长三角多尺度城市网络联系特征及其对城市高质量发展的影响

doi:10.3969/j.issn.1004-9479.2024.03.20230437

摘要/Abstract

摘要：

随着交通基础设施和通信技术的不断完善，城市间相互作用程度显著提高。本文基于长三角26个地级市面板数据，运用社会网络分析方法、随机效应模型和固定效应模型等方法，研究了企业总部-分支联系视角下的长三角多尺度城市网络特征及其对高质量发展的影响。研究结果显示：无论是从整体网络特征还是从节点的网络联系来看，基于企业内部组织的不同尺度城市网络均呈现出网络化的发展趋势；长三角群内尺度网络联系和群外尺度网络联系均具有明显的层级性，网络层级越高，联系对数量则越少且参与的城市等级越高，同时受到距离与行政隶属约束越弱；长三角内部城市能够通过嵌入不同尺度的城市网络，显著地提升其城市高质量发展，同时城市网络联系对城市高质量发展的影响存在尺度异质性和规模异质性；长三角内部城市主要通过城市网络的经济效应、社会效应以及创新效应三种传导机制实现城市高质量发展。

关键词: 流空间, 城市网络外部性, 高质量发展, 公司总部-分支联系, 长三角, 企业

Abstract:

With the continuous improvement of transportation infrastructure and communication technology, the degree of interaction between cities has significantly increased. Based on panel data of 26 prefecture-level cities in the Yangtze River Delta, this paper investigates the characteristics of the multi-scale urban network and the impact of urban network on high-quality development from the perspective of corporate headquarters-branch connections. The results are as follows: (1)Both the overall network characteristics and the node network connections indicate that the urban network at different scales in the Yangtze River Delta exhibits a trend of network development. (2) Urban network connections in the Yangtze River Delta exhibit significant hierarchical characteristics. As the network hierarchy increases, the number of connections decreases, and the levels of participating cities increase, with less constraint imposed by distance and administrative levels.(3) Cities within the Yangtze River Delta can significantly advance high-quality development by integrating into an urban network of different scales, and the impact of urban network connections on high-quality development demonstrates both scale heterogeneity and size heterogeneity. (4) Cities within the Yangtze River Delta primarily achieve high-quality development through three transmission mechanisms: the economic effect, social effect, and innovation effect of the urban network.

Key words: flow space, urban network externalities, high-quality development, corperate headquater-branch connection, Yangtze River Delta, enterprise

李培庆, 赵新正, 姜永青, 郁星, 张得康. 长三角多尺度城市网络联系特征及其对城市高质量发展的影响[J]. 世界地理研究, 2024, 33(3): 147-160.

Peiqing LI, Xinzheng ZHAO, Yongqing JIANG, Xing YU, Dekang ZHANG. Multi-scale urban network connectivity characteristics in the Yangtze River Delta and its impact on high-quality urban development: A perspective on corporate headquarter-branch connections[J]. World Regional Studies, 2024, 33(3): 147-160.

图/表 10

参考文献 44

1	CASTELLS M. The Rise of the Network Society. Oxford: Blackwell, 1996.
2	TAYLOR P. Hierarchical tendencies amongst world cities: A global research proposal. Cities, 1997, 14(6): 323-332.
3	谭一洺, 杨永春, 冷炳荣, 等. 基于高级生产者服务业视角的成渝地区城市网络体系. 地理科学进展, 2011, 30(6): 724-732.
	TAN Y, YANG Y, LENG B, et al. Urban network system in Chengdu-Chongqing region in the perspective of advanced producer service. Progress in Geography, 2011, 30(6): 724-732.
4	赵新正, 李秋平, 芮旸, 等. 基于财富500 强中国企业网络的城市网络空间联系特征. 地理学报, 2019, 74(4): 694- 709.
	ZHAO X, LI Q, RUI Y, et al. The characteristics of urban network of China: A study based on the Chinese companies in the Fortune Global 500 list. Acta Geographica Sinica, 2019, 74(4): 694-709.
5	胡国建, 陆玉麒. 基于企业视角的城市网络研究进展、思考和展望. 地理科学进展, 2020, 39(9): 1587-1596.
	HU G, LU Y. Progress, thoughts, and prospect of urban network research based on enterprise perspective. Progress in Geography, 2020,39(9): 1587-1596.
6	LUTHI S, THIERSTEIN A, GOEBEL V. Intra-firm and extra-firm linkages in the knowledge economy: The case of the emerging mega-city region of Munich. Global Networks, 2010, 10(1): 114-137.
7	PAN F, XIA Y. Location and agglomeration of headquarters of publicly listed firms within China's urban system. Urban Geography, 2014, 35(5): 757-779.
8	CAPELLO R.The city network paradigm: Measuring urban network externalities.Urban Studies,2000,37(11):1925-1945.
9	VAN M, NEAL Z, DERUDDER B. Disentangling agglomeration and network externalities: A conceptual typology. Papers in Regional Science, 95(1), 61-80.
10	MEIGERS E, BURGER M, HOOGERBRUGGE M. Borrowing size in networks of cities: City size, network connectivity and metropolitan functions in Europe. Papers in Regional Science, 2016, 95(1): 181-198.
11	ALONSO W. Urban zero population growth. Daedalus, 1973, 102(4): 191-206.
12	BURGER M, MERJERS E, VAN O. Regional spatial structure and retail amenities in the Netherlands. Regional Studies, 2014, 48(12): 1972-1992.
13	CAMAGNI R, CAPELL R, CARAGLIU A. Static vs. dynamic agglomeration economies: Spatial context and structural evolution behind urban growth. Papers in Regional Science, 2017, 95(1): 133-158.
14	MEIJERS E, BURGER M. Stretching the concept of "borrowed size". Urban Studies, 2016, 54(1): 269-291.
15	叶珊珊, 曹明明, 胡胜. 关中平原城市群经济联系网络结构演变及对经济增长影响研究. 干旱区地理, 2022, 45(1): 277-286.
	YE S, CAO M, HU S. Study on the evolution of economic connection network structure of urban agglomeration in Guanzhong Plain and its impact on economic growth. Geography of Arid Areas, 2022, 45 (1): 277-286.
16	姚常成,吴康.集聚外部性、网络外部性与城市创新发展.地理研究,2022,41(9):2330-2349.
	YAO C, WU K. Cluster externality, network externality and urban innovative development. Geographical Research, 2022,41 (9): 2330-2349.
17	谭爽, 魏冶, 李晓玲, 等. 不同邻近性视角下城市网络外部性、集聚外部性对城市经济的影响——以辽宁省城市网络为例. 地理研究, 2022, 41(9): 2404-2417.
	TAN S, WEI Y, LI X, et al. The impact of urban network externalities and agglomeration externalities on urban economy through the lens of different proximity: A case of urban network in Liaoning Province. Geographical Research, 2022, 41(9): 2404-2417.
18	程玉鸿, 陈利静. 城市网络发育特征及其对城市竞争力的影响——基于珠三角主要金融行业148家企业选址数据. 产经评论, 2014, 5(4): 117-127.
	CHENG Y, CHEN L. Characteristics of urban network development and its impact on urban competitiveness-based on site selection data of 148 enterprises in major financial industries in the Pearl River Delta. Industrial and Economic Review, 2014, 5(4): 117-127.
19	盛科荣, 张杰, 张红霞. 上市公司500强企业网络嵌入对中国城市经济增长的影响. 地理学报, 2021, 76(4): 818-834.
	SHENG K, ZHANG J, ZHANG H. Network embedding and urban economic growth in China: A study based on the corporate networks of top 500 public companies. Acta Geographica Sinica, 2021, 76(4): 818-834.
20	罗能生, 田梦迪, 杨钧, 等. 高铁网络对城市生态效率的影响——基于中国277个地级市的空间计量研究. 中国人口·资源与环境, 2019, 29(11): 1-10.
	LUO N, TIAN M, YANG J, et al. The impact of high-speed rail network on urban ecological efficiency-a spatial econometric study based on 277 prefecture level cities in China. China's Population, Resources and Environment, 2019, 29 (11): 1-10.
21	周灿, 曾刚, 曹贤忠. 中国城市创新网络结构与创新能力研究. 地理研究, 2017, 36(7): 1297-1308.
	ZHOU C, ZENG G, CAO X. Research on the structure and innovation ability of China's urban innovation network. Geographical Research, 2017, 36(7): 1297-1308.
22	覃成林, 桑曼乘. 城市网络与城市经济增长. 学习与实践, 2015(4): 5-11.
	QIN C, SANG M. Urban network and urban economic growth. Study and Practice, 2015(4): 5-11.
23	VOLGMANN K, RUSCHE K. The geography of borrowing size: Exploring spatial distributions for German urban regions. Tijdschrift voor Economische en Sociale Geografie, 2020, 111(1): 60-79.
24	姚常成, 宋冬林. 借用规模、网络外部性与城市群集聚经济. 产业经济研究, 2019(2): 76-87.
	YAO C, SONG D. Borrowed-size, network externalities and agglomeration economies in the urban agglomerations. Industrial Economics Research, 2019(2): 76-87.
25	刘修岩, 陈子扬. 城市体系中的规模借用与功能借用——基于网络外部性视角的实证检验. 城市问题, 2017(12): 12-19.
	LIU X, CHEN Z. "Borrowed size" and "borrowed functions" in urban system: Empirical research on agglomeration economy from the view of externalities of networks. Urban Problems, 2017(12): 12-19.
26	刘乐, 盛科荣, 张杰, 等. 金融网络嵌入对中国城市创业活力的影响研究. 地理科学进展, 2022, 41(12): 2244-2257.
	LIU L, SHENG K, ZHANG J, et al. The impact of financial network embedding on entrepreneurial vitality of cities in China. Progress in Geography, 2022, 41(12): 2244-2257.
27	OTSSUKA A. How do population agglomeration and interregional networks improve energy efficiency? Asia-Pacific Journal of Regional Science, 2019, 41(1): 43-52.
28	刘传明, 马青山. 黄河流域高质量发展的空间关联网络及驱动因素. 经济地理, 2020, 40(10): 91-99.
	LIU C, MA Q. Spatial association network and driving factors of high quality development in the Yellow River Basin. Economic Geography, 2020, 40(10): 91-99.
29	李金昌, 史龙梅, 徐蔼婷. 高质量发展评价指标体系探讨. 统计研究, 2019, 36(1): 4-14.
	LI J, SHI L, XU A. Probe into the assessment indicator system on high quality development. Statistical Research, 2019, 36(1): 4-14.
30	聂长飞, 简新华. 中国高质量发展的测度及省际现状的分析比较. 数量经济技术经济研究, 2020, 27(2): 26-47.
	NIE C, JIAN X. Measurement of China's high- quality development and analysis of provincial status. The Journal of Quantitative & Technical Economics, 2020, 27(2): 26-47.
31	MARSHALL A. Principles of Economics. London: Macmillan, 1966.
32	JACOBS J. The Economy of Cities. New York: Random House, 1969.
33	PORTER M, PORTER E.The competitiveness advantage of nations.Competitive Intelligence Review, 2010, 1(1): 14-14.
34	ARROW K J. The economic implications of learning by doing. The Review of Economic Studies, 1962, 29(3): 155-173.
35	ROMER P. Increasing returns and long-run growth. Journal of Political Economy, 1986, 94(5): 1002-1037.
36	HU C, XU Z, YASHIRO N. Agglomeration and productivity in China: Firm level evidence. China Economic Review, 2015(33): 50-66.
37	BATHELT H, MALMBERG A, MASKELL P. Clusters and knowledge: Local buzz, global pipelines and the process of knowledge creation. Progress in Human Geography, 2015, 8(1): 31-56.
38	MASKELL P, BATHELT H. MALMBERG A. Building global knowledge pipelines: The role of temporary clusters. European Planning Studies, 2016, 14(8): 997-1013.
39	BATHELT H. Buzz-and-pipeline dynamics: Towards a knowledge-based multiplier model of clusters. Geography Compass, 2017, 1(6): 1282-1298.
40	CAO K, DERUDDER B, DAI L, et al. 'Buzz-and-pipeline' dynamics in Chinese science: The impact of interurban collaboration linkages on cities' innovation capacity. Regional Studies, 2022, 56(2): 290-306.
41	陈旭, 张亮, 张硕. 多中心空间发展模式与雾霾污染: 基于中国城市数据的经验研究. 重庆大学学报(社会科学版), 2021, 27(5): 30-44.
	CHEN X, ZHANG L, ZHANG S. Polycentric spatial structure and haze pollution: An empirical study based on Chinese urban data. Journal of Chongqing University (Social Science Edition), 2021, 27(5): 30- 44.
42	丁松, 李若瑾. 数字经济、资源配置效率与城市高质量发展. 浙江社会科学, 2022(8): 11-21.
	DING S, LI R. Digital economy, resource allocation efficiency and high-quality development in prefecture-level cities. Zheijiang Social Sciences, 2022(8): 11-21.
43	TONE K. A slacks-based measure of super-efficiency in data envelopment analysis. European Journal of Operational Research, 2002(143): 32-41.
44	ALDERSON A, BECKFIELD J. Power and position in the world city system. American Journal of Sociology, 2004, 109(4): 811-851.

指标	一级指标	二级指标
投入指标	劳动力投入	常住人口
	资本投入	全社会固定资产投入
	能源投入	万吨标准煤
产出指标	经济产出	GDP
	创新产出	城市专利申请量
	社会产出	政府财政收入
	非期望产出	二氧化硫排放
		工业废水排放
		烟粉尘排放

指标	一级指标	二级指标
投入指标	劳动力投入	常住人口
	资本投入	全社会固定资产投入
	能源投入	万吨标准煤
产出指标	经济产出	GDP
	创新产出	城市专利申请量
	社会产出	政府财政收入
	非期望产出	二氧化硫排放
		工业废水排放
		烟粉尘排放

变量	（1）	（2）	（3）	（4）	（5）	（6）	（7）
DEGREE	0.39^**(4.57)	0.42^**(4.41)	0.43^***(4.74)	0.43^***(4.91)	0.41^***(4.46)	0.42^***(4.25)	0.40^***(4.00)
POP		－0.30 (－1.57)	－0.73^*** (－3.83)	－0.74^*** (－3.99)	－0.84^*** (－4.08)	－0.82^*** (－3.60)	－1.37^*** (－5.26)
TEC			0.70^***(3.20)	0.71^***(3.27)	0.83^***(3.94)	0.83^***(3.92)	0.62^*(1.94)
FDI				0.14^***(4.44)	0.13^***(4.27)	0.13^***(4.34)	0.16^***(9.00)
AGG					0.23^***(2.79)	0.23^***(2.71)	0.17^*(1.88)
HUM						－0.05(－0.52)	－0.31(－0.55)
CONS	－0.07(－0.37)	－0.09(－0.46)	0.27(1.48)	0.20(1.25)	0.31^*(1.90)	0.31^*(1.91)	0.09(0.42)
时间	YES	YES	YES	YES	YES	YES	YES
城市	YES	YES	YES	YES	YES	YES	YES
模型	随机效应	随机效应	随机效应	随机效应	随机效应	随机效应	固定效应
R²	0.32	0.34	0.38	0.42	0.43	0.43	0.44

变量	（1）	（2）	（3）	（4）	（5）	（6）	（7）
DEGREE	0.39^**(4.57)	0.42^**(4.41)	0.43^***(4.74)	0.43^***(4.91)	0.41^***(4.46)	0.42^***(4.25)	0.40^***(4.00)
POP		－0.30 (－1.57)	－0.73^*** (－3.83)	－0.74^*** (－3.99)	－0.84^*** (－4.08)	－0.82^*** (－3.60)	－1.37^*** (－5.26)
TEC			0.70^***(3.20)	0.71^***(3.27)	0.83^***(3.94)	0.83^***(3.92)	0.62^*(1.94)
FDI				0.14^***(4.44)	0.13^***(4.27)	0.13^***(4.34)	0.16^***(9.00)
AGG					0.23^***(2.79)	0.23^***(2.71)	0.17^*(1.88)
HUM						－0.05(－0.52)	－0.31(－0.55)
CONS	－0.07(－0.37)	－0.09(－0.46)	0.27(1.48)	0.20(1.25)	0.31^*(1.90)	0.31^*(1.91)	0.09(0.42)
时间	YES	YES	YES	YES	YES	YES	YES
城市	YES	YES	YES	YES	YES	YES	YES
模型	随机效应	随机效应	随机效应	随机效应	随机效应	随机效应	固定效应
R²	0.32	0.34	0.38	0.42	0.43	0.43	0.44

变量	（8）	（9）	（10）	（11）
DEGREE	0.28^*** (4.97)	0.29^*** (4.19)	0.42^*** (5.48)	0.20^** （2.56）
控制变量	YES	YES	YES	YES
时间	YES	YES	YES	YES
城市	YES	YES	YES	YES
模型	随机效应	固定效应	随机效应	固定效应