Clear Signals or Ambiguity? How Long-Buyers and Short-Sellers React Differently to Competitive Actions.
In general, that competitive behavior can be observed, interpreted, and utilized as informational cues that investors use when evaluating the firm's future value is posited. The findings from the Bettis and Weeks (1987) study provided an early glimpse into this phenomenon. Although both Kodak's and Polaroid's market value declined during the study's 1976-1977 time period, Kodak's losses were steeper than Polaroid's. Beyond examining each firm's fundamentals, it appears that most investors expected Kodak's actions it carried out to help the company fend off Polaroid's attacks on its market position. However, upon closer examination, Polaroid's attacks and Kodak's ineffective counter-attacks served to expose Kodak's competitive weaknesses. The investment community, interpreting and reacting to the Kodak-Polaroid battle as it unfolded, adjusted Kodak's future earnings estimates sharply downward.
Investor reactions to the Kodak-Polaroid battle demonstrates that some investors do indeed pay close attention to evaluative information beyond financial ratios. More specifically, owing to their unique perceptions and the use of systematic information processing approach, short-sellers are suggested to more likely than long-buyers to take specific attributes of a firm's competitive behavior into account when establishing estimates of future value. Indeed, notwithstanding the scope of prior competitive dynamics research, an intriguing, yet understudied aspect of how competitive actions influence performance involves the perceptions and impressions held by industry participants and observers. To date, only a few studies have explored, for example, the relationship between organizational actions and legitimacy (Pollock and Rindova, 2003), organizational actions and reputation (Rindova et al., 2007), organizational reputation and performance (Rindova et al., 2005), or how a rival's actions increase the level of competitive tension perceived by managers (Chen et al., 2007). The aim of this study is to contribute to this stream of research by exploring whether and how long-buyers and short-sellers--as investor-observers--perceive and react differently to informational cues embedded in the firm's pattern of competitive actions. This investigation considers the influence of competitive actions on two distinct stock market outcomes of a given firm: cumulative abnormal returns and the short-interest ratio. Whereas cumulative returns captures the reactions of all investor types, the short-interest ratio captures the reactions of only short-sellers.
Within finance research, the efficient markets hypothesis--a key tenet of asset pricing theory--posits that markets are informationally efficient. That is, prices for traded assets such as stocks and bonds should at least already reflect all publicly available information. Therefore, these prices are unbiased in that they incorporate the collective beliefs of all investors about future prospects (Fama, 1970). However, behavioral finance scholars have begun to challenge the efficient markets hypothesis by arguing that a myriad of factors can affect how investors form opinions about stocks. At one extreme, studies have found, for example, that the amount of sunlight in the city in which the exchange where the stock is listed and trade influences stock prices (Hirshleifer, 2001; Hirshleifer et al., 2011; Henderson, 2012). This suggests that factors beyond informationally efficient markets can impact market outcomes for some firms (Hirshleifer, 2001). From this, arguments are made that the informational cues associated with observed competitive strategy is not efficiently nor uniformly processed and used by all investors. Instead, analysis of how the patterns and intensity of a series of competitive actions carried out among rival firms impacts the perceptions and beliefs that different investors form about a firm's future potential, which is reflected in the value of its equity shares, is undertaken.
Investigation of this phenomenon is seen from the perspective of two classes of investors: one investor sells a stock; the investor on the other side of the transaction is buying it. This simple reality provides logical and observational evidence that investors do have differing views of the publicly available information about the security. Hirshleifer (2001: 1533) contends that the "great missing chapter in asset-pricing theory ... is a model of the process by which people form and transmit ideas about markets and securities." Thus, the goal of this study is to develop a model of this process for longbuyers and short-sellers through a strategic management lens. In so doing, theory drawn from competitive dynamics, social judgment theory, and cognitive psychology is integrated to explain that investors react differently to observed competitive strategy because they likely use distinctly different decision-making processes. Posited is that long-buyers predominantly use a heuristic decision process, whereas short-sellers rely on a systematic decision process in an effort to discern greater meaning perhaps hidden in the firm's pattern of competitive actions.
Short selling is a means for an investor who expects a stock price to decline to realize a profit without initially owning the stock. Instead, the investor contracts to sell shares of a stock "short" at its current price by borrowing the shares from a brokerage firm. If the investor's projection is correct, the shares are purchased later at a lower price and returned to the broker-lender with the investor earning a profit. However, the short-seller loses money if the price of the shares increases, forcing the short-seller to cover the short position with shares purchased at a higher price. Thus, short-sellers face much greater potential losses than long-buyers at a given price (de Roon and Szymanowska, 2012). Long-buyers may lose their entire investment if they invest in a firm that goes out of business. Short-sellers, however, can lose many multiples of their original investment if they short stocks that increase dramatically in price. Therefore, conventional wisdom purports that such disproportionate risk exposure obliges short-sellers, as compared to long-buyers, to analyze more carefully all information about target investment firms' competitive strategies and anticipated future moves.
To date, "short interest"--conceptualized and measured as the percentage of a firm's outstanding shares sold short--has only been recently examined using a strategic management lens (Hughes-Morgan and Ferrier, 2016). These authors found, for example, that when viewed as an indicator of poor future performance, higher levels of short interest strongly motivate firms to exhibit more aggressive competitive behavior in the ensuing time period. This suggests that short interest is an important strategic variable. Indeed, finance scholars have conclusively demonstrated that higher levels of short interest (5% or greater) are associated with negative changes in stock prices, an average of -18.1% over the next year (Dechow et al., 2001; see, also, Boehmer et al., 2010; Zhang and Gimeno, 2010). Very low levels of short interest are associated with gains in one-year-ahead abnormal returns (+2.3%) (Dechow et al., 2001). So, to the extent that poor past performance results from higher levels of short interest ought to motivate the firm to compete more or less aggressively. Also, the level of short interest is an indicator of the heterogeneity of investor opinions (Boehmer et al., 2010); higher levels of short interest indicate mixed investor evaluations of the efficacy of a firm's strategy. Greater heterogeneity thus portends declining stock prices. Moreover, according to scholars in finance, short-sellers are perhaps more motivated than the average investor to systematically use a wider range of informational cues in their evaluations because of the high cost and significant risk involved in shorting stocks (Diamond and Verrechia, 1987). Therefore, providing a deeper understanding of the relationship between characteristics of a company's strategy and a greater likelihood of investors "shorting" a firm's stock is important to both finance and strategy scholars alike.
A Theory of Competitive Action Ambiguity and Investor Sense-making
Competitive actions defining the firm's strategy are the central focus of empirical and theoretical research by competitive dynamics scholars. Competitive actions are predetermined, externally-directed competitive moves initiated to enhance the firm's position relative to competitors (Smith et al., 2001). Action-reaction dyads comprised the level of analysis for early research in this field whereby the characteristics of a given competitive action influenced the likelihood, type, and speed of competitive response by a rival (e.g., Chen and MacMillan, 1992; Chen et al., 1992). However, the vast majority of research in the past 20 years studied the antecedents and outcomes associated with competitive action repertoires: the entire set of competitive actions carried out in a given time period (e.g., Miller and Chen, 1996; Ferrier et al., 1999; Gnyawali et al., 2006; Connelly et al., 2016). Battling against each other, firms will execute a series of moves and countermoves--e.g., product introductions, advertising programs, plant expansions, price discounts, etc.--to gain profits and to maintain the edge against rivals (D'Aveni, 1994; Smith et al., 2001). As each competitive move is carried out over time, investors (particularly short-sellers) are argued to simultaneously evaluate whether the competitive action will likely succeed or fail, and whether an entire series of moves comprises a coherent, successful strategic whole. This impacts the investor's decision to buy, continue to own, sell, or short the firm's stock.
By integrating ideas from competitive dynamics, behavioral finance, and cognitive psychology, the characteristics of a firm's competitive action repertoire that each type of investor perceives and believes to be beneficial to value creation for the firm are explored. As noted, long-buyers are argued to more likely use an heuristic decision-making approach to stock evaluation which involves considerable rule-based rational thought, but relatively limited systematic effort. Consistent with social judgment theory, it is suggested that investors take a variety of signals or cues, such as observed competitive actions, into direct account (Sherif et al., 1965; Brockmann and Anthony, 1998). Information theory supports this notion by introducing representational (or "information-processing") explanations of this type of coding of cues, known as "serial pattern processing," and postulates one or more processes for inducing pattern description from sequences. According to Newell and Simon (1972) people appear to have strong propensities, whether learned or innate, to discover patterns in temporal sequences presented by the environment, and to use these patterns to predict positive or negative future outcomes--they know what they see and whether they like or dislike what they see.
Information theory implies that one direct method to measure information sequences is by their complexity, i.e., the amount of information, the breadth of the information, and the variability of elements within the sequence of information. Thus, when looking at various types of strategies one can logically assume that investors are classifying the sequences in a similar fashion. This assumption gives rise to strategic classifications such as volume (amount of information), and complexity and heterogeneity (breadth of information--how different a focal firm's strategy is from its previous strategies and those of its competitors). Decisions and judgments based on these data are processed by long-buyers according to heuristic choice rules that reduce decision-making effort and are generally useful in most decision contexts. However, this can lead to biases or systematic judgment errors (Tversky and Kahneman, 1974).
Because of the extreme financial risk associated with being wrong about a given short sell, short-sellers are strongly motivated to strive for a more comprehensive and certain assessment related to the connection between the firm's observed competitive actions and future stock performance. Short sellers are more likely than long-buyers to engage in systematic decision processing that involves deep "cognitive elaboration" with regard to the links between decision inputs, process, and outcomes (Chaiken et al., 1996). Drake et al. (2011), using different terminology, came to the same conclusion. They found that compared to the members of the broader investment community, short-sellers incorporated a much more comprehensive set of information-linked variables into their investment decisions.
Ambiguity in Competitive Repertoires
In investors' eyes, the focal firm's set of competitive actions can be characterized as having low ambiguity or having high ambiguity. In the former case, firms carry out a large number of competitive actions, have simple competitive action repertoires, and carry out a set of actions similar to that of rivals. Such action repertoires will be viewed by investors as equilibrating competitive behavior (Smith and DiGregorio, 2002) insofar as these characteristics decrease the variance in investors' cause-effect mental maps of a given strategy (Bogner and Barr, 2000); will reinforce the emergence and convergence of similar competitive actions carried out by an increasing number of rivals (Spender, 1989); and will reduce ambiguity (Mosakowski, 1997).
A high-ambiguity competitive action repertoire is characterized as having fewer total competitive actions, being also composed of a more complex and diverse set of competitive actions, and being non-conforming when compared to the set of actions carried out by rivals. This will be viewed by investors as disequilibrating competitive behavior that increases ambiguity (Mosakowski, 1997) and induces higher states of strategic disequilibrium (D'Aveni, 1999).
Given that a firm's competitive action repertoire is likely to vary along a continuum of equilibration-disequilibration, the level of investor incoherence--defined as a condition in which investors apply different interpretive and evaluative mechanisms to the same set of market stimuli--is a situation in which the market system "...continually introduces new events, each of which requires a new learning process to understand their implications" (Zuckerman, 2004: 409). Thus, that long-buyers and short-sellers have different lenses through which they perceive and evaluate the firm's observed competitive actions is predicted. By the same token, long-buyers will more easily perceive and favor equilibrating, low-ambiguity competitive action repertoires. This will have a positive effect on the firm's cumulative abnormal returns. Long-buyers will have difficulty perceiving and making sense of a disequilibrative, high-ambiguity competitive action repertoire that will negatively affect the firm's stock returns. By contrast, short-sellers will likely perceive an equilibrating, low-ambiguity strategy as risky or nondistinctive relative to rivals, which places the focal firm at a competitive disadvantage. As a result, they will tend to sell the firm's stock short (high short interest ratio). When confronted with a disequilibrating, high-ambiguity competitive action repertoire, short-sellers will systematically evaluate and perceive the value-creating/enhancing benefits of the actions and tend not to sell the firm's stock short (low short interest ratio).
Action Repertoire Volume
A core tenet of competitive dynamics posits that firms that carry out a sustained and forceful set of actions will stun and confuse rivals and keep them off balance, thereby rendering them less capable of responding (D'Aveni, 1994; Ferrier et al., 1999; Ferrier, 2001). Young et al. (1996) found that when firms increase their competitive moves, they experience higher returns on assets and sales; that is, firms win when they consistently carry out more competitive actions than do rivals. Several studies have also both proposed and shown volume of competitive moves to be beneficial when defending market share. Huff and Robinson (1994) contended that firms improve their competitive position when they undertake competitive actions to steal market share from the market leader. Likewise, market share leaders are more likely to lose their position unless they act competitively to prevent competitors from eroding their market share (Ferrier et al., 1999). However, these strategic moves come with an associated cost and use of firm resources (Porter, 1980). So the impact on investor perception could ultimately be either positive or negative.
Psychologists have long observed that repeated, reinforced exposure to a stimulus increases positive affect toward the stimulus (Maslow, 1937). Early research showed that repeated exposures and increasing familiarity generally elicited more positive ratings of a given object or medium (Meyer, 1903; Gilliland and Moore, 1924). Additional evidence for the hypothesis that increased exposure leads to more positive affect toward a stimulus comes from studies of social interaction (Festinger, 1951; Newcomb, 1963). Some research in finance reinforces these findings suggesting, for example, that a firm's overall visibility with investors, as measured by its product market advertising, has positive consequences for the equity shares (Grullon et al., 2004). Thus, a firm carrying out a large volume of competitive moves (greater visibility) may benefit by the longbuyer's use of the exposure heuristic. By contrast, firms that carry out too few actions (as in high-ambiguity contexts) are not aggressive enough in attacking rivals. Thus, longbuyers will discount future cash flows based on their interpretation of competitive complacency and inactivity.
Hypothesis 1A: Action repertoire volume will be positively related to stock returns.
Short-sellers will likely evaluate competitive action repertoire volume differently. Using a systematic decision-making approach, these investors will likely come to realize that some competitive actions are necessary to create or sustain value. Yet, as volume increases substantially beyond some unspecified threshold, the benefits of competitive aggressiveness are offset by higher costs and slower implementation speeds (Andrevski and Ferrier, 2016). Thus, the use of a systematic decision-making process will allow the short-seller to realize, as espoused by Porter (1985), that there is an associated cost to implementing these strategic moves and, in fact, costs may rise faster than revenues so this low ambiguity scenario may not be beneficial. They also explicitly consider the risk of competitor retaliation or the "Red Queen effect" that may offset the benefit of carrying out a very high volume of competitive actions (Derfus et al., 2008). This will lead to increased levels of short-selling in response to higher costs and risks. In sum, too few actions place the focal firm in a state of competitive risk, i.e., rivals will be more aggressive. Too many actions will be perceived as being unwieldy, superfluous, and costly. This implies that short-sellers value a moderate number of actions--and implies a curvilinear relationship between competitive actions and short interest ratio.
Hypothesis 1B: Action repertoire volume will exhibit a U-shaped relationship with short interest ratio.
Action Repertoire Complexity
Psychology scholars have shown that both the ease and speed with which observer-evaluators can process a range of stimuli affect the valuations of object or medium to which the stimuli apply (Jacoby and Brooks, 1984). This describes the fluency heuristic used by observers in making decisions and subjectively ascribing positive evaluations to stimuli that are simple to observe and interpret. Similarly, because of "nonlearning," some observers are indifferent to or have difficulty interpreting and evaluating complex stimuli. This often results in negative observer evaluations or feelings toward the object or medium (Eagly, 1974; Chaiken and Eagly, 1976, 1983). This highlights a rather simple tendency, that observers place greater positive weight on information that feels easy to process.
Prior research suggests that competitors can more readily understand and react to simpler competitive strategies, i.e., fewer competitive moves, as compared with strategy repertoires encompassing many diverse types of competitive actions (Ferrier et al., 1999; Ferrier, 2001). Thus, owing to their reliance on a heuristic decision-making process, long-buyers will become gradually less motivated to interpret the future value of the firm's stock price as the complexity or diversity of a firm's competitive action repertoire increases. Instead, these investor-observers view increasingly complex patterns of competitive actions carried out by the firm as being reflective of a strategy that is unfocused and lacking in familiarity. More specifically, as competitive action repertoire complexity increases, long-buyers, owing to their discomfort with high levels of ambiguity, will shift from using a fluency heuristic to an [negative] affect heuristic that evokes subjectively derived negative attitudes, feelings of unpleasantness, or even discomfort toward the firm's strategy (Eagly, 1974; Chaiken and Eagly, 1976, 1983). This, in turn, motivates the long-buyer to sell the stock, thereby lowering stock prices.
Hypothesis 2A: Action repertoire complexity will be negatively related to stock returns.
When faced with higher costs and risks associated with selling the firm's stock short, short-sellers will likely use a systematic decision-making process to first unravel and assess each element of a firm's competitive strategy while also evaluating the entire repertoire of competitive actions as a Gestalt (Rindova el al., 2010). Like long-buyers, short-sellers will believe that the firm's rivals can easily decipher and effectively respond to a simple set of competitive actions. Such simplicity places the firm at higher levels of competitive risk, thereby leading to higher levels of short interest associated with the focal firm's stock. However, as competitive action repertoire complexity and ambiguity increase, short-sellers will better appreciate the advantage of the firm being less vulnerable to attacks by rivals. Here, when complexity increases beyond the level at which the long-buyer becomes uncomfortable, the short-seller's use of a systematic decision-making approach will accommodate the perception, interpretation, and value of higher and higher levels of strategic complexity in thwarting rivals. So, whereas the highest levels of strategic complexity confound the long-buyer, the more highly complex/ambiguous strategies are embraced by the short-seller.
Hypothesis 2B: Action repertoire complexity will be negatively related to short interest ratio.
Action Repertoire Non-Conformity
Strategy scholars disagree about the consequences of competitive action repertoire heterogeneity. On one hand, some argue that carrying out a set of competitive actions that deviate from industry norm will baffle, confuse, or surprise rivals with moves that are tricky to identify and respond to (Porter, 1980; D'Aveni, 1994). On the other hand, Miller and Chen (1996) assert that competitive behaviors that deviate from the norm oftentimes confuse observer-investors. Here, the costs of strategic non-conformity may outweigh their benefits. One study argues that the performance consequences of nonconformity depend upon industry context: non-conformity favors firms that compete in established industries, whereas familiarity favors firms that compete in nascent markets (Rindova et al., 2010). Still other studies that draw from institutional theory suggest a balance between the two extremes; competitive strategies that are neither too similar to nor too different from that of rivals experience better performance (Deephouse, 1999). Given these conflicting views, it's important to explain how strategic differentiation and heterogeneity impacts stock market performance.
When competing firms differ greatly in the composition, pattern, and pacing of the competitive actions each carries out against the other, long-buyers will not fully appreciate and ascribe value to the deviation of the firm's competitive strategy from the status quo. Instead, long-buyers will be influenced by the recognition heuristic, which suggests these investors consider firms that conform to the strategies that are familiar to referent others to be more legitimate and of higher value. Bornstein (1989) believes a preference for something recognized or familiar is a logical human process, as unfamiliar stimuli and situations are potentially riskier than familiar ones. This heuristic has also been prevalent in empirical studies of stock selection. Scholars have demonstrated private investors tend to purchase "high-profile" stocks that have previously experienced high volumes or returns, or have been publicized in recent press releases and news reports. This investment strategy, however, has been shown to underperform the market index (Barber and Odean, 2005). Weber et al. (2005) provided some insight into why investors might follow an unprofitable investment strategy driven by the "attention-grabbing" features of shares. They found that people tend to perceive that shares of companies whose names they recognize are less risky than those with which they are unfamiliar. It follows, then, that some firms within an industry become known for strategies that are recognized and acceptable in that industry, and that some investors, particularly longbuyers who are more likely to resort to heuristics and eschew high levels of ambiguity, will penalize firms that deviate from the established patterns. Thus, the greater the heterogeneity of a firm's strategic repertoire, the lower the stock returns.
Hypothesis 3A: Action repertoire non-conformity will be negatively related to stock returns.
In contrast, short-sellers are more likely to ascribe negative future values (i.e., higher levels of short interest) to firms that carry out strategies that are similar to those of rivals. This is in line with, for example, Porter's (1980, 1985) view of the dangers of strategic conformity (i.e., the absence of any sources of differentiation). In addition, from the Austrian perspective, effective competition espouses strategic and resource heterogeneity (Jacobsen, 1992). This perspective advocates creation of competitive advantage through possession of the knowledge, resources, and flexibility to engage in a variety of actions, and that successful firms are able to combine and direct these resources differently than other firms. Thus, much of the basis for value creation is attributed to the ability of firms to innovate or compete in a manner unique to their competitors. Short-sellers, however, will likely appreciate this ambiguity and recognize the firm's efforts to depart from convention as value creating. Thus, as strategic heterogeneity increases, short-sellers are less likely to short the company's stock, resulting in lower levels of short interest.
Hypothesis 3B: Action repertoire non-conformity will be negatively related to short interest ratio.
To establish the sample, all firms in COMPUSTAT that listed their main line of business as pharmaceutical preparations (SIC code 2834) were selected. This industry is characterized by precisely defined boundaries, ensuring that competitive moves implemented by industry members are designed to enhance a firm's industry position relative to competitors. Thus, the pharmaceutical industry provides an ideal forum for studying reactions by the stock market to competitive moves. Market appraisals of pharmaceutical firms depend mainly upon estimates of eventual cash flows; thus, companies widely announce competitive moves with the intent to boost future valuations. In addition, competitive interaction among firms in the sample is intense.
The final sample consists of an eight-year (2007-2014), cross-sectional database of 102 publicly-traded pharmaceutical companies. N for this analysis thus is 9792 (102 firms x 8 years x 12 months).
Cumulative abnormal returns (CAR). The event-study methodology approach recommended by McWilliams and Siegel (1997) was used to measure the abnormal stock price returns of the firms in response to the sequential patterns of competitive actions. This procedure estimates a market model for each firm and then calculates abnormal returns relative to some index, in this case, the S&P 500. CAR is an estimated variable composed of the stock's rate of return, the S&P rate of return, and the stock's systematic risk, as well as the regressed intercept and error terms.
Returns within a three-day observation window surrounding each observed competitive action were utilized. This helps account for changes in the variation of the firm's stock price between the particular day of the action, as well as the days before and after. This three-day window also helps account for possible "leakage" prior to the publication of the news headline or slow reactions by some investors to a particular strategic action or tactic.
Short interest ratio. A firm's short interest ratio is the percentage of the total shares outstanding in month that are sold short. The NYSE and NASDAQ stock exchanges typically collect short interest data midway through each month and issue this information in the Wall Street Journal.
Consistent with prior research, a competitive action is defined as an observable, specific, and externally directed move aimed at outmaneuvering rivals to gain a superior competitive position (D'Aveni, 1994; Ferrier, 2001, Smith et al., 2001). Following prior research, structured content analysis of news articles found in Factiva was used. To ensure the reliability of coding all actions into the appropriate categories, two strategic management academics independently categorized a randomly selected sample (N=300) of news article headlines into the ten categories. This approach produced a reliability index of 0.89, exceeding the conventionally acceptable level of 0.70 (Denzin and Lincoln, 2000).
Action repertoire volume. To measure the extent to which a firm's competitive repertoire consists of a greater or fewer total number of competitive actions (irrespective of the types of actions), the number of competitive actions carried out each month were tallied. This measure is consistent with that used in prior research (Young et al., 1996; Ferrier et al., 1999).
Action repertoire complexity. To capture the degree to which a company's competitive repertoire includes a wide range of different action types, a Herfindahl-type index that accounts for the weighted variety among the ten action types was used (Ferrier et al., 1999; Ferrier, 2001). For example, if one firm's competitive action repertoire consisted mainly of one type of action, it is considered a simple repertoire. If the repertoire consists of a set of actions of each type, the repertoire is more complex. Therefore, a firm with a low action complexity score utilized only a few action types, while a firm with a high complexity score carried out a wide range of action types.
Action repertoire non-conformity. To assess the differences among firms' competitive action repertoires, a Euclidean distance score was used. Here, the monthly frequencies for each of the types of actions carried out by each firm in a given month were tallied. Then, the Euclidean distance between each firm's repertoires of competitive actions in the month were calculated relative to the industry average. A low score suggests that the firm executes a mix of actions very similar to those of other companies within the industry. A high score indicates that the firm's competitive action repertoire is quite unlike the repertoires of rivals.
Control variables. In the analysis, firm size was controlled for using the log of total assets and firm age measured as years since founding. Altman's Z-score was used as a measure past performance. Altman's Z has been used in several competitive dynamics studies as an indicator of financial distress (Ferrier et al., 2002), it consists of five accounting and market performance ratios that are combined into a single score and (Chakravarthy, 1986). This is a more comprehensive measure of firm performance than solely using ratios such as ROA or ROE. High Z-scores indicate a condition of strong financial health; low Z-scores indicate risk of financial distress and/or bankruptcy. To control for different levels of absorbed slack and resource allocations that could affect returns and varying levels of short interest, capital intensity was also used as a control.
The sample means, standard deviations, and correlations for all variables are reported in Table 1. To control for autocorrelation within each firm, a mixed, fixed-effects regression analysis was undertaken that accounted for time by including each observation's month-year as a separate effect.
Hypothesis 1 predicted that the relationship between action repertoire volume-the total number of actions carried out by the firm in a given month--would be related to stock market performance and short interest. Hypothesis la was supported. As reported in Table 2, the coefficient representing the influence of action repertoire volume on cumulative abnormal returns is positive and significant (Model 1: b = 3.382, p<0.01). Hypothesis lb was also supported. Both linear and squared terms for competitive action repertoire volume were significant (Model 4: b = -0.0008, p<0.01; b = 0.0003, p < 0.01). This indicates that action repertoire volume exhibits a U-shaped relationship with short interest ratio.
No support was found for either variant of Hypothesis 2. The coefficients representing the influence of action repertoire complexity--the extent to which the firm's repertoire of competitive actions comprises a diverse set of different types of competitive actions--on both cumulative abnormal returns (Model 2: b = 4.456, n.s.) and short interest ratio (Model 5: b = -0.0007, n.s.) were not significant.
The relationship between action repertoire non-conformity--the extent to which the focal firm's repertoire of competitive actions is different from those carried out by referent rivals--was found to be negatively related to cumulative abnormal returns (Model 3: b = -8.779; p<0.01) and negatively related to short interest (Model 6: b = 0.0019, p<0.05). This provides support for both Hypothesis 3a and Hypothesis 3b.
DISCUSSION AND CONCLUSIONS
Drawing from core ideas in competitive dynamics and decision-making, this study stands among the first to explore how competitive behavior among rivals differentially influences investor reactions. Findings suggest that long-buyers and short-sellers react differently to specific characteristics of a firm's competitive strategy. The authors argue that the difference is associated with the interpretive and evaluative mechanisms each type of investor likely uses.
More specifically, findings suggest that long-buyers positively reacted to firms that carried out a high number of competitive actions. It is reasoned that this was associated with the long-buyers reliance on a simple, more-is-better heuristic. It is also reflective of an exposure heuristic: the more visible the firm and its strategy (via a high volume of observed actions), the more positive the response bias. So, more actions garner more attention which, in turn, gives rise to higher stock prices. So, despite the additional costs and slower action implementation speeds associated with the firm carrying out a very high volume of competitive actions, long-buyers apparently view strategic volume as a form of competitive aggressiveness that, according to the literature on temporary advantage (D'Aveni, 1994), signals that the firm seeks to press its advantage(s) in a disruptive, ambiguity-decreasing, and disequilibrating way (D'Aveni, 1999; Smith and DiGregorio, 2002).
To a point, findings suggest that short-sellers, like long-buyers, also valued the initial increase in the number of competitive actions. Yet, beyond a moderately aggressive repertoire number, short sellers are likely to directly account for the rapidly escalating costs and execution difficulties associated with overly aggressive competitive action repertoires (Andrevski and Ferrier, 2016).
In general, findings pertaining to how investors perceive and evaluate a large number of strategic moves carried out by a firm is supportive of those from prior research--i.e., more competitive moves are associated with higher profitability (Young et al., 1996) and market share gains (Ferrier el al., 1999). Further, results for the relationship between action repertoire volume and short interest are also in line with some prior studies in competitive dynamics that have found U-shaped or inverted U-shaped relationships between several action-based characteristics of a firm's competitive strategy and performance. For instance, strategic complexity exhibited a U-shaped relationship with stock price (Ferrier and Lee, 2002) and market share gain (Ferrier, 2001). However, these studies examined the relationship between competitive strategy and performance at the competitive attack level of analysis--i.e., an uninterrupted sequence of competitive actions unconstrained by time markers--whereas analysis centered on the firm's competitive actions carried out in a specified time period. Clearly, this study, along with earlier work, suggests that more research is needed to help reach consistency and convergence in the competitive action-performance relationship.
Relationships between action repertoire complexity and either of the chosen stock market outcomes were not significant. Given the strong and robust findings from prior research about the relationship between strategic complexity (or simplicity) and performance (Smith et al., 2001), this lack of findings is puzzling. In an effort to flesh out a more nuanced relationship, post hoc analysis was conducted to explore the possibility of a non-linear relationship between strategic complexity and both cumulative abnormal returns and short interest. Like the main results, post hoc analysis did not yield significant results. At one level, these non-findings suggest that investors are indifferent about the firm's level of strategic repertoire complexity: long-buyers do not value strategic simplicity as an ambiguity-diminishing device in their sense-making and valuation process, and short-sellers seem not to value strategic complexity as a disequilibrative, strategic supremacy-enhancing characteristic of the firm's strategy. Future research could fruitfully explore, for instance, how the relationship between competitive repertoire complexity and stock market outcomes may be moderated by a variety of organizational factors (Ferrier and Lyon, 2004; Uhlenbruck el al., 2016) and contextual factors (Rindova et al., 2010).
Findings that relate to whether long-buyers regard between-firm differences in the pattern of competitive actions the firm carries out over time (i.e., action repertoire nonconformity) are generally supportive of Miller and Chen (1994) who posited that distinctive processes such as heterogeneous strategies may do more harm than good by decreasing the "legitimacy" of the firm. Instead, long-buyers likely use the recognition heuristic and assign increasingly higher value to familiarity (i.e., action repertoire conformity) and tends to reward firms whose strategies closely adhere to the industry norm.
In contrast, short-sellers--undertaking a more systematic evaluation of the strategy at hand--subscribe to Porter's (1980) view that heterogeneous competitive repertoires confuse rivals and create value by catching them off guard. So, as the strategy becomes increasingly different from that of referent others, short-sellers appear to believe the firm continues to leverage its competitive advantage through differentiation. Consequently, short sellers are less likely to short firms that boldly differentiate themselves.
Within the field of competitive dynamics, competitive actions are seen as a major factor that contributes to the performance differentials across companies (Bettis and Weeks, 1987; Smith et al., 2001). Thus, integration of financial theories that prescribe how this area of strategy contributes to firm value is a logical step in answering the call set forth by Bettis (1983: 414):
"... there is a need for strategic management researchers to establish closer working relationships with finance scholars...ultimately such cross communication is essential, or else practitioners will be forced to select among contradictory paradigms--a most undesirable circumstance."
Competitive dynamics in strategy research maintains that to understand the outcomes of competition, one must examine and evaluate the stream of competitive actions of companies (a strategic repertoire), and how this repertoire will affect the future value of the firm. While the field of competitive dynamics has yielded noteworthy results, many important questions remain unanswered, particularly with respect to Bettis' (1983) call.
Recognizing that "human behavior is bewilderingly complex and heterogeneous" (Preuschoff et al., 2005: 2), scholars can perhaps come to a better understanding of how human differences affect the decision-making processes that lead to different evaluations of the competitive interaction among rival firms. Undoubtedly, both categories of investors included in this study--long-buyers and short-sellers--are ultimately concerned with firm-specific investments, strategies, and tactics that are effective versus ineffective, imitable versus inimitable, routine versus deviant. Yet, such analysis requires well-developed information-scanning and interpretive capabilities that help investors to know where to look, what to look for, and how to ascribe meaning to the patterns of events they see. In the absence of the motivation to scan for and scrutinize all available information, some investors are likely to apply certain decision-making heuristics that best allow them to confidently make a decision about the future value-generating capability of a firm's chosen strategies. In fact, Goedhart et al. (2006) indicated that some investors do indeed resort to alternative mechanisms in evaluating stocks, rather than fastidiously evaluating corporate fundamentals and organizational assets that have future value-creating potential (or lack thereof) for the corporation's equity shares, especially in the short term. The authors agree that relative to longbuyers, short-sellers seek out and react to alternative factors; i.e., competitive behavior.
Andrevski, G., and W. J. Ferrier. 2016. "Does it Pay to Compete Aggressively? Contingent Roles of Internal and External Resources." Journal of Management 0149206316673718.
Barber, B. M., and T. Odean. 2005. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors." EFA 2005 Moscow Meetings paper. Available at SSRN: http://ssrn.com/abstract=460660.
Bettis, R. A. 1983. "Modern Financial Theory, Corporate Strategy and Public Policy: Three Conundrums." Academy of Management Review 8(3): 406-415.
Bettis, R. A., and D. Weeks. 1987. "Financial Returns and Strategic Interaction: The Case of Instant Photography." Strategic Management Journal 8(6): 549-563.
Boehmer, E., Z. Huszar, and B. Jordan. 2010. "The Good News in Short Interest." Journal of Financial Economics 96(1): 80-97.
Bogner, W. C., and P. Barr. 2000. "Making Sense in Hypercompetitive Environments: A Cognitive Explanation for the Persistence of High Velocity Competition." Organization Science 11(2): 212-226.
Bornstein, R. F. 1989. "Exposure and Affect: Overview and Meta-Analysis of Research, 1968-1987." Psychological Bulletin 106(2): 265-289.
Brockmann, E., and W. Anthony. 1998. "The Influence of Tacit Knowledge and Collective Mind on Strategic Planning." Journal of Managerial Issues 10(2): 204-222.
Chaiken, S., and A. Eagly. 1983. "Communication Modality as a Determinant of Persuasion: The Role of Communicator Salience." Journal of Personality and Social Psychology 45(2): 241-256.
Chaiken, S., and A. Eagly. 1976. "Communication Modality as a Determinant of Message Persuasiveness and Message Comprehensibility." Journal of Personality and Social Psychology 34(4): 605-614.
Chaiken, S., R. Giner-Sorolla, and S. Chen. 1996. "Beyond Accuracy: Defense and Impression Motives in Heuristic and Systematic Information Processing." In The Psychology of Action: Linking Cognition and Motivation to Behavior. Ed. P. Gollwitzer andj. Bargh. pp. 553-578. New York: Guilford.
Chakravarthy, B. S. 1986. "Measuring Strategic Performance." Strategic Management Journal 7(5): 437-458.
Chen, M., and I. MacMillan. 1992. "Nonresponse and Delayed Response to Competitive Moves: The Roles of Competitor Dependence and Action Irreversibility." Academy of Management Journal 35(3): 539-570.
Chen, M. J., and D. Miller. 2015. "Reconceptualizing Competitive Dynamics: A Multidimensional Framework." Strategic Management Journal 36(5): 758-775.
Chen, M. J., K. Smith, and C. Grimm. 1992. "Action Characteristics as Predictors of Competitive Responses." Management Science 38(3): 439-455.
Chen, M. J., K. Su, and W. Tsai. 2007. "Competitive Tension: The Awareness-Motivation-Capability Perspective." Academy of Management Journal 50(1): 101-118.
Connelly, B., L. Tihanyi, D. Ketchen, C. Carnes, and W. Ferrier. 2016. "Competitive Repertoire Complexity: Governance Antecedents and Performance Outcomes." Strategic Management Journal 38(5): 1151-1173.
D'Aveni, R. A. 1999. "Strategic Supremacy through Disruption and Dominance." MIT Sloan Management Review 40(3): 127-135.
D'Aveni, R. A. 1994. Hypercompetition. New York, NY: The Free Press.
de Roon, F., and M. Szymanowska. 2012. "Asset Pricing Restrictions on Predictability: Frictions Matter." Management Science 58(10): 1916-1932.
Dechow, P. M., A. Hutton, L. Meulbroek, and R. Sloan. 2001. "Short-Sellers, Fundamental Analysis and Stock Returns "Journal of Financial Economics 61(1): 77106.
Deephouse, D. L. 1999. "To be Different, or to Be the Same? It's a Question (and Theory) of Strategic Balance." Strategic Management Journal 20(2): 147-166.
Denzin, N. K., and Y. Lincoln. 2000. "Introduction: The Discipline and Practice of Qualitative Research." In Handbook of Qualitative Research. Eds. N. K. Denzin and Y. S. Lincoln, pp. 1-28. London, UK: Sage Publishing.
Derfus, P. J., P. Maggitti, C. Grimm, and K. Smith. 2008. "The Red Queen Effect: Competitive Action and Performance." Academy of Management Journal 51(1): 61-80.
Diamond, D. W., and R. Verrecchia. 1987. "Constraints on Short Selling and Asset Price Adjustment to Private Information. "Journal of Financial Economics 18(2): 277-311.
Drake, M. S., L. Rees, and E. Swanson. 2011. "Should Investors Follow the Prophets or the Bears? Evidence on the Use of Public Information by Analysts and Short-Sellers." Accounting Review 86(1): 110-130.
Eagly, A. H. 1974. "Comprehensibility of Persuasive Arguments as a Determinant of Opinion Change." Journal of Personality and Social Psychology 29(6): 758-773.
Factiva. 2017. Available at www.dowjones.com/factiva/index.asp (subscription required).
Fama, E. F. 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work." Journal of Finance 25(2): 383-417.
Ferrier, W., C. MacFhionnlaoich, K. Smith, and C. Grimm. 2002. "The Impact of Performance Distress on Aggressive Competitive Behavior: A Reconciliation of Competing Views." Managerial and Decision Economics 23: 301-316.
Ferrier, W. J. 2001. "Navigating the Competitive Landscape: The Drivers and Consequences of Competitive Aggressiveness." Academy of Management Journal 44(4): 858-877.
Ferrier, W. J., and H. Lee. 2002. "Strategic Aggressiveness, Variation, and Surprise: How the Sequential Pattern of Competitive Rivalry Influences Stock Market Returns." Journal of Managerial Issues 14(2): 162-180.
Ferrier, W. J., and D. W. Lyon. 2004. "Competitive Repertoire Simplicity and Firm Performance: The Moderating Role of Top Management Team Heterogeneity." Managerial and Decision Economics 25(6-7): 317-327.
Ferrier, W. J., K. Smith, and C. Grimm. 1999. "The Role of Competitive Action in Market Share Erosion and Industry Dethronement: A Study of Industry Leaders and Challengers." Academy of Management Journal 42(4): 372-388.
Festinger, L. 1951. "Architecture and Group Membership." Journal of Social Issues 7: 152-63.
Gilliland, A. R., and H. Moore. 1924. "The Immediate and Long Range Effects of Classical and Popular Phonograph Selections." Journal of Applied Psychology 8(3): 309-323.
Gnyawali, D., J. He, and R. Madhavan. 2006. "Impact of Co-operation on Firm Competitive Behavior: An Empirical Examination." Journal of Management 32(4): 507-530.
Goedhart, M., B. Jiang, and T. Roller. 2006. "The Irrational Component of your Stock Price." McKinsey Quarterly July.
Grullon, G., G. Kanatas, and J. Weston. 2004. "Advertising, Breadth of Ownership, and Liquidity." Review of Financial Studies 17(2): 439-461.
Henderson, V. 2012. "Prospect Theory, Liquidation, and the Disposition Effect." Management Science 58(2): 445-460.
Hirshleifer, D. 2001. "Investor Psychology and Asset Pricing." Journal of Finance 56(4): 1533-1597.
Hirshleifer, D., S. Teoh, and J. Yu. 2011. "Short Arbitrage, Return Asymmetry, and the Accrual Anomaly." Review of Financial Studies 24(7): 2429-2461.
Huff, L. C., and W. Robinson. 1994. "The Impact of Leadtime and Years of Competitive Rivalry on Pioneer Market Share Advantages." Management Science 40(10): 13701377.
Hughes-Morgan, M., and W. Ferrier. 2014. "Competitive Action Repertoires and Stock Risk ."Journal of Managerial Issues 26(1): 55.
Hughes-Morgan, M., and W. J. Ferrier. 2016. "Short Interest Pressure and Competitive Behaviour." British Journal of Management 28: 120-134.
Jacobson, R. 1992. "The "Austrian" School of Strategy." Academy Management Review 17(4): 782-807.
Jacoby, L. L., and L. Brooks. 1984. "Nonanalytic Cognition: Memory, Perception and Concept Learning." In The Psychology of Learning and Motivation. Ed. G.H. Bower, pp. 1-47. Orlando, FL: Academic Press.
Maslow, A. H. 1937. "The Influence of Familiarization on Preference." Journal of Experimental Psychology 21: 162-180.
McWilliams, A., and D. Siegel. 1997. "Event Studies in Management Research: Theoretical and Empirical Issues." Academy of Management Journal 40(3): 626-657.
Meyer, M. 1903. "Experimental Studies in the Psychology of Music." American Journal Psychology 14(3/4): 192-214.
Miller, D., and M. Chen. 1996. "The Simplicity of Competitive Repertoires: An Empirical Analysis." Strategic Management Journal 17(6): 419-439.
Miller, D., and M. Chen. 1994. "Sources and Consequences of Competitive Inertia: A Study of the U.S. Airline Industry." Administrative Science Quarterly 39(1): 1-23.
Mosakowski, E. 1997. "Strategy Making Under Causal Ambiguity: Conceptual Issues and Empirical Evidence." Organization Science 8(4): 414-442.
Newcomb, T. M. 1963. "Stabilities Underlying Changes in Interpersonal Attraction." Journal of Abnormal Social Psychology 66: 376-86.
Newell, A., and H. Simon. 1972. Human Problem Solving. Englewood Cliffs, NJ: Prentice-Hall.
Pollock, T. G., and P. Rindova. 2003. "Media Legitimation Effects in the Market for Initial Public Offerings." Academy of Management Journal 46(5): 631-642.
Porter, M. E. 1985. Competitive Advantage. New York, NY: The Free Press.
Porter, M. E. 1980. Competitive Strategy: Techniques for Analyzing Industries and Competitors. New York, NY: The Free Press.
Preuschoff, K., S. Quartz, and P. Bossaerts. 2005. "Markowitz on the Brain? Computational and Neural Systems." Unpublished discussion paper, California Institute of Technology.
Rindova, V., W. Ferrier, and R. Wiltbank. 2010. "Value from Gestalt: How Sequences of Competitive Actions Create Advantage for Firms in Nascent Markets." Strategic Management Journal 31(13): 1474-1497.
Rindova, V. P., A. Petkova, and S. Kotha. 2007. "Standing Out: How New Firms in Emerging Markets Build Reputation." Strategic Organization 5(1): 31-70.
Rindova, V. P., I. Williamson, A. Petkova, and J. Sever. 2005. "Being Good or Being Known: An Empirical Examination of the Dimensions, Antecedents, and Consequences of Organizational Reputation." Academy of Management Journal 48(6): 1033-1049.
Sherif, M., C. Sherif, and R. Nebergall. 1965. Attitude and Attitude Change: The Social Judgment-Involvement Approach. Philadelphia, PA: W. B. Saunders.
Smith, K. G., and D. DiGregorio. 2002. "Bisociation, Discovery and the Role of Entrepreneurial Action." In Strategic Entrepreneurship: Creating a New Mindset. Eds. M. A. Hitt, R. D. Ireland, S. M. Camp, and D. L. Sexton, pp. 129-150. Hoboken, NJ: Wiley-Blackwell.
Smith, K. G., W. Ferrier, and H. Ndofor. 2001. "Competitive Dynamics Research: Critique and Future Directions." In Handbook of Strategic Management. Eds. M. A. Hitt, R. E. Freeman, and J. Harrison, pp. 315-361. London, UK: Blackwell Publishers.
Spender, J. C. 1989. Industry Recipes: An Inquiry into the Nature and Sources of Management Judgment. London, UK: Sage Publishing.
Tversky, A., and D. Kahneman. 1974. "Judgment under Uncertainty: Heuristics and Biases." Science 185(9): 1124-1131.
Uhlenbruck, K., M. Hughes-Morgan, M. Hitt, W. Ferrier, and R. Brymer. 2016. "Rivals' Reactions to Mergers and Acquisitions: A Competitive Dynamics Perspective." Strategic Organization, in press.
Weber, E., U. Siebenmorgen, and M. Weber. 2005. "Communicating Asset Risk: How the Format of Historic Volatility Information affects Risk Perception and Investment Decisions." Risk Analysis 25: 597-609.
Young, G., K. Smith, and C. Grimm. 1996. "Austrian and Industrial Organization Perspective on Firm-Level Competitive Activity and Performance." Organization Science 7(3): 243-254.
Zhang, Y., and J. Gimeno. 2010. "Earnings Pressure and Competitive Behavior: Evidence from the U.S. Electricity Industry ."Academy of Management Journal 53(4): 743-768.
Zuckerman, E. W. 2004. "Structural Incoherence and Stock Market Activity." American Sociological Review 69(3): 404-432.
Walter J. Ferrier
University of Kentucky
Fred W. Morgan
Wayne State University
Table 1 Descriptive Statistics and Correlations Control Mean Std. Dev. 1 2 1. Age 25.555 15.7177 2. Altman's Z 5.7034 26.8423 -0.044 ** 3. Size 2.3742 1.09964 0.149 ** 4. Capital Intensity 0.1769 0.13363 0.355 ** -0.153 ** Independent 5. Complexity 0.0493 0.15879 0.214 ** 0.008 6. Heterogeneity 0.0042 0.27566 0.077 ** 7. Volume 0.0887 0.47606 -0.034 ** Dependent 8. CARS 1.9842 35.3827 0.002 0.002 9. SIR 0.0086 0.02063 -0.051 ** 0.033 Control 3 4 5 1. Age 2. Altman's Z 3. Size 4. Capital Intensity 0.124 ** Independent 5. Complexity 0.271 ** 0.056 ** 6. Heterogeneity 0.110 ** 0.042 ** 0.399 ** 7. Volume 0.074 ** 0.060 ** 0.009 Dependent 8. CARS -0.004 0.026 -0.004 9. SIR -0.015 ** -0.097 ** -0.019 Control 6 7 8 1. Age 2. Altman's Z 3. Size 4. Capital Intensity Independent 5. Complexity 6. Heterogeneity 7. Volume 0.052 ** Dependent 8. CARS 0.003 -0.021 9. SIR 0.005 -0.008 0.016 * p < 0.05 ** p < 0.01 Table 2 Fixed Effect Regression of Stock Returns and Short Interest on Competitive Strategy Cumulative Abnormal Returns Model 1 Model 2 Model 3 Intercept -1.7882 0.6310 -0.5330 Firm Age 0.2618 ** 0.1689 * 0.2243 ** Altman's Z -0.1104 0.1252 0.0363 Firm Size -3.3890 ** 1.0125 -2.4320 Optioned Stock Capital Intensity -26.8978 * -3.6253 ** -37.082 ** Action Repertoire 3.3825 ** Volume (linear) Action Repertoire Volume (squared) Action Repertoire 4.4561 Complexity Action Repertoire -8.7790 ** Non-Conformity -2 Log Likelihood 2872.7 3898.9 2899.3 Model Significance p<0.001 p<0.001 p<0.001 Short Interest Ratio Model 4 Model 5 Model 6 Intercept 0.0090 *** 0.0128 ** 0.0159 Firm Age 0.0003 0.0009 -0.0002 * Altman's Z -0.0004 *** -0.0004 *** -0.0001 Firm Size -0.0018 -0.0028 -0.0034 Optioned Stock 0.0050 ** 0.0108 ** 0.0147 Capital Intensity 0 .0082 0.0062 * 0.0068 Action Repertoire -0.0008 ** Volume (linear) Action Repertoire 0.0003 ** Volume (squared) Action Repertoire -0.0007 Complexity Action Repertoire -0.0019 * Non-Conformity -2 Log Likelihood 3389.7 4625.2 3471.4 Model Significance p<0.001 p<0.001 p<0.001 * p < 0.05 ** p < 0.01 *** p < 0.001
|Printer friendly Cite/link Email Feedback|
|Author:||Hughes-Morgan, Margaret; Ferrier, Walter J.; Morgan, Fred W.|
|Publication:||Journal of Managerial Issues|
|Date:||Mar 22, 2018|
|Previous Article:||Buying to be Socially Responsible: Emerging Market Multinational Corporations' Cross-border Acquisitions and Corporate Social Performance.|
|Next Article:||The Generation for Change: Millennial, Their Career Orientation, and Role Innovation.|