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Structural equation model of customer satisfaction for the New York City subway system Stuart, Kenneth R ; Mednick, Marc ; Bockman, Johanna

By: Stuart, Kenneth RContributor(s): Mednick, Marc | Bockman, JohannaPublication details: Transportation Research Record, 2000Description: nr 1735, s. 133-7Subject(s): USA | Underground railway | Public transport | Mathematical model | Passenger | | Level of service | J04Bibl.nr: VTI P8167:1735Location: Abstract: A more complex model in content and design than previously applied to the measurement of customer satisfaction within the transportation industry is used in this study. Drawing from the results of previous studies that had a narrower focus, a network of 10 potentially important factors that affect customer satisfaction within the New York City subway system was postulated and tested using data collected from a cross section of adult residents. Results indicate that several factors have a direct influence on satisfaction, whereas others have an effect through intermediary variables. Path coefficients for the posited model are statistically significant, although several factors have notably more impact than others. Using model diagnostics, minor revisions and improvements to the initial model have been made while adhering closely to the principles of the original theory. Future developments are discussed, as is the model's application for planning and resource allocation.
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A more complex model in content and design than previously applied to the measurement of customer satisfaction within the transportation industry is used in this study. Drawing from the results of previous studies that had a narrower focus, a network of 10 potentially important factors that affect customer satisfaction within the New York City subway system was postulated and tested using data collected from a cross section of adult residents. Results indicate that several factors have a direct influence on satisfaction, whereas others have an effect through intermediary variables. Path coefficients for the posited model are statistically significant, although several factors have notably more impact than others. Using model diagnostics, minor revisions and improvements to the initial model have been made while adhering closely to the principles of the original theory. Future developments are discussed, as is the model's application for planning and resource allocation.

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