Evaluating airline service quality through a comprehensive text-mining and multi-criteria decision-making analysis

IF 3.9 2区工程技术 Q2 TRANSPORTATION

Journal of Air Transport Management Pub Date : 2024-08-01 DOI:10.1016/j.jairtraman.2024.102655

Haotian Xie , Yi Li , Yang Pu , Chen Zhang , Junlin Huang

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引用次数: 0

Abstract

Service quality is of paramount importance for the long-term sustainability of the airline industry, which is characterized by intense competition. However, previous research in this field has frequently been limited by shortcomings in sample size, efficiency, and dependability. This study addresses these deficiencies by introducing refined insights and establishing 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 employ the SentiWordNet lexicon and the TextBlob package for sentiment analysis based on the aforementioned 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. Finally, the ranking of airlines from best to worst based on perceptions gained from online reviews provides an immediate visualization solution. This study not only assists consumers in making informed decisions but also provides airlines with insights that can be used to enhance their service offerings. The study presents novel insights into the assessment of service quality, with potential applicability to the airline industry and beyond.

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通过综合文本挖掘和多标准决策分析评估航空公司服务质量

服务质量对于竞争激烈的航空业的长期可持续性至关重要。然而，由于样本量、效率和可靠性等方面的不足，该领域以往的研究经常受到限制。本研究针对这些不足，提出了精炼的见解，并建立了一个全面而又高度阐释性的排名框架。首先，我们采用潜在语义分析法（LSA）从 80 家航空公司的在线评论中提炼出主要的主题和情感。随后，我们使用 SentiWordNet 词库和 TextBlob 软件包对上述评论进行情感分析。随后，我们采用与理想解决方案相似度排序偏好综合技术（Technique for Order Preference by Similarity to Ideal Solution）和 Kriterijumska Optimizacija I Kompromisno Resenje-Adversarial Interpretive Structural Model（TOPSIS-VIKOR-AISM）方法，利用折中解决方案的计算构建了一个分层结构。最后，根据从在线评论中获得的感知对航空公司进行从最佳到最差的排名，提供了一种即时可视化解决方案。这项研究不仅有助于消费者做出明智的决定，还为航空公司提供了可用于提高服务质量的见解。这项研究为服务质量评估提供了新颖的见解，具有适用于航空业及其他行业的潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Air Transport Management TRANSPORTATION-

CiteScore

12.40

自引率

11.70%

发文量

期刊介绍： The Journal of Air Transport Management (JATM) sets out to address, through high quality research articles and authoritative commentary, the major economic, management and policy issues facing the air transport industry today. It offers practitioners and academics an international and dynamic forum for analysis and discussion of these issues, linking research and practice and stimulating interaction between the two. The refereed papers in the journal cover all the major sectors of the industry (airlines, airports, air traffic management) as well as related areas such as tourism management and logistics. Papers are blind reviewed, normally by two referees, chosen for their specialist knowledge. The journal provides independent, original and rigorous analysis in the areas of: • Policy, regulation and law • Strategy • Operations • Marketing • Economics and finance • Sustainability