Identifying and prioritizing factors affecting in-cabin passenger comfort on high-speed rail in China: A fuzzy-based linguistic approach
Type of publication: International Journal
Year of publication: 2020
Authors: Zhen-Song Chen
Director: Xiao-Lu Liu, Rosa María Rodríguez, Xian-Jia Wang, Kwai-Sang Chin, Kwok-Leung Tsui, Luis Martínez
Type: Applied Soft Computing
Volumen: 95
Number: 106558
ISSN number: 1568-4946
Abstract: "Factors affecting customer comfort are crucial for the success of many services such as public transportation, health facilities, and so on. Therefore, the identification and prioritization of such factors is an important demand from stakeholders. This research aims to identify and prioritize the factors that affect in-cabin passenger comfort on high-speed rail (HSR) based on empirical evidence collected from China. For the identification process, the quality-management tool known as quality function deployment (QFD) to capture the voice of the customer is used to discover the most important demands as the driving influencing factors of in-cabin passenger comfort, by utilizing passengers’ feedback regarding their experiences with HSR posted in social media. Such factors will be prioritized by a fuzzy linguistic group decision-making approach based on the adoption of generalized comparative linguistic expressions obtained from a questionnaire investigation on randomly selected HSR passengers, and accomplishing a decision-solving procedure that includes consistency-checking and consensus-reaching processes to achieve an effective, reliable, and agreed prioritization of the factors. The research outputs will suggest the factors of greatest concern among all HSR passenger demands. This study gives HSR operators and designers not only insights and tools for managing HSR passenger demands but also advice for refining the design and service quality of HSR in China."