Average user ratings prompt disparate decision strategies in online retail shopping

Mark LaCour, Michael J. Serra

Research output: Contribution to journalArticlepeer-review

Abstract

Online shoppers have a vast array of information available to aid their purchasing decisions (e.g., average user ratings, histograms of ratings). Past research is ambiguous regarding the degree to which shoppers try to simplify this information integration process. Some results suggest that customers will invest a substantial amount of time and effort into the decision process, while others suggest that customers prefer to keep the process as simple as possible and avoid extra effort. In the present study, we sought to examine the conditions under which people will use heuristic strategies versus more analytic ones. We found that the average user rating plays a large role in determining which strategy customers use to integrate product information into a purchasing decision. We show that people use a “binary bias”—assessing the relative number of “high” and “low” ratings and choosing items with the more favorable ratio—when products have a lackluster (~three-star) average user rating. However, when average ratings are higher, customers instead use even simpler cues to make decisions. We also found evidence that individual differences in analytical thinking dispositions are associated with using more effortful information integration strategies. Thus, the present research suggests different strategies for displaying product information to customers depending on the average user ratings of the product and characteristics of the shoppers themselves.

Original languageEnglish
JournalJournal of Consumer Behaviour
DOIs
StateAccepted/In press - 2021

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