The Applications of Artificial Intelligence in Tourism

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closed (30 June 2025)

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31 August 2025

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Topic Information

Dear Colleagues,

Recent developments in Artificial Intelligence (AI), primarily due to the widespread use of large language models, are transforming different sectors. In tourism, AI has the potential to enable advanced data-driven decision making, personalize traveler experiences, and optimize operations across industries. AI applications in tourism span a wide array of areas, including visitor behavior analysis, real-time service enhancements, predictive modeling, and destination management. From AI-powered chatbots assisting travelers to machine learning models predicting demand and optimizing resources, AI can potentially reshape how tourism services are delivered and experienced. In this Topic, we spotlight innovative strategies within the tourism sector using AI, covering customer personalization, adaptive marketing, dynamic pricing, cultural heritage preservation, and more. This Topic on “The Applications of Artificial Intelligence in Tourism” offers a platform for publishing comprehensive reviews exploring the benefits and challenges of AI in tourism, as well as original research. We invite contributions with diverse perspectives on AI’s role in evolving and personalizing the tourism experience.

Dr. Angelica Lo Duca
Dr. Jose Berengueres
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
World world	1.9	-	2020	28.6 Days	CHF 1200	Submit
Informatics informatics	2.8	8.4	2014	34.9 Days	CHF 1800	Submit
Information information	2.9	6.5	2010	18.6 Days	CHF 1800	Submit

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19 pages, 1630 KiB  

Open AccessArticle

Tourism Resource Evaluation Integrating FNN and AHP-FCE: A Case Study of Guilin

by Xujiang Qin, Zhuo Peng, Xin Zhang and Xiang Yang

Informatics 2025, 12(2), 54; https://doi.org/10.3390/informatics12020054 - 17 Jun 2025

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Abstract

With the rapid development of the tourism industry, scientific evaluation of tourism resources is crucial to realize sustainable development. Especially how to quantify resource advantages in international tourism cities has become an important basis for tourism planning and policy making. However, the limitations [...] Read more.

With the rapid development of the tourism industry, scientific evaluation of tourism resources is crucial to realize sustainable development. Especially how to quantify resource advantages in international tourism cities has become an important basis for tourism planning and policy making. However, the limitations of traditional evaluation methods in the allocation of indicator weights and nonlinear data processing make it difficult to meet the development needs of international tourism cities. Therefore, this study takes Guilin, an international tourist city, as the research object and proposes a hybrid framework integrating fuzzy neural network (FNN) and analytic hierarchy process-fuzzy comprehensive evaluation (AHP-FCE). Based on 800 questionnaire data covering tourists, practitioners, and local residents, the study constructed a multilevel evaluation system (containing 12 specific indexes in the three dimensions of nature, service, and culture) using the Delphi method of expert interviews. It is found that AHP-FCE can effectively analyze the hierarchical relationship of evaluation indexes, but it is easily affected by the subjective judgment of experts. In contrast, FNN can effectively improve evaluation accuracy through the adaptive learning mechanism, and it especially shows significant advantages in dealing with tourists’ perception data. The empirical analysis shows that Guilin has obvious room for improvement in “environmental friendliness” and “cultural communication effectiveness”. The integration framework proposed in this study aims to enhance the scientific validity and accuracy of the assessment results, and provides reference and inspiration for the sustainable development of Guilin international tourism destination. Full article

(This article belongs to the Topic The Applications of Artificial Intelligence in Tourism)

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