World Regional Studies ›› 2020, Vol. 29 ›› Issue (3): 557-567.DOI: 10.3969/j.issn.1004-9479.2020.03.2019384
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Ying YU(), Qing LIU(), Guicai LI
Received:
2019-08-08
Revised:
2019-12-05
Online:
2020-05-30
Published:
2020-06-12
Contact:
Qing LIU
通讯作者:
刘青
作者简介:
余颖(1995-),女,硕士研究生,研究方向为城市与区域规划,E-mail: yu-ying@pku.edu.cn。
基金资助:
Ying YU, Qing LIU, Guicai LI. The spatial evolution of Shenzhen high-tech electronic information technology agglomeration pattern and locational determinants[J]. World Regional Studies, 2020, 29(3): 557-567.
余颖, 刘青, 李贵才. 深圳高新电子信息企业空间格局演化及其影响因素[J]. 世界地理研究, 2020, 29(3): 557-567.
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URL: https://sjdlyj.ecnu.edu.cn/EN/10.3969/j.issn.1004-9479.2020.03.2019384
参数 | 2007年 | 2013年 | 2017年 |
---|---|---|---|
I值 | 0.25*** | 0.35*** | 0.37*** |
Z值 | 23.72 | 25.23 | 29.11 |
显著度 | 显著集聚 | 显著集聚 | 显著集聚 |
Tab. 1 Moran's I of Shenzhen HEIT enterprises
参数 | 2007年 | 2013年 | 2017年 |
---|---|---|---|
I值 | 0.25*** | 0.35*** | 0.37*** |
Z值 | 23.72 | 25.23 | 29.11 |
显著度 | 显著集聚 | 显著集聚 | 显著集聚 |
年份 | 数量(关内/全市) | 原关内企业数量占比 |
---|---|---|
2007 | 1031/1564 | 65% |
2013 | 851/1835 | 46% |
2017 | 3006/6888 | 42% |
Tab. 2 Statistics of electronic HEIT enterprises inside the Zone borders
年份 | 数量(关内/全市) | 原关内企业数量占比 |
---|---|---|
2007 | 1031/1564 | 65% |
2013 | 851/1835 | 46% |
2017 | 3006/6888 | 42% |
集聚热点区 | 2007年 | 2013年 | 2017年 | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
总数 | 百分比 | 峰值 | 均值 | 总数 | 百分比 | 峰值 | 均值 | 总数 | 百分比 | 峰值 | 均值 | |
高新区集聚区(南山) | 524 | 33.50% | 81 | 14 | 491 | 26.75% | 57 | 13 | 2301 | 33.41% | 227 | 32 |
老工业区集聚区(福田) | 301 | 19.25% | 62 | 8 | 186 | 10.14% | 46 | 7 | 507 | 7.36% | 167 | 22 |
龙头企业集聚区(龙华) | - | - | - | - | 67 | 3.65% | 15 | 4 | 513 | 7.45% | 76 | 18 |
Tab.3 Statistics of enterprise-agglomeration area in 2007, 2013, 2017
集聚热点区 | 2007年 | 2013年 | 2017年 | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
总数 | 百分比 | 峰值 | 均值 | 总数 | 百分比 | 峰值 | 均值 | 总数 | 百分比 | 峰值 | 均值 | |
高新区集聚区(南山) | 524 | 33.50% | 81 | 14 | 491 | 26.75% | 57 | 13 | 2301 | 33.41% | 227 | 32 |
老工业区集聚区(福田) | 301 | 19.25% | 62 | 8 | 186 | 10.14% | 46 | 7 | 507 | 7.36% | 167 | 22 |
龙头企业集聚区(龙华) | - | - | - | - | 67 | 3.65% | 15 | 4 | 513 | 7.45% | 76 | 18 |
分类 | 变量 | 变量代码 | 定义与解释 |
---|---|---|---|
政策因素 | 园区政策 | PARK | 格网内是否有企业在产业园区内* |
产业规划 | PLANNING | 格网内是否在高新技术产业规划园区范围内 | |
集聚因素 | 产业集聚 | AGGLO | 格网内上一期电子信息企业数量 |
旧工业区 | OLD | 格网内在旧工业区的企业数量 | |
智力因素 | 知识技术 | INSTITUTE | 格网内的知识创新载体数量 |
基础因素 | 道路密度 | RDENSITY | 格网的道路密度 |
对内交通 | METRO | 格网内的地铁站数量** | |
对外交通 | RSTATION | 格网中心距离最近火车站的距离 | |
城市服务 | CBD | 格网中心距离最近CBD的距离 |
Tab.4 Variables and definitions of influence factors
分类 | 变量 | 变量代码 | 定义与解释 |
---|---|---|---|
政策因素 | 园区政策 | PARK | 格网内是否有企业在产业园区内* |
产业规划 | PLANNING | 格网内是否在高新技术产业规划园区范围内 | |
集聚因素 | 产业集聚 | AGGLO | 格网内上一期电子信息企业数量 |
旧工业区 | OLD | 格网内在旧工业区的企业数量 | |
智力因素 | 知识技术 | INSTITUTE | 格网内的知识创新载体数量 |
基础因素 | 道路密度 | RDENSITY | 格网的道路密度 |
对内交通 | METRO | 格网内的地铁站数量** | |
对外交通 | RSTATION | 格网中心距离最近火车站的距离 | |
城市服务 | CBD | 格网中心距离最近CBD的距离 |
变量名 | 2007年 | 2017年 | ||||
---|---|---|---|---|---|---|
OSL | SLM | SEM | OSL | SLM | SEM | |
CONSTANT | -0.008 | -0.007 | -0.008 | -0.016 | -0.015 | -0.016 |
PARK | 0.711*** | 0.681*** | 0.715*** | 0.552*** | 0.547*** | 0.565*** |
PLANNING | 0.263*** | 0.235*** | 0.254*** | 0.157*** | 0.153*** | 0.165*** |
OLD | 0.353*** | 0.349*** | 0.351*** | 0.232*** | 0.232*** | 0.242*** |
AGGLO | 0.109*** | 0.110*** | 0.112*** | 0.279*** | 0.277*** | 0.269*** |
INSTITUTE | 0.024* | 0.009 | 0.009 | 0.038*** | 0.036*** | 0.037*** |
RDENSITY | 0.057*** | 0.043*** | 0.056*** | 0.057*** | 0.054*** | 0.048*** |
METRO | 0.062*** | 0.055*** | 0.047*** | 0.025* | 0.025* | 0.020* |
RSTATION | 0.105* | 0.075 | 0.121* | -0.078** | -0.076** | -0.077** |
CBD | -0.132** | -0.093* | -0.152** | 0.045 | 0.045 | 0.039 |
R2 | 0.872 | 0.875 | 0.877** | 0.822 | 0.822 | 0.825 |
ρ | 0.115*** | 0.021 | ||||
λ | 0.288*** | 0.21*** | ||||
Log likelihood | -869.878 | -848.277 | -841.126 | -1241.190 | -1240.660 | -1225.884 |
AIC | 1759.760 | 1718.550 | 1702.250 | 2502.380 | 2503.330 | 2471.770 |
SC | 1816.940 | 1781.450 | 1759.430 | 2559.560 | 2566.230 | 2528.950 |
Tab.5 Regression result of influence factors in of HEIT enterprises
变量名 | 2007年 | 2017年 | ||||
---|---|---|---|---|---|---|
OSL | SLM | SEM | OSL | SLM | SEM | |
CONSTANT | -0.008 | -0.007 | -0.008 | -0.016 | -0.015 | -0.016 |
PARK | 0.711*** | 0.681*** | 0.715*** | 0.552*** | 0.547*** | 0.565*** |
PLANNING | 0.263*** | 0.235*** | 0.254*** | 0.157*** | 0.153*** | 0.165*** |
OLD | 0.353*** | 0.349*** | 0.351*** | 0.232*** | 0.232*** | 0.242*** |
AGGLO | 0.109*** | 0.110*** | 0.112*** | 0.279*** | 0.277*** | 0.269*** |
INSTITUTE | 0.024* | 0.009 | 0.009 | 0.038*** | 0.036*** | 0.037*** |
RDENSITY | 0.057*** | 0.043*** | 0.056*** | 0.057*** | 0.054*** | 0.048*** |
METRO | 0.062*** | 0.055*** | 0.047*** | 0.025* | 0.025* | 0.020* |
RSTATION | 0.105* | 0.075 | 0.121* | -0.078** | -0.076** | -0.077** |
CBD | -0.132** | -0.093* | -0.152** | 0.045 | 0.045 | 0.039 |
R2 | 0.872 | 0.875 | 0.877** | 0.822 | 0.822 | 0.825 |
ρ | 0.115*** | 0.021 | ||||
λ | 0.288*** | 0.21*** | ||||
Log likelihood | -869.878 | -848.277 | -841.126 | -1241.190 | -1240.660 | -1225.884 |
AIC | 1759.760 | 1718.550 | 1702.250 | 2502.380 | 2503.330 | 2471.770 |
SC | 1816.940 | 1781.450 | 1759.430 | 2559.560 | 2566.230 | 2528.950 |
1 | 刘子諝,周江华,李纪珍. 过犹不及:财政补贴对企业创新的多重作用机制分析. 科学学与科学技术管理. 2019, 40(01): 51-64. |
Liu Z, Zhou J, LI J. Not only additionality: The dual effects of subsidies on firm innovation. Science of Science and Management of S.&.T. 2019, 40(01): 51-64. | |
2 | 卢明华,李丽. 北京电子信息产业及其价值链空间分布特征研究. 地理研究. 2012, 31(10): 1861-1871. |
Lu M, Li L. The spatial distribution of electronic information industries and its value chain parts in Beijing. Geographical Research. 2012, 31(10): 1861-1871. | |
3 | 樊杰,王宏远,陶岸君,等. 工业企业区位与城镇体系布局的空间耦合分析——洛阳市大型工业企业区位选择因素的案例剖析. 地理学报. 2009, 64(02): 131-141. |
Fan J, Wang H, Tao A, et al. Coupling industrial location with urban system distribution: A case study of China's Luoyang Municipality. Acta Geographica Sinica, 2009, 64(02): 131-141. | |
4 | 王铮,赵晶媛,刘筱,等. 高技术产业空间格局演变规律及相关因素分析. 科学学研究. 2006(02): 227-232. |
Wang Z, Zhao J, Liu X, et al. Ananlysis to the evolution law of high-tech industry in space and its factors. Studies In Science of Science. 2006(02): 227-232. | |
5 | 王承云,秦健,杨随. 京津沪渝创新型城区研发产业集群研究. 地理学报. 2013, 68(8): 1097-1109. |
Wang C, Qin J, Yang S. Analysis of the cluster mode of R&D industry in the innovative city districts: Taking Beijing, Tianjin, Shanghai and Chongqing as examples. Acta Geographica Sinica. 2013, 68(8): 1097-1109. | |
6 | 袁丰,魏也华,陈雯,等. 苏州市区信息通讯企业空间集聚与新企业选址. 地理学报. 2010, 65(2): 153-163. |
Yuan F, Wei Y, Chen W, et al. Spatial agglomeration and new firm formation in the information and communication technology industry in Suzhou. Acta Geographica Sinica. 2010, 65(2): 153-163. | |
7 | 毕秀晶,汪明峰,李健,等. 上海大都市区软件产业空间集聚与郊区化. 地理学报. 2011, 66(12): 1682-1694. |
Bi X, Wang M, Li J, et al. Agglomeration and suburbanization: A study on the spatial distribution of software industry and its evolution in metropolitan Shanghai. Acta Geographica Sinica. 2011, 66(12): 1682-1694. | |
8 | 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. 地理科学进展. 2019, 38(3): 383-394. |
Duan L, Du D, Huang X. Spatial and temporal changes and influencing factors of the location of internet start-ups in Shanghai, China. Progress in Geography. 2019, 38(3): 383-394. | |
9 | 王丹,方斌,陈正富. 基于社区尺度的互联网企业空间格局与演化——以扬州市区为例. 经济地理. 2018, 38(6): 133-141. |
Wang D, Fang B, Chen Z. Spatial pattern and evolution of internet companies based on community scale —A case study of Yangzhou. Economic Geography, 2018, 38(6): 133-141. | |
10 | 林娟,张欣炜,汪明峰. 上海大都市区物联网产业集聚与空间演化. 人文地理, 2017(3): 131-136+145. |
Lin J, Zhang X, Wang M. Agglomeration and spatial evolution of the internet of things industry in Shanghai metropolitan. Human Geography, 2017(3): 131-136+145. | |
11 | Scott A J. Industrial organization and the logic of intra-metropolitan location: I. theoretical considerations. Economic Geography, 1983, 59(3): 233-250. |
12 | 王铮,毛可晶,刘筱,等.高技术产业聚集区形成的区位因子分析.地理学报,2005(4):567-576. |
Wang Z, Mao K, Liu X, et al. An analysis for location factors that cause industrial agglomeration. Acta Geographica Sinica, 2005(4): 567-576. | |
13 | Aranya R. Location theory in reverse?Location for global production in the IT industry of Bangalore. Environment & Planning A. 2008, 40(2): 446-463. |
14 | Arauzo-Carod J M, Viladecans-Marsal E. Industrial Location at the Intra-Metropolitan Level: The Role of Agglomeration Economies. Regional Studies, 2009, 43(3): 545-558. |
15 | Saxenian A. Regional advantage: Culture and competition in Silicon Valley and Route 128. Research Policy, 1995, 25(3): 484-485. |
16 | Porter M E. The competitive advantage of nations. New York: Free Press, 1990: 1-896. |
17 | 刘青,李贵才,仝德,等. 基于ESDA的深圳市高新技术企业空间格局及影响因素. 经济地理, 2011, 31(6): 926-933. |
Liu Q, Li G, Tong D, et al. The spatial pattern and influence factors of high- tech firms in Shenzhen based on ESDA. Economic Geography, 2011, 31(6): 926-933. | |
18 | 张惠璇,刘青,李贵才. "刚性·弹性·韧性"——深圳市创新型产业的空间规划演进与思考. 国际城市规划. 2017, 32(3): 130-136. |
Zhang H, Liu Q, Li G. "Rigidity · Flexibility · Resilience": The thought and evolution of spatial planning on innovative industries in Shenzhen. Urban Planning International, 2017, 32(3): 130-136. | |
19 | Martin R. Roepke lecture in economic geography—Rethinking regional path dependence: beyond lock-in to evolution. Economic Geography, 2010, 86(1): 1-27. |
20 | Dicken P. Global shift: Transforming the world economy. 3rd Edition. Paul Chapman Publishing, 1998: 1-512. |
21 | Klepper S. The capabilities of new firms and the evolution of the US automobile industry. Industrial & Corporate Change, 2002, 11(4): 645-666. |
22 | Wallsten S J. An empirical test of geographic knowledge spillovers using geographic information systems and firm-level data. Regional Science & Urban Economics, 2001, 31(5): 571-599. |
23 | Boschma R A, Wenting R. The spatial evolution of the British automobile industry: Does location matter?Industrial & Corporate Change, 2007, 16(2): 213-238. |
24 | Delgado M, Porter M, Stern S. Clusters and entrepreneurship. Working Papers, 2010, 10(10): 495-518. |
25 | Arbia G, Espa G, Giuliani D, et al. Detecting the existence of space–time clustering of firms. Regional Science & Urban Economics, 2010, 40(5): 311-323. |
26 | 杨凡,杜德斌,段德忠,等. 城市内部研发密集型制造业的空间分布与区位选择模式——以北京、上海为例. 地理科学, 2017, 37(4): 492-501. |
Yang F, Du D, Duan D, et al. The intra-metropolitan location of r&d-intensive manufacturing in Beijing and Shanghai. Scientia Geographica Sinica, 2017, 37(4): 492-501. | |
27 | 谢敏,赵红岩,朱娜娜,等. 宁波市软件产业空间格局演化及其区位选择. 经济地理. 2017, 37(4): 127-134+148. |
Xie M, Zhao H, Zhu N, et al. Spatial pattern evolution and location selection of software industry in Ningbo. Economic Geography, 2017, 37(4): 127-134+148. | |
28 | Marcon E, Puech F. Evaluating the geographic concentration of industries using distance-based methods. Journal of Economic Geography, 2003, 3(4): 409-428. |
29 | Wong D W S, Lee J. Statistical analysis of geographic information with ArcView GIS and ArcGIS. Wiley, 2008: 1-464. |
30 | 王远飞,何洪林. 空间数据分析方法. 北京:科学出版社, 2007: 1-243. |
Wang Y, He H. Methods of spatial data analysis. Beijing: Science Press, 2007: 1-243. | |
31 | 张松林,张昆. 空间自相关局部指标Moran指数和G系数研究. 大地测量与地球动力学, 2007, 27(3): 31-34. |
Zhang S, Zhang K. Contrast study on Moran and Getis-Ord indexes of local spatial autocorrelation indices. Journal of Geodesy and Geodynamics, 2007, 27(3): 31-34. | |
32 | Anselin L. Spatial econometrics: methods and models. Springer, 1988: 1-284. |
33 | Mills E S. Handbook of regional and urban economics. Vol. 2. Urban Economics. North Holland, 1987: 1-638. |
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