Exploring Global Tourism Trends Through Mathematical Modeling: Service Quality and Revisit Intentions

Abstract

The global tourism industry is a dynamic and ever-evolving sector influenced by economic, cultural, and technological factors. This study explores global tourism trends by leveraging mathematical modeling to evaluate the relationship between service quality and revisit intentions. Using a combination of predictive analytics, regression models, and structural equation modeling (SEM), the research examines how critical factors such as customer satisfaction, cultural immersion, and technological advancements in hospitality influence tourists' decisions to revisit destinations. Data collected from international tourists across major global destinations provide insights into the role of service quality dimensions, including reliability, responsiveness, assurance, and empathy, in shaping customer experiences. The findings highlight that high service quality significantly enhances customer satisfaction and fosters strong revisit intentions, moderated by demographic and psychographic variables. Moreover, the study identifies regional variations in tourist preferences, driven by cultural and technological differences. This research contributes to the understanding of tourism dynamics and provides actionable insights for stakeholders in the tourism and hospitality sectors to improve service delivery and enhance customer loyalty. By integrating mathematical modeling into tourism research, the study offers a robust framework for forecasting trends, optimizing resources, and supporting sustainable tourism practices globally.