Personal data has become a key input in Internet Commerce, facilitating the matching between millions of customers and merchants. Recent data regulation in China, Europe and US restricts Internet platforms’ ability to collect and use personal data for personalized recommendation and may fundamentally impact Internet Commerce. In collaboration with the world’s largest E-commerce platform, we conduct a large-scale field experiment to measure the potential impact of data regulation policy, and to understand the value of personal data in Internet Commerce. For a large and random subset of the customers on the platform, we simulate the regulation by banning the use of personal data in the homepage recommendation algorithm and record the matching process and outcomes between these customers and merchants. Compared to the control group using personal data, we observe a significant change in the algorithmic recommendation of product matching in the treatment group and a very sharp decrease in the matching outcomes as measured by both customer engagement (clickthrough rate and number of products browsed) and market transaction (GMV). The negative effect is disproportionate and more pronounced for niche merchants and customers who would benefit most from E-commerce. We further find evidence that the ban of personal data significantly increases customers’ search cost on the platform and may reduce their welfare gained from E-commerce. We discuss the economic impact of data regulation on Internet Commerce in the short and long run, as well as the role of personal data in creating value and fostering innovations in the Digital Economy.
A buffet lunch will be available at 11:45 am. The talk will begin at 12:00 pm.
Tianshu is the Robert R. Dockson Assistant Professor of Business Administration at the Marshall School of Business, University of Southern California, with a joint appointment in the department of computer science.