数字经济增长动力与区域收入的空间分布规律

doi:10.11821/dlxb202108005

Abstract

Abstract:

To explore the dynamic digital economy growth, regional differences, and the spatial distribution of regional income, this study takes Zhejiang Province, China's digital economy innovation highland, as a research sample, constructs the index system of dynamic factors of digital economic growth, and proposes the concept of a Digital Economy Growth Driving Index (DEGDI). Using the Weaver-Thomas model, grey correlation analysis, and GIS hierarchical coloring method, the paper analyzes the dominant driving force of digital economic growth in Zhejiang at the city level and verifies its relevance with regional income. The research results show that: (1) The dynamic characteristics of digital economic growth in this province fluctuates in a small range. (2) From the spatial pattern, the digital economic growth presents a "double core" phenomenon, in which Hangzhou and Ningbo are the cores. The industry-supply leading type is mainly distributed in the southwest of Zhejiang; the market-demand-driven, information-application-driven, and innovation-driven types are mainly found in the northwest part of the province. (3) There is a strong correlation between the DEGDI and regional income. The higher the DEGI, the higher the regional income, and vice versa. The change of the leading dynamics structure of the digital economy is forming a complex and diverse regional economic growth behavior mode.

Key words: digital economy, growth dynamics, regional income, Weaver-Thomas model, spatial distribution, Zhejiang Province

CHEN Xiuying, MIAO Zhenlong. Spatial distribution of digital economic growth dynamics and regional income[J].Acta Geographica Sinica, 2021, 76(8): 1882-1894.

Figures/Tables 8

Tab. 1

Tab. 2

Tab. 3

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Tab. 4

Grey correlation coefficient between the dynamic index of digital economic growth and regional income in Zhejiang Province from 2007 to 2017

年份	$s 0'$	$s i'$	$s i' - s 0'$	$γ 0 i$
2007	3.3828	2.5582	0.8246	0.8938
2010	3.6750	3.1397	0.5354	0.9359
2015	3.8942	2.9769	0.9174	0.8956
2017	3.5928	1.2794	2.3134	0.7174

Tab. 4

References 40

[1]	Marcus A, Weinelt B, Goutrobe A. Expanding participation and boosting growth: The infrastructure needs of the digital economy. World Economics Forum, 2015: 1-44.
[2]	Zhang L M, Chen S. China's digital economy. IMF Working Papers, 2019, 19(16):1-24.
[3]	G20 DETF. G20 digital economy development and cooperation initiative. G20 Digital Economy Task Force, 2016: 1-9.
[4]	Jing Wenjun, Sun Baowen. Digital economy promotes high-quality economic development: A theoretical analysis framework. Economist, 2019(2):66-73.
	[ 荆文君, 孙宝文. 数字经济促进经济高质量发展: 一个理论分析框架. 经济学家, 2019(2):66-73.]
[5]	Rodríguez-Pose A. Convergence or divergence? Types of regional responses to socio-economic change in western Europe. Tijdschrift Voor Economische En Sociale Geografie, 1999, 90(4):365-378. doi: 10.1111/tesg.1999.90.issue-4
[6]	OECD. OECD digital economy outlook 2015. Paris: OECD Publishing, 2015: 20-24.
[7]	Bukht R, Heeks R. Defining, conceptualising and measuring the digital economy. GDI Development Informatics Working Papers, No.68, Global Development Institute, The University of Manchester, Manchester, 2017: 1-24.
[8]	Sun Jie, Miao Zhenlong, Chen Xiuying. The impact of China's information technology gap on regional income difference. Economic Geography, 2019, 39(12):31-38.
	[ 孙杰, 苗振龙, 陈修颖. 中国信息化鸿沟对区域收入差异的影响. 经济地理, 2019, 39(12):31-38.]
[9]	Pei Changhong, Ni Jiangfei, Li Yue. Approach to digital economy from the perspective of political economics. Finance & Trade Economics, 2018, 39(9):5-22.
	[ 裴长洪, 倪江飞, 李越. 数字经济的政治经济学分析. 财贸经济, 2018, 39(9):5-22.]
[10]	Handel M. The effects of information and communication technology on employment, skills, and earnings in developing countries. Background Paper for the World Development Report 2016. Washington, DC, 2016: 9-11.
[11]	Han J S. A study on the factors on regional economic growth in the perspective of technology innovation theory. Productivity Review, 2014, 28(4):509-536. doi: 10.15843/kpapr
[12]	Kang Y H. Influence factors of regional economic growth. The Korean Association for Public Administration, 2008, 42(1):365-381.
	[ 강윤호. 지역경제 성장의 영향요인 분석. 한국행정학보, 2008, 42(1):365-381.]
[13]	Miao Z L. Digital economy value chain: Concept, model structure, and mechanism. Applied Economics, 2021, 53(3):1-16. DOI: 10.1080/00036846.2021.1899121. doi: 10.1080/00036846.2021.1899121
[14]	Wang Binyan, Tian Junfeng, Cheng Lisha, et al. Spatial differentiation of digital economy and its influencing factors in China. Scientia Geographica Sinica, 2018, 38(6):859-868. doi: 10.13249/j.cnki.sgs.2018.06.004
	[ 王彬燕, 田俊峰, 程利莎, 等. 中国数字经济空间分异及影响因素. 地理科学, 2018, 38(6):859-868.]
[15]	Xu Jin, Liang Miya. On ant effect and digital economy: Analysis and application on the negative proposition of herd effect. Economist, 2017(4):27-35.
	[ 徐晋, 梁米亚. 论蚂蚁效应与数字经济: 对羊群效应否命题的分析与应用. 经济学家, 2017(4):27-35.]
[16]	Ahmad N, Ribarsky J. Towards a framework for measuring the digital economy. Paper for 16th Conference of IAOS OECD Headquarters. Paris, 2018: 1-33.
[17]	Zhang Xun, Wan Guanghua, Zhang Jiajia, et al. Digital economy, financial inclusion, and inclusive growth. Economic Research Journal, 2019, 54(8):71-86.
	[ 张勋, 万广华, 张佳佳, 等. 数字经济、普惠金融与包容性增长. 经济研究, 2019, 54(8):71-86.]
[18]	Liu Shuchun. Targeting path and policy supply for the high quality development of China's digital economy. Economist, 2019(6):52-61.
	[ 刘淑春. 中国数字经济高质量发展的靶向路径与政策供给. 经济学家, 2019(6):52-61.]
[19]	Zhang Xueling, Jiao Yuexia. A preliminary study of China's digital economy development index and its application. Zhejiang Social Sciences, 2017(4):32-40, 157.
	[ 张雪玲, 焦月霞. 中国数字经济发展指数及其应用初探. 浙江社会科学, 2017(4):32-40, 157.]
[20]	Chen Xiaohong. Trend analysis of technology fusion and application innovation in the digital economy era. Social Scientist, 2018(8):8-23.
	[ 陈晓红. 数字经济时代的技术融合与应用创新趋势分析. 社会科学家, 2018(8):8-23.]
[21]	Zhao Changwen, Xu Zhaoyuan, Zhu Hongming. The new driving force of China economic growth in the late stage of industrialization. China Industrial Economics, 2015(6):44-54.
	[ 赵昌文, 许召元, 朱鸿鸣. 工业化后期的中国经济增长新动力. 中国工业经济, 2015(6):44-54.]
[22]	Solow R M. A contribution to the theory of economic growth. The Quarterly Journal of Economics, 1956, 70(1):65-94. doi: 10.2307/1884513
[23]	Shumpeter J A. The Theory of Economic Development. New Briunswick: Transaction Publishers, NJ, 1983.
[24]	Dellink R, Chateau J, Lanzi E, et al. Long-term economic growth projections in the shared socioeconomic pathways. Global Environmental Change, 2017, 42:200-214. doi: 10.1016/j.gloenvcha.2015.06.004
[25]	Li Ruzi, Liu Yaobin, Xie Dejin. Evolution of economic efficiency and its influencing factors in the industrial structure changes in China. Acta Geographica Sinica, 2017, 72(12):2179-2198. doi: 10.11821/dlxb201712005
	[ 李汝资, 刘耀彬, 谢德金. 中国产业结构变迁中的经济效率演进及影响因素. 地理学报, 2017, 72(12):2179-2198.]
[26]	Hao Dajiang, Zhang Rong. Factor endowment, agglomeration effect and economic growth power conversion. Economist, 2018(1):41-49.
	[ 郝大江, 张荣. 要素禀赋、集聚效应与经济增长动力转换. 经济学家, 2018(1):41-49.]
[27]	OECD. OECD Digital Economy Outlook 2017. Paris: OECD Publishing, 2017: 11-13.
[28]	Dutta S, Mia I. The global information technology report 2010: 2011 transformations 2.0. Geneva, Switzerland: World Economic Forum, 2011: 3-32.
[29]	DESI. Digital economy and society index. European Commission, 2018: 1-124.
[30]	Barefoot K, Curtis D, Jolliff W, et al. Defining and measuring the digital economy. Bureau of Economic Analysis Working Paper, 2018: 1-24.
[31]	Lee Y S. An empirical analysis on the impact of municipalities social development expenditure on economic outcome. Journal of the Korean Regional Science Association, 2009, 25(3):5-23.
[32]	Weaver J C. Changing patterns of cropland use in the middle west. Economic Geography, 1954, 30(1):1-47. doi: 10.2307/142233
[33]	Thomas D. Agriculture in Wales during the Napoleonic Wars. London: Wales Publishing Co., 1963: 184-187.
[34]	Kumar S. Dynamics of cropping pattern in northwestern Haryana a spatio-temporal study. Research Review International Journal of Multidisciplinary, 2019, 4(3):1156-1161.
[35]	Li M, Fang C. A study on the design of decision support system for industrial distribution in town. WRI World Congress on Software Engineering, 2009: 157-162.
[36]	Guo H L, Min L. Key industries selection of business and trade service in Tongzhou district. 13th International Conference on Service Systems and Service Management (ICSSSM), 2016: 1-5.
[37]	Gu Ming. Research on strategic industry development of Sichuan Province based on weaver-Thomas model. Journal of Chongqing Technology and Business University (Natural Science Edition), 2012, 29(5):35-39.
	[ 顾明. 基于Weaver-Thomas模型的四川省工业战略产业研究. 重庆工商大学学报(自然科学版), 2012, 29(5):35-39.]
[38]	Hu W. Construction and analysis of China's industrial network of carbon correlation. Applied Ecology and Environmental Research, 2019, 17(6):14487-14503. doi: 10.15666/aeer/1706_1448714503
[39]	Zhao Yuan, Hao Lisha. Analysis on the region classification of crude oil flow in China. Journal of Natural Resources, 2009, 24(1):93-103.
	[ 赵媛, 郝丽莎. 我国石油资源空间流动的地域类型分析. 自然资源学报, 2009, 24(1):93-103.]
[40]	Zhang Yaoguang, Wei Donglan, Wang Guoli, et al. Analysis of interprovincial space difference in marine economy and the building of marine economically strong provinces in China. Geographical Research, 2005, 24(1):46-56.
	[ 张耀光, 魏东岚, 王国力, 等. 中国海洋经济省际空间差异与海洋经济强省建设. 地理研究, 2005, 24(1):46-56.]

动力类型	代表指标	指标计算公式	单位	标签	文献来源
市场需求动力	人均在线购物数额	地区社会消费品零售总额/地区总人口	元	Onlicon	[19, 27, 29]
市场需求动力	人均在线支付数额	地区电信业务收入总额/地区总人口	元	Onlipay	[19, 29]
信息应用动力	百人移动电话保有率	地区移动电话数量/地区总人口	个/万人	Mobile	[14, 27, 30]
	百人互联网网民比例	地区互联网网民数量/地区总人口	%	Internet	[6, 27]
	信息通信产业就业比例	信息通信产业就业人数/城镇总就业人数	%	Infojob	[6, 8, 29]
创新驱动动力	万人专利保有量	地区授权专利数/地区总人口	个/万人	Patent	[6, 29]
创新驱动动力	万人大学生保有量	地区大学生数/地区总人口	人/万人	Student	[6, 11]
产业供给动力	服务业产值占RGDP比例	服务业RGDP/区域GDP总量	%	Servout	[12, 27]
	服务业投资占固定投资比例	服务业投资额/总固定投资额	%	Servinve	[6, 29]
	财政自给率	地方财政一般预算内收入/一般预算内支出	%	Finself	[11-12, 31]

要素组合类型	计算方法	Infojob	Student	Onlipay	Onlicon	Finself	Patent	Servinve	Internet	Mobile	Servout
一元驱动	X_i	22.06	16.29	9.09	8.54	8.40	7.37	7.20	7.10	6.99	6.96
	X	100	0	0	0	0	0	0	0	0	0
	(X_i-X)²	6074.12	265.46	82.54	72.88	70.57	54.32	51.78	50.41	48.91	48.47
	S²	681.95
二元驱动	X_i	22.06	16.29	9.09	8.54	8.40	7.37	7.20	7.10	6.99	6.96
	X	50	50	0	0	0	0	0	0	0	0
	(X_i-X)²	780.46	1136.17	82.54	72.88	70.57	54.32	51.78	50.41	48.91	48.47
	S²	239.65
三元驱动	X_i	22.06	16.29	9.09	8.54	8.40	7.37	7.20	7.10	6.99	6.96
	X	33.3	33.3	33.3	0	0	0	0	0	0	0
	(X_i-X)²	126.26	289.24	586.35	72.88	70.57	54.32	51.78	50.41	48.91	48.47
	S²	139.92
···
六元驱动	X_i	22.06	16.29	9.09	8.54	8.40	7.37	7.20	7.10	6.99	6.96
	X	16.6	16.6	16.6	16.6	16.6	16.6	0	0	0	0
	(X_i-X)²	29.85	0.09	56.47	65.01	67.23	85.19	51.78	50.41	48.91	48.47
	S²	50.34
···
十元驱动	X_i	22.06	16.29	9.09	8.54	8.40	7.37	7.20	7.10	6.99	6.96
	X	10	10	10	10	10	10	10	10	10	10
	(X_i-X)²	145.52	39.60	0.84	2.14	2.56	6.92	7.86	8.41	9.04	9.23
	S²	23.21

Spatial distribution of digital economic growth dynamics and regional income

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 8

References 40

Related Articles 15

Metrics

Comments

城市	2007年	2010年	2015年	2017年
杭州	43	43	43	34
宁波	43	43	42	41
温州	11	11	11	11
嘉兴	22	22	21	21
湖州	12	41	43	34
绍兴	41	41	41	41
金华	41	33	32	33
衢州	31	32	31	31
舟山	41	24	33	41
台州	41	11	11	11
丽水	31	31	31	31

[1]	GUAN Haoming, YANG Qingshan, HAO Feilong, FENG Zhangxian. Economic resilience characteristics of Shenyang city based on a perspective of industry-enterprise-space [J]. Acta Geographica Sinica, 2021, 76(2): 415-427.
[2]	LIU Min, HAO Wei. Spatial distribution and its influencing factors of national A-level tourist attractions in Shanxi Province [J]. Acta Geographica Sinica, 2020, 75(4): 878-888.
[3]	DENG Hui, BU Fan. Spatial distribution of the Tang Po Lakes upon the Central Hebei Plain during the Northern Song Dynasty [J]. Acta Geographica Sinica, 2020, 75(11): 2332-2345.
[4]	ZHOU Yang, HUANG Han, LIU Yansui. The spatial distribution characteristics and influencing factors of Chinese villages [J]. Acta Geographica Sinica, 2020, 75(10): 2206-2223.
[5]	LIN Xiao,XU Wei,DU Debin,YANG Fan. Spatial pattern and technology-capital geographic proximity of venture capital firms in Shanghai [J]. Acta Geographica Sinica, 2019, 74(6): 1112-1130.
[6]	Jianbang WANG, Jun ZHAO, Chuanhua LI, Yu ZHU, Chongyang KANG, Chao GAO. The spatial-temporal patterns of the impact of human activities on vegetation coverage in China from 2001 to 2015 [J]. Acta Geographica Sinica, 2019, 74(3): 504-519.
[7]	Tao PEI, Yaxi LIU, Sihui GUO, Hua SHU, Yunyan DU, Ting MA, Chenghu ZHOU. Principle of big geodata mining [J]. Acta Geographica Sinica, 2019, 74(3): 586-598.
[8]	DONG Suocheng,YANG Yang,LI Fujia,CHENG Hao,LI Jingnan,BILGAEV Alexey,LI Zehong,LI Yu. Influencing mechanism and policy suggestions of China- Mongolia-Russia high-speed railway construction [J]. Acta Geographica Sinica, 2019, 74(2): 297-311.
[9]	HAN Huiran,YANG Chengfeng,SONG Jinping. Impact factors of location choice and spatial pattern evolution of wholesale enterprises in Beijing [J]. Acta Geographica Sinica, 2018, 73(2): 219-231.
[10]	TIAN Guanghui,MIAO Changhong,HU Zhiqiang,MIAO Jianming. Environmental regulation, local protection and the spatial distribution of pollution-intensive industries in China [J]. Acta Geographica Sinica, 2018, 73(10): 1954-1969.
[11]	FAN Zemeng,HUANG Yan,YUE Tianxiang. Scenarios simulation of vascular plant species abundance distribution on Qinghai-Tibet Plateau [J]. Acta Geographica Sinica, 2018, 73(1): 164-176.
[12]	Shuai MA, Yu SHENG, Wei CAO, Jichun WU, Xiaoying HU, Shengting WANG. Numerical simulation of spatial distribution and change of permafrost in the source area of the Yellow River [J]. Acta Geographica Sinica, 2017, 72(9): 1621-1633.
[13]	He ZHU, Jiaming LIU, Ziwen SANG, Wendong WEI, Zongcai WEI. Characteristic and contribution factors of different types of ethnic cultural resources: A case study of Gesar cultural and ecological protection experiment area [J]. Acta Geographica Sinica, 2017, 72(6): 1118-1132.
[14]	Yanji ZHANG, Lei ZHANG, Lingyan WU. Spatial distribution of street vending and its spatial relationship with formal commerce: Quantitative research using distance-based methods [J]. Acta Geographica Sinica, 2017, 72(4): 618-632.
[15]	Xiang HE, Zhenshan LIN, Huiyu LIU, Xiangzhen QI. Analysis of the driving factors of PM_2.5 in Jiangsu province based on grey correlation model [J]. Acta Geographica Sinica, 2016, 71(7): 1119-1129.