上海互联网新创企业的时空演化及影响因素

doi:10.18306/dlkxjz.2019.03.008

摘要/Abstract

摘要：

基于互联网经济转型和信息技术浪潮下的创新创业活动已成为社会广泛关注的热点。论文利用上海互联网新创企业数的截面数据,采用核密度估计、Ripley's K函数、负二项回归模型等方法探究互联网新创企业的时空演化特征与区位影响因素。结果表明：① 时序变化上,互联网创业在2010年后进入活跃期,行业分布与全国创业形势及上海产业导向相一致。② 空间演变上,整体呈现“大集聚小分散”的分异特征,企业高度集聚于中环线内的同时向郊区中心镇和新城扩散。中心城区企业集聚强度不断增强,集聚规模由4.5 km扩张到6.5 km;在空间上由相对均衡向多中心集聚的形态演变。黄浦-静安-徐汇片、五角场、陆家嘴、张江和漕河泾等5大核心集聚区以其特定的资源优势获得互联网新创企业的青睐。③ 孵化环境、生活环境、商务环境、投资环境等构成互联网创业活动的外部环境需求;产业集聚、技术因子和土地价格等对互联网新创企业区位分布产生了显著影响。

关键词: 空间演变, 互联网新创企业, 创业环境, 企业区位因子, 负二项回归, 上海

Abstract:

Innovation and entrepreneurial activities based on the transformation of Internet economy and information technology have become a focus of attention in today's society. Using the cross-sectional data on the number of Internet start-ups in Shanghai Municipality, this study explored their spatial distribution characteristics and location factors by adopting the methods of nuclear density analysis, Ripley's K function, and negative binomial regression model. The results show that: 1) Internet entrepreneurship has entered an active period since 2010, and the change is consistent with the situation nationwide and the urban industrial orientation in Shanghai. 2) With regard to the spatial distribution, an overall pattern of agglomeration at the macro level and dispersion at the micro level is present. While highly concentrated within the middle ring, enterprises also spread to suburban central towns and new towns. In the central urban areas, agglomeration intensity has continuously increased, and the scale has expanded from 4.5 km to 6.5 km. The spatial distribution changed from relatively balanced to multi-center agglomerations. The five core agglomeration areas, including Huangpu-Jing'an-Xuhui, Wujiaochang, Lujiazui, Zhangjiang, and Caohejing, have won the favor of Internet start-ups depending on their specific resource advantages. 3) Concerning the influencing factors, incubation environment, living environment, business environment, and investment environment constitute the external environment demand of Internet entrepreneurial activities. Industrial agglomeration, technological factors, and land prices have had significant impacts on the spatial distribution of Internet start-ups.

Key words: spatial change, internet start-ups, entrepreneurial environment, firm location factors, negative binomial regression, Shanghai

段吕晗, 杜德斌, 黄筱彧. 上海互联网新创企业的时空演化及影响因素[J]. 地理科学进展, 2019, 38(3): 383-394.

Lvhan DUAN, Debin DU, Xiaoyu HUANG. Spatial and temporal changes and influencing factors of the location of internet start-ups in Shanghai, China[J]. PROGRESS IN GEOGRAPHY, 2019, 38(3): 383-394.

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一级变量	二级变量	变量含义	预期
创业环境因子	孵化环境 Incubation1 Incubation2	街道内信息服务产业基地数量(个) 街道内传统孵化器数量(个)	+ +
	Incubation3	街道内新型孵化器数量(个)	+
	投资环境 Invest	街道内互联网风险投资机构数量(个)	+
	生活环境 Amenity	街道内星巴克/健身房/图书馆的数量(个)	+
	商务环境 Business1 Business2	街道内商务写字楼和三星级以上酒店数量(个) 街道内中小企业服务机构数量(个)	+ +
企业区位因子	产业集聚 Industry	街道内全国100强互联网企业总部/分部数量(个)	+
	技术因子 University	街道中心到最近高等院校的直线距离(km)	-
	交通通达性 Transport1 Transport2	街道内的地铁覆盖程度(km/km²) 街道内道路密度(km/km²)	+ +
	劳动力数量 Labor	街道内15~64岁就业适龄人口数(人)	+
	土地价格 Landprice	2013年上海办公基准地价分类：1=一级地价、2=二级地价,依此类推	-

变量	模型1	模型2	模型3	模型4	模型5	模型6
Incubation1	0.543^***					0.364^***
	(0.136)					(0.134)
Incubation2		0.213^***				0.220^***
		(0.0489)				(0.0518)
Incubation3		0.124^**				0.0207
		(0.0576)				(0.0511)
Invest			0.0259^*			-0.0064
			(0.0155)			(0.0058)
Amenity				0.0439^***		0.0299^***
				(0.00783)		(0.0059)
Business1					0.0217^***	0.0156^***
					(0.0046)	(0.0041)
Business2					0.132^***	0.0092
					(0.0391)	(0.0414)
Industry	0.396^***	0.304^***	0.417^***	0.367^***	0.335^***	0.158^**
	(0.0964)	(0.0674)	(0.0799)	(0.0680)	(0.0842)	(0.0764)
University	-0.0320^*	-0.0325^*	-0.0410^**	-0.0351^*	-0.0410^**	-0.0309^*
	(0.0169)	(0.0171)	(0.0189)	(0.0182)	(0.0190)	(0.0168)
Transport1	-0.981^**	-0.806^*	-0.764^*	-0.700*	-0.932^**	-0.854^***
	(0.464)	(0.438)	(0.447)	(0.360)	(0.371)	(0.330)
Transport2	-0.0083	-0.0080	-0.0152	-0.0153	-0.0187^*	-0.0128
	(0.0139)	(0.0134)	(0.0139)	(0.0123)	(0.0118)	(0.0102)
Labor	-0.0003	-0.0002	-0.0002	-0.0002	-0.0001	-6.76E-05
	(0.0002)	(0.0002)	(0.0002)	(0.0002)	(0.0002)	(0.0002)
Landprice	-0.259^***	-0.223^***	-0.224^***	-0.153^**	-0.167^***	-0.113^**
	(0.0523)	(0.0588)	(0.0630)	(0.0607)	(0.0564)	(0.0537)
常数	3.992^***	3.640^***	3.867^***	2.946^***	3.264^***	2.452^***
	(0.426)	(0.456)	(0.482)	(0.501)	(0.427)	(0.442)
pseudo R²	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
Log-likelihood	-651.4698	-646.8692	-656.0258	-640.7540	-640.0985	-616.9416