How Do Recommender Systems Lead to Consumer Purchases a A Causal Mediation Analysis of a Field Experiment

• 成果类型: Article
• 署名作者: Li, Xitong; Grahl, Joern; Hinz, Oliver
• 署名单位: Hautes Etudes Commerciales (HEC) Paris; University of Cologne; Goethe University Frankfurt
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.2021.1074
• 发表日期: 2022
• 页码: 620-637
• 关键词: long tail; Information overload; empirical-analysis; search costs; IMPACT; CHOICE; MODEL; networks; identification; inference

摘要

How do recommender systems induce consumers to buy? Extant research neglects to examine the causal paths through which the use of recommender systems leads to consumer purchases. In this study, we conduct a randomized controlled field experiment on the website of an online book retailer and explore the causal paths by employing the recently developed causal mediation approach. Not surprisingly, the results show that the presence of personalized recommendations increases consumers' propensity to buy by 12.4% and basket value by 1.7%. More importantly, we find that these positive economic effects are largely mediated through affecting the consumers' consideration sets. Specifically, the presence of personalized recommendations increases both the size of consumers' consideration sets (breadth) and how intensively they are involved with each alternative in consideration (depth). It is the two changes that go on to increase consumers' propensity to buy and basket value. Furthermore, we find that the proportion of the total effects mediated through the breadth of consideration set is much larger and more significant than that mediated through the depth.