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中国管理科学 ›› 2023, Vol. 31 ›› Issue (12): 149-162.doi: 10.16381/j.cnki.issn1003-207x.2022.2727

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区块链技术、供应链网络与数据共享:基于演化博弈视角

孙国强1(),谢雨菲2   

  1. 1.山西财经大学组织创新与网络治理研究中心, 山西 太原 030006
    2.山西财经大学管理科学与工程学院, 山西 太原 030006
  • 收稿日期:2022-11-01 修回日期:2023-05-15 出版日期:2023-12-15 发布日期:2023-12-20
  • 通讯作者: 孙国强 E-mail:gqsun@163.com
  • 基金资助:
    国家自然科学基金资助面上项目(71872104);山西省哲学社会科学规划项目(2022YD093);山西省社科联重点项目(SSKLZDKT2022085)

Blockchain Technology, Supply Chain Networks and Data Sharing: Based on the Perspective of Evolutionary Game

Guo-qiang SUN1(),Yu-fei XIE2   

  1. 1.Research Center of Organization Innovation and Network Governance,Shanxi University of Finance and Economics,Taiyuan 030006,China
    2.School of Management Science and Engineering,Shanxi University of Finance and Economics,Taiyuan 030006,China
  • Received:2022-11-01 Revised:2023-05-15 Online:2023-12-15 Published:2023-12-20
  • Contact: Guo-qiang SUN E-mail:gqsun@163.com

摘要:

现有供应链网络自发形成的数据共享模式存在诸多弊端,区块链技术的发展和应用,为供应链网络数据共享提供了新路径。通过引入区块链技术,构建政府与供应链网络上下游子群三方演化博弈模型,分析三方策略的动态演化过程及其博弈均衡策略,并进行仿真分析。结果表明:首先,在区块链技术赋能下,三方初始意愿强弱对形成最终稳定均衡状态具有显著影响,有助于提高供应链网络数据共享效率。其次,提高数据共享激励和惩罚力度能够提高上下游子群数据共享意愿,而降低数据共享边际成本和投机收益可有效抑制上下游子群机会共享。再次,当激励力度大于临界值时,政府宽松监管,上下游子群倾向于数据共享;当而惩罚力度小于临界值时,政府严格监管,上下游子群也会选择机会共享策略,此时区块链监管失效。最后,监管成本越低、社会正负面效应作用越显著,政府部门越倾向于在监管中持续发力。通过对供应链网络上下游子群和政府部门三方协同机理分析,为新发展格局下供应链网络数字治理提供了理论支撑和决策依据。

关键词: 供应链网络, 区块链技术, 数据共享, 演化博弈, 仿真分析

Abstract:

Supply chain networks achieve precise coordination of supply and demand through real-time data sharing, reducing production blindness and mitigating the “bullwhip effect.” They also open up new market opportunities and generate comparative advantages, leading to steady improvements in productivity and breaking the zero-sum game of supply chain relationships. However, potential opportunism risks in actual transactions can result in a high failure rate of supply chain network cooperation, reaching 50%~70%. Therefore, intelligent technology is urgently needed to innovate the digital governance model of supply chain networks, solve data isolation problems and opportunism dilemmas, and promote digital transformation of supply chain networks. A three-party evolutionary game model of government and upstream and downstream subgroups in supply chain networks is constructed to explore the mechanism behind opportunity sharing behavior in supply chain networks and then blockchain technology is introduced to determine the optimal strategy choices of participating entities under different influencing factors. It analyzes the impact of initial willingness, costs, benefits, etc. on the willingness and efficiency of data sharing in supply chain networks and conducts simulation analysis. The results show that, first, under the empowerment of blockchain technology, the initial willingness of the three parties significantly affects the formation of the final stable equilibrium state, which helps to improve the efficiency of data sharing in supply chain networks. Second, increasing the incentive and punishment intensity of data sharing can increase the willingness of upstream and downstream subgroups to share data, while reducing marginal costs and speculative gains can effectively suppress opportunity sharing behavior. Third, when the incentive intensity is greater than the critical value, the government's loose regulation tends to promote data sharing behavior, while when the punishment intensity is lower than the critical value, the government's strict regulation also leads to opportunity sharing behavior, rendering the blockchain regulation ineffective. Finally, the lower the regulatory cost and the more significant the negative and positive social effects, the more the government is inclined to continue to exert supervision efforts. By analyzing the collaborative mechanism of the upstream and downstream subgroups and the government, theoretical support and decision-making basis are provided for digital governance of supply chain networks under the new development pattern.

Key words: supply chain network, blockchain technology, data sharing, evolutionary game, simulation analysis

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