Department of Industrial Engineering & Decision Analysis [IEDA Seminar] - Learning to rank under strategic manipulation in small and large markets

10:30am - 11:30am
Room 2302 (lift 17-18)

We consider a dynamic learning and ranking problem of a digital platform. Uninformed of the products' intrinsic qualities, the platform strives to design a ranking rule that learns from historical traffic data while accounting for potential manipulation by sellers through "brushing" activities, such as fake orders or sales. How does the ranking manipulation disrupt ranking efficiency under various market conditions? Are there effective yet simple ranking algorithms to combat ranking manipulation?

Under an Experiment-Then-Commit (ETC) policy framework, we formulate an $N$-player-$T$-period dynamic "brushing war" game for the sellers. We provide a (static) budget-competition equilibrium characterization and study its asymptotic behavior when $T$ is large. For a small market with two sellers, we show the nonexistence of pure strategy equilibria and identify a mixed-strategy equilibrium, shedding light on the possibility of efficiency loss. For a large market, we formulate a novel non-atomic game with a continuum of sellers as a limiting case where $N$ is large. We characterize a "self-reinforcing" market equilibrium, where the seller's brushing amount increases in the product's quality. In other words, the sellers' strategic responses "reinforce" complete learning of the platform.

講者/ 表演者:
Prof. Yifan FENG
Business School National University of Singapore

Yifan Feng is an Assistant Professor at NUS Business School's Department of Analytics and Operations. With an interest in the intersection of artificial intelligence, operations management, and optimization, he tackles complex e-commerce and marketplace challenges, focusing on learning, experimentation, and demand fulfillment.

Yifan's work has been published or accepted in renowned business journals like Operations Research and Management Science and AI conferences such as NeurIPS, ICML, and EC. He has also secured over one million USD in funding as either Principal or Co-Principal Investigator (PI/Co-PI) from various public and private sources. Before joining NUS, Yifan obtained his PhD in Management Science/Operations Management from the University of Chicago Booth School of Business.

Department of Industrial Engineering & Decision Analytics