计算机科学
管理科学
行为运筹学
工作(物理)
航程(航空)
人工智能
知识管理
数据科学
经济
工程类
机械工程
航空航天工程
作者
Andrew M. Davis,Shawn Mankad,Charles J. Corbett,Elena Katok
标识
DOI:10.1287/msom.2022.0553
摘要
Problem definition: Two disciplines increasingly applied in operations management (OM) are machine learning (ML) and behavioral science (BSci). Rather than treating these as mutually exclusive fields, we discuss how they can work as complements to solve important OM problems. Methodology/results: We illustrate how ML and BSci enhance one another in non-OM domains before detailing how each step of their respective research processes can benefit the other in OM settings. We then conclude by proposing a framework to help identify how ML and BSci can jointly contribute to OM problems. Managerial implications: Overall, we aim to explore how the integration of ML and BSci can enable researchers to solve a wide range of problems within OM, allowing future research to generate valuable insights for managers, companies, and society.
科研通智能强力驱动
Strongly Powered by AbleSci AI