Research on the Behavior and Governance Countermeasures of Big Data “Killing” on E-Commerce Platform

随着数字经济的迅猛发展,电商平台大数据“杀熟”行为逐渐凸显,引发社会各界广泛关注,大数据“杀熟”是电商平台基于用户画像和行为数据,对老用户或高消费群体实施差异化定价的行为,其本质是一种算法驱动的价格歧视。本文聚焦电商平台大数据“杀熟”的基本内容,从定义、表现形式及特征入手,分析了大数据“杀熟”的隐蔽性、广泛性及其对市场公平与消费者权益的侵害,并从商业伦理缺失、大数据技术滥用、消费者与平台之间信息不对称及法律监管困境四个方面探讨其成因。针对这些问题,本文提出强化平台企业伦理建设、规范大数据技术应用、打破信息不对称格局、完善法律与监管体系的治理对策,以创造更加公平的市场竞争环境,促进电商行业健康可持续发展。With the rapid development of the digital economy, the big data “killing” behavior of e-commerce platforms has gradually become prominent, which has aroused widespread concern in all sectors of society. Big data “killing” is the behavior of e-commerce platforms to implement differentiated pricing for old users or high-consumption groups based on user portraits and behavioral data. Its essence is an algorithm-driven price discrimination. This paper focuses on the basic content of the big data “killing” of e-commerce platform. Starting from the definition, expression form and characteristics, this paper analyzes the concealment and universality of the big data “killing” and its infringement on market fairness and consumer rights and interests, and discusses its causes from four aspects: lack of business ethics, abuse of big data technology, information asymmetry between consumers and platforms, and legal supervision dilemma. In view of these problems, this paper puts forward countermeasures to strengthen the ethical construction of platform enterprises, standardize the application of big data technology, break the pattern of information asymmetry, and improve the legal and regulatory system, so as to create a more fair market competition environment and promote the healthy and sustainable development of the e-commerce industry.

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Publication Details

Journal
E-Commerce Letters
Published
2025-01-01
DOI
https://doi.org/10.12677/ecl.2025.1451418
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
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article

Research on the Behavior and Governance Countermeasures of Big Data “Killing” on E-Commerce Platform

文婷 宋
E-Commerce Letters
Impact of AI and Big Data on Business and Society
article

Research on the Behavior and Governance Countermeasures of Big Data “Killing” on E-Commerce Platform

文婷 宋
article en

Abstract

随着数字经济的迅猛发展,电商平台大数据“杀熟”行为逐渐凸显,引发社会各界广泛关注,大数据“杀熟”是电商平台基于用户画像和行为数据,对老用户或高消费群体实施差异化定价的行为,其本质是一种算法驱动的价格歧视。本文聚焦电商平台大数据“杀熟”的基本内容,从定义、表现形式及特征入手,分析了大数据“杀熟”的隐蔽性、广泛性及其对市场公平与消费者权益的侵害,并从商业伦理缺失、大数据技术滥用、消费者与平台之间信息不对称及法律监管困境四个方面探讨其成因。针对这些问题,本文提出强化平台企业伦理建设、规范大数据技术应用、打破信息不对称格局、完善法律与监管体系的治理对策,以创造更加公平的市场竞争环境,促进电商行业健康可持续发展。With the rapid development of the digital economy, the big data “killing” behavior of e-commerce platforms has gradually become prominent, which has aroused widespread concern in all sectors of society. Big data “killing” is the behavior of e-commerce platforms to implement differentiated pricing for old users or high-consumption groups based on user portraits and behavioral data. Its essence is an algorithm-driven price discrimination. This paper focuses on the basic content of the big data “killing” of e-commerce platform. Starting from the definition, expression form and characteristics, this paper analyzes the concealment and universality of the big data “killing” and its infringement on market fairness and consumer rights and interests, and discusses its causes from four aspects: lack of business ethics, abuse of big data technology, information asymmetry between consumers and platforms, and legal supervision dilemma. In view of these problems, this paper puts forward countermeasures to strengthen the ethical construction of platform enterprises, standardize the application of big data technology, break the pattern of information asymmetry, and improve the legal and regulatory system, so as to create a more fair market competition environment and promote the healthy and sustainable development of the e-commerce industry.

E-Commerce LettersVol. 14(05)
Decent work and economic growth
Openalex Percentile: Top 88%
Impact of AI and Big Data on Business and Society
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