SPEAKER：Yang Wang（汪阳），Assistant Professor ，University of Wisconsin-Milwaukee

TIME/DATE：2025.6.12  14：00

CLASSROOM：A305

ABSTRACT：

Product reviews, a type of user-generated content (UGC), are found to affect sales; however, their impact on product returns has not been fully explored. Research has revealed that lofty descriptions and catchy images of products may increase returns, which spells trouble for retailers by increasing product returns. To address the issue, we explore how product contextualization in customer-posted images and review texts helps shoppers assess a product’s functionality and aesthetics and, in turn, reduce returns. Using the archival data from an outdoor gear and clothing retailer, we demonstrate that contextual cues in the reviews generally help reduce product returns. When comparing the role of images versus texts, we propose two mechanisms for shoppers’ utilization of contextual information in the UGC to evaluate functional features. The level of detail in writing suggests that contextual cues for these attributes (e.g., the warmth, flexibility, and water-resistance of a jacket) can be better conveyed through text instead of image because many of them can be measured on a scale (e.g., temperature), depicted in subtleties (e.g., running vs. jogging) and, occasionally, on a temporal dimension (e.g., a two-hour storm). As such, shoppers may prefer to use verbal descriptions to make purchases. Alternatively, the picture superiority effect suggests that processing visual information is much more efficient than processing text. Customers may sacrifice some level of detail by using images to assess the functionality. We examine the proposed explanations using experimental and survey studies. Although customers agree that contextual cues in texts are more accurate, detailed, and sufficient, they prefer to use the images to evaluate functional features. Regarding product aesthetics, since customers often adopt a sensory-based strategy to assess these attributes (e.g., color and design), images are likely to be a preferred choice. Our empirical findings support this conjecture. Yet, when a product’s aesthetics are tied to its geometric fit (e.g., the size of a tent), contextual cues in the text have a stronger effect on returns. We offer business insights about how to use UGC to better manage operating costs by reducing product returns.

GUEST BIO：

Dr. Yang Wang is an assistant professor of IT Management at the University of Wisconsin-Milwaukee, Lubar College of Business. His research focus is on the intersection of management information systems and business analytics. One particular topic he aims to address is product uncertainty in online markets. By collaborating with an online retailer specializing in outdoor clothing and gear, he applies multi-method to answer questions about how user-generated content helps online shoppers reduce pre-purchase product uncertainty and, in turn, reduce product returns. Another topic his research covers is the social impact of online misinformation, e.g., untruthful reviews, fake news, etc. His studies employ various quantitative approaches, including econometric modeling, machine learning algorithms, controlled experiments, etc.

Dr. Wang has published research works in various journals, including Information Systems Research, Decision Support Systems, Information Technology & People, Information Systems Frontier, etc. He has presented research projects at the International Conference on Information Systems (ICIS), ISMS Marketing Science Conference, Conference on Information Systems and Technology (CIST), and Workshop on Information Systems and Technology (WITS).