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Where Are Business Incubators Built? County-Level Spatial Distribution and Rationales Based on the Big Data of Chinese Yangtze River Delta Region.
- Source :
-
ISPRS International Journal of Geo-Information . Jun2024, Vol. 13 Issue 6, p169. 19p. - Publication Year :
- 2024
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Abstract
- Business incubators (BIs) in China have predominantly exhibited a government-led characteristic, recently broadening their spatial and temporal scope and extending reach to the county level. Regarding the inadequacies of county-level analysis scale, this study leverages Points of Interest (POI) big data to overcome them. To comprehend the governmental rationale in the construction of BIs, we examine the evolution dynamics of BIs in conjunction with policies. An economic geography framework is developed, conceptualizing BIs as quasi-public goods and productive services, and incorporating considerations of county-level fiscal operations and industrial structures. Focusing on the Yangtze River Delta (YRD) region as a case study, our findings reveal that over 98% of County Administrative Units (CAUs) have built BIs. Using kernel density estimation and Moran's I, the spatial patterns of CAUs are identified. The CAUs are further classified into three categories of economic levels using the k-means algorithm, uncovering differentiated relationships between industry, finance, and their respective BI. Additionally, we analyze the density relationship between BIs and other facilities at a micro-level, showcasing various site selection rationales. The discussions highlight that while BIs tend to align with wealthier areas and advanced industries, affluent CAUs offer location advantages on BIs, whereas less wealthy CAUs prioritize quantity for political achievements. This paper concludes with recommendations about aligning BIs based on conditions and outlooks on future research. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 22209964
- Volume :
- 13
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- ISPRS International Journal of Geo-Information
- Publication Type :
- Academic Journal
- Accession number :
- 178195573
- Full Text :
- https://doi.org/10.3390/ijgi13060169