報(bào)告時(shí)間：2025年4月10日（星期四）14:30-17:00
報(bào)告地點(diǎn)：工程管理與智能制造研究中心725會(huì)議室
報(bào) 告 人：Chenshuo Sun researcher
工作單位：清華大學(xué)
舉辦單位：管理學(xué)院
報(bào)告簡(jiǎn)介：
Search aid technologies, especially pre-populated search bars, are increasingly 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. On the basis of individual customer-level analyses, this study finds that pre-populating trending keywords boosts purchases by 10.4% (spending +8.8%) without reducing self-entered queries. Personalized keywords increase purchases by 21% (spending +17%) but reduce self-entered queries. Niche keywords have little impact. I also find that pre-filled search bars complement, rather than replace, other navigation tools. These findings draw timely implications for ecommerce managers, contributing to relevant literature on consumer search and product recommendation strategies on digital platforms.
報(bào)告人簡(jiǎn)介：
Chenshuo Sun earned his Ph.D. from New York University Stern School of Business. He is now a researcher 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.
