TY - JOUR
T1 - An intercity investment network dataset of China based on the enterprise registration records (2000-2020)
AU - Shu, Tianheng
AU - Yang, Shuo
AU - Cheng, Guangyu
AU - Yu, Fangtao
AU - Ren, Yitian
AU - Shi, Fangchen
AU - Derudder, Ben
AU - Liao, Xia
PY - 2025
Y1 - 2025
N2 - Intercity investment activities among enterprises reflect the flow of capital between cities, thereby directly illustrating the economic connections between them. However, there is currently no publicly available dataset that captures this important feature. In this study, we introduce an intercity investment network (IIN) dataset for China, covering the period from 2000 to 2020, based on 17,273,411 large-scale enterprise registration records. The dataset represents 367 cities as nodes, with investment frequency between cities serving as edge weights to construct both directed and undirected networks. It captures the spatiotemporal patterns of China’s IIN, highlighting dynamic changes in economic connectivity over time and space. The dataset aligns closely with urban networks formed by China’s population mobility and the economic gravity model, is consistent with official records and existing research findings, and satisfies the distance decay effect, thus validating its scientific reliability. This dataset provides unique opportunities for exploring economic interactions and functional organization between cities, and advancing urban network research in China.
AB - Intercity investment activities among enterprises reflect the flow of capital between cities, thereby directly illustrating the economic connections between them. However, there is currently no publicly available dataset that captures this important feature. In this study, we introduce an intercity investment network (IIN) dataset for China, covering the period from 2000 to 2020, based on 17,273,411 large-scale enterprise registration records. The dataset represents 367 cities as nodes, with investment frequency between cities serving as edge weights to construct both directed and undirected networks. It captures the spatiotemporal patterns of China’s IIN, highlighting dynamic changes in economic connectivity over time and space. The dataset aligns closely with urban networks formed by China’s population mobility and the economic gravity model, is consistent with official records and existing research findings, and satisfies the distance decay effect, thus validating its scientific reliability. This dataset provides unique opportunities for exploring economic interactions and functional organization between cities, and advancing urban network research in China.
UR - https://doi.org/10.1038/s41597-025-04658-w
UR - https://mp.weixin.qq.com/s/-ItfZ9ZpJJfpHQpo6GcHLA
M3 - Article
SN - 2052-4463
JO - Scientific Data
JF - Scientific Data
ER -