Competitive Dynamics in Strategic Management
Competitive Dynamics in Strategic Management
- Claudio GiachettiClaudio GiachettiDepartment of Management, Ca' Foscari University of Venice
- and Giovanni Battista DagninoGiovanni Battista DagninoDepartment of Law, Palermo Campus, LUMSA
Competitive dynamics inquiry originates from a sequence of attacks and counterattacks among firms in an industry. Firms attack and respond to attacks of rivals in order to strengthen or defend their competitive position within their competitive space. Competitive dynamics research is thus centered on the analysis of how the firm’s actions affect rivals’ reactions and performance. Actually, the nature of competitive dynamics research is the open recognition that firm strategies are “dynamic”: Strategic actions initiated by one firm may trigger a series of actions among rival firms. The new competitive environment in many industries has generated the inception of furious competition, emphasizing flexibility, speed, and innovation in response to fast-changing technological and institutional conditions and temporary competitive advantages.
The key constructs and the intellectual roots of competitive dynamics (i.e., Schumpeter’s theory of creative destruction and industrial organization economics and related oligopoly theories) offer some practical examples of industry and firm cases where competitive dynamics have found their main applications.
The relevant underpinnings of the awareness–motivation–capability (AMC) framework provide an integrative model of the key behavioral drivers that shape a competitive actions and responses framework (i.e., the factors influencing the firm’s awareness of the context; the factors inducing or impeding the motivation of firms to respond to competitors’ action; and the capability-based factors affecting the firm’s ability to undertake actions), the three key attributes (i.e., the specific actions of firms in the industry, the firm’s competitive interdependence, and the antecedents and performance implications of firms’ competitive actions and reactions), and the three main levels of analysis used in competitive dynamics literature (i.e., action-level studies, business-level studies, and corporate-level studies).
Some insights regarding the relationship between dynamic competition and the sources of temporary competitive advantage, coopetition dynamics, as well as the kind of accelerated competition epitomizing early 21st-century digital dynamics settings update the traditional competitive dynamics flavor, as they are connected with firms’ strategic interaction and the pursuit of temporary advantages.
- Business Policy and Strategy
Competitive Dynamics: Key Constructs and Examples
Competitive dynamics emanate from a sequence of attacks and counterattacks among firms in an industry. Firms attack and respond to attacks of rivals in order to strengthen or defend their competitive position within their competitive arena (MacMillan et al., 1985). Successful actions, namely those attacks that help the focal firm to increase its performance vis-à-vis rivals, trigger a reaction by rivals, which may attempt to obstruct or emulate the focal firm’s actions and in turn affect the latter’s attempt to sustain its competitive advantage. Competitive dynamics research is centered on the analysis of how the firm’s actions affect rivals’ reactions and performance (Chen & Miller, 2012, 2015; Smith et al., 2006).
As the phrase “competitive dynamics” states, the essence of competitive dynamics research is an explicit recognition that firm strategies are “dynamic”: Strategic actions initiated by one firm may trigger a series of actions among (a number of) rival firms. The new competitive environment epitomizing many industries, as described by some authors (Bettis & Hitt, 1995; Thomas & D’Aveni, 2009), has given rise to vicious competition, emphasizing flexibility, speed, and innovation in response to fast-changing technological and institutional conditions and temporary competitive advantages (D’Aveni et al., 2010). Authors have used the term “hypercompetition” (D’Aveni, 1994) precisely to describe the rapidly changing conditions that can be observed in many industries. Since the beginning of the 1990s, three factors have contributed to accelerate the pace of market evolution and to trigger competitive warfare in many industries: (a) the globalization process and the related boost to foreign markets competition, (b) the wave of deregulation that has spread out in both developed, transitioning, and developing countries in the form of pro-market reforms and liberalization, and (c) radical changes in technology, especially driven by the diffusion of digital technologies, biomedical machinery, and the internet.
Authors have examined competitive dynamics in various industries, from commodities to technology-based products. In fact, competitive actions and reactions can be of different types, from price wars to comparative advertising, from retail chain geographical expansion to change in retail formats, from new product introduction to product imitations, from market entry to market exit. An action is a specific and detectable market move initiated by a firm, while a response is a specific and datable countermove that a firm takes to defend or improve its performance in its industry (Chen & Miller, 2012). An example of competitive dynamics is the clash between Coca-Cola (Coke) and Pepsi-Cola (Pepsi) that various authors started analyzing since the early 1990s (D’Aveni, 1994; Fosfuri & Giarratana, 2008; Ghemawat, 1991). The two U.S. multinational beverage companies began to aggressively compete against each other at the beginning of the last century. Although Coke dominated the soft drink market with a wide market share gap vis-à-vis Pepsi, the latter decided to challenge Coke’s market power during the 1930s and 1940s by initiating a series of aggressive price cuts of all its cola drinks. Coke, probably underestimating Pepsi’s potential counterattack strategy, did not immediately respond with a price reduction, and given the similarity of the two “commodity” products, this resulted in a situation where Pepsi was able to reduce its market share gap relative to Coke. To keep up its momentum, in the 1950s, Pepsi added to its competitive action repertoire a set of aggressive investment campaigns in advertising. Low price and massive advertising helped Pepsi to continue gaining share, but also damaged its profitability. In the 1960s, both soft drink vendors increased the number of drinks in their product portfolio, a strategic action aimed at reaching the rapidly growing market made of increasingly heterogeneous consumer segments. At the beginning of the 1970s, Pepsi began to attack Coke with a series of comparative advertising campaigns aimed at signaling to consumers Pepsi’s different, sweeter taste. Coke, aware that its brand image was not enough to block Pepsi’s growth path, this time responded by reducing prices of its cola drinks. Then Pepsi counterresponded by changing its advertising strategy, showing celebrity endorsements in its commercials, one of the most effective strategic decisions that helped the firm to finally dethrone Coke temporarily from its market share leadership. Due to the new Pepsi market leadership in the mid-1980s, Coke decided to introduce a new cola, which it called “New Coke,” with a new flavor formula that tasted similar to the sweeter Pepsi drink, and also decided to withdraw the original Coke flavor. The result was a total failure because this action signaled a change in the original Coke’s timeless flavor. Coke then decided to strategically retreat by reintroducing Coke’s original formula, rebranded as “Coca-Cola Classic,” and this competitive reaction resulted in a significant gain in sales so that Coke regained its market share leadership in many countries. The battle between Coke and Pepsi has been characterized by rapid and continuous attacks and counterattacks between the two soft drink vendors. Every time a competitive action was undertaken, it was followed by the rival’s countermove, with an effect on both firms’ performances.
Another interesting example of competitive dynamics is the incessant head-to-head rivalry to get or to keep ahead of one another in the mobile phone industry. In fact, as observed by some authors, mobile phone vendors have always struggled to imitate each other’s product innovations in a race to maintain competitive parity of their new phones (Giachetti et al., 2017). Focal mobile phone vendors that successfully adopt new product technologies before rivals obtain first-mover advantages (e.g., sales increases). The higher performance of these first movers, combined with performance losses experienced by rivals, motivate rivals to respond by imitating as quickly as possible successful technologies introduced by first movers. The more intense and rapid the rivals’ imitative response, the more the focal mobile phone vendor experiences a threat to its performance, and the more it feels pressure to respond by launching new product technologies or by imitating those introduced by competitors. The result is that when handset vendors learn that the competitive advantage of a new line of phones is temporary, they undertake competitive actions in response to competition, thereby intensifying the level of competition further. This intensification triggers further competitive actions, which foster still stronger competition, and so on. For example, Nokia’s pioneering of most digital technologies for mobile phones, such as infrared, games, email client, and wireless application protocol (WAP) during the 1990s, elicited various reactions from rivals. Siemens was among the first ones to install the latest generations’ technologies in its devices. This strategic move reinforced Siemens’ product portfolio competitiveness and increased its sales performance relative to slower adopters, such as NEC, Philips, and Sagem. Still, these competitive actions helped Siemens to enjoy only a temporary competitive advantage until Nokia’s innovations were adopted by other handset vendors. The challenge to rapidly adopt new product technologies occurred once more at the beginning of the 2000s when some handset vendors pioneered other product technologies such as Bluetooth, MMS, and photo camera. But this time companies like Sony-Ericsson and Samsung were able to install this set of features in their new lines of phones more quickly than Siemens. Although in the first time period (i.e., during the 1990s decade) Siemens was able to adopt quickly the latest generation technologies and, in turn, enjoyed a temporary competitive advantage, in the second time period (i.e., the beginning of the 2000s), it did not possess the resources and capabilities required to adopt the newly introduced technologies earlier than its key rivals and soon it had to abandon the field, thereby withdrawing its mobile phone business from most countries. Interestingly, the escalating pressure to be aligned with competitors as concerns the newly introduced product technologies not only increased rivalry among mobile phone vendors, but also accelerated the technological evolution of the industry. In fact, since the first digital mobile phone introduced at the beginning of the 1990s, in a few years the industry moved away from basic portable devices capable of providing merely phone calls to highly convergent multitasking devices that integrate nearly all types of nonvoice functionality.
Competitive Dynamics, Intellectual Roots, and Initial Evolution
Schumpeter’s Theory of Creative Destruction
The importance of competitive dynamics was first emphasized by the Austrian-born economist Joseph Schumpeter (1934, 1950). Schumpeter pioneered the theorizing about how competitive dynamics affect not only firm and industry performance, but also the economy as a whole. During the late 1930s, Schumpeter developed the concept of “creative destruction” to explain the dynamic market process by which firms act upon and react to one another in the pursuit of market opportunities. According to Schumpeter, new products and processes introduced by innovative firms are “creative” because they are able to bring new solutions to consumers and the economy as a whole. Nonetheless, they are also “disruptive” as they make obsolete the previous products and technologies performing similar functions, thereby threatening the survival of firms that relied on them. In fact, creative destruction was defined as the inevitable decline of firms through the process of competitive action and reaction. Firms act and rivals respond, and these actions and reactions determine eventually their survival and long-term performance (Chen & Miller, 2012).
Schumpeter’s framework was based on the idea that market share and profit gains obtained by an innovative entrepreneur that introduced a new successful product, service, or product process will motivate other firms to undertake new competitive actions in an attempt to catch up to the pioneer entrepreneur’s initial advantage (i.e., try to gain competitive parity). The outcome of this market process is inevitable market share and profit erosion experienced by innovative entrepreneurs over time through the process of competition (Schumpeter, 1934, 1950). Schumpeter emphasized that as a result of this creative destruction process, no market leadership is safe or sustainable. The empirical test of Schumpeter’s idea concerning the condition that, over time, the creative actions of challengers threaten the stability of the innovative firm position, thereby determining its dethronement, was in fact one of the goals of the first wave of competitive dynamics studies (e.g., Ferrier et al., 1999).
Industrial Organization and Oligopoly Theories
Although Schumpeter’s creative destruction is the key intellectual root of competitive dynamics studies, most of the studies that emphasize competitive dynamics find their roots also (a) in industrial organizational economics (Caves & Porter, 1977; Porter, 1979, 1980) because they examine how firms can sustain their competitive advantage by means of competitive actions and reactions within an industry, and (b) in oligopoly theories (Edwards, 1955; Knickerbocker, 1973) as they examine how interfirm rivalry can be mitigated by strategic actions that deter rivalry, eventually leading to collusive behaviors. For example, studies about multimarket competition, that is, the situations in which firms compete simultaneously against the same rivals in more than one market (Karnani & Wernerfelt, 1985), trace their primary theoretical origin to Edwards’ (1955) studies on oligopolistic competition. In multimarket competition, firms that meet each other in multiple markets are likely to show lower rivalry because they realize that their strategic interdependence increases the risk of starting a dangerous warfare in all markets they have in common, a situation commonly known as “mutual forbearance” (Ma, 1998; Yu et al., 2009). In their seminal work, Bernheim and Whinston (1990) offered one of the initial formal treatments of multimarket contact and tacit collusion. Subsequently, competitive dynamics studies have drawn on industrial organizations’ oligopoly theories to examine the firms’ propensity to undertake competitive actions and reactions (and performance consequences) when they encounter rivals in multiple markets (e.g., Baum & Korn, 1996; Gimeno & Woo, 1996; Yu et al., 2009).
Initial Evolution of the Field
The initial empirical studies on competitive dynamics appeared in the mid-1980s with the analysis of MacMillan et al. (1985) on the response times of competitors to easily imitate new products in the banking industry. A couple of years later, Bettis and Weeks (1987) published a study on stock market reactions to product moves and countermoves in the instant photography industry, and Smith et al. (1989) followed up with a research piece identifying the characteristics of competitive actions triggering rapid countermoves in technology-intensive industries.
Over the 1990s, various articles were published on the drivers and performance implications of competitive actions and reactions using as an empirical setting mainly the U.S. airlines industry (e.g., Chen & Hambrick, 1995; Chen & MacMillan, 1992; Chen & Miller, 1994; Chen et al., 1992; Smith et al., 1991, 1992).
In the next sections, the evolution of the field of competitive dynamics in the past three decades (since the 1990s) is described by regrouping the key papers published according to their key methodological and theoretical characteristics.
The Awareness–Motivation–Capability (AMC) Framework
Competitive dynamics examines the interactions between and among competitors, focusing not only on actions but also on the responses elicited. Authors have noted that in order to predict competitive responses, it is essential to understand how a competitive action affects the internal behavior of the defending organization (Chen & Miller, 1994). In fact, the firm will respond to the rivals’ attacks only if it is aware of the attacks. This means that competitive actions have to generate clear signals that are visible to the firm (Chen et al., 1992; Smith & Grimm, 1991). Moreover, the motivation that actors have to attack or respond to rivals’ actions depends on the potential performance gains or losses from the contested product (Ferrier, 2001). Finally, the decision to attack or to defend depends on the firms’ capabilities to do so (Smith et al., 1991). More specifically, there are three organizational characteristics that influence strategic actions: (a) factors that influence the awareness of the context and signal threats or opportunities for focal firms; (b) factors that induce or impede the motivation of firms to respond to competitors’ actions; and (c) the capability-based factors that affect the firm’s ability to undertake actions (Chen, 1996; Smith et al., 2006).
The awareness–motivation–capability (AMC) framework provides an integrative model of the three key behavioral drivers that shape a competitive action and response framework (Chen, 1996; Grimm et al., 2006; Smith et al., 2001; Yu & Cannella, 2007).
Individual AMC components are manifested in a range of variables. For example, awareness about rivals’ actions has been measured with rivals’ size (e.g., revenues or market share) or the visibility of rivals’ actions (given by their appearance in business-oriented magazines), where larger size or action visibility results in greater awareness (Chen & Hambrick, 1995). Motivation to attack a rival was measured by the extent to which a focal firm meets its rivals in multiple markets (Gimeno & Woo, 1996), where higher multimarket contact results in mutual forbearance and less motivation to trigger warfare. The capability to attack rivals was measured with organizational slack (i.e., the resources available to the firm above the resources necessary to achieve immediate business and operational requirements), where a higher slack resource level results in a greater capability to attack (Smith et al., 1991).
The AMC framework has been used to examine interfirm rivalry in several industries (see Chen & Miller, 2012, for a comprehensive review). For example, authors have noted that the AMC framework is useful to understand the drivers of international market entry. In their analysis of patent wars and international market entry in the global mobile phone industry, Onoz and Giachetti (2021) have shown that to understand how and if a firm will respond to a patent litigation risk in a target country, it is necessary to concurrently assess if the firm is aware of this risk, if it is motivated to react to this risk, and if it is able to respond to this risk. A firm’s awareness of the threats and opportunities related to patent wars in a country was conceptualized in terms of the firm’s previous experience with patent infringement lawsuits. A firm’s motivation to enter a country was conceptualized in terms of the share of a firm’s current patent applications in a target country. Finally, the size of a firm’s patent stock was used to capture a firm’s ability to navigate patent infringement lawsuits in a specific country, a resource endowment protecting the firm from plaintiffs in the host country.
Key Attributes of Competitive Dynamics Studies
Literature review studies (e.g., Chen & Miller, 2012; Smith et al., 2006) suggest three key attributes of competitive dynamics research. First, competitive dynamics studies are centered on the specific actions of firms in the industry. Each action occurs at a particular moment in time and in a particular business environment (e.g., country, industry). For example, a firm can introduce a new product technology, enter a new market, lessen the price of one of its products, or launch a new advertising campaign with the aim of increasing its performance vis-à-vis rivals. Accordingly, overall, the field of competitive dynamics offers a detailed approach aimed at understanding what a particular firm, such as Pepsi, does when it competes with specific rivals, such as Coke, and how this action–reaction process shapes firms’ and rivals’ performances.
Second, competitive dynamics research examines the firms’ competitive interdependence, which is a firm’s performance as a function of the actions of the firm and the responses of its rivals. In this vein, competition is considered to be “dynamic” and “interactive,” and action and response dyads and repertoires of actions constitute the building blocks of competition. Competitive dynamics studies thus focus directly on interfirm rivalry, an aspect widely discussed in all models of competitive advantage.
Third, competitive dynamics research has focused on the analysis of the antecedents and performance implications of competitive actions and reactions. The analysis of antecedents is important in understanding what motivates a firm to attack or to respond to rivals. The analysis of performance outcomes is important to understand which competitive actions have a greater impact on firm performance.
Levels of Analysis in Competitive Dynamics
Action-Level Studies: Action–Response Dyads
An influential stream of studies in the competitive dynamics literature has taken the exchange of individual competitive actions and responses as the level of analysis and has elaborated on a number of hypotheses as the drivers of competitive responses (Baum & Korn, 1999; Chen & Miller, 1994; Lee et al., 2000; Smith et al., 1992, 2001).
For example, Chen and Miller (1994), by relying on a sample of competitive action and response dyads in the U.S. airline industry, examined how competitive attacks can best reduce the chances of retaliation. Results of this study show that undetectable attacks would provoke fewer responses than more visible and more easily imitated moves. In their action-level study, Lee et al. (2000) examined the effects of timing, order of strategic moves, and the durability of first-mover advantages by analyzing the stock market reactions to new product introductions and imitations in various industries. The authors found that both timing and order of strategic moves are important features and that rivals’ reactions usually undermine the durability of first-mover advantages.
Business-Level Studies: Action Repertoire
Another stream of competitive dynamics studies focuses on the firm or business level, thereby looking at the whole set of competitive actions undertaken by a firm over a given time period (usually 1 year) and examining the antecedents and performance outcomes of this action repertoire. Firm-level data used in this stream are inferred by examining a wide variety of competitive moves that firms take in engaging with their rivals over time.
For instance, Chen and Hambrick (1995) examined how small firms differ in their competitive behaviors from their large rivals in the U.S. domestic airline industry and explored the implications of performance differences. The unit of analysis was the firms’ action and response behaviors in a given year. Per each of the 16 different action types, ranging from new product offerings, mergers, and new hub creations, to price cuts, new promotional campaigns, and joint advertising efforts, the average annual company scores were calculated for each of the seven action (propensity for action, action execution speed, action visibility) and response (responsiveness, response announcement speed, response execution speed, response visibility) attributes. The authors found that small firms differ descriptively from their larger counterparts in their competitive behaviors. For instance, small firms tend to be more active than large ones in initiating competitive moves.
Giachetti et al. (2017) built a model that captures how decisions to imitate new product technologies stimulate further imitation by rivals and how this “competitive imitation” in turn influences and is influenced by changing industry conditions. They argue that in this situation, managers face two basic issues when they consider imitation as the best next move. The first issue is how many product technologies to copy (i.e., “imitation scope”). The second issue is how quickly to imitate (i.e., “imitation speed”). Using data on the U.K. mobile phone industry extracted during the 1990s and 2000s, the authors show that the scope and speed decisions of one firm in a given year influence the scope and speed decisions of rivals in the subsequent year. Rivals’ imitation scope and speed decisions will then influence the firms’ subsequent scope and speed decisions as well as the focal firm’s performance. What emerges is an interesting coevolutionary process that results when firms learn to undertake competitive actions in response to competition, thereby intensifying the level of competition. This competitive intensification triggers further learning and competitive actions, which foster stronger competition, and so on. The more rapidly firms accumulate competitive experience, the faster they learn, and the more powerful they become. The peculiarity of this process is that firms are forced to compete if they want to retain their competitive position, but more intense competition will at best keep them in the same position (i.e., the so-called Red Queen effect).
Other authors (Ferrier, 2001; Ferrier & Lee, 2002), also adopting a repertoire approach, introduced the concept of “competitive aggressiveness,” defined as the extent to which a firm forcefully takes a large number and a large variety of actions to outperform its competitors. Aggressive firms, relative to conservative firms, are regarded as those that demonstrate greater “intensity” and greater “complexity” of strategic activity. Competitive dynamics theorists have defined “strategic intensity” as the firm’s capability to “carry out a large number of competitive actions in rapid succession” (Ferrier & Lee, 2002, p. 164), and “strategic complexity” as the “extent to which a sequence of actions is composed of actions of many different types” (Ferrier & Lee, 2002, p. 164). Based on a multiyear, multi-industry study of thousands of competitive actions, the authors found that a firm’s competitive aggressiveness is influenced by past performance, organizational slack, and top management team (TMT) heterogeneity, as well as industry characteristics such as growth and concentration.
Moreover, findings of competitive dynamics research show that action aggressiveness is positively related to firm profitability and market share (Chen & MacMillan, 1992; Chen et al., 2010; Ferrier, 2001; Ferrier et al., 1999; Giachetti, 2016; Young et al., 1996). Action aggressiveness has been shown to be beneficial to both market leaders and challengers. On the one hand, competitive dynamics scholars have shown that challengers forcefully taking a large number of competitive actions are more likely to catch up with market leaders. On the other hand, “leaders that carry out more competitive actions than challengers will have a lower rate of market share gap erosion” (Ferrier et al., 1999, p. 375). For example, Ferrier et al. (1999) and Smith et al. (2001) investigated the “dethronement” and market-share erosion of market leaders in approximately 40 industries over a 7-year period. They found that market leaders are more likely to be dethroned or at least to experience market share erosion when, compared to their challengers in the industry, they undertake fewer competitive actions, carry out actions of the same type instead of delving into their repertoire of heterogeneous competitive actions, and are slower in undertaking competitive actions.
Likewise, in their case study analysis of changes in industrial leadership in the global mobile phone industry, Giachetti and Marchi (2017) explained the way in which, at the end of the 1990s, Nokia leapfrogged over Motorola by showing that the Finnish vendor took an aggressive competitive posture during those years, mainly in three ways. First, to exploit the opportunities offered by the emerging digital standard for mobile phones earlier than its rivals and much earlier than the other mobile phone vendors, Nokia focused on the development of digital services and equipment so that it became the leading supplier for GSM cellular infrastructure in Europe. Second, much earlier than rivals, Nokia installed in its phones most of the revolutionary innovations based on the digital standard, such as SMS and games, thereby making its new line of portable phones more technologically advanced vis-à-vis those of its rivals. Third, it rapidly lengthened its product line with respect to the other handset vendors in order to offer digital phone customers a larger variety of product choices.
Corporate-Level Studies: Multimarket Competition
While action-level studies focus on the antecedents and performance outcomes of action–response dyads and firm-level studies examine antecedents and performance implications of actions repertoires, a third stream of studies in the competitive dynamics literature has examined how firms manage their competitive action and reactions when competing in multiple markets. These studies have mainly drawn on “multimarket competition,” arising from the field of oligopoly theories.
Since the second half of the 1990s, competitive dynamics research has contributed significantly to the extension of the theory of multimarket competition (e.g., Baum & Korn, 1999; Gimeno, 1999; Gimeno & Woo, 1996, 1999; Greve, 2008; Yu et al., 2009). Most of these studies have tested the mutual forbearance hypothesis (Edwards, 1955); that is, the idea that firms operating in the same markets will recognize their interdependence and, as a result, will undertake competitive actions in such a way as to minimize the risks of dangerous warfare.
One of the empirical settings competitive dynamics scholars used the most was the U.S. airline industry. When an airline company competes with another, the two are likely to encounter each other in a considerable number of markets (routes). The multiplicity of their contacts may blunt the edge of their competition. A prospect of advantage in one route from vigorous competition may be weighed against the danger of retaliatory forays by the competitor in other routes. Therefore, each airline may adopt a live-and-let-live strategic posture designed to stabilize rivals’ strategic interdependence.
In their dynamic analysis of California commuter airlines from 1979 through 1984, Baum and Korn (1996) found support for the mutual forbearance hypothesis by showing that (a) close competitors avoid engaging in intense rivalry, and (b) firms interacting in multiple markets are less aggressive toward each other than those that interact in one or in a few markets. Likewise, Yu et al. (2009), using a database of nearly 2,000 competitive actions by 13 automobile companies operating in 27 countries over a 7-year period, examined how the deterring influence of multimarket contact on the competitive aggressiveness of a multinational company’s subsidiaries is contingent upon the extent of subsidiary ownership, the cultural distance from the multinational’s home country, the latitude of local regulatory restrictions, and the presence of local competitors. They found all these factors to influence the multimarket contact-competitive aggressiveness relationship. In particular, higher subsidiary ownership enhances the rivalry, lessening the impact of multimarket contact on competitive aggressiveness, while cultural distance from the multinational’s home country, the latitude of local regulatory restrictions, and the presence of local competitors diminish it.
Dynamic Competition and Temporary Competitive Advantage
Competitive dynamics research is closely tied to the study of hypercompetition and temporary competitive advantage. Actually, in environments epitomized by dynamic competition, more than building a sustainable competitive advantage, firms must attempt to build a string or a concatenation of short-lived competitive advantages. This condition is due to the fact that firm-specific advantages are not sustainable over time (D’Aveni et al., 2010). Actually, in such environments, far from being enduring, a competitive advantage is ephemeral and fleeting. In fact, any advantage a firm generates will be inevitably eroded as a result of rivals’ reactions in an unremitting sequence of punctuations of advantages set by the firms’ actions and reactions, moves and countermoves (Chen et al., 2010).
There are three key characteristics of the temporary competitive advantages view vis-à-vis the more traditional sustainable competitive advantage view:
Performance variation is greater in this context (Chen et al., 2010).
Interfirm heterogeneity is “predominantly a study of experimentation and short-run failure, not long-term success” (Thomas & D’Aveni, 2009, p. 416).
Operational speed is paramount to deliver competitive responses; then success comes about when the competitor’s rates of response decline to zero.
Accordingly, some empirical studies have shown that performance volatility has greatly increased in the last half century (since the 1980s) in many country-specific contexts such as the United States (Thomas & D’Aveni, 2009; Wiggins & Ruefli, 2005). Therefore, recalling the Austrian school (Jacobson, 1992; Kirzner, 1997), the study of firm and industry performance heterogeneity, more than leaning toward post-Marshallian partial or sector equilibriums, turns into the study of a process that is termed “disequilibrium and transience” (Thomas & D’Aveni, 2009). In fact, the strategic capability to deploy operational speed enables the creation of events. The number of events in any given period of time that requires a competitive response (also termed “tempo” in warfare manuals; Rao, 2011) is a crucial indicator of operational speed. The higher the tempo, or the number of events in such a time period that require competitive response, the higher will be the delivery of shock and surprise. Shock and surprise in turn degrades and disrupts the competitors’ ability to respond to events, and success comes about when competitors’ rates of response decline (near or) to zero. This condition is epitomized by Spotify’s entry into the music streaming service market in the United Kingdom. Spotify made such steps forward because it was able to enter the music streaming market by innovating. First, it offered a music streaming service with an entry point through its free advertising-supported service. Then it managed to protect and nurture its market by further offering algorithmic data to personalize the user experience and social recommendations.1 Other music platforms, while “setting their price at £9.99, suggesting that the amount charged by Spotify has become a kind of ‘going rate’ for streaming services,” did not follow Spotify but preferred other ways to differentiate (such as exclusive offers from affiliated musicians) (Lilico & Sinclair, 2017, pp. 60–61).
In addition, rediscovering the prominence of firm actions and behaviors advocated by D’Aveni’s (1994) initial work, Chen et al. (2010) emphasized the role that top management teams (TMTs) can play in these dynamic advantage contexts. They show how TMT sociobehavioral integration (i.e., “how well senior executives of a firm work together, both socially and as a team” [Chen et al., 2010, p. 1413]) may be a positive component in accelerating firms’ competitive aggressiveness. It is exactly in hypercompetitive environments that TMTs may develop into an important element in fostering firms’ capacity to produce a series of competitive actions that generate a sequence of temporary advantages.
Evidence suggests that TMT integration is vital in subduing environmental noise, trimming down volatility, and balancing opposite views between managers so as they may take crucial moves vis-à-vis rivals, especially when the competitive advantage is short-termed and transitory. The executive teams building the perseverance and strength for such integration are the ones that are in fact able to spawn more frequent and intense competitive actions and, through these actions, to perform better than the others.
Digital Dynamics and Temporary Competitive Advantage
In the past decade, since the 2010s, the inception of the so-called digital turn of the economy and society, or the progressive “virtualization of the world” (Westera, 2012), accelerated severely by the global spread of the COVID-19 pandemic since 2020, is making individuals spend an increasing portion of their lives in digital spaces. As such, on one hand, it has become visible that digital transformation is a process that affects not only a segment but the firm as a whole, dramatically reshaping its strategies, entrepreneurial processes, innovation, R&D, and governance structures (Cennamo et al., 2020).
On the other hand, the digitalization process has undoubtedly amplified the dynamics of competitive intensity among firms (Giachetti & Dagnino, 2014). These new rapidly evolving virtual settings in which firms increasingly cannot escape, coupled with the pervasive dissemination of exponential technologies powered by a panoply of interconnected digital paraphernalia (e.g., big data analytics, machine learning, and artificial intelligence), are pivotal elements leading to increased technological uncertainty and market ambiguity. In fact, digitally driven dynamics transform firms and cut across industries in a way that is much faster (Kunisch et al., 2018), much deeper, and more disruptive (Ansari et al., 2015) than ever experienced heretofore. In such a way, firms operating in digital environments need to “continuously search for new technological, organizational, and strategic solutions that may allow them not only to hang on in the market but also to thrive and prosper” (Dagnino et al., 2021 [italics in original]). This condition involves exponential technologies scaling up (Gnyawali et al., 2010), the presence of low or negative entry barriers (once considered as an exception), and a dynamic exchange or sequence of actions and responses between the digital disruptor and the incumbent.
In connected digital settings, firms are expected to continuously orchestrate their resources and capabilities in line with demand and technological uncertainties (Brown & Fai, 2006). Consequently, firms do not attempt to use the benefits of a competitive advantage over time. On the contrary, before a disruptor may come over to tear down its advantage, the incumbent will attempt to win a new advantage. In fact, they “constantly destroy and cannibalize prior competencies to build up a stock of inimitable and unique competencies” (Fiol, 2001, p. 629). This means that firms may well decide to self-cannibalize their competitive advantage to prevent an external attack (Dagnino et al., 2021). Therefore, firms may be able to hold up or avert the sources of the Red Queen effect (Derfus et al., 2008) or the ones extending from the so-called technology S curves (Adner & Kapoor, 2016). In such a perspective, far from benefiting from the profit of a traditional sustainable competitive advantage, disruptors’ moves tend to subvert the conventional nature and duration of competitive advantages to purposefully nurture a series of short-lived advantages. As such, a sequence of digitally sourced temporary competitive advantages can make available to firms a full set of resources and capabilities ready to promote further disruptions (Huang et al., 2015).
Coopetition and Coopetitive Dynamics
An intriguing approach of looking at competitive dynamics from the angle of firms’ opportunity of coupling the dynamics of cooperation with the dynamics of competition is the one offered by the coopetition research stream (Bengtsson & Koch, 2014; Czakon et al., 2020; Dagnino & Rocco, 2009; Gnyawali & Ryan Charleton, 2018). As know, coopetition features the simultaneous existence of “competition and cooperation among firms with the intent to create value” (Czakon et al., 2020) or, more simply, the firms’ cooperation with their competitors. Actually, coopetition is deemed a viable strategic option, beyond sheer competition and cooperation, for firms that want to build and maintain their temporary advantages over time (Dagnino, 2009). Coopetition strategy has been considered as the use of coopetitive relationships to reap the advantages of a combination of innovation in new areas as a result of competition while accessing and exploiting new resources and capabilities as a consequence of cooperation (Bengtsson et al., 2010). In such a way, it is possible to look at coopetition dynamics.
One relevant vantage point of this research domain is to look at how the dynamics between competition and cooperation evolve over time by taking into account the inception of important learning effects (Han & Cai, 2019). This kind of dynamic evolution of coopetition is observable in the development path of strategic alliances as well as in the evolving relationship between the focal firm and its coopetitors’ portfolios (Yan et al., 2020). As such, Yan et al. (2020) empirically examined a data set of 323 firms operating in the global solar photovoltaic industry in the period 1995–2015. They analyzed the effect of a focal firm’s technological, market, and geographical overlap with coopetitors on its ability to engender breakthrough inventions. In particular, Yan et al. (2020) found an inverted U-shaped relationship between a focal firm’s technological overlap with its coopetitors’ portfolios and its breakthrough inventions. Besides, they also found that the focal firm’s market and geographical overlap with its coopetitors’ portfolios moderate the curvilinear relationship. Nonetheless, when both market overlap and geographical overlap are simultaneously considered, the moderation effect of geographical overlap becomes irrelevant. Another study has examined the dyadic-level evolution of coopetition between Apple and Samsung in the global smartphone industry while considering a relevant complementor (Google) in the value net (Park & Kim, 2020). Park and Kim (2020) reported that in industry-convergent conditions, innovative leaders from other industries are expected to enter newly convergent segments. In such instances, coopetition between giant entrants and incumbents plays a significant role in the quest for industry leadership. In addition, the cooperative relationships between giant entrants and incumbents may transform into coopetition over time. Such results are particularly interesting because they enlighten the role of technological, market, and geographical overlap and (shifting) convergent industry characteristics in coopetitive relationships’ evolution. Further research in coopetition dynamics might explore the change in the intensity degree of coopetition over time, especially in the presence of multiple coopetitors’ portfolios and within the realms of entrepreneurial ecosystems, strategic networks, and digital platforms.
This article focuses on understanding the key constructs and the intellectual roots of competitive dynamics. To do so, it depicts the key underpinnings of the awareness–motivation–capability (AMC) framework. In addition, it complements the traditional competitive dynamics approach with a set of novel insights on the relationship between dynamic competition and the sources of temporary competitive advantage, coopetition dynamics, as well as the accelerated competition epitomizing early 21st-century digital dynamics settings.
To advance further the understanding of competitive dynamics, future research is expected to tackle some relevant issues such as the following: First, as Chen and Miller (2015) suggested, it is important to check whether the AMC framework might prove helpful for recognizing not only competitors, but also cooperative partners. Given the relational orientation of competitive dynamics and that the causal mechanisms associated with awareness, motivation, and capability are quite similar in both cases, the AMC view might be possibly used for both competitive and cooperative analyses and applications.
Second, future research needs to tackle the performance consequences (as well as the operationalization and the measures) of relational competition (i.e., financial and nonfinancial, short-term and long-term) and determine the extent to which they emerge in different contexts. Finally, while this article paves the way by suggesting some fresh insights in this direction, future research is expected to delve more profoundly and precisely into issues such as dynamic competition and the sources of temporary competitive advantage, the antecedents, structure, and consequences of coopetition dynamics, and the accelerated competition epitomizing early 21st-century digital dynamics settings, also by featuring the appropriate interconnections between them.
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1. “Algorithms relying on Spotify’s aggregated user data and personal data can help surface the right content at the right time based on time of day and user context. That level of personalization is much tougher to copy, and Spotify’s scale gives it a distinct advantage in that realm” (Levy, 2018).