A Sequential Search Model with Partial Depth Evaluation

Improvement in infrastructure and advances in information technology have strived to make both online and offline store visits better experiences and less costly for consumers. In addition, on-site product information search has been unprecedentedly facilitated by provisions of tools such as mobile store apps, search engines, screening/sorting aids, and better in-store display etc. With the decrease in the cost to visit stores, may firms have an incentive to facilitate consumers’ information collection and evaluation on product attributes? This paper attempts to shed light on this important question with a model that considers both travel cost (transportation cost between firm visits) and search cost (product evaluation cost) and explores how they affect consumer search behavior and firms’ pricing decisions. Specifically, consumers make a trade-off between how many attributes to evaluate (search depth) and whether continuing the search to the next firm (search breadth). We extend the classical framework for sequential search developed by Wolinsky (1986) and Anderson and Renault (1999) by letting consumers choose search depth at each step. The analysis reveals a novel interaction effect: lower (higher) search cost benefits firms if travel cost is lower (higher). Thus, facilitating consumers’ product evaluation may benefit firms in the context of reduced travel cost. Critically, we show that this interaction effect occurs only when search depth is endogenous with partial-depth search as the result. In addition, we show that travel and search costs may play opposite roles on depth and prices—they increasing (decreasing) in travel (search) cost. Relevant managerial implications are discussed.