Only timeline will tell: Temporal framing of competitive announcements and rivals’ responses Sucheta Nadkarni Cambridge Judge Business School University of Cambridge Trumpington St Cambridge, CB2 1AG, United Kingdom Email:  s.nadkarni@jbs.cam.ac.uk Lingling Pan Eli Broad College of Business Michigan State University Department of Management East Lansing, MI 48824-1122 Email: panl@broad.msu.edu Tianxu Chen School of Business Administration Portland State University 615 SW Harrison Street Portland, Oregon 97201 Email: chen36@pdx.edu We would like to thank Jianhong Chen, Cynthia Devers, Gerry McNamara and Tieying Yu for their insightful comments on earlier versions of this manuscript. Only timeline will tell: Temporal framing of competitive announcements and rivals’ responses ABSTRACT Research has focused predominantly on the influence of the language firms use in their announcements on the reactions of constituents such as shareholders and the media. We extend this research by examining a new form of linguistic construction––temporal framing—in the context of competitive interactions. Building on inter-temporal choice theory, we theorized and tested how a focal firm’s temporal framing of its competitive action announcements affects rivals’ response speed. We examined three dimensions of temporal framing: temporal vagueness (lack of clarity and completeness regarding timelines); temporal distance (length of the action timeline: proximal versus distal); and frequency (repetition of vagueness and distance cues). Based on analysis of 2,130 competitive action press releases of 28 duopoly firms from 14 industries, we found that the temporal framing dimensions, both individually and interactively, were related to the response speed of rivals. Specifically, temporally vague and distally framed timelines in action announcements delayed rivals’ response speed, and increased frequency of vagueness and distance cues strengthened these effects. This study explicates the linguistic underpinnings of competitive interactions and highlights the importance of temporal framing in the competitive context. Key words: Competitive dynamics, framing, temporal vagueness, temporal distance Strategy and management scholars increasingly recognize that firms intentionally use language as a strategic tool to garner positive reactions from external constituents (e.g., investors, customers, suppliers and media) on whom the firm depends for key resources (Graffin, Carpenter, & Boivie, 2011; Graffin, Haleblian, & Kiley, 2016; Lounsbury & Glynn, 2001; Rindova, Becerra, & Contardo, 2004). Constituents lack access to the actual realities behind the focal firm’s actions and therefore rely on firm announcements as ready-made and easily accessible sources in evaluating these actions (Busenbark, Lange, & Certo, 2017; Martens, Jennings, & Jennings, 2007; Narayanan, Pinches, Kelm, & Lander, 2000). However, positive linguistic tactics aimed at garnering favorable responses from constituents (Pollock & Rindova, 2003: 634; Prabhu & Stewart, 2001; Rindova et al., 2004) may alert competitors and invite retaliation. This creates a major dilemma: How can a firm signal that it will be introducing a new product or entering a new market without tipping off competitors about these impending strategies? This dilemma is reflected in the intentionally vague description of RCAI’s entry into new markets by Gordon Davies, President of RCAI: “The new markets that we are now working in are…without competition …we do not want to alert competitors to them. Once we are comfortable with our position in these markets, we will be able to describe them to our shareholders and the public in greater detail” (Business Wire, 2005). Yet, research has focused mainly on firms’ linguistic tactics directed at garnering favorable responses from constituents without consideration of the implications of these tactics for competitors who closely watch the focal firms’ actions and whose reactions determine focal firms’ competitive advantage (Chen, 1996; Porter, 1980; Guo et al., 2017). This constitutes a major limitation, because focal firms’ goals in linguistic tactics with constituents are fundamentally different from their goals with rivals (Chen & Miller, 2015; Connelly, Tihanyi, Certo, & Hitt, 2010; Zhang & Gimeno, 2010). Firms strive for “public expressions of approval” of constituents (Pollock & Rindova, 2003: 634), but their interests are opposed to those of the rivals. Therefore, firms try to make an announced action appear less threatening to rivals so as to avoid retaliation (Rindova et al., 2004). Nevertheless, the language aimed at constituents can inadvertently alert rivals and evoke strong retaliation (Anton & Yao, 2002; Verrecchia, 1990). Examining this competitive side can inform us as to whether there is indeed a dark side to linguistic presentation of firm actions, in the form of speedy retaliation from rivals. Comparing the implications of language for the competitive context to findings of linguistic research directed at constituents can inform us as to whether a trade-off exists for focal firms, in the form of pleasing constituents at the risk of inviting retaliation from rivals and vice versa. The concept of temporal framing, rooted in inter-temporal choice theory, is useful in examining the role of linguistic presentation in the competitive context (Loewenstein, 1988; Lowenstein & Prelec, 1992). It captures the linguistic cues (e.g. 2005, the next five years, soon) used to communicate the timelines of an action. It is especially relevant to competitive engagement, because the timelines of focal firms’ actions and their outcomes form the basis of rivals’ evaluation of the temporal window of opportunity in which to respond and their sense of urgency in retaliating (Chen, Lin, & Michel, 2010; Chen & Miller, 2015; D'Aveni, Dagnino, & Smith, 2010; Katila & Chen, 2008). Because rivals lack access to the focal firms’ actual timelines (Chen & Miller, 2012), they are likely to rely on the temporal cues in a focal firm’s action announcements to evaluate the available window of opportunity and the urgency of responding. Accordingly, we pose the following question: Does the variation in focal firms’ temporal framing of their competitive action announcements influence rivals’ responses? We address this question by using data from 2,130 competitive action announcements of 28 duopoly firms from 14 industries. This study contributes to the existing research in two ways. First, it introduces framing as a new perspective from which to conceptualize the linguistic underpinnings of competitive interactions and to highlight the dark side of favorable language directed at constituents—speedy retaliation from rivals. When juxtaposed with findings of research focused on constituents and the public relations motive, the dark side highlighted in this study points to the trade-off firms face in linguistically framing their actions. Second, this study introduces temporal framing as an important cueing mechanism in the linguistic basis of competitive interactions. THEORY DEVELOPMENT Action-based view of competitive dynamics Following the “action-based view,” studies have focused mainly on the observable characteristics of firms’ competitive actions in theorizing inter-firm rivalry. Three interrelated factors have been theorized as the loci of a rival’s interpretation of and retaliation in response to the competitive threat associated with observable actions of focal firms. First, observable action cues such as visibility, novelty, and expected payoffs associated with specific types of action (e.g., alliances, pricing) prime rivals to respond to the action in predictable ways (Chen, Su, & Tsai, 2007; Chen, Venkataraman, Sloan Black, & MacMillan, 2002; Derfus, Maggitti, Grimm, & Smith, 2008). Second, timing of announcements (when firms announce the action) primes rivals’ responses. Early announcements convey firms’ proactivity in competing and allow firms to assemble necessary financial resources for execution, but they also provide rivals more time for retaliation (Bayus, Jain, & Rao, 2001; Chen & Hambrick, 1995); the reverse is true for delayed announcements (Heil & Langvardt, 1994). Firms weigh these pros and cons in deciding the timing of the announcement (Heil & Robertson, 1991). Finally, the intensity of rivalry also determines rivals’ motivation to respond. In concentrated industries with few dominant and equally matched rivals, each action of an incumbent garners more attention, and rivals respond speedily so as not to signal competitive weakness, regardless of the action type or announcement timing (Derfus et al., 2008; Ferrier et al., 1999). In contrast, in industries with many competitors, the actions of each incumbent are less salient to rivals, who therefore do not retaliate as quickly or fiercely (Carroll & Hannan, 1989; Derfus et al., 2008). Scholars increasingly recognize that in addition to these factors, the language used by firms to describe their actions provides important external cues that prime rivals’ evaluations and responses (Prabhu & Stewart, 2001; Rindova et al., 2004). Competition is viewed as “enacted not only through intensified competitive interactions but also through communication acts” that involve extensive linguistic construction (Rindova et al., 2004: 671). Building on this contention, we use framing as a theoretical lens for examining the role of language in inter-firm rivalry. Framing as an intentional strategy Framing is an intentional strategy by which firms deliberately assemble words, phrases, and sentences to selectively present a situation in a way that steers audience members toward a particular line of causal reasoning about its future outcomes and consequences, and ways to deal with it (Benford & Snow, 2000; Entman, 1993; Scheufele, 1999). As Crilly et al. (2016: 708) note, “firms…use language strategically to persuade others and to present themselves in the best light.” Rhee and Fiss (2014: 1734) concur that firms use framing to strategically craft “accounts that selectively convey preferred meanings and suggest certain interpretations, while hiding others” to “affect the interpretation of certain events and influence the response of their stakeholders.” Gao, Yu and Cannella (2016: 22) argued that public documents such as press releases contain “words and text issued by an organization with specific strategic intent,” and Ahern and Soysura (2014: 242) found that firms manipulate the language in their acquisition press releases to influence their stock price “precisely when they would benefit the most from a temporary price increase.” Tan, Wang and Zhou (2015) also concluded that firms intentionally craft their earnings press releases to “opportunistically obfuscate unfavorable benchmarks while embracing clarity for favorable ones that are less important” (American Accounting Association). Thus, framing entails intentional crafting of language to influence stakeholders’ reactions. Framing is distinct from the related concepts of sense-giving and signaling, which subsume varied forms of communication, of which language is just one of many (Fiss & Zajac, 2006). Communication activities such as speeches and meetings are integral parts of sense-giving (Gioia & Chittipeddi, 1991). Similarly, actions such as price-cutting, hiring of a new CEO and new product introduction are key competitive signals (Connelly et al., 2011; Prabhu & Stewart, 2001). Framing is a specific form of sense-giving and signaling that focuses on language as the main form of disclosure, and that clearly distinguishes between linguistic cues and behaviors. As Fiss and Zajac (2006) note: “The concept of framing thus provides an attractive approach for understanding the process of sensegiving” (p. 1174). Therefore, we deem framing to be an appropriate theoretical lens for explaining the role of language in competitive dynamics. Although framing constitutes an intentional strategy to manage stakeholder reactions, the diverse and opposing interests of the different stakeholders create potential trade-offs for firms in framing their announcements. Therefore, a focal firm’s choice of “framing will…likely depend on the power and interests of different stakeholder groups” (Fiss & Zajac, 2006: 1177). Strong dependencies on shareholders in terms of power (e.g., institutional ownership), financial resources (e.g., poor slack resources) and executive compensation (e.g., CEO stock options) motivate firms to prioritize shareholder approval over deterring rival retaliation. They therefore frame their actions in the way most likely to please shareholders, even at the cost of rival retaliation (Connelly et al., 2010; Zhang & Gimeno, 2010). Conversely, firms that compete intensely with matched rivals (e.g., duopoly) will likely prioritize deterring rival retaliation (Chen, Lin, & Michel, 2010; Derfus et al., 2008), even at the risk of shareholder disapproval. Gao et al. (2016: 21) argue that focal firms’ public announcements reflect “language used as a strategic tool to engage competitors.” Therefore, firms carefully weigh the pros and cons in choosing a framing strategy to communicate their action announcements. We theorize that this variation in the framing will influence rivals’ reactions. We examine the competitive implications of a specific form of framing that is central to audience interpretation and responses––temporal framing. The role of temporal framing Rooted in inter-temporal choice theory, research on temporal framing rests on the premise that timelines form the basis of how decision situations are construed, which response alternatives are generated, and ultimately which choices are made (Loewenstein & Elster, 1992; Read & Loewenstein, 2000). The framing of timelines of the actions affects how audiences construe, interpret, and respond to the action (Berns, Laibson, & Loewenstein, 2007). Temporal framing entails the use of numerical dates (e.g., in 2005, on September 1, 2010), time frames (e.g., 10-year contract, the next two years), and temporal descriptors (e.g., soon, immediately, long-term) to present action timelines (Grant & Tybout, 2008; Sanna, Chang, Parks, & Carter, 2005). Temporal framing is distinct from the timing of announcements (Chen & Hambrick, 1995). Whereas timing (early or late) reflects the focal firms' decision on when to announce the action, temporal framing captures focal firms' selective presention of the timelines of the action in the announcement. The following strategic alliance announcements of SKF are similarly timed (as to the day of signing of the agreement) but present different timelines of the alliance. The first announcement conveys the more proximal, start date of the contract (July of the same year), whereas the second cites the more distal, end date of the contract (5 years later). “SKF has signed a contract with Metso Lindemann to operate their global wear…The contract will be effective as of July this year.” (May 5, 2010). “SKF today signed a framework agreement with the State Forestry Administration in China to plant new forests…The project is expected to run for five years.” (May 21, 2010) The framing of timelines shapes audience members’ evaluation of the perceived importance of the action and thus their sense of urgency in acting (Berns et al., 2007; Loewenstein, 1988; Sanna et al., 2005; McElroy & Mascari, 2007). McElroy and Mascari (2007) found that when the expected occurrence of the Asian disease outbreak was framed as temporally proximal, subjects treated it as more important and took more efforts to process the information than when it was framed distally. Similarly, Sanna et al. (2005) found that proximal framing of task deadlines increased group members’ sense of urgency in acting more than distal framing did. In their review of temporal framing research, Berns and colleagues (2007: 428) concluded that choices “expressed in terms of speed-up” are seen as more important and are acted upon more quickly. Temporal framing is pertinent to competitive dynamics because the dynamic of competition is “a fundamentally temporal process” (Chiles, Bluedorn, & Gupta, 2007: 488). Central to rivals’ formulation of competitive responses is their evaluation of the timelines associated with a focal firm’s action and the temporal window available for retaliation (Chen, 2009; D'Aveni et al., 2010; Thomas & D'Aveni, 2009). The timeline of a focal firm’s action serves as a “continuous moving target” for rival firms to catch up within a specific period (Katila & Chen, 2008: 596); errors in accurately predicting the temporal windows of a focal firm’s action can result in delays and foreclose a rival’s opportunity to retaliate (Chen et al., 2002; Ferrier, 2001). However, externally observable cues such as the type of action (e.g., pricing, mergers & acquisitions) provide only a partial understanding of action timelines (Chen & Miller, 2012; Ferrier, Smith, & Grimm, 1999). Rather, internal factors such as organizational structures and processes, routines, inter-unit coordination and conflicts, and middle managerial interactions can facilitate or delay actual initiation and execution (Chen & Miller, 2012; Elbanna & Child, 2007; Nag & Gioia, 2012; Teece, 2007). These factors are difficult to observe from the outside and focal firms intentionally hide them from rivals, who therefore find it difficult to accurately predict the timelines over which focal firms’ actions will unfold. Given this information gap, rivals will rely on ready-made sources such as press releases about focal firms’ actions to gauge the timeline. As highlighted in framing research, focal firms will take advantage of this information gap in temporally framing their press releases; after carefully weighing the trade-offs, they will selectively reveal certain action timelines while obfuscating others to prime rivals’ ability to react.[footnoteRef:1] [1: We used qualitative interviews with 10 experts to corroborate that the notion of intentionality stressed in the broader framing research holds for temporal framing. The results of these interviews, discussed in the methods section, provide face validity and field evidence of the assumption of intentionality in the temporal framing of action announcements. ] We examine three dimensions of temporal framing—temporal vagueness (lack of clarity and completenenss), temporal distance (length of action timeline), and temporal frequency (repetition of temporal cues) (Berns et al., 2007; Loewenstein, 1988). These dimensions are strongly grounded in inter-temporal choice theory and have been widely theorized and tested (Berns et al., 2007; Loewenstein, 1988; Sanna et al., 2005; McElroy & Mascari, 2007); they are also conceptually distinct and capture unique underlying mechanisms. Finally, they are substantively relevant to theorizing how temporal framing shapes rivals’ responses, because uncertainty (vagueness), imminence (distance) and salience (frequency) of competitive cues have been proposed as determinants of how rivals evaluate and respond to the timeline of a focal firm’s action (Chen et al., 2010; D'Aveni et al., 2010; Katila & Chen, 2008). We examine the effects of focal firms’ temporal framing of their action announcements on rivals’ response speed, which determines the competitive advantage enjoyed by a focal firm as the result of its action--speedy retaliation can erode the competitive advantage (Ferrier et al., 1999; Yu & Cannella, 2007). HYPOTHESES Temporal vagueness Temporal vagueness captures the degree to which an action timeline lacks clarity and completeness (Dhar, Gonzalez-Vallejo, & Soman, 1995; Di Mauro & Maffioletti, 1996). Qualitative temporal descriptors (e.g., soon, long term, immediately) are more vague than numerical dates (e.g., 2010, 1995) and time frames (e.g., five years, one month). The inter-temporal choice theory contends that the central mechanism of the effect of temporal vagueness is the temporal discounting bias––downgrading of the importance attached to an action and in turn reduction of the motivation to respond (Berns et al., 2007; Loewenstein, 1988). This bias results from perceived uncertainty--the degree to which information about action timelines is seen as unclear and incomplete. Perceived uncertainty triggered by vagueness reduces audiences’ confidence in deciding on the basis of the available information (Barley et al., 2012), and inflicts on audience members the “subjective experience of missing information relevant to a prediction,” which diminishes their confidence in making a decision (Kuhn, 1997: 57; Levin et al., 1986). As a result, audience members downgrade the importance of these actions and adopt a wait-and-see approach while awaiting more information (Berns et al., 2007; Bier & Connell, 1994). Conversely, actions conveying clear and concrete timelines are perceived as more certain and boost confidence in evaluating the action and formulating a response (Tan & Chua, 2004). As a result, audience members attach greater importance to these actions and prioritize them for quicker responses (Kuhn, 1997). Thus although the communication of clear and concrete timelines in press releases helps the focal firm to garner support from key constituents, it simultaneously prompts rivals to assign greater importance (low temporal discounting) to the framed actions, and therefore to feel confident in formulating a response and prioritizing retaliation. Conversely, temporally vague framing in a focal firm’s press releases will leave the timeline associated with the action unclear and incomplete, thus increasing constituents’ and rivals’ perceived uncertainty about the realization of payoffs. Such vague framing will trigger discounting of the action by key constituents such as shareholders, who may hesitate to direct resources toward the focal firm; at the same time, it will delay the response of rivals, because accurately interpreting the temporal window available for response and adjusting the timing of the response accordingly are central to successful retaliation (Chen et al., 2010; Chen & Miller, 2015; D'Aveni et al., 2010; Katila & Chen, 2008). Undertaking actions hastily simply to keep up with the focal firm’s actions can prevent rivals from considering broader range of action alternatives and developing a well-designed execution plan (Katila & Chen, 2008). Therefore, when the timing of a competitive threat is difficult to ascertain, rivals typically take a wait-and-see approach until more concrete information about the timing of the action becomes available (Chen et al., 2002; Heil & Robertson, 1991). H1: Temporal vagueness in a focal firm’s framing of its competitive action announcements will be negatively related to the speed of the rivals’ response. Temporal distance Temporal distance represents the length of the action timeline. Proximal framing conveys that the action will occur in the short term (e.g., one day or one week), whereas distal framing conveys a longer timeline (e.g., five years, a decade). Temporal distance is distinct from temporal vagueness; although the terms soon (proximal) and much later (distal) are both high on vagueness, they vary considerably in temporal distance. Similarly, end of the month (proximal) and 10 years from now (distal) are both low on vagueness but convey different temporal distances. Inter-temporal choice theory contends that temporal distance, like temporal vagueness, triggers the temporal discounting, but through a different mechanism: perceptions of urgency (Gan et al., 2015; Loewenstein, 1988; Sanna et al., 2005; Shu & Gneezy, 2010). Proximal framing conveys that the action is imminent and fast approaching (Kardes, Cronley, & Kim, 2006; Trope & Liberman, 2010), prompting audience members to assign greater importance to the action and to experience a sense of urgency in formulating a response (Gan et al., 2015; Loewenstein, 1988; Shu & Gneezy, 2010). Conversely, distally framed actions promote complacency and calculation of the time remaining as longer than it actually is, causing actions to be downgraded in importance and viewed as less urgent (Gan et al., 2015; Shu & Gneezy, 2010), so that response is delayed. Proximal task deadlines increase the sense of urgency and prioritized pacing of efforts more than distal task deadlines do (Gersick, 1988, 1989, 1994; Labianca, Moon, & Watt, 2005; Staudenmayer, Tyre, & Perlow, 2002). Building on this research, we theorize that proximally framed action timelines in the focal firm’s competitive announcements will convey a strong sense of imminence of the action, which, although garnering positive reactions and support from constituents, will elevate rivals’ sense of imminent competitive threat. Competitive dynamics research has argued that cues of imminent competitive threats amplify rivals’ fear that failure to catch up quickly with the focal firm’s actions can erode their own competitive advantage and therefore intensifies their sense of urgency to respond ( Chen et al., 2002; Katila & Chen, 2008). In contrast, distally framed action timelines in the focal firm’s announcements will evoke low perceived imminence and perception of a longer temporal window for retaliation, leading rivals to downgrade the imminence of the threat and to feel little urgency to respond. Competitive dynamics research contends that when a competitive threat is not imminent, rivals become complacent and adopt a wait-and-see approach (Chen et al., 2002). H2: Temporal distance in a focal firm’s framing of its competitive action announcements will be negatively related to the speed of the rivals’ response. Interaction of temporal framing variables Temporal vagueness and temporal distance. Framing research suggests that audience members simultaneously process multiple framing cues to develop an overall evaluation of an action (Giorgi & Weber, 2015). By linking different framing cues, audience members connect the dots so as to construct a holistic meaning of the action or event (Loewenstein, Ocasio & Jones, 2012). As a result, different aspects of framing work in conjunction to jointly shape audience members’ reactions and responses (Kennedy, 2008). Therefore, we expect that rivals will simultaneously process temporal vagueness and distance cues in developing an overall evaluation of the importance and urgency to respond, with these two dimensions will jointly affect rivals’ temporal discounting of the framed action. The sources of temporal discounting bias associated with vagueness (uncertainty) and distance (urgency) are distinct but complementary mechanisms that reinforce each other (Green & Myerson, 2004). The temporal discounting of uncertainty cues is amplified as the temporal distance increases (Liberman & Trope, 1998; Trope & Liberman, 2003). Therefore, we expect that temporal distance will strengthen the negative effect of temporal vagueness on rivals’ response speed. Distal framing of the vague action timeline will amplify rivals’ temporal discounting of the action by triggering complacency, over and above the perceived uncertainty promoted by temporal vagueness in itself. This diminished urgency will tend to lengthen the delay in a rival’s response. Conversely, proximally framed timelines will neutralize the temporal discounting resulting from vagueness by triggering a sense of imminence and urgency to act. Vague timelines that seem more proximal will be acted on more quickly than those that seem distal, and clear timelines that seem distal will be acted on less quickly than a proximally framed timeline. H3: The negative effect of temporal vagueness in the focal firm’s framing of its competitive announcements on the rivals’ response speed will be stronger when the temporal distance is distal than when it is proximal. Frequency of temporal vagueness and distance. Frequency––the degree to which cues are repeated through the use of specific words and their synonyms––is considered a fundamental characteristic of framing (Entman, 1993; Scheufele & Tewksbury, 2007). Repetition increases a framed text’s salience—the degree to which a stimulus stands out as more important and significant than other stimuli (Augoustinos & Walker, 1998; Entman et al., 2009; Wade et al., 1997). By increasing salience, high word frequency typically prompts audience members to interpret the information as highly significant; audience members are more likely to deduce the meanings of frequently used words than of infrequently used words (Bonardi & Keim, 2005; Pollock et al., 2008). Strategy scholars have also argued that salience increases the likelihood that external stakeholders will evaluate an announcement as important and therefore will become more involved with the focal firm’s activities (Rindova et al., 2004). Building on these contentions, we theorize that the repetition of temporal vagueness and temporal distance cues in focal firms’ competitive announcements will make each timeline dimension more salient in the announcement and strengthen its effect on rivals’ responses. If a focal firm’s announcement is vague and includes only non-numerical timeline descriptors (e.g., soon, long term), repetition of these vague cues will render the issue of uncertainty salient to rivals and amplify their tendency to temporally discount the action. In contrast, for announcements with clear numerical timelines (e.g., 2005, five years), repetition of these concrete cues will make the certainty of the action timeline more significant and important to rivals, further boosting their confidence in the need to evaluate and formulate a response quickly. H4: The negative effect of temporal vagueness in a focal firm’s framing of its competitive announcements on rivals’ response speed will be stronger when the frequency of vague cues is higher than when it is lower. Repetition of the longest timeline in the announcement will render the length of the timeline salient to rivals. If the longest timeline is distal (e.g. long term, 10 years), repeating it will reinforce rivals’ interpretation of a longer temporal window to respond, increasing their complacency and exaggerated evaluation of more remaining time than is actually remaining. Thus, a rival’s tendency to temporally discount the focal firm’s action and in turn delay response will increase with repetition of distal timelines. Similarly, repetition of proximal timelines (e.g. next month, soon) will intensify rivals’ perceptions of imminence and the importance they attach to acting urgently. Such a heightened assessment of the short temporal window associated with a focal firm’s actions increases rivals’ urgency to respond (Chen et al., 2007; Marcel et al., 2011). H5: The negative effect of temporal distance on the focal firm’s framing of its competitive announcements on the rivals’ response speed will be stronger when the frequency of the given temporal distance is higher than when it is lower. METHODS Sample and time frame We tested the hypotheses using duopoly industries, in which the two top firms controlled most of the market share. Competitive interdependencies between the two firms are more explicit and intense than firms in less concentrated industries (Derfus et al., 2008; Singh & Vives, 1984). Duopoly firms are head-to-head rivals; one firm’s action directly affects the gain or loss of the other, and the moves and countermoves of both are clear and easily observable (Waldman & Jensen, 2001). As a result, rivals’ responses to a focal firm’s competitive announcements are clearly ascertained from archival data (Derfus et al., 2008). Moreover, the duopoly context involves intense rivalry between matched market leaders who follow each other’s competitive signals closely and retaliate strongly (Derfus et al., 2008). Therefore, engagement with rivals is likely to be a key consideration in focal firms’ crafting of temporal cues in their action announcements. At the same time, a duopoly industry provides a conservative test of temporal framing hypotheses, because intense rivalries prompt incumbents to retaliate speedily just to match competitive fierceness, regardless of the cues (e.g., temporal framing) associated with the individual actions (Derfus et al., 2008; Ferrier et al., 1999). We defined duopoly industries as those in which the top two firms hold a market share of at least 80% for the entire duration of the time frame (Schwalbe & Zimmer, 2009). We excluded industries in which incumbents’ competitive behaviors are not easily observable (e.g., the financial & real estate industries) (Derfus et al., 2008). The time frame of the study, 1999 to 2011, was sufficiently long to robustly capture the variation in incumbent firms’ competitive actions (Ferrier et al., 1999). It also captured cyclical variations in economic conditions, such as the dot-com bubble covering 1999 and 2000, as well as the economic upturn (2007), downturn (2008), and recovery (2010-2011). Therefore, we could establish the robustness of our results under varying economic conditions. We conducted sensitivity analyses to address the truncation issue resulting from the start date of 1999. Results based on different start dates in identifying the first set of action-response dyads (e.g., 2000, 2003 and 2006) were consistent with the main results reported in the study. The final sample comprised 28 firms from 14 industries (four-digit SIC classification).[footnoteRef:2] [2: The 14 industries were: metal ores, fats and oils, office furniture, public buildings and related furniture, book printing, polishing and sanitation preparations, hydraulic cement, construction machinery and equipment, mining machinery and equipment, ball and roller bearings, household appliances, public warehousing and storage, wholesale and durable goods, and amusement and recreation services.] Data collection We identified competitive actions by triangulating data from the firms’ own press releases as well as from external media reports. Firms strategically issue press releases for some firm activities but not for others (Graham, Harvey, & Rajgopal, 2005; Hayes & Lundholm, 1996). Because press releases for individual actions constitute “less formal communication channels” not mandated by SEC, firms enjoy greater discretion in their decision to issue or not issue a press release (Lang & Lundholm, 1993). In Graham et al.’s survey (2005), 58.8 per cent of corporate executives admitted not disclosing certain competitive activities of the firm even if rivals could infer the information from other resources. Therefore, competitive dynamics studies have typically used external media sources (e.g., Aviation Daily and Automotive News) to identify the competitive actions of focal firms (Marcel et al., 2011; Yu & Cannella, 2007). Organizational communication research has documented media bias in frequently reporting certain types of action and firms while ignoring other actions and firms (Pfarrer, Pollock, & Rindova, 2010; Rindova, Pollock, & Hayward, 2006). Therefore, using both sources yields more comprehensive data and mitigates the selection biases associated with use of each. To obtain competitive action data, we first collected all the articles and press releases between 1999 and 2011 containing the name of one of the 28 sampled firms in the Factiva and Lexis-Nexus databases, which include over ten thousand magazines, newspapers, and industry-specific journals (Lee & James, 2007; Uotila, Maula, Keil, & Zahra, 2009). Next, two coders, following the established structured content analysis of article headlines, retained only the headlines reporting an observable competitive move initiated by a firm to enhance its market position (κ = 0.98) (Yu et. al., 2007), and removed duplicate announcements of the same action. This procedure yielded 3,762 unique competitive action announcements. Framing data for each competitive action was based on the original press release of each action explicitly authored by the focal firm. When a firm wants to publicize its action, it issues a press release, which is diffused to key external constituents, both directly and through the media (Kennedy, 2008). Press releases are characterized as “a disclosure mechanism revealing a package of information” to external constituents, including rivals (Davis, Piger, & Sedor, 2012: 845). The language used in a press release provides a coherent framework within which “qualitative and quantitative disclosures are made” about a firm’s actions (Davis et al., 2012: 845). A press release is a major information source for rivals in assessing firm prospects (Carroll & McCombs, 2003; Zavyalova et al., 2012). The original press releases of competitive actions are suitable for framing analysis because “these releases are especially designed for dissemination to the media and are stored in the original, unedited form” (Fiss & Hirsch, 2005: 34). We found original press releases issued by the sampled firms for 2,130 competitive actions in PR Newswire and Business Wire; 30 % of the media articles did not have corresponding original press releases, whereas 41% of the original press releases did not have corresponding media reports. Heckman’s (1979) two-stage model confirmed that the missing original press releases did not alter the main results.[footnoteRef:3] We also explored whether competitive action announcements originating from different sources affected the rival’s response speed. We found no significant difference (p = 0.31) in rivals’ response speed to competitive actions announced only via focal firms’ original news releases and those announced only via third-party media articles. Thus, rivals’ response speed seemed to not differ significantly when the action was announced by the focal firms or by external news sources. [3: In stage one, we created a dichotomous “choice variable” to indicate whether a competitive action had a corresponding original press release and would be included in the sample and stage-two analysis (yes = 1), or whether the competitive action would be excluded from stage two because of missing original press releases (no = 0). We ran a probit model with this “choice variable” as the dependent variable and the focal firm variables--debt to equity ratio, CEO stock options, institutional ownership—as the independent variables. We then computed the inverse Mills ratio and included it as a control in stage-two regression models. The inverse Mills ratio was not significant and did not alter the main results.] Measures Rivals’ response speed. Rivals’ response speed is computed on the basis of the earliest action taken by a rival in response to a focal firm’s announcement (Yu & Cannella, 2007). We adopted Yu and Cannella’s (2007) process-based approach to derive the speed of response. We first temporally ordered the competitive action announcements of the two duopoly firms in each industry, starting with the first announcement in the time frame of the study. We used an earlier competitive action initiated by firm A as a starting point to identify the subsequent response of firm B. The actions of the rival between a focal firm’s two successive action announcements were deemed as the rival’s responses to the firm’s first competitive action announcement. Thus, “[e]ach action is therefore a response (ending one set of response opportunities) and an initiating action (starting a set of response opportunities)” (Yu & Cannella, 2007: 667). The absence of a rival’s actions between a focal firm’s two successive announcements was deemed a non-response (Ferrier, 2001; Yu & Cannella, 2007). Such temporal precedence “emphasizes accuracy in identifying the timing and target of action” and allows more complete generation of action-response dyads, including non-responses from rivals (Yu & Cannella, 2007: 667). Because temporal precedence in itself does not ensure “that a given action is a clear-cut and direct ‘response’ to the earlier action by a rival,” we adapted key-words from prior studies to establish the rival’s action as a response (Yu & Cannella, 2007; 667). Two coders used keywords (e.g., “combat,” “to compete”) in the media articles and press releases of rivals’ actions to confirm that the rivals’ actions were responses against the focal firms (Cohen’s Kappa, κ = .81) (Yu & Cannella, 2007). Because the duopoly firms are intensely competitive and acutely attuned to each other’s actions, we deem that the use of competitive key-words is a clear indication that the rival’s action is a response against the focal firm and therefore provides face validity in deriving action-response linkages. Next, we used the action-response links identified to estimate the hazard of the rival’s response to a focal firm’s announcement, using event history analysis (Allison, 2005), to be described in the analysis and results section. Temporal framing. We measured temporal framing variables in two phases. First, research has demonstrated the intentionality behind certain forms of framing (e.g., valence and promotion-based) but has not corroborated this assumption of intentionality for temporal framing. Therefore, we followed the recommended inductive approach to corroborate this premise of intentionality for temporal framing of firms’ action announcements (e.g. Stern & Westphal, 2010). We interviewed a panel of top executives from our sampled companies directly involved in strategy development (n = 3) and corporate communications (n = 2), journalists from a business newspaper (n = 3) and industry analysts familiar with our sampled industries (n = 2). We posed open-ended questions such as “Do companies intentionally adjust the timelines of the actions presented in their press releases?” and “What are the considerations in presenting a particular timeline?” Each interview lasted about 30 minutes. The experts corroborated our premise of intentionality behind focal firms’ framing of their action timelines in the press releases and explained how firms intentionally craft their timelines to prime rivals’ and constituents’ perceptions of the action. A journalist stated, “Companies purposely make certain things vague because they don’t want to tip anyone off, particularly competitors…so if a company thinks that this company will acquire another company X in the next two years, they will not say next two years they will say next several years…So that is very normal…it’s definitely intentional to suit their purposes.” A top executive and an industry analyst concurred: “It is quite common for companies to exaggerate the timeline of actions, for example, to make them to look closer than they actually are…particularly when they are thinking of raising more money to make this action happen. In many cases, companies do this to get shareholders excited about this and hike-up their stock price.” “Sometimes companies have to announce actions that they would rather hide…so they will make it very vague, give very little details of the timeline…even make it appear far away.” After corroborating the premise of intentionality, we proceeded to measure the temporal framing variables based on content analysis of the focal firms’ press releases. First, we adapted the protocols from prior temporal framing studies (Liberman et al., 2007; Rim, Hansen, & Trope, 2013; Stephan, Liberman, & Trope, 2010) to construct a dictionary of dates (e.g., 2001, 2005), numeric time frames (e.g., five years, two months), and non-numeric temporal descriptors (e.g., soon, quickly, long term, short term, in the coming days) (see Appendix 1A). We then used automated content analysis to extract the temporal cues from the press releases of focal firms, based on the dictionary just described. Existing content analysis programs such as LIWC and Diction do not allow simultaneous coding and categorization of numerical and non-numerical keywords or complex coding of numeric values (e.g., longest timeline) in the text. Therefore, we had to develop a customized content analysis program to automatically extract and categorize (e.g., qualitative and numeric) temporal cues[footnoteRef:4] from the focal firms’ press releases and to compute the temporal framing variables. We manually checked the coding for 10 percent of the press releases (n = 213) to confirm the reliability of the program in extracting qualitative and numeric temporal cues (α = 0.87) and in coding the cues to derive temporal vagueness (α = 0.91), temporal distance (α = 0.79), and temporal frequency (α = 0.87) measures, using Krippendorff’s alpha. We also conducted manual checks to ensure that the temporal cues conveyed timelines about the announced action. [4: All press releases had at least one (numerical or non-numerical) temporal cue from the dictionary.] Temporal vagueness reflects the extent to which the text in the press release lacks clarity and completeness of information about the timeline of the focal action (Dhar et al., 1995; Kuhn, 1997). We created an ordered categorical measure of temporal vagueness for each press release: 3 (most vague) = only qualitative cues and no numeric cues; 2 (moderately vague) = mix of numeric and qualitative cues; 1 (least vague) = only numeric cues and no qualitative cues. Frequency of temporal vagueness was measured by the total number of qualitative cues. Following temporal framing research, we measured temporal distance as the number of days between the date of the press release and the latest date (e.g., August 22, 2013) or time frame (e.g., in the next three years, in the coming years) cited in the press release ( Liberman et al., 2007; Rim et al., 2013). For press releases with no numeric cues, we used the procedures in temporal framing studies (Liberman et al., 2007; Rim et al., 2013; Stephan et al., 2010) to derive temporal distances from non-numeric temporal descriptors (e.g., soon, long term). Three coders blind to the hypotheses categorized the non-numeric descriptors in the press releases into proximal (e.g., now, immediately and short term), distal (e.g., long term and much later) and medium-term (e.g., sometime from now) distances (ICC = 0.71). We then followed Liberman et al. (2007) to assign proximal descriptors the minimum temporal distance, distal descriptors the maximum distance, and medium-term descriptors the median temporal distance found in all the press releases of that focal firm in our data. Appendix 1B shows examples of temporal distances derived from non-numeric descriptors of timelines. Frequency of temporal distance was measured by the number of times the longest time frame was repeated in a press release. Controls We controlled for action, focal and rival firm, industry, and time variables that could serve as alternative explanations of rivals’ response speed. Action controls. First, we controlled for the type of action being announced. Actions that require fewer resources and skills and are easy to execute (e.g., pricing) are seen as more feasible and attract more rapid responses from rivals than actions that require more resources and are difficult to execute (e.g., Mergers and Acquisitions) (Chen et al, 1992; Yu & Cannella, 2007). To avoid common source bias, we used a separate source to identify action type—media articles reporting the same action[footnoteRef:5]. Two coders blind to the hypotheses read the headline and lead paragraph of all media reports and coded the announced actions into one of the nine types identified in prior studies: pricing, product, marketing & promotional, technology innovations, distribution & after-sales service, new capacity, organizational structure & management system changes, mergers & acquisitions, and alliances & collaboration (κ = 0.94) (Ferrier, 2001; Yu & Cannella, 2007). We further validated the categorization for a subset of headlines (15%), using an expert panel of managers and industry analysts with specialized knowledge of specific industries and firms within the industry (ICC = 0.97). Such expert informants have been shown to provide accurate and reliable ratings of firm strategies (Chen, Farh, & MacMillan, 1993; Kadan, Madureira, Wang, & Zach, 2012). We included action-type dummies in the analyses. [5: For actions announced in the press releases but not reported in the media (18%), we used the original press releases to code the action types. Results after dropping these actions were consistent with the main results. Heckman’s two stage analysis also did not alter the main results. ] Second, action announcement timing can encourage rival retaliation by expanding the window for retaliation (early) or deter a rival’s response by shortening the available window for retaliation (Bayus et al., 2001; Chen & Hambrick, 1995). We computed the timing of announcement by the number of days between the focal firm’s first announcement of the action and the final announcements of the action execution. Third, a focal firm’s string of actions within a short timespan can make it difficult for rivals to respond separately to individual actions (Ferrier, 2001). To address this issue, we controlled for the volume (total number of actions in the sequence) and duration (total number of days during which the sequence existed) of a focal firm’s “uninterrupted sequence of actions” prior to the focal firm’s press release (Ferrier, 2001). Moreover, we confirmed that the results based on average vagueness, distance, and frequency measures for the press releases of all the focal firm’s actions in the uninterrupted sequence were consistent with the main results. Finally, to determine whether rivals were responding to the framing or to the actual action, we used a dummy control for whether (1) or not (0) actions reported in the focal firms’ original press releases were executed prior to rivals’ responses. We also tested the interaction effect of this variable and reran the analyses separately for each subgroup. The interaction term was not significant, and the results for each subgroup were consistent with the main results. Focal firm and rival firm controls. We added several focal and rival firm controls. Focal and rival firms’ past performance (one-year change in the return on assets) and the rival’s relative market share (the ratio of the rival firm’s market share to the focal firm’s market share) determine the rival’s motivation to respond speedily (Derfus et al., 2008; Ferrier et al., 1999). The rival’s firm size (log of yearly employee size) and slack resources determine its capacity to implement a timely response, whereas the focal firm’s size and slack resources influence its motivation to respond (Chen et al., 2007; Connelly et al., 2010). We measured slack by averaging current ratio (available slack), debt-equity ratio (potential slack), and the general and administrative expenses to sales ratio (recoverable slack) (Cheng & Kesner, 1997). Industry controls. We controlled for five industry variables that define the intensity of inter-firm rivalry, competitive buffers and uncertainty confronting incumbents, and in turn shape the incumbents’ motivation to respond: capital intensity (total capital investment/sales), R & D intensity (R & D expenses/sales), advertising intensity (advertising expenses/sales), industry munificence (percent change in industry gross sales between the current and the previous year) and dynamism (Connelly et al., 2010; Derfus et al., 2008). To compute a standardized industry dynamism index, we regressed industry values of shipment over 5 years against time and used the standard error of the regression coefficient divided by the average value of the industry’s shipments (Bergh & Lawless, 1998). Other controls. We created a dummy for each year from 1999 to 2011 to control for the effects of time. We used the year 2011 as the comparison group and excluded it from the model. We also controlled for the length of the press release (total number of words in the press release). ANALYSES AND RESULTS Model specification We modeled the hypotheses using event history analysis, which effectively addresses, and provides unbiased estimation in the face of right censoring bias. This bias was prominent in our data because of our use of a finite time window (between focal firms’ two successive action announcements) to specify the rival’s response. Event history analysis models do not model the response time, but rather the hazard—the instantaneous risk that a response will be observed at time t, given that no response occurred prior to time t. An increase in the rival’s response speed was represented by an increase in the hazard function (Allison, 2005). By modeling a hazard function, we could explicitly compute response speed (Box-Steffensmeier & Jones, 2004; Yu & Cannella, 2007). We chose the stratified Cox proportional hazard model because it allows for the possibility that events can occur at any point within the observation window and requires no assumptions about the exact nature of the hazard’s probability distribution (Allison, 1995; Puranam, Singh, & Zollo, 2006). We generated two variables: response, a dichotomous variable that indicated whether a response occurred; and time delay, a continuous variable that indicated the time span. We specified the spells of the occurrence of the event by day and evaluated the hazard on a daily basis since the focal firm’s announcement. We closed the observation either if the rival firm responded or if the focal firm announced another action. If a rival’s response was observed, we recorded the response as 1 and time delay as the number of days between the date of the focal firm’s announcement and the date of the rival’s first response (Ferrier, 2001; Yu & Cannella, 2007). We used right censoring if no response was observed during the observation window and recorded the response as 0 and time delay as the number of days between two consecutive announcements. The model was specified as follows: where = time delay and = likelihood of the response, during the time interval to . Although used extensively in prior research, the time interval between focal firms’ successive actions is just one way of defining the observation window in estimating the hazard of rival’s responses and identifying censoring cases. Therefore, we tested the sensitivity of our results to an alternative construction of the observation window—fixed number of days since the focal firm’s announcement (Allison, 1995). We reran the analyses, using several fixed interval observation windows (30, 60, 90, 120, and 180 days). Rivals’ actions outside the fixed windows were treated as non-responses. Results using varied fixed observation windows following the date of the focal firm’s initial press release were consistent with the main results, and confirm the robustness of the results to varied observation windows. To test the hypotheses, we first entered only the controls. We then added all the study variables, and finally all the interaction terms. To test for the moderation effects, we adopted two approaches. We first adopted the widely used multiplicative approach (Aiken, West, & Reno, 1991; Hoetker, 2007). However, this approach may lead to inappropriate conclusions for non-linear models, because the coefficients of interaction terms provided by the model do not reflect the magnitude of the effect (Ai & Norton, 2003; Hoetker, 2007). Therefore, we used the recommended split-sample tests to explore the moderation effects, followed by Wald chi-square tests to compare the marginal effects (Hoetker, 2007; Penner-Hahn & Shaver, 2005). Interaction plots are critical in interpreting interaction effects in nonlinear models (Hoetker, 2007). We followed Long and Freese’s (2001) procedure, using one standard deviation above and below the mean to represent high and low levels of each of the three moderators. We obtained the value for each interaction separately, holding the other variables at their means. We standardized independent variables in all the regression models (Aiken, West, & Reno, 1991). The variance inflation factors (VIF) values for all variables were below the recommended level of two (Neter, Wasserman, & Kutner, 1985). Results Table 1 reports the descriptive statistics and correlations for the variables in this study. The low correlation between temporal vagueness and distance (r = -0.07) confirm that they constitute distinct dimensions of temporal framing. Interestingly, the length of the press release related much more strongly to the frequency of temporal vagueness (r = 0.57) than to the frequency of temporal distance (r = 0.23). Framing research suggests that framers intentionally use lengthy wording to create ambiguity and confusion about the issue being presented (Li, 2008; Loughran & McDonald, 2014). Therefore, “wordiness” reflects another form of vague framing and is for this reason more closely tied to temporal vagueness than to temporal distance, as shown by the correlations. This distinct pattern of correlations provides further evidence of the distinctness of temporal vagueness and distance. Finally, the weak correlation between action announcement timing and temporal distance (r = 0.04) points to their distinctness. ----------------------------------------- Insert Tables 1, 2, & 3 about here ----------------------------------------- The Cox regression results for the main effects of temporal vagueness and temporal distance on rivals’ response speed are shown in Table 2. Both temporal vagueness (b = -0.13, p < .05) and temporal distance (b = -0.32, p < .001) relate negatively to rivals’ response speed. In addition to being statistically significant, these findings are important in terms of the magnitude of the effect (100[exp(β) − 1])—the percentage change in the hazard associated with a one unit increase in covariate. If temporal vagueness in the focal firm’s press release increases by one unit, the rival’s hazard of response decreases by 12 percent. Similarly, if the temporal distance in the focal firm’s press release increases by one unit, the rival’s hazard of response decreases by 27 percent. These results support H1 and H2. The interaction effects of the temporal framing variables are shown in Table 2. The interaction term temporal vagueness × temporal distance is significant (b = -0.50, p < .001). Table 3 also shows subgroup comparisons of distal and proximal framing based on median-split. The effect of temporal vagueness on rivals’ response speed is strong and negative for the distal subgroup (b = -0.36, p < .001), but this effect is not significant for the proximal subgroup (b = 0.07, ns). The Wald chi-statistic confirmed the significance of these differences across the distal and proximal subgroups (Chi-square statistic = 11.8, p < .001). Similarly, Figure 1A shows that the slope of the effect of temporal vagueness on rivals’ response speed is steep and negative for distal framing but is flat for proximal framing. Taken together, these results support H3. -------------------------------------------------- Insert Figures 1A, 1B, & 1C about here -------------------------------------------------- Temporal vagueness × temporal vagueness frequency is negative and significant (b = - 0.74, p < .001). Furthermore, the effect of temporal vagueness on rivals’ response speed is negative and significant for the high-frequency subgroup of press releases (b= -0.81, p < .001) but is not significant for the low-frequency subgroup (b= -0.02, ns) (Chi-square statistic = 16.0, p < .001). In figure 1B, the slope of the effect predicting rivals’ response speed is steep and negative for distal framing but flat for proximal framing. These results lend support to H4. Finally, the moderation effect of temporal distance frequency on the effect of temporal distance framing on rivals’ response speed is significant (b = - 0.28, p < .05). Temporal distance exerts a strong negative effect on rivals’ response speed when the frequency is high (b= - 0.45, p < .001). However, this effect is not significant when the frequency is low (b = 0.06, ns). This significant difference between the high- and low-frequency subgroups (Chi-square statistic = 7.0, p < .01) is visually depicted in Figure 1C. Overall, H5 is supported. The interactions effects are also practically significant in terms of the magnitude. A one-unit increase of the temporal distance × temporal vagueness interaction is associated with the decrease of the rival’s hazard of response by 39%, whereas a one-unit increase in the temporal vagueness × vagueness frequency interaction is associated with a 52% decrease in the rival’s hazard of response. Finally, a one-unit increase in the temporal distance × distance frequency interaction is associated with a 24% decrease in the rival’s hazard of response. Robustness checks We conducted extensive checks to confirm the robustness of our results. A host of un-modelled factors could affect both the focal firms’ temporal framing in press releases and the rivals’ response speed. These confounds are likely because a focal firm’s “framing will…likely depend on the power and interests of different stakeholder groups” (Fiss & Zajac, 2006: 1177). We used the recommended two-stage procedure to address the potential endogeneity resulting from the tradeoffs firms face in framing their press releases (Wooldridge, 2014). In stage one, we created two regression models, with one regressing temporal distance and the other regressing temporal vagueness, with four holdout focal firm variables that determine a firm’s dependency on the key supportive stakeholder group consisting of shareholders and investors: (1) number of CEO stock options, (2) percentage of institutional ownership, (3) debt to equity ratio and (4) stock price declines. The first three variables determine how important investors and shareholders are to the focal firm and how strongly the focal firms’ interests are aligned with those of these groups, in turn motivating focal firms to prioritize shareholders and investor favorability in framing their action announcements (Connelly et al., 2010; Devers, Wiseman, & Holmes, 2007). Stock price declines can pressure companies to prioritize shareholder interests even at the cost of losing competitive edge to rivals (Zhang & Gimeno, 2010). As expected, all four instrumental variables were strongly related to temporal vagueness (p < .001) and temporal distance (p < .001) in the first stage. In the second stage, in which we used the fitted values and the residuals for temporal distance and temporal vagueness, the results (shown in Appendix 2) were consistent with the main results.[footnoteRef:6] [6: We thank the anonymous reviewer for suggesting this method for correcting for endogeneity in our models. ] We controlled for action characteristics by use of an alternative approach. Instead of using action-type dummies, as in the main analysis, two coders coded the headline and the lead paragraph of each media report of action on five attributes: time horizon, uncertainty, irreversibility, resource commitment requirement, and implementation difficulty (Chen et al., 1992; Chen & Miller, 2015; Connelly et al., 2010). They carefully read the headline and lead paragraph for each action and coded its action characteristic on a five-point scale: (1 = very low, 5 = very high) (ICC= 0.96). Adding the action controls did not alter the main results. We reran the models by use of an alternative measure of vagueness that captured the completeness of numeric cues: 3 (most vague) = no numeric cues; 2 (moderate vagueness) = numeric cues specifying years, but not specifying months, weeks or days; and 1 (least vague) = numeric cues specifying months, weeks or days. Results based on this measure of temporal vagueness were consistent with the main results. To better address press releases with both qualitative and quantitative cues, we reran the models by measuring frequency of temporal vagueness as the total number of vague cues/total number of temporal cues (clear + vague). The results were consistent with those of the main analyses. Firm context: We reran the analyses using firm fixed effects to rule out confounds created by un-modeled variables. The results were consistent with the main analyses. DISCUSSION Building on the temporal framing research rooted in inter-temporal choice theories, we examined the following question: Does focal firms’ temporal framing of their competitive action announcements influence rivals’ responses? The motivations guiding this research question were twofold: first, to examine firms’ linguistic communication in the competitive context; and second, to introduce a new form of framing––temporal framing. This study yielded important insights in both regards. First, it highlighted the effects of framing of a focal firm’s action announcement on rivals’ response speed, over and beyond the action-based explanations proposed in competitive dynamics research. Second, it introduced temporal framing as an important cueing mechanism in how rivals evaluate and respond to a focal firm’s action announcement. Both temporal vagueness and distance decreased rivals’ response speed, and frequency amplified the main effects of each. Moreover, temporal distance strengthened the negative effect of temporal distance on rivals’ response speed. Theoretical implications. Linguistic underpinnings of competitive dynamics. Research rooted in the action-based view has posited action-based explanations of rivals’ responses, including action type, announcement timing and the competitive context as the drivers of rivals’ construal of and response to focal firms’ action (Chen et al., 2007; Derfus et al., 2008; Ferrier et al., 1999). We theorized temporal framing as an important additional cueing mechanism for rivals’ reactions to a focal firm’s action announcement (Berns et al., 2007; Loewenstein, 1988). Our empirical context of duopoly industries lends a conservative test of the temporal framing hypothesis, because duopoly firms compete fiercely and retaliate speedily just to keep up with rivals, regardless of linguistic cues (e.g., temporal framing) (Derfus et al., 2008; Ferrier et al., 1999). The results of this study confirmed the key role of temporal framing over and above these alternative explanations. Temporal vagueness (b = -0.13, p < .05) and temporal distance (b = -0.32, p < .001) in the focal firms’ press releases individually and interactively explained the incremental additional variance in rivals’ response speed, after action type and characteristics, timing of action announcement, and relative market share had been controlled for. Our results are especially notable because they illustrate that focal firms’ temporal framing shape rivals’ retaliation even in the duopoly contexts where the plausibility of the null hypotheses is high. These results complement and extend the sparse but growing research in competitive dynamics that posits language as a basis of inter-firm rivalry (Gao et al., 2016; Guo et al., 2017; Rindova et al., 2004). Guo and colleagues (2017) showed how, in a company’s annual report, language highlighting environmental uncertainty lowers the likelihood of market entry by competitors. Our study introduces temporal framing as a fundamentally new perspective for theorizing inter-firm rivalry. The results show how focal firms can actively embed an “interpretive temporal context” in their rivals through temporal framing. Although competitive dynamics research has long recognized that contextual uncertainties and urgency are important considerations in competitor analysis, it has identified environments (e.g., velocity, dynamism) and action characteristics (e.g., execution difficulty, uncertainty) as sources of uncertainty and urgency in competitor analysis (D'Aveni et al., 2010; Ferrier, 2001). We drew on inter-temporal choice theories to posit how focal firms can intentionally vary the temporal vagueness and distance cues in their press releases to prime rivals’ perceptions of uncertainty and urgency in construing and responding to their actions. Our inductive qualitative interviews with strategy and public relations executives, media reporters and analysts confirmed this intentionality behind firms’ framing of the timelines of their action in the press releases. Future studies could build on the promising results of this study to examine other forms of framing that could guide rivals’ interpretations. For example, internal versus external attribution framing in focal firms’ press releases could prime rivals’ perceptions of the focal firm’s degree of control over the environment (Salancik & Meindl, 1984). Valence framing (e.g., gain-enhancing versus loss avoidance), on the other hand, could guide rivals’ interpretations of focal firms’ proactive versus reactive competitive stance (Levin et al., 1986). Such investigations could strengthen our understanding of how language permeates inter-firm rivalry. Trade-offs in framing action announcements. The competitive implications of framing demonstrated in this study call for a broad and multi-faceted theorizing of the strategic implications of language in organizational communication. Organizational communication research has devoted much attention to examining how firms use linguistic manipulation as part of a public relations campaign to garner approval from key constituents such as shareholders and the media but has largely ignored the reactions of competitors to action announcements (Fiss & Zajac, 2006; Pollock & Rindova, 2003; Rhee & Fiss, 2014; Westphal & Deephouse, 2011). This omission of how framing of action announcements affects the reactions of rivals is the key to an important puzzle:why would firms use language that increases the likelihood and speed with which a competitor retaliates to a strategic action? Alternatively, why would firms use unflattering language to depict their actions even at this risk of alienating key stakeholders? This study is among the first to examine the challenges that firms face in using framing as a strategic vehicle to gain advantage in their engagement with rivals who have sharply opposing interests in the firms’ action timing. Our results address this puzzle and contribute to the organizational communication research by highlighting the dark side of favorable language in presenting action announcements. Table 4 summarizes our study findings and future implications of this dilemma related to linguistically communicating action announcements. As shown in Table 4, we found that focal firms’ clear (low vagueness) and proximal presentation of action timelines attracted speedy retaliation from rivals. The results of this study, combined with the cumulative insights from prior organizational communication research, highlight the conflicts that focal firms face in harmonizing the divergent stakes of key stakeholders in framing their action announcements. The results of the first stage of the instrumental analysis hint at the public relations motives behind temporal framing, possibly aimed at constituents. For example, increased dependence of the firm on shareholders, reflected in a greater proportion of institutional investors (b = -0.02, p < .001), greater alignment of the CEO’s interests with those of the shareholders evident in greater percentage of CEO stock options (b = -0.02, p < .001) and greater investor pressure because of stock price declines (b = 0.06, p < .001), related negatively to temporal vagueness in focal firms’ press releases. The intent behind such concrete framing could be to present the competitive action favorably to shareholders and investors by highlighting its clarity. Conversely, matched rivalry (relative market share) related positively to temporal vagueness, possibly intended to tone down the competitive threat of the action to the matched rival and thus avoid harmful retaliation (b = -0.27, p < .001). Taken together, these results point to the opposing motives of firms in temporally framing their action announcements to accommodate the “interests and concerns of stakeholders” while accounting for the competitive nature of the market environment (Chen & Miller, 2015: 6). Future studies could build on our research to further theorize and test the implications highlighted in table 4. Such research could help us better understand how firms balance these trade-offs when using temporal framing in action announcements. ------------------------------- Insert Table 4 about here ------------------------------- The role of temporal framing in organizational communication. The promising results on the important role of temporal framing in driving rivals’ responses, beyond the established action-based explanations, lend credence to inter-temporal choice theories that contend that timelines form the basis of how decision situations are construed, which response alternatives are generated, and ultimately which choices are made (Loewenstein & Elster, 1992; Read & Loewenstein, 2000; Trope & Liberman, 2003). The introduction of temporal framing complements existing organizational communication research that has examined affect (positive/negative) and valence (gain/loss, prevention/ promotion) as the basis of linguistic strategies in organizational communication (Pollock & Rindova, 2003; Rhee & Fiss, 2014; Weber & Mayer, 2011). Temporal framing constitutes a distinct form of framing that induces audience reactions through a unique mechanism not examined in prior research––the temporal discounting bias originating from perceptions of uncertainty (vagueness) (Keren & Roelofsma, 1995) or urgency (distance) (Trope & Liberman, 2003). Our results suggest that these underlying temporal mechanisms are particularly important in the competitive context, where gauging the temporal window of opportunity is central to retaliation (Chen & Miller, 2015; Katila & Chen, 2008). Competitive dynamics scholars have acknowledged the importance of temporal windows of opportunities in cueing rival’s responses and alluded to the “wait-and-see” approach adopted by rivals in the face of action uncertainty (Chen et al., 2002); however, they have defined action timing (early versus late) as the locus of this temporal cueing of responses (D'Aveni et al., 2010; Defus et al.,2008). Our results suggest that aspects of the temporal language (vagueness and distance) in the announcements serve as additional temporal cueing mechanisms beyond action timing, which was also an important driver of rival’s response speed. The unique and complex interactions among the temporal framing variables lend a more holistic picture of the competitive ramifications of focal firms’ framing of their competitive actions. Examining these temporal framing interactions in the context of constituents such as shareholders and the media is an important area of extension. The effects of the proportion of institutional investors, proportion of CEO stock compensation and stock price declines on temporal vagueness and distal framing point to this public relations motive behind firms’ temporal framing targeted at shareholders. Because focal firms’ motives in framing directed toward constituents are inherently different from their motives in competitive framing (Chen & Miller, 2015; Connelly et al., 2010; Zhang & Gimeno, 2010), the nature of the main effects and interactions of temporal framing may turn out to be different in the context of constituents. The current study constitutes an initial step in examining the strategic implications of temporal framing. The rich tradition of temporal framing in psychology provides ample avenues for expanding the results of this study. One particularly promising avenue is to integrate temporal framing with the affect- and valence-based linguistic construction examined in prior organizational communication research (Pollock & Rindova, 2003; Rhee & Fiss, 2014; Weber & Mayer, 2011). The inter-temporal choice theory suggests that the effect of temporal distance is stronger for affect-based, “hot” value than for cognition-based, “cool” value (Loewenstein, 1996; Metcalfe & Mischel, 1999). Although the value of all outcomes is discounted over temporal distance, affective outcomes (e.g., positive or negative market reactions to the new product) undergo steeper time discounting than do cognitive outcomes (e.g., technical specifications of the new product). Similarly, the effect of temporal distance depends on whether the valence of the outcomes is positive (gain) or negative (loss). Because “avoidance (loss-avoidance) gradients are steeper than approach (gain-enhancing) gradients, the discounting rate is greater for negative outcomes (losses) than for positive outcomes (gains)” (Trope & Liberman, 2003). Examining the complex interactions between proximal versus distal framing of action timelines and affective versus cognitive and gain versus loss framing of action outcomes may yield interesting additional insights into the boundary conditions of temporal distance framing. These complex interactions of temporal and valence framing may also be pertinent to how firms craft their language so as to balance the divergent interests of constituents and rivals. Because positive valence is discounted less with temporal distance, focal firms could combine positive outcome valence with distal timeline to portray the action favorably to constituents. The focal firm’s positive valence constitutes negative valence for rival firms. However, because negative valence depreciates steeply over temporal distance, the distal length of the timeline may serve as a buffer from competitive retaliation. Limitations, future directions, and conclusions Some limitations deserve acknowledgment. First, because our sample was restricted to duopoly industries, the framing effects found in this study may not generalize to industries characterized by more open competition, where incumbent firms face various rivals with very different competitive positions and stakes. Examining temporal framing effects in less concentrated industries is an important area of future research. Second, temporal framing represents just one content domain of framing. Future studies could explore the competitive implications of other forms of framing, such as positive versus negative framing (Tversky & Kahneman, 1981) and attribution framing (internal firm versus external environmental drivers of competitive action) (Elliott & Hayward, 1998; Prabhu & Stewart, 2001), and thus could complement the results of this study and provide new insights. Third, our study focused only on the influence of focal firms’ temporal framing on competitors’ responses. Future studies could explore the impact of temporal framing on other potential audiences, such as shareholders. For example, firms may differ considerably in their motivation to please the shareholders, depending on the viability of securing resources from them. If the firms rely less on, or have less likelihood of securing resources from, shareholders, they would prioritize competitive deterrence in framing their announcements vaguely, caring little about shareholders’ adverse reactions to such vague temporal framing. However, if they are in dire need of resources from shareholders, they will prioritize them in their clear temporal framing, even at the risk of competitive retaliation. Future research could examine the factors driving the difficult choices firms make in their framing of competitive announcements. In conclusion, our study offers temporal framing as a new lens, through which to examine the linguistic underpinnings of competitive dynamics. 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