[Professor Altman's Lab] An Evolutionary Game-Theoretic Approach for Analyzing Startups' Funding Mechanisms Considering Opportunistic and Responsible Behavior Based on System Dynamics
Paper Title : An evolutionary game-theoretic approach for analysis of startups’ funding mechanisms considering their opportunistic and responsible behavior based on system dynamics
Research Background
In response to climate change and sustainability challenges, established technology firms are increasingly adopting Green Technological Innovation (GTI) as a core strategic objective. Collaborating with startups has emerged as a fast and effective pathway to implement GTI, as startups often provide radical innovations and flexibility that large firms lack. However, such collaborations are inherently risky, particularly due to startups’ potential opportunistic behavior, which can undermine GTI outcomes and lead to significant investment losses for technology firms.
Existing studies on corporate–startup collaboration and startup financing have largely relied on static game-theoretic models or one-shot contractual analyses. These approaches fail to capture the dynamic nature of collaboration, where firms and startups continuously adjust their strategies over time under bounded rationality. To address this gap, this study adopts a dynamic analytical framework that integrates Evolutionary Game Theory (EGT) with System Dynamics (SD) to examine how investment strategies, penalty mechanisms, government intervention, and feedback structures jointly shape the long-term stability of GTI-oriented collaborations.
Research Content
This study models interactions between two populations—technology firms and startups—within an evolutionary game framework. Technology firms choose between a one-period investment strategy and a two-period (staged) investment strategy, while startups decide whether to exert green innovative effort or engage in non-green, opportunistic behavior.
First, the evolutionary game model is developed to derive Evolutionarily Stable Strategies (ESSs) under different parameter conditions. The analytical results are then embedded into a system dynamics model to simulate how strategic choices evolve over time. The model explicitly incorporates:
- The cost structure of green innovative efforts by startups
- Static versus dynamic penalty strategies imposed by technology firms
- Government subsidies that reduce investment risk
- Negative feedback loops, where rising innovation costs discourage sustained effort
- Positive feedback loops, where successful GTI outcomes enhance startup credibility and increase collaboration success
Simulation results show that static penalty strategies can temporarily restrain opportunistic behavior but often lead to persistent oscillations and system instability in the long run. In contrast, dynamic penalty strategies, which adjust penalties based on the degree of opportunistic behavior, effectively dampen oscillations and promote convergence toward stable cooperative outcomes.
The analysis further reveals that government subsidies increase technology firms’ willingness to invest in GTI-related projects, but without adaptive penalty mechanisms, subsidies alone may amplify system volatility. Finally, when startup credibility is endogenously enhanced through GTI performance, positive feedback loops significantly improve long-term collaboration stability and green innovation outcomes.
Implications and Expected Contributions
This study contributes to the literature by conceptualizing corporate–startup collaboration as an evolving strategic process, rather than a static contractual arrangement.
First, the findings highlight the superiority of dynamic penalty mechanisms over static ones in managing opportunistic behavior and ensuring long-term system stability.
Second, the results suggest that while government intervention is crucial for encouraging green investments, subsidy policies must be carefully coordinated with monitoring and incentive mechanisms to avoid unintended instability.
Third, the study underscores the importance of strengthening mechanisms through which startups’ green innovation efforts translate into credibility and reputation, thereby creating self-reinforcing incentives for responsible behavior and sustainable collaboration.
Publication Information
This study was conducted by Mohammad-Ali Eghbali, Morteza Rasti-Barzoki, and Jörn Altmann, and has been accepted for publication in the international journal Kybernetes (Accepted: March 2025).
The research was supported by the National Research Foundation of Korea (NRF) and the BK21 FOUR program.
Research Background
In response to climate change and sustainability challenges, established technology firms are increasingly adopting Green Technological Innovation (GTI) as a core strategic objective. Collaborating with startups has emerged as a fast and effective pathway to implement GTI, as startups often provide radical innovations and flexibility that large firms lack. However, such collaborations are inherently risky, particularly due to startups’ potential opportunistic behavior, which can undermine GTI outcomes and lead to significant investment losses for technology firms.
Existing studies on corporate–startup collaboration and startup financing have largely relied on static game-theoretic models or one-shot contractual analyses. These approaches fail to capture the dynamic nature of collaboration, where firms and startups continuously adjust their strategies over time under bounded rationality. To address this gap, this study adopts a dynamic analytical framework that integrates Evolutionary Game Theory (EGT) with System Dynamics (SD) to examine how investment strategies, penalty mechanisms, government intervention, and feedback structures jointly shape the long-term stability of GTI-oriented collaborations.
Research Content
This study models interactions between two populations—technology firms and startups—within an evolutionary game framework. Technology firms choose between a one-period investment strategy and a two-period (staged) investment strategy, while startups decide whether to exert green innovative effort or engage in non-green, opportunistic behavior.
First, the evolutionary game model is developed to derive Evolutionarily Stable Strategies (ESSs) under different parameter conditions. The analytical results are then embedded into a system dynamics model to simulate how strategic choices evolve over time. The model explicitly incorporates:
- The cost structure of green innovative efforts by startups
- Static versus dynamic penalty strategies imposed by technology firms
- Government subsidies that reduce investment risk
- Negative feedback loops, where rising innovation costs discourage sustained effort
- Positive feedback loops, where successful GTI outcomes enhance startup credibility and increase collaboration success
Simulation results show that static penalty strategies can temporarily restrain opportunistic behavior but often lead to persistent oscillations and system instability in the long run. In contrast, dynamic penalty strategies, which adjust penalties based on the degree of opportunistic behavior, effectively dampen oscillations and promote convergence toward stable cooperative outcomes.
The analysis further reveals that government subsidies increase technology firms’ willingness to invest in GTI-related projects, but without adaptive penalty mechanisms, subsidies alone may amplify system volatility. Finally, when startup credibility is endogenously enhanced through GTI performance, positive feedback loops significantly improve long-term collaboration stability and green innovation outcomes.
Implications and Expected Contributions
This study contributes to the literature by conceptualizing corporate–startup collaboration as an evolving strategic process, rather than a static contractual arrangement.
First, the findings highlight the superiority of dynamic penalty mechanisms over static ones in managing opportunistic behavior and ensuring long-term system stability.
Second, the results suggest that while government intervention is crucial for encouraging green investments, subsidy policies must be carefully coordinated with monitoring and incentive mechanisms to avoid unintended instability.
Third, the study underscores the importance of strengthening mechanisms through which startups’ green innovation efforts translate into credibility and reputation, thereby creating self-reinforcing incentives for responsible behavior and sustainable collaboration.
Publication Information
This study was conducted by Mohammad-Ali Eghbali, Morteza Rasti-Barzoki, and Jörn Altmann, and has been accepted for publication in the international journal Kybernetes (Accepted: March 2025).
The research was supported by the National Research Foundation of Korea (NRF) and the BK21 FOUR program.
