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

被引:1009
作者
Peng, David Xiaosong [2 ]
Lai, Fujun [1 ]
机构
[1] Univ So Mississippi, Coll Business, Dept Management & Int Business, Long Beach, MS 39503 USA
[2] Texas A&M Univ, Mays Business Sch, Dept Informat & Operat Management, College Stn, TX 77843 USA
基金
中国国家自然科学基金;
关键词
Partial least squares (PLS); Structural equation modeling (SEM); Empirical research methods; Operations management; STRUCTURAL EQUATION MODELS; SAMPLE-SIZE; PLS; INDICATORS; COVARIANCE; QUALITY; CONSTRUCTION; INTEGRATION; VALIDITY; POM;
D O I
10.1016/j.jom.2012.06.002
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
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. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:467 / 480
页数:14
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