{"title":"Field experiments in operations management","authors":"Yang Gao, Meng Li, Shujing Sun","doi":"10.1002/joom.1240","DOIUrl":null,"url":null,"abstract":"<p>While the field experiment is a powerful and well-established method to investigate causal relationships, operations management (OM) has embraced this methodology only in recent years. This paper provides a comprehensive review of the existing OM literature leveraging field experiments. It also serves as a one-stop guide for future application of field experiments in the OM area. We start by recapping the characteristics that distinguish field experiments from other common types of experiments and organizing the relevant OM studies by topic. Corresponding to the commonly overlooked issues in field experiment-based OM studies, we then provide a detailed roadmap, ranging from experimental design and implementation to post-experiment analysis. We further outline the methodological and practical issues as well as corresponding solutions when applying field experiments. We conclude by identifying future research directions from an OM perspective.</p>","PeriodicalId":51097,"journal":{"name":"Journal of Operations Management","volume":"69 4","pages":"676-701"},"PeriodicalIF":6.5000,"publicationDate":"2023-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Operations Management","FirstCategoryId":"91","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/joom.1240","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 0
Abstract
While the field experiment is a powerful and well-established method to investigate causal relationships, operations management (OM) has embraced this methodology only in recent years. This paper provides a comprehensive review of the existing OM literature leveraging field experiments. It also serves as a one-stop guide for future application of field experiments in the OM area. We start by recapping the characteristics that distinguish field experiments from other common types of experiments and organizing the relevant OM studies by topic. Corresponding to the commonly overlooked issues in field experiment-based OM studies, we then provide a detailed roadmap, ranging from experimental design and implementation to post-experiment analysis. We further outline the methodological and practical issues as well as corresponding solutions when applying field experiments. We conclude by identifying future research directions from an OM perspective.
期刊介绍：
The Journal of Operations Management (JOM) is a leading academic publication dedicated to advancing the field of operations management (OM) through rigorous and original research. The journal's primary audience is the academic community, although it also values contributions that attract the interest of practitioners. However, it does not publish articles that are primarily aimed at practitioners, as academic relevance is a fundamental requirement.
JOM focuses on the management aspects of various types of operations, including manufacturing, service, and supply chain operations. The journal's scope is broad, covering both profit-oriented and non-profit organizations. The core criterion for publication is that the research question must be centered around operations management, rather than merely using operations as a context. For instance, a study on charismatic leadership in a manufacturing setting would only be within JOM's scope if it directly relates to the management of operations; the mere setting of the study is not enough.
Published papers in JOM are expected to address real-world operational questions and challenges. While not all research must be driven by practical concerns, there must be a credible link to practice that is considered from the outset of the research, not as an afterthought. Authors are cautioned against assuming that academic knowledge can be easily translated into practical applications without proper justification.
JOM's articles are abstracted and indexed by several prestigious databases and services, including Engineering Information, Inc.; Executive Sciences Institute; INSPEC; International Abstracts in Operations Research; Cambridge Scientific Abstracts; SciSearch/Science Citation Index; CompuMath Citation Index; Current Contents/Engineering, Computing & Technology; Information Access Company; and Social Sciences Citation Index. This ensures that the journal's research is widely accessible and recognized within the academic and professional communities.
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