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Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China

Research Article

Cluster Analysis on the High Quality Development of Foreign Trade in Guangdong-Hong Kong-Macao Greater Bay Area

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  • @INPROCEEDINGS{10.4108/eai.17-6-2022.2322609,
        author={Shuang  Zhang},
        title={Cluster Analysis on the High Quality Development of Foreign Trade in Guangdong-Hong Kong-Macao Greater Bay Area},
        proceedings={Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China},
        publisher={EAI},
        proceedings_a={ICIDC},
        year={2022},
        month={10},
        keywords={guangdong-hong kong-macao greater bay area; high-quality development of foreign trade; cluster analysis},
        doi={10.4108/eai.17-6-2022.2322609}
    }
    
  • Shuang Zhang
    Year: 2022
    Cluster Analysis on the High Quality Development of Foreign Trade in Guangdong-Hong Kong-Macao Greater Bay Area
    ICIDC
    EAI
    DOI: 10.4108/eai.17-6-2022.2322609
Shuang Zhang1,*
  • 1: Guangdong University of Technology School of Economics and Trade
*Contact email: Alyssazzz@163.com

Abstract

Based on the foreign trade development data of 11 regions in the Guangdong-Hong Kong-Macao Greater Bay Area in 2018, to establish a system of indicators for high-quality development of foreign trade. Combining the elbow rule and contour coefficient method, the foreign trade quality classification of 11 regions is obtained, and the k-means clustering algorithm is used to classify the high-quality development level of foreign trade in 11 regions. The differences in the high-quality development of foreign trade in 11 regions of the Guangdong-Hong Kong-Macao Greater Bay Area are studied, and the reasons for the differences are analyzed and appropriate suggestions are given.

Keywords
guangdong-hong kong-macao greater bay area; high-quality development of foreign trade; cluster analysis
Published
2022-10-13
Publisher
EAI
http://dx.doi.org/10.4108/eai.17-6-2022.2322609
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