嘉　宾：孙辰朔 访问学者  清华大学

主持人：宋婷婷  副教授  上海交通大学安泰经济与管理学院

时　间：2025年3月12日（周三）10:00-11:30

地　点：上海交通大学徐汇校区安泰楼A305

内容简介:

Search aid technologies, especially pre-populated search bars, are growingly adopted by major players in the fast-growing e-commerce industry. Yet, surprisingly little is known about the effect of pre-populating search bars with keywords on online consumer journey. In this study, I designed and ran a randomized field experiment on a large e-commerce platform involving 72,587 customers who were randomly exposed to three types of keywords prefilled in the search bar. On the basis of individual customer-level analyses, this study finds that pre-populating trending category keywords encourages users to discover and buy items from these categories without reducing queries using self-entered keywords, ultimately leading to a 10.4% (8.8%) increase in purchase incidence (spending), compared to an empty search bar. Pre-populating personalized keywords brings about more focused product search within the categories recently browsed by users and results in a 21% (17%) increase in purchase incidence (spending), though this is offset by the negative effect due to a reduction in queries using self-entered keywords. Exposing niche category keywords shows little impact. I also find that a pre-populated search bar does not substitute the traffic and revenue generated through the other navigation tool, making it a beneficial addition to the focal ecommerce platform‘s performance. These findings draw timely implications for e-commerce managers, contributing to relevant literature on consumer search and product recommendation strategies on digital platforms.

演讲人简介：

Chenshuo Sun earned his Ph.D. from New York University Stern School of Business. He is now a visiting scholar at Tsinghua University. His work has been published in, or accepted by, journals such as Management Science, Information Systems Research, and Marketing Science. He serves on the Editorial Review Board of Management Science. His research has been recognized with the ISS Nunamaker-Chen Dissertation Award runner-up, the JP Morgan Chase AI Research Award, and multiple best paper awards at information systems conferences.

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