The combined use of symmetric and asymmetric approaches: partial least squares-structural equation modeling and fuzzy-set qualitative comparative analysis

Abstract

Purpose This study aims to propose guidelines for the joint use of partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to combine symmetric and asymmetric perspectives in model evaluation, in the hospitality and tourism field. Design/methodology/approach This study discusses PLS-SEM as a symmetric approach and fsQCA as an asymmetric approach to analyze structural and configurational models. It presents guidelines to conduct an fsQCA based on latent construct scores drawn from PLS-SEM, to assess how configurations of exogenous constructs produce a specific outcome in an endogenous construct. Findings This research highlights the advantages of combining PLS-SEM and fsQCA to analyze the causal effects of antecedents (i.e., exogenous constructs) on outcomes (i.e., endogenous constructs). The construct scores extracted from the PLS-SEM analysis of a nomological network of constructs provide accurate input for performing fsQCA to identify the sufficient configurations required to predict the outcome(s). Complementing the assessment of the model’s explanatory and predictive power, the fsQCA generates more fine-grained insights into variable relationships, thereby offering the means to reach better managerial conclusions. Originality/value The application of PLS-SEM and fsQCA as separate prediction-oriented methods has increased notably in recent years. However, in the absence of clear guidelines, studies applied the methods inconsistently, giving researchers little direction on how to best apply PLS-SEM and fsQCA in tandem. To address this concern, this study provides guidelines for the joint use of PLS-SEM and fsQCA.

Effects of informal controls and psychological empowerment on job satisfaction

“…Thus, it answers the call from studies to explore the role of informal controls in particular (Pant, 2001;Tucker, 2019), providing evidence for yet another context of organizations (Goebel & Weißenberger, 2017b;Monteiro & Lunkes, 2021;Wohlgemuth et al, 2019). Finally, the methodological contribution stands out by using the emerging mixed methods approach in research within the context of management controls (Crespo et al, 2019;Frare & Beuren, 2020, 2021, especially by supporting the inclusion of asymmetrical analyses using fsQCA (Bedford et al, 2016;Felício et al, 2021;Rasoolimanesh et al, 2021).…”

“…Studies within the context of management control support the use of fsQCA (Bedford et al, 2016;Felício et al, 2021), especially the complementary use of PLS-SEM and fsQCA, respectively (Crespo et al, 2019;Frare & Beuren, 2020, 2021. In fact, by considering a quantitative approach (PLS-SEM) along with a qualitative one (fsQCA), complementary results can be obtained that provide a richer overview (Crespo et al, 2021;Rasoolimanesh et al, 2021).…”

Progress in partial least squares structural equation modeling use in marketing research in the last decade

“…As evidenced by PLS‐SEM's numerous extensions (e.g., Liengaard et al, 2021; Rasoolimanesh et al, 2021; Richter et al, 2020) and by controversial debates (Hair et al, 2021b; Rönkkö et al, 2021), research in the field is highly dynamic (Hwang et al, 2020; Khan et al, 2019). This rapid progress makes it difficult for researchers to keep up with the latest developments and to make up their minds regarding which research stream to follow.…”

“…For example, Richter et al (2020) subject the PLS‐SEM‐produced construct scores to a necessary condition analysis (NCA). By following a necessity logic, NCA implies that an outcome—or a certain level of an outcome—can only be achieved if the necessary cause is in place, or is at a certain level (see also Rasoolimanesh et al, 2021). PLS‐SEM‐based construct scores have also been used in other contexts, such as in the identification and treatment of endogeneity (Hult et al, 2018).…”

Guest editorial: Sports management research using partial least squares structural equation modeling (PLS-SEM)

“…The emergence of more complex modeling requirements goes hand-in-hand with (and confirms) the critical importance of advanced analytical methods and robustness checks (Sarstedt et al, 2020b). These include confirmatory tetrad analysis to empirically assess the mode of measurement (Gudergan et al, 2008), necessary condition analysis (NCA) and fuzzy set qualitative confirmatory analysis to support theoretically established relationships in the structural model (Rasoolimanesh et al, 2021a;Richter et al, 2020), nonlinear relationships (Basco et al, 2021), finite mixture and prediction-oriented segmentation analysis to identify and treat unobserved heterogeneity (Becker et al, 2013;Hair et al, 2016;Sarstedt et al, 2017Sarstedt et al, , 2021a and many other advances in composite-based SEM (for an overview, see Hair et al, 2022).…”