Evaluating the determinants of sustainable tourists perceptions and tourist well being in Bangladesh

Abstract Tourism is increasingly recognized not only for its economic and recreational value but also for its potential to promote environmental and social sustainability. This study explores the sustainable tourists’ perceptions and their impact on tourist well-being, emphasizing how destination attributes aligned with sustainability influence these perceptions. Drawing on data from 209 Bangladeshi tourists across diverse destinations, collected via a purposive sampling method, the study applies a triangulated methodological framework—Partial Least Squares Structural Equation Modeling (PLS-SEM), Necessary Condition Analysis (NCA), and Artificial Neural Network (ANN)—to deliver robust insights. The findings underscore the pivotal role of social media in shaping sustainable tourists' perceptions by disseminating sustainability-related information and narratives. Transport facilities, evaluated through the sustainability lens (e.g., accessibility to eco-friendly transport), show varying degrees of influence. Importantly, tourists’ knowledge—particularly regarding sustainable practices and destinations—emerges as a consistent and critical driver of perception. Additionally, weather and climate, often overlooked in sustainability discourse, positively affect tourists’ sustainable perceptions, though the strength of this effect varies across methods. The study offers actionable implications for tourism stakeholders. Emphasizing sustainability in social media content, investing in green transport infrastructure, and enhancing environmental awareness among tourists are essential strategies for fostering sustainable tourism. By integrating PLS-SEM, NCA, and ANN, this research provides comprehensive guidelines for the tourism industry to align services and communications with sustainability goals in the post-COVID-19 era.