区域科学发展

京津冀协同创新多维测度研究

  • 赵成伟 ,
  • 翟瑞瑞 ,
  • 曹智 ,
  • 张生太
展开
  • (1.新疆大学 经济与管理学院,新疆 乌鲁木齐 830046;2.中国科学技术发展战略研究院,北京100038;3.北京邮电大学 网络教育学院,北京100876;4.中国科学院地理科学与资源研究所 中国科学院区域可持续发展分析与模拟重点实验室,北京 100101;5.北京邮电大学 经济管理学院,北京 100876)
赵成伟(1982—),男,山东济宁人,博士,新疆大学经济与管理学院讲师、硕士生导师,中国科学技术发展战略研究院博士后,研究方向为区域创新战略、京津冀协同创新;翟瑞瑞(1987—),女,山东菏泽人,博士,北京邮电大学网络教育学院讲师,研究方向为创新与国际商务、数字经济与高质量发展;曹智(1989—),男,山东济南人,中国科学院地理科学与资源研究所中国科学院区域可持续发展分析与模拟重点实验室副研究员,研究方向为土地利用与乡村发展、城乡融合发展与乡村振兴;张生太(1962—),男,山西应县人,博士,北京邮电大学经济管理学院教授,研究方向为知识管理与人力资本管理。本文通讯作者:曹智。

收稿日期: 2022-07-06

  修回日期: 2022-09-28

  网络出版日期: 2023-08-29

基金资助

科技部国家高端智库研究联合体重大研究课题项目(ZKLH202104)

The Multi-dimensional Measurement of Beijing-Tianjin-Hebei Collaborative Innovation

  • Zhao Chengwei ,
  • Zhai Ruirui ,
  • Cao Zhi ,
  • Zhang Shengtai
Expand
  • (1.School of Economics and Management, Xinjiang University, Urumqi 830046,China;2.China Academy of Science and Technology Development Strategy,Beijing 100038,China;3.School of Network Education, Beijing University of Posts and Telecommunications,Beijing 100876,China;4. Key Laboratory of Regional Sustainable Development Modeling,Institute of Geographic Sciences and Natural Resources Research,CAS,Beijing 100101,China;5.School of Economics and Management,Beijing University of Posts and Telecommunications,Beijing 100876,China)

Received date: 2022-07-06

  Revised date: 2022-09-28

  Online published: 2023-08-29

摘要

区域协同创新是区域协同发展的高级阶段,是新时代区域协同发展的重要表现形式。基于京津冀3个主体创新资源的细分数据,结合熵值法、熵权法、引力模型和社会网络分析等多种方法,从宏观城市群之间、微观京津冀内部两个维度,测度京津冀协同创新水平、挖掘其空间网络联系,立体呈现京津冀协同创新现状。研究结果发现,对比国内三大世界级城市群,京津冀属于研发推动的源发型科技创新体系;在三地各省域内的43个研究单元间普遍存在创新资源分布不均衡、协同创新水平差距较大现象;区域间高效协同创新网络尚未完全建立。

本文引用格式

赵成伟 , 翟瑞瑞 , 曹智 , 张生太 . 京津冀协同创新多维测度研究[J]. 科技进步与对策, 2023 , 40(16) : 72 -83 . DOI: 10.6049/kjjbydc.2022070121

Abstract

Although the Beijing-Tianjin-Hebei Collaborative Development Plan was issued in 2015, there is still a large gap in the current level of innovation development and the scale of innovation resource allocation in Beijing, Tianjin and Hebei, restricting the coordinated innovation development of the three regions. 92.5% of Beijing's scientific research achievements have been industrialized in the Yangtze River Delta and the Pearl River Delta, which means that the innovation chain and industrial chain of Beijing Tianjin R&D and Hebei incubation transformation have not yet formed. It is difficult for Beijing's scientific and technological achievements to land in Tianjin and Hebei, and it is difficult for the industries in the three regions to coordinate with each other, which has become a prominent problem of Beijing-Tianjin-Hebei coordinated innovation. Understanding the status quo of Beijing-Tianjin-Hebei collaborative innovation and the characteristics of spatial network connection is the prerequisite for promoting collaborative innovation. The present research is inadequate to analyze in detail the level of collaboration between various regions in Beijing and Tianjin and cities in Hebei.#br#The ultimate goal of regional collaborative innovation is to narrow the innovation gap between regions. The most important way is to promote the free flow of innovation elements and innovation collaboration across regions and subjects. The innovation network is the most important spatial manifestation of regional collaborative innovation. This paper attempts to measure the level of Beijing-Tianjin-Hebei collaborative innovation from the macro and micro dimensions with focus on the differences between the collaborative innovation development and the Yangtze River Delta,the Guangdong Hong Kong-Macao Greater Bay Area, the status quo of the collaborative innovation development of 43 sub-units in Beijing-Tianjin-Hebei, and the construction of the Beijing- Tianjin-Hebei innovation network. On the macro level, focusing on the synergy among science, technology and industry, this study makes comparisons with the Yangtze River Delta and the Guangdong Hong Kong-Macao Bay Area, and summarizes the characteristics of Beijing-Tianjin-Hebei collaborative innovation by the entropy method. On the micro level, it analyzes the collaborative innovation in 43 sub regions, mainly using the entropy weight method. Given the collaborative innovation capability of each subdivided region, it further analyzes the construction of the Beijing-Tianjin -Hebei innovation network through network analysis by combining gravity model and social network analysis, and the analysis results are presented visually with ArcGIS software.#br#Compared with the two world-class urban agglomerations of the Yangtze River Delta and the Guangdong-Hong Kong-Macao Greater Bay Area, Beijing -Tianjin-Hebei has a very strong scientific research level and is at the front end of the innovation chain. The front end scientific research level and technology diffusion level of Beijing-Tianjin-Hebei are high, but the connection with the back end industrial chain is not enough, and the industrial development level is poor, which seriously restricts the improvement of the collaborative innovation level of Beijing-Tianjin-Hebei. The innovation and development of each region in Beijing, Tianjin and Hebei are not balanced. From 2014 to 2020, the level of collaborative innovation in Beijing-Tianjin-Hebei has been improved to a large extent, but the synergy between the main bodies is still at a low level, and the polarization has been accelerating. An efficient and collaborative innovation network has not been formed among Beijing, Tianjin and Hebei. Although the total amount and network density of the actual relationship of Beijing-Tianjin-Hebei collaborative innovation are growing rapidly, they are still at a low level. The network connections are mostly generated in Beijing, Tianjin and between Beijing and Tianjin, showing the spatial characteristics of Beijing and Tianjin as two poles, and gradually expanding to the surrounding areas. In the future, efforts should be focused on promoting the integration of context-driven innovation industries, improving Beijing's innovation radiation driving capacity, and building an innovation network with efficient collaboration between Beijing, Tianjin and Hebei.#br#

参考文献

[1] 田学斌,卢燕.新发展格局下京津冀产业链创新链深度融合推动河北产业高质量发展——2021京津冀协同发展参事研讨会综述[J].中共石家庄市委党校学报,2022,24(1):39-44.
[2] 张贵,温科.协同创新、区域一体化与创新绩效——对中国三大区域数据的比较研究[J].科技进步与对策,2017,34(5):35-44.
[3] COOKE P. Introduction: origins of the conception [C]. London:UCL Press, 1998:2-25.
[4] LEYDESDORFF L,FRITSCH M. Measuring the knowledge base of regional innovation systems in Germany in terms of a triple helix dynamics[J]. Research Policy,2006,35(10):1538-1553.
[5] 鲁继通.京津冀区域协同创新能力测度与评价——基于复合系统协同度模型[J].科技管理研究,2015,35(24):165-170,176.
[6] 王志宝,孙铁山,李国平.区域协同创新研究进展与展望[J].软科学,2013,27(1):1-4,9.
[7] 孙瑜康,李国平.京津冀协同创新水平评价及提升对策研究[J].地理科学进展,2017,36(1):78-86.
[8] 祝尔娟,何皛彦.京津冀协同创新水平测度与提升路径研究[J].河北学刊,2020,40(2):137-144.
[9] FREEMAN C. Networks of innovators:a synthesis of research issues[J].Research Policy,1991,20(5):499-514.
[10] LUNDVALL B . Scope, style, and theme of research on knowledge and learning societies[J]. Journal of the Knowledge Economy,2010,1(1): 18-23.
[11] 盖文启. 创新网络——区域经济发展新思维[M]. 北京:北京大学出版社,2002.
[12] MEIJERS E.Polycentric urban regions and the quest for synergy:is a network of cities more than the sum of the parts[J]. Urban Studies,2005,42(4):765-781.
[13] NIETO M J, SANTAMARIA L. The importance of diverse collaborative networks for the novelty of product innovation[J]. Technovation, 2007, 27(6): 367-377.
[14] 上海科学所译.区域创新体系概论[M].上海:上海交通大学出版社,2000.
[15] BOSCHMA R A. Proximity and innovation: a critical assessment[J]. Regional Studies,2005,39(1):61-74.
[16] 解学梅,刘丝雨.都市圈中观视角下的协同创新演化研究综述[J].经济地理,2013,33(2):68-75.
[17] 陆大道.京津冀城市群功能定位及协同发展[J].地理科学进展,2015,34(3):265-270.
[18] 刘冬梅,赵成伟.成渝地区建设全国科创中心的路径选择[J].开放导报,2021,30(3):72-79.
[19] 李晓琳,李星坛.高水平推动京津冀协同创新体系建设[J].宏观经济管理,2022,38(1):60-67.
[20] 胡悦,马静,李雪燕.京津冀城市群创新网络结构演化及驱动机制研究[J].科技进步与对策,2020,37(13):37-44.
[21] 毕娟.京津冀科技协同创新影响因素研究[J].科技进步与对策,2016,33(8):49-54.
[22] 杜勇宏,王汝芳.基于研发枢纽—网络的京津冀协同创新效果分析[J].中国流通经济,2021,35(5):85-97.
[23] 国子健,钟睿,朱凯.协同创新视角下的区域创新走廊——构建逻辑与要素配置[J].城市发展研究,2020,27(2):8-15.
[24] 赵成伟,孙启明.京津冀人口与第三产业分布匹配研究——兼论影响首都人口疏解效果的因素[J].求是学刊,2018,45(6):53-60.
[25] REILLY W J. Methods for the study of retail relationships[M]. Austin:University of Texas Press,1929.
[26] 李琳,牛婷玉.基于SNA的区域创新产出空间关联网络结构演变[J].经济地理,2017,37(9):19-25,61.
[27] COOKE P. Regional innovation system: general findings and some new evidence frombiotechnology clusters[J].Journal of Technology Transfer,1992,27:133-145.
[28] 尹西明,苏雅欣,陈劲,等.场景驱动的创新:内涵特征、理论逻辑与实践进路[J].科技进步与对策,2022,39(15):1-10.
[29] 赵成伟,刘冬梅,王砚羽.产业疏解对京津冀协同发展的作用路径及效果研究[J].经济与管理评论,2022,39(3):53-66.
文章导航

/