Asymmetric modeling of intention to purchase tourism weather insurance and loyalty

This study aims to craft and test a theory by examining the combinations of causal antecedents for predicting intention to purchase tourism weather insurance (IPTWI) and destination loyalty. Weather expectation, disconfirmation, perceived risk, and visit time are used as ingredients of complex configurations. To assess occurrences of both positive and negative contrarian cases, cross-tabulations were performed with data from tourists who traveled to a Mediterranean island (North Cyprus). Asymmetrical fuzzy set Qualitative Comparative Analysis (fsQCA) data analyses were run to identify recipes of antecedent conditions for predicting high scores in IPTWI and loyalty. Results from fsQCA support the major tenets of complexity theory. Apart from fit validity of the measurement model, evidence of predictive validity of algorithm models is provided. This study tests an empirical model with complexity theory that contributes to the literature by providing new insights into the configural conditions indicating high score for IPTWI and loyalty, which is useful for proposing new risk-attached services (e.g., tourism weather insurance).