DOI: 10.57760/sciencedb.34741
title: A Dataset for Constructing a Risk Interaction Knowledge Graph of Chinese Enterprises Participation in "The Belt and Road " Connectivity Initiatives
title: 中国企业参与“一带一路” 互联互通风险交互知识图谱构建数据集

description: "The Belt and Road"connectivity Initiatives is the core path for serving common development and the construction of a community with a shared future for mankind. However,Chinese enterprises face numerous internal and external risks and challenges when participating in large-scale infrastructure projects under"The Belt and Road"connectivity Initiatives.Many projects have been interrupted or cancelled,which has a negative impact on the advancement of"The Belt and Road"connectivity Initiatives.Existing research has insufficiently explored and systematically described the causes of risks in large-scale infrastructure projects under"The Belt and Road"connectivity Initiatives,which limits the in-depth analysis and utilization of data resources based on actual cases.Constructing a risk interaction knowledge graph dataset for Chinese enterprises' participation in"The Belt and Road"connectivity Initiatives is a key support for breaking the data barriers in enterprise risk research and is of great significance for deepening the governance of international engineering risks and optimizing project decisions.This study adopts a case analysis research paradigm and combines web crawlers and triangulation methods for data mining.It systematically collects data on 1,311 large-scale infrastructure cooperation projects along"The Belt and Road"connectivity Initiative that were participated in by Chinese enterprises and experienced interruptions or cancellations from 2000 to 2023 from authoritative websites such as government official websites and the World Bank PPI database.Based on case analysis, it identifies and sorts out the main risk events and influencing factors of the projects, forming a knowledge graph dataset containing six entity types and eight entity relationships.This dataset adopts a structured storage and visualization adaptation design,providing assistance for the analysis of the risk interaction mechanism and the construction of knowledge graphs for large-scale infrastructure projects under"The Belt and Road"connectivity Initiative, and providing high-quality data support for systematic and in-depth research on enterprise risks.This dataset consists of two parts: the first part is an Excel data table, covering 17 fields and 1,311 project data; the second part is a knowledge graph dataset, including 6 entity files and 10 entity relationship files.
description: "The Belt and Road"connectivity Initiatives is the core path for serving common development and the construction of a community with a shared future for mankind. However,Chinese enterprises face numerous internal and external risks and challenges when participating in large-scale infrastructure projects under"The Belt and Road"connectivity Initiatives.Many projects have been interrupted or cancelled,which has a negative impact on the advancement of"The Belt and Road"connectivity Initiatives.Existing research has insufficiently explored and systematically described the causes of risks in large-scale infrastructure projects under"The Belt and Road"connectivity Initiatives,which limits the in-depth analysis and utilization of data resources based on actual cases.Constructing a risk interaction knowledge graph dataset for Chinese enterprises' participation in"The Belt and Road"connectivity Initiatives is a key support for breaking the data barriers in enterprise risk research and is of great significance for deepening the governance of international engineering risks and optimizing project decisions.This study adopts a case analysis research paradigm and combines web crawlers and triangulation methods for data mining.It systematically collects data on 1,311 large-scale infrastructure cooperation projects along"The Belt and Road"connectivity Initiative that were participated in by Chinese enterprises and experienced interruptions or cancellations from 2000 to 2023 from authoritative websites such as government official websites and the World Bank PPI database.Based on case analysis, it identifies and sorts out the main risk events and influencing factors of the projects, forming a knowledge graph dataset containing six entity types and eight entity relationships.This dataset adopts a structured storage and visualization adaptation design,providing assistance for the analysis of the risk interaction mechanism and the construction of knowledge graphs for large-scale infrastructure projects under"The Belt and Road"connectivity Initiative, and providing high-quality data support for systematic and in-depth research on enterprise risks.This dataset consists of two parts: the first part is an Excel data table, covering 17 fields and 1,311 project data; the second part is a knowledge graph dataset, including 6 entity files and 10 entity relationship files.