Shu Tianheng, Yang Shuo, Yu Taofang, Cheng Guangyu, Ren Yitian, Shi Fangchen, Derudder Ben, Liao Xia
School of Architecture, Tsinghua University, Beijing, 100084, China.
Department of Real Estate and Construction, Faculty of Architecture, The University of Hong Kong, Hong Kong, 999077, China.
Sci Data. 2025 Mar 3;12(1):369. doi: 10.1038/s41597-025-04658-w.
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.
企业间的城际投资活动反映了城市间的资本流动,从而直接说明了它们之间的经济联系。然而,目前尚无公开可用的数据集能捕捉到这一重要特征。在本研究中,我们基于17273411条大规模企业注册记录,引入了一个涵盖2000年至2020年期间的中国城际投资网络(IIN)数据集。该数据集将367个城市表示为节点,城市间的投资频率作为边权重来构建有向和无向网络。它捕捉了中国IIN的时空模式,突出了经济连通性随时间和空间的动态变化。该数据集与由中国人口流动形成的城市网络以及经济引力模型紧密契合,与官方记录和现有研究结果一致,并满足距离衰减效应,从而验证了其科学可靠性。这个数据集为探索城市间的经济互动和功能组织以及推进中国城市网络研究提供了独特的机会。