Research on Data Quality Optimization Strategy Based on Tripartite Evolutionary Game Theory
With data being traded as a factor of production,improving data quality and breaking through the mismatch between supply and demand are of great significance.This paper uses evolutionary game theory to construct a tripartite evolu-tionary game model involving data trading platforms,data suppliers,and data demanders.It analyzes the strategic evolution paths and influencing factors of each participating entity,followed by numerical simulation and case analysis combined with the busi-ness history of Guiyang Big Data Exchange.The conclusion is that an increase in platform transaction volume and the willing-ness of demanders to purchase contribute to the platform's high investment in guiding the improvement of data quality;The strategic choices of data suppliers are related to the direct and indirect benefits of providing high-quality data and the costs of additional expenditures;The higher the data quality and the more benefits created for enterprises,the more it will motivate de-manders to purchase high-quality data.Based on this,we should improve the incentive mechanism to enhance the enthusiasm of the main participants;Adjust the business model to improve the service level of the platform;And build a collaborative opti-mization system to promote the circulation of high-quality data.
data tradingdata qualitythree party evolutionary gameGuiyang Big Data Exchange
NETL
NSTL
万方数据
