報告時間：2023年5月10日（星期三）9:30-10:30
報告地點：工程管理與智能制造研究中心大樓825室
報 告 人：鐘遠光 教授
工作單位：華南理工大學
舉辦單位：管理學院
報告簡介：
With the rapid growth of the sharing economy, on-demand staffing platforms have emerged to help companies manage their temporary workforce. In this paper, we study how to maximize and distribute the benefits of an on-demand workforce in this new business context. We consider an on-demand staffing platform that serves multiple employers with uncertain demands using a common pool of self-scheduling workers. To compare this method with traditional staffing solutions, we first investigate when an on-demand staffing platform can be beneficial from the perspective of a central planner. Next, we propose a novel fill rate-based allocation and coordination mechanism that enables the on-demand workforce to be shared optimally when individual employers and the platform operator make decisions in their own interest. Our results suggest that a win-win-win solution can be achieved in an appropriately designed system: Individual employers and the platform operator share the maximum benefits of on-demand staffing, while workers are able to set their own hours.
報告人簡介：
鐘遠光，華南理工大學工商管理學院教授，博士生導師，工業工程系系主任。長期致力于供應鏈庫存優化、庫存共享與分配、優化理論方法與應用等領域的研究，代表性論文發表在Management Science, Operations Research, Manufacturing & Service Operations Management，Production and Operations Management，Transportation Research Part B: Methodological、IISE Transactions等期刊上。入選教育部青年長江學者（2021年）、廣東省青年珠江學者（2017年）、香江學者（2017年）。獲得教育部高等學校科學研究優秀成果三等獎，廣東省哲學社會科學優秀成果獎一等獎（兩次）和二等獎，安徽省科學技術三等獎等獎勵。主持了國家自然科學基金（其中1項結題“特優”），廣東省自然科學基金和企業橫向項目10多項。
