Modelling service-specific and global transit satisfaction under travel and user heterogeneity

Jaime Allen, Juan Carlos Muñoz and Juan de Dios Ortúzar

Transportation Research Part A: Policy and Practice, 2018, vol. 113, issue C, 509-528

Abstract: Service provider administrators need to identify which perceived service quality (PSQ) elements are more relevant for users. By doing this, specific tactical and operational policies can be implemented to retain and attract new customers. In the public transport (PT) arena, few PSQ studies account for both service encounter and global satisfaction. Further, although some studies consider customer heterogeneity, we believe it has not been adequately captured. Regarding the problem of modelling PSQ from a PT service provider, we present a case study from Santiago, Chile. We analyse the PSQ derived from an extensive (n = 25,094) urban bus system satisfaction survey using structural equation models (SEM). Explicitly, we incorporate heterogeneity for both travel characteristics and sociodemographic attributes utilising a Multiple Indicator Multiple Cause (MIMIC) approach. We model two simultaneous regression equations regarding satisfaction with the bus-line (service encounter) being used and with the system (global), correcting for heterogeneity in all the satisfaction constructs via the SEM-MIMIC approach. Our main result is that the most critical variable for service encounter satisfaction is frequency/waiting time. For global satisfaction, the most significant attribute is tangibles/image, which includes satisfaction with the allied Metro service, with other users’ behaviour, and with information availability. As the perceived waiting time affects all satisfaction constructs negatively, we consider it a critical policy variable to tackle. Our model can serve as a planning tool for any PT administrator. The framework applies to any service setting with independent service-specific and global satisfaction attributes.

Keywords: Public transport; Structural equation modelling; MIMIC model; Consumer satisfaction surveys; Perceived service quality; Heterogeneity (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (39)

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DOI: 10.1016/j.tra.2018.05.009

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