An exploratory analysis of observed and latent variables affecting intercity train service quality in developing countries

Md Hadiuzzaman (), Nahid Parvez Farazi (), Sanjana Hossain () and D. M. Ghius Malik ()
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Md Hadiuzzaman: Bangladesh University of Engineering and Technology
Nahid Parvez Farazi: Bangladesh University of Engineering and Technology
Sanjana Hossain: Bangladesh University of Engineering and Technology
D. M. Ghius Malik: Bangladesh University of Engineering and Technology

Transportation, 2019, vol. 46, issue 4, No 16, 1447-1466

Abstract: Abstract Service quality (SQ) and customer satisfaction as perceived by 1037 passengers on intercity train services in Bangladesh were examined using structural equation modeling to explain the overall SQ of intercity train service. This study presents two structural equation models to reveal the influence of the observed variables on the SQ of intercity train service in the context of a developing country. Out of the two models, the best one is selected based on statistical parameters and resemblance with real life expectations. The framework of the models is based on eighteen observed variables; among them five were considered as endogenous and rest of the thirteen as exogenous variables. The number of latent variables used in the models is one, which is confirmed by the factor analysis. Out of the eighteen observed variables, ‘Overall security’, ‘Female harassment’, ‘Fitness of compartment’ and ‘Waiting place condition’ are found to be the variables which predominantly influence SQ. Moreover, the effect of heterogeneity among users on the performance of the best model is investigated. All the study findings match the real life scenario of a developing country. Acknowledging limited resources of a developing country, the present study provides a guideline to the railway operator for making the intercity train service more attractive for both prospective and existing users.

Keywords: Service quality; Intercity passenger train; Structural equation modeling; Latent attributes; Principal component analysis (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11116-017-9843-6

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