Preference Elicitation for Algorithmic Personalization
Prof. Phyliss Jia Gai
Assistant Professor of Marketing,
Guanghua School of Management,
Peking University
Date: 20 May 2025 (Tuesday)
Time: 10:30-12:00
Venue: E22-G015
Host: Prof. Li Yan, Associate Professor in Marketing
Abstract
Companies and platforms frequently request consumers to indicate their preferences to generate personalized content, assuming that users will reveal their full range of interests. However, a series of experiments, including several conducted on custom-built platforms, reveals that consumers often omit interests that they would otherwise select or consider when sharing their preferences with algorithms. This tendency arises because 1) consumers believe that sharing narrow preferences reduces the risk of being misclassified by algorithms, and 2) they do not adequately consider all predefined categories of interest. Two separate research projects document these distinct processes. Crucially, the preferences shared by consumers create a feedback loop: those who select narrow preferences receive less diverse recommendations, which further narrows their choices and subsequent recommendations. Our findings thus delineate the conditions under which filter bubbles are generated and dismantled, suggesting that simple yet effective design features can significantly alter the content that individuals are exposed to and engage with.
Speaker
Prof. Phyliss Jia Gai is the Assistant Professor of Marketing at Guanghua School of Management, Peking University. She investigates consumer behavior, with a particular interest in digital consumption. Her research has been published in Journal of Consumer Research, Journal of Marketing, and Journal of Experimental Psychology: General, among others. Before joining Guanghua, she earned her PhD at Rotterdam School of Management, Erasmus University in the Netherlands.
All are welcome!
