The Use of Latent Semantic Analysis in Operations Management Research

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Authors
Kulkarni, Shailesh S.
Apte, Uday
Evangelopoulos, Nicholas E.
Subjects
Big Data Analytics
Latent Semantic Analysis
Operations Management Research
Unstructured Text
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2014-10
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Decision Sciences Institute
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Abstract
In this article, we introduce the use of Latent Semantic Analysis (LSA) as a technique for uncovering the intellectual structure of a discipline. LSA is an emerging quantitative method for content analysis that combines rigorous statistical techniques and scholarly judgment as it proceeds to extract and decipher key latent factors. We provide a stepwise explanation and illustration for implementing LSA. To demonstrate LSA’s ability to uncover the intellectual structure of a discipline, we present a study of the field of Operations Management. We also discuss a number of potential applications of LSA to show how it can be used in empirical Operations Management research, specifically in areas that can benefit from analyzing large volumes of unstructured textual data.
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Article
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https://hdl.handle.net/10945/45028
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Decision Sciences, A Journal of the Decision Sciences Institute, Volume 45, Number 5, October 2014
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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