What the paper studied
Existing research on AI in tourism tends to look at individual technologies in isolation, without a common way to compare their sustainability performance. This study evaluates and ranks six major AI applications in tourism management from a sustainability perspective using an integrated Entropy–TOPSIS multi-criteria decision-making framework. The six applications assessed are Generative AI Systems, AI Chatbots, Digital Twin Systems, Smart Destination Management, Smart Governance, and Open Data Tourism Platforms. Ten evaluation criteria spanning economic, environmental, social, managerial, and ethical dimensions were drawn from a literature review; Entropy fixed the objective weights and TOPSIS produced the rankings.
Key findings
- Personalization capability (weight 0.2217), privacy and ethical risk (0.2190), and energy efficiency (0.2108) were the most discriminating sustainability criteria.
- Smart Destination Management ranked highest overall (CC = 0.5968), followed by Digital Twin Systems (0.5950) and Open Data Tourism Platforms (0.4978).
- AI applications that combine sustainability-oriented destination management, operational intelligence, and personalized visitor services outperform those focused on isolated technological functions.
Why it matters for hospitality and tourism
Destinations and tourism operators are being pushed to invest in AI while also meeting sustainability goals. This paper gives them a defensible way to compare candidate AI investments — not just by hype or vendor claims, but against a common set of economic, environmental, social, managerial, and ethical criteria. The finding that integrated destination-level solutions beat single-purpose tools has direct implications for how DMOs and tourism boards prioritize spend.
Practical takeaways
- Use a multi-criteria framework (like Entropy–TOPSIS) rather than intuition when comparing AI vendors or applications for sustainability impact.
- Weight personalization capability, privacy/ethical risk, and energy efficiency heavily — they discriminate performance most.
- Favor AI investments that operate at the destination or ecosystem level (smart destination management, digital twins, open data platforms) over narrow point solutions.