This study investigates the increasingly important issue of sustainable tourism development through the lens of Big Data analytics, economic considerations, and policy frameworks. Guided by the Theory of Planned Behavior, we formulated seven hypotheses to explore how these variables impact attitudes, subjective norms, perceived behavioral control, intentions, and actual engagement in sustainable tourism. Using a questionnaire-based survey we collected data from N=398 respondents and employing Structural Equation Modeling (SEM) for data analysis, we found substantial evidence supporting our hypotheses. Findings revealed that Big Data analytics significantly influence attitudes towards sustainable tourism. Economic factors shape societal norms and expectations regarding sustainable tourism, whereas policy frameworks impact individuals' perceived control over sustainable tourism activities. The study also confirmed that positive attitudes towards sustainable tourism led to higher intentions to engage in such practices, which in turn are predictive of actual engagement. Furthermore, societal norms and perceived behavioural control were found to be significant predictors of both the intention to engage in and the actual engagement with sustainable tourism practices. Overall, the results indicate that Big Data analytics play a significant role in shaping attitudes and behaviors towards sustainable tourism. Moreover, economic and policy considerations were also found to be key determinants. This research not only fills a scholarly gap but also provides actionable insights for policymakers and business stakeholders in the tourism sector.