Advertising as Information for Ranking E-Commerce Search Listings

The authors thank Jack Lin, Xiliang Lin, Bo Long, Yun Xiao, Paul Yan, and JD.com’s search and ads teams for support with data access and business context. The authors also thank Brett Gordon; seminar participants at the Stanford Quant Marketing Seminar, Kellogg Quant Marketing Workshop, KAIST College of Business, Korea University Business School, Harvard Business School, Carnegie Mellon University Tepper School of Business, Indian Institute of Management Ahmedabad Brij Disa Centre for Data Science and Artificial Intelligence, Indiana University Kelley School of Business, Cornell SC Johnson College of Business, 2021 INFORMS Society for Marketing Science Marketing Science Conference, 2023 Artificial Intelligence in Management Conference, and 2023 Workshop on Platform Analytics; and Caio Waisman in particular for helpful comments and suggestions. The randomization involved in the experiment is covered by JD.com’s terms of service agreed via opt-in by users at the point of sign-up for the platform’s services. Yang served as a research intern at JD.com, Nair served as a consultant to JD.com, and Xi was an employee of JD.com during the time the study was conducted.