Structural equation modeling of user satisfaction of bus transit service quality based on stated preferences and latent variables

Md Hadiuzzman · Tanmay Das · Md. Mehedi Hasnat · Sanjana Hossain · Sarder Rafee Musabbir

49 citations0/0 files storedTransportation Planning and Technology

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Transportation Planning and Optimization Customer Service Quality and Loyalty Economic and Environmental Valuation

Abstract

Few studies have been conducted on the service quality (SQ) of bus transit in developing countries. This paper presents a structural equation modeling (SEM) approach to identifying the relationships among major attributes that affect the SQ of bus transit in the city of Dhaka in Bangladesh. Specifically, 22 bus transit SQ attributes, drawn from 655 questionnaires, are used to develop different SEM models for the city. Along with stated preferences, the effect of three latent variables on SQ is analyzed. Among the developed models, the best model is selected by using different statistical approaches. With the best model, selected attributes are rated according to their relative importance on SQ. Acknowledging limited resources of a developing nation, this study gives a clear way ahead to planners, operating companies and transport managers to design appropriate transport policies which will ensure more effective services to current bus users as well as attracting new passengers.

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References

1981Evaluating Structural Equation Models with Unobservable Variables and Measurement Error 1999Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives 2012Principles and Practice of Structural Equation Modeling 1992Alternative Ways of Assessing Model Fit 1985A Conceptual Model of Service Quality and Its Implications for Future Research 1991Structural Equations with Latent Variables.2000A Review and Synthesis of the Measurement Invariance Literature: Suggestions, Practices, and Recommendations for Organizational Research 1990Structural Model Evaluation and Modification: An Interval Estimation Approach

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