Partial least squares path modeling: Time for some serious second thoughts

被引:193
|
作者
Ronkko, Mikko [1 ]
McIntosh, Cameron N. [2 ]
Antonakis, John [3 ]
Edwards, Jeffrey R. [4 ]
机构
[1] Aalto Univ, Sch Sci, POB 15500, FI-00076 Aalto, Finland
[2] Publ Safety Canada, 340 Laurier Ave West, Ottawa, ON K1A 0P8, Canada
[3] Univ Lausanne, Fac Business & Econ, Internef 618, CH-1015 Lausanne, Switzerland
[4] Univ N Carolina, Kenan Flagler Business Sch, Campus Box 3490,McColl Bldg, Chapel Hill, NC 27599 USA
关键词
Partial least squares; Structural equation modeling; Statistical and methodological myths and; urban legends; OPERATIONS MANAGEMENT RESEARCH; RIGDONS RETHINKING; FIT INDEXES; PLS; INFORMATION; VALIDITY; UNIDIMENSIONALITY; IDENTIFICATION; INTEGRATION; PERFORMANCE;
D O I
10.1016/j.jom.2016.05.002
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Partial least squares (PLS) path modeling is increasingly being promoted as a technique of choice for various analysis scenarios, despite the serious shortcomings of the method. The current lack of methodological justification for PLS prompted the editors of this journal to declare that research using this technique is likely to be desk-rejected (Guide and Ketokivi, 2015). To provide clarification on the inappropriateness of PLS for applied research, we provide a non-technical review and empirical demonstration of its inherent, intractable problems. We show that although the PLS technique is promoted as a structural equation modeling (SEM) technique, it is simply regression with scale scores and thus has very limited capabilities to handle the wide array of problems for which applied researchers use SEM. To that end, we explain why the use of PLS weights and many rules of thumb that are commonly employed with PLS are unjustifiable, followed by addressing why the touted advantages of the method are simply untenable. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:9 / 27
页数:19
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