论文标题
通过全面的文本挖掘和Topsis-Vikor-Aism分析评估航空公司服务质量
Evaluating Airline Service Quality Through the Comprehensive Text-mining and TOPSIS-VIKOR-AISM Analysis
论文作者
论文摘要
服务质量排名对于维持竞争激烈的航空公司行业的可持续性至关重要。但是，该领域的先前研究通常在样本量，效率和可靠性方面缺乏。这项研究介绍了对这一领域的精致见解，并建立了一个全面但高度阐述的排名框架。最初，我们采用潜在语义分析（LSA）来提炼80个航空公司在线评论中的主要主题和情感。随后，我们利用Sentiwordnet词典和TextBlob软件包来基于这些评论进行情感分析。之后，我们使用折衷解决方案的计算来构建层次结构，采用集成技术来通过与理想解决方案相似的订单偏好，相对于Kriterijumska OptimizacijaCijaCijai i kompromisno i kompromisno recenenje resenje reasenje-反逆转解释性结构模型（topsis-vikor-aism）方法。除了帮助消费者的决策和促进航空公司的增长外，这项研究还为评估航空公司和其他部门的功效提供了新的观点。
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-à-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.
