91九色

时间Time: 2025年12月17日（北京时间Beijing Time） 08:15AM - 10:40AM

地点Venue: 线上会议（Zoom）

会议链接Zoom Link: //tennessee.zoom.us/j/89752059595

会议密码Password: 999999

【讲座一】How Does Best Seller Recommendation Shape the Ecosystem of an Online Marketplace?

主讲人Speaker: Yi Xu, University of Maryland

时间Time: December 16（12月16日）, 7:15PM-8PM EST（12月17日上午 08:15 - 09:00 Beijing北京时间）

摘要Abstract: 

This paper studies the impact of the bestseller recommendation on sellers and the online platform. In a two-period model, competing sellers decide their prices, while consumers form their consideration set and search products within it before purchasing. With the bestseller recommendation, a consumer randomly searches in the first period, but she will definitely include the bestseller of the first period in their consideration set in the second period. Our model explores the dual effects of the bestseller recommendation: The informational effect leads to higher perceived value of the bestseller, and the search effect results in the guaranteed spot in the consumer's consideration set in the second period. We show that the bestseller recommendation system can increase price competition among sellers and lead to lower equilibrium prices compared to a no-recommendation scenario. This intensified competition is due to both the information and search effects of the recommendation system, which, while giving an edge to the bestseller in the second period, prompts non-bestsellers to lower their prices to remain competitive aggressively. Furthermore, the study reveals that the bestseller recommendation system can hurt sellers and the platform due to intensified price competition. The bestseller recommendation can be profitable when there's an outside option for consumers, as it induces a demand-enhancing effect. It also leads to a divergence in platform and seller interests, with sellers potentially disfavoring the recommendation system, even though the platform might benefit from its use. These insights underscore the complexity of implementing a bestseller recommendation system and the need for platforms to consider various factors when adopting such systems.

【讲座二】Regulating Powerful Platforms

主讲人Speaker: Allen Zhuoxin Li, University of Wisconsin

时间Time: December 16（12月16日）, 8:05PM-8:50PM EST（12月17日上午 09:05 - 09:50 Beijing北京时间）

摘要Abstract:

Platform giants typically possess strong power over other participants on the platforms. Such power asymmetry gives platform owners the edge on setting platform fees to capture the surplus created on their platforms. While there is a heated debate on regulating these powerful platforms, the lack of empirical studies hinders the progress toward evidence-based policymaking. This research empirically investigates this regulatory issue in the context of on-demand delivery. Delivery platforms (e.g., DoorDash) charge restaurants a commission fee, which can be as high as 30% per order. To support small businesses, recent regulatory scrutiny has started to cap the commission fees for independent restaurants. This research empirically evaluates the effectiveness of platform fee regulation, by investigating recent regulations across 14 cities and states in the United States. Our analyses show that independent restaurants in regulated cities (i.e., those paying reduced commission fees) experience a decline in orders and revenue, whereas chain restaurants (i.e., those paying the original fees) see an increase in orders and revenue. This intriguing finding suggests that chain restaurants, not independent restaurants, benefit from the regulations that were intended to support independent restaurants. We find that platforms’ discriminative responses to the regulation may explain the negative effects on independent restaurants. That is, after cities enact commission fee caps, delivery platforms become less likely to recommend independent restaurants to consumers, and instead turn to promote chain restaurants. Moreover, delivery platforms increase their delivery fees for consumers in regulated cities, suggesting that these platforms attempt to cover the loss of commission revenue by charging customers more.

【讲座三】AI-Augmented Healthcare Workflows

主讲人Speaker: Simrita Singh, Santa Clara University

时间Time: December 16（12月16日）, 8:55PM-9:40PM EST（12月17日上午09:55 - 10:40 Beijing北京时间）

摘要Abstract: 

This talk tackles the practical challenges of integrating AI into real-world healthcare. We'll first explore how to best design AI-augmented patient pathways. Is AI better suited as a 'gatekeeper,' a 'second opinion,' or neither? Then, we'll address a common scenario where AI algorithms generate probabilities for dozens of potential diseases. Given this complex, multidimensional starting point, what's the most effective sequence of diagnostic tests to arrive at the right diagnosis? We'll discuss a framework for navigating this uncertainty to optimize the diagnostic process.

主讲人简介Bios:

Yi Xu

Yi Xu is Professor of Operations Management at the Robert H. Smith School of Business at the University of Maryland. He received his Ph.D. in Operations Management from The Wharton School, University of Pennsylvania. His research interests are in online platform operations, sharing economy, pricing, and innovation management. His research articles have appeared in Management Science, Marketing Science, Production and Operations Management, and Manufacturing and Service Operations Management, among others. He is a Senior Editor of Production and Operations Management. Professor Xu teaches Operations Management, Pricing and Revenue Management, and Lean Management in the MBA, MS, EMBA and Executive Education Programs at the Smith School. He has taught for and consulted with several Fortune 500 companies, government agencies and non-profit organizations. Professor Xu has been a frequent presenter and speaker at international conferences.

Zhuoxin Allen Li

Professor Zhuoxin "Allen" Li is the Michael and Mary Sue Shannon Professor and an Associate Professor in the Department of Operations and Information Management. He is also a faculty affiliate in the Data Science Institute (DSI) and the Pan Asia Pacific Sustainability Initiative (PAPSI) at UW-Madison. He is a recipient of the National Science Foundation (NSF) CAREER Award, Poets & Quants Top 50 Undergraduate Business Professors (2021), Sandra A. Slaughter Early Career Award (2023), the Gordon B. Davis Young Scholar Award (2020), and the Nunamaker-Chen Dissertation Award (2016). Professor Li's research focuses on digital platforms, digital transformation, and AI strategy. Digitization has profoundly reshaped the economy—it has created new distribution channels, reorganized supply chains, and transformed how businesses reach and serve their customers. Professor Li's research seeks to improve the value creation process through the design of digital strategy. Professor Li earned his M.S. in Economics (2014) and Ph.D. in Information, Risk, and Operations Management (2015) from the University of Texas at Austin. He also received a B.S. in Computer Science.

Simrita Singh

Simrita Singh is an Assistant Professor in the Department of Information Systems & Analytics. She holds an undergraduate degree in Electronics and Communication Engineering from the Indian Institute of Technology, Roorkee, and an M.S. and Ph. D. in Operations Management from The Kellogg School of Management at Northwestern University. Simrita investigates the joint use of the latest technology, data-driven approaches (analytics, deep learning), and the more traditional modeling and optimization techniques to predict demand and improve costs and access in service systems, particularly healthcare and, more recently, in retail. She studies the latest data-driven innovations in healthcare operations, including computer-aided triage (CADt), clinical decision support systems (CDSS), big data analytics on healthcare claims, digital twins, and personalised connected care. Some of her works have been published in top journals such as PLOS Medicine, Nature Scientific Reports, and British Medical Journal (BMJ) Open, while others are under review in leading management journals. Before her Ph.D., Simrita worked as a business analyst at JP Morgan and also as an independent consultant for many educational institutes in India.