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Cited by 1,532Psychometric Methodologies and TestingBusiness Strategies and Management ResearchAdvanced Statistical Methods and Models

The DOI matches its Crossref record; 78 of the 82 references it cites were found in a registry or an index.

Using partial least squares in operations management research: A practical guideline and summary of past research

Open access
Peng, David Xiaosong, Lai, Fujun·2012·Journal of Operations Management
DOI 10.1016/j.jom.2012.06.002
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Abstract

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.

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Research works printed but not linked: 8

  1. Bagozzi R.P., 1994, Basic Principles of Marketing Research, 317
  2. Chin W.W., 1995, Partial least squares is to lisrel as principal components analysis is to common factor analysis, Technology Studies, 2, 315
  3. 10.1509/jmkg.70.3.058 · DOI
  4. Kenny D.A., 1998, The Handbook of Social Psychology, vol. 1, 233
  5. Nunnally J.C., 1994, Psychometric Theory
  6. Roth A.V., 2007, Handbook of Metrics for Operations Management: Multi‐item Measurement Scales and Objective Items
  7. Wold H., 1966, International symposium on Multivariate Analysis
  8. Wold H., 1982, Systems Under Indirect Observations: Causality, Structure, Prediction, Part 2, 1

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Metadata

Authors
Peng, D. X., & Lai, F.
Affiliations
  • Texas A&M University (US)
  • University of Southern Mississippi (US)
Corresponding author
Peng, David Xiaosong
ORCID
Venue
Journal of Operations Management
Publisher
Wiley
Published
2012-06-26
Volume
30
Issue
6
Pages
467-480
ISSN
  • 0272-6963 (ISSN-L)
  • 1873-1317
DOI
10.1016/j.jom.2012.06.002
OpenAlex
W2097247056
Cited by
1,532
References
82
Citations by year
2026: 77 · 2025: 117 · 2024: 136 · 2023: 162 · 2022: 176 · 2021: 161 · 2020: 167 · 2019: 117 · 2018: 135 · 2017: 80 · 2016: 64 · 2015: 57 · 2014: 57 · 2013: 25 · 2012: 1
FWCI
59.12
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Operations Management (publishedVersion)
  • Aquila Digital Community (University of Southern Mississippi) (submittedVersion, cc-by-nc-nd)
  • SSRN Electronic Journal (submittedVersion)
Funders
National Natural Science Foundation of China (71090403/71090400)
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Business Strategies and Management Research
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
Keywords
partial least squares, structural equation modeling, operations management research, research methodology guidelines

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