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Predicting Consumer Behaviour Using Partial Least Squares Structural Equation Modelling (PLS-SEM)

Special issue call for papers from European Business Review

The ScholarOne site will open for submissions July 2019.

Guest Editors

Joe F. Hair, University of South Alabama, USA

Jun-Hwa Cheah (Jacky), Universiti Putra Malaysia, Malaysia

Christian M. Ringle, Hamburg University of Technology (TUHH), Germany and the University of Waikato, Hamilton, New Zealand

Marko Sarstedt, Otto-von-Guericke-University Magdeburg, Germany and Monash University Malaysia, Malaysia

Hiram Ting, UCSI University and Sarawak Research Society, Malaysia

Aims and Scope

With the growing complexity of consumer behaviour theories, researchers are increasingly moving from universalistic to more multifaceted models (e.g., Codini et al., 2018; Hair et al. 2018a; Rashidirad et al, 2018; Van Tonder et al., 2017; Sharifi, 2014). For example, there is much more interest in unravelling the contingencies that characterize the differences between subgroups of individuals or environments. Understanding such contingencies and their effect requires a rigorous assessment of observed or unobserved heterogeneity. Similarly, researchers are now moving beyond the modelling of linear effects and increasingly considering complex nonlinearities among constructs of interest (e.g., Ahrholdt et al., 2019; Braun & Hadwich, 2017; Plötner et al., 2013; Pehrsson, 2011; Palmer, 2010). This emergence of more advanced statistical techniques and methods facilitates and substantiates more complex models and analyses to obtain additional or revised findings and discussions.

Partial least squares structural equation modelling (PLS-SEM) has recently gained increasing prominence for analysing the dynamics and complexities in consumer behaviour, especially when prediction is the goal of the analysis (e.g., Hair et al., 2014 Hair et al., 2017; Hair et al., 2018b). PLS-SEM allows researchers to bridge the concepts of prediction and confirmation, because they can expect their model to have high predictive accuracy, while simultaneously being grounded in well-developed causal explanations (Sarstedt et al., 2017). However, applications of PLS-SEM typically focus on confirmation, neglecting the assessment of a model’s predictive power. This common practice is disconcerting, since ensuring a model’s predictive power is a conditio sine qua non for its practical relevance in decision-making.

The aim of this special issue of European Business Review is to introduce and disseminate PLS as a prediction-oriented SEM to a wider audience in an effort to broaden the understanding of consumer behaviour.
(1)    We are looking for high-quality and innovative papers that use PLS-SEM to address the interplay between confirmation and prediction in an effort to advance our understanding of consumer behaviour. These applications shall utilise criteria that have been established within the PLS-SEM context (e.g., model evaluation criteria including PLSpredict and predictive model selection). However, the applications can also employ established criteria and analyses, which have not been used in a PLS-SEM context so far, but are compatible with the method (e.g., robustness checks and/or model specification analyses).  
(2)    In addition, we also seek technical papers that introduce methodological advances, which strongly emphasize predictive aspects. Corresponding papers should illustrate how the proposed advances of the original PLS-SEM method are practically relevant for predicting consumer behaviour phenomena.

The special issue is tied to the MAG Scholar Conference of Business, Marketing, and Tourism in Macau, China on 24 – 26 June 2019 ( as well as the International Symposium on Applied Structural Equation Modelling and Methodological Matters in Melaka, Malaysia on 21 - 24 August 2019 ( Outstanding papers presented at these conferences will be invited for full paper submission. The guest editors also welcome submissions to the special issue that have not been submitted to or presented at these conferences.

Submission Instructions

(1) Researchers are invited to consider and submit high-quality, original work that has neither appeared in nor is currently under review for publication in another journal.

(2) Submissions must not exceed 7,000 words in length (excluding references). Longer manuscripts will be returned to the authors without it having been reviewed. For further information and formatting requirements, please visit the European Business Review website at:

(3) Manuscripts should be submitted to the journal through the online submission system The guest editors/editorial desk will review all submissions to initially determine their suitability and relevance for publication in this special issue. Papers that either lack originality, contribution, and/or clarity in presentation, or fall outside the scope of the special issue will not be submitted for blind review and the authors will be promptly informed. Final acceptance of manuscripts depends on their quality and reviewer reports.

Important Dates

•    Paper submission deadline: 30 September 2019
•    Initial review report: 15 November 2019
•    Revised manuscript due: 29 January 2020
•    Second round of review report: 15 April 2020
•    Final acceptance notification: 31 May 2020


Ahrholdt, D. C., Gudergan, S. P., & Ringle, C. M. (2019). Enhancing loyalty: When improving consumer satisfaction and delight matters. Journal of Business Research, 94(1), 18-27.
Braun, C., & Hadwich, K. (2017). Determinants of perceived internal service complexity: An empirical analysis of promoting and limiting complexity factors. European Business Review, 29(1), 123-152.
Codini, A. P., Miniero, G., & Bonera, M. (2018). Why not promote promotion for green consumption? The controversial role of regulatory focus. European Business Review, 30(5), 554-570.
Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research. European Business Review, 26(2), 106-121.
Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM). 2nd edition. Sage Publications.
Hair Jr, J. F., Harrison, D. E., & Risher, J. J. (2018a). Marketing Research in the 21st Century: Opportunities and Challenges. Revista Brasileira de Marketing, 17(5), 666-699.
Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2018b). Advanced issues in partial least squares structural equation modeling. SAGE Publications.
Palmer, A. (2010). Customer experience management: A critical review of an emerging idea. Journal of Services marketing, 24(3), 196-208.
Pehrsson, A. (2011). Product/customer scope: Competition antecedents, performance effects and market context moderations. European Business Review, 23(5), 418-433.
Plötner, O., Lakotta, J., & Jacob, F. (2013). Differentiating market offerings using complexity and co-creation: Implications for customer decision-making uncertainty. European Business Review, 25(1), 65-85.
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2017). Partial least squares structural equation modeling. In C. Homburg, M. Klarmann & A. Vomberg (Eds.), Handbook of Market Research. Heidelberg: Springer.
Sharifi, S. S. (2014). Impacts of the trilogy of emotion on future purchase intentions in products of high involvement under the mediating role of brand awareness. European Business Review, 26(1), 43-63.
Shmueli, G. (2010). To explain or to predict? Statistical Science, 25(3), 289-310.
Van Tonder, E., Petzer, D. J., & Van Zyl, K. (2017). A mediated model of relationship quality factors affecting behavioural intention at a luxury motor vehicle dealership. European Business Review, 29(1), 43-60.