Guest editorial: Using partial least squares structural equation modeling (PLS-SEM) in quality management

Citation

Magno, F., Cassia, F. and Ringle, C.M. (2024), "Guest editorial: Using partial least squares structural equation modeling (PLS-SEM) in quality management", The TQM Journal, Vol. 36 No. 5, pp. 1237-1241. https://doi.org/10.1108/TQM-06-2024-426

Partial least squares structural equation modeling (Chin, 1998; Lohmöller, 1989; Wold, 1982) allows researchers to estimate models with constructs (also see Hair et al., 2022; Hair et al., 2018). PLS-SEM offers researchers multiple benefits such as coping with small samples, estimating complex models and balancing prediction and explanations (e.g. Hair et al., 2019; Tenenhaus, 2008). In business research, the method is particularly suitable for success factor research or exploring the sources of competitive advantages (Albers, 2010; Hair et al., 2012).

In quality management studies, few researchers have also begun to successfully exploit the potential of PLS-SEM for their analyses to obtain relevant results (e.g. Turkyilmaz et al., 2010). In addition, a number of important methodological PLS-SEM developments have recently been introduced that further expand the method’s usefulness for quality management. These advances include, for example, the combination of PLS-SEM and the necessary condition analysis (Duarte et al., 2022; Richter et al., 2020; Sukhov et al., 2022), prediction-oriented model assessment (Sharma et al., 2022; Shmueli et al., 2016, 2019), predictive model comparison and selection (Liengaard et al., 2021; Sharma et al., 2019), PLS-SEM in agent-based simulation (Schubring et al., 2016), uncovering unobserved heterogeneity by latent class segmentation (Becker et al., 2013; Sarstedt et al., 2022), robustness checks (Sarstedt et al., 2020), moderation and multigroup analysis (Hair et al., 2018), importance-performance map analysis (Ringle and Sarstedt, 2016), mediation (Cheah et al., 2021; Nitzl et al., 2016) and higher-order constructs (Becker et al., 2023; Sarstedt et al., 2019). This broad analysis portfolio makes PLS-SEM a valuable method for answering research questions that are fundamental to quality management, such as identifying the antecedents and outcomes of customer-perceived quality.

However, a comprehensive exposition of PLS-SEM’s application in quality management research has not yet been carried out. This is a significant research gap compared to other disciplines where such a discussion has already begun to make the most of the PLS-SEM’s capabilities. The goal of this special issue is to introduce the application of advanced PLS-SEM methods more broadly to researchers in quality management. It is also intended to contribute to expanding the methodological toolbox of quality management research and thus making it more effective. Overall, this special issue aims to shed new light on how the application of advanced PLS-SEM methods can enrich both existing theories and business practices in the quality management discipline. For that purpose, this special issue on PLS-SEM in quality management contains a total of six articles.

The article titled “A brief review of partial least squares structural equation modeling (PLS-SEM) use in quality management studies” by Magno et al. (2024) provides a review of 107 articles applying PLS-SEM and published in eight leading quality management journals. The analysis shows that PLS-SEM’s use in quality management studies is rather new but also highlights a solid upward trend since 2016. The findings also reveal that advanced PLS-SEM analysis techniques are still scarcely applied by quality management scholars, including prediction-based model evaluation, which is one of the most valuable features of PLS-SEM. As a result, this article underlines several areas of improvement in the use of PLS-SEM in this field. Moreover, it provides guidance for quality management researchers to embrace a more comprehensive application of this technique to obtain richer and more detailed results and conclusions from their studies.

The article “Enhancing TQM’s effect on small business performance: a PLS-SEM exploratory study of TQM applied with a comprehensive strategic approach” by Manley et al. (2024) applies PLS-SEM to examine the relationship between TQM and small business performance and the moderating role of comprehensive strategic approach (CSA). The findings from a sample of 241 US small businesses indicate that TQM (modeled as a higher-order construct consisting of seven lower-order constructs) has a positive effect on financial performance and that this relationship is positively moderated by CSA (a higher-order construct consisting of strategic planning, goal setting and financial ratio analysis). This article draws on several advanced PLS-SEM features (including hierarchical component models, moderation analysis and predictive model assessment) to evaluate a complex model. The findings of this analysis provide business leaders with clear insights into how to increase their TQM investment return.

The article titled “The moderating role of Lean Six Sigma practices on quality management practices and quality performance in medical device manufacturing industry” by Sim et al. (2024) applies PLS-SEM to examine the moderating effect of Lean Six Sigma (LSS) on the relationship linking quality management practices (QMPs) and quality performance. The study uses several advanced PLS-SEM features, including hierarchical component models (QMPs and LSS are modeled as second-order and third-order constructs, respectively), moderation analysis and predictive model assessment. The findings from 103 medical device manufacturing companies in Malaysia highlight that QMPs have a positive impact on quality performance, but –contrary to expectations– this effect becomes weaker as LSS practices increase. Based on these findings, the authors provide industry practitioners with insights into the incorporation of LSS practices in the TQM environment.

The article “A roadmap for the application of PLS-SEM and IPMA for effective service quality improvements” by Teeluckdharry et al. (2024) draws on Ringle and Sarstedt’s (2016) work and highlights the sequential steps that need to be taken to apply PLS-SEM and importance–performance map analysis (IPMA) to improve service quality (which comprises both process quality and technical quality). The proposed roadmap begins with the identification of the relevant service quality dimensions and attributes and ends with the recommendations descending from IPMA to improve critical service quality attributes. For illustrative purposes, this article also presents the PLS-SEM and IPMA roadmap application in three different service contexts using data from 429 sports and fitness center members, 426 clients from Subway restaurants and 405 university students. Beyond providing further evidence on the advantages of applying PLS-SEM and IPMA for service quality improvements, this study stresses the importance of selecting the right measuring instrument to holistically capture service quality in the specific service context under examination.

The article titled “Predicting customer loyalty to Airbnb using PLS-SEM: the role of authenticity, interactivity, involvement and customer engagement” by Sallaku and Vigolo (2024) proposes a model to predict customer engagement and customer loyalty towards an online peer-to-peer accommodation platform. The authors draw on social exchange theory and argue that customer engagement can improve relationship quality, which is reflected by loyalty. The model is assessed via PLS-SEM using data from a sample of 226 Italian tourists who had booked at least once through Airbnb in the previous 12 months. The findings show that authenticity, interactivity and involvement positively impact both customer engagement and customer loyalty. In addition, customer engagement partially mediates the relationships linking the three independent variables (authenticity, interactivity and involvement) to customer loyalty. Finally, the PLS-SEM analysis reveals that the model has high power in predicting loyalty.

The article “Increasing the willingness to stay – a novel and comprehensive member satisfaction index (MSI) model tested in a leading German tennis club” by Kölbl et al. (2024) examines member satisfaction in tennis clubs and its relationship with the willingness to stay. In detail, the study proposes a novel member satisfaction index (MSI), which results from member perceptions of various formatively measured service quality dimensions (club atmosphere, club facilities and the price/quality ratio of the membership fee). The findings from a sample of 185 members of a leading tennis club in Germany show that MSI has a positive effect on willingness to stay and that this relationship is mediated by member identification with the club. In addition, to provide tennis club managers with more detailed insights, the authors apply IPMA on the indicator level. IPMA clearly shows the indicators that should be prioritized by managers to improve MSI.

We are confident that the articles in this special issue will stimulate further interest and useful applications of PLS-SEM in quality management studies. In particular, this special issue should encourage quality management researchers to adopt the recent methodological extensions of PLS-SEM, which can be of great interest to this field of study. We would like to take this opportunity to thank all authors for their valuable contributions to this special issue and acknowledge the extraordinary support of the reviewers who contributed their valuable time and expertise to the development and success of this special issue. Finally, we thank the editors-in-chief of The TQM Journal, Professor Maria Vincenza Ciasullo (University of Salerno) and Professor Alex Douglas (The Management University of Africa), for giving us the opportunity to undertake this important publication project. We greatly appreciate their support and the assistance of the journal’s editorial staff in the development of this special issue.