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Using partial least squares in operations management research: A practical guideline and summary of past research
Open accessAbstract
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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“In our case, we noted the Q² for BDAAI (0.73) and OP (0.81), indicating high predictive relevance (Peng and Lai, 2012).”
From Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations (2020) · cites this paper as Peng and Lai, 2012
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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
- 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
- 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
- green
- aquila.usm.edu
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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