Assessing Satisfaction with Public Transport Service by Ordered Multiple Correspondence Analysis

Rosaria Lombardo (), Ida Camminatiello () and Eric J. Beh ()
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Rosaria Lombardo: University of Campania
Ida Camminatiello: University of Campania
Eric J. Beh: University Drive

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2019, vol. 143, issue 1, No 16, 355-369

Abstract: Abstract This paper provides a composite indicator for comparing the perceived service of satisfaction of public transport by residents of a southern Italian city across three time periods spanning 2008–2012. Data were collected from 400 respondents that rated their agreement with 15 attribute-related statements regarding local public transport services. This study identifies passenger satisfaction in terms of the various quality aspects of public transport services using features of ordered multiple correspondence analysis. Such a method combines dimension reduction and cluster analysis for categorical data by objectively assigning individuals to clusters and identifying optimal scaling values to each of the categories. The main findings of our study indicate that there are differences in how public transport is perceived during the period of time studied.

Keywords: Customer satisfaction indicator; Public transport service; Correspondence analysis; Orthogonal polynomials; Classification (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11205-018-1972-6

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