Choice Overload with Search Cost and Anticipated Regret : Theoretical Framework and Field Evidence

As consumers are offered an ever-increasing number of options for almost every purchase decision in online retail, understanding the impact of assortment size on consumer choice decisions––especially on both search and purchase behavior––is critical. Our research speaks to this question by combining empirical analyses with theoretical modeling. First, via a large-scale field experiment involving $1.6$ million consumers on Alibaba's online retail platforms, we causally examine how consumers' click and purchase behavior changes as the number of products in a choice set increases. We document that consumers' likelihood of clicking or purchasing at least one product increases at first but then decreases as the number of offered products rises. To explain this inverted-U-shaped relationship, we develop a ``consider-then-choose-with-regret" (CTCR) choice model that incorporates consumers’ search cost and anticipated regret. Numerical experiments suggest that our CTCR model leads to smaller optimal assortments containing products of higher expected utilities and lower prices on average than the classical multinomial logit choice model. Altogether, this work presents real-world experimental evidence for choice overload on both search and purchase behavior, advances the field's understanding of how assortment sizes alter consumer choices, and provides a theoretical foundation for incorporating the choice overload effect in operational decisions