A review of operations management literature: a data-driven approach

Andrew Manikas, Lynn Boyd, Jian (Jeff) Guan and Kyle Hoskins

International Journal of Production Research, 2020, vol. 58, issue 5, 1442-1461

Abstract: Production and operations management has been a significant field of research for many years. However, other than an educated guess by researchers in the field or a perusal of textbook chapter titles, the major topics and their trends over time are not well established. This study provides a comprehensive review of production and operations management literature using a data-driven approach. We use Latent Semantic Analysis on 21,053 abstracts representing all publications in six leading operations management journals since their inception. 18 unique topic clusters were identified algorithmically. Just being aware of the history of research topics should be of great interest to all academics in the field, but to help future researchers we conducted three post hoc analyses: 1) analysis of methods used in all these studies, 2) citation rates by topic area over time, and 3) the growing prevalence of research covering multiple topics.

Date: 2020
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DOI: 10.1080/00207543.2019.1651459

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