管理科学系学术讲座（8月20日）

时   间：2025年8月20日（周三） 10:00-11:30

地   点：管理学院思源楼524室

主题：Index Policies for Campaign Promotion Strategies in Reward-based Crowdfunding

主讲人：Dong Li （李栋） 兰卡斯特大学管理学院教授

主持人：Jelmer Pier van der Gaast 复旦大学管理学院副教授

Abstract: Reward-based crowdfunding plays a crucial role in fundraising for start-up entrepreneurs. Recent studies, however, have shown that the actual success rate of fundraising projects is surprisingly low across multiple crowdfunding platforms. We consider crowdfunding platforms' decision-making of selecting projects to highlight on their homepage to boost the chance of success for projects, and investigates promotion strategies aiming at maximizing platforms' revenue over a fixed period. We characterize backers' investment decisions by a discrete choice model with a time-varying coefficient of herding effect, and formulate the problem as a stochastic dynamic program, which is however computationally intractable. To address this issue, we follow the Whittle's Restless Bandit approach to decompose the problem into a collection of single-project problems and prove indexability for each project under some mild conditions. We show that the index values of the proposed index policy can be directly derived from the value-to-go of each project under the non-promotion policy, which is calculated recursively offline with a linear-time complexity. To further enhance the scalability, we develop a closed-form approximation to calculate the index values online. To the best of our knowledge, this work is the first in the literature to develop index policies for campaign promotions in reward-based crowdfunding. It is also the first attempt to provide indexability analysis of bi-dimensional restless bandits coupled by not only resource but also demand. Extensive numerical experiments show that the proposed index policies outperform the other benchmark heuristics in most of the scenarios considered.

Bio:

Dong Li is a Professor of Operational Research at Lancaster University Management School, UK. His main research interests include Revenue Management and Pricing (applied in Sharing/Platform economy), Discrete Choice-Modelling, Scheduling and Resource Allocation. Methodologically he is mostly skilled in Markov Decision Process, Approximate Dynamic Programming, Reinforcement Learning, and Multi-armed Bandits (Restless Bandits). Dong has also done significant works in Stochastic Programming. His research has appeared in top peer reviewed international journals including, Production and Operations Management, European Journal of Operational Research, Transportation Research Part B, Journal of Operational Research Society, Naval Research Logistics, Annals of Operations Research, etc. Dong is an associate editor of Computational Management Science.