电商平台信用信息共享策略演化  

Evolutionary dynamics of E-commerce platform's credit information sharing strategy

作　　者：杨丰梅[1] 王安瑛 吴军[2] 汤铃 Yang Fengmei Wang Anying Wu Jun Tang Ling(School of Science, Beijing University of Chemical Technology, Beijing 100029, China School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China School of Economics and Management, Beihang University, Beijing 100191, China)

机构地区：[1]北京化工大学理学院,北京100029 [2]北京化工大学经济管理学院,北京100029 [3]北京航空航天大学济管理学院,北京100191

出　　处：《系统工程学报》2017年第5期596-603,共8页Journal of Systems Engineering

基　　金：国家自然科学基金资助项目(71433001;71301006;71372195)

摘　　要：作为电子商务的主要媒介,电商平台可记录入驻商户和消费者的交易信息,实现对双方信用的有效评估,故电商平台间的信用信息共享策略,能有效改善我国互联网信用环境.对此,基于演化博弈理论,构建了共享策略基础博弈模型,并考虑互联网环境中电商平台数量有限的情形,引入Moran过程分析共享策略的随机演化动态,以探讨促使电商平台选择信用信息共享策略的有利条件.研究发现,通过降低共享数据处理成本、加大非合作的惩罚力度、增强面向优质商户的优惠政策等手段,能有效激励各电商平台达到信息共享策略的稳定状态.此外,数值算例充分论证了模型的有效性及政策建议的合理性.As the major media of E-commerce market, E-platforms can record the online trading activities of merchants and consumers, and thus their respective credits are effectively evaluated. Therefore, the sharing strategy of credit information among platforms can help improve E-commerce credit environments, especially in China. In such a context, this paper establishes a game model of information sharing strategy based on evolutionary game theory, and employs the Moran process, assuming a limited number of agents to analyze the corresponding random evolution, to explore the conditions for credit information sharing cooperation. The results strongly suggest that reducing costs of processing shared data, enhancing penalties on noncooperation and developing reward policies for high-credit merchants can help platforms reach a steady state of information sharing cooperation. Furthermore, the numerical experiment verifies the validity of the proposed model and the corresponding policy implications.

关 键 词：电商平台 信用 信息共享 Moran过程 随机演化博弈 

分 类 号：F270[经济管理—企业管理]