摘要
当前我国企业间数据自由流通水平较低,不仅未能充分释放数据价值,甚至还引发数据垄断问题,导致新型产业发展受阻。故此,促进数据开放共享成为理论界和实务界讨论的焦点,但鲜有研究关注应采取何种措施才能有效激励企业积极共享数据。利用演化博弈分析方法,构建政府不同介入策略对企业数据共享行为影响的演化博弈模型,通过仿真模拟求得演化稳定策略。研究结果表明:政府和企业的策略选择与双方的相对净支付密切相关,当双方选择不同策略的相对净支付不断变化时,出现多种演化稳定均衡。政府选择直接激励策略、数据共享所需的技术成本减少和法律风险降低将有助于提升企业积极共享数据的意愿。促进企业积极共享数据的有效办法是,出台直接激励数据共享的政策、推进数字基础设施建设、健全数据分级分类保护制度。
At present,the low level of data free circulation among enterprises in China not only fails to fully release the data value,but also causes the problem of data monopoly,leading to the development of new industries.Therefore,the promotion of open data sharing has become the focus of discussion in the theoretical and practical circles,but few studies have focused on what measures should be taken to effectively motivate enterprises to actively share data.By using the evolutionary game analysis method,an evolutionary game model of the influence of different government intervention strategies on enterprise data sharing behavior is constructed,and the evolutionary stable strategy is obtained through simulation.The results show that the strategic choice for the government and the firm is closely related to the relative net payment of both sides.When the relative net payment of different strategies chosen by both sides is constantly changing,there are multiple evolutionary stable equilibrium.The government’s choice for direct incentive strategies,the reduction of technical costs and legal risks required for data sharing will help increase companies’willingness to actively share data.The effective way to encourage enterprises to actively share data is to introduce policies that directly encourage data sharing,promote the construction of digital infrastructure,and improve the classification and protection system of data.
作者
陈柳汐
李谢标
Chen Liuxi;Li Xiebiao(Law School,South China University of Technology,Guangzhou 541000,Guangdong,China)
出处
《征信》
北大核心
2023年第10期51-60,共10页
Credit Reference
基金
国家社会科学基金重大研究专项项目(19VHJ005)
国家社会科学基金项目(19BFX141)。
关键词
数字经济
数据共享
演化博弈
数据资源
策略选择
激励监管
digital economy
data sharing
evolutionary game
data resources
strategy choice
incentive supervision
作者简介
陈柳汐(1997-),女,广西桂林人,在读博士,主要研究方向为数字创新、数据治理;李谢标(1997-),男,广东揭阳人,在读博士,主要研究方向为数据法学、政策研究。
