How Recommendation Affects Customer Search: A Field Experiment

• 成果类型: Article; Early Access
• 署名作者: Yuan, Zhe; Chen, A. J. Yuan; Wang, Yitong; Sun, Tianshu
• 署名单位: Zhejiang University; University of Southern California; University of British Columbia; American University
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.2022.0294
• 发表日期: 2024
• 关键词: privacy regulation; systems; IMPACT; CHOICE; COSTS; channels; agents; sales; MODEL

摘要

Product recommendation and search are two technology -mediated channels through which e -commerce platforms can help customers find products. However, the relationship between the two channels and the underlying mechanisms and implications for platform design are not well understood. We leverage a randomized field experiment with 555,800 customers on a large e -commerce platform to investigate how product recommendation affects customer search. We vary the relevance of the recommendation that users experience upon arriving at the home page of the platform and find that a decrease in recommendation relevance leads to a significant increase in consumers' use of the search channel, indicating a (partial) substitution effect between the two at the aggregate level. We find substantial heterogeneity across product categories, propose a conceptual framework, and theorize how different states of customer demand-demand fulfillment and demand formation-may drive such heterogeneity. The results are aligned with our framework and provide evidence that both demand formation and fulfillment are at work in the channel interactions between recommendation and search. Specifically, when customers receive more product recommendations in a category, they search more in that category with generic query words, which indicates complementarity between recommendation and search. However, when customers receive fewer product recommendations in a category of interest, they compensate for this reduction by searching more in that category with long -tail query words, which indicates a substitution between recommendation and search. This experimental study is among the first to examine the causal relationship between the recommendation channel and search channel and offers implications for the design of e -commerce platforms.