讲者: 顾宪博士 美国印第安纳大学布卢明顿分校市场营销学助理教授

时间：2025年6月4日（周三） 14：00

地点: 同济大厦A楼402教室

课程描述 | DESCRIPTION

Open access (OA) provides free digital access to scholarly content without copyright restrictions, aiming to enhance knowledge visibility and accessibility. While increasingly adopted by OA platforms and publishers to broaden consumer reach, open access raises concern about potential revenue loss and fairness, as its impacts on book downloads and sales may differ across authors and consumer groups in ways that are not yet fully understood. This research addresses these issues through a randomized field experiment with a leading digital platform for academic content. Approximately 1,400 book titles were randomly assigned to a control group (no OA) or a treatment group (OA). Despite concerns, we show that open access significantly increases book downloads without reducing book sales on average. However, open access disproportionately reduces sales for books by female authors and has divergent effects across consumers — decreasing sales in lower GDP areas while increasing them in wealthier, more educated regions. Analysis of individual treatment effects reveals substantial heterogeneity: about half of the books experience increased sales, while the other half see declines. Further investigation reveals that open access tends to increase sales for older or less popular books, suggesting that its impact varies based on a book’s existing market presence. Our findings suggest that open access can expand readership without reducing average revenue, offering platforms and publishers a sustainable model to broaden impact. To maximize benefits, platforms and publishers should adopt differentiated release strategies based on a book’s age and popularity and address equity concerns arising from heterogeneous effects across author and consumer socioeconomic backgrounds.

GUEST BIO | 讲者介绍

Dr. Xian Gu is an Assistant Professor of Marketing at the Kelley School of Business at Indiana University. She received her Ph.D. in Marketing from the University of Maryland in 2019. Her research interests are in quantitative marketing with applications of econometric models, machine learning techniques, and Bayesian methods to the substantive areas of digital marketing, focusing on influencer marketing, live streaming, freemium, and mobile marketing.