The tourism sector is significant in emerging nations like Thailand. The cost of lodging is a significant component of practically every trip, thus it is important to consider accommodation development while trying to draw in visitors from other nations. The long-stay tourism industry is crucial since longer visitor stays result in more revenue. Following this, other research on long-term lodging of all forms has been conducted, with an emphasis on both the tourist and real estate sectors. The best tourist option in Thailand is long-term travel. As evidenced by the American, European, and Japanese visitors, the target market is tourists from nations with high costs of living, frigid climates, and aging populations. Therefore, it is anticipated that the tourist demographic will change in future, leading to the emergence of the retirement home niche market as a part of long-stay tourism. The characteristics of long-stay tourism in Thailand are examined in this paper, and we assess the theoretical and conceptual framework as an analysis of Thailand's tourism. Examining the current situation of the Thai long-stay tourist business is the initial and main objective of this study. There is currently no perfect answer, but various alternatives from comparable markets in representative nations have been used as examples to subsequently create tourism accommodation in Thailand for long-stay tourism.

Creative tourism in Thailand’s rural mountain areas provides new opportunities for local economic development while supporting cultural heritage preservation. This study identifies creative tourist segments using K-means cluster analysis based on survey data collected from 404 Thai visitors to the Pha Chang Noi region in Phayao and Nan provinces. These groups reflect both global trends in creative tourism and specific Thai preferences for festivals and communal experiences. The findings provide insights for the expansion of culturally and sustainable tourism resort approaches to rural Thailand. By understanding tourist motivations, local communities can shape TR offerings to enhance tourist satisfaction by protecting cultural heritage and strengthening local communities. This research provides a deeper meaning for sociodemographic (SD) factors, cultural values, and current travel motivations that shape behavior in rural areas. These insights can help TR planners design initiatives that align with community strengthening, which promotes sustainable engagement. This study contributes SD factors, motivation towards post-pandemic situations, and local cultural contexts that impact TR behavior and provide insights for designing culturally sensitive tourism.

The tourism sector is significant in emerging nations like Thailand. The cost of lodging is a significant component of practically every trip, thus it is important to consider accommodation development while trying to draw in visitors from other nations. The long-stay tourism industry is crucial since longer visitor stays result in more revenue. Following this, other research on long-term lodging of all forms has been conducted, with an emphasis on both the tourist and real estate sectors. The best tourist option in Thailand is long-term travel. As evidenced by the American, European, and Japanese visitors, the target market is tourists from nations with high costs of living, frigid climates, and aging populations. Therefore, it is anticipated that the tourist demographic will change in future, leading to the emergence of the retirement home niche market as a part of long-stay tourism. The characteristics of long-stay tourism in Thailand are examined in this paper, and we assess the theoretical and conceptual framework as an analysis of Thailand's tourism. Examining the current situation of the Thai long-stay tourist business is the initial and main objective of this study. There is currently no perfect answer, but various alternatives from comparable markets in representative nations have been used as examples to subsequently create tourism accommodation in Thailand for long-stay tourism.

Local food tourism (LFT) significantly impacts destination experiences by shaping tourists’ perceptions, satisfaction, and post-visit behavior. The limited empirical understanding of how experiential attributes influence satisfaction and behavioral intention (BI). This research uses a thorough Structural Equation Modeling (SEM) framework to examine the variables affecting customer satisfaction (CS) and business intelligence (BI) in LFT. 380 valid responses were obtained from a quantitative cross-sectional survey of visitors who sampled local cuisine at particular Thai culinary sites. A structured questionnaire measured six exogenous constructs: food quality (FQ), Authenticity (AU), service quality (SQ), physical environment (PE), cultural experience (CE), and perceived value (PV) along with CS as a mediator and BI (revisit intention and Consumer referral behavior) as the endogenous outcome. Cronbach’s alpha, composite reliability (CR), average variance extracted (AVE), and discriminant validity using the Fornell-Larcker criterion were used to evaluate reliability and validity. Utilizing confirmatory factor analysis (CFA), the measurement model was validated. The findings suggest that CS is strongly and favorably influenced by FQ, AU, CE, and PV. The association between experience qualities and loyalty outcomes is partially mediated by CS, which also strongly predicts BI. A well-fitting measurement model is indicated by the model’s acceptable goodness-of-fit indices, which include a Comparative Fit Index (CFI) of 0.952, Tucker–Lewis Index (TLI) of 0.945, Root Mean Square Error of Approximation (RMSEA) of 0.056, and Standardized Root Mean Square Residual (SRMR) of 0.058. SPSS findings provide practical insights for enhancing tourist loyalty through authentic and high-quality culinary experiences.

Sustainable tourism has emerged as an important approach in achieving a harmonious balance between economic development and environmental protection in destinations following low carbon development approaches. This study explores the working mechanism of resilient low carbon tourism destinations through exploring failure management, infrastructure resilience, low carbon practices, and communication quality at major destinations in Thailand, such as Bangkok, Phuket, and Chiang Mai. The study made use of an explanatory sequential mixed methods approach whereby quantitative data was first collected from 602 tourists and followed by an interpretative approach using semi-structured interviews conducted among 30 individuals. The results of structural equation modeling (SEM) analysis show that low carbon practices, infrastructure resilience, and communication quality positively affect tourist satisfaction, while perceived failure dimensions have an adverse impact on satisfaction and destination loyalty indirectly. In particular, the qualitative phase focused on providing explanations related to the findings of SEM analysis with special attention paid to tourist perception and experience of implemented strategies aimed at enhancing resilience and sustainability at tourist destinations. Thematic analysis of interview data allowed the emergence of several themes, including perceived failures of services and the environment, low carbon adaptation, infrastructure resilience, and open communication promoting trust and loyalty.

Local food tourism (LFT) significantly impacts destination experiences by shaping tourists’ perceptions, satisfaction, and post-visit behavior. The limited empirical understanding of how experiential attributes influence satisfaction and behavioral intention (BI). This research uses a thorough Structural Equation Modeling (SEM) framework to examine the variables affecting customer satisfaction (CS) and business intelligence (BI) in LFT. 380 valid responses were obtained from a quantitative cross-sectional survey of visitors who sampled local cuisine at particular Thai culinary sites. A structured questionnaire measured six exogenous constructs: food quality (FQ), Authenticity (AU), service quality (SQ), physical environment (PE), cultural experience (CE), and perceived value (PV) along with CS as a mediator and BI (revisit intention and Consumer referral behavior) as the endogenous outcome. Cronbach’s alpha, composite reliability (CR), average variance extracted (AVE), and discriminant validity using the Fornell-Larcker criterion were used to evaluate reliability and validity. Utilizing confirmatory factor analysis (CFA), the measurement model was validated. The findings suggest that CS is strongly and favorably influenced by FQ, AU, CE, and PV. The association between experience qualities and loyalty outcomes is partially mediated by CS, which also strongly predicts BI. A well-fitting measurement model is indicated by the model’s acceptable goodness-of-fit indices, which include a Comparative Fit Index (CFI) of 0.952, Tucker–Lewis Index (TLI) of 0.945, Root Mean Square Error of Approximation (RMSEA) of 0.056, and Standardized Root Mean Square Residual (SRMR) of 0.058. SPSS findings provide practical insights for enhancing tourist loyalty through authentic and high-quality culinary experiences.