An integrated data mining and multi-criteria decision models for assessing service quality in the airline industry
學年 115
學期 1
出版（發表）日期 2026-08-01
作品名稱 An integrated data mining and multi-criteria decision models for assessing service quality in the airline industry
作品名稱（其他語言）
著者 James J.H. Liou; Han-Lung Liu; Ying-Hung Lin; Chao-Che Hsu; Yen-Ching Chuang
單位
出版者
著錄名稱、卷期、頁數 Journal of Air Transport Management 135, p.103018
摘要 Traditional airline service quality research often faces limitations due to restricted survey sample sizes, hindering comprehensive passenger sentiment capture. This study seeks to overcome such constraints by leveraging big data and artificial intelligence (AI) methodologies. A novel, scientifically rigorous evaluation framework is proposed and applied for analysis of extensive unsolicited textual passenger feedback from diverse channels. Using advanced text mining and Natural Language Processing (NLP) techniques, including aspect-based sentiment analysis, textual comments are systematically transformed into quantifiable indicators reflecting key service dimensions. A robust Multi Criteria Decision Making (MCDM) model is integrated to objectively assess actual passenger perceptions and levels of satisfaction. The goals are to identify the service factors most critical to passenger satisfaction or dissatisfaction, uncover the fundamental drivers behind these sentiments, and generate actionable data-driven service improvement recommendations. Grounded in real-world passenger feedback, this framework provides a more accurate, objective, and scalable assessment method, empowers airlines to strategically enhance service quality, boost passenger satisfaction, and strengthen market competitiveness. The method is validated through correlation with operational metrics and expert evaluation.
關鍵字 Airline; Service quality; Neutrosophic set; Data mining; MCDM
語言 en_US
ISSN
期刊性質 國外
收錄於 SCI SSCI ABS*
產學合作
通訊作者
審稿制度 否
國別 NLD
公開徵稿
出版型式 ,電子版,紙本
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/129960 )