Do Fit Opinions Matter? The Impact of Fit Context on Online Product Returns
Presidential Professor and Emma Eccles Jones Presidential Chair of Information Systems
David Eccles School of Business, University of Utah
Friday, March 29, 2019
10:30 AM – noon
Speakman Hall Suite 200
Product fit uncertainty is cited as one of the top reasons for high online product return rates. In this study, we examine the informational role of online product fit opinions in helping reduce purchase errors that ultimately lead to product returns. Fit describes how well a product suits a consumer’s needs, and the value of a product drops sharply when it deviates from a consumer’s ideal fit. We investigate the impact of two types of structured product fit information – fit valence and fit reference – on online product returns of apparel goods, which is a product category especially sensitive to fit. Using the lens of advice-taking, we illustrate how the context (i.e. fit reference) of fit opinions helps a consumer better interpret fit valence. A change in the product review system at an online retailer allows us to use a natural experiment to examine the causal effects of such fit information from multiple advisors. We find that the availability of mere fit valence (e.g. whether the apparel is true to size or runs large/small) increases product returns; rather, it is the combination of fit valence and fit reference that drives a significant reduction in product returns. Applying generalized propensity score analysis, we observe a dynamic treatment effect and a 19.86% decrease in product return probability due to the combined fit information. The treatment effect increases when 1) a customer shares similar fit-related needs with the reviewers, and 2) the valence of fit opinions is dispersed. More interestingly, our results suggest that when fit context is provided, negative fit valence is especially helpful in reducing product returns. This study makes theoretical contributions to the understanding of advice-taking in matters of fit. Our findings are generalizable to situations where fit attributes dominate the product evaluation process. We provide business implications to online sellers grappling with high product return rates.
Olivia Sheng is Presidential Professor and Emma Eccles Jones Presidential Chair of Information Systems at the David Eccles School of Business, University of Utah. She also directs the Global Knowledge Management Center (http://gkmc.utah.edu) to seek research and education extension of business analytics, and organizes one of the first academic conferences on business intelligence/analytics (http://winterbaconf.org) annually.
Her research focuses on predictive and prescriptive analytics to address the needs in healthcare, marketing, social media, business relationship and performance, human resource, products and operations management. Her research has received funding from U.S. Food and Drug Administration, National Science Foundation, Overstock, Yahoo!, U.S. Army, IBM Tivoli, Toshiba Corp., Sun Microsystems, SAP University Alliance, and Wasatch Advisors. Currently, she engages companies in Utah such as Backcountry, Utah Transit Authority, University of Utah Health Services, and Intermountain Healthcare Company to collaborate on research and capstone projects related to big data analysis. Along with her collaborators, she was a recipient of the 2017 INFORMS Design Science Award. Her research publications received various media attention and professional recognitions.
Dr. Sheng received the B.S. degree from the National Chiao Tung University in Taiwan, R.O.C. and the Master’s and Ph.D. Degrees in Computers and Information Systems from the University of Rochester. Prior to University of Utah, she was on faculty of Management Information Systems at the University of Arizona since 1985 and was the Department Head from 1997 to 2002. Since 1995, Dr. Sheng visited and taught globally at different institutions including Hong Kong University of Science and Technology, Tokyo Institute of Technology, Shanghai Jiao Tung University, and Molde University College in Norway.