Service quality rankings are pivotal for maintaining sustainability in the fiercely competitive airline industry. However, prior research in this domain has often fallen short in aspects of sample size, efficiency, and dependability. This study introduces refined insights into this area and establishes a comprehensive, yet highly elucidative, ranking framework. Initially, we employ Latent Semantic Analysis (LSA) to distill principal themes and sentiments from online reviews of 80 airlines. Subsequently, we utilize the SentiWordNet lexicon and the TextBlob package for conducting sentiment analysis based on these reviews. Following this, we construct a hierarchical structure using the computation of compromise solutions, employing an integrated Technique for Order Preference by Similarity to Ideal Solution, vis-\`a-vis Kriterijumska Optimizacija I Kompromisno Resenje-Adversarial Interpretive Structural Model (TOPSIS-VIKOR-AISM) methodology. Beyond aiding consumer decision-making and fostering airline growth, this study contributes novel viewpoints on evaluating the efficacy of airlines and other sectors.

翻译：服务质量排名对于维持竞争激烈的航空业的可持续性至关重要。然而，该领域先前的研究在样本量、效率和可靠性方面往往存在不足。本研究对该领域提出了更深入的见解，并构建了一个全面且具有高度解释性的排名框架。首先，我们采用潜在语义分析（LSA）从80家航空公司的在线评论中提取主要主题和情感。随后，利用SentiWordNet词典和TextBlob包基于这些评论进行情感分析。在此基础上，我们通过集成逼近理想解排序法、折衷排序法与对抗性解释结构模型（TOPSIS-VIKOR-AISM）方法论计算折衷解，构建了层次结构。除了有助于消费者决策和促进航空公司发展外，本研究还为评估航空公司及其他行业效能提供了新视角。