Highlights We propose a fuzzy integral-based model to evaluate and improve the service quality of transport systems. The model addresses the dependent relationships among various criteria for a non-additive weighted gap analysis. It remedies the inconsistent problem of assuming that the criteria are interdependent but entails the use of additive models. Data from Taipei city bus companies are used to demonstrate this method.

    Abstract How to improve transportation service quality and thus attract more passengers to use public transportation systems is an important concern for city governments around the world. In this study, we propose a novel information fusion model that addresses the dependent relationships among the various criteria for a method of non-additive weighted gap analysis aimed at evaluating and improving the service quality of transport systems. The hybrid model remedies prior shortcomings and should be more applicable to real-world situations. The proposed model is applied to a real case study of Taipei city bus companies to demonstrate its usefulness. The resulting analysis and the managerial applications for improving the bus service quality are also discussed with regards to the current policies of Taipei city.


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    Title :

    Improving transportation service quality based on information fusion


    Contributors:


    Publication date :

    2014-07-16


    Size :

    15 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English