Spatial proximity, enterprise agglomeration, and innovation output
Mechanisms and insights from China
Bibliographic Data
| ID | 6455447 |
|---|---|
| Authors | Mao Zhang (0000-0002-9693-6908), Feiwei Qin (0000-0001-5036-9365) |
| Year | 2025 |
| Volume | 9 |
| Pages | 100793-100793 |
| Publication date | 2025-06-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sustainable Futures (JOURNAL) |
| Journal identifiers | ISSN: 2666-1888 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.sftr.2025.100793 |
| OpenAlex | W4411080840 |
| Language | EN |
| References cited | 57 |
As global economic transformation accelerates, enterprise agglomeration is pivotal in driving regional innovation and economic growth, particularly in late-developing economies with limited resources. This study introduces a dynamic geospatial measurement method using enterprises’ latitude and longitude data to quantify agglomeration levels, overcoming the limitations of static indicators. Using data from A-share listed companies in Shanghai and Shenzhen (2012–2022), the findings show that enterprise agglomeration significantly enhances innovation quantity and quality, especially in high-tech manufacturing industries with extensive cycles, scale, and reputations, yet may significantly inhibit innovation via intensified competition. Key mechanisms include local knowledge networks, inter-enterprise reciprocity, and government subsidies. Moreover, the agglomeration effect diminishes with greater geographical distance, highlighting spatial dependence. This paper advances agglomeration economy theory while offering actionable policy insights for resource-constrained countries to foster innovation-driven, sustainable development
Business · China · Economic geography · Economic growth · Economics · Economies of agglomeration · Geography · Industrial organization · Regional science · Innovation Policy and RD · Regional Development and Policy · Regional Economics and Spatial Analysis
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| Highly cited | No |
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