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Using partial least squares in operations management research: A practical guideline and summary of past research
Author(s) -
Peng David Xiaosong,
Lai Fujun
Publication year - 2012
Publication title -
journal of operations management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.649
H-Index - 191
eISSN - 1873-1317
pISSN - 0272-6963
DOI - 10.1016/j.jom.2012.06.002
Subject(s) - guideline , partial least squares regression , computer science , structural equation modeling , field (mathematics) , management science , process management , business , engineering , mathematics , medicine , machine learning , pathology , pure mathematics
The partial least squares (PLS) approach to structural equation modeling (SEM) has been widely adopted in business research fields such as information systems, consumer behavior, and marketing. The use of PLS in the field of operations management is also growing. However, questions still exist among some operations management researchers regarding whether and how PLS should be used. To address these questions, our study provides a practical guideline for using PLS and uses examples from the operations management literature to demonstrate how the specific points in this guideline can be applied. In addition, our study reviews and summarizes the use of PLS in the recent operations management literature according to our guideline. The main contribution of this study is to present a practical guideline for evaluating and using PLS that is tailored to the operations management field.