政府-平台电商协同监管大数据"杀熟"的演化博弈研究
Research on the evolutionary game theory of government-platform e-commerce collaborative regulation of big data"killing off"
王海燕 1赵久富 2郑雪琪 1张娜 1毛昭军3
作者信息
- 1. 南京信息工程大学商学院,南京 210044
- 2. 31700 部队,辽阳 111000
- 3. 军事科学院系统工程研究院,北京 100091
- 折叠
摘要
为有效遏制数字经济背景下平台卖家大数据"杀熟"行为,推动平台经济高质量发展,文中在现有研究基础上,以演化博弈理论为核心,分析了信息不对称情境下政府、平台电商与平台卖家间的利益博弈关系,构建了协同监管激励机制模型.通过引入政府规制,求解政府与平台电商最优惩罚力度、最优激励监管系数以及各主体行为演化方向,讨论大数据"杀熟"监管时各外生变量对各主体最优策略选择的影响,证明了协同监管的优越性与必要性,为网络交易市场监管提供理论参考.
Abstract
To effectively curb the big data"killing off"behavior of platform sellers in the context of the digital e-conomy and promote the high-quality development of the platform economy,this paper,based on existing re-search and using evolutionary game theory as the core,analyzes the interest game relationship between the gov-ernment,platform e-commerce,and platform sellers in the context of information asymmetry,and constructs a collaborative regulatory incentive mechanism model.By introducing government regulations,the optimal punish-ment intensity,optimal incentive supervision coefficient,and evolution direction of each entity's behavior for e-commerce between the government and the platform are solved.The impact of exogenous variables on the optimal strategy selection of each entity during big data"killing off"regulation is discussed,the superiority and necessity of collaborative regulation proven,and theoretical reference provided for the regulation of online trading markets.
关键词
数字经济/大数据"杀熟"/演化博弈/数值仿真Key words
digital economy/big data"killing off"/evolutionary game/numerical simulation引用本文复制引用
出版年
2024
NETL
NSTL
万方数据