Highlights Affective-Events-Theory explains customer reactions to transit service disruptions. Reaction types are defined by Hirchman’s exit-voice-loyalty framework. A web-based survey elicits transit users’ affective and behavior reactions. Customer frustration decreases with higher service quality and operator efficacy. Complaints behavior reduces transit avoidance by ‘airing out’ frustration.

    Abstract Transit systems are complex open systems susceptible to service disruptions due to a variety of operational and infrastructure failures. Demand-side transit user reactions form an important part of system resilience. This study proposes Affective Events Theory (AET) to understand transit users’ frustration and behavioral reaction to service disruptions. The behavioral reactions are structured in accordance with Hirschman’s Exit-Voice-Loyalty framework. While service disruptions can cause passenger frustration, the behavioral response varies from complaints (voiced) to avoiding transit use on the next trip (exit), and continue as usual (loyalty). The collected data is a representative sample of 1629 transit users from Innsbruck (Austria). Exploratory factor analysis followed by an estimation of a structural equation model served to validate the model framework. Better network coverage, service quality, and personnel behavior mitigate the frustration of transit users upon event occurence. Higher transit user frustration is related to a higher frequency of service disruptions. Higher frustration is related to more complaints (voiced). However, the tendency to complain is associated with lower, reduced transit use on the next trip (exit), meaning that voice and exit substitute each other.


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    Titel :

    Applying affective event theory to explain transit users’ reactions to service disruptions


    Beteiligte:


    Erscheinungsdatum :

    2019-09-30


    Format / Umfang :

    13 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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