管理工程学报2025，Vol.39Issue(3)：119-135,17.DOI:10.13587/j.cnki.jieem.2025.03.009
竞争平台用户数据授权与定价策略选择及福利分析
Consumer data licensing and pricing strategy selection of competitive platforms and welfare analysis
摘要
Abstract
With the development of the platform economy,massive volumes of consumer data have become increasingly critical for production.For instance,platforms can track user browsing data to improve advertisement targeting,generating substantial benefits for the online advertising industry.However,collecting,processing,and monetizing user data can negatively affect consumers.First,the over-collection and misuse of user data can potentially infringe upon privacy.Second,using consumers' searching,purchasing,and browsing history data,platforms can infer consumers' willingness to pay and implement price discrimination.Although platforms claim that using consumer data enables them to offer data-based value-added services,such as personalization,consumers complain about privacy breaches and price discrimination.In the digital era,addressing conflicting interests between consumers and platforms is challenging. Empowering consumers to control their data has been increasingly emphasized worldwide to protect consumer rights.Notable examples include the Data Act launched by the European Union and the California Consumer Privacy Act enacted by the California State Legislature.In China,the Personal Information Protection Law and Opinions on Establishing a Data Base System to Maximize a Better Role of Data Elements were issued in response to the challenges of safeguarding consumer rights in the digital era;the latter proposes a hierarchical data licensing mechanism and requires platforms to use consumer data legally and reasonably per the consumer license agreement.All these policies require platforms to obtain consumer consent before data collection and usage. However,some platforms use long-winding privacy policy documents to prevent users from deciding whether to allow data tracking.For instance,Meta hinders users from choosing whether to consent to the platform processing personal data for targeted advertising through a privacy policy statement.In such cases,consumers are automatically enrolled in data tracking.However,some platforms give users the right to control their data and gain a competitive advantage.iPhone has recently rolled out an updated privacy policy to inform consumers about how apps collect and use data.This policy allows users to opt out of data tracking and has received widespread consumer acclaim.Market competition seems to motivate platforms to adopt hierarchical data-licensing mechanisms. As user data adds tremendous commercial value to platforms,platforms face tradeoffs between profitability and consumer privacy protection when choosing a data-licensing strategy.Moreover,as user data empowers platforms to implement price discrimination,platforms face a choice between uniform pricing and pricing discrimination.To examine platforms' selection of data licensing and pricing strategies,we consider four scenarios:1)competitive platforms adopt compulsory data licensing and uniform pricing,2)competitive platforms adopt hierarchical data licensing and uniform pricing,3)competitive platforms adopt compulsory data licensing and personalized pricing,and 4)competitive platforms adopt hierarchical data licensing and personalized pricing.We aim to address the following questions:which data licensing and pricing strategies are more profitable for platforms?Which data licensing and pricing strategies benefit consumers?How can regulatory mechanisms be designed to protect consumer welfare? To answer these questions,we analyze the equilibria under these four scenarios.The results show that,under uniform pricing,competitive platforms can set high prices with hierarchical data licensing because it increases consumers' willingness to pay.Moreover,when competitive platforms adopt hierarchical data licensing and personalized pricing,consumers' data licensing decisions depend on privacy costs,data-based value-added service levels,and service prices.We also compare market outcomes under the four scenarios.The results show that personalized pricing is more profitable for competitive platforms if they can use consumer data to improve advertising effectiveness considerably.Otherwise,competitive platforms prefer uniform pricing.However,if platforms can significantly enhance advertising effectiveness through consumer data usage,uniform pricing contributes to a higher consumer surplus than personalized pricing.Under uniform pricing,competitive platforms prefer hierarchical data licensing.By contrast,under personalized pricing,competitive platforms opt for compulsory data licensing when the data-based value-added service level is low.Regarding the consumer surplus,we found that it is beneficial to protect consumer interests if competitive platforms adopt hierarchical data licensing when the data-based value-added service level is low.Furthermore,if the data-based value-added service level is high,then compulsory data licensing can benefit consumers. In summary,the main findings of this study are as follows.First,when the data-based value-added service level is low,consumer surplus is better with hierarchical data licensing.However,personalized pricing induces competitive platforms to implement compulsory data licensing.Moreover,competitive platforms adopt personalized pricing to squeeze the consumer surplus;however,consumers prefer personalized pricing when it intensifies price competition.In such a case,if the government imposes monetary fines when platforms do not perform uniform pricing,the consumer surplus increases.Second,when the data-based value-added service level is moderate,market competition encourages self-regulation,benefiting both platforms and consumers.Third,when the data-based value-added service level is high,compulsory data licensing is preferred from a consumer perspective.关键词
数字经济/数据授权/平台定价/数据价值Key words
Digital economy/Data licensing/Platform pricing/Data value分类
管理科学引用本文复制引用
范昊雯,张玉林..竞争平台用户数据授权与定价策略选择及福利分析[J].管理工程学报,2025,39(3):119-135,17.基金项目
国家社会科学基金重大项目(21&ZD118) （21&ZD118）
国家自然科学基金项目(72071040) The Major Program of the National Social Science Foundation of China(21&ZD118) （72071040）
The National Natural Science Foundation of China(72071040) （72071040）
