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Finding Service Quality Improvement Opportunities Across Different Typologies of Public Transit Customers

Publication Date: 2018

Existing approaches dealing with customer perception data have two fundamental challenges: heterogeneity of customer perceptions and simultaneous interrelationships between attitudes that explain customer behavior. This paper aims to provide practitioners with a methodology of service quality (SQ) evaluation based on public transit customers behavioral theory and advanced market segmentation that deals with these two fundamental challenges. The original contributions of this paper are: the definition of customer typologies based on advanced customer segmentation with latent class clustering; analysis of the effect of SQ perceptions on behavioral intentions within the behavioral theory framework that considers multiple attitudes simultaneously affecting customers’ intentions; identification of transit service improvement opportunities for specific customer typologies as well as common to most customers. Our research shows practitioners and researchers that specific needs and perceptions of customers can be identified by using advanced segmentation. We applied our method to a light-rail transit service in Seville, Spain. We measured the direct effects on behavioral intentions of the LRT SQ, customer satisfaction and, in the case of some customers, the available transportation alternatives. Other observed that attitudes of customers were indirectly related to behavioral intentions as well. We found customer agreement around these LRT SQ aspects of tangible service equipment, accessibility, information, individual space and environmental pollution. Customers clearly showed different opinions related to safety, customer service and availability.

Authors: José Luis Machado León, Rocio de Ona, Francisco Diez-Mesa, Juan De Ona
Recommended Citation:
Machado, J. L., de Oña, R., Diez-Mesa, F., & de Oña, J. (2018). Finding service quality improvement opportunities across different typologies of public transit customers. Transportmetrica A: Transport Science, 14(9), 761-783.