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      講座:Managing the Gig Economy via Behavioral and Operational Lenses

      發布者:人力資源辦公室    發布時間:2020-12-28

      題 目:Managing the Gig Economy via Behavioral and Operational Lenses

      演講人:Park Sinchaisri, Ph.D. Candidate, University of Pennsylvania

      主持人:李成璋  助理教授 上海交通大學安泰經濟與管理學院

      時 間:2020年12月31日(周四)10:40-12:10

      會議方式:ZOOM會議(校內師生如需會議號和密碼,請于12月30日中午12點前發送電郵至managementscience@acem.sjtu.edu.cn獲取

      內容簡介

      Gig economy firms benefit from labor flexibility by hiring independent workers in response to real-time demand.  However, workers' flexibility in their work schedule poses a great challenge in terms of planning and committing to a service capacity.  Understanding what motivates gig economy workers is thus of great importance.  In collaboration with a ride-hailing platform, we study how on-demand workers make labor decisions and learn in complex environments.  Using a large comprehensive dataset, we first develop an econometric model to analyze workers' labor decisions in response to incentives while accounting for their personal goals, sample selection, and endogeneity.  Our careful analysis has revealed behavioral insights, from income targeting to inertia behaviors, that can inform better incentive and regulatory design.  We then propose a novel machine learning algorithm to automatically extract best practices from the data and infer interpretable tips that can help workers learn to improve their performance in the absence of peer learning.  To this end, we designed a virtual queue-management game that requires the participants to make a series of decisions to minimize overall service time.  Our behavioral studies show that the tips generated by our algorithm are effective at improving performance and they help participants build on their own experience to discover additional strategies and overcome their resistance to exploring counterintuitive strategies. 

      演講人簡介

      Park Sinchaisri is a fifth-year doctoral candidate in Operations, Information, and Decisions at The Wharton School at the University of Pennsylvania.  His research largely centers around behavioral and data-driven operations management, particularly the role of human behavior in the future of work, services, and cities.  Currently, he is studying the gig economy, human-AI interface, and analytics for social good.  Prior to Wharton, he earned a ScB in Computer Engineering and Applied Mathematics-Economics from Brown University, a SM in Computational Science and Engineering from MIT, and worked for Oracle, Goldman Sachs, and Deloitte Consulting.  Growing up in Bangkok, Park is a world traveler, avid foodie, urban planning enthusiast, and aspiring creative artist. 

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