A Sustainability Assessment of Artificial Intelligence Applications in Tourism Management Using an Entropy–TOPSIS Framework

Artificial intelligence (AI) is increasingly transforming tourism management by improving operational efficiency, enhancing visitor experiences, and supporting sustainability objectives. However, existing studies primarily focus on individual AI technologies and lack a comprehensive framework for comparing their sustainability performance. Therefore, this study evaluates and ranks major AI applications used in tourism management from a sustainability perspective. An integrated Entropy–TOPSIS framework was developed to assess six AI applications: Generative AI Systems, AI Chatbots, Digital Twin Systems, Smart Destination Management, Smart Governance, and Open Data Tourism Platforms. Ten evaluation criteria covering economic, environmental, social, managerial, and ethical dimensions were identified through a comprehensive literature review. The Entropy method was employed to determine objective criterion weights, while the TOPSIS method was used to rank the alternatives. The results indicate that personalization capability, privacy and ethical risk, and energy efficiency are the most discriminating evaluation criteria, with weights of 0.2217, 0.2190, and 0.2108, respectively. Smart Destination Management achieved the highest sustainability performance (CC = 0.5968), followed closely by Digital Twin Systems (CC = 0.5950) and Open Data Tourism Platforms (CC = 0.4978). The findings suggest that AI applications integrating sustainability-oriented destination management, operational intelligence, and personalized visitor services outperform solutions focusing on isolated technological functions. The proposed framework offers a practical decision support tool for tourism managers and policymakers seeking to prioritize AI investments that maximize sustainability outcomes while supporting responsible digital transformation.