ISSN: 2226-3624
Open access
This study investigates the intricate interplay between economic, environmental, and social sustainability in the context of rural tourism, with a particular focus on their influence on tourist experience and loyalty. Utilizing structural equation modeling and innovative predictive analysis techniques, the research empirically validates a comprehensive model. Out of the 443 surveys distributed, 337 were successfully collected, yielding a response rate of 75.8%, which is considered adequate for applying structural equation modeling (SEM) in data analysis. From the collected surveys, 319 were identified as clean and deemed suitable for detailed analysis. To conduct data analysis and test the hypotheses, researchers chose the Smartpls4 software. This software is acknowledged for its proficiency in employing structural equation modeling (SEM) techniques, aligning seamlessly with the study's analytical requirements, and adhering to the guidelines outlined in the research methodology. The results reveal that economic sustainability significantly impacts both tourist experience and loyalty. Collaborative economic practices with local businesses, culturally enriching activities, and fair economic engagement emerge as critical strategies for rural tourism operators. Similarly, environmental sustainability plays a pivotal role, with eco-friendly practices, natural resource preservation, and showcasing ecological diversity contributing significantly to both tourist experience and loyalty. Social sustainability, encompassing community engagement and cultural initiatives, emerges as a crucial factor influencing both dimensions. The study also introduces the mediating role of the tourist experience, indicating that the overall quality of interactions shapes the relationship between sustainability components and loyalty. Practically, the research provides actionable strategies for rural tourism operators to enhance sustainability and foster loyalty, emphasizing the importance of creating memorable and immersive experiences. The study's methodological contributions include the use of PLSpredict and the Cross-Validated Predictive Ability Test (CVPAT) for robust predictive analysis. Theoretical advancements encompass refining frameworks to comprehend the complex relationships among sustainability dimensions, tourist experience, and loyalty. Suggestions for future research involve exploring the impact of emerging technologies, investigating cultural and socio-economic influences, and conducting longitudinal studies to track the evolution of tourist loyalty over time.
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