OPERATIONS, TECHNOLOGY, AND INFORMATION MANAGEMENT


OM Forum - Te Best of Both Worlds: Machine Learning and Behavioral Science in Operations Management


ANDREW M. DAVIS PROFESSOR


BREAZZANO FAMILY TERM PROFESSOR OF MANAGEMENT


Samuel Curtis Johnson Graduate School of Management


Cornell SC Johnson College of Business Cornell University


Manufacturing and Service Operations Management, 26, 5, Sept. 2024 LINK TO PAPER LINK TO ANDREW DAVIS VIDEO


Co-authors • Andrew M. Davis


Professor, Breazzano Family Term Professor of Management,


Samuel Curtis Johnson Graduate School of Management, Cornell SC Johnson College of Business, Cornell University


• Charles J.Corbett, Anderson School of Management, University of California Los Angeles


• Elena Katok, Naveen Jindal School of Management, University of Texas at Dallas • Shawn Mankad, North Carolina State University


Summary Two disciplines increasingly applied in operations management (OM) are ma-


chine learning (ML) and behavioral science (BSci). Machine learning is a form of engineering that aims to solve problems, whereas behavioral science aims to understand how the world works. Rather than treating these as mutually ex- clusive fields, the authors discuss how they can work as complements to solve important operations management problems.


First, they illustrate how ML and BSci enhance one another in non-OM domains before detailing how each step of their respective research process- es can benefit the other in OM settings. Tey then conclude by proposing a framework to help identify how ML and BSci can jointly contribute to OM problems, complementing each other to compensate for individual weakness- es in certain areas. Overall, the authors aim to explore how the integration of ML and BSci can enable researchers to solve a wide range of problems, allow- ing future research to generate valuable insights for managers, companies, and society.


CONTENTS TO MAIN


| RESEARCH WITH IMPACT: CORNELL SC JOHNSON COLLEGE OF BUSINESS • 2024 EDITION


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