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Informatization Diffusion,Industrial Cluster and Technological Innovation Performance based on Regional Panel Data from 2005 to 2018 |
Yang Changzheng |
(School of Journalism & New Media, Xi'an Jiaotong University, Xi'an 710049,China) |
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Abstract In recent years, China has been stepping up efforts to promote the construction of the national economic circle and the technology innovation-driven strategy to create emerging industrial economic zones and technological innovation platforms of our country.Industrial cluster is a phenomenon that competitive industries, professional suppliers, service providers, manufacturers and related industrial organizations gather in certain fields or regions.Industry clustering puts forward new requirements on the level of technological innovation, thereby driving the continuous upgrading of regional or national technological innovation.Meanwhile, in recent years, informatization construction of our country has been rapidly carried forward.The rapid information diffusion brought by informatization construction has promoted the sharing and exchange of international and domestic knowledge, and has accelerated the flow of information, the diffusion of knowledge, and the interactive integration of knowledge in multiple fields, and has also promoted national or regional technological innovation so that informatization construction, industrial cluster and technological innovation have become important strategies for national development.Therefore, exploring the relationship between information diffusion, industrial cluster and technological innovation performance is greatly significant to the development of national technology and economy. In order to seek for the main influencing factors of economic development and technological innovation in different regions, the paper explores the relationship between informatization level, industrial cluster, and technological innovation performance.The paper uses China′s regional panel data from 2005 to 2018, and uses VAR model, panel data model, and state space model to analyze the relationship between informationization level, industrial cluster, and technological innovation performance.The paper gathered data come from the China Statistical Yearbook, Qingbo Database, China Science and Technology Statistical Yearbook, China Internet Development Report, Wind database, Guotaian CSMAR database, and selected ten medium-sized industries from 2005 to 2018 and relevant indicators for the research object. The research finds that (1) The change of the marginal influence of industrial agglomeration on technological innovation performance is an inverted U-shaped parabola, and the marginal influence of informatization level on technological innovation performance is increasing.The marginal influence of informatization level on industrial agglomeration shows a linear growth trend, while the change in the marginal influence of technological innovation performance on industrial agglomeration is an inverted U-shaped parabola.(2) The order of the effect of informationization level and industrial agglomeration on technological innovation performance is Eastern, Central, and Western regions, and the impact of informationization levels on technological innovation performance in eastern and central regions is greater than the impact of industrial agglomeration.The impact of industrial agglomeration in the western region on the performance of technological innovation is greater than the impact of informatization level.(3) The order of the effects of informatization level and technological innovation performance on industrial agglomeration is eastern, central, and western regions, and the impact of technological innovation performance on industrial agglomeration in the eastern region is greater than the impact of informationization level.The impact of informatization in the western region on industrial agglomeration is greater than the impact of technological innovation performance. This paper put information diffusion, industrial cluster and technological innovation in the same theoretical framework as a systemic structure for model construction, analyzed the impulse response and marginal influence of endogenous variables, and analyzed the difference of the influence of various variables in different regions.The research findings had great significance for technological innovation upgrading and industrial development.In theory, it can help to construct a long-term balanced and effective theoretical model of technological innovation and industrial development which agrees with the reality of our country.In practice, the improvement of information diffusion can be used to promote industrial upgrading and drive technological innovation.Technological innovation and industrial cluster can also promote the improvement of regional or national information diffusion.Based on this, we can find the main influencing factors of economic development and technological innovation in specific regions, so as to formulate driving strategies and specific measures that conform to the policy of specific regional economic development and technological innovation.
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Received: 01 February 2021
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[1] BHAWSAR P,CHATTOPADHYAY U.Evaluation of industry cluster competitiveness:a quantitative approach[J].Benchmarking an International Journal,2018,25(7):2318-2343.[2] 刘利永,李道亮.我国农业信息化水平指数测度研究[J].科技情报开发与经济,2013,23(11):98-100. [3] ANTOKHINA Y,GUZIKOVA L,KOLESNIKOV A.Informatization,R&D and innovation in regions of Russia:together or apart[J].Advanced Science Letters,2018,24(9):6293-6295. [4] MUSIOLIK J, MARKARD J, HEKKERT M.Networks and network resources in technological innovation systems:towards a conceptual framework for system building[J].Technological Forecasting and Social Change,2012,79(6):1032-1048. [5] 储伊力,储节旺.信息化与技术创新的关系研究:基于东中西三大区域的比较分析[J].情报杂志,2016,35(7):61-65,30. [6] 卓乘风,邓峰,白洋,等.丝绸之路经济带区域创新与区域信息化的耦合协调性分析[J].科技管理研究,2017,37(4):192-199.[7] 张骞,吴晓飞.信息化对区域创新能力的影响——马太效应存在吗[J].科学决策,2018, 25(7):1-21. [8] 惠宁,刘鑫鑫.信息化对中国工业部门技术创新效率的空间效应[J].西北大学学报(哲学社会科学版),2017,47(6):94-103. [9] ZHU L,LI G X.Information technology,government management and innovation mechanism:a case study of China's administration[C]//2018 Chinese Control And Decision Conference (CCDC).June 9-11,2018,Shenyang,China.IEEE,2018:5547-5552. [10] 李玲,陶厚永.技术信息获取、政府科技资助影响企业创新能力吗[J].科技进步与对策,2020,37(2):34-41.[11] 李玲,陶厚永.技术信息获取、政府科技资助影响企业创新能力吗[J].科技进步与对策,2020,37(2):34-41.[12] ZHANG L P,JIANG W,TANG Z W.Study on the promotion effect of informationization on entrepreneurship:an empirical evidence from China[J].Journal of Global Entrepreneurship Research,2019,9(1):1-22. [13] CHU Y Z,CHI M M,WANG W J,et al.The impact of information technology capabilities of manufacturing enterprises on innovation performance:evidences from SEM and fsQCA[J].Sustainability,2019,11(21):5946. [14] TANG G H,TANG W L.The impact of the Internet on the innovation effect of medical and pharmaceutical products manufacturing[C]//International Conference on Application of Intelligent Systems in Multi-modal Information Analytics. Springer, Cham, 2019: 552-559. [15] YAM R C M,LO W,TANG E P Y,et al.Analysis of sources of innovation,technological innovation capabilities,and performance:an empirical study of Hong Kong manufacturing industries[J].Research Policy,2011,40(3):391-402. [16] MALECKI E J.Technological innovation and paths to regional economic growth[M]//Growth Policy in The Age of High Technology.Routledge,2018:97-126.[17] 杜传忠,金华旺,金文翰.新一轮产业革命背景下突破性技术创新与我国产业转型升级[J].科技进步与对策,2019,36(24):63-69. [18] 张涵.多维邻近下高技术产业集聚的空间溢出与区域创新研究[J].经济体制改革,2019,37(6):68-74. [19] KOGAN L,PAPANIKOLAOU D,SERU A,et al.Technological innovation,resource allocation,and growth[J].The Quarterly Journal of Economics,2017,132(2):665-712. [20] LAI Y L,HSU M S,LIN F J,et al.The effects of industry cluster knowledge management on innovation performance[J].Journal of Business Research,2014,67(5):734-739. [21] DELGADO M,PORTER M E,STERN S.Clusters and entrepreneurship[J].Journal of Economic Geography,2010,10(4):495-518. [22] 杨武,杨大飞,雷家骕.R&D投入对技术创新绩效的影响研究[J].科学学研究,2019,37(9):1712-1720. [23] 冯云廷,计利群.技术创新与城市经济增长波动:基于我国15个副省级城市面板数据的实证研究[J].工业技术经济,2020,39(1):41-49.[24] 姜爱林.论信息扩散的八种测算方法[J].国家图书馆学刊,2002(4):48-52. [25] ELLISON G,GLAESER E L,KERR W R.What causes industry agglomeration? evidence from coagglomeration patterns[J].American Economic Review,2010,100(3):1195-1213. [26] 林立杰,修莹,钟全雄,等.现代农业信息化指数测评体系构建[J].情报科学,2015,33(6):63-70. [27] 黄中伟,王宇露.关于经济行为的社会嵌入理论研究述评[J].外国经济与管理,2007,29(12):1-8. [28] 陈华珊,王呈伟.茧房效应与新闻消费行为模式:以腾讯新闻客户端用户评论数据为例[J].社会科学,2019,41(11):73-87. |
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