Comparing Transport Quality Perception among Different Travellers in European Cities through Co-Cluster Analysis

Miriam Pirra and Ruggero G. Pensa
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Miriam Pirra: DIATI, Politecnico di Torino, C.so Duca degli Abruzzi 24, 10129 Torino, Italy
Ruggero G. Pensa: Department of Computer Science, University of Torino, C.so Svizzera 185, 10149 Torino, Italy

Sustainability, 2019, vol. 11, issue 24, 1-17

Abstract: The quality of the transport system offered at city level constitutes an important and challenging goal for society, for local authorities, and transport operators. Therefore, appropriate evaluation of travellers’ satisfaction is required to support service performance monitoring, benchmarking, and market analysis. This aspect implies the collection of satisfaction levels for different passengers’ groups, as it could provide interesting suggestions for identifying priority areas of action. To this end, an original study aimed at understanding the main aspects affecting the common view of satisfaction among different kinds of travellers at European level is presented in this paper. A specific survey investigating how travellers perceive the quality of their journey is proposed to people living in cities characterised by different sizes. Data are then analysed through a multi-view co-clustering algorithm, an innovative machine learning technique that highlights clusters of respondents grouped according to various categories of features. Such results could be used by local authorities and transport providers to understand the specific actions to be operated to improve the quality of transport service offered in a market segmentation dimension.

Keywords: users’ perception; machine learning; transport quality; urban mobility; passenger satisfaction; clustering (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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