A Personal Perspective on Doing Good Research Seminar Series - Professor LENG Mingming

About the Speaker

Professor LENG Mingming

Dean of the Faculty of Business
Chair Professor of Operations and Risk Management
 

Biography

Professor Leng Mingming holds a Ph.D. in Management Science/System from the DeGroote School of Business at McMaster University, Canada. He is currently a Chair Professor of Operations and Risk Management, the Dean of the Faculty of Business, and the Acting Director of the Institute of Insurance and Risk Management. Professor Leng’s research interests are centered on game theory (with a focus on cooperative game theory), operations management, and supply chain operations. He has published numerous papers in top journals such as Management Science, Operations Research, Manufacturing & Service Operations Management, Production and Operations Management, IISE Transactions, Naval Research Logistics, and others. Professor Leng is a member of the Editorial Review Board of Production and Operations Management and an Associate Editor of INFOR: Information Systems and Operational Research. In addition, Professor Leng has five years of industry experience.

Abstract

We use cooperative game theory to investigate multi-player allocation problems under the almost diminishing marginal contributions (ADMC) property. This property indicates that a player's marginal contribution to a non-empty coalition decreases as the size of the coalition increases. We develop ADMC games for such problems and derive a necessary and sufficient condition for the non-emptiness of the core. When the core is non-empty, at least one extreme point exists, and the maximum number of extreme points is the total number of players. The Shapley value may not be in the core, which depends on the gap of each coalition. A player can receive a higher allocation based on the Shapley value in the core than based on the nucleolus, if the gap of the player is no greater than the gap of the complementary coalition. We also investigate the least core value for ADMC games with an empty core. To illustrate the applications of our results, we analyse a code-sharing game, a group-buying game, and a scheduling profit game.