数字经济增长动力与区域收入的空间分布规律

doi:10.11821/dlxb202108005

摘要/Abstract

摘要：

为探究数字经济增长的动力构成、地域差异以及与区域收入之间的空间分布规律,本文以中国数字经济创新高地浙江省为样本,构建了数字经济增长动力要素指标体系,并首先提出了数字经济“增长动力指数”构想。借助Weaver-Thomas模型、灰色关联分析以及GIS分层设色法,从地级市层面对浙江省数字经济增长的主导动力构成进行空间可视化分析,并验证了其与区域收入的关联性。结果表明：① 浙江省数字经济增长动力类型特征呈弱波动状态。② 从整体空间格局来看,数字经济增长呈现以杭州和宁波为核心的“双核心”空间格局现象,产业供给动力主导型主要分布在浙西南地区;市场需求动力主导型、信息应用动力主导型及创新驱动动力主导型主要分布在浙西北地区。③ 数字经济“增长动力指数”与区域收入之间存在较强的关联性,较高的数字经济增长动力指数对应的地区收入也处于较高水平,反之亦然。数字经济主导动力结构的变化正在形成一种复杂多样的区域经济增长行为模式。

关键词: 数字经济, 增长动力, 区域收入, Weaver-Thomas模型, 空间分布, 浙江省

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

陈修颖, 苗振龙. 数字经济增长动力与区域收入的空间分布规律[J]. 地理学报, 2021, 76(8): 1882-1894.

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

图/表 8

表1

表2

表3

图1

图2

图3

图4

表4

2007—2017年浙江省数字经济增长动力指数与域收入灰色关联度系数

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

表4

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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