The Influencing Factors and Promotion Countermeasures of Industrial Generic Technology Diffusion Based on Differential Game

Wang, Fenglian; Xie, Rongjian; Hu, Wengting

doi:10.1155/2021/6643922

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…The government’s final decision and the rate at which a stable state is achieved are not affected by the penalty for breach of contract

. In terms of the collaborative innovation mode of green technology with government participation and cooperation between an enterprise and a university/institute, the changing penalty for breaches of contract directly affects the profits of the enterprise and the university/institute, which then has an impact on their cooperation intentions [ 61 ]; however, it does not affect the government’s profit. Therefore, under the premise of the government being inclined to participate in green technology innovation, increasing the penalty for breaches of contract is conductive to promoting the building of the pilot of government–industry–university–institute collaborative innovation; however, reducing this revenue hinders completion of the pilot.…”

Section: Simulation and Discussionmentioning

confidence: 99%

Research on the Mechanism of Government–Industry–University–Institute Collaborative Innovation in Green Technology Based on Game–Based Cellular Automata

Zhou

2022

IJERPH

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In order to ensure stable cooperation among the government, enterprise and university/institute in the green technology innovation process and guide an increasing number of innovation agents in the region to adopt cooperation, this paper studies the mechanism of green technology innovation. A tripartite evolutionary game model is established and the strategy choices of the government, industry and university/institute are analyzed through mathematical derivation. On this basis, the cellular automata theory is used to explore strategy choices of all innovation agents in the region from the perspective of a spatial game. From the numerical tests, the following results are obtained: increasing the cooperative innovation revenue, fairness of this revenue distribution or penalties for breach of contract can consolidate the cooperative relationship among the government, enterprise and university/institute, achieving the goal of guiding all innovation agents in the region to accept the collaborative innovation mode; regulating the government subsidy or government penalty can consolidate the cooperative relationship among participants in the pilot project, but cannot guide all innovation agents in the region accept the collaboration innovation mode. This paper’s results not only enrich the theory of government–industry–university–institute collaborative innovation in green technology, but provide ideas for stable cooperation mechanisms and comprehensive promotion of this collaborative innovation mode as well.

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“…The government’s final decision and the rate at which a stable state is achieved are not affected by the penalty for breach of contract

Section: Simulation and Discussionmentioning

confidence: 99%

Research on the Mechanism of Government–Industry–University–Institute Collaborative Innovation in Green Technology Based on Game–Based Cellular Automata

Zhou

2022

IJERPH

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“…The government tends to provide direct funding to UR and indirect funding, such as R&D subsidies and incentives, to enterprises [25]. A large number of studies have also used empirical analysis and game models to confirm that the implementation of subsidies and incentives by the government can help increase the R&D investment of enterprises and promote collaborative R&D [26,27]. The main aspects of policy and institutional guidance include the establishment of special programs, intellectual property regimes, and innovation funds for GPTs [28,29].…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-Agent Collaborative R&D Strategies of General-Purpose Technologies: Commonality and Synergy Perspective

2023

Teh. vjesn.

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New round of emerging scientific and technological revolution mingled with industrial revolution has intensified the competition among countries for generalpurpose technologies (GPTs), as they attempt to strengthen their strategic layout and seize decisive development opportunities. However, in reality, the collaborative R&D of GPTs by multiple subjects often fails, thereby leading to the low success rate of GPTs. To identify the influencing factors of multi-agent collaborative R&D GPTs, an evolutionary game model of multi-agent collaborative R&D based on types of GPTs and the degree of synergy among multiple agents was constructed in this study. The multi-agent collaborative R&D strategies under the two scenarios with and without government participation were then explored, and MATLAB numerical simulation was performed to compare the influence of different types of GPTs and the degree of synergy under government strategies and measures on multi-agent collaborative R&D strategies. Results show that: (1) in the R&D process of basic, pre-competitive and applied GPTs, the degree of synergy required for multi-agent cooperation gradually decreases, and the focus of synergy also changes along with types of technologies. (2) In the R&D process of basic GPTs, when the degree of synergy is higher than the critical value, the willingness of enterprises to conduct R&D decreases and then increases in a "U-shaped" trend as the willingness of universities and research institutes (UR) to conduct R&D increases. In the R&D process of pre-competitive GPTs, when the degree of synergy is lower than the critical value, the willingness of UR to conduct R&D increases and then decreases in an "inverted U" trend as the willingness of enterprises to conduct R&D decreases. In the R&D process of all three types of GPTs, government participation is particularly effective, and when the degree of synergy is much higher than the critical value, the willingness of enterprises to engage in R&D increases. (3) In the case of government participation, the proportion of subsidies, the strength of knowledge protection and the degree of synergy among multiple subjects are adjusted by the government in line with the importance of GPTs to act on precise policies. To some extent, conclusions provide theoretical basis and policy suggestions for industry-university-research collaborative R&Ds of GPTs and government measures.

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Technology adoption path of construction and demolition waste recycling under governmental subsidy: a theoretical model

Hua

Chen

Liu

et al. 2023

Environ Sci Pollut Res

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The Influencing Factors and Promotion Countermeasures of Industrial Generic Technology Diffusion Based on Differential Game

Cited by 4 publications

References 7 publications

Research on the Mechanism of Government–Industry–University–Institute Collaborative Innovation in Green Technology Based on Game–Based Cellular Automata

Research on the Mechanism of Government–Industry–University–Institute Collaborative Innovation in Green Technology Based on Game–Based Cellular Automata

Multi-Agent Collaborative R&D Strategies of General-Purpose Technologies: Commonality and Synergy Perspective

Technology adoption path of construction and demolition waste recycling under governmental subsidy: a theoretical model

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