The coevolution mechanism of stakeholder strategies in the recycled resources industry innovation ecosystem: the view of evolutionary game theory.

• A tripartite evolutionary game model is employed to unpack the black box of evolution mechanism in the Recycled resources industry(RRI) innovation ecosystem. • There are six ESS in the evolutionary game model, and the ideal state (1,1,1) could be achieved. • The interactions among the three groups exist with the subsidy policy; however, the interplays between UR and Enterprise are kept only without the subsidy policy. • The factors and their influencing mechanisms to these agents' strategy choice are clarified, also transmission effect has been found. • The subsidy is a "double-edged" sword, which should be set in a reasonable range. The recycled resources industry (RRI) is considered one of the pillars for sustainable development. Few studies to date have evaluated the innovation regime in RRI, although it is one of the dilemmas that RRI is facing. Therefore, including "Government," "Enterprise," and "University-Research institute" in the evolutionary game model, this paper draws on innovation ecosystem theory and conducts a mechanism analysis to clarify the evolutionary stability of stakeholder strategies in the RRI. The findings highlight six potential Evolutionary Stable Strategies (ESS), with which the 'ideal state' can be achieved. Moreover, with and without the subsidy policy, the strategic choices of players are differently interdependent, the divergent factors and the influencing mechanisms to the main stakeholders are identified, and the transmission effect of the influence is found. What's more, a subsidy policy would promote active cooperation between these stakeholders when the subsidy quota is within an appropriate range. This paper unpacks the evolution mechanism black box from the stakeholders' perspective, which provides a clearer understanding of the evolutionary dynamics of industrial innovation ecosystems. The critical findings also provide evidence for policymakers to facilitate the coevolution of the agents in the innovation ecosystem, thereby improving the overall innovation ability of the RRI. [ABSTRACT FROM AUTHOR]