Abstract: The frequent disclosure of the big data killing phenomenon in e-commerce market reveals the hidden danger of the moral hazard of e-commerce platforms. First, this paper establishes an evolutionary game model for the “killing behavior” of platforms in pricing and the channel choice of consumers under the supervision of the government. The results show that the punishment of the government plays a decisive role in avoiding the moral hazard of platforms. When the punishment is strong enough, the system will eventually converge to an ideal evolutionary stable strategies (ESS) of “Internet consumption, and fair pricing”. However, when the punishment is not strong enough, although the fairness concern of the consumers can affect the pricing strategy of the platforms to some extent, the system will converge to the ESS of “Internet consumption, and unfair pricing” or to a no ESS state. Consequently, the market will fall into the dilemma where consumers frequently encounter the problem of big data “killing” from e-commerce platforms. So, how should the trust crisis problem caused by the e-commerce market be resolved? Based on the above facts, an evolutionary game model under the mechanism of collaborative supervision of the governments and consumers is developed. This study indicates that the key factors that affect the supervision strategy of consumers are social incomes and supervision costs. The greater the difference between social benefits and supervision costs, the fast the evolution of the behavior of active supervision. Especially when the punishment of the government is not sufficient, the pressure of public opinion and the loss of image brought by the supervision of consumers can effectively restrain the killing behavior of the platforms. Moreover, the combination of reputation loss and government punishment can accelerate the evolution speed of avoiding the killing behavior of platforms, and force the platforms to make fair pricing. This paper can provide some implications for the design of supervision mechanism of big data “killing” in e-commerce market.

Key words: big data killing, e-commerce platforms, moral hazard, fairness concern, evolutionary game

摘要： 电商市场频频被披露隐性存在的大数据“杀熟”现象，暴露出电商市场存在平台道德风险问题的隐患。以政府监管为主导，建立电商平台“杀熟”定价行为及用户消费渠道选择的演化博弈模型，结果表明：政府的惩罚力度对平台道德风险问题的规避具有决定性的作用，当政府惩罚力度足够大时，系统稳定于（网络消费，公平定价）的理想情形；但如果政府惩罚力度不足，消费者的公平关切水平在一定程度上可以影响电商平台的定价策略，系统均衡结果将趋向于（网络消费，“杀熟”定价）或不存在演化稳定策略，电商市场陷入平台大数据“杀熟”的困境。那么，电商市场应如何破除大数据“杀熟”所造成的信任危机？基于此，建立政府和消费者协同监管机制下的演化博弈模型，研究得到：社会收益与监督成本是影响消费者监督策略的关键因素，社会收益与监督成本的差值越大，消费者选择“积极监督”行为的演化速度越快；而且，当政府惩罚力度不足时，消费者监督带来的舆论压力和声誉损失可以有效约束平台的“杀熟”行为，倒逼平台进行“公平定价”。研究结果对电商市场大数据“杀熟”行为监管机制的设计具有一定的启示。

关键词: 大数据“杀熟”, 电商平台, 道德风险, 公平关切, 演化博弈