Article ID: | iaor201522049 |
Volume: | 45 |
Issue: | 5 |
Start Page Number: | 971 |
End Page Number: | 994 |
Publication Date: | Oct 2014 |
Journal: | Decision Sciences |
Authors: | Kulkarni Shailesh S, Apte Uday M, Evangelopoulos Nicholas E |
Keywords: | knowledge management, datamining, decision, management |
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.