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Artificial Intelligence (AI) Adoption for Ecotourism Development: A Multi-Stakeholder Analysis in Sri Lanka

DOI: 10.4236/jilsa.2026.181004, PP. 45-76

Keywords: Artificial Intelligence, Chatbots, Ecotourism, Sustainable Tourism, UTAUT, Organizational Readiness, Institutional Theory, Sri Lanka

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Abstract:

Artificial Intelligence (AI) offers transformative potential for the tourism industry by enhancing operational efficiency, personalizing visitor experiences, and advancing sustainability objectives. In the ecotourism sector, AI-powered chatbots can provide real-time information, facilitate bookings, promote eco-friendly practices, and engage visitors in conservation awareness. Despite these benefits, adoption within Sri Lanka’s ecotourism industry remains limited, hindered by infrastructural constraints, organizational readiness, and varying levels of tourist acceptance. This study adopts an exploratory sequential mixed-methods design to investigate the technological, organizational, and behavioral factors influencing the adoption intention and actual usage of AI chatbots among ecotourism service providers and tourists in Sri Lanka. In the first qualitative phase, semi-structured interviews with ecotourism operators will identify context-specific barriers and enablers such as digital literacy, infrastructure readiness, workforce capabilities, and Corporate Social Responsibility (CSR). Insights from this phase will refine the subsequent survey instrument. In the second quantitative phase, a stratified random sample of tourists and service providers will be surveyed, and data will be analyzed using Structural Equation Modeling (SEM) to test hypothesized relationships among constructs. Grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT), Organizational Readiness for Change (ORC), and Institutional Theory, the research examines performance expectancy, effort expectancy, social influence, facilitating conditions, perceived trust, anthropomorphism, perceived intelligence, technological anxiety, cost considerations, workforce capabilities, sustainable initiatives, and CSR. The findings are expected to generate empirical insights into adoption drivers and barriers while integrating stakeholder perspectives, offering practical and policy recommendations to enhance AI integration for sustainable ecotourism development in Sri Lanka.

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