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Over the last years, powerful advances in the area of dynamic games have enriched game theory and made it more applicable to the modeling of real-world competitive strategies. The study of strategic behaviors of firms in an oligopoly market has received little attention, even though real firms have been shown to compete in output and in price in a single industry. The purpose of this study is to propose a game-theoretic approach to studying strategic behaviors of firms in an oligopoly market structure.

This approach was developed to study market dynamics and pricing strategic behavior of firms that have the possibility of deciding to be one of the two types (price-maker or price-taker) and reconsider the choice overtime on the basis of their current insights and knowledge and their experience. Firms try to improve their performance in the competitive market in a strategic way, by considering their steady-state profits and choosing the best type given the other firms’ types, actions and interactions.

The results of the present study confirm the previous study that the Cournot market is a stable market, where each firm can be a price-maker and enjoy individual learning as well as social learning. On the contrary, the market with price-takers only is never stable, and, therefore, the Walrasian equilibrium may not be supported in some instances. The Cournot market loses its stability as the number of firms in the market increases due to the fact that it will be more profitable for a firm to switch to price-taking when the number of firms is high enough. In such a situation, when the number of price-takers increases, there are no stable markets and price dynamics are destabilized.

The study and modeling of real-world competitive strategies would enhance the understanding of oligopoly markets. The study of strategic behaviors of firms in an oligopoly market has received little attention, even though real firms have been shown to compete in output and in price in a single industry as price-takers and price-makers.

Collaborative research and development have remained a pertinent mechanism for conducting technological innovations. With the lens of knowledge-based view (KBV), this study aims to examine the role of changes in knowledge couplings and network cohesion to elevate innovation performance.

Data analysis has been performed on 53,459 patents through regression analysis with random effects. These independent and joint patents are extracted from Derwent Innovation Database.

Findings explicate that change in external existing or existing and new knowledge couplings have inverted U-shaped effects on a firm’s innovation performance. Changes in internal existing or existing and new knowledge couplings have direct positive effects on firm’s innovation performance. The moderation effect of network cohesion flattens the inverted U-shaped effect of external new and existing knowledge coupling, whereas it has no significant effect on external existing knowledge coupling. Network cohesion further elevates the effects of internal knowledge couplings – existing or existing and new.

This study theoretically contributes to KBV and innovation management literature by highlighting the scope of changes in internal and external knowledge couplings and subsequent output. Network cohesion flattens the curviness of changes in external new and existing knowledge couplings, which is a contribution to strategic management literature.

Organizations need to carefully manage changes in knowledge couplings and ensure their benefits (obtain new knowledge domain or new combination) outweigh liabilities (damages to organizational routines or increase in collaboration costs). Managers must consider four kinds of knowledge coupling changes along with developing network cohesion as an R&D strategy.

This study is one of its types to flatten the curve through network cohesion. This study divided the changes in knowledge coupling into four types and two dimensions; external existing and new and existing knowledge couplings and internal existing and new and existing knowledge couplings.