建设全球创新策源国家的路径、模式及启示——基于跨国面板数据的定性比较分析

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Abstract Drawing on innovation ecosystem theory and complex emergence,a configurational model of the innovation origination ecosystem is proposed.Using fuzzy-set Qualitative Comparative Analysis(fsQCA)and panel data from 120 countries and regions(2011—2021),this research identifies effective combinations of conditions that enhance innovation origination capacity over time.The Kruskal-Wallis rank sum test further reveals spatial disparities in these configurations.Results indicate that no single factor is necessary for high innovation origination,but the subsystems of digital environment,science and technology,talent,and industry demonstrate significant temporal effects.Four configurational pathways to high innovation capacity are identified,which include the strong ecological balance model,primitive ecological model,and weak ecological strong government model.Temporally,the consistency of these pathways declined in 2016 and 2020,likely due to major global events such as Brexit,U.S.elections,and the COVID-19 pandemic.Spatially,global innovation origination has evolved into a“core-semi-periphery-periphery”structure across continents.Based on these insights,policy recommendations are provided to support China's emergence as a global innovation leader.

Key words： Innovation-driven country Innovation ecosystem Configurational effect Dynamic fsQCA

Received: 10 May 2024

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F062.3

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	Pan Junhao
	Yang Yifan

Cite this article:

Pan Junhao,Yang Yifan. Pathways, Models and Insights for Building a Global Innovation-driven Country——A Qualitative Comparative Analysis Based on Cross-National Panel Data[J]. , 2025, 6(5): 128-138.

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http://www.zgkjlt.org.cn/EN/ OR http://www.zgkjlt.org.cn/EN/Y2025/V6/I5/128

[1] 敦帅,陈强.创新策源能力:概念源起、理论框架与趋势展望[J].科学管理研究,2022,40(4):33-41.
[2] 李滋阳,石宏伟,罗建强.高校创新策源能力的概念、维度与提升策略:研究中的辨析与讨论[J].中国高校科技,2022(9):67-75.
[3] 衣春波,赵文华,邓璐芗,等.基于专利信息的技术创新策源评价指标体系构建与应用[J].情报杂志,2021,40(2):55-62.
[4] 朱梦菲,陈守明,邵悦心.基于AHP-TOPSIS和SOM聚类的区域创新策源能力评价[J].科研管理,2020,41(2):40-50.
[5] 程翔,简苏尔·居来提,杨宜.中国科技创新策源能力综合评价及时空演化特征研究[J].经济与管理研究,2023,44(10):90-108.
[6] 谢婼青.科技创新策源能力:影响因素与提升路径[J].上海经济研究,2023(2):64-77.
[7] 胡斌,吕建林,杨坤.人工智能企业创新策源能力影响因素分析[J].西安财经大学学报,2020,33(5):27-34.
[8] 刘琦,罗卫国,罗萧.人才网络视角下粤港澳大湾区创新策源能力影响机理研究[J].企业经济,2022,41(12):98-106.
[9] 敦帅,陈强,丁玉.基于贝叶斯网络的创新策源能力影响机制研究[J].科学学研究,2021,39(10):1897-1907.
[10] 蒙克,魏必.反思QCA方法的“时间盲区”:为公共管理研究找回“时间”[J].中国行政管理,2023(1):96-104.
[11] 埃里克·冯·希普尔.创新的源泉:追循创新公司的足迹[M].上海:东方出版中心,2022.
[12] 敦帅,陈强,马永智.创新策源能力评价研究:指标构建、区域比较与提升举措[J].科学管理研究,2021,39(1):83-89.
[13] 傅翠晓,许海娟.区域新能源汽车产业创新策源能力分析:以上海为例[J].创新科技,2021,21(10):82-92.
[14] 曹萍,赵瑞雪,尤宇,等.创新策源能力如何影响区域创新绩效:基于30个省份的QCA分析[J].科技管理研究,2022,42(13):1-9.
[15] 杨一帆,潘君豪.全球科技创新中心构型规律与演化机制研究[J].科技进步与对策,2024,41(20):98-108.
[16] 吴江.畅通教育科技人才良性循环[J].中国人才,2024(5):20-22.
[17] SILVA L E N,GOMES L A V,FARIA A M,et al.Innovation processes in ecosystem settings:An integrative framework and future directions[J].Technovation,2024,132:102984.
[18] 杨一帆,潘君豪.地方政府参与科技创新推动产业结构转型升级的实证分析[J].中国科技论坛,2024(3):70-82.
[19] TING X,MAKHIJA M,KARIM S.A Knowledge recombination perspective of innovation:Review and new research directions[J].Journal of Management,2021,48(6):1724-1777.
[20] PERTUZE J A,REYES T,VASSOLO R S,et al.Political uncertainty and innovation:The relative effects of national leaders' education levels and regime systems on firm-level patent applications[J].Research Policy,2019,48(9):103808.
[21] NADEEM M A,YOUNIS A,YI X.Innovation and sustainable development:Does aid and political instability impede innovation[J].Sage Open,2020(4):21582440209.
[22] ERICK L,PC P.Smart territories and IoT adoption by local authorities:A question of trust,efficiency,and relationship with the citizen-user-taxpayer.[J].Technological Forecasting and Social Change,2022,174:121195.
[23] ZHENG C,WANG Z,PAN S,et al.Does financial structure still matter for technological innovation when financial technology and financial regulation develop[J].Technological Forecasting and Social Change,2023,194:122747.
[24] SEREDA V.The role of law in promoting the efficiency of the modern economy(theoretical approach)[J].Science and Innovation,2021,17(4):62-71.
[25] ROBERTO G C,MIGUEL A A.Ageneral approach to panel data set-theoretic research[J].International Journal of Management & Decision Making,2016,1(1):11-41.
[26] 张放.影响地方政府信息公开的因素:基于省域面板数据的动态QCA分析[J].情报杂志,2023,42(1):133-141,207.
[27] BRA G R.Pillars of the global innovation index by income level of economies:Longitudinal data(2011—2022)for researchers' use[J].Data in Brief,2023,46:108818.
[28] 王建华,赵柯,谢清泉.创新策源与城市战略性新兴产业技术路径发展[J].科学学研究,2024,42(11):2454-2464.
[29] 黄斌,云如先.教育发展何以强国:基于1960—2020年认知技能国际可比数据的实证分析[J].教育研究,2023,44(10):125-136.
[30] FAN P S.Export technological sophistication of China:Measurement and impact factor[J].Discrete Dynamics in Nature and Society,2021(1):3561495.
[31] ZHOU Q,CHENG C G,FANG Z,et al.How does the development of the digital economy affect innovation output? Exploring mechanisms from the perspective of regional innovation systems[J].Structural Change and Economic Dynamics,2024,70:1-17.
[32] RAJAN R,ZINGALES L.Financial dependence and growth[J].American Economic Review,1998,88(3):559-586.
[33] SOFIK H.Worldwide governance indicators:Cross country data set 2012—2022[J].Data in Brief,2023,51:109814.
[34] GUEDES M J,GONÇALVES VC,SOARES N,et al.UK evidence for the determinants of R&D intensity from a panel fsQCA[J].Journal of Business Research,2016,69(11):5431-5436.
[35] 杜运周,贾良定.组态视角与定性比较分析(QCA):管理学研究的一条新道路[J].管理世界,2017(6):155-167.
[36] 王珂,李侠.影响国家创新能力的社会基础条件[J].中国科技论坛,2022(9):18-24.
[37] SCHNEIDER C Q,WAGEMANN C.Set-theoretic Methods for the social sciences:A guide to qualitative comparative analysis[M].Cambridge:Cambridge University Press,2012.