{"title":"Revealing intrinsic communities in the international foreign direct investment networks through their backbones","authors":"Sheng Zhu , Tong-Yu Wang , Wen-Jie Xie , Wei-Xing Zhou","doi":"10.1016/j.chaos.2025.116766","DOIUrl":null,"url":null,"abstract":"<div><div>Foreign direct investment (FDI) affects the economic development of an economy. We explore the characteristics and evolutionary patterns of intrinsic communities in the international foreign direct investment networks (iFDINs) by analyzing their backbones. Using bilateral FDI data from 2009 to 2022, we construct the iFDINs, extract their backbones, and then apply the Louvain community detection algorithm to identify communities. The evolutionary process of these communities is then analyzed over time. With the recovery from the financial crisis in 2008, the iFDIN gradually expanded, leading to the formation of several long-term stable community structures in the backbone. After 2018, however, the network began to contract, influenced by international events such as the US tax reform, the US–China trade conflict, rising investment protectionism, and the COVID-19 pandemic. As a result, several community structures in the backbone underwent fragmentation and reorganization. By extracting the intrinsic community blocks of the network, we find that most economies in the same intrinsic community block are geographically clustered. Moreover, free trade zones and economic cooperation organizations can effectively facilitate the FDI relationships between member economies. Additionally, historical and cultural ties not only reduce the transaction costs of FDI, but also enable economies to maintain stable FDI relationships across geographical boundaries.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"199 ","pages":"Article 116766"},"PeriodicalIF":5.3000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chaos Solitons & Fractals","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0960077925007799","RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Foreign direct investment (FDI) affects the economic development of an economy. We explore the characteristics and evolutionary patterns of intrinsic communities in the international foreign direct investment networks (iFDINs) by analyzing their backbones. Using bilateral FDI data from 2009 to 2022, we construct the iFDINs, extract their backbones, and then apply the Louvain community detection algorithm to identify communities. The evolutionary process of these communities is then analyzed over time. With the recovery from the financial crisis in 2008, the iFDIN gradually expanded, leading to the formation of several long-term stable community structures in the backbone. After 2018, however, the network began to contract, influenced by international events such as the US tax reform, the US–China trade conflict, rising investment protectionism, and the COVID-19 pandemic. As a result, several community structures in the backbone underwent fragmentation and reorganization. By extracting the intrinsic community blocks of the network, we find that most economies in the same intrinsic community block are geographically clustered. Moreover, free trade zones and economic cooperation organizations can effectively facilitate the FDI relationships between member economies. Additionally, historical and cultural ties not only reduce the transaction costs of FDI, but also enable economies to maintain stable FDI relationships across geographical boundaries.
期刊介绍:
Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.