Sustainable Environmental Tourism Practices and their Relationship with Tourist Satisfaction in Geotourism Areas in Bohol
by Carolyn B. Rabago, Heart Evanne A. Mejor, Hersheylou M. Cabig, Resalyn T. Lagura
Published: April 30, 2026 • DOI: 10.47772/IJRISS.2026.100400136
Abstract
This study assessed the sustainable environmental tourism practices and their relationship with tourist satisfaction in geotourism areas in Bohol, Philippines. Specifically, it examined sustainability practices in three dimensions—solid waste management, water conservation, and energy efficiency—and evaluated tourist satisfaction through service quality and physical environment. Using a descriptive-correlational design, data were collected from 300 tourists visiting four geotourism sites: Can-umantad Falls (Candijay), Cabagnow Cave Pool (Anda), Hinagdanan Cave (Dauis), and Pahangog Twin Falls (Dimiao). Results showed that tourists perceived sustainable practices at a high level (grand mean = 3.60), with solid waste management rated highest and energy efficiency lowest. Tourist satisfaction was also notably high (grand mean = 3.47), driven primarily by staff hospitality and site safety. A significant positive relationship was found between sustainable environmental tourism practices and tourist satisfaction (r = 0.459, p < .001), although the R² of 0.211 indicated that sustainability practices accounted for 21.1% of variance in satisfaction. Age and civil status significantly predicted both sustainability perception and satisfaction, while educational attainment was the only variable showing a significant difference in satisfaction levels. The study recommends stronger visibility of energy-saving measures, improved enforcement of conservation policies, and continued investment in hospitality and comfort infrastructure. The modest R² highlights the multi-dimensional nature of tourist satisfaction and calls for future multi-predictor models. Limitations include the reliance on convenience sampling and self-reported data; future research should employ probability sampling, expanded multi-destination scopes, and mixed-methods designs to strengthen generalizability and causal inference.