Tourism engaging with the public health agenda: can we promote 'wellville' as a destination of choice?

Attribute Framework Validation for Wellness Tourism within the Context of Thailand

Background: Research on the theoretical integration of attributes of wellness tourism in the form of the physical, mental, spiritual, and environmental (PMSE) attribute framework and the effect of cultural differences on the framework validation has not been conducted before. Objectives: This study developed and validated the key underlying attributes of the wellness tourism experience framework within the Thailand context. Methods: From reviewing the related literature to identify potential sub attributes under the four dimensions of the PMSE framework, themes were developed using a theory- and prior research-driven method within different cultural contexts. The fitness of the PMSE attribute framework model within the context of Thailand wellness tourism was confirmed through a survey design with a quantitative approach from the generalities of the sample groups. The entire dataset was statistically tested with descriptive statistics and confirmatory factor analysis (CFA). Results and Conclusions: After adjustments, the four-factors with a 28-item model substantiated the data. The results validated that the mental experience dimension accounted for the most variance, with an indicator value of 0.99 in the framework, predicting the effective wellness tourism experience better than the other attributes. Experience design should involve the participation of all stakeholders in the wellness tourism system in terms of managerial contribution. Recommendations for the planning of wellness experiences concerning each four-factor will be investigated in future studies.

Post-COVID-19 Tourists’ Preferences, Attitudes and Travel Expectations: A Study in Guayaquil, Ecuador

Expectations about a destination influence the tourist experience during the travel process stages. In the post-COVID-19 normalcy, people are adjusting their priorities and social values. Therefore, it becomes crucial to identify tourists’ expectations before traveling. The objectives of this research were: (a) identify the preferences of tourists; (b) establish the attitudes of tourists; and (c) determine the expectations of tourists for post-COVID-19 destination selection. The study analyzed a sample of 491 people during pandemic lockdowns in Guayaquil, Ecuador. Statistical techniques such as exploratory and confirmatory factor analysis were used in data analysis. The results show that after the pandemic, tourists prefer urban tourism, followed by cultural tourism and traveling with relatives. It also shows a more responsible and supportive attitude when traveling. Likewise, the results support the dimensional structure that explains a set of post-pandemic tourist expectations. Five factors were identified: Smart Care, pricing strategy, safety, comfort, and social distancing. Finally, the theoretical and managerial implications of the results that will guide for tourism destination managers were discussed.

Sustainable Growth of Social Tourism: A Growth Mixture Modeling Approach Using Heterogeneous Travel Frequency Trajectories

As travel activity has gained attention as one of the essential ways of understanding the sustainable growth of social tourism, a growing number of research projects have been conducted to elucidate the relationship between residents’ travel quantity (frequency) and quality (experience) in both macro and micro perspectives. Yet, very little research has highlighted that travel opportunities are not equally available to residents, especially a longitudinal perspective. The current study classified domestic travelers into four distinct classes using four years of longitudinal data from 5054 Korean residents. Latent growth curve modeling (LGCM) and growth mixture modeling (GMM) were employed to find out (1) the optimal number of classes, (2) the longitudinal travel frequency trajectory of each class, and (3) the distinctive demographic and travel characteristics of the four classes. This study provides some practical implications for policymakers when optimizing available resources for sustainable travel opportunities to relevant target sub-populations. Furthermore, detailed step-by-step analytic tutorials are also introduced for the extended application of longitudinal latent variable analysis in the tourism and hospitality fields, providing additional insights for relevant stakeholders.