“大数据杀熟”可以避免吗?——电子商务逆向选择风险规避
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摘要
新兴的电子商务为消费者提供更多选择及更便利的购物场景,也同时利用大数据技术采集了消费者的消费数据,绘制了用户画像,部分厂商甚至采用"大数据杀熟"制定了价格歧视定价策略,产生了逆向选择的风险问题。本文基于经典的Akerlof的"柠檬"问题理论模型,在电子商务市场框架下研究商家与顾客间的信息非对称情况,并通过爬虫技术对天猫商城的购物数据进行了实证分析。本文研究发现,消费者对于商品价格信息的披露最为敏感,与购买意愿的关联度最高;卖家信用与商品评价项目的信息披露与商品的逆向选择现象之间存在一定的负相关性,可以有效消除"大数据杀熟"的风险。
Emerging e-commerce provides consumers with more choices and more convenient shopping scenarios. At the same time, it uses big data technology to collect consumer data and draw user portraits. Some manufacturers even use"big data to kill". A price discrimination pricing strategy has been developed, which has created a risk of adverse selection. Based on the classic "Lemon" problem model of Akerlof, this paper studies the information asymmetry between merchants and customers under the framework of e-commerce market, and empirically analyzes the shopping data of Tmall Mall through crawler technology. This paper finds that consumers are most sensitive to the disclosure of commodity price information and have the highest correlation with purchase intention; there is a certain negative correlation between the information disclosure of seller credit and commodity evaluation projects and the reverse selection of commodities, which can effectively eliminate The risk of "big data killing".
Emerging e-commerce provides consumers with more choices and more convenient shopping scenarios. At the same time, it uses big data technology to collect consumer data and draw user portraits. Some manufacturers even use"big data to kill". A price discrimination pricing strategy has been developed, which has created a risk of adverse selection. Based on the classic "Lemon" problem model of Akerlof, this paper studies the information asymmetry between merchants and customers under the framework of e-commerce market, and empirically analyzes the shopping data of Tmall Mall through crawler technology. This paper finds that consumers are most sensitive to the disclosure of commodity price information and have the highest correlation with purchase intention; there is a certain negative correlation between the information disclosure of seller credit and commodity evaluation projects and the reverse selection of commodities, which can effectively eliminate The risk of "big data killing".
引文
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[2]徐旭、刘红军.基于BP神经网络模型的移动电子商务用户信任评价[J].统计与决策,2016(10).
[3]洪亮、任秋圜、梁树贤.国内电子商务网站推荐系统信息服务质量比较研究--以淘宝、京东、亚马逊为例[J].图书情报工作,2016(23).
[4]Ichihashi S.Online Privacy and Information Disclosure by Consumers[J].Social Science Electronic Publishing,2018.
[5]邹开亮、刘佳明.大数据“杀熟”的法律规制困境与出路--仅从《消费者权益保护法》的角度考量[J].价格理论与实践,2018(8).
[6]胥雅楠、王倩倩、董润、汪辛怡、吴峥.“大数据杀熟”的现状、问题与对策分析[J].改革与开放,2019(1).