An assessment of the use of partial least squares structural equation modeling in marketing research

被引:4871
作者
Hair, Joe F. [1 ]
Sarstedt, Marko [2 ,3 ]
Ringle, Christian M. [3 ,4 ]
Mena, Jeannette A. [5 ]
机构
[1] Kennesaw State Univ, KSU Ctr, DBA Program, Kennesaw, GA 30144 USA
[2] Ludwig Maximilians Univ Munich LMU, Inst Market Based Management IMM, D-80539 Munich, Germany
[3] Univ Newcastle, Fac Business & Law, Newcastle, NSW 2300, Australia
[4] Hamburg Univ Technol TUHH, Inst Human Resource Management & Org HRMO, D-21073 Hamburg, Germany
[5] Univ S Florida, Coll Business, Tampa, FL 33620 USA
关键词
Empirical research methods; Partial least squares; Path modeling; Structural equation modeling; RESPONSE-BASED SEGMENTATION; SINGLE-ITEM MEASURES; FORMATIVE MEASUREMENT; MANAGEMENT RESEARCH; PLS; INDICATORS; VARIABLES; JOURNALS; QUALITY; SCALE;
D O I
10.1007/s11747-011-0261-6
中图分类号
F [经济];
学科分类号
02 ;
摘要
Most methodological fields undertake regular critical reflections to ensure rigorous research and publication practices, and, consequently, acceptance in their domain. Interestingly, relatively little attention has been paid to assessing the use of partial least squares structural equation modeling (PLS-SEM) in marketing research-despite its increasing popularity in recent years. To fill this gap, we conducted an extensive search in the 30 top ranked marketing journals that allowed us to identify 204 PLS-SEM applications published in a 30-year period (1981 to 2010). A critical analysis of these articles addresses, amongst others, the following key methodological issues: reasons for using PLS-SEM, data and model characteristics, outer and inner model evaluations, and reporting. We also give an overview of the interdependencies between researchers' choices, identify potential problem areas, and discuss their implications. On the basis of our findings, we provide comprehensive guidelines to aid researchers in avoiding common pitfalls in PLS-SEM use. This study is important for researchers and practitioners, as PLS-SEM requires several critical choices that, if not made correctly, can lead to improper findings, interpretations, and conclusions.
引用
收藏
页码:414 / 433
页数:20
相关论文
共 50 条
[41]   Guest editorial: Sports management research using partial least squares structural equation modeling (PLS-SEM) [J].
Cepeda-Carrion, Gabriel ;
Hair, Joseph F. ;
Ringle, Christian M. ;
Luis Roldan, Jose ;
Garcia-Fernandez, Jeronimo .
INTERNATIONAL JOURNAL OF SPORTS MARKETING & SPONSORSHIP, 2022, 23 (02) :229-240
[42]   Assessing Consumer Behavior in Sustainable Product Markets: A Structural Equation Modeling Approach with Partial Least Squares Analysis [J].
Islam, Qamrul ;
Khan, Syed Md Faisal Ali .
SUSTAINABILITY, 2024, 16 (08)
[43]   Examining the interaction of flood vulnerability determinants in Cambodia and Vietnam using partial least squares structural equation modeling [J].
Hoang Ha Anh ;
Tran Minh Da Hanh ;
Nguyen Thi Tuong Vi ;
Yao Shunbo .
WATER POLICY, 2018, 20 (06) :1256-1278
[44]   Segmentation in Structural Equation Modeling Using a Combination of Partial Least Squares and Modified Fuzzy Clustering [J].
Mukid, Moch Abdul ;
Otok, Bambang Widjanarko ;
Suharsono, Agus .
SYMMETRY-BASEL, 2022, 14 (11)
[45]   An in-depth discussion and illustration of partial least squares structural equation modeling in health care [J].
Avkiran, Necmi Kemal .
HEALTH CARE MANAGEMENT SCIENCE, 2018, 21 (03) :401-408
[46]   An introduction to the partial least squares approach to structural equation modelling: a method for exploratory psychiatric research [J].
Riou, Julien ;
Guyon, Herve ;
Falissard, Bruno .
INTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH, 2016, 25 (03) :220-231
[47]   Special issue editorial: Advanced partial least squares structural equation modeling (PLS-SEM) applications in business research [J].
Gudergan, Siegfried P. ;
Moisescu, Ovidiu I. ;
Radomir, Lacramioara ;
Ringle, Christian M. ;
Sarstedt, Marko .
JOURNAL OF BUSINESS RESEARCH, 2025, 188
[48]   A Critical Examination of Common Beliefs About Partial Least Squares Path Modeling [J].
Ronkko, Mikko ;
Evermann, Joerg .
ORGANIZATIONAL RESEARCH METHODS, 2013, 16 (03) :425-448
[50]   Modeling and partial least squares approaches in OODA [J].
Isabel Sanchez-Rodriguez, Maria ;
Caridad, Jose M. .
BIOMETRICAL JOURNAL, 2014, 56 (05) :771-773