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ORIGINAL RESEARCH article

Front. Environ. Sci.
Sec. Environmental Economics and Management
Volume 12 - 2024 | doi: 10.3389/fenvs.2024.1393011
This article is part of the Research Topic Greenhouse Gas Emission (GHG) Reduction and Economic Structural Transformation View all 15 articles

A study on the spatial correlation network structure and its influencing factors of coupling coordination between FDI Flow network and Carbon Transfer network in the Belt and Road Initiative countries

Provisionally accepted
Yong Huang Yong Huang *Di You Di You *Haozhen Yu Haozhen Yu *Chengye Yang Chengye Yang *Jiawen Mao Jiawen Mao *
  • School of Business Administration and Tourism Management, Yunnan University, Kunming, Yunnan Province, China

The final, formatted version of the article will be published soon.

    Clarifying the spatial correlation characteristics and influencing factors of coupling coordination between Foreign Direct Investment (FDI) flow networks and carbon transfer networks in countries along the Belt and Road Initiative is of utmost importance for the formulation of regional carbon governance strategies and the establishment of a high-quality Green Silk Road. This study used a comprehensive approach combining social network analysis and coupling coordination model to measure the coupling coordination degree of FDI flow networks and carbon transfer networks of 67 Belt and Road countries from 2010 to 2016. In addition, a modified gravity model is used to characterize the spatial correlation network structure of coupling coordination between the two networks, and the QAP regression analysis method is applied to investigate the factors influencing the spatial association network. The results are as follows: (1) The spatial correlation network of coupling coordination between the two networks has good accessibility and relatively high overall network stability. (2) Countries such as Qatar and the United Arab Emirates occupy central positions in the network, while Bahrain and Jordan are positioned on the periphery of the network. (3) The spatial correlation network can be divided into three sectors: net outflow, net inflow, and bidirectional overflow sectors. (4) Spatial adjacency, bilateral investment treaties, economic development, and institutional quality have significant positive effects on the spatial association network, while the industrial structure and the level of infrastructure development have a significant negative impact. This study proposes an indicator system for the coupling coordination between FDI flow networks and carbon transfer networks. The aim is to investigate the coupling coordination relationship between FDI flow networks and carbon emission transfer networks in countries along the Belt and Road Initiative, providing important guidance for the formulation of regional cooperative carbon emission reduction strategies in other regions.

    Keywords: FDI flow network, carbon transfer network, social network analysis, coupling coordination model, Modified gravity model, spatial correlation

    Received: 28 Feb 2024; Accepted: 07 Jun 2024.

    Copyright: © 2024 Huang, You, Yu, Yang and Mao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Yong Huang, School of Business Administration and Tourism Management, Yunnan University, Kunming, Yunnan Province, China
    Di You, School of Business Administration and Tourism Management, Yunnan University, Kunming, Yunnan Province, China
    Haozhen Yu, School of Business Administration and Tourism Management, Yunnan University, Kunming, Yunnan Province, China
    Chengye Yang, School of Business Administration and Tourism Management, Yunnan University, Kunming, Yunnan Province, China
    Jiawen Mao, School of Business Administration and Tourism Management, Yunnan University, Kunming, Yunnan Province, China

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