With the rapid development of global economy and changes of the domestic and foreign political environment, the development of China's shipping, logistics, and ports is facing various opportunities and challenges as well. However, the current development model of ports is encountering resistances because of the slowdown in imbalance of industrial layout, intensification in port competition, and increase in costs of environmental protection. Therefore, it has become a key issue for ports to deal with the problems such as how to promote port service innovation, overcome the adverse effects of internal and external factors, and achieve informatization, automation, and intelligent development, in order to gain a dominant position in the international competition. This study aims to develop a novel model for the evaluation and selection of development strategies of smart ports by combining the SWOT analysis and the AHP model. The proposed model is able to analyze factors influencing the development of smart ports in both qualitative and quantitative ways. Taking the coastal Port Z of China as an example, a case study has been conducted to demonstrate the feasibility and rationality of the proposed method. The research results reveal that Port Z suffers from the problems including information islands and overexpansion of unstructured data, restricting the improvement of informatization benefits during its development as a smart port. In order to improve its international competitiveness, Port Z is suggested to pay more attention to improving the operating efficiency of the local port company, building a logistics information management platform that connects with customs, railways and highways, and promoting port technology innovation and upgrade. The model proposed in this research can provide theoretical support for formulating and selecting reasonable and practical competitive strategies for the development of smart ports.


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    Title :

    A SWOT-AHP method for the selection of strategies of smart port development


    Contributors:
    Jiang, Xinchen (author) / Chen, Qi (author) / Zhang, Jin (author) / Chen, Chen (author)


    Publication date :

    2021-10-22


    Size :

    3401971 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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