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<p>Traditional decision-making methods often lack effective technology in multi-dimensional, fuzzy, and uncertain tourism contexts. This study proposes an extended VIKOR (VlseKriterijuska Optimizacija I Komoromisno Resenje) method, integrating probabilistic linguistic term sets (PLTS) and regret theory for evaluating generative artificial intelligence (GAI) in Tourism. This combination enables more accurate, adaptable assessments by effectively capturing fuzziness and uncertainty while incorporating trade-offs among criteria and decision-makers’ psychological factors. A case study, parameter analysis, and comparison with the extended TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method verify the method’s robustness and efficacy. This method not only facilitates structured, data-driven decision-making but also highlights the strategic potential of GAI in enhancing tourism experiences and operational efficiency. The research results discover that the extended VIKOR method not only provides more effective and robust GAI tool assessments within complex tourism scenarios but also establishes a theoretical foundation and reference framework to support optimal GAI tool selection, which can provide significant academic and practical value for natural language processing.</p>

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Evaluation of generative artificial intelligence tools in tourism using the extended VIKOR method with probabilistic linguistic information incorporating regret theory

  • 期刊论文

  • 发表日期：

    2025年12月18日

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  • Wenshuai Wu,
  • Rob Law

摘要

Traditional decision-making methods often lack effective technology in multi-dimensional, fuzzy, and uncertain tourism contexts. This study proposes an extended VIKOR (VlseKriterijuska Optimizacija I Komoromisno Resenje) method, integrating probabilistic linguistic term sets (PLTS) and regret theory for evaluating generative artificial intelligence (GAI) in Tourism. This combination enables more accurate, adaptable assessments by effectively capturing fuzziness and uncertainty while incorporating trade-offs among criteria and decision-makers’ psychological factors. A case study, parameter analysis, and comparison with the extended TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method verify the method’s robustness and efficacy. This method not only facilitates structured, data-driven decision-making but also highlights the strategic potential of GAI in enhancing tourism experiences and operational efficiency. The research results discover that the extended VIKOR method not only provides more effective and robust GAI tool assessments within complex tourism scenarios but also establishes a theoretical foundation and reference framework to support optimal GAI tool selection, which can provide significant academic and practical value for natural language processing.