Research on collaborative innovation cooperation strategies of manufacturing digital ecosystem from the perspective of multiple stakeholders

激励 业务 产业组织 斯塔克伯格竞赛 微分博弈 补贴 知识管理 环境经济学 营销 微观经济学 经济 计算机科学 市场经济 数学优化 数学
作者
Y. Richard Wang,Juan Shi,Guohua Qu
出处
期刊:Computers & Industrial Engineering [Elsevier BV]
卷期号:190: 110003-110003 被引量:7
标识
DOI:10.1016/j.cie.2024.110003
摘要

The digital ecosystem has hastened the fusion of manufacturing and digital technology in realizing product and service value. However, due to the coordination dilemmas within the digital ecosystem such as risk sharing, competition and cooperation among stakeholders, this study aims to explore the collaborative innovation cooperation strategies of multiple stakeholders, and to investigate the interaction effects of differential incentives on each other's strategies. By constructing a dynamic differential game model, this study solves the optimal innovation efforts, digital servitization levels and innovation benefits under different cooperation intensities, and analyzes the influence of various factors on the total innovation benefits of the digital ecosystem. It is found that under different decision-making modes, the influence of incentive subsidy coefficient and cost-sharing coefficient on the innovation efforts and innovation benefits of multiple stakeholders is different. Under the decentralized decision-making mode, the incentive mechanism positively promotes the innovation efforts of both parties of cooperative enterprises, while the local government is not affected, while under the centralized decision-making mode, the incentive mechanism positively affects the innovation efforts and innovation benefits of all three parties. Specifically, under the Stackelberg game, both the innovation efforts and innovation benefits achieve Pareto improvement, while under the cooperative game, the total system innovation benefits reach Pareto optimality and the optimal strategy is realized. In addition, an optimal range exists for the benefit distribution coefficient and the policy guidance coefficient. Furthermore, factors like the cooperative benefit impact coefficient, innovation capability coefficient, and policy guidance coefficient have a positive effect on the total system innovation benefits. Conversely, factors like the discount rate, technology decay coefficient, and innovation input coefficient inhibit the growth of the total system innovation benefits. The value provides theoretical support for collaborative innovation cooperation in the digital ecosystem, thus facilitating the progress of digital transformation in manufacturing.
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