The micro-location patterns and influencing factors of entrepreneurial spaces: A case study of Guangzhou

doi:10.3969/j.issn.1004-9479.2023.08.2021748

Abstract

Abstract:

To a certain extent, the entrepreneurial spaces represent the spatial expression of entrepreneurial activities in the context of the "Internet +" transformation. This article combines the methods of bivariate spatial autocorrelation, geographically weighted regression, and negative binomial regression model to identify the urban innovation and entrepreneurship environment with entrepreneurial vitality and industrial characteristics, and explores the micro-location patterns and influencing factors of the entrepreneurial spaces in Guangzhou under the background of Mass Entrepreneurship and Innovation. Results indicate that: ①Since the implementation of the Mass Entrepreneurship and Innovation, entrepreneurial spaces in Guangzhou have continued to emerge. Mass innovation spaces in Guangzhou have shown a trend of rapid ascending followed by leveling off and the transition from the location window period to the spatial agglomeration, and the spatial distribution of incubators is relatively stable. ②Micro-location patterns of entrepreneurial spaces are characterized by innovative and entrepreneurial patterns, creative and innovative patterns, creative-oriented, technology-intensive and capital-proximity patterns. The proportion of entrepreneurial spaces driven by technology-intensive and relying on universities has increased. The central business district, historical urban areas, and urban villages have spatial heterogeneity in the micro-location of entrepreneurial spaces. The proximity of universities and the radiation of industrial parks are the key influencing factors of the local and global location selection of entrepreneurial spaces.

Key words: mass innovation space, technology business incubator, micro location, urban innovation and entrepreneurship environment, Guangzhou

摘要：

创业空间一定程度上代表“互联网+”转型背景下创业活动的空间表达。本文结合双变量空间自相关、地理加权回归、负二项回归模型等方法，通过识别兼具创业活力和产业特性的城市创新创业环境，探讨双创政策背景下广州创业空间的微区位模式及影响因素。研究表明：①实施“双创”政策以来，广州创业空间不断涌现，众创空间呈现由初期暴增到逐渐平缓的态势，从区位窗口期向空间集聚转变，孵化器空间分布较为稳定。②创业空间微区位模式表现为创新创业型、创意创新型、创意导向型、技术密集型和资本邻近型，技术密集驱动和依托高校建立的创业空间比例上升。中央商务区、历史城区和城中村等不同区域微区位影响存在空间异质性，其中高校邻近和园区辐射是局部和全局创业空间区位选择的关键影响因子。

关键词: 众创空间, 科技企业孵化器, 微区位, 城市创新创业环境, 广州市

Xiangjie LIU, Min WANG, Chengliang LIU. The micro-location patterns and influencing factors of entrepreneurial spaces: A case study of Guangzhou[J]. World Regional Studies, 2023, 32(8): 73-87.

刘向杰, 王敏, 刘承良. 创业空间的微区位模式及影响因素[J]. 世界地理研究, 2023, 32(8): 73-87.

Figures/Tables 15

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变量类型	变量名	变量含义
主要变量	创意导向Creative	格网内2016年前文化创意产业数量/个
	技术密集Tech	格网内2016年前信息技术服务企业数量/个
	资本邻近VC	格网内2016年前风险投资机构数量/个
控制变量	生活便利Amenity	格网内星巴克、健身房数量/个
	设施多样化Diversity	格网内土地利用混合度/种
	高校邻近lnCollege	格网距最近重点高等院校距离/m，取对数
	园区辐射lnIndustry	格网距最近工业园区/生产性服务业园区距离/m，取对数
	地租成本landprice	格网办公基准地价：一级地价为1，二级为2，以此类推
	集聚效应Aggl	格网内2016年前创业空间数量/个

变量类型	变量名	变量含义
主要变量	创意导向Creative	格网内2016年前文化创意产业数量/个
	技术密集Tech	格网内2016年前信息技术服务企业数量/个
	资本邻近VC	格网内2016年前风险投资机构数量/个
控制变量	生活便利Amenity	格网内星巴克、健身房数量/个
	设施多样化Diversity	格网内土地利用混合度/种
	高校邻近lnCollege	格网距最近重点高等院校距离/m，取对数
	园区辐射lnIndustry	格网距最近工业园区/生产性服务业园区距离/m，取对数
	地租成本landprice	格网办公基准地价：一级地价为1，二级为2，以此类推
	集聚效应Aggl	格网内2016年前创业空间数量/个

变量	最小值	最大值	平均值	标准差
Y创业空间	0.054	2.068	0.958	0.360
X1创意	0	140.262	11.012	17.498
X2技术	0	588.22	23.977	49.692
X3资本	0	125.03	3.010	9.726

变量	最小值	最大值	平均值	标准差
Y创业空间	0.054	2.068	0.958	0.360
X1创意	0	140.262	11.012	17.498
X2技术	0	588.22	23.977	49.692
X3资本	0	125.03	3.010	9.726

变量	回归系数	VIF	比较指标	数值
截距值	0.873^***	—	调整R²	0.198
X1	0.001 334^**	2.317	AICc值	710.654
X2	0.002 615^***	1.914	—	—
X3	0.002 392^**	1.685	—	—