Evolutionary Game of Multiple Subjects Collaborative Innovation Under Double Uncertainty

IF 1.6 4区 工程技术 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Complexity Pub Date : 2026-03-16 DOI:10.1155/cplx/3743541
Xumei Yuan, Ming Zhang, Fuli Wei, Xu Zhang
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引用次数: 0

Abstract

Multisubject technology collaborative innovation serves as an essential driving force to improve technology transfer efficiency as well as implement the innovation-driven strategy. Particularly, collaborative innovation in accordance with technological orientation and market demand enables the efficient resource allocation that stimulates innovation willingness and improves innovation performance. This study explores the strategies and conditions for multiagent collaborative innovation under technological and market uncertainties, employing a government–enterprise–university evolutionary game model. Numerical simulations demonstrate that both technology and market factors are critical drivers of collaborative innovation systems, with market influences outweighing technological ones. Notably, technological universality proves more impactful than novelty. When technology and market drivers are weak, government willingness becomes the decisive factor in shaping other participants’ strategic choices. Punitive measures have a stronger effect on system evolution than government incentives. The study’s key contribution lies in emphasizing technological sophistication, technological universality, market price, participant willingness, and policy impacts. The findings underscore the dynamic interplay of technology, market, and government in collaborative innovation, offering novel theoretical and practical insights into its driving mechanisms and implementation pathways.

Abstract Image

双不确定性下多主体协同创新的进化博弈
多学科技术协同创新是提高技术转移效率、实施创新驱动战略的重要动力。特别是根据技术导向和市场需求进行协同创新,可以实现资源的高效配置,激发创新意愿,提高创新绩效。本文采用政府-企业-大学演化博弈模型,探讨了技术和市场不确定性下多主体协同创新的策略和条件。数值模拟表明,技术和市场因素都是协同创新系统的关键驱动因素,市场影响大于技术影响。值得注意的是,技术的普遍性比新颖性更有影响力。当技术和市场驱动力较弱时,政府意愿成为影响其他参与者战略选择的决定性因素。惩罚性措施比政府激励对制度演化的影响更大。该研究的主要贡献在于强调了技术复杂性、技术普遍性、市场价格、参与者意愿和政策影响。研究结果强调了技术、市场和政府在协同创新中的动态相互作用,为其驱动机制和实施途径提供了新颖的理论和实践见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Complexity
Complexity 综合性期刊-数学跨学科应用
CiteScore
5.80
自引率
4.30%
发文量
595
审稿时长
>12 weeks
期刊介绍: Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.
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