Port choice is an important issue to be investigated to ensure the effective integration of container supply chains and the sustainable development of regional economy. The selection of appropriate ports to facilitate shipping activities and international trade is crucial for many stakeholders, including shipping lines, port administrators, cargo shippers and national governments. The task is essentially a process of multiple criterion decision-making (MCDM) under uncertainty, requiring analysts to derive rational decisions from uncertain and incomplete data related to different quantitative and qualitative determinants. This paper aims at proposing a new conceptual port choice method by explaining the role fuzzy logic in evidential reasoning in a complementary way, in which various forms of raw data (either objective or subjective) collected to evaluate port performance can first be converted into and presented as fuzzy grades defined using linguistics terms with degrees of belief (DoBs) and second be combined using evidential reasoning to produce a port choice preference score. The method is applied to analyse the selection of major Northeast Asian (NEA) container ports from a shipping line’s perspective. The outcome, a port choice preference score, is calculated using evidential reasoning to directly synthesize the true estimation of the port with respect to each criterion and therefore, unlike a relative ranking index, keeps the ‘goodness’ of port evaluation, capable of benchmarking a specific port’s performance and monitoring the increase of its competitiveness in a longitude study with respect to an individual criterion or all the criteria as a whole.


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    Titel :

    Modelling port choice in an uncertain environment


    Beteiligte:
    Yeo, Gi-Tae (Autor:in) / Ng, Adolf K.Y. (Autor:in) / Lee, Paul Tae-Woo (Autor:in) / Yang, Zaili (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    16.04.2014


    Format / Umfang :

    17 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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