A fuzzy segmentation analysis of airline passengers in the U.S. based on service satisfaction. (December 2020)

• Record Type: Journal Article
• Authors: Leon, Steven; Martín, Juan Carlos
• Is Part Of: Research in transportation business & management. Volume 37(2020)
• Publication Date: 2020-12
• Subjects: Airline passenger satisfaction -- Fuzzy logic -- Fuzzy segmentation -- Service quality -- TOPSIS; Transportation -- Research -- Periodicals; Transportation -- Management -- Periodicals; Transportation -- Management; Transportation -- Research; Periodicals; 388.068
• DOI: 10.1016/j.rtbm.2020.100550
• Languages: English
• ISSNs: 2210-5395

Abstract

Abstract: This study investigates airline passenger satisfaction and service quality in the U.S. market, employing fuzzy logic and fuzzy segmentation methods. Elasticities are then determined to evaluate the sensitivity of satisfaction based on service quality attributes. The survey was developed consistent with functional and technical quality and from existing airline service quality and satisfaction literature. Data were collected online using Amazon Mechanical Turk, resulting in 624 respondents. The results show that both technical and functional quality play a role in determining satisfaction with airlines, though passengers are more satisfied with functional quality than technical quality. Overall, a majority of airline passengers are indifferent; they are neither satisfied nor unsatisfied toward airline service quality. Additionally, this research introduced additional factors in the analysis that have not been previously researched laying the groundwork for future research.