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The purpose of this paper is to seek to advance the understanding of competitive interaction framework based on competitive dynamics theory that investigates how nonmarket and market factors concurrently affect the relationships among action and response, their integration, and initiating firm performance.

To test the hypotheses for this study, the authors used data collected from the news found in web sites of 72 Chinese firms over a five-year period from January 2007 to December 2011. The authors use the approach suggested by Baron and Kenny (1986) to test the mediated effect of rival response and speed, after structured content analysis is adopted to overcome the challenges of identification and measurement by using a sample of competitive actions and responses.

The results test partial mediating role of rival response and speed in linking nonmarket, market, and integrated action with initiating firm performance outcomes. Rival responses and speed may vary systematically in nonmarket action. The relationship between the integration of competitive action and initiating firm performance is positive, high, and significant.

The results of this study were limited by a sample in China. The authors further need to consider how nonmarket and market components are operationalized in different institutional environments. The authors study only captures observable moves reported in the news of Chinese firms’ web sites. This single-data source collection raises the specter of cognitive bias. It is advised to collect data from multiple sources, perhaps directly measuring the managers’ perception by using a questionnaire-based survey.

Firms whose main focus is to launch market actions in an effort to gain competitive advantage should ensure that their nonmarket actions constitute interfirm rivalry. Particularly, this study also encourages managers to continuously and rapidly integrate nonmarket actions into their analyses of market competition for firm success. Additionally, managers need to develop effective information-processing mechanisms to analyze, monitor, forecast, and interpret rival response and speed for each competitor.

The research contributes to the authors’ understanding of the nature of nonmarket and market competition by bridging nonmarket action into traditional competitive dynamics.

The purpose of this paper is to explore the nature of a competitive action and its impact on the response of rivals in the digital market. Specifically, this paper introduces the concept of action complexity and action variation to delineate the configuration characteristics of each digital competitive action and empirically investigates how these action characteristics further affect rivals’ response speed.

This paper uses structural content analysis methods to code competitive actions based on the news of Chinese online travel agencies (OTAs) from 2010 to 2015. The cox proportional hazards regression models are employed to test the hypotheses.

The results indicate that action complexity of the focal firm is negatively associated with rivals’ response speed as it constrains their interpretation (awareness), motivation and capability to respond, while action variation of the focal firm is positively associated with rivals’ response speed as it enhances their attention (awareness) and motivation to respond. Furthermore, the negative relationship between action complexity and response speed is weaker when action variation is high.

Further to advancing competitive dynamics theory, this paper proposes an action-configuration perspective to explore the particular content and quality of each digital competitive action. The discussion of competitive rivalry between OTAs also enriches the application of competitive dynamics in the digital market. Meanwhile, this paper further clarifies the decision-making process of rivalry drawing on the awareness–motivation–capability (AMC) framework.

This study aims to develop a competitive dynamics model of container shipping liners, one which examines how inter-firm network embeddedness would affect inter-firm rivalry such as the likelihood of a competitive action of a focal firm and the likelihood of its rivals’ response and how the inter-firm rivalry then has an influence on the market share of the focal firm. Structural and relational network embeddedness between a focal firm and its competitors would be investigated as drivers of the likelihood of the competitive action and response. The theoretical framework on the relationship between network embeddedness, inter-firm rivalry and market share in the liner shipping industry will be developed and relevant propositions are then suggested in relation to the model. This attempt may provide meaningful insights for managers and academic researchers into the key factors which affect the inter-firm rivalry between shipping liners and may also detail the impact of inter-firm rivalry on the focal firm’s market share. This research would therefore contribute to the development of the competitive strategy of container shipping companies so as to help them strategically manage their rivals’ competitive behaviors and maximize their market share.

The interdependence of firms in the marketplace implies that the effectiveness of an action cannot be valued without considering potential reactions. Therefore, the main objectives of this paper are to analyse the effect of the initiating company characteristics on the perceived attributes of its action and to understand the effect of these dimensions on the number of companies that respond to it.

Based on action‐reaction dynamics, a series of hypotheses was theoretically justified inking the characteristics of the actor with the dimensions of its action, and these dimensions with the probability of response from rivals. Their validity with data obtained from a survey of marketing managers of Spanish companies was checked, using a variety of statistical techniques.

Results indicate that the probability of reaction is influenced by the level of visible threat of action. Further findings indicate that the leadership position of the actor has an indirect influence on the probability of response.

The size of the sample and the measures used are both limited. Also, the explanatory capacity of the model could be improved by considering new variables.

Prior knowledge of the probability of a reaction is an important input for the managerial process of strategic planning, capable of improving the success rate in implementing actions and thereby the competitive position.

Few research studies of competitive interaction have focused on the probability of response, into which this paper offers an insight.

When a foreign firm cross-lists on an exchange in the US, it signals stronger investor protection. This is because cross-listing firms must comply with SEC and exchange regulations, thus producing stronger corporate governance. Consequently, cross-listing increases firm attractiveness to investors and places domestic rivals at a disadvantage. Rivals might respond by mimicking the governance changes resulting from cross-listing. The purpose of this paper is to examine whether firms respond to their rivals’ cross-listings through improvement in governance.

This study uses earnings management as a measure of governance for a set of international firms. The authors track the changes in governance of non-cross-listing firms following their rivals’ cross-listings. The authors employ an event study methodology to assess the spillover effect of a competitor’s cross-listing.

The authors find that rivals exhibit imitative improvements in their governance following a competitor’s cross-listing. This response is immediate and is the strongest in the year of cross-listing. Further, rivals with greater growth opportunities, lower market share, stronger past performance, and larger size demonstrate greater improvements in governance. Rivals make greater improvements in response to more rigorous Level III listings.

This study finds that cross-listing effects are underestimated. It is not only the investors of the listing-firms who benefit from the cross-listing, but also the investors of non-listing rival as competitors try to match the higher governance standard.

This study is the first that examines the intra-industry spillover effect of a cross-listing. This study also expands the analysis of the spillover effect in a new dimension: corporate governance.

The purpose of this paper is to explore how managers’ evaluation of and reaction to multiple rivals’ actions will be affected by the distributional characteristics of these actions, including the extent to which rivals’ actions are centered on certain firms (actor concentration), concentrated in certain time periods (temporal concentration), and clustered in certain geographic locations (spatial concentration).

The analyses are based on panel data on Taiwanese producers of personal computers and peripherals and the investments they made in mainland China after the Asian financial crisis. The authors employ fixed-effect logit regression to test the hypotheses.

Rivals’ recent actions in China increase a focal firm’s inclination to act especially when these rivals’ actions are characterized by a high level of actor, temporal, and/or spatial concentration.

The analytical approach goes beyond a dyad-level conceptualization of interfirm rivalry. Incorporating insights from behavioral decision making, the paper shows how a firm with limited attentive capacity reacts to the aggregate impact of multiple rivals’ actions.

Although two decades have passed since the publication of Walsh and Ungson’s (1991) seminal article on organizational memory, there has been only limited theoretical elaboration and application of this critical aspect of cognition in the strategic management literature. We remedy this gap by advancing the construct of competitive memory, which we define as a firm’s dynamic capability consisting of stored information from its past competitive interaction with a given rival that can be brought to bear on present or future competitive actions. We theorize that competitive memory is composed of both procedural and declarative elements and can be accessed automatically and deliberatively. Additionally, we suggest that competitive memory is relational: As rivals within a competitive set interact in the market, competitive memory drives not only their strategic actions, but also their expectations about their competitors. Last, competitive memory is also dynamic, which can be constructed and reconstructed over time by an organization’s enactment of its internal and external environments and by purposive memory trials with its competitive set.

The purpose of this paper is to examine intra‐industry contagion and the following apparent violations of the efficient market hypothesis around large one‐day price decline events in individual stocks.

The paper examines daily stock returns around one‐day price declines of 10 percent or more for event stocks and their rivals. Using techniques similar to those used in Bremer and Sweeney and Cox and Peterson, the paper includes event stocks whose prices are at least $10 per share prior to the event to reduce the possible price reversal induced by bid‐ask price bounce. As is typical for the literature, the stock daily abnormal return (AR) is calculated as the difference between the actual daily stock return and the estimated stock return based on the market model estimated over a 200‐trading‐day pre‐event period [−220, −21]. Cumulative abnormal returns (CARs) for each stock are formed by aggregating the individual daily stock ARs. Denoting the large price decline event day as day 0, we examine the ARs of 41 trading days [−20,+20], the CARs for the [+1,+3] period, and the CARs for the [+4,+20] period. Cross‐sectional average ARs and CARs are calculated and tested for statistical significance. Furthermore, the paper examines whether the post‐event abnormal stock returns for the event firm and its rivals can be explained by prior event firm and industry variables.

On average, after an event, the event stock experiences a positive three‐day AR (S&P 600 stocks) followed by a 17‐day negative AR (both S&P 500 and 600 stocks). Moreover, for that 17‐day period: the rivals' stocks outperform the event firms' stocks and the event firms' returns are statistically significantly related to prior variables. The paper also finds statistically significant relationships between the prior variables and the rivals' post‐event stock returns. It provides an intra‐industry effects explanation for these results.

The paper offers insights into abnormal stock returns, for the event firm and its rivals, following the event firm's large one‐day stock price drop.

The purpose of this paper is to examine the role of competitive memory that assists the new ventures to overcome challenges due to the liability of newness in the strategic adaptation stage.

This is a conceptual paper. Through a critical literature review on new venture survival and organizational memory, the authors identified the possibility for new ventures to learn from other firms from organizational learning and resource-based perspectives.

The authors found that new ventures can acquire and analyze the existing rivals' strategic moves documented in multiple sources, such as published yearbook, financial report, media, etc., and develop their own strategies. New ventures can also benefit from the relatively high degree of organizational inertia of existing rivals.

New venture survival and performance are substantially affected by the initial organizational learning and strategic decision-making. Applying the memory-inconsistent strategy (MIS), new ventures that lack competitive experiences can learn from their rivals by internalizing the rivals' competitive memory as strategic resources and utilizing such resources to develop a competitive strategy.

New venture research in competitive markets focuses on the challenges and difficulties due to the lack of experiences, neglecting the fact that new ventures can learn from competitive memories of existing rivals. However, the lack of competitive experiences also means a lower degree of organizational inertia and other strategic commitments. The authors introduce the MIS and suggest that new ventures can benefit from strategic flexibility and create a temporary competitive advantage by surprising existing firms.

In this study, we develop understanding of factors that shape the propensity of market incumbents to collaborate in response to the threat posed by new market entrants. We are particularly interested in instances when a market's competitive structure becomes unsettled by new entrants who engage in nonconforming strategic tactics. In such situations, we propose two factors – strategic similarity among competitors and market-share instability – will systematically shape competitors' collaborative response to new entrants. To test our theory, we use data on strategic tactics and collaborative dynamics in the US airline industry from 1989 to 2010. We demonstrate that greater strategic similarity among a market's incumbents increases the likelihood of cooperation in response to the threat of a nonconforming new entrant, while greater market-share instability reduces cooperative response. Through this study, we extend existing understanding of the contextual circumstances under which established competitors recognize their mutual interests and band together.