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Investigating Green Supply Chain Management Practices and Performance:  
The Moderating Roles of Supply Chain Ecocentricity and Traceability  
 
 
Paul D. Cousins 
School of Economics, Finance, and Management 
University of Bristol. 
Bristol, UK. 
 
Benn Lawson 
Cambridge Judge Business School 
University of Cambridge 
Cambridge, UK. 
 
Kenneth Petersen 
Helen Robson Walton Chair in Marketing Strategy. 
Michael F Price College of Business 
University of Oklahoma, USA. 
 
Brian Fugate 
Oren Harris Chair in Transportation 
Walton College of Business 
University of Arkansas, USA 
 
 
 
 
Accepted for publication in International Journal of Operations & Production 
Management (DOI: 10.1108/IJOPM-11-2018-0676), May 2019  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
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Investigating Green Supply Chain Management Practices and Performance: The 
Moderating Roles of Supply Chain Ecocentricity and Traceability  
 
 
Abstract:  
 
Purpose: Sustainable supply chain management has become an increasingly important driver 
of business performance. Understanding the contingent nature of how performance is 
improved in this context is, therefore, a critical task for management. We explore the 
moderating effects of two practices unique to sustainable supply chain - ecocentricity and 
supply chain traceability - on a firm’s environmental and operating cost performance. 
 
Design: Survey data were collected from 248 UK manufacturing firms and analyzed using 
moderated hierarchical regression.  
 
Findings: The results suggest that green supply chain management practices (GSCM) are 
associated with improvements in both environmental and operating cost performance. 
Further, higher levels of ecocentricity and supply chain traceability are associated with 
stronger relationships between green supply chain management practices and cost 
performance. Contrary to expectations, high levels of supply chain traceability were found to 
negatively moderate the relationship between green supply chain management practices and 
environmental performance.    
 
Limitations: Our research design was survey-based and cross-sectional. Future studies would 
benefit from longitudinal research designs that capture the effects of GSCM practices on 
performance over an extended period. Our survey data is also perceptual; using secondary 
data to capture environmental performance outcomes, for example, would be another 
opportunity for future research.  Finally, the ecocentricity and supply chain traceability scales 
are newly developed and more work needs to be done to validate these scales. 
 
Practical Implications: We provide additional support to findings that green supply chain 
management practices benefit both environmental and cost performance dimensions. In this 
context, we show that investments by firms in working with a broader set of eco-system 
partners (ecocentricity) and building supply chain traceability influences the effects of GSCM 
practices on performance. We encourage managers to carefully consider how they 
conceptualize and monitor their supply chains. 
 
Originality: This paper offers several contributions to the research in this area. First, we 
develop and validate a measurement scale for ecocentricity and supply chain traceability.  
Second, we show how these two variables – unique to sustainable supply chains – can 
positively influence cost and environmental performance.  
 
  
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1. Introduction 
Firms have increasingly adopted practices aimed at addressing environmental issues in their 
supply chains. The preponderance of extant literature suggests that the implementation of 
green supply chain management practices (GSCM) has a positive effect on both 
environmental performance (e.g. Geng, Mansouri and Aktas, 2017; Sadia, Kaur, Ersoz, 
Lotero and Gerhard-Wilhelm, 2019) and operating cost performance (e.g. Schmidt, Foerstl 
and Schaltenbrand, 2017). Other studies suggest managers face significant challenges to 
realizing fully the benefits of GSCM practices (Kirchoff, Omar and Fugate, 2016), perhaps 
resulting from a host of possible barriers to their implementation (Goyal and Kumar, 2017). 
In this vein, our research seeks to understand why performance outcomes might vary across 
different implementations of GSCM practices and is directly motivated by calls for research 
to explore the broader moderating effects on GSCM implementation (Montabon, Pagell and 
Wu, 2016; Pagell and Shevchenko, 2014; Touboulic and Walker, 2015) and performance 
outcomes. Most broadly, our research seeks to examine this central focal GSCM/performance 
relationship in the context of predicted moderators, which is an approach that is critically 
important to developing stronger and more robust GSCM theory (Fawcett and Waller, 2011; 
Goldsby and Autry, 2011; Maloni and Carter, 2006; Markman and Krause, 2016).  
 Our paper focuses on two moderators unique to a sustainable supply chain 
management context - namely ecocentricity and supply chain traceability – each of which has 
been theorized to be a key moderator that influences the effectiveness of GSCM practices 
(Pagell and Wu, 2009). We conceptualize ecocentricity as the firm’s proclivity to engage and 
learn from external stakeholders to achieve sustainability goals.  Various scholars, and in 
particular Pagell and Wu (2009), have argued that the notion of ecocentricity is under-
developed and lacks empirical measurement (Gold, Hahn and Seuring, 2013; Paulraj, 2011; 
Wu and Pagell, 2011).  In order to address these concerns, we developed a measurement scale 
4 
for ecocentricity.  Supply chain traceability assesses the level of knowledge of the firm with 
regard to the location and processes of their products from its original source to its end 
customer (Dabbene, Gay and Tortia, 2014; Skilton and Robinson, 2009; Wowak, Craighead 
and Ketchen, 2016). Whilst widely used in practice, traceability as pointed out by Hoejmose 
et al. (2012), has received relatively little empirical attention.  In order to address these 
concerns, we also develop and validate a measurement scale for supply chain traceability.   
Intuitively, supply chain ecocentricity and traceability are likely to play a contingent 
role on the relationship between GSCM practices and a firm’s cost and environmental 
performance. Consider that much of a firm’s ability to attain its corporate sustainability 
standards (CSS) resides outside of its direct organizational control, often within the multiple 
tiers of its upstream suppliers (Grimm, Hofstetter and Sarkis, 2016). Often under-estimated 
however is the important role played by non-traditional supply chain actors, like industry 
associations and NGOs who hold valuable knowledge and expertise to address environmental 
performance. Similarly, the ability to track materials from the point of origin to the point of 
consumption underpins firm abilities to identify and address specific areas of environmental 
risk within its supply chains. Indeed, the reputational risks arising from a lack of supply chain 
traceability may be substantial (Hajmohammad and Vachon, 2015; Hartmann and Moeller, 
2014; Roehrich, Grosvold and Hoejmose, 2014; Wright, 2016).  In sum, an interesting 
question remains – in the presence of supply chain traceability and ecocentricity, does the 
relationship between GSCM practices and performance (environmental and cost) improve 
(or worsen)?   
We conducted an empirical study that employed a survey of 248 manufacturing firms 
who operate in the United Kingdom.  In doing so, we make several contributions to the 
literature. First, we develop and validate empirical scales for supply chain ecocentricity and 
traceability.  Second, we examine how GSCM practices are associated with environmental 
5 
and operating cost performance.  Most importantly, we examine the GSCM practices-
performance link to understand the importance supply chain traceability and ecocentricity as 
moderators of the relationship between GSCM practices and both cost and environmental 
performance.    
The remainder of our paper is structured as follows. First, we review the literature to 
develop the foundation of our theoretical model, with a specific focus on the hypotheses 
among green supply chain management practices, environmental and cost performance, and 
the moderating roles of ecocentricity and supply chain traceability. Our research method, data 
analyses, and results are then overviewed. Finally, we discuss our results and conclude with 
both theoretical and managerial implications. 
 
2. Literature Review and Hypotheses Development 
2.1  Theoretical background: The Natural Resource-Based View (NRBV)  
The Natural Resource-Based View (NRBV), proposed by Hart (1995), grew out of the earlier 
developments of the Resource-Based View (RBV) of the firm (Barney, 1991; Penrose, 1959). 
The RBV provides a theoretical framework to explain how a firm may mobilise its valuable, 
rare and inimitable resources to achieve sustainable competitive advantage (Barney, 1986; 
Wernerfelt, 1984).  Indeed, it is the inimitable nature of a firm’s strategic resources that 
protects the firm against its competition. Hart (1995: 956), however, argues that RBV theory 
places an over-reliance on internal resources and does not adequately consider the role of the 
natural environment.  Firms should not only consider the resources at their disposal, but also 
how those resources ‘fit’ with the external ‘natural’ environment.  Hart (1995) maintains that 
it is this ‘fit’ that can bridge the internal and external deficiencies within RBV theory, and 
thus proposes NRBV to better understand this fit between an organisation and its natural 
environment.   
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Specifically, NRBV highlights that sustainability practices are resources that 
competitors cannot easily imitate or acquire because of institutional or capability constraints 
and thus may be considered “strategic resources” from an RBV perspective (Hart and 
Dowell, 2011).  The NRBV accordingly calls for a focus on the natural environment, arguing 
that firms are constrained not just by their internal resources, but also by the availability and 
cost of external environmental resources.  
Three inter-related environmental strategies are proposed by NRBV: ‘pollution 
prevention’ (minimizing environmental damage and degradation such as emissions reduction, 
packaging reduction and so on), ‘product stewardship’ (minimizing life-cycle costs of 
products through, for example, product modification or redesign), and finally, ‘sustainable 
development’ (minimizing the environmental burden of the firm on the natural environment 
(the latter was relabelled as ‘clean technologies’ by Hart and Ahuja (1996)). These three 
‘natural environment’ strategies, within the confines of RBV, could prove to be a source of 
sustainable competitive advantage.  Importantly, green supply chain management practices 
may be considered key to carrying out these three natural environment strategies.    
 
2.2  Green supply chain management practices and performance    
Carter and Rogers (2008: 368) define GSCM as the “strategic, transparent integration and 
achievement of an organisation’s social environment, and economic goals in the systematic 
coordination of key inter-organisational business processes for improving the long-term 
economic performance of the individual company and its supply chains.” Building on this 
definition, we follow Tachizawa et al. (2015) who further contends that GSCM as a 
conceptual approach should be differentiated from the practices of GSCM.  We focus our 
attention on GSCM practices specifically, which include organizational core tactics such as 
7 
internal environmental management, green purchasing, supplier selection, and investment 
recovery. 
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Insert Figure 1 About Here 
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 The positive association between GSCM practices and improved environmental 
(Geng, et al., 2017; Rao and Holt, 2005; Russo and Fouts, 1997; Sadia, et al., 2019; Zhu, 
Sarkis and Geng, 2005) and cost performance (Geng, et al., 2017; Pullman, Maloni and 
Carter, 2009; Zhu, et al., 2005) is well established. The principal objective in this research 
was thus to examine the contingencies that affect these relationships. Nonetheless, we present 
the GSCM practices-environmental and -cost performance links as baseline hypotheses for 
the purpose of statistical testing (e.g., Kim, Hur and Schoenherr (2015)), and for further 
empirical support of these important relationships. 
These hypotheses are grounded in NRBV, which has a particular focus on achieving 
competitive advantage within the constraints of the natural environment (e.g., Bals and Tate, 
2018) by focusing resources to develop capabilities to deploy environmental practices to 
achieve environmental goals. NRBV also provides support that GSCM practices lead to 
improved economic performance (e.g., Pullman, et al., 2009; Zhu, et al., 2005).  In particular, 
significant cost advantages can result from GSCM practices (Carter, Kale and Grimm, 2000), 
such as superior waste management, use of less expensive recycled raw materials, energy 
consumption, environmental accidents and number of components in products (Jacobs, 
Singhal and Subramanian, 2010), and pollution prevention, which limits the cost of 
compliance with environmental regulations (Hart, 1995). 
H1a:   Green supply chain management practices are positively associated with 
environmental performance improvement. 
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H1b.  Green supply chain management practices are positively associated with 
operating cost performance improvement. 
 
2.3  The moderating role of supply chain ecocentricity  
Pagell and Wu (2009, p. 50) argue that firms possessing a proclivity for environmental 
sustainability will “reconceptualize who is in the supply chain,” such that they will leverage 
the expertise and skills of external environmental stakeholders. This notion of 
“reconceptualising” the supply chain stems from research in the area of ecocentricity 
(Gladwin, Kennelly and Krause, 1995; Seuring, 2004), which is defined as a characteristic of 
firms that consider the well-being of, and potential learning benefits gained from, their 
broader constituents in the environment.  Ecocentricity has been discussed in the literature 
from a theoretical and conceptual perspective (e.g. Chavez, Yu, Feng and Wiengarten, 2016; 
Gold, et al., 2013), but has received limited empirical attention (Pagell and Wu, 2009). 
NRBV suggests that key resources must be in place to facilitate core managerial practices. 
Ecocentricity may be such a key resource, as it is rare and non-imitable—the notion of 
ecocentricity involves collaborative, relational, and cultural characteristics of the 
organization, each of which are noted with NRBV as being especially challenging to imitate 
easily by other organizations.   
Firms are frequently influenced by environmentally-focused external stakeholders 
such as regulatory bodies, government, non-governmental organizations, and trade 
associations. Firms  that lack supply chain ecocentricity may view these environmental 
external stakeholders as adversaries (Pagell and Wu, 2009), associating regulatory bodies and 
government as a source of coercive pressure (Zhu and Sarkis, 2007) and feeling threatened by 
regulators who levy legal action, penalties and fines if they do not comply with 
environmental regulation (Sarkis, Gonzalez-Torre and Adenso-Diaz, 2010).  These firms may 
attempt to satisfy the institutional forces in their social context (Dacin, Oliver and Roy, 2007) 
9 
to gain legitimacy with their external environmental stakeholders (Bansal and Clelland, 2004; 
Suchman, 1995), instead of engaging and learning to continuously improve.  Thus, their 
practices to improve environmental performance may be out-of-date with the most current 
and innovative green supply chain management thinking.  If ineffective, such green practices 
may even be viewed as superficial “greenwashing” (Laufer, 2003).  Ignoring this expertise, 
such as recently revised standards of environmental conduct and compliance (Tate, Dooley 
and Ellram, 2011) from environmental external stakeholders may even result in conducting 
GSCM practices that damages, rather than improves, the environment.   
Other business organizations, however, actively seek environmental supply chain 
capabilities embedded in their external stakeholders with the hope that they might drive 
substantive environmental improvements in their firms (Borwankar and Velamuri, 2009). 
These partnerships reflect an integrative arrangement where actors across sectors engage in 
non-hierarchical processes to achieve mutual goals (Van Huijstee and Glasbergen, 2010; 
Visseren-Hamakers, Arts and Glasbergen, 2011). Engaging these environmental stakeholders 
may well result in obtaining insights about cleaner transportation methods or the ecological 
packaging of materials about which the firm was previously unaware (Johnson, Dooley and 
Hyatt, 2018).  Learning from external environmental stakeholders may facilitate more 
accurate definitions and measurement of standards for green product purchasing and 
environmental criteria for supplier selection (Tate, et al., 2011).  Thus, firms with a high level 
of supply chain ecocentricity will proactively engage environmental stakeholders in these 
efforts to enhance the effectiveness of GSCM practices on the environment (Simpson, Power 
and Samson, 2007).   
H2a.  The relationship between GSCM practices and environmental performance 
improvement is stronger when a firm has high levels of supply chain 
ecocentricity, rather than low.  
10 
 
Similarly, engaging in and learning from environmental stakeholders should enhance 
the cost improvements resulting from GSCM efforts.  Non-traditional supply chain members, 
such as NGOs, not-for-profits, and local governments can offer expertise in environmental 
technologies and processes that are most economical (Tate, et al., 2011).  Such expertise 
should facilitate the planning and operational practices that have become embedded in 
organizational routines, improving efficiencies. By contrast, in less proactive firms they 
might be non-existent (Matos and Hall, 2007).  Additionally, gaining access to recent 
environmental technologies and processes may reduce conflicts and confusion among 
managers who are implementing GSCM which, in turn, leads to decreased costs stemming 
from the improved alignment of environmental supply chain practices with relevant 
environmental issues (Sarkis, Zhu and Lai, 2011).  Approaches that foster cooperation and 
environmental learning from environmental stakeholders should also result in knowledge 
allows the firm to mitigate risks from potential legal action, penalties, and fines associated 
with GSCM implementation (Roehrich, et al., 2014).  Supply chain ecocentricity may even 
facilitate partnerships with non-traditional environmental supply chain members that assist in 
off-setting costs of GSCM investments (Pagell and Wu, 2009).   
H2b.  The relationship between GSCM practices and operating cost performance 
improvement is stronger when a firm has high levels of supply chain 
ecocentricity, rather than low.  
 
2.4  The moderating role of supply chain traceability  
The monitoring of supply chain activities has received relatively less attention in the 
literature (Faucheux and Nicolaï, 2011; Jenkin, McShane and Webster, 2011; Setterstrom, 
2008; Wang, Yeung and Zhang, 2011).  Monitoring is, however, an important risk 
11 
management tool to reduce information asymmetry (Tachizawa, et al., 2015). One particular 
approach to monitoring is through the use of traceability (Wowak, et al., 2016).  Traceability 
is broadly defined as the ability to identify and verify the components and chronology of 
events throughout the supply chain (Skilton and Robinson, 2009).  It refers to tracking, which 
is determining the origin and characteristics of a particular product and tracing, which is 
collecting the history of products related to its displacement along the supply chain (Bechini, 
Cimino, Marcelloni and Tomasi, 2008). Traceability involves, for example, knowing the 
sources of raw materials, what chemicals or elements are in purchased products, tracking the 
environmental performance throughout the supply chain and processes involved in producing 
products, and tracing the origins of purchased products throughout the supply chain 
(Dabbene, et al., 2014).  Traceability is particularly relevant under the premise of NRBV 
(Pullman, et al., 2009), exhibiting the NRBV criteria necessary for a natural resource to 
sustain advantage: it is rare and non-imitable, achieved via characteristics of causal ambiguity 
and complexity (Hart, 1995).  Indeed, traceability it is not dependent on a single company, 
but relies on the complexities of a group of companies, such as intra- and inter-firm 
technologies and supply chain knowledge (Wowak, et al., 2016), that are challenging to copy 
(Skilton and Robinson, 2009).   
In particular, the ability to track and trace products and activities reduces information 
asymmetry among supply chain members and the potential for suppliers to act 
opportunistically (Wowak, et al., 2016), which positively moderates the effect of 
organizationally focused GSCM practices on environmental performance (Plambeck, Lee and 
Yatsko, 2012).  Traceability affords an improved level of monitoring, which has empirically 
been shown to increase suppliers’ initial and ongoing investments in environmental initiatives 
(Klassen and Vachon, 2003; Lee and Klassen, 2008), enabling an increased environmental 
performance impact of GSCM practices. Without supply chain traceability, the efforts of 
12 
firms to improve performance may be hampered, and even lead to sending of wrong signals 
to their (Wowak, et al., 2016).  Thus, we propose:  
H3a: The relationship between GSCM practices and environmental performance 
improvement is stronger when a firm has high levels of supply chain traceability, 
rather than low.  
Tracking and tracing products with a complex supply network involves managerial 
decisions about their supply chain to reach efficiency improvements in processing 
organization and risk management (Rábade and Alfaro, 2006).  In assessing the benefits of 
improving traceability, Alfaro and Rabade (2009) find that organizations realize several 
advantages, such as enhanced operational efficiency. They conclude that traceability 
amplifies the performance of existing operating procedures that are intended to lower levels 
of spoiled inventory, reduce stock-outs, and shorten lead-times. With respect to 
environmental impacts, supply chain traceability improves the quality of reporting to external 
stakeholders, reducing both the costs of reporting as well as the risks of potential 
environmentally related legal costs, penalties, and fines (Regattieri, Gamberi and Manzini, 
2007).  Thus, while implementing and developing GSCM practices heighten awareness by 
consumer and government stakeholders (i.e., it raises the bar on expectations), supply chain 
traceability minimizes the additional costs associated with said GSCM practices, thereby 
positively moderating their impact on operating cost performance (Meinlschmidt, Schleper 
and Foerstl, 2018).  Thus, we propose:  
H3b: The relationship between GSCM practices and operating cost improvement is 
stronger when a firm has high levels of supply chain traceability, rather than low.  
 
3.  Research Method 
3.1 Survey administration and data collection  
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A sample of 2,000 United Kingdom manufacturing firms was randomly surveyed from a 
commercial database obtained from The Manufacturer, a UK subscription-based trade 
publication. Each respondent in the sample was selected based on job function, plant size (at 
least 50 employees), and the industry sector by SIC code. We first mailed a copy of the 
survey to our entire sample. Two further email rounds were sent to non-responders.  
Respondents were also offered the incentive of a composite summary of the research results. 
We received 277 responses, of which 29 were deemed not usable due to missing data. A 
further 34 surveys could not be delivered. The effective response rate was thus 12.6% 
(248/1,966).  
The characteristics of the organizations in the sample are shown in Table 1, including 
the number of employees, industry sector and respondent title. The average number of years 
in the position was 9.32, and 15.2 years in the business unit, providing support that our 
informants were also knowledgeable about the issues under investigation. Respondents were 
asked to complete the survey with respect to their strategic business unit’s supply chain. 
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The survey was pilot tested in two phases. First, the draft questionnaire was sent to 
five academic faculty members with expertise in this area of scholarship.  These scholars 
were asked to comment on the content, clarity, and scaling of the survey instrument.  Several 
changes were made as a result of this feedback.  Next, the survey’s web address was sent to a 
further nine industry members with expertise in this area of practice.  Each was asked to 
complete the survey online, with a specific focus on the content, design, and usability of the 
instrument. Some minor design changes were also made at this stage of the survey instrument 
development process.  
Tests for non-response bias were carried out by comparing early respondents 
(responses received within the first two weeks) and later respondents (responses received 
14 
within the third week or later) (Armstrong and Overton, 1977).  A t-test of difference was 
conducted on firm size (employees and sales), and mean responses to each question.  We 
were unable to identify any statistically significant differences between earlier and later 
responses.  
3.2  Operationalization of variables  
The survey scales employed were either established scales or were developed and validated 
from the literature. In the latter case, for supply chain ecocentricity and environmental supply 
chain traceability, we followed multi-stage scale development techniques suggested by 
DeVellis (2003).  This process included several preliminary qualitative interviews with 
purchasing managers, an extensive review of the extant academic and practitioner literature, 
pretesting, and a Q-sort with knowledgeable stakeholders. All constructs are reflective and 
measured using a seven-point Likert scale (see Appendix A).  
Operating cost improvement - measured using a three-item scale used by Vachon and 
Klassen (2008). Respondents were asked to compare their organization’s total product costs, 
production costs and labor productivity, relative to primary competitors.  
Environmental performance improvement – developed by Zhu and Sarkis (2007) and 
used to assess the degree of improvement in environmental performance over the past 1-2 
years. Respondents were asked to identify metrics relating to solid waste disposal, 
atmospheric emissions, raw materials usage, energy usage, wastewater reduction and 
recycling of product and solid waste.  
Green supply chain management practices – A seven-item scale developed by 
Gonzalez-Benito and Gonzalez-Benito (2006), with respondents asked to consider the extent 
to which their firm’s logistics practices, packaging, logistics-related waste recycling, sourcing 
strategies, and supplier selection criteria considered the natural environment.  
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Supply chain ecocentricity –a new scale developed for this study, based on supply 
chain tactics identified by Pagell and Wu (2009), as well as insights from Seuring (2004), 
Gold et al. (2013) and Gladwin, Kennelly, and Krause (1995). Respondents were asked about 
the involvement of external stakeholders in improving their supply chain environmental 
sustainability and included four-items assessing the degree of external feedback sought, 
partnerships with NGOs or NFPs, and input from regulators.  
Supply chain traceability – a new scale developed for this study, based on the 
literature on inventory tracking and supply chain transparency (Dabbene, et al., 2014; Skilton 
and Robinson, 2009; Wowak, et al., 2016). Items assessed the extent to which the firm, for its 
complete supply chain, traces the origins of purchases, knows the source of raw materials, 
knows the chemicals and elements in purchased components, tracks the processes involved in 
producing product and tracks environmental performance.   
Control variables – Three additional control variables were included in the analysis. 
First, a series of dummy variables were used to control for industry, reflecting the different 
pressures and industry models within the sample. Second, organization size could influence 
the extent of engagement in green supply chain management practices and the ability to 
influence cost and environmental performance. Including the number of employees 
controlled for the size of each respondent’s organization. Finally, we control for a firm’s 
previous financial performance as this dimension may influence the ability to invest in 
making improvements in our dependent variables, environmental and cost performance.  
 
4.  Results 
Exploratory factor analysis, using principal axis factoring with oblimin rotation, was used to 
extract factors with eigenvalues greater than 1.0 (Tabachnick and Fidell, 2001). Following 
Harman’s one-factor test, all items were analyzed together, and as no one factor accounted 
16 
for most of the variance, common method variance was not considered to be a substantial 
concern (Podsakoff, MacKenzie, Lee and Podsakoff, 2003). The results of the exploratory 
factor analysis are presented in Table 2 and suggest a six-factor solution arising from the 32 
items analyzed. All factor loadings were considerably above .40 and are therefore considered 
practically significant (Hair, Black, Babin, Anderson and Tatham, 2006). Table 3 provides 
correlations and descriptive statistics.  
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Insert Table 3 About Here 
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Ordinary least squares moderated hierarchical regression was used to test the various 
hypotheses. Control variables were entered in Step 1, followed by the independent variables 
in Step 2.  Independent variables were mean centered before the multiplication of the 
interaction terms, which were entered in Step 3.  Variance Inflation Factors (VIF) were all 
below 10, indicating multi-collinearity was not a substantial concern (Neter, Kutner, 
Nachtsheim and Wasserman, 1996).   
Table 4 presents the results of the testing of our theoretical model. Hypothesis 1 was 
largely supported with GSCM practices positively related to environmental (β=.29, p<.001), 
and marginally significantly related to cost performance (β=.17, p<.10).  While we did not 
find support for Hypothesis 2a, we did find support for Hypothesis 2b, in that supply chain 
ecocentricity positively moderates the relationship between GSCM practices and cost 
performance (β=.24, p<.001).  This finding is supported by simple slope computations 
showing that high levels of ecocentricity were significant (t = 2.77, p <.01), while low levels 
of ecocentricity were non-significant (t = −-0.06, p = .95).   
We also find partial support for Hypothesis 3a, in that a significant negative 
moderation effect of traceability exists on the relationship between GSCM practices and 
17 
environmental performance (β=-.11. p<.05).  This finding is supported by simple slope 
computations showing that low levels of traceability were significant (t = 4.54, p <.001), 
while high levels of traceability were nonsignificant (t = 1.50, p = .134).  Additionally, we 
found support for Hypothesis 3b, in that a significant positive moderation effect of 
traceability exists on the relationship between GSCM practices and cost improvement (β=.20, 
p<.001).  This finding is supported by simple slope computations showing that high levels of 
traceability were significant (t = 2.54, p <.05), while low levels of traceability were 
nonsignificant (t = 2.78, p = .78).   
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To further illustrate the effects of moderation, we plot the simple slope of the 
relationship between GSCM and environmental or cost performance at high and low levels of 
each moderator. High and low values are defined as plus and minus one standard deviation 
from the mean (Cohen and Cohen, 1983).  Figures 2–4 illustrate these effects.   
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Insert Figure 3 About Here 
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5.  Discussion 
Our study examined the effects on performance arising from the adoption of GSCM 
practices, as well as the contingent effects of ecocentricity and supply chain traceability.  
Results from our survey of 248 UK manufacturing organizations indicates that GSCM 
practices are associated with improvements in cost and environmental performance, though 
the effects are moderated by ecocentricity and supply chain traceability. The remainder of 
18 
this section discusses the theoretical and managerial contribution of each finding in further 
detail.  
5.1 Theoretical implications 
Our research sought to examine the moderating effects of ecocentricity and traceability on 
GSCM practices and subsequently how it influences their impact on environmental 
performance and operating cost improvement. Our findings support the notion of using 
sustainability practices throughout the supply network (Meinlschmidt, et al., 2018), and add 
to the growing empirical evidence suggesting a positive relationship between GSCM 
practices and performance (Albertini, 2013; Carter, et al., 2000; Golicic and Smith, 2013). 
Consistent with prior literature, we find GSCM practices are strongly associated with 
improvements in environmental performance. We also find a marginally positive relationship 
between GSCM practices and operating cost improvement. Overall, our findings elaborate on 
presenting empirical evidence that sustainability simultaneously positively affects 
environmental and operating cost improvements.   
We now turn to explore the findings around the moderation effects of ecocentricity 
and supply chain traceability on GSCM practice and performance. In the development of our 
theoretical framework, we proposed that ecocentricity through collaboration with non-
traditional stakeholders and supply chain traceability as a monitoring tool may be considered 
‘strategic resources’. However, we find that their effects on the GSCM practices to 
performance link was mixed. Our first contingency considered the moderating effect of 
ecocentricity on GSCM practices and its environmental (H2a) and cost performance (H2b).  
We found no significant contingent effects of ecocentricity (at high or low levels) on 
environmental performance, but a significant positive effect on operating cost performance 
when ecocentricity was high. One explanation for these findings is that the majority of firms 
were primarily interested in low-level cost savings, and as such working with non-traditional 
19 
partners reverts to a focus on efficiency (Hart and Dowell, 2011).  It could also indicate that 
because this is a ‘collaboration’ approach it will require increased skills, flexible 
organizational design, stakeholder involvement and management, and more complex and 
long-term measurements.  Ecocentricity could, therefore, be viewed as a strategic resource 
that facilitates a system view of the value chain, which the firm uses for broader learning 
from partners to drive cost minimization and potentially other value-added strategies which 
were not covered in our study.  
Our second moderation hypothesis focused on supply chain traceability - the location 
and origin of materials, and type of processes used by suppliers – and how this affected 
performance, Tachizawa et al. (2015) refers to this as a ‘monitoring’ approach – arguing that 
this helps firms reduce risk and manage compliance to standards.  Thus, our findings provide 
further empirical support to the proposed Tachizawa et al. (2015) framework.  Moreover, we 
find that investing in high levels of supply chain traceability has a positive effect on the 
association between GSCM practices and operating cost improvement. As with supply chain 
ecocentricity, supply chain traceability provides the data and transparency needed to identify 
cost improvement opportunities.   
Second, and contrary to expectations, we found that supply chain traceability (H3a) 
had a negative moderating effect on the relationship between GSCM practices and 
environmental performance. We show that as a firm’s investment in GSCM practices moves 
from low to high levels, the rate of environmental performance improvement increases; 
however, it does so at a negative rate as greater levels of supply chain traceability are 
developed. That is, firms with low levels of supply chain traceability had a significantly more 
positive rate of environmental performance improvement, relative to firms who already had 
high levels of supply chain traceability. We also note that supply chain traceability, as our 
hypothesized moderator variable, has no direct effect on environmental performance 
20 
improvement.  This surprising finding is counter-intuitive to our conceptual model. However, 
the experience of many firms implementing traceability systems for environmental 
monitoring and compliance purposes may provide a potential explanation. Low levels of 
transparency may indicate that the firm has only limited insight into the environmental 
compliance of tier 1 suppliers, with whom they work directly and often have coercive power 
to encourage supplier compliance and adoption of environmental initiative. On the other 
hand, firms with high levels of supply chain traceability in place have a very different 
situation – they can trace the sources of their raw materials, often back to their origin as well 
as being able to track and trace product and processes throughout their supply chain 
networks. This level of traceability provides firms with a clearer picture of the challenges 
they face in achieving supplier compliance to environmental requirements throughout their 
entire supply chain, from source to customer; and let alone achieving improvements in 
environmental performance. For firms in this latter case, they may be aware of the broader set 
of improvement opportunities in their supply chain; yet their ability to achieve these 
sustainability improvements is more limited in sub-suppliers (Meinlschmidt, et al., 2018; 
Wilhelm, Blome, Bhakoo and Paulraj, 2016).  
Finally, our results advance understanding of the GSCM-performance relationship.  
Research investigating this relationship has suggested that the meaning underlying this 
association is complicated and that future research should explore more contextual factors 
that may well explain the nature of this association more fully (e.g., Jacobs, et al., 2010; Zhu, 
et al., 2005).  Our findings showed such an interaction effect, such that high levels of 
ecocentricity and supply chain traceability could act as key strategic resources when trying to 
improve cost performance by adopting GSCM practices.  
21 
5.2 Managerial Implications 
From a managerial point of view, our findings provide insights into making a case for GSCM 
initiatives within their organization, as well as how to be more effective with said initiatives.  
First, the finding of a positive relationship between GSCM and operating cost improvement 
suggests that managers seeking to enhance GSCM or propose GSCM initiatives to senior 
management team could craft their message around such synergistic effects on financial 
performance.  This implication is also consistent with recent research showing GSCM 
practices are related to superior financial and market-related performance (Schmidt, et al., 
2017).  Second, our research provides managers with a better understanding of how to carry 
out GSCM practices by promoting ecocentricity and supply chain traceability more 
appropriately.  For instance, the development of supply chain ecocentricity should be 
approached as a longer-term initiative that may not provide direct, immediate effects on 
environmental performance. It is possible that larger systems-level gains may, however, be 
achieved via collaboration with these non-traditional partners.  
Also, managers should seek opportunities to increase their supply chain traceability 
through more comprehensive monitoring systems (Bititci, Garengo, Dörfler and Nudurupati, 
2012; Hervani, Helms and Sarkis, 2005).  Organizations that have robust monitoring systems 
could use this a strategic resource, contributing to reduced supply chain risk and improved 
pollution prevention strategies. Overall, our findings suggest that managers may consider 
high levels of collaboration with non-traditional partners and active monitoring to achieve 
supply chain traceability as key capabilities when trying to achieve cost performance by 
improving GSCM practices. 
6.  Future Research & Limitations  
Our research design was survey-based and cross-sectional. Future research should explore the 
opportunities for using longitudinal data, particularly as the effects of GSCM initiatives may 
22 
influence performance differentially over time. Testing and extending this theoretical 
framework beyond United Kingdom manufacturing firms into other contexts, such as the role 
of public sector procurement requirements (Amann, Roehrich, Esig and Harland, 2014), as 
well as to an examination of social responsibility in supply chains may be beneficial. Our 
data was collected using perceptual scales. While past research has found that managerial 
assessments are consistent with objective internal performance (Dess and Robinson Jr, 1984; 
Pearce, Robbins and Robinson, 1987) and with external secondary data (Venkatraman and 
Ramanujam, 1986), future research should incorporate secondary data, for example, on 
dependent variables like environmental performance.  Finally, while the ecocentricity 
construct was developed in a way that was driven by the literature (Chavez, et al., 2016; 
Gladwin, et al., 1995; Gold, et al., 2013; Pagell and Wu, 2009; Seuring, 2004), we feel 
compelled to agree with Pagell and Wu (2009) that this construct has not received little 
empirical attention, which is both a limitation of the development of this scale as it is an 
opportunity for further research. 
Moreover, future research could explore additional practices as moderators to the 
GSCM practice-performance relationship, such as technology or innovation.  A few highly 
practical and relevant practices in this area could be, for example, blockchain, internet-of-
things, and standards (such as GS1).  Finally, given the results of our research, we suggest 
that future studies could also examine the critical impact of these practices on GSCM’s 
ability to deliver operating cost performance.   
 
7.  Conclusions  
Capturing the value from sustainability-related activities directed at their supply chains 
represents a significant challenge for most firms.  Our study contributes to this area via an 
examination of the contingent effects of GSCM practices on environmental and operating 
23 
cost performance, in particular by validating and testing two new moderating constructs: 
ecocentricity and supply chain traceability.  Consistent with prior literature, we show that 
GSCM practices help to improve both environment and cost performance; with supercharged 
benefits for operating cost improvement where the firm has high levels of supply chain 
traceability and adopts a broader view of their supply chains which incorporates non-
traditional actors. We highlight the importance to managers of focusing on both monitoring 
and collaboration activities in their supply chains to extract the benefits from their 
sustainability activities.  
  
24 
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30 
Figure 1:  Theoretical Framework 
 
 
 
 
 
  
31 
Figure 2:  Moderation effect of supply chain traceability on GSCM practices and 
environmental performance improvement  
 
 
 
 
 
Figure 3:  Moderation of supply chain traceability on GSCM practices and operating cost 
improvement 
 
 
  
32 
Figure 4:  Moderation of supply chain ecocentricity on GSCM practices and operating cost 
improvement 
 
 
 
 
33 
Table 1: Sample Characteristics 
 
Industry  Number Percentage 
Machinery & Equipment 45 18.3 
Packaging 24 9.8 
Furniture 20 8.1 
Automotive 27 11.0 
Aerospace 15 6.1 
Fabricated Metal Products 33 13.4 
Computer & Electronics 27 11.0 
Chemical & Plastics 31 12.6 
Food 7 2.8 
Missing  19 7.8 
Total  248 100 
 
Position  Number Percentage 
Director of Purchasing/Head of Supply Chain  30 12.1 
Head of Operations 10 4.0 
Purchasing/Supply Chain Manager 80 32.3 
Senior Buyer / Buyer  23 9.3 
Materials/Logistics Manager 46 18.5 
Operations/Quality Manager 33 13.3 
Environmental Manager 13 5.2 
Missing 13 5.2 
Total  248 100 
 
Organisation Size (employees) Number Percentage 
50 - 99 68 27.4 
100 -149 32 12.9 
150 - 199 18 7.3 
200 - 499 76 30.6 
500 - 999 21 8.5 
Over 1000  25 10.1 
Missing  8 3.2 
Total  248 100 
 
 
 
  
34 
Table 2: Exploratory Factor Analysis 
 
 
1 2 3 4 5 6
Environmental Performance Improvement
… Diverted solid waste from landfills 0.76
… Recycling of solid waste (not incineration) 0.76
… Reduced solid waste disposal 0.73
… Reduced raw materials usage 0.71
… Reduced emissions into the atmosphere 0.70
… Reduced waste water usage 0.66
… Reduced energy usage 0.63
… Recycling of product (not incineration) 0.62
… Decrease use of hazardous/harmful/toxic materials 0.55
Green Supply Chain Management Practices
… ecological materials for primary packaging 0.79
… recyclable or reusable packaging/containers in logistics 0.77
… selection of cleaner transportation methods 0.70
… a preference for green products in purchasing 0.69
… recuperation and recycling systems 0.64
… environmental criteria in supplier selection 0.61
… consolidation of shipments 0.53
Supply Chain Traceability
… We know the sources of our raw materials 0.87
… We track the processes involved in producing product throughout 
our complete supply chain
0.84
… We trace the origins of our purchases through the entire supply chain 0.83
… We track the environmental performance of our complete supply 0.74
… We know what chemicals or elements are in our purchased 0.63
Financial Performance 
… Profit growth 0.90
… Return on total assets 0.88
… Return on sales 0.85
… Return on investment 0.79
Operating Cost Improvement
… Total product costs 0.88
… Production costs 0.88
… Labour productivity 0.78
Supply Chain Ecocentricity
… We incorporate external feedback (e.g. from trade associations) to 
help improve the sustainability of our supply chain 0.80
… We partner with NGO’s and not-for-profit organisations to learn 
about potential solutions to environmental problems
0.72
… We actively engage external parties (e.g. customers, suppliers) in 
seeking to improve environmental performance 0.61
… We incorporate input from regulators (e.g. UK Environment Agency, 
DEFRA) into our supply chain policy and practices
0.60
Items 
Component
35 
Table 3: Descriptive Statistics 
 
 
 
 
Variable a, b 1 2 3 4 5 6 7 8 9 10 11 12
1 Operating cost improvement .89
2 Environment performance improvement .26 .88
3 GSCM practices .30 .54 .90
4 Supply chain ecocentricity .16 .52 .58 .78
5 Supply chain traceability .20 .32 .54 .42 .89
6 Industry - machinery/equipment .00 -.18 -.05 -.16 .01 -
7 Industry - automotive/aerospace .00 -.02 -.02 -.03 .05 -.21 -
8 Industry - fabricated metal -.02 -.03 -.11 -.04 -.19 -.18 -.18 -
9 Industry - chemical / plastics .01 .06 .02 .06 -.04 -.17 -.16 -.14 -
10 Industry - computer hardware / electronics -.06 .11 .03 .16 .11 -.18 -.17 -.15 -.13 -
11 Organization size (employees) .15 .12 .14 .16 .08 -.16 .16 .01 -.04 .05 -
12 Financial performance .50 .31 .32 .24 .24 -.06 .04 -.07 -.01 .04 .16 .93
Mean 4.61 5.11 4.57 4.24 4.32 .18 .17 .13 .11 .13 785.90 0.61
Standard Deviation 1.04 1.04 1.26 1.36 1.51 .39 .38 .34 .31 .33 3510.13 1.07
a Signifcant at .05 (two-tailed) when r > .125 
b Cronbach alpha shown in bold on diagonal
n=248
36 
Table 4: Results of Multiple Regression Analysis a, b 
 
 
 
 
Variables Mod 1 Mod 2a Mod 2b Mod 1 Mod 2a Mod 2b
Block 1: Controls
Industry – machinery/equipment -.12† -.12† -.11† .00 -.02 -.02
Industry – automotive/aerospace -.04 -.04 -.03 -.07 -.06 -.07
Industry – fabricated metal .01 .01 .01 -.01 -.02 -.01
Industry – chemical/plastics .02 .02 .03 -.01 -.01 -.03
Industry – computer/electronics .03 .03 .02 -.11† -.10 -.10
Organization size (log employee) .00 .00 .01 .07 .07 .06
Financial performance .13* .13* .14* .44*** .42*** .43***
Block 2: Main effects
GSCM practices .34*** .33*** .32*** .12† .17* .17*
Supply chain ecocentricity .26*** .25*** .24*** -.04 -.01 -.03
Supply chain traceability .00 -.01 .00 .05 .06 .05
Block 3: Two-way interactions
GSCM practices x Supply chain ecocentricity -.02 .18**
GSCM practices x Supply chain traceability -0.11* .15**
Adjusted R 2 0.35 0.35 0.36 0.26 0.28 0.28
F 13.72 12.44 13.06 9.27 9.55 9.23
∆R 2  b 0.00 0.01 0.03 0.02
F for ∆R 2  b 0.18 4.46* 9.08** 6.62*
a Standardized  regression coefficients are shown
b Changes in R2 are from Mod 1 within the same model
† p<.10, *  p<.05, ** p<.01, *** p<.001
Cost Performance 
Improvement
Environmental 
Performance 
Improvement