Can tourist engagement enhance tourist behavioural intentions? A combination of PLS-SEM and fsQCA approaches

Abstract

This study aims to investigate the effects of tourist engagement dimensions on revisit and word of mouth (WOM) intentions of heritage tourists. The data were collected from domestic tourists in the heritage city of Kashan, Iran. To analyse the collected data, this study applies Partial Least Squares -Structural Equation Modeling (PLS-SEM) as a symmetric analysis technique, as well as fuzzy-set Qualitative Comparative Analysis (fsQCA) as an asymmetric analysis approach to strengthen the findings. The findings of PLS-SEM showed the significant effect of the absorption dimension on revisit intention, whereas these results demonstrated the significant effects of the dimensions of interaction, and identification on WOM intention. However, the results of fsQCA identified more heterogenous combinations of dimensions of visitor engagement to predict revisit and WOM intentions. Overall, this study contributes to the extant literature on tourist engagement by constructing a composite picture of tourist engagement dimensions on the behavioral intentions of heritage tourists. The study's theoretical contributions, its restrictions and practical implications for heritage site operators are further discussed.

People’s expectations and experiences of big data collection in the Saudi context

“…Necessary conditions analysis entails determining if each antecedent condition’s personal effect is required for the recommended results. If a causal condition is always present when the result is established, it is said to be “necessary conditions.” If the consistency scores of a necessary component surpass 0.90, it can be verified ( Schneider & Wagemann, 2010 ; Seyfi et al, 2021 ). The necessary conditions for generating higher behavioural intention to use remanufactured products were analyzed.…”

“…For instance, customer diversification in terms of control, privacy and regulation and data collection towards consumer autonomy may not be captured in a framework examined using conservative multivariate regression techniques. Thereby, due to the restrictions of previous existing papers, which used orthodox multivariate methods such as SEM to examine differences among countries, this study employs asymmetric affiliation between concepts and introduces the influence of a construct on the output, whilst complexity theory and configurational models necessitate that researched variables be necessary ( Seyfi et al, 2021 ).…”

“…Prior researchers have incorporated both symmetrical (SEM) and asymmetrical (fsQCA) econometric methodologies to gain a better understanding of complex human behaviour ( Pappas & Woodside, 2021 ; Seyfi et al, 2021 ). For the significance of hypothesized relationships in the proposed model, researchers in this study have used PLS-SEM software.…”

“…There are three steps involved using fsQCA, i.e ., calibration, truth table and counterfactual analysis. Calibration converts the crisp values into fuzzy set values ( Woodside, 2014 ; Seyfi et al, 2021 ). fsQCA treats each variable as if it were part of a loosely defined set whose membership values change over time ( Ragin, 2008 ).…”

“…Lastly, counterfactual analysis, also known as necessary conditions analysis (NCA), enables scholars to determine the necessary and sufficient factors to predict the proposed outcome ( Schneider & Wagemann, 2010 ; Coelho et al, 2021 ). In this regard, two criteria are used: consistency and coverage to select the excellent and necessary recipes ( Seyfi et al, 2021 ). In NCA, a condition is essential if it has a consistency is more than 0.90, whereas it is found sufficient it has found to have coverage of more than 0.20.…”