信息化水平与科技创新能力的空间关联性及影响因素研究

doi:10.3969/j.issn.1004-9479.2025.08.20230138

摘要/Abstract

摘要：

以广东省各市为研究对象，运用因子分析法、空间自相关分析、地理探测器等分析方法，深入探究广东省区域信息化水平与科技创新的空间关联性及科技创新能力的影响因素。结果表明：①总体上看，广东省信息化水平与科技创新能力呈现增强趋势，但内部不平衡性较大。②从空间关联上看，广东省信息化水平和科技创新能力发展存在显著的空间正相关性，以HH集聚和LL集聚为主。③广东省信息化水平和科技创新能力在各地市之间存在空间扩散效应，但该扩散效应只发生在局部区域。④从影响因素来看，信息化水平对广东省科技创新能力具有促进作用，且经济发展水平、工业产业基础、人力资本、研发投入、教育水平和城镇化水平均能通过提高信息化水平来影响区域创新能力。

关键词: 信息化水平, 科技创新能力, 空间关联, 影响因素, 广东省

Abstract:

Information & communication technologies(ICTs) and regional innovation capabilities(RICs) have a very close relationship.It is necessary to describe the spatio-temporal relationship between ICTs and RICs from the perspective of spatial econometric analysis.In this study, the authors use the factor analysis method, spatial auto-correlation analysis, geographic detector and other quantitative research methods and spatial analysis to deeply explore the spatio-temporal correlations between the ICTs level and RICs and the factors influencing technological innovation capability in Guangdong Province at city-level. There are four main conclusions from this research: ①In general, the informationization level and technological innovation capability in Guangdong Province show an overall enhancement, but the internal imbalance is large.②In terms of spatial correlation, there is a significant positive spatial correlation between informatization level and technological innovation capability in Guangdong Province, with "HH" clusters and "LL" clusters as the main ones.③There is a spatial diffusion effect of informationization level and technological innovation capability in Guangdong Province, but the diffusion effect only occurs in local regions. ④from the perspective of influencing factors, the level of informatization has a promoting effect on the difference of scientific and technological innovation ability in Guangdong Province, and the level of economic development, industrial base, human capital, R&D investment, education level and urbanization level can affect regional innovation ability by improving the level of informatization.

Key words: informatization level, technological innovation capability, spatial correlation, influencing factors, Guangdong Province

方远平, 张峰, 刘凤, 陆文心. 信息化水平与科技创新能力的空间关联性及影响因素研究[J]. 世界地理研究, 2025, 34(8): 170-182.

Yuanping FANG, Feng ZHANG, Feng LIU, Wenxin LU. Spatial correlations and influencing factors on informatization level and technological innovation capability: A case study of Guangdong Province[J]. World Regional Studies, 2025, 34(8): 170-182.

图/表 10

参考文献 29

[1]	沈坤荣,林剑威,傅元海.网络基础设施建设、信息可得性与企业创新边界.中国工业经济,2023(1): 57-75.
	SHEN K, LIN J, FU Y. Network Infrastructure construction, information accessibility and the innovation boundaries of enterprises. China Industrial Economics, 2023(1): 57-75.
[2]	张杰,付奎.信息网络基础设施建设能驱动城市创新水平提升吗?—— 基于 "宽带中国" 战略试点的准自然试验.产业经济研究,2021(5): 1-14.
	ZHANG J, FU K. Can the construction of information network infrastructure drive the level of urban innovation? A quasi-natural experiment of "Broadband China" pilot policy. Industrial Economics Research, 2021(5): 1-14.
[3]	沈国兵,袁征宇.企业互联网化对中国企业创新及出口的影响.经济研究,2020, 55(1): 33-48.
	SHEN G, YUAN Z. The effect of enterprise internetization on the innovation and export of Chinese enterprises. Economic Research Journal, 2020, 55(1): 33-48.
[4]	陈丛波,叶阿忠,陈娟.信息通信技术对城市创新产出的影响.经济地理,2022, 42(10): 92-99.
	CHEN C, YE A, CHEN J. Effects of information and communication technology on urban innovation output. Economic Geography, 2022, 42(10): 92-99.
[5]	张锦文,何风隽.信息通讯技术影响技术创新的地区差异与空间效应.技术经济与管理研究,2022(10): 22-27.
	ZHANG J, HE F. Regional differences and spatial effects of information and communication technology on technological innovation. Technology Economics & Management Research, 2022(10): 22-27.
[6]	何舜辉,杜德斌,焦美琪,等.中国地级以上城市创新能力的时空格局演变及影响因素分析.地理科学,2017, 37 (7): 1014-1022.
	HE S, DU D, JIAO M, et al. Spatial-temporal characteristics of urban innovation capability and impact factors analysis in China. Geographical Science, 2017, 37(7): 1014-1022.
[7]	王俊松,颜燕,胡曙虹.中国城市技术创新能力的空间特征及影响因素:基于空间面板数据模型的研究.地理科学,2017, 37(1): 11-18.
	WANG J, YAN Y, HU S. Spatial pattern and determinants of Chinese urban innovative capabilities base on spatial panel data model. Geographical Science, 2017, 37 (1): 11-18.
[8]	TANG J, CUI W. Does the internet trigger an innovative spatial revolution: Evidence from china. Information Technology & Management, 2024, 25(4):305-318.
[9]	马向平,陈聪聪.长三角区域创新与信息化耦合协调及影响因素分析.湖北农业科学,2019, 58 (15): 167-171.
	MA X, CHEN C. Coupling coordination and influencing factors of regional innovation and informatization in the Yangtze River Delta. Hubei Agricultural Sciences, 2019, 58 (15): 167-171.
[10]	卓乘风,邓峰,白洋,等.区域创新与信息化耦合协调发展及其影响因素分析.统计与决策,2017(19): 139-142.
	ZHUO C, DENG F, BAI Y, et al. Coupling coordination development and influencing factors of regional innovation and informatization. Statistics & Decision, 2017 (19): 139-142.
[11]	武晓静,杜德斌,肖刚,等.长江经济带城市创新能力差异的时空格局演变.长江流域资源与环境,2017,26(4):490-499.
	WU X, DU D, XIAO G,et al.The temporal and spatial evolution of city innovation capability differences inthe Yangtze River Rconomic Belt on the numbers of patents.Resources and Environment in the Yangtze Basin,2017,26(4): 490-499.
[12]	SALDANHA T, JOHN-MARIADOSS B, WU M, et al.How information and communication technology shapes the influence of culture on innovation: A country-level analysis.Journal of Management Information Systems,2021,38(1): 108-139.
[13]	ZHANG C, WANG X. The influence of ict-driven innovation: A comparative study on national innovation efficiency between developed and emerging countries. Behaviour & Information Technology, 2019, 38(9): 876-886.
[14]	KLEIS L, CHWELOS P, RAMIREZ R, et al. Information technology and intangible output: The impact of it investment on innovation productivity. Information Systems Research, 2012, 23(1): 42-59.
[15]	WERNSDORF K, NAGLER M, WATZINGER M. Ict, collaboration, and innovation: Evidence from bitnet. Journal of Public Economics, 2022 (211): 104678.
[16]	ALMEIDA P, KOGUT B. Localization of knowledge and the mobility of engineers in regional networks. Management Science, 1999, 45(7): 905-917.
[17]	VU K. ICT as a source of economic growth in the information age: Empirical evidence from the 1996-2005 period. Telecommunications Policy, 2011, 35(4): 357-372.
[18]	刘晓阳,黄晓东,丁志伟.长江经济带县域信息化水平的空间差异及影响因素.长江流域资源与环境,2019, 28(6): 1262-1275.
	LIU X, HUANG X, DING Z.Spatial pattern and its influencing factors of informationization level at county level in Yangtze River Economic Belt. Resources and Environment in the Yangtze Basin,2019,28(6):1262-1275.
[19]	杜传忠,杨志坤.我国信息化与工业化融合水平测度及提升路径分析.中国地质大学学报 (社会科学版),2015,15(3): 84-97.
	DU C, YANG Z.Research on evaluation of convergence between industrialization and informatization and its development level in China.Journal of China University of Geosciences (Social Sciences Edition),2015,15(3): 84-97.
[20]	刘跃,惠美宁.区域信息化与人力资本关系实证研究.地域研究与开发,2012, 31(3): 43-47.
	LIU Y, HUI M. An empirical research of relationship between regional information progress and human capital. Areal Research and Development, 2012, 31(3): 43-47.
[21]	苏方林.中国省域 R&D 活动的探索性空间数据分析.广西师范大学学报 (哲学社会科学版), 2008, 44(6): 52-56.
	SU F. An exploratory spatial data analysis of R&D activities in China. Journal of Guangxi Normal University (Philosophy and Social Sciences Edition), 2008, 44 (6): 52-56.
[22]	方远平,谢蔓,林彰平.信息技术对服务业创新影响的空间计量分析.地理学报,2013, 68 (8): 1119-1130.
	FANG Y, XIE M, LIN Z. A spatial econometric analysis of impact of ICT on service innovation: Based on analysis of 21 cities in Guangdong Province. Acta Geographica Sinica, 2013, 68 (8): 1119-1130.
[23]	WARTENBERG D. Multivariate spatial correlation: a method for exploratory geographical analysis. Geographical Analysis,2010(17):263-283.
[24]	黄涛,王艳慧,关鸿亮,等.乡村振兴背景下农村基本公共服务与多维贫困的时空耦合特征研究.人文地理,2021, 36 (6): 135-146.
	HUANG T, WANG Y, GUAN H, et al. Research on the coupling characteristics of time and space between rural basic public services and multidimensional poverty under the background of rural revitalization. Human Geography, 2021, 36 (6): 135-146.
[25]	王劲峰,徐成东.地理探测器:原理与展望.地理学报,2017, 72 (1): 116-134.
	WANG J, XU C. Geodetector: Principle and prospective. Acta Geographica Sinica, 2017, 72 (1): 116-134.
[26]	董俊鸷,孟怡伟,丁志伟.中国县域创新产出的空间分异及其影响因素.世界地理研究,2023,32(8): 88-102.
	DONG J, MENG Y, DING Z. Spatial differentiation and influencing factors of innovation output at county scale in China. World Regional Studies, 202332(8): 88-102.
[27]	HAN L, SONG Y. The method of measuring the agglomeration degree of high-tech industries and its influence mechanism: Taking guangdong province as an example. Mathematical Problems in Engineering, 2021.
[28]	CARAGLIU A, NIJKAMP P. Space and knowledge spillovers in european regions: The impact of different forms of proximity on spatial knowledge diffusion. Journal of Economic Geography, 2016, 16(3): 749-774.
[29]	钟韵,赵蓓蕾,李寒.广州市制造业与生产性服务业协同集聚与空间相似性.地理科学,2021, 41(3): 437-445.
	ZHONG Y, ZHAO B, LI H. Co-agglomeration and spatial similarity: Based on the analysis of manufacturing and producer services in Guangzhou, China. Geographical Science, 2021, 41(3): 437-445.

总指数	分类指数	代号	指标
信息化水平	基础设施指数	X1	移动电话普及率/(部/人)
		X2	互联网宽带接入用户数/万户
		X3	信息产业基础设施总投资占固定投资比重/%
	应用指数	X4	人均邮电业务量/万元
	应用指数	X5	人均函件/(件/人)
	知识指数	X6	每万人在校大学生数/万人
	知识指数	X7	每万人专利授权数/万人
	环境与效果指数	X8	信息产业增加值占GDP的比重/%
		X9	信息产业研究与开发经费占GDP的比重/%
		X10	人均GDP/ (元/人)
	信息消费指数	X11	人均电信业务消费量/ (元/人)

总指数	分类指数	代号	指标
信息化水平	基础设施指数	X1	移动电话普及率/(部/人)
		X2	互联网宽带接入用户数/万户
		X3	信息产业基础设施总投资占固定投资比重/%
	应用指数	X4	人均邮电业务量/万元
	应用指数	X5	人均函件/(件/人)
	知识指数	X6	每万人在校大学生数/万人
	知识指数	X7	每万人专利授权数/万人
	环境与效果指数	X8	信息产业增加值占GDP的比重/%
		X9	信息产业研究与开发经费占GDP的比重/%
		X10	人均GDP/ (元/人)
	信息消费指数	X11	人均电信业务消费量/ (元/人)

总指标	分类指标	代号	指标/单位
科技创新能力	科技创新投入	Y1	R&D人员的全时当量/人年
		Y2	R&D活动经费投入/亿元
		Y3	政府财政科技支出占GDP比重/ %
	科技创新环境	Y4	全年固定资产投资/亿元
		Y5	教育经费占财政总支出的比重/%
		Y6	高等学校数/所
	科技创新产出	Y7	高新技术企业/个
		Y8	发明专利授权数/件
		Y9	高新技术企业新产品产值/元

总指标	分类指标	代号	指标/单位
科技创新能力	科技创新投入	Y1	R&D人员的全时当量/人年
		Y2	R&D活动经费投入/亿元
		Y3	政府财政科技支出占GDP比重/ %
	科技创新环境	Y4	全年固定资产投资/亿元
		Y5	教育经费占财政总支出的比重/%
		Y6	高等学校数/所
	科技创新产出	Y7	高新技术企业/个
		Y8	发明专利授权数/件
		Y9	高新技术企业新产品产值/元

年份	Moran’s Ⅰ指数	p 值	z 得分	年份	Moran’s Ⅰ指数	p 值	z 得分
2010	0.415	0.014	3.458	2016	0.455	0.004	3.727
2011	0.431	0.009	3.429	2017	0.473	0.004	3.881
2012	0.449	0.007	3.656	2018	0.469	0.006	3.712
2013	0.472	0.010	3.468	2019	0.457	0.003	3.757
2014	0.448	0.008	3.611	2020	0.436	0.007	3.485
2015	0.440	0.007	3.692