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Spatial-temporal Evolution and Determinants of the Belt and Road Ini-tiative: A Maximum Entropy Gravity Model Approach

HUANG Qinshi ZHU Xigang LIU Chunhui WU Wei LIU Fengbao ZHANG Xinyi

HUANG Qinshi, ZHU Xigang, LIU Chunhui, WU Wei, LIU Fengbao, ZHANG Xinyi. Spatial-temporal Evolution and Determinants of the Belt and Road Ini-tiative: A Maximum Entropy Gravity Model Approach[J]. 中国地理科学, 2020, 30(5): 839-854. doi: 10.1007/s11769-020-1144-x
引用本文: HUANG Qinshi, ZHU Xigang, LIU Chunhui, WU Wei, LIU Fengbao, ZHANG Xinyi. Spatial-temporal Evolution and Determinants of the Belt and Road Ini-tiative: A Maximum Entropy Gravity Model Approach[J]. 中国地理科学, 2020, 30(5): 839-854. doi: 10.1007/s11769-020-1144-x
HUANG Qinshi, ZHU Xigang, LIU Chunhui, WU Wei, LIU Fengbao, ZHANG Xinyi. Spatial-temporal Evolution and Determinants of the Belt and Road Ini-tiative: A Maximum Entropy Gravity Model Approach[J]. Chinese Geographical Science, 2020, 30(5): 839-854. doi: 10.1007/s11769-020-1144-x
Citation: HUANG Qinshi, ZHU Xigang, LIU Chunhui, WU Wei, LIU Fengbao, ZHANG Xinyi. Spatial-temporal Evolution and Determinants of the Belt and Road Ini-tiative: A Maximum Entropy Gravity Model Approach[J]. Chinese Geographical Science, 2020, 30(5): 839-854. doi: 10.1007/s11769-020-1144-x

Spatial-temporal Evolution and Determinants of the Belt and Road Ini-tiative: A Maximum Entropy Gravity Model Approach

doi: 10.1007/s11769-020-1144-x
基金项目: 

Under the auspices of A Category of Strategic Priority Research Program of Chinese Academy of Sciences (No. XDA20010101)

详细信息
    通讯作者:

    ZHU Xigang.E-mail:zhuxigang522@hotmail.com

Spatial-temporal Evolution and Determinants of the Belt and Road Ini-tiative: A Maximum Entropy Gravity Model Approach

Funds: 

Under the auspices of A Category of Strategic Priority Research Program of Chinese Academy of Sciences (No. XDA20010101)

  • 摘要: The spatial interaction model is an effective way to explore the geographical disparities inherent in the Belt and Road Initiative (BRI) by simulating spatial flows. The traditional gravity model implies the hypothesis of equilibrium points without any reference to when or how to achieve it. In this paper, a dynamic gravity model was established based on the Maximum Entropy (MaxEnt) theory to estimate and monitor the interconnection intensity and dynamic characters of bilateral relations. In order to detect the determinants of interconnection intensity, a Geodetector method was applied to identify and evaluate the determinants of spatial networks in five dimensions. The empirical study clearly demonstrates a heterogeneous and non-circular spatial structure. The main driving forces of spatial-temporal evolution are foreign direct investment, tourism and railway infrastructure construction, while determinants in different sub-regions show obvious spatial differentiation. Southeast Asian countries are typically multi-island area where aviation infrastructure plays a more important role. North and Central Asian countries regard oil as a pillar industry where power and port facilities have a greater impact on the interconnection. While Western Asian countries are mostly influenced by the railway infrastructure, Eastern European countries already have relatively robust infrastructure where tariff policies provide a greater impetus.
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Spatial-temporal Evolution and Determinants of the Belt and Road Ini-tiative: A Maximum Entropy Gravity Model Approach

doi: 10.1007/s11769-020-1144-x
    基金项目:

    Under the auspices of A Category of Strategic Priority Research Program of Chinese Academy of Sciences (No. XDA20010101)

    通讯作者: ZHU Xigang.E-mail:zhuxigang522@hotmail.com

摘要: The spatial interaction model is an effective way to explore the geographical disparities inherent in the Belt and Road Initiative (BRI) by simulating spatial flows. The traditional gravity model implies the hypothesis of equilibrium points without any reference to when or how to achieve it. In this paper, a dynamic gravity model was established based on the Maximum Entropy (MaxEnt) theory to estimate and monitor the interconnection intensity and dynamic characters of bilateral relations. In order to detect the determinants of interconnection intensity, a Geodetector method was applied to identify and evaluate the determinants of spatial networks in five dimensions. The empirical study clearly demonstrates a heterogeneous and non-circular spatial structure. The main driving forces of spatial-temporal evolution are foreign direct investment, tourism and railway infrastructure construction, while determinants in different sub-regions show obvious spatial differentiation. Southeast Asian countries are typically multi-island area where aviation infrastructure plays a more important role. North and Central Asian countries regard oil as a pillar industry where power and port facilities have a greater impact on the interconnection. While Western Asian countries are mostly influenced by the railway infrastructure, Eastern European countries already have relatively robust infrastructure where tariff policies provide a greater impetus.

English Abstract

HUANG Qinshi, ZHU Xigang, LIU Chunhui, WU Wei, LIU Fengbao, ZHANG Xinyi. Spatial-temporal Evolution and Determinants of the Belt and Road Ini-tiative: A Maximum Entropy Gravity Model Approach[J]. 中国地理科学, 2020, 30(5): 839-854. doi: 10.1007/s11769-020-1144-x
引用本文: HUANG Qinshi, ZHU Xigang, LIU Chunhui, WU Wei, LIU Fengbao, ZHANG Xinyi. Spatial-temporal Evolution and Determinants of the Belt and Road Ini-tiative: A Maximum Entropy Gravity Model Approach[J]. 中国地理科学, 2020, 30(5): 839-854. doi: 10.1007/s11769-020-1144-x
HUANG Qinshi, ZHU Xigang, LIU Chunhui, WU Wei, LIU Fengbao, ZHANG Xinyi. Spatial-temporal Evolution and Determinants of the Belt and Road Ini-tiative: A Maximum Entropy Gravity Model Approach[J]. Chinese Geographical Science, 2020, 30(5): 839-854. doi: 10.1007/s11769-020-1144-x
Citation: HUANG Qinshi, ZHU Xigang, LIU Chunhui, WU Wei, LIU Fengbao, ZHANG Xinyi. Spatial-temporal Evolution and Determinants of the Belt and Road Ini-tiative: A Maximum Entropy Gravity Model Approach[J]. Chinese Geographical Science, 2020, 30(5): 839-854. doi: 10.1007/s11769-020-1144-x
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