市场营销系学术讲座系列第一百一十五讲

主 题：Making Recommendations More Effective Through Framings: Impacts of User- Versus Item-Based Framings on Recommendation Click-Throughs

主讲人: 盖嘉（伊拉斯谟大学）

时 间：2019-10-08 10:00

地 点：明德商学楼1007室

语 言：中英文

Abstract：

Companies frequently offer product recommendations to customers, according to various algorithms. This research explores how companies should frame the methods they use to derive their recommendations, in an attempt to maximize click-through rates. Two common framings—user-based and item-based—might describe the same recommendation. User-based framing emphasizes the similarity between customers (e.g., “People who like this also like...”); item-based framing instead emphasizes similarities between products (e.g., “Similar to this item”). Six experiments, including two field experiments within a mobile app, show that framing the same recommendation as user-based (vs. item-based) can increase recommendation click-through rates. The findings suggest that user-based (vs. item-based) framing informs customers that the recommendation is based on not just product matching but also taste matching with other customers. Three theoretically derived and practically relevant boundary conditions related to the recommendation recipient, the products, and other users also offer practical guidance for managers regarding how to leverage recommendation framings to increase recommendation click-throughs. 

Short biography：

Phyliss Jia Gai is a fifth-year PhD candidate in marketing management. She studies consumer behavior, focusing on digital consumption, self-control and ethics. Before joining RSM, she completed her Master degree in Social Science at University of Chicago and her Bachelor degree in Psychology at the Chinese University of Hong Kong.