[EN] Market segmentation can help transit operators to identify groups of passengers that share particular characteristics and specific needs and requirements about the service. Traditionally, socioeconomic variables have been used to perform a simple segmentation, although satisfaction rates about service attributes were not similar among individuals belonging to a group. Cluster analysis emerges as a novel analytical technique for extracting passengersâ profiles. This paper investigates passengersâ profiles at the metropolitan Light Rail Transit service of Seville (Spain). Latent Class Clustering algorithm is applied and satisfaction rates about different service quality attributes are considered for the segmentation. Particularly, two different cluster analyses are accomplished: first level, with only socioeconomic attributes; and second level, with eight service quality factors and socioeconomic attributes. The service quality factors are obtained through a principal component analysis, at which, the large number of attributes describing the service is reduced into constructs underlying them. Equivalent satisfaction rates are calculated for these service factors. Then, homogeneous groups of passengers are obtained. Additionally, the main differences among cluster are identified. Diez De Los Rios Mesa, F.; De Oña López, R.; De Oña López, J. (2016). The effect of service attributesâ hierarchy on passengersâ segmentation. A light rail transit service case study. En XII Congreso de ingenierÃa del transporte. 7, 8 y 9 de Junio, Valencia (España). Editorial Universitat Politècnica de València. 2124-2131. https://doi.org/10.4995/CIT2016.2015.3844 OCS 2124 2131
The different versions of the original document can be found in:
DOIS: 10.1016/j.trpro.2016.12.032 10.4995/cit2016.2015.3844
Published on 01/01/2016
Volume 2016, 2016
DOI: 10.1016/j.trpro.2016.12.032
Licence: Other
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