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

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Authors: Thudugalage Don Chaminda Pushpakumara, Fazeela Jameel Ahsan, D. A. C. Suranga Silva
Cited by: 2
References: 66

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.

Fields of Study & Subjects

AI in Service Interactions Digital Marketing and Social Media Technology Adoption and User Behaviour

Publication details

Journal / source
Journal of Intelligent Learning Systems and Applications
Publisher
Scientific Research Publishing, Inc.
Volume
18
Issue
01
Pages
45–76
Publication date
1 January 2026