The Incentive Mechanisms for Data Trading from the Perspective of Data Security——On the Governance of Data Trading Platforms
Data trading and sharing are keys to unleashing the value of data assets.However,while the development of digital technologies increases the demand for data,it simultaneously intensifies the risks associated with digital security,leading to a scenario where the potential value of data cannot be fully realized.From the perspective of data security,this paper develops a dynamic general equilibrium model encompassing three sectors including a data trading platform.It introduces decision-making processes within the data trading platform across three dimensions:data integration,data trading,and data security services.The study explores the impact of the governance of data trading platforms on the scale of data trading,investment in digital technology capital by firms,and consumer welfare.The findings reveal,firstly,that while transaction commissions imposed by data trading platforms increase the cost of data trading,they also encourage firms to trade more data by providing digital security services,resulting in an inverted U-shaped relationship between consumer welfare,the scale of data trading,and the commission rate.Secondly,due to the price distortions,the commission rate that maximizes the scale of data trading is lower than the rate that maximizes consumer welfare.Lastly,the equilibrium consumer welfare and scale of data trading are higher when commissions are levied on sellers as opposed to buyers,due to varying degrees of price distortions.This paper offers insights for the governance of data security and the design of incentive mechanisms for data trading platforms in the context of big data.
Data SecurityData TradingMechanism DesignData Trading PlatformsDigital Technology Capital
NETL
NSTL
万方数据
