Analysis of spatial-temporal evolution and investment model of industrial cross-regional investment network-taking the Pearl River Delta urban agglomeration as an example
Cross-regional investment behavior plays a pivotal role in enterprise development and regional economic growth. Nonetheless, existing investment network analyses often adopt a broad perspective, most studies tend to invest in network models and focus on a particular industry, and pay less attention to investment models in different industries. Therefore, this paper will combine the dual perspectives of space and network to observe the spatial and temporal evolution characteristics of enterprise investment and its investment model. Additionally, it delves into the unique features of investment networks within various industries at the district and county levels. The results show that enterprise investment agglomeration exhibits a development pattern characterized by points, bands, and surfaces, with a notable distance attenuation trend in investment distances. The overall structure of the industry investment network showcases characteristics of being multi-centered and multi-nodal. The investment models across different industries can be categorized into four distinct types. The research conclusion is of great significance to optimize multi-scale intercity investment, realize industrial gradient transfer and promote the coordinated development of industry.
Authors
- Youwei Tan
- Yiting Wang (ORCID: https://orcid.org/0000-0001-7751-0592)
- Zhihui Gu (ORCID: https://orcid.org/0000-0003-4456-9197)
- Lipeng Duan
Institutions
- Hong Kong Polytechnic University (HK)
- Shenzhen University (CN)
- Shenzhen Bao'an District People's Hospital (CN)
- Fujian Institute of Subtropical Botany (CN)
Publication Details
- Journal
- Heliyon
- Published
- 2024-09-01
- DOI
- https://doi.org/10.1016/j.heliyon.2024.e37623
- Citations
- 5
- Primary Topic
- Global Urban Networks and Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 9.79
Funders
- National Natural Science Foundation of China
- Shenzhen University