关系依赖如何影响全球化城市网络的生长发育——以苹果手机供应商为例

doi:10.12118/j.issn.1000–6060.2021.198

Abstract

Abstract:

Recently there has been an increase in the number of the relationship turns and the evolution of new economic geography, which facilities the transformation of city network research, namely, from structural characteristics to influence mechanism. In light of the existing research progress, the paper introduces microconfiguration through the lens of the structural perspective to investigate the growth and development mechanism of city networks. To be more specific, initially, the city networks of R&D-oriented, production-oriented, and OEM service-oriented are specified built based on the suppliers’ data of iPhone’s components and parts in 2019, and afterward, we conduct motif analysis and exponential random graph model (ERGM) to examine the microprocesses in the spatial growth of city networks. The results demonstrate that: (1) reciprocity and the intermediary effect are widely and commonly distributed in the three types of city networks, which profoundly affect connectivity development and promote the growth of the hierarchical structure and the availability of the entire network. (2) The process of preferential attachment and the effect of receiver and sender (branches) constitute core structural mechanisms interpreting hierarchical centrality pattern of city networks, both of them embody the phenomenon of path dependence centered on in-degree centrality in the growth processes of city networks. (3) Triangle structure (transitive triangle and circular triad motif) and homogeneity are micro basis components that promote the cluster growth and community structure of city network and the phenomenon of rich clubs. Moreover, the homogeneity influence on the spatial growth of city networks is primarily reflected in the linkages between core cities. (4) Enterprises’ path dependence and distance are the main external factors that drive and affect the growth of city networks. Overall, in the current city network research, there is still a problem that quite focuses on measuring structural characteristics, while ignoring the analysis of the influence mechanism. Furthermore, in the existing literature on the influence mechanism of city networks, many researchers focus on a qualitative macro description based on independent variables, nevertheless, but little on the micro growth and development mechanism of city networks from the standpoint of graph theory and structuralism. Hence, a microconfiguration of ERGM is used through the lens of relationship dependence in this paper, subsequently; we introduce exogenous covariates and endogenous structural variables into the hypothesis verification of city network influence mechanism, which is very important for broadening the research scope of the influence mechanism of the existing city network research.

Key words: globalizing city networks, iPhone, relationship dependence, exponential random graph model

LIU Qing,JIANG Xiaorong. How does relationship dependence affect the spatial growth of globalizing city networks: A case of iPhone’s suppliers[J].Arid Land Geography, 2022, 45(1): 310-324.

Figures/Tables 10

Fig. 1

Fig. 2

Fig. 3

Tab. 1

Tab. 2

Estimation results of ERGM regression"

变量	研发型城市网络		生产型城市网络		代工服务型城市网络
变量	估计值（标准误）	t-比率	估计值（标准误）	t-比率	估计值（标准误）	t-比率
edges	-5.65（0.23）^***	-0.01	-3.74（0.11）^***	-0.02	-1.78（0.17）^***	-0.01
mutual	3.32（0.14）^***	-0.03	2.34（0.59）^***	0.04	2.02（0.32）^***	0.03
gwidegree	3.16（0.72）^***	-0.02	1.63（0.38）^**	-0.04	1.04（0.11）	0.12
gwodegree	-0.73（0.12）	0.07	0.59（0.24）	-0.07	0.99（0.36）	-0.09
multiple 2-paths	0.59（0.33）^***	-0.08	1.23（0.63）^***	-0.04	0.71（0.57）^***	-0.02
transitiy	2.49（0.37）^***	-0.02	1.33（0.14）^*	0.07	0.98（0.21）	0.08
cyclic triad	0.81（0.19）^**	-0.07	0.66（0.28）^**	-0.09	-0.27（0.03）	-0.09
sender_br	0.75（0.13）	-0.09	0.46（0.28）	-0.08	0.55（0.11）	-0.03
receiver_br	1.88（0.74）^***	0.05	2.69（0.43）^***	-0.02	2.05（0.92）^***	0.01
node_core	3.99（0.83）^***	-0.01	1.29（0.66）^***	-0.05	2.56（0.79）^***	0.02
node_ordinary	1.77（0.13）	0.06	0.94（0.11）^**	0.07	0.88（0.51）	-0.14
β₁_GDP	-0.99（0.08）	-0.08	2.03（0.19）^***	0.01	-1.28（0.37）	0.03
β₂_highway	0.74（0.22）	-0.09	1.27（0.53）^***	-0.02	0.68（0.79）^***	-0.07
β₃_patent	3.56（1.23）^***	-0.01	-1.99（0.55）	0.06	-0.82（0.15）	0.08
β₄_popularity	4.44（0.98）^**	-0.02	2.08（0.34）	0.02	1.38（0.22）	0.05
β₅_pop	-0.32（1.57）	0.09	-0.65（0.09）	-0.04	-0.54（1.25）	0.19
β₆_Herfindahl	-1.99（0.82）^***	-0.05	-0.76（0.11）	-0.06	-0.47（0.09）^*	0.04
edgecov₁	1.04（0.53）^**	0.06	2.97（1.22）^***	0.01	0.39（0.02^）*	-0.05
edgecov₂	3.33（0.94）^***	-0.01	-1.25（0.18）	0.05	1.62（0.88）^**	-0.06
edgecov₃	2.14（0.88）^***	-0.02	1.09（0.26）^**	-0.01	1.31（0.69）	0.05
edgecov₄	5.23（1.64）^***	0.01	3.33（0.73）^***	-0.02	4.31（0.99）^***	-0.01
AIC	20.79		26.03		28.35
BIC	32.86		41.22		42.64
GOF t-比率	-0.02		-0.05		-0.03

Tab. 2

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

References 23

[1]	Dicken P. Global shift: Reshaping the global economic map in the 21st century[M]. Beijing: The Commercial Press, 2009.
[2]	宁越敏. 企业空间组织与城市-区域发展[M]. 北京: 科学出版社, 2011.
	[Ning Yuemin. Spatial organization of enterprise and development of city-regional[M]. Beijing: Science Press, 2011. ]
[3]	陈肖飞, 苗长虹, 潘少奇, 等. 轮轴式产业集群内企业网络特征及形成机理——基于2014年奇瑞汽车集群实证分析[J]. 地理研究, 2018, 37(2):353-365. doi: 10.11821/dlyj201802009
	[Chen Xiaofei, Miao Changhong, Pan Shaoqi, et al. Characteristics and construction mechanism of enterprise networks in “Hub-and-Spoke” cluster: Empirical evidence from Chery cluster in 2014, China[J]. Geographical Research, 2018, 37(2):353-365. ] doi: 10.11821/dlyj201802009
[4]	刘清, 杨永春, 蒋小荣, 等. 基于全球价值链的全球化城市网络分析:以苹果手机供应商为例[J]. 地理学报, 2021, 76(4):870-887. doi: 10.11821/dlxb202104007
	[Liu Qing, Yang Yongchun, Jiang Xiaorong, et al. An analysis of the multidimensional globalizing city networks based on global value chain: A case study of iPhone’s suppliers[J]. Acta Geographica Sinica, 2021, 76(4):870-887. ] doi: 10.11821/dlxb202104007
[5]	刘清, 杨永春, 蒋小荣. 全球价值生产的空间组织: 以苹果手机供应链为例[J]. 地理研究, 2020, 39(12):93-112.
	[Liu Qing, Yang Yongchun, Jiang Xiaorong. Spatial organization of global value production: A case study of supply chain of Apple’s iPhone[J]. Geographical Research, 2020, 39(12):93-112. ]
[6]	李仙德. 基于上市公司网络的长三角城市网络空间结构研究[J]. 地理科学进展, 2014, 33(12):1587-1600. doi: 10.11820/dlkxjz.2014.12.002
	[Li Xiande. Spatial structure of the Yangtze River Delta urban network based on the pattern of listed companies network[J]. Progress in Geography, 2014, 33(12):1587-1600. ] doi: 10.11820/dlkxjz.2014.12.002
[7]	薛德升, 邹小华. 基于中资商业银行全球空间扩展的世界城市网络及其影响因素[J]. 地理学报, 2018, 73(6):989-1001. doi: 10.11821/dlxb201806001
	[Xue Desheng, Zou Xiaohua. The world city network based on the global expansion of Chinese commercial banks and its influencing factors[J]. Acta Geographica Sinica, 2018, 73(6):989-1001. ] doi: 10.11821/dlxb201806001
[8]	盛科荣, 杨雨, 孙威. 中国城市的网络地位及影响因素研究——基于上市公司500强企业网络视角[J]. 地理科学, 2020, 40(5):68-78.
	[Sheng Kerong, Yang Yu, Sun Wei. Network position and underlying factors of cities in China: A study from corporate networks of the largest 500 public companies[J]. Scientia Geographica Sinica, 2020, 40(5):68-78. ]
[9]	袁红林, 辛娜. 中国高端制造业的全球贸易网络格局及其影响因素分析[J]. 经济地理, 2019, 39(6):108-117.
	[Yuan Honglin, Xin Na. Global trade network pattern and influencing factors of advanced manufacturing in China[J]. Economic Geography, 2019, 39(6):108-117. ]
[10]	邵璇璇, 姚永玲. 长江中游城市群的空间网络特征及其影响机制[J]. 城市问题, 2019(10):15-26.
	[Shao Xuanxuan, Yao Yongling. Spatial network characteristics and influence mechanism of urban agglomerations in the middle reaches of the Yangtze River[J]. Urban Problems, 2019(10):15-26. ]
[11]	盛广耀. 中国省际人口流动网络的演化及其解释[J]. 中国人口·资源与环境, 2018, 28(11):1-9.
	[Sheng Guangyao. Study on the evolution and explanation of inter-provincial population flow network in China[J]. China Population, Resources and Environment, 2018, 28(11):1-9. ]
[12]	盛科荣, 张红霞, 赵超越. 中国城市网络关联格局的影响因素分析——基于电子信息企业网络的视角[J]. 地理研究, 2019, 38(5):32-46.
	[Sheng Kerong, Zhang Hongxia, Zhao Chaoyue. Determinants of the urban spatial network in China: An analysis through the lens of corporate networks within electronic information industry[J]. Geographical Research, 2019, 38(5):32-46. ]
[13]	Chong Z, Pan S. Understanding the structure and determinants of city network through intra-firm service relationships: The case of Guangdong-Hong Kong-Macao Greater Bay Area[J]. Cities, 2020, 103(5):1-11.
[14]	Liu X, Derudder B, Liu Y. Regional geographies of intercity corporate networks: The use of exponential random graph models to assess regional network formation[J]. Regional Science, 2015, 94(1):109-126.
[15]	Ma D, Yu Q, Li J, et al. Innovation diffusion enabler or barrier: An investigation of international patenting based on temporal exponential random graph models[J]. Technology in Society, 2020, 64:1-12.
[16]	刘林青, 陈紫若, 田毕飞. 结构依赖如何影响贸易网络形成及演化: 以“一带一路”为例[J]. 世界经济研究, 2020, 316(6):107-121, 138.
	[Liu Linqing, Chen Ziruo, Tian Bifei. How does structural dependence affect the formation and evolution of trade network: An empirical analysis based on “the Belt and Road”[J]. World Economy Studies, 2020, 316(6):107-121, 138. ]
[17]	马卫, 黄晓燕, 曹小曙. “一带一路”沿线国家开放度时空格局及其影响因素[J]. 干旱区地理, 2020, 43(5):207-219.
	[Ma Wei, Huang Xiaoyan, Cao Xiaoshu. Spatio-temporal pattern of openness of countries along the Belt and Road Initiative and its influencing factors[J]. Arid Land Geography, 2020, 43(5):207-219. ]
[18]	Boschma R A, Frenken K. Why is economic geography not an evolutionary science? Towards an evolutionary economic geography[J]. Journal of Economic Geography, 2006, 6(3):273-302. doi: 10.1093/jeg/lbi022
[19]	李从容, 向文倩. 关中平原城市群中心城市空间联系强度研究[J]. 干旱区地理, 2020, 43(6):1593-1602.
	[Li Congrong, Xiang Wenqian. Spatial connection intensity of central cities in Guanzhong Plain City Group[J]. Arid Land Geography, 2020, 43(6):1593-1602. ]
[20]	Hymer S. The multinational corporation and the law of uneven development: Perspectives on world politics[M]. London: Routledge, 2006.
[21]	Lusher D, Koskinen J, Robins G. Exponential random graph models for social networks: Theory, methods, and applications[M]. Cambridge: Cambridge University Press, 2013.
[22]	Zhang F, Ning Y M, Lou X Y. The evolutionary mechanism of China’s urban network from 1997 to 2015: An analysis of air passenger flows[J]. Cities, 2020, 103(5):1-10.
[23]	Davis J A, Leinhardt, S. The structure of positive relations in small groups[C]// Berger J, Zelditch M, Anderson B, et al. Sociological Theories in Progress. Boston, MA: Houghton Mifflin, 1972: 218-251.

网络效应	参数	Statnet命名	假设检验
内生结构效应	弧	edges	一个图中的关联数,表征关系的存在（常数项）
	互惠性	mutual	城市之间是否倾向于建立双向链接关系?
	流行性	gwidegree	城市网络是否具有聚敛性趋势,核心城市节点形成以输入关系为主的星型结构?
	积极性	gwodegree	城市网络是否具有扩张性趋势,核心城市节点形成以输出关系为主的星型结构?
	连通性	multiple 2-paths	城市之间是否倾向于建立中介关系,整体网络从而具备较高连通性?
	传递三角形	transitiy	城市网络是否具有传递性集聚的三角关系,拥有多个合作伙伴的城市间具有分工合作的倾向?
	循环三方组	cyclic triad	城市网络是否具有闭合性集聚的三角关系,子网络是否具有三元闭合特征?
行动者—网络效应	发送者（分支机构）	sender_br	分支工厂布局较多的城市是否更倾向于发送更多关系?
	接收者（分支机构）	receiver_br	分支工厂布局较多的城市是否更倾向于接收更多关系?
	同质性	homophily	核心城市是否更趋向于与其他核心城市建立链接关系?
		homophily	普通城市是否更趋向于与其他普通城市建立链接关系?
	城市相关属性（β）	nodecov	属性β强的城市能否吸引更多跨国公司设立分支机构?
网络关系协变量	地理邻近	edgecov₁	地理邻近的城市间是否更倾向于建立链接关系?
	认知邻近	edgecov₂	认知邻近的城市间是否更倾向于建立链接关系?
	开放程度	edgecov₃	开放程度高的城市是否更容易构建生产分工关系?
	路径依赖	edgecov₄	城市网络是否倾向于在已有城市网络的基础上构建?

How does relationship dependence affect the spatial growth of globalizing city networks: A case of iPhone’s suppliers

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 10

References 23

Related Articles 0

Metrics

Comments

Recommended 0