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An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research

Faizan Ali (College of Hospitality and Tourism Leadership, University of South Florida - Sarasota-Manatee, Sarasota, Florida, USA)
S. Mostafa Rasoolimanesh (Housing, Building and Planning School, Universiti Sains Malaysia, Penang, Malaysia)
Marko Sarstedt (Faculty of Economics and Management, Otto-von-Guericke University Magdeburg, Magdeburg, Germany, and University of Newcastle, Callaghan, Australia)
Christian M. Ringle (Faculty of Management Science and Technology, Hamburg University of Technology (TUHH), Hamburg, Germany)
Kisang Ryu (Department of Food Service Management, Sejong University, Seoul, Republic of Korea)

International Journal of Contemporary Hospitality Management

ISSN: 0959-6119

Article publication date: 8 January 2018




Structural equation modeling (SEM) depicts one of the most salient research methods across a variety of disciplines, including hospitality management. Although for many researchers, SEM is equivalent to carrying out covariance-based SEM, recent research advocates the use of partial least squares structural equation modeling (PLS-SEM) as an attractive alternative. The purpose of this paper is to systematically examine how PLS-SEM has been applied in major hospitality research journals with the aim of providing important guidance and, if necessary, opportunities for realignment in future applications. Because PLS-SEM in hospitality research is still in an early stage of development, critically examining its use holds considerable promise to counteract misapplications which otherwise might reinforce over time.


All PLS-SEM studies published in the six SSCI-indexed hospitality management journals between 2001 and 2015 were reviewed. Tying in with the prior studies in the field, the review covers reasons for using PLS-SEM, data characteristics, model characteristics, the evaluation of the measurement models, the evaluation of the structural model, reporting and use of advanced analyses.


Compared to other fields, the results show that several reporting practices are clearly above standard but still leave room for improvement, particularly regarding the consideration of state-of-the art metrics for measurement and structural model assessment. Furthermore, hospitality researchers seem to be unaware of the recent extensions of the PLS-SEM method, which clearly extend the scope of the analyses and help gaining more insights from the model and the data. As a result of this PLS-SEM application review in studies, this research presents guidelines on how to accurately use the method. These guidelines are important for the hospitality management and other disciplines to disseminate and ensure the rigor of PLS-SEM analyses and reporting practices.

Research limitations/implications

Only articles published in the SSCI-indexed hospitality journals were examined and any journals indexed in other databases were not included. That is, while this research focused on the top-tier hospitality management journals, future research may widen the scope by considering hospitality management-related studies from other disciplines, such as tourism research or general management.


This study contributes to the literature by providing hospitality researchers with the updated guidelines for PLS-SEM use. Based on a systematic review of current practices in the hospitality literature, critical methodological issues when choosing and using the PLS-SEM were identified. The guidelines allow to improve future PLS-SEM studies and offer recommendations for using recent advances of the method.



Even though this research does not explicitly refer to the use of the SmartPLS software (, Ringle acknowledges a financial interest in SmartPLS.


Ali, F., Rasoolimanesh, S.M., Sarstedt, M., Ringle, C.M. and Ryu, K. (2018), "An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research", International Journal of Contemporary Hospitality Management, Vol. 30 No. 1, pp. 514-538.



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