信息不对称下个人健康数据交易双边定价策略研究  

Two-sided pricing strategy for personal health data trading under information asymmetry

作　　者：郭鑫鑫 王海燕[1] 孔楠 GUO Xinxin;WANG Haiyan;KONG Nan(School of Economics and Management,Southeast University,Nanjing 211189,China;College of Engineering,Purdue University,West Lafayette,Indiana 47906,USA)

机构地区：[1]东南大学经济管理学院,江苏南京211189 [2]普渡大学工程学院,印第安纳州西拉法叶47906

出　　处：《管理工程学报》2022年第4期129-139,共11页Journal of Industrial Engineering and Engineering Management

基　　金：国家自然科学基金资助项目(72071042、71531004)。

摘　　要：数据交易平台为健康数据所有者与健康数据需求者交易健康数据提供了场所,如何基于健康数据供需双方交易意愿和收益情况确定公平合理的双边交易价格是数据交易平台面临的关键问题。考虑到数据交易平台与健康数据所有者和健康数据需求者之间存在双边信息不对称,本文采用迭代双边拍卖方法设计健康数据交易分配规则和定价/奖励规则。为了协调健康数据所有者与健康数据需求者间的利益矛盾,以健康数据交易系统收益最大化为目标分配健康数据交易任务,计算最优的健康数据供给报价和需求报价;考虑到健康数据所有者和健康数据需求者是理性的,设计最优的健康数据交易双边定价策略,以实现各自收益最大化。最后,本文通过设计分布式迭代算法来计算实现市场出清的最优健康数据供需报价、任务分配和双边交易价格,并以数粮平台为案例验证所提出的健康数据交易双边定价策略的有效性。研究发现:数据交易平台对健康数据所有者设计的最优交易价格与其提交的供给报价呈负相关关系;而对健康数据需求者设计的最优交易价格等于其提交的需求报价。从实践角度来讲,本文研究结论为数据交易平台开展健康数据交易撮合服务提供了有效支持,能够在一定程度上缓解健康数据供需矛盾,推动健康数据的市场流动。At present,there are many health data demanders(e.g.,government,relevant enterprises in the health industry etc.)in the market who want to obtain a large amount of personal health data to provide better health services.While health data generated by individuals is scattered in various wearable health devices or applications,which has not been collected and managed uniformly,so that the application value cannot be fully mined.Facing the conflicting interests between supply and demand on the health data market,data trading platforms provide a place for individuals,namely the owners of health data,to trade health data with health data demanders.Due to the existence of information asymmetry between the data trading platform with health data owners and health data demanders,how to design a fair and reasonable health data trading pricing strategy is an important challenge for the data trading platform.Given the unique nature of personal health data,some common pricing methods cannot be effectively applied to health data trading through a crowdsensing mode.Therefore,according to the analysis of trading willingness and interest conflict between health data owners and demanders,this paper proposes to use the iterative double auction method to design a task allocation mechanism and pricing strategy of health data trading.In the process of health data trading,the data owners and demanders rationally decide whether to participate in the trading.When collecting personal health data through the crowdsensing mode,individuals will not only obtain monetary rewards,but also internal benefits(e.g.,increasing understanding of their own health status,obtaining corresponding health service guidance,etc.).Therefore,based on the analysis of the supply behavior of health data owners and the demand behavior of health data demanders,this paper constructs an income function model of health data owners and demanders.The income functions of both parties are private information,thus there is two-sided information asymmetry in the process of he

关 键 词：个人健康数据交易 信息不对称 双边定价 迭代双边拍卖 分布式迭代算法 

分 类 号：C939[经济管理—管理学]