Ecotourism Dynamics and AI Integration: Study of Dumboor Lake in Tripura, India

Abstract

This study assesses the ecotourism potential of Tripura with a specific focus on Dumboor Lake by integrating tourist inflow trends, destination rankings, visitor characteristics, and perceptions toward artificial intelligence (AI) in tourism management. The primary objective is to understand the emerging role of AI in strengthening sustainability, enhancing visitor experience, and improving safety and environmental monitoring in lake tourism. The study employs a mixed-method approach, combining secondary data on domestic and foreign tourist arrivals and online travel platform rankings with a field survey of 112 tourists conducted along the banks of Dumboor Lake. Findings indicate a substantial rise in tourist inflow between 2022 and 2024, underscoring the growing economic relevance of the lake within Tripura’s tourism landscape. Although heritage sites dominate digital rankings, natural and ecotourism destinations such as Dumboor Lake show significant scope for improved promotion, infrastructure investment, and technological integration. Survey results reveal that visitors are largely family and excursion groups, represent budget-to-mid-range expenditure patterns, and prefer self-organised travel. Perception analysis confirms strong acceptance of AI applications for ecosystem management, navigation, immersive experiences, and safety services. Statistical tests further establish that technological, environmental, institutional, and social factors significantly influence AI adoption. The study highlights the need for sustainable development, digital enhancement, and community-driven ecotourism strategies in Tripura.