An Evolutionary Game Model of Collaborative Innovation Between Enterprises and Colleges Under Government Participation of China

Su, Nina; Shi, Zhuqin; Xian-qi, Zhu; Xin, Yunsheng

doi:10.1177/2158244021994854

Cited by 11 publications

(11 citation statements)

References 30 publications

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“…TEGMs have been extensively used in various fields, including physics (Park and Traulsen, 2017), medicine (Sartakhti et al, 2017), and social science (Su et al, 2021). In the field of environmental management, Estalaki et al (2015) examined the effect of penalty mechanisms on water pollution control using evolutionary game theory.…”

Section: Tripartite Evolutionary Game Modelmentioning

confidence: 99%

“…Considering the TEGM, local government A and local government B select the "implementing fully" strategy or the "implementing incompletely" strategy randomly and independently, while the central government selects the "inspecting thoroughly" strategy or the "inspecting incompletely" strategy randomly and independently. This paper uses the replication dynamic mechanism (Su et al, 2021;Chu et al, 2021) to simulate the tripartite evolutionary game process among the central government and two local governments (Table 3). If the proportion of the central government choosing to inspect thoroughly is x, the proportion of the central government that chooses to inspect incompletely is 1−x.…”

Section: Tripartite Evolutionary Game Modelmentioning

confidence: 99%

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The evolutionary mechanism of haze collaborative governance: novel evidence from a tripartite evolutionary game model and a case study in China

Zhang

et al. 2023

Humanit Soc Sci Commun

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The topic of haze collaborative governance has become a hot policy issue attracting worldwide attention. However, existing studies do not pay enough attention to haze collaborative governance in the process of central environmental protection inspection (CEPI). This paper employs a tripartite evolutionary game model to explore the evolutionary mechanism of haze collaborative governance among China’s central and local governments and verifies its findings further through a case study of CEPI for air pollution in Beijing-Tianjin-Hebei and surrounding regions. The results show that haze collaborative governance is mainly affected by the performance evaluation system, policy implementation cost, clean government construction, industrial transfer trend, fiscal subsidy, environmental inspection cost, environmental accountability, and public participation. The implementation of CEPI is conducive to haze collaborative governance among central government and local governments. To promote the full implementation of air pollution control policies, the local governments need to optimize the performance evaluation system by considering economic development and environmental protection, reduce policy implementation costs by cost-sharing, and strengthen clean government construction by preventing rent-seeking corruption. In addition, the local governments need to strengthen the coordination of cross-regional industrial development and optimize fiscal subsidies to promote ecological compensation and transfer payments. For supervising the policy implementation of local governments thoroughly, the central government needs to reduce the environmental inspection cost using the evaluation framework of cost-benefit analysis, strengthen the haze governance accountability through normalizing supervision, and broaden the public’s external supervision channels. It is vital to take effective measures to carry out haze collaborative governance, providing a useful experience for developing countries.

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Section: Tripartite Evolutionary Game Modelmentioning

confidence: 99%

Section: Tripartite Evolutionary Game Modelmentioning

confidence: 99%

The evolutionary mechanism of haze collaborative governance: novel evidence from a tripartite evolutionary game model and a case study in China

Zhang

et al. 2023

Humanit Soc Sci Commun

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“…Duan et al (2019) compared the advantages and disadvantages of independent and cooperative innovation in digital media enterprises and proposed that enterprises should cooperate with scientific research institutions. Su et al (2019) studied the tripartite collaborative innovation behavior of the government, enterprises and scientific research institutions, and proposed that the government should improve the incentive mechanism of industry, education and research.…”

Section: Multiagent Governance With Public Participationmentioning

confidence: 99%

Research on multiagent governance of the marine ecoeconomic system in China considering marine scientific research institutions and media

Le-hua

Yan

Cai

2023

Front. Environ. Sci.

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The multiagent governance model of the marine ecoeconomic system requires local governments to actively guide the participation of social subjects. Under the new reality of multiagent governance mechanism, this study proposes an analytical framework for describing the dynamic relation between local governments and marine production enterprises. It uses the analytical tools of evolutionary game theory to establish an evolutionary game system between the two parties and takes China as the specific research object. For doing so, it selects marine scientific research institutions and media with a strong public value representation and discusses the unilateral evolutionary stability strategy of the system by introducing four parameters, namely, the number of marine scientific research institutions, the contribution level of marine scientific research institutions, the participation level of media, and the authenticity level of information released by media. Furthermore, we used MATLAB to simulate and analyze by combining our research data in 14 cities in coastal areas of China. The results demonstrate that: 1) improving the contribution level and number of marine scientific research institutions is conducive to the collaborative governance of the marine ecoeconomic system; 2) the authenticity level of information released by media is positively correlated with the development of the multiagent governance model of the marine ecoeconomic system; and 3) differently biased objects with distorted media report information affect the trend of the governance effect of the marine ecoeconomic system. Thus, a timely improvement or reduction of the participation level of media is necessary.

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“…Each group of actors is deemed as an entirety. In the co-evolutionary process of innovation ecosystems, actors will usually make decisions to maximize their own interests due to bounded rationality (Su et al, 2021), which can be analyzed through game theory. As decision-makers, both GFF and GRI strategize cooperation or default, GC and GG decide whether to cooperate in innovation ecosystem co-evolution.…”

Section: Game Relationships In An Innovation Ecosystemmentioning

confidence: 99%

An Evolutionary Analysis of Relational Governance in an Innovation Ecosystem

et al. 2022

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Despite considerable research highlighting the significance of relational governance in inter-organizational relationships, few have involved the connections between relational governance and innovation ecosystems. This study explores this issue to discover the influential mechanisms of relational governance in innovation ecosystem co-evolution. Building an evolutionary game model, we embody trust and reciprocity (two dominance of relational governance) into co-evolutionary relationships of an innovation ecosystem composed of focal firms, research institutes, customers, and governments, and discuss how relational governance affects innovation strategies of actors. Moreover, the impacts of benefit distribution are also examined. We reveal that (1) focal firms and governments prefer cooperative strategies; (2) reciprocity and trust foster cooperation; increasing benefit distribution drives all actors to collaborate except research institutes; (3) governments finitely encourage cooperation through regulation; and (4) the power of relational governance is restricted due to the below-the-average strategies of customers and research institutes and the neutralizing effects of benefits. Our findings offer a complementary and novel framework for relational governance and extend a deeper understanding of innovation ecosystem studies.

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An Evolutionary Game Model of Collaborative Innovation Between Enterprises and Colleges Under Government Participation of China

Cited by 11 publications

References 30 publications

The evolutionary mechanism of haze collaborative governance: novel evidence from a tripartite evolutionary game model and a case study in China

The evolutionary mechanism of haze collaborative governance: novel evidence from a tripartite evolutionary game model and a case study in China

Research on multiagent governance of the marine ecoeconomic system in China considering marine scientific research institutions and media

An Evolutionary Analysis of Relational Governance in an Innovation Ecosystem

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