遏制大数据“杀熟”:政府主导的协同治理模式

Curb Swindling Money out of Old Customers by Big Data: A Collaborative Governance Model Led by the Government

大数据“杀熟”是数字经济时代的独特产物,其产生的消极影响引发了社会公众的担忧与批判。理性看待大数据“杀熟”,辨析其与价格欺诈、个性化定价、价格歧视等相关概念的关系,廓清不同概念之间的交织边界,是辩证认识和深入理解大数据“杀熟”并提出有效治理方案的前提条件。传统“二元分散治理”模式无法应对大数据“杀熟”的复杂问题,构建“政府主导、多元参与”的协同治理新格局是一种回应现实需求的有益探索,主要通过发挥政府的核心优势,建立多元主体间的协作与互动,完善协同治理的顶层设计与权责分工,利用文化渲染和激励手段增加协同治理参量,以此达成政府与平台商户、消费者协同遏制大数据“杀熟”的治理目标。

Swindling money out of old customers by big data is a unique product of the digital economy era. The negative effects it produces have aroused the concern and criticism of the public. A rational view of swindling money out of old customers by big data, identifying its relationship with price fraud, personalized pricing, price discrimination and other related concepts, and clarifying the intertwined boundaries between different concepts are the preconditions for a dialectical and in-depth understanding as well as effective measures for this phenomenon. The traditional “dual decentralized governance” model cannot deal with the complex problem of swindling money out of old customers by big data. Building a new pattern of collaborative governance with “government leading and multiple participation” is a beneficial exploration to respond to the actual needs, mainly by giving full play to the core advantages of the government, establishing cooperation and interaction among multiple subjects, improving the top-level design and division of rights and responsibilities of collaborative governance, using cultural impact and incentives to increase collaborative governance parameters, so as to achieve the governance goal of curbing swindling money out of old customers by big data with the joint efforts of the government, platform merchants and consumers.