Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/76057
Title: A fuzzy segmentation analysis of airline passengers in the U.S. based on service satisfaction.
Authors: Leon, Steven
Martín Hernández, Juan Carlos 
UNESCO Clasification: 531212 Transportes y comunicaciones
Keywords: Airline passenger satisfaction
Fuzzy logic
Fuzzy segmentation
Service quality
Topsis
Issue Date: 2020
Journal: Research in Transportation Business and Management 
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.
URI: http://hdl.handle.net/10553/76057
ISSN: 2210-5395
DOI: 10.1016/j.rtbm.2020.100550
Source: Research in Transportation Business and Management[ISSN 2210-5395], (Enero 2020)
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