Evaluation of service quality in public bus transportation using interval-valued intuitionistic fuzzy QFD methodology. (December 2019)

• Record Type: Journal Article
• Authors: Deveci, Muhammet; Öner, Sultan Ceren; Canıtez, Fatih; Öner, Mahir
• Is Part Of: Research in transportation business & management. Volume 33(2019)
• Publication Date: 2019-12
• Subjects: Public bus transportation -- Customer satisfaction -- Interval-valued intuitionistic fuzzy sets -- Quality function deployment (QFD) -- Principal component analysis; Transportation -- Research -- Periodicals; Transportation -- Management -- Periodicals; Transportation -- Management; Transportation -- Research; Periodicals; 388.068
• DOI: 10.1016/j.rtbm.2019.100387
• Languages: English
• ISSNs: 2210-5395

Abstract

Abstract: This study aims to develop a quantitative assessment framework for public bus operators to translate the passenger demands into service quality specifications. The results of a customer satisfaction survey, carried out to identify the passenger demands, are used as an input to measure the level of service quality in a public transport operator. Firstly, the number of customer satisfaction criteria is reduced with Principal Component Analysis (PCA) and secondly the evaluation factors are identified with Quality Function Deployment (QFD). Both methods are integrated with an interval-valued intuitionistic fuzzy (IVIF) approach to reflect the uncertainty in the QFD evaluations of decision makers. By this way, our approach synthesizes customer and design requirements via interval-valued intuitionistic fuzzy QFD. The results show that the proposed method helps decision makers of public bus operators to focus on high priority areas so that they can effectively deploy their resources to address people's mobility needs. Graphical abstract: Unlabelled Image Highlights: Customer satisfaction problem in the public transportation. We aim to develop a quantitative methodology in public transport sector to prioritize the areas of improvement. The relations between customer requriment and design requirement via interval-valued intuitionistic fuzzy QFD.