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

Xinyu Hao, Guangfu Liu, Xiaoling Zhang and Liang Dong

Technological Forecasting and Social Change, 2022, vol. 179, issue C

Abstract: 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.

Keywords: Recycled resources industry; innovation ecosystem; strategy choice; evolutionary game model (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162522001597
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:179:y:2022:i:c:s0040162522001597

DOI: 10.1016/j.techfore.2022.121627

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().