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Article

DESIGNING THE APPROPRIATE DATA COLLECTION METHOD FOR PUBLIC TRANSPORT PASSENGER SATISFACTION ANALYSIS

DOI: 10.7708/ijtte.2018.8(2).03


8 / 2 / 177-183 Pages

Author(s)

Blawal Hussain - Budapest University of Technology and Economics, Department of Transport Technology and Economics, Hungary -

Mohammad Maghrour Zefreh - Budapest University of Technology and Economics, Department of Transport Technology and Economics, Hungary -

Adam Torok - Budapest University of Technology and Economics, Department of Transport Technology and Economics, Hungary -


Abstract

Incessantly increasing urbanization is a threat to mobility, environment and ultimately to the quality of life. Promoting public transport in the major cities seems to be a promising solution to this issue which can be achieved by moving toward attracting more satisfied public transport passengers (PTP). The first step in PTP satisfaction analysis is collecting the reliable data which is equally suitable for all passenger groups (i.e. handicapped, visually impaired, etc.) in order to limelight the most important concerns of the public transport users. We assume that a satisfied customer would be willing to purchase the product again and will stay loyal to the provider as long as the gap between his perceived quality and expected quality is less. Among various methods of data collection, Customer satisfaction survey (CSS) suits best to know about the extent of users’ satisfaction. In the current paper, at first, the relevant data collection methods have been reviewed and then a passenger satisfaction questionnaire has been designed which rates the extent of Budapest PTP satisfaction and dissatisfaction on a Likert chart. It should be underlined that different set of individual characteristics (age, gender, level of education, overall passenger health condition, etc.), as well as different service attributes (price, frequency, ease of boarding and alighting, etc.), are considered in the aforementioned questionnaire for further cluster analysis of the collected data.


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Acknowledgements:

This work is supported by the ÚNKP-17-III New National Excellence Program of the Ministry of Human Capacities of Hungary.


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