shown in Figure 4 by their increase in leverage from 2004. This is because these investment 

banks effectively persuaded the US Securities and Exchange Commission (SEC) in 2004 that 

they were not deposit-taking institutions, and hence had low risk in terms of deposit runs, 

whereby investors lose confidence and remove deposits all at once (Adrian and Shin, 2010). 

The SEC was suitably convinced and allowed the investment banks to determine their capital 

requirements based on their own risk models. This favourable change to the reserve 

requirements partially incentivised the banks to increase their leverage and shift their business 

models from agent to principal. It seems that such a practice was also prevalent among retail 

banks such as Barclays, which were able to use their retail deposits to fund taking positions as 

principal in the investment banking business rather than funding such operations through the 

inter-bank wholesale markets. 

 

 

 

 

 

 

 

 

 

 
56 The banks could see the “colour of the market” better than any individual customers, as they act as the 
intermediary of the transactions in the marketplace.  



293 
 

Figure 9.2: Leverage of US Investments Banks 

 

Source: Adrian, T. and Shin, H. S. (2010) 
 
 
9.3 Implications for Business Model Design 

 
The global financial crisis (GFC) and some of the related financial misconduct resulted in 

significant costs to various stakeholders (Meeks and Velu, 2018). First, customers lost access 

to finance, as banks significantly curtailed their lending. Second, employees lost their jobs, as 

was the case with Lehman Brothers and other banks. The banks had to pay fines of up to £260 

billion globally between 2012 and 2016. Third, the operations of the market and competition 

were significantly affected. The Nobel Laureate, George Akerlof, highlighted the costs of such 

information asymmetry using the analogy of the sale of “lemons” in the used-car market 

(Akerlof, 1970). A second-hand car dealer – who will inevitably have more information about 



294 
 

a used car – who sells a decrepit old car, a “lemon”, portraying it as a good car, will contribute 

to two types of cost of such misinformation. First, there is the cost to the customer who buys 

the lemon and incurs costs later when the car develops issues. The second cost is the loss that 

arises from driving legitimate business out of existence, as customers lose faith in the second-

hand-car market and hence withdraw from buying used cars. The cost of driving such legitimate 

business out of the market often exceeds the costs of any individual customer who has been 

cheated. A similar phenomenon happened during the GFC; for example, some financial 

markets such as the REPO market froze and stopped functioning (FCIC Report, 2011, p. 136). 

Studies have shown that uninformed investors could rationally withdraw from the market as a 

result of information asymmetry, which could then deprive the market of the risk 

transformation function of financial markets (Lev, 1988). Moreover, the US government had 

to bail out some of the major financial institutions with funds of over US$2,700 billion (FCIC 

Report, 2011).  

The FCA considers business model analysis and business model challenge to be key to 

identifying the drivers of a firm’s conduct risks. Moreover, the FCA and the Prudential 

Regulation Authority (PRA) in the UK have a number of prescribed responsibilities as part of 

the Senior Managers’ Certification Regime (SMCR), which includes (FCA Handbook, 2021, 

SYSC 24.2.6): “Responsibility for the development and maintenance of the firm’s business 

model by the governing body.” 

The SMCR places personal accountability on senior directors/managers in terms of 

managing conduct-related risks, among other responsibilities. One of the aims of the SMCR, 

as noted by Jonathan Davidson, Director of Supervision – Retail and Authorisations at the 

FCA, is to deter business models that create commercial behaviour leading to poor outcomes 

for customers and the associated pay structure that rewards such misconduct (Davidson, 2017). 

In doing so, the SMCR explicitly makes senior managers accountable not only for taking 



295 
 

responsibility for their own actions but also in leading the institution in terms of the formulation 

of strategy and business model design. A failure to do so can result in personal fines. 

There has been an increase in information asymmetry over time as a result of structural 

changes in the financial sectors causing incentive misalignments and hence contributing to 

conduct risk. For example, the crisis in the Lloyds insurance market has been linked to the 

growth of the market weakening the personal links and ties of trust between client and firm, 

and formal information channels did not keep pace (Duguid 2014). In the retail market for 

mortgages, potential customers used to have to build a savings record with – and become 

known to – a building society before they could get a loan – a far cry from the multi-layered 

supply chain in the US case, where the originators and the ratings agencies failed to bridge the 

information gap (Wigan et al., 2005). It is incumbent upon the senior managers of firms to 

develop their strategy and design business models in such a way as to reduce conduct risk by 

minimising information asymmetry and aligning incentives between customers and the firm. 

In the spirit of doing just that, it is instructive that Vikram Pandit, the CEO of Citigroup at the 

time, made the following remark (Cassidy, 2010): "It's all about clients,"… In place of a 

business model that was largely dependent on making quick gains, he is trying to revive a 

banking culture based on cultivating long-term relationships with Citi's customers. "Once you 

make your business all about relationships, conflicts of interest are not an issue." Three 

principles stand out in the statement by Vikram Pandit, which are worth emphasising in terms 

of how banking business models should be designed. These are how to align customers’ 

interests with the firm’s interest, reducing conflicts of interest and cultivating long-term 

relationships.  

In order to address these principles, it is worth looking at other industries where such 

conflict-of-interest-driven business models, combined with information asymmetry, have 

resulted in customer detriment – and how the issue was addressed by redesigning the business 



296 
 

model. The two examples involve servitisation-based business models in capital equipment 

such as aero engines or earth-movers. In the earth-moving equipment market, Caterpillar used 

to earn four times more from providing spare parts over the life of the product compared to the 

initial sales. Hence, the business model was dependent on the failure of the equipment and 

customer detriment and therefore ridden with conflicts of interest and information asymmetry. 

Customers with important contractual deadlines, such as major building projects, often 

incurred significant penalties as a result of the breakdown of this earth-moving equipment. 

These customers were increasingly unhappy with the product provided by firms such as 

Caterpillar, which prompted the firm to embed sensors into the earth-moving equipment to 

monitor its performance and effectively predict when the machines were likely to break down 

(Baines and Lightfoot, 2013). In this way, Caterpillar has been able to provide an integrated-

solution optimal use of machine, as well as repairs, optimised the coordination of machines in 

the worksite (e.g. quarry) and even moved to a model of charging customers based on the price 

per tonne of material mined. Moreover, Caterpillar’s dealers assume responsibility for a 

portfolio of equipment, including multi-vendor products (e.g. John Deree, Volvo equipment), 

which allows them to be replaced with the manufacturer’s own products later.  

In the same way, Rolls-Royce, one of the major providers of aero engines, was 

dependent on engine breakdowns to generate income, which was resisted by some of the major 

airlines (Smith, 2013). Rolls-Royce subsequently adopted a servitised business model, 

whereby its TotalCare programme provides support and service by embedding sensors into the 

aero engine, and it is paid for by the hour that the engine is flown: the power-by-the-hour 

model. Rolls-Royce is able to monitor the engines remotely and hence provide advice on how 

best to use the aircrafts and which routes optimise engine performance. These servitised 

business models of Caterpillar and Rolls-Royce provide better alignment of customers’ 

interests with those of the firm and therefore reduce conduct-related risks. 



297 
 

Similarly, business models based on better alignment of customer and bank interests 

are beginning to emerge, such as the loan provided by the French bank BNP Paribas to JetBlue, 

a major domestic airline in the United States. JetBlue announced that it would be “carbon-

neutral” on its flights in the US by 2040 by purchasing more efficient engines and using biofuel 

blends. There was a financial incentive to follow through on its public commitment to reduce 

its carbon footprint. JetBlue signed a new credit facility – the first of its kind in the airline 

industry. The credit facility is a $550 million sustainability-linked loan arranged by BNP 

Paribas: the interest rate will go up or down in conjunction with JetBlue achieving its 

environmental, social and governance (ESG) score, as determined by Vigeo Eiris, a Paris-based 

sustainability research group owned by Moody’s (Financial Times, 2020).  

The shift to solutions-based business models requires a transformation from products 

to solutions, transactions to relationships, and from suppliers to a network of partners (Martinez 

et al., 2017). In addition, appropriate business model designs could align customers’ and firms’ 

interests in complex products; services also need to have concertive controls, which are a 

negotiated consensus on values that workers use to infer proper behavioural premises for self-

control and team management. Concertive controls are often practised by firms in the 

hospitality industry, such as Ritz Carlton (HBS Case, 2005; Barker, 1993). They call upon 

employees to be counted on to respond to, and anticipate, individual customer wants and needs. 

Employees need to do the right thing in the right way, even when the right thing has not been 

specified. Such values play to the spirt of Mark Twain’s quote ‘Laws control the lesser man… 

Right conduct controls the greater one.’ The critical question becomes not whether one can 

legally make a transaction but rather whether one should ethically make a transaction (HBR 

Case, 2014).  

 



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9.6 Conclusion 

Conduct risk encompasses the need to prevent detriment to customers and markets. It can be 

seen as the preservation of the customer and markets and maintaining adequate competition so 

that there will be fair customer outcomes. Hence, conduct risk can be seen as the external-

facing risk for firms and could manifest itself in terms of the impact on the performance of 

firms in the medium to long term. Although conduct risk has always been prevalent, the global 

financial crisis brought it into sharp contrast, as the global impact on financial markets and the 

real economy was significant. The Salz Review pointed out that regulation alone is insufficient 

to address conduct-related issues (Salz, 2013, p. 6): 

It is understandable, and in many respects necessary, that since the start of the financial crisis, 

there has been an explosion in new regulation and in the intrusiveness of regulators. However, 

regulation alone cannot address the fundamental underlying causes that led to the business 

practices which are in the spotlight – the cultural shortcomings we found. 

Conduct risk is particularly problematic when there is asymmetric information and conflicts of 

interest. Although financial regulators such as the Financial Conduct Authority (FCA) in the 

UK were pioneers in developing the set of guidelines for managing conduct risk among 

financial institutions, the issue of conduct risk is just as important in other industries where 

there are conflicts of interest. For example, KPMG was fined a record £13 million in 2021 

following a case of misconduct dating back to 2011. This is because KPMG had acted as 

advisors for Silentnight, a bedding company, and HIG, a private equity firm, with significant 

conflicts of interest. KPMG helped to push Silentnight into insolvency so that HIG could buy 

the assets out of administration and sell off the costly pension scheme of Silentnight (The 

Guardian, 2021).  



299 
 

The issue of conduct risk needs to be managed effectively as firms respond to digital 

technologies such as artificial intelligence (AI) and machine learning (ML). Although AI and 

ML enhance customer solutions, they are also prone to creating new types of asymmetric 

information, as well as conflicts of interest. For example, the Open Banking initiative in Europe 

requires banks to open up customer data (if the customer consents) to third-party – typically 

banks/finance companies/tech groups using application programme interfaces (APIs) – 

protocols that transfer data automatically from one piece of software to another. This would 

allow third parties to “aggregate” data from all customer accounts and advise on which 

products are most suitable. The idea is that the customer benefits, as there would be greater 

transparency and better value for money. Some banks have, in response, launched platforms 

that enable third-party organisations to develop applications – including Open Banking.  

There are several challenging business model design issues to consider. For example, 

should the firm launch the new business as a separate business unit or within its existing 

business; and what are the associated implications for conduct risk? As discussed in Chapter 

3, the organisational design to accommodate new business models could have an impact on 

customer outcomes. For example, the fulfilment of orders using Tesco’s physical stores by its 

online business, Tesco.com, could have a detrimental impact on customers coming into stores 

to shop, as they would need to manoeuvre around the trolleys being used to fulfil the online 

orders. Similarly, banks need to pay close attention to the organisational design of new business 

models as a result of the adoption of digital technologies such as blockchains, artificial 

intelligence and quantum computing, among others, in order to manage conduct-related risks. 

Such risks are not exclusive to financial institutions, with other industries just as prone to them 

as they adopt new business models.  

There are a number of areas that warrant further investigation of business model design 

and conduct risk. The first is to better understand how new digital technologies such as 



300 
 

blockchains, artificial intelligence and quantum computing might contribute to conduct risk 

and the implications for business model design. In particular, how could firms systematically 

learn from industries that are ahead in the adoption curve of these digital technologies? Hence, 

how does one manage such conduct-related risks and the associated implications for business 

model design? The second area is the design issues related to new business model development 

and the associated conduct risk. How does one manage the conflicts that arise between the new 

business model and the existing business model? The introduction of new business models 

could result in conflicts with the existing business model and also increase information 

asymmetry between the customer and the firm – and hence contribute to customer detriment. 

Moreover, the introduction of new business models could increase the conflicts between 

various departments within an organisation, such as marketing and new product development, 

which might also lead to increases in conduct risks. How does organisational design launch 

new business models in order to manage conduct risk? Third, digital technologies increasingly 

call for collaborative business models, whereby conduct-related risks are dependent on a series 

of firms within the ecosystem. Are there lessons to be learnt from managing other types of 

systemic risk? This calls for managing conduct risk at ecosystem rather than firm level. Further 

research needs to be conducted to better understand the business model design implications for 

managing systemic conduct-related risks.  

This chapter has provided an overview of the opportunities and challenges of conduct 

risk and business model design and proposed some outstanding research issues on this topic.  

 

 

 

 



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Akerlof, G. A. (1970). The Market for "Lemons": Quality Uncertainty and the Market 
Mechanism. The Quarterly Journal of Economics 84(3): 488–500. 
 
Baines, T. and Lightfoot, H. (2013). Made to Serve: How Manufacturers can Compete Through 
Servitization and Product Service Systems. John Wiley & Sons. 
 
Barker, J. (1993). Tightening the Iron Cage: Concertive Controls in Self-Managing Teams. 
Administrative Science Quarterly 38(3): 408–437. 
 
Bernanke, B.S., Geithner T.F. and Paulson. H.M. (2019) Firefighting: The Financial Crisis an 
its Lessons. Penguin Random House, New York. 
 
Cassidy, J. (2010). What Good Is Wall Street? Much of what investment bankers do is socially 
worthless. The New Yorker. 
 
Davidson, J. (2017). Culture and conduct – extending the accountability regime. Speech 
delivered at City and Financial Summit, London, 20 September 2017. 
 
Duguid, Andrew. (2014) On the Brink: How a Crisis Transformed Lloyd's of London. Palgrave 
Macmillan. 
 
FCA Handbook (2021). SYSC 24 Senior managers and certification regime: Allocation of 
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Financial Times (2012). FSA slams "aggressive" selling of retail investments, 13 March. 
 
Financial Times (2020). JetBlue signs loan linked to ESG goals, 23 February. 
 
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Louis, J. and Zinkin, R. (2019). Better Governance Across the Board:  Creating Value Through 
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Martinez, V., Neely, A. Velu, C, Leinster-Evans, S, and Bisessar, D. (2017) Exploring the 
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Meeks, G. and Velu, C. (2018). Ten years from the crash: time to row back on financial 
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Mintz, Robert. A. (2008). Business Failure are not a Crime. Wall Street Journal, 26 June 2008. 
 
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Salz, A. (2013). An Independent Review of Barclay’s Business Practices. Salz Review.  
 
Smith, D. J. (2013). Power-by-the-hour: the role of technology in reshaping business strategy 
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CHAPTER 10: CONCLUSION 

  



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CHAPTER 10: CONCLUSION 

 

Simplicity is the ultimate sophistication.  

(Leonardo da Vinci) 

 

10. Introduction 

New business models are created in response to a combination of society’s explicit or implicit 

needs and technological developments. Hence, to better understand the overall evolution of 

business models, it is worth reviewing the broader technological progress that has enabled 

value to be created and captured by businesses – and the role of the state and the market in 

facilitating such an exchange. In this concluding chapter we first provide a historical overview 

of the technological developments that created the techno-economic foundations for business 

model innovation. We briefly discuss the impact of the COVID-19 pandemic on business 

models before reviewing the role of the state and the economic system in nurturing and 

accommodating business models. In doing so, we highlight the importance of business model 

design in distributing value among stakeholders in order to ensure fairness in society as the 

world we live in embraces further prosperity and well-being. 

This chapter provides a broad overview of business model developments going from 

the industrial revolutions that started in Britain in the 18th century to the more recent digital 

technology era. The following section reviews the impact of the pandemic on business model 

innovation and some of the initial lessons for firms. The chapter then discusses how the role of 

the state and the economic system are key to influencing the design and evolution of business 

models. The concluding section discusses the imperative of the distribution consequences of 

business models and the implications for economic growth in an equitable society.  

 



305 
 

10.1. Industrial Revolution and Business Models 

The reasons why the Industrial Revolution – a more mechanised production system with 

features related to technological, socio-economic and cultural change – took place in Britain in 

the 18th century, and not elsewhere, continue to be a major bone of contention57 (Allen, 2009, 

2011). The reasons are varied and have been attributed to the British constitution, culture and 

science, among other things (Crafts, 2018; Hartwell, 1967; Mokyr, 1993). The crux of the 

argument relies on whether it is the factors that are conducive to a greater supply of inventions 

or the drivers that encourage a favourable cost and commercial environment that create a 

demand for inventions. On the one hand, the supply-side proponents say that there was a period 

of “industrial enlightenment”, driven by British society’s willingness to apply scientific 

discoveries to social and economic problems, which provided the incentive for the supply of 

inventions (Mokyr, 2010).  

On the other hand, the demand-side thesis says that Britain had a more pressing 

economic need for labour-saving technology – the spinning jenny, the steam engine and coke 

smelting, among others – compared to other countries because of its higher wages and lower 

energy costs (Allen, 2009). The higher wages were due to Britain’s unique position in 

international trade in the late 18th century and early 19th century, while the lower energy costs 

were a result of the abundant supply of coal in Britain. These factors gave Britain the economic 

incentive to develop energy using technology that would substitute capital for labour. Hence, 

despite the more advanced state of science in some European countries, such as France, there 

was a greater need to mechanise production and displace labour in Britain. Some scholars have 

said that it is probably the combination of supply and demand conditions that formed the basis 

 
57 Arnold Toynbee used the term Industrial Revolution to describe Britain’s economic development from 1760 
to around 1840 (Encyclopaedia Britannica, 2022). 



306 
 

for Britain leading the Industrial Revolution (Crafts, 2018). In time, the Industrial Revolution 

was diffused to other European nations, such as France and Germany. 

Before the mid-19th century, there were no multi-functional, multinational and multi-

product enterprises administered by professional managers (Chandler, 1986). The enormous 

increase in volume and output that led to these types of firm arising was not due to the First 

Industrial Revolution, which took place between the mid-18th and mid-19th centuries in Europe, 

led by Britain. The concept of mass-production techniques that led to the development of 

modern large-scale business enterprises did not take place until after the 1840s, led by the 

United States. The increase was a result of the Second Industrial Revolution, from the mid-19th 

to the early 20th centuries, when the emergence of transportation, communication technologies 

(such as the telegraph) and stable energy (first in the form of coal and then electricity) enabled 

such firms to emerge (Chandler, 1977). The European economies had a more fragmented 

market than America and were also dominated by family-owned and -managed firms. Hence, 

European economies, together with Japan, were slower to adopt mass-production techniques, 

coupled with large marketing and purchasing organisations.  

In contrast, American firms often developed machinery based on European inventions, 

as the latter were more technologically advanced. Alfred Chandler, in his influential book The 

Visible Hand, argued that American firms were the first to adopt large-scale managerial 

capitalism, whereby firms were run by professional managers administering them as a result of 

their growth in terms of both vertical and horizontal integration (Chandler, 1977). This was 

partly due to the significant growth in the American markets, which became large, homogenous 

and open to international trade, between the American Civil War58 and World War I (WW1). 

 
58 The American Civil War took place between 1861 and 1865 and World War I between 1914 and 1918. 



307 
 

Hence, there is merit in studying the development and growth of American corporations to 

better understand the mechanisms driving business model innovation. 

Alfred Chandler showed that production and distribution in the United States were 

primarily carried out by family-owned general merchants in the late 18th century until the 1840s 

(Chandler, 1977). From the period of ratification of the US Constitution, from the 1790s 

onwards, the legal and political development of the national economy provided the impetus for 

the growth of goods that were produced and distributed. However, the businesses that were 

conducting these production and distribution activities continued to be traditional single-unit 

enterprises, which remained the dominant business organisation until the 1840s, when new 

sources of energy such as coal, transportation provided by railroad and telecommunication 

through the telegraph provided the catalyst for change in business enterprises in the US.  

Between the 1790s and 1840s in the US, there were exceptions such as armouries and 

textile mills, where there was evidence of the subdivision of labour and the integration of 

several production processes within a single establishment. The armouries were able to grow 

as a result of the guaranteed market enabling them to cover production and distribution costs. 

The textile market manufacturers relied on the large flowing rivers to generate power. For 

example, because of the growing demand for clothing, Lowell’s Boston Manufacturing 

integrated weaving and spinning in a single factory and had a higher productivity rate than any 

other textile factory in the United States59 (Chandler, 1977, p. 58). However, for most industries 

during this period, the growth of the economy was driven by business enterprises that displayed 

increasing specialisation of particular activities and relied on the market to conduct transactions 

between enterprises. For example, specialised business enterprises focused on manufacturing, 

distribution and financing activities. The growth of these enterprises made the transactions less 

 
5959 The owner, Francis Cabot Lowell, had smuggled the plans for the power loom out of Britain (Chandler, 
1977, p. 58). 



308 
 

personalised, with the merchants often not knowing the producers and consumers across the 

long chain of activities in moving the goods through the economy. However, the basic business 

enterprise remained small and was managed personally because the volume of business did not 

require a large hierarchical management.  

10.1.2 Mass Production and Distribution 

Mass-production techniques were first used in industries processing liquids or semi-liquids 

such as crude oil (Chandler, 1977) because such industries had a steady flow of raw materials 

that needed to be worked on through the use of continuous process machinery. The flow of 

activities was less continuous and related to less controllable factors such as biological 

constraints and weather in industries such as agriculture and construction. The application of 

continuous process machinery enabled the integration of tasks and the reorganisation of the 

factory system to increase throughput and hence productivity. This resulted in improvements 

in technology in terms of efficient machinery, the quality of raw materials and intensified 

application of energy. Such technological innovation, in turn, called for organisational 

innovation to arrange the artefacts and coordination of materials and workers. From the 1840s 

to the 1870s, the combination of coal to reliably produce heat, and the development of the rail 

system for transportation and the telegraph for communication, enabled better coordination of 

input and output, which further stimulated the development of mass-production factories. The 

speed of production through the use of continuous production methods was responsible for the 

increased productivity. However, the textile industry, beyond the integration of spinning and 

weaving, experienced a slower rate of adoption of continuous production methods until much 

later on.  

The steel industry followed the adoption of mass-production techniques in the 1870s in 

the United States. In the 1830s and 1840s the steel industry started to disintegrate from the 



309 
 

“iron plantation” facilities as a result of the availability of coal. Coal permitted greater and 

steadier output, enabling specialisation in blast furnaces, forges, rolling and finishing mills. 

However, reintegration of the steel mills started with the adoption of the Bessermer steel 

process, where the co-location of the different processes for steel-making resulted in 

continuous production processes and increased productivity. One of the first examples of such 

a factory was the Edgar Thomson Works (E.T. Works) of Andrew Carnegie, which opened in 

1875 in Pennsylvania. Andrew Carnegie had adopted administrative procedures to manage the 

business from his previous experience in the railroad industry. These integrated iron works, 

together with more systematic management procedures, brought about business model 

innovation in the steel-making industry, with significantly improved productivity and 

profitability for the business. In the metal-working industries that produced many of the tools 

and mass-produced metal works (e.g. for armoury) there was a type of business model 

innovation involving “inside contracting”; the owners sub-contracted to skilled mechanics a 

specified number of parts over a specified period of time (e.g. one year), were credited for the 

value and charged for the cost of providing the floor space, machinery, power and other related 

materials. At the end of the period any surplus was paid to the contractor as profits. This way, 

the owner needed to provide only light supervision of the overall process of manufacturing.  

However, the period from the 1870s resulted in a slowdown in economic growth, and 

hence demand, which put additional pressure on firms to manage and contain costs. To improve 

productivity, factories started to share the benefits of productivity improvements with 

employees and managers, which resulted in the development of the Taylorist management 

approach, which is often seen as the beginning of the scientific management system.60 

However, the increased mechanisation and capital intensity of mass-production industries 

 
60 The Taylorist management system was introduced by Frederick W. Taylor at the Midvale Steel Company; a 
paper was written in 1895 and was termed “scientific management”. Several papers discuss the merits and 
shortcomings of the Taylorist approach (Wagner-Tsukamoto, 2007).  



310 
 

resulted in increased fixed costs. Hence, to keep the machinery, workers and managers fully 

employed, there was increased pressure on the owners of these firms to control the supply of 

raw materials and semi-finished components, as well as the marketing and distribution of their 

products. This economic pressure resulted in business model innovation in the form of vertical 

integration of production and distribution.  

Vertical integration enabled increased profitability through decreasing costs and 

increasing productivity. The completion of the railroad and telegraphic network went into full 

operation in the 1870s and 1880s in the United States. The growth of railroads lowered the 

barriers to transportation and enabled small enterprises to compete on a nationwide scale. 

Moreover, the development of the telegraph and then the telephone enabled the centralised 

supervision of geographically dispersed operations of these businesses. The prices of products 

started to decline as a result of the combination of increased competition – due to the 

development of transportation and communication technologies – and the economic depression 

that began in 1873. This economic pressure prompted firms to integrate horizontally in order 

to maintain profits by controlling the prices and output of the operating units. American 

manufacturers operationalised such horizontal integration predominantly through mergers. 

Many of the firms that grew via horizontal integration through mergers remained profitable 

only if they followed their consolidation with a strategy of vertical integration forward into 

marketing and backward into purchasing raw or semi-finished goods. These integrated 

enterprises replaced the invisible hand of market forces with the visible hand of management 

in coordinating the flow from the suppliers of raw materials to the consumer (Chandler, 1977, 

p. 315).  

The emergence of business models of integrated firms took place at different speeds 

across various industries. The industries that adopted the continuous flow technologies, such 

as petroleum, food and complex but standardised machinery, were the first to successfully 



311 
 

adopt the integrated-firm business model structure. Industries that needed labour input or 

complex products, which could not use continuous process machinery for production, were 

slower to adopt such a model. The increased production rate from large-batch continuous 

process machinery meant that firms needed to coordinate the production and sales of their 

output, and therefore they tended to internalise the marketing and sales channels. Moreover, 

these firms needed to develop management skills that enabled the coordination, monitoring and 

planning of these operating units in order to achieve improved performance compared to the 

constituent operations or firms, with such operations working independently. The key factor 

that determines profits in these large-batch, continuous-flow industries is not capacity but 

throughput, which requires management expertise to coordinate the production processes with 

distribution and marketing (Chandler, 1986).61 Therefore, the locus of competition shifts from 

the price of the product to all stages of production and distribution, including the availability 

of credit and aftersales service. For example, Singer developed an extensive sales distribution 

channel for its sewing machines and aftersales service in repair and maintenance.  

The increased adoption of salaried managers required two basic functions of 

management to be sharpened and improved in these large integrated organisations. First, it was 

necessary to coordinate and monitor the current production and distribution of goods and 

services. Second, there was a need to allocate resources for future production and distribution. 

However, managers tended to focus on current operations rather than long-term planning. 

Moreover, firms started to diversify from their own specific technological base: Du Pont from 

its nitrocellulose chemistry into paint, dyes, films and fibres; and General Motors from using 

knowledge in diesel automotives to diesel locomotives.  

 
61 Management expertise is needed to ensure such coordination to achieve and maintain production and 
distribution at the minimum efficient scale – the volume of the operations that archives the lowest unit costs. 
Therefore, it is posited that economies of scale are technological, while throughput is organisational (Chandler, 
1986). 



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There was a severe recession in 1920–21 after World War I, which caused firms to 

rethink their management approaches. Firms adopted techniques to improve the coordination 

of forecasting and planning for demand changes. Du Pont adopted the integrated autonomous 

divisions for different product lines from the functional departmental structure, which helped 

to improve its profitability. General Motors adopted the committee structure to coordinate 

across functions and the flow of current and future demand. Hence, the administration systems 

in the large integrated American firms were improved after WWI, permitting middle managers 

to focus on coordinating the current flows and top management to focus on evaluating, planning 

and allocating resources. Hence, the first modern enterprises created to administer the new 

railroad and telegraph firms in the 19th century came to be adopted by integrated multi-product 

managerial enterprises in the 20th century. These firms dominated American industry post-

World War II (WWII) – the 200 largest industrial firms in the US accounted for 47.2% of the 

total corporate manufacturing assets in 1947, 56.3% in 1963 and 60.9% in 1968 (Chandler, 

1977, p. 482).   

The economist view, based on Adam Smith’s invisible hand of the market, whereby 

improved technology and markets result in increased specialisation and hence vertical 

disintegration, was increasingly questioned (Chandler, 1977, p. 490). Such a dictum overlooks 

the important aspect of administrative coordination, where the speed and regularity with which 

goods flow through the process of production and distribution, and the ways in which these 

flows are organised, affect the volume and unit costs62 – the choice of business model design 

affects productivity (Wannakrairoj and Velu, 2020). There are alternative perspectives on the 

role of administration and coordination on business model design. 

 

 
62 Economists traditionally classify this organisational and managerial aspect of the firm as a residual effect of 
the production function, which is the proportion of output not explained by input (Wannakrairoj and Velu, 2020).  



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10.1.3. An Alternative Theory for Vertical Integration 

Langlois (2003) had a different conceptualisation of the vertically integrated firm that Chandler 

(1977) had described in response to achieving high-throughput production as a result of the 

emergence of the railroad for transportation, the telegraph for communication and coal as a 

source of heat energy. Langlois argued that, as the population and income grow, and technology 

and legal barriers decline, the process of the division of labour will result in finer specialisation 

of function and increased coordination through markets. However, the components of the 

process, such as technology, organisations and institutions, tend to change at different rates. 

Hence, Langlois (2003) argued that the vertically integrated firms that Chandler described were 

an organisational response to overcoming the imbalance at the time between the needs of high-

throughput technologies and the ability of existing markets and institutions to meet this 

demand. Thompson (1967) had argued that organisations tend to buffer uncertainty in the 

environment by surrounding the technical core of their production process with input and 

output components. The role of management in such a process is to act as an information-

processing function, managing uncertainties by translating complex information into routine 

information that the production system can use. Integration and management are ways of 

controlling or buffering product flow uncertainties due to the higher fixed costs of a vertically 

integrated system compared to a decentralised system. This management function enables the 

firm to create and capture value in such a way as to deliver the most utility to customers at the 

lowest cost. 

Levinthal and March (1993) go further, invoking Herbert Simon’s (1962) notion of a 

nearly decomposable system, with modularisation enabling components to become 

independent of one another and interactions happening within modules, while interactions 

among modules are kept to a minimum and managed through formal interfaces. Modularisation 

enables loose coupling, whereby each function can concentrate on the local rather than global 



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consequences of the information that it receives. This nearly decomposable system is akin to 

Adam Smith’s view of specialisation – and hence the advantages of the invisible hand of the 

market. The Chandlerian vertical integrated firm can then be explained in terms of dynamic 

transaction costs, with the need to coordinate and systematically reorganise production and 

distribution requiring centralised organisation, which overcomes the benefits of decentralised 

organisation, with a focus on specialisation. When many components of the system need to be 

changed simultaneously as a result of new technologies or market needs, the centralised vertical 

integrated structure reduces the dynamic transaction costs of systemic change. These vertically 

integrated firms were initially geared towards the management of economies of scale. 

However, the lumpiness of resources, and the resultant excess capacity, encourage firms to 

diversify into adjacent markets, which increases the economies of scope, resulting in 

diversified enterprises (Penrose, 1959).63  

However, the charmed life of US corporations in the 1950/60s was disrupted by new 

technologies, particularly digital technologies, in the 1970/80s. The impact of these new 

technologies, which was the premise of the new digital economy, was effectively to simplify 

and reduce scale in some aspects, while increasing the benefits of scale in other respects. 

Moreover, digital technologies enabled better mass customisation, which required firms to 

increase the variety of their product offering. In particular, the benefits of vertical integration 

reduce with the need to be more responsive to changes in the growing markets for customised 

products. The variation induced by such mass customisation implies the need for the system to 

be responsive to changes in demand and supply, which results in the unbundling of the vertical 

structure of the managerial corporation. Increasingly, firms across industries, from 

 
63 Economies of scale and economies of scope are ultimately related to the need for the same structure of 
knowledge and the need to increase efficiency: economies of scale are due to increasing production of the same 
product, while economies of scope increase the production of something different that requires similar 
knowledge (Langlois, 1999).  



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pharmaceuticals and semiconductor manufacturing to automobiles, were outsourcing parts of 

their production and marketing functions to specialist firms, and these firms were becoming 

general specialists by diversifying their portfolio to serve multiple industries (Langlois, 2003). 

In doing so, they were able to smooth demand and facilitate high-throughput production 

through a more decentralised modular system, the aim of which is to standardise the more 

abstract visible design rules of the system rather than the products and processes (Baldwin and 

Clarke, 2000).  

In conforming to the visible design rules, it is not necessary for each participant to 

disclose its activities, which become hidden design parameters, and yet they can achieve mass 

customisation by reducing product standardisation. This was evident in the way that Dell was 

able to sell customised personal computers from standardised components. However, firms are 

able to exert considerable administrative control over the stages of production that they do not 

control, effectively creating the benefits of vertical integration. The benefits of information-

improving innovation on the market structure, such as the degree of vertical integration, are 

ambiguous. The trade-off depends on whether the information-improving innovation renders 

the cost of organising internally within the firm greater than reducing organisation in markets. 

The major technology that enabled information-improving innovation in the late 20th century 

was the digital computer and the Internet. Next, we review the historical development and 

impact of the digital computer and the Internet on information, communication and 

coordination mechanisms, and their influence on firm structure – and hence business models.  

10.2 The Advent of the Digital Computer 



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There was an explicit plan led by the US government and other allied forces to ensure that the 

technological inventions from World War II should have benefits to society (Bush, 1945).64 

One of the major technological breakthroughs was the development of digital computers for 

business applications based on principles developed during WWII. The first digital computer 

developed in the US was the ENIAC machine, at the University of Pennsylvania, to calculate 

artillery firing tables for the US Army Ballistic Research Laboratory in 1945. In the UK a secret 

programme was developed to crack the German Enigma code during the war, which led to the 

development of the Colossus.65 Colossus was the first large-scale electronic digital computer, 

which was operational in December 1943.66  

In the years following WWII, the American mathematician John von Neumann was 

influential in building the first stored-program digital computer, the EDVAC, at the Institute 

for Advanced Studies at Princeton.67 The EDVAC was influential in terms of early US 

computers and the precursor to the IBM 701, the company’s first mass-produced stored 

programme computer. In the UK, following WWII, expertise for the development of the digital 

computer was taken up by the National Physical Laboratory (NPL) and called the Automatic 

Computing Engine (ACE) machine (Copeland, 2005). Subsequently, there were developments 

 
64 Hence, the commercial development of technologically complex products, such as synthetic rubber, high-
octane gasoline, radar, electronic antisubmarine devices and other related war-time technologies, led to the 
systematic application of science to industry. This resulted in the development of various chemical and synthetic 
materials, as well as a wide range of electronic products. 
65 There was a computing machine – a precursor to Colossus – called Bombe that was used to decode the German 
Enigma machine. Bombe was initially based on electromagnetic relays (relays with small switches of metal rods 
that opened and closed based on electrical circuits), although later versions of the Colossus were based on valves 
or vacuum tubes that operate many times faster, as the only moving part is a beam of electrons.  
66 Before the 1970s few knew about the use of electronic computation during WWII, as the Colossus was kept 
secret by the British government. It was not until 2000 that the US and Britain declassified the information about 
Colossus, which was developed by Thomas Flowers, from the Post Office Research Station, and Cambridge 
mathematician Max Newman (who subsequently led the computing effort at Manchester University). The lack 
of knowledge about Colossus led some to, understandably but erroneously, think that the ENIAC was the first 
electronic computing machine (Copeland, 2005).  
67 The stored-program digital computers were envisioned by Cambridge mathematician Alan Turing in his 1936 
paper on computable numbers and subsequently developed further by John Van Neumann as part of the EDVAC 
(Copeland, 2005). 



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at Manchester and Cambridge universities, with the Manchester Mark 1 and Electronic Delay 

Storage Automatic Calculator (EDSAC), respectively. The work at the University of 

Cambridge led to the development of Lyons Electronic Office (LEO), the first digital business 

computer. These basic developments, combined with application use cases demanded by 

government and businesses, led to the proliferation of digital computers around the world. At 

the end of 1968 IBM announced that it would unbundle its software with its hardware, which 

until then had been coupled together (Ceruzzi, 1998). 68 This enabled the firm to charge 

separately for the software packages. This decision effectively opened up software 

development to a myriad of third-party developers, which led to a plethora of applications, 

particularly to solve business problems. Moreover, there was a move to connect these disparate 

computers in order for them to work more effectively. There were several private- and public-

sector initiatives to link these computers and enhance communications between them. Chief 

among these was an initiative to link the computers under the ARPA programme funded by the 

US Department of Defense, ARPANET (Campbell-Kelly and Garcia-Swartz, 2013). The 

combination of these initiatives with the Transmission Control Protocol/Internet Protocol 

(TCP/IP) and the World Wide Web led to the emergence of the Internet.  

The early uses of digital computers were for engineering and scientific applications, 

later moving to commercial business applications (Cortada, 2003, 2005); the digital computer 

collects, stores, analyses and produces information. Simon (1973) highlighted that 

organisational design should be based on dividing the work in such a way as to make them as 

independent as possible, while reducing the need to manage the coordination between parts. In 

a world that is becoming more information-driven, the focus of organisational design needs to 

shift from dividing the work to produce output in the most efficient way to dividing while 

 
68 This was a result of the pressure from the US government to untie the monopoly that IBM had on the computer 
industry. 



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factoring in decision-making, because post-industrial society is shifting from producing goods 

to services – or from producing houses to housing.69 The anatomy of an organisation that is 

viewed as a collection of people that need to be subdivided will look very different to an 

organisation viewed as a decision-making and information-processing system. A goods-

producing organisation will be divided into tasks in departments that can be as independent of 

one another as possible, with coordinating mechanisms. An information-processing 

organisation’s division of labour means the decision needs to be made in relatively independent 

subsystems in order to minimise concerns about interactions with others. The reason for this is 

the limited processing capacity of the man or machine in comparison with the magnitude of 

the decision problem that the organisation needs to undertake. Therefore, the number and 

interdependencies of the decision need to be minimised in order to have a coordination 

mechanism within manageable bounds. The computer then acts as a memory and processing 

unit. As a memory unit, the computer acts as a means of storing potential information, which, 

if indexed appropriately, can be available at a reasonable cost. The computer as a processing 

unit models complex situations and infers the consequences of alternative decisions through 

models that calculate optimal decisions, simulate the consequences of alternative decisions and 

even help to make decisions. 

Firms initially used digital computers to reduce operational costs. The applications of 

digital computers were threefold: first, they helped to reduce the labour content of some 

activities (e.g. data entry); second, they lowered the operating overheads (e.g. the cost of 

inventory); and, third, they led to more effective work performance (e.g. modelling production 

schedules in manufacturing). The adoption of digital computers, combined with 

complementary digital technologies and the emergence of the Internet, enabled more 

customisation of products and services. Furthermore, the increased data from the combination 

 
69 This has also been termed the service dominant logic (Vargo and Lusch, 2016). 



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of Internet usage, sensors, mobile devices and other related sources has increased the demand 

for artificial intelligence and machine learning capabilities; and the combination of these 

technology trends has increased the demand for new business models. Moreover, the sheer 

volume and complexity of data requirements is creating the demand for quantum computers 

and related quantum-enabled technologies for communications, sensing and imaging, and also 

for position, navigation and timing. These technology developments provide the foundations 

for more personalisation of value to customers, which could take the form of personalised 

medicine, design and delivery of goods and services based on a segment of one. Such 

personalisation will incentivise the design of revolutionary business models to help improve 

society and well-being. We saw a glimpse of such a trend in the recent COVID-19 pandemic, 

which caused major disruptions to supply chains and increased reliance on digital 

transformation, which we discuss below. 

10.2 The Pandemic and Business Model Innovation 

The COVID-19 pandemic created a period of unprecedented uncertainty that affected both the 

demand and supply of goods and services simultaneously (Said et al., 2022). Firms had to 

respond very quickly to this economic downturn, while leveraging the opportunity to contribute 

to the healthcare challenges (Chesbrough, 2020; Financial Times, 2020; von Behr et al., 2022). 

For example, some firms in the aerospace sector managed to adapt their products to provide 

healthcare equipment such as ventilators to the healthcare industry. Other firms took the 

opportunity to rethink their core capabilities and diversified their product offering to other 

sectors, as the civil aerospace industry experienced a dramatic reduction in air travel. Research 

shows that small and medium-sized enterprises (SMEs) that invested in intangible capital, such 

as human, organisational and information capital, demonstrated effective leadership by 

engaging and empowering their employees prior to the pandemic, and they were the ones that 

were most able to make these types of business model change during the pandemic (Said et al., 



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2022). Hence, firms and governments should continue to invest in programmes to help 

strengthen the intangible capital of SMEs.  

Firms had to respond to major restrictions such as social distancing requirements and 

working from home (WFH) directives. They responded to the impact of the pandemic in two 

principal ways (Popper and Velu, 2021), the first being to make supply chains more agile. For 

example, many supply chains were configured for a “just-in-time” delivery model based on 

optimisation methods enabled by digital technologies. Firms are reconsidering building supply 

chains based on “just-in-case” principles, whereby inventory is held on the assumption that it 

might be needed urgently in the case of supply chain disruptions. However, “just-in-time” has 

benefits, such as being less tolerant of defective parts, thereby improving both quality and the 

relationship between partners from the close collaboration (Yoffie, 2022). Hence, firms might 

want to adopt the best of “just-in-time” while incorporating some of the principles of “just-in-

case”. Moreover, firms have also begun to build supply chains that are more focused on 

domestic supply rather than relying on international supply. However, the IMF has recently 

warned that such domestically reliant supply chains might not be as robust as diversified supply 

chains, which could be more resilient to global disruptions (Wall Street Journal, 2022).  

The second way that firms responded to the impact of the pandemic was to cut out the 

middleman to get closer to the customer. For example, a large European personal-care company 

developed a direct customer model without the need to sell through retailers by developing its 

investment in “virtual tryouts” (such as mixing hair colouring), which allow customers to apply 

beauty products digitally while receiving real-time advice. Moreover, a US-based multinational 

conglomerate decided to remove long-standing intermediaries from its distribution channels 

and go direct to customers, similar to Amazon’s business model. The firm felt that 

intermediaries provided fewer insights, such as whether the products were bought for stock or 

immediate use, especially during the crisis period. These two principal approaches require 



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firms to adopt a more agile strategic planning process, which is just as much about stopping 

doing an initiative as it is about starting to develop new business models as firms prepare for a 

more volatile crisis-management environment. Moreover, the possibilities that biology and 

biotechnology might bring to solve various problems of humankind were highlighted by 

scientists even before the pandemic, for example, the benefits arising from the convergence of 

biology with engineering (Hockfield, 2019). Such a promise became a reality with the sheer 

speed of development of the COVID-19 vaccines, especially the promise that mRNA vaccines 

as a foundational technology might bring to society.70 

In addition, one of the key lessons arising from the crisis is for firms to think in a more 

allocentric71 manner, to work more collaboratively across firms and other stakeholders to 

address future crises in the most efficient and effective manner (Pedersen et al., 2020). Hence, 

it is important, as firms develop the new normal and build back better after the crisis by 

adopting digital technologies, for such an allocentric model to become one of the basic 

principles for new business model design. We next review the role of the state and economic 

systems in designing and accommodating business models for the benefit of society. 

10.3 State Capitalism and Business Model Design Choices 

The East India Company (EIC) provides the principles to examine such issues, as it was one of 

the major corporations that started as a private company before being run as a state-owned 

institution, accounting for half of the world's trade during the mid-1700s and early 1800s 

(Farrington, 2002). Adam Smith, in his famous treatise on The Wealth of Nations, was critical 

 
70 The standard conventional vaccine works by injecting a dead or weakened form of a pathogen into the body, 
which then trains the immune system to recognise and respond to the infection. In contrast, RNA vaccines 
introduce a messenger RNA (mRNA) sequence that contains the genetic instructions for the body to produce the 
vaccine antigens and generate an immune response to the infectious agent (Pardi et al., 2018). 
71 Allocative implies a community minded approach, whereby a firm’s interest is centred on other firms’ 
objectives as well. 



322 
 

of the EIC (Smith, 1776).72 The EIC was granted a licence to trade in 1600 with the objective 

of procuring goods (such as silk) and food items (such as spices) from the then wealthy states 

in the East Indies – the Indian subcontinent and South East Asia. The British government had 

to renew the charter of the EIC every 20 years, as it viewed the firm as a low-cost source of 

finance and a way of outsourcing the objective of pursuing its interests in Asia. Although the 

EIC was seen as economically successful in its first decade, the company got into financial 

difficulties in the mid-1700s because of its monopoly power and poor governance structure73 

(Robbins, 2006).  

The EIC had obtained Diwani rights in Bengal in 1765. Diwani was a grant to collect 

taxes by the Mughal emperor, who remained the nominal sovereign of Bengal and received 

geographical protection from the EIC. One of the main bones of contention was whether a 

private company such as the EIC should have sovereign rights to the lucrative patronage of 

collecting taxes. If the UK Crown or Parliament gained control of this patronage, it would be 

likely to have enormous influence as an arbiter of British politics. Hence, freedom was given 

to the EIC in order to retain the balance of power in Britain, with the consequence of not being 

able to resolve the mismanagement of affairs in India. However, the Seven Years’ War (1756–

63) left Britain victorious but nearly bankrupt.74 The British prime minister at the time, William 

Pitt, saw the Diwani as a divine intervention to fill the coffers of the Treasury.  

As part of this initiative, in 1766 the company agreed to pay the Treasury an annual tax, 

which then permitted the firm to pay an annual dividend of 12.5%. However, the EIC collapsed 

 
72 The East India Company was originally chartered as “Governor and Company of Merchants of London Trading 
into the East-Indies” and is also known as “The John Company”.  
73 For example, the EIC had directors who leased their vessels to the company, which resulted in the firm renting 
more vessels than needed at a higher price. These directors were often shareholders, and hence the rental of 
the vessels can be seen as a redistribution of corporate rents, as they could maximise personal gains by trading 
off losses from the EIC against the higher rental income (Hejeebu, 2015). 
74 The Seven Years’ war was a global conflict between Great Britain and predominantly France but also with 
other European countries for global pre-eminence.  



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in 1772 and needed a bailout of government loans. This was granted after much debate in 

Parliament, which gave the British government effective control over the EIC.75 Warren 

Hastings was the first governor general of India; his official residence was Belvedere House in 

Calcutta, as shown in Figure 1.  Although the EIC was effectively transferred to the British 

government, the company continued to have a level of independence in administrative affairs 

in India. It even had its own armed forces to protect its interests and govern the territories under 

its control in India and elsewhere. However, the level of unequal trading in the relationship 

contributed to a continual drain of resources, resulting in harm to the traders and producers in 

India. Moreover, the continued engagement in a series of wars by the EIC resulted in significant 

expenditure that could not be recovered from revenue. Therefore, the EIC changed its business 

model in the late 1700s by emphasising the private or privilege trade model, which allowed its 

executives to buy goods in India on their own account and to use the shipping facilities of the 

company to transport them for sale.76 This inverted the EIC from being a trading business on 

its own account, employing servants as factors, to a situation whereby the servants traded on 

their own account and used the company as agent and factors by paying a commission77 

 
75 Parliament would appoint a governor general of India (the first was Warren Hastings) who had authority over 
all three presidencies in India: Calcutta, Bombay and Madras. Also, there would be a five-person council, with 
three of the members being appointed by Parliament. 
76 Such private trade was allowed among the captains, officers and crew of the EIC based on a sliding scale of 
cargo value and space, respectively, depending on their rank. Although the EIC allowed private trade between 
its officers and the local merchants in India, which sometimes contributed to corruption and abuse of power, 
scholars have argued that such a practice was the basis of the success of the English East India Company in the 
18th century compared to the Dutch East India Company (Verenigde Oostindische Compagnie – VOC) and the 
French East India Company (Compagnie Royale des Indes Orientales), which initially did not permit such trading 
but subsequently allowed the practice. Private trade was seen as a strategic complement to company trading, 
as it allowed the EIC to attract and retain servants as an inducement to enhance their own earnings, as well as 
providing information on the network of trading patterns, which was beneficial for the performance of the 
company (Berg et al., 2015; Hejeebu, 2005).  
77 Edmund Burke, a Member of Parliament in the House of Commons in Great Britain (Marshall, 1981), was a 
major critic of this business model of the EIC and its unequal power over India. Moreover, there was general 
disagreement between members of the Court of Directors of the EIC about permitting such private trade (India 
Office Records, 1800–2).  



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(Marshall, 1981). However, this new business model was barely profitable and was unable to 

save the firm from its difficult financial situation.    

 

 

Figure 10.1: Belvedere House in Calcutta 

 

Source: India Office Records, The British Library 

Following the Indian Rebellion or Indian Mutiny of 1857, under the provision of the 

Government of India Act, the British government nationalised the East India Company, which 

was dissolved in 1858; the British government, through the India Office, then took over its 

assets, administrative powers and its armed forces. The EIC is an example of a firm that started 

as a private company and increasingly become government-owned until its full nationalisation. 

The degree of arms-length governance arrangement, partial ownership and then full 



325 
 

nationalisation by the British government influenced the design and objectives of the firm, and 

hence its business model, including how value was created and distributed among its 

stakeholders. The case of the EIC shows that state capitalism can determine the economic and 

well-being outcomes of countries. 

The structure of state capitalism could influence how firms are owned by the 

government for certain strategic purposes, to pursue economic or political gaols (Musacchio et 

al., 2015). Hence, the business model design of state-owned enterprises (SOEs) will have 

implications for how value is created and distributed to stakeholders. Although there are 

generally accepted definitions of state capitalism, a country can be considered state capitalist 

if the government has an ownership stake in, or significant influence over, more than one-third 

of the 500 largest companies – by revenue – in that country (Kulantzick, 2016). Under this 

definition, some of the major global economies, such as China, Brazil, India and Russia, 

practise state capitalism, to different degrees. State-capitalism-based firms could have both 

positive and negative consequences. For example, over three decades ago the Brazilian 

government provided aircraft manufacturer Embraer with lucrative contracts and related 

subsidies in order to compete with Boeing and Airbus in producing regional jets. This 

government ownership, combined with preferential treatment, enabled Embraer to become the 

world’s largest producer of regional jets and the third largest producer of civil aircraft after 

Boeing and Airbus. In the 2000s and 2010s Russia developed a reputation for using its state-

controlled natural gas giant, Gazrpom, which has the largest gas reserves in the world, as a 

means to curtail the power of other states, such as Ukraine. For example, during 2013–15 

Russia used Gazprom to threaten the supply of gas to the Kremlin-opposed regime in Ukraine 

and its allies in Western Europe.78 

 
78 Russia invaded Ukraine in February 2022, resulting in major economies such as the US and UK promising to 
stop buying hydrocarbon-based products such as natural gas from Russia (Financial Times, 2022).  



326 
 

There are four major perspectives when it comes to accounting for state capitalism’s 

strategic behaviour: the managerial view, the social view, the political view and the institutional 

based-view (Mussacchio et al., 2015). The first three imply a negative relationship because of 

the liability of state-ness, while the fourth implies a positive relationship between state 

ownership and profitability. According to the managerial view, SOEs will face conflicts 

between managers and government objectives; in the social view the government will use SOEs 

to pursue social objectives; and in the political view politicians will use these SOEs to direct 

political gain. According to the institution-based view, SOEs could fill institutional voids in 

certain counties that lack appropriately developed product, labour and financial markets, hence 

reducing transaction costs and improving productive efficiency, which contributes to increased 

profitability. Hence, the degree of state ownership between wholly owned, state as majority 

investor,79 state as minority investor80 and state strategic involvement,81 to direct industrial 

policies, could influence the degree to which the four major perspectives on state capitalism’s 

strategic behaviour plays out in terms of business model design, with consequences for value 

creation and distribution. Some scholars have argued that there is an increasing resurgence of 

state capitalism seeking to learn from past failures of the liabilities of state-ness, while 

leveraging the benefits (Kulantzick, 2016). In addition, some scholars have studied the impact 

of privatisation – the transfer of ownership of state-owned organisations to private stakeholders 

– on the efficiency and effectiveness of the business model, whereby a balanced view is called 

 
79 For example, firms with majority state ownership include oil majors such as Rosneft in Russia, Petrobas in 
Brazil and Sinopec in China. Banking firms include Sberbank in Russia, the Bank of China and the State Bank of 
India.  
80 For example, firms with minority state ownership include Deutsche Telecom and France Telecom in Europe 
and the Life Insurance Corporation of India.  
81 For example, the South Korean model of development involves the state acting as a country-level catalyst of 
private entrepreneurship in order to encourage the development of certain strategic industries by taking a 
minority stake in certain firms.  



327 
 

for so that society is not in a situation where profits are privatised and losses are socialised 

(Radic et al., 2021).  

Some scholars have argued that the liberal market structure of the United States has 

contributed to the increased financialisation of US corporations as they have transitioned from 

the old economy to the new digital economy (Lazonick, 2010). The new economy, based on 

digital technologies, requires a more open architecture, with less proprietary technology, 

compared to the old economy and the focus on organisational learning as the core 

competencies. The new economy has led to vertical specialisation compared to the more 

vertical integration of the old economy model. The inter-firm mobility of labour and liquid 

capital markets were needed to grow the new economy firms. Professional, technical and 

administrative staff needed to eschew the security of the established old economy of job 

security for the inducement offered by stock options based on potential initial public offerings 

(IPOs). As a result, there has been increased financialisation of the business models of US 

corporations, whereby the performance of the firms is measured by financial measures such as 

earnings per share. The inducement of executive compensation via stock options fuelled firms 

to adopt a programme of stock buy-backs to boost their respective share prices. This separates 

the interests of those who exercise strategic control from the rest of the corporation, sacrifices 

the interests of employees for the sake of booking profits, and reduces the financial 

commitment to invest in innovation. Such trends have exacerbated inequity because certain 

groups are able to extract more value and instability, with this value extraction undermining 

the ability to invest in productive capabilities. It has been argued that the financialisation of the 

business models of US firms might restrict the potential for economic growth (Lazonick, 2010).  

 

 



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10.4 Discussion 

The basic premise of the business model is to ensure that the benefits of science, technology 

and knowledge for human progress in other dimensions of the humanities and the social 

sciences are translated into value for society to foster economic, social and general well-being. 

In doing so, we must remember that business models are the mechanisms that enable value to 

be created, delivered and captured through a collaborative network of stakeholders. On the one 

hand, the financial crisis of 2008 showed how the design of the mortgage value chain, whereby 

individual firms had business models designed to maximise their own returns, collectively 

resulted in amplifying risks, which contributed to the failure of firms, to the detriment of the 

market. On the other hand, the architecture of the market could also contribute to the sustained 

operations of firms that are inherently unprofitable. For example, in the 1990s General Electric 

(GE) built a financial services firm to provide financing of its aero-engine business to airlines 

(Dissanaike et al., 2022). The leasing and services business of General Electric Commercial 

and Aviation Services (GECAS) developed a significant market share between 2000 and 2008, 

to the extent that GE could benefit from aftersales services, including spare parts and repairs. 

The GE leasing services business could provide good terms, partly driven by the ability to 

convert capital expenditure for the airlines into operating expenses through sale and lease-back-

style leases, thereby benefiting from tax savings.82 This enabled GE to have exclusivity and 

priority with the aircraft manufacturer to choose the GE engine, resulting in the firm having 

more than a 65% market share in large aircraft engines during the early 2000s.83  

Airlines were not making profits because of severe competition and reduced prices, 

which benefited consumers. However, GE was able to use its power in the marketplace to 

 
82 GE also leveraged its AAA credit standing to borrow money from the capital markets on favourable terms. 
83 The bundling of financing with the sales of the aircraft engine also enables GE to provide other aftersales 
services such as spare parts and repairs. 



329 
 

provide funding to these airlines and redeploy aircrafts between airlines more seamlessly. This 

meant that the less profitable airlines could continue in business. However, the financial crisis 

brought this practice of enabling unsuccessful firms to survive to a screeching halt, with 

General Electric needing to be bailed out as a result of its heavily leveraged financial services 

business.84 The case vignette shows that the design of the business model within a wider supply 

chain could result in allocative inefficiencies but provide efficiency through creditor 

concentration in preventing the premature bankruptcy of the firms, with the consequent loss of 

consumer welfare.  

The design of economic systems themselves could foster different business models and 

hence outcomes for society. It is worth noting that two prominent scholars, Adam Smith and 

Karl Marx, studied the trading rights afforded to the East India Company and came up with 

different formulations of an ideal economic system. The shares of the EIC plummeted 

significantly after 1769 following a period of speculative trading that created a bubble in the 

share price following the news of the Diwani reaching London in 1766. This fall in the share 

price of the EIC nearly ruined several elites who were shareholders in London. Adam Smith, 

observing the financial crash of the EIC, viewed its monopoly powers as the bane of preventing 

the full forces of the market power to operate and called for more free-market-based economic 

systems in his classic treatise, The Wealth of Nations (Smith, 1776).  

The EIC’s monopoly privilege on Indian trade was lifted in 1813 and opened up to 

private competition under certain conditions, except its monopoly of Chinese trade, 

predominantly in tea.85 Leveraging its privilege to trade in China, the EIC developed the opium 

trade by growing opium in Bengal and exporting it to China, which became increasingly 

 
84 GE resorted to an emergency stock sale, including a portion to Berkshire Hathaway, because of cashflow 
insolvency at GE’s financial services business, GE Capital. 
85 This monopoly privilege was removed from the EIC in 1833. 



330 
 

lucrative,86 albeit illegal (Gao, 2019). Karl Marx went on to write a series of articles in the 

early to mid-1850s in The New York Daily Tribune – the world’s bestselling newspaper at the 

time – about how the EIC, while openly preaching free trade, was defending the monopoly of 

the manufacture of opium (Marx, 1853). Moreover, Marx went on to argue that the control of 

the EIC by the British government enabled it to plunder the Indian subcontinent and benefit a 

small portion of the wealthy society in Britain (Marx,1858). Based on these insights and other 

observations of the factory-based industrial system, Marx argued in his general writings against 

the benefits of the free-market capitalist economy based on private profit, particularly in his 

famous book Das Kapital (Marx, 1867).87 

One aspect that the above analysis brings to the fore is the meaning of profit. There are 

two theoretical positions provided by economics: the neoclassical economics of marginalism; 

and the classical political economy perspectives (Tinker, 1980). In the neoclassical view, firms 

trade in factor and product markets, and profit is therefore an indication of the firm’s market 

viability and social efficiency in utilising these resources. According to the political economy 

view, profit is conceptualised as the social power of capitalism. Therefore, in the political 

economy view, the rate of profit provides an indication of the social, institutional and 

monopolistic power of the stakeholders, with capital rather than social efficiency and 

productive efficiency. The traditional emphasis of neoclassical economics is predominantly on 

production and exchange, with less focus on the distributional conditions. The political 

economy view brings to the forefront the distribution aspects (Cooper, 1980). In fact, 

arguments have been put forward by more left-leaning economists that all creation of wealth 

 
86 Although the trade in opium was illegal, the term “unauthorised trade” was commonly used. The EIC was 
finding it difficult to sell British goods in China in order to buy tea for sale in Britain, which became Britain’s 
favourite drink by the end of the 18th century. In order to address this commercial problem, the EIC developed 
opium production in its colony in Bengal and sold it to private merchants on credit, who in turn sold it to the 
Chinese. The Chinese then paid the EIC representatives in Canton, who used the money to purchase tea.  
87 The first volume of Das Kapital was published in 1867. 



331 
 

from history is based on a collective process of the division of labour, the use of natural 

resources and the accumulation of knowledge, and hence it should be more equally divided 

(Piketty, 2022). However, more recently there has been a resurgence in the emphasis on the 

distributional implications among mainstream economics (Galor, 2022; Rajan, 2019). Rajan 

(2019) highlights the importance of understanding the economic impact on communities, and 

hence the distribution of value, as the third pillar, in conjunction with the traditional view of 

analysing markets and the state. Increasingly, these two views, based on market efficiency and 

social power perspectives, are seen as complementary, which could have enormous 

consequences for the design of business models.  

The different views from the perspective of business model design choices can be 

explored in the “Cambridge capital controversy”88 (Harcourt, 1969). At the heart of the matter 

is how to determine the rate of return to capital – profit accruing to providers of capital. The 

rate of return on capital will determine the proportion of labour and capital used for production 

and hence contribute to economic growth and employment. On one side, there are the 

neoclassical economists from Cambridge, Massachusetts, in the United States. The 

neoclassical school assumes that the rate of return to capital is based on the marginal revenue 

from the use of capital, which is assumed to be exogenously given, and the firm then chooses 

the technique of production that maximises returns subject to paying for the other factor input, 

such as labour with the wage rate.  

On the other side, there is the post-Keynesian economist from Cambridge, England, 

who argued that the rate of return on capital could only be determined by calculating the value 

of the capital (Tinker, 1980). However, the value of the capital would be based on the present 

 
88 The Cambridge capital controversy was a dispute between the proponents of two differing theoretical 
positions in economics in the 1950–60s, between economists such as Joan Robinson and Piero Sraffa at the 
University of Cambridge in England, on the one hand, and economists such as Paul Samuelson and Robert Solow 
at the Massachusetts Institute of Technology, in Cambridge, the United States, on the other. The English 
Cambridge economists were often labelled "post-Keynesian" and the US Cambridge side "neoclassical". 



332 
 

value of the income stream that is due to the capital-holders (Robinson, 1953); but determining 

such an income stream requires an assumption about how the income is distributed between 

labour and capital, and no rationale can be provided for choosing one distribution over another. 

Therefore, the neoclassical view of being able to determine the rate of return to capital based 

on the marginal revenue product is indeterminate unless a distribution of income is assumed 

beforehand. However, the distribution of income for capital is what the analysis seeks to 

identify in arriving at the rate of profit – and hence the return to capital (Harcourt, 1969). 

Therefore, there are in-built assumptions – which might be difficult to defend – inherent in 

some of the production function models related to determining productivity and the 

corresponding rate of growth of the economy.  

The Cambridge capital controversy highlights that the chosen blueprint of the technique 

of production would determine the distribution of income between labour and capital – and 

hence the rate of return on capital.89 Chandler – through detailed case studies of the changes to 

business models through both vertical and horizontal integration to get the benefits of 

economies of scale and scope – shows how the tension between labour and capital in 

manufacturing drove the design of incentives and business models, which led to the growth of 

American business (Chandler, 1977). Studies have shown that the choice of business model 

design and the boundary of the firm could have an impact on productivity, and hence economic 

growth (Coyle, 2019; Wannakrairoj and Velu, 2021). Moreover, there has been much debate 

in the literature about whether mission-oriented state investment is needed to take discoveries 

from science to innovation that are useful to society or whether state intervention alone is 

 
89 Robert Allen coined the term Engel’s pause (based on Friedrich Engels, The Condition of the Working Class in 
England in 1844, where he argued that labour was losing out to capitalism as part of the Industrial Revolution) 
to describe the two-stage growth in labour’s share of income in 19th-century England (Allen, 2009). In the early 
part of the 19th century, the growth of capital as part of the Industrial Revolution caused output to increase and 
the share of income to capital to increase, at the expense of labour income – hence, “Engel’s pause”. However, 
once the capital accumulation took place as part of the Industrial Revolution, the share of wages in income grew 
in line with labour productivity. 



333 
 

sufficient to address market failure (Mowery, 2010; Mazzucato, 2013). There are ample 

examples from history that strategic state interventions to address grand themes on societal 

challenges – such as national development, national security, poverty alleviation, health 

challenges, and others – can be powerful at a system-wide level and can overwhelm any 

calculations based on welfare economics and market failure (Janeway, 2018; Lerner, 2009). 

This comparison between mission-oriented state policies and market failure interventions could 

have significant implications for business model design choices. 

10.5 Concluding Remarks 

This book has proposed that it is necessary to have a holistic-systems-based perspective to 

enable business model innovation – a perspective that highlights the hierarchical nature of 

business models, whereby the combination of activities comprises subsystems, which, in turn, 

can be connected to other subsystems. A change in one component of the system could have 

complex effects on other components, which contributes to new business model innovation. 

Hence, the design and adoption of new business models require leadership that combines an 

understanding of techno-economic and political challenges. The adoption of new business 

models is key to tackling the opportunities provided by digital technologies and to addressing 

issues related to sustaining the leadership of incumbent firms, scaling up start-up firms and 

promoting the competitiveness of SMEs. These business models are required to tackle some of 

the most challenging issues faced by society today, including climate change and various socio-

economic development issues; they need to be managed bearing in mind the conduct-related 

issues of maintaining fair customer and market outcomes. 

It is imperative that the business model, which acts as the blueprint for strategic change, 

be designed by not only paying attention to the architectural configuration at firm level but also 

by looking within the industrial system and the economic system that they operate. This multi-



334 
 

level systems perspective of the design of business models is needed to address some of the 

most pressing challenges that humans face today in terms of climate change, healthcare, 

education, economic inequality and achieving emotional and mental well-being, among others. 

We are fortunate to have the benefit of digital technologies and other emerging technologies 

from both the physical and biological sciences to address these challenges by designing suitable 

business models. We hope that this book provides some of the basic conceptual frameworks 

for designing business models to inspire those in academia, industry and government to work 

collectively to foster economic and social development that is fair and just for all. 



335 
 

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