Research on collaborative innovation behavior of enterprise innovation ecosystem under evolutionary game

Ning Yuan and Meijuan Li

Technological Forecasting and Social Change, 2024, vol. 206, issue C

Abstract: Establishing an innovation ecosystem revitalizes enterprises by fostering collaboration with other entities within the system. This collaboration results in increased resources for innovation and development, further strengthening participants' innovation and survival capacities. As the existing literature on collaborative innovation behavior within innovation ecosystems is relatively limited, the primary objective of this study is to investigate the evolutionary process and impact factors of players' collaborative innovation behavior in the enterprise innovation ecosystem (EIE). This study establishes an evolutionary game (EG) model that includes three players in an EIE to analyze their collaborative innovation behaviors in scenarios where their initial strategic probabilities are low, medium, and high. The simulation results indicate the existence of six potential evolutionary stable strategies (ESSs) within the system. The ideal ESS identified in this three-party evolutionary game model is characterized by “active collaboration, active collaboration, participation”. Furthermore, the player's behaviors in different states are affected by initial probability, synergy sensitivity, transformation efficiency, output elasticity, subsidy, punishment, and public impact. The results of this study reveal the mechanism of collaborative innovation behavior among different players in the EIE, providing beneficial references for its sustainable development.

Keywords: Enterprise innovation ecosystem; Collaborative innovation; Evolutionary game; Strategy choice (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:206:y:2024:i:c:s0040162524003044

DOI: 10.1016/j.techfore.2024.123508

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