IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i5p597-d796915.html
   My bibliography  Save this article

Spatio-Temporal Evolution of Urban Innovation Networks: A Case Study of the Urban Agglomeration in the Middle Reaches of the Yangtze River, China

Author

Listed:
  • Li Liu

    (School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China
    School of Information Engineering, Jiangxi University of Technology, Nanchang 330098, China
    These authors contributed equally to this work.)

  • Jin Luo

    (School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China
    Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China
    These authors contributed equally to this work.)

  • Xin Xiao

    (School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China
    Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China)

  • Bisong Hu

    (School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China
    Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China)

  • Shuhua Qi

    (School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China
    Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China)

  • Hui Lin

    (School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China
    Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China)

  • Xiaofang Zu

    (School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China
    Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China)

Abstract

Understanding the evolutionary characteristics of innovation network structure can improve urban innovation and regional construction. Urban innovative development is affected by various factors, which can be analyzed via models of innovation networks. We establish a multi-criteria evaluation system of innovation capability and use an improved gravity model to construct an innovation network for 2015–2018, employing social network methods to analyze structural characteristics and spatial patterns. Results show that: (1) The innovation of cities in the urban agglomeration in the middle reaches of the Yangtze River has gradually increased, with an accompanying increase in the complexity of innovation networks. The cities of Wuhan, Changsha, and Nanchang are located at the absolute core of this network, which exhibits a Matthew effect, and has a triangle integration mode of growth. (2) The attraction of innovative resources and the promotion of individual innovation are increasing every year within the cities. The aggregation pattern of innovation shows a multi-core state in the urban agglomeration in the middle reaches of the Yangtze River, but the innovation radiation pattern has changed from a single center to a double center. (3) Multiple spatial innovation axes are seen in the network, with a location and direction consistent with the urban agglomeration’s development axis in the Yangtze River’s middle reaches and a triangle integration growth mode. Policy implications are proposed for regional innovation and development, and our results can provide future policy guidance and direction for governmental entities and other stakeholders.

Suggested Citation

  • Li Liu & Jin Luo & Xin Xiao & Bisong Hu & Shuhua Qi & Hui Lin & Xiaofang Zu, 2022. "Spatio-Temporal Evolution of Urban Innovation Networks: A Case Study of the Urban Agglomeration in the Middle Reaches of the Yangtze River, China," Land, MDPI, vol. 11(5), pages 1-21, April.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:5:p:597-:d:796915
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/5/597/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/11/5/597/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fei Fan & Shangze Dai & Keke Zhang & Haiqian Ke, 2021. "Innovation agglomeration and urban hierarchy: evidence from Chinese cities," Applied Economics, Taylor & Francis Journals, vol. 53(54), pages 6300-6318, November.
    2. Konstantin Kunze, 2016. "Empirical analysis of innovation and trade in Europe: a gravity model approach," International Journal of Trade and Global Markets, Inderscience Enterprises Ltd, vol. 9(3), pages 197-211.
    3. Yu Fu & Agus Supriyadi & Tao Wang & Luwei Wang & Giuseppe T. Cirella, 2020. "Effects of Regional Innovation Capability on the Green Technology Efficiency of China’s Manufacturing Industry: Evidence from Listed Companies," Energies, MDPI, vol. 13(20), pages 1-22, October.
    4. Chen, Yang & Li, Weiwei & Yi, Pingtao, 2020. "Evaluation of city innovation capability using the TOPSIS-based order relation method: The case of Liaoning province, China," Technology in Society, Elsevier, vol. 63(C).
    5. Xu Wang & Hong Fang & Fang Zhang & Siran Fang, 2018. "The Spatial Analysis of Regional Innovation Performance and Industry-University-Research Institution Collaborative Innovation—An Empirical Study of Chinese Provincial Data," Sustainability, MDPI, vol. 10(4), pages 1-16, April.
    6. Freeman, C., 1991. "Networks of innovators: A synthesis of research issues," Research Policy, Elsevier, vol. 20(5), pages 499-514, October.
    7. Mingxing Li & Mengjuan Zhang & Fredrick Oteng Agyeman & Hira Salah ud din Khan & Isabella Torcicollo, 2021. "Research on the Influence of Industry-University-Research Cooperation Innovation Network Characteristics on Subject Innovation Performance," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-13, August.
    8. Wang, Jiating & Cai, Siyuan, 2020. "The construction of high-speed railway and urban innovation capacity: Based on the perspective of knowledge Spillover," China Economic Review, Elsevier, vol. 63(C).
    9. Fang Zhou & Bo Zhang & Yi Su, 2021. "Detecting and Visualizing the Communities of Innovation in Beijing-Tianjin-Hebei Urban Agglomeration Based on the Patent Cooperation Network," Complexity, Hindawi, vol. 2021, pages 1-14, January.
    10. Miao, Chenglin & Fang, Debin & Sun, Liyan & Luo, Qiaoling, 2017. "Natural resources utilization efficiency under the influence of green technological innovation," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 153-161.
    11. Mario A. Maggioni & Mario Nosvelli & Teodora Erika Uberti, 2007. "Space versus networks in the geography of innovation: A European analysis," Papers in Regional Science, Wiley Blackwell, vol. 86(3), pages 471-493, August.
    12. Picci, Lucio, 2010. "The internationalization of inventive activity: A gravity model using patent data," Research Policy, Elsevier, vol. 39(8), pages 1070-1081, October.
    13. Francesco Capone & Luciana Lazzeretti & Niccolò Innocenti, 2021. "Innovation and diversity: the role of knowledge networks in the inventive capacity of cities," Small Business Economics, Springer, vol. 56(2), pages 773-788, February.
    14. Ningning Fu & M. De Aguiar, 2021. "Innovation Efficiency and the Spatial Correlation Network Characteristics of Intelligent-Manufacturing Enterprises," Complexity, Hindawi, vol. 2021, pages 1-15, November.
    15. Weidong Zhu & Zilin Yue & Naiying He & Kuifeng Luan & Li Ye & Chuyi Qian, 2022. "Analysis of China’s Urban Innovation Connection Network Evolution: A Case Study of Henan Province," Sustainability, MDPI, vol. 14(3), pages 1-19, January.
    16. Xiaohua Wang & Tianyu Wan & Qing Yang & Mengli Zhang & Yingnan Sun, 2021. "Research on Innovation Non-Equilibrium of Chinese Urban Agglomeration Based on SOM Neural Network," Sustainability, MDPI, vol. 13(17), pages 1-21, August.
    17. Ma, Jian & Fan, Zhi-Ping & Huang, Li-Hua, 1999. "A subjective and objective integrated approach to determine attribute weights," European Journal of Operational Research, Elsevier, vol. 112(2), pages 397-404, January.
    18. Leoncini, R. & Maggioni, M. A. & Montresor, S., 1996. "Intersectoral innovation flows and national technological systems: network analysis for comparing Italy and Germany," Research Policy, Elsevier, vol. 25(3), pages 415-430, May.
    19. Chengliang Liu & Caicheng Niu & Ji Han, 2019. "Spatial Dynamics of Intercity Technology Transfer Networks in China’s Three Urban Agglomerations: A Patent Transaction Perspective," Sustainability, MDPI, vol. 11(6), pages 1-24, March.
    20. Lachang Lyu & Weiping Wu & Haipeng Hu & Ru Huang, 2019. "An evolving regional innovation network: collaboration among industry, university, and research institution in China’s first technology hub," The Journal of Technology Transfer, Springer, vol. 44(3), pages 659-680, June.
    21. Yuxin Zhu & Dazuo Tian & Feng Yan, 2020. "Effectiveness of Entropy Weight Method in Decision-Making," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-5, March.
    22. Zhang, Lin, 2017. "The knowledge spillover effects of FDI on the productivity and efficiency of research activities in China," China Economic Review, Elsevier, vol. 42(C), pages 1-14.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gang Li & Qifeng Yuan & Xiao Liu & Wei Zhan & Shuya Yang, 2025. "Measuring Intra-Urban Innovation Space from the Unit-Network Perspective: A Case Study of Guangzhou," Land, MDPI, vol. 14(3), pages 1-22, February.
    2. Bowen Xiang & Rushuang Chen & Gaofeng Xu, 2022. "Uncovering Network Heterogeneity of China’s Three Major Urban Agglomerations from Hybrid Space Perspective-Based on TikTok Check-In Records," Land, MDPI, vol. 12(1), pages 1-21, December.
    3. Weihui Peng & Zehuan Hu & Jie Li & Chenggang Li, 2025. "Urban Agglomeration Technology Innovation Networks, Spatial Spillover, and Agricultural Ecological Efficiency: Evidence from the Urban Agglomeration in the Middle Reaches of the Yangtze River in China," Sustainability, MDPI, vol. 17(11), pages 1-27, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mario A. Maggioni & Emanuela Marrocu & Teodora Erika Uberti & Stefano Usai, 2019. "Of Trees and Monkeys. The evolution of technological specialization of European regions," DISEIS - Quaderni del Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo dis1904, Università Cattolica del Sacro Cuore, Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo (DISEIS).
    2. Laurent R. Bergé, 2017. "Network proximity in the geography of research collaboration," Papers in Regional Science, Wiley Blackwell, vol. 96(4), pages 785-815, November.
    3. Stefano Usai & Emanuela Marrocu & Raffaele Paci, 2017. "Networks, Proximities, and Interfirm Knowledge Exchanges," International Regional Science Review, , vol. 40(4), pages 377-404, July.
    4. Montobbio, Fabio & Sterzi, Valerio, 2013. "The Globalization of Technology in Emerging Markets: A Gravity Model on the Determinants of International Patent Collaborations," World Development, Elsevier, vol. 44(C), pages 281-299.
    5. Li, Jing & Yu, Qian & Ma, Ding, 2024. "Does China's high-speed rail network promote inter-city technology transfer? ——A multilevel network analysis based on the electronic information industry," Transport Policy, Elsevier, vol. 145(C), pages 11-24.
    6. Sari Pekkala Kerr & William R. Kerr, 2018. "Global Collaborative Patents," Economic Journal, Royal Economic Society, vol. 128(612), pages 235-272, July.
    7. repec:zbw:bofrdp:2017_003 is not listed on IDEAS
    8. Mila Davids & Koen Frenken, 2015. "Proximity, knowledge base and the innovation process: The case of Unilever’s Becel diet margarine," Papers in Evolutionary Economic Geography (PEEG) 1504, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Feb 2015.
    9. Umut Yilmaz Cetinkaya & Erkan Erdil, 2016. "Cohesion and Competition of Europe: Innovation Policy from the Perspective of Networks and Entropy," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 10(4), pages 7-24.
    10. Morescalchi, Andrea & Pammolli, Fabio & Penner, Orion & Petersen, Alexander M. & Riccaboni, Massimo, 2015. "The evolution of networks of innovators within and across borders: Evidence from patent data," Research Policy, Elsevier, vol. 44(3), pages 651-668.
    11. Sari Pekkala Kerr & William R. Kerr, 2018. "Global Collaborative Patents," Economic Journal, Royal Economic Society, vol. 128(612), pages 235-272, July.
    12. Manuel Acosta & Daniel Coronado & Jennifer Medina, 2024. "Effects of co-patenting across national boundaries on patent quality. An exploration in pharmaceuticals," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 33(2), pages 248-281, February.
    13. Zhijun Feng & Hechang Cai & Wen Zhou, 2020. "Structural Characteristics and Spatial Patterns of the Technology Transfer Network in the Guangdong–Hong Kong–Macao Greater Bay Area," Sustainability, MDPI, vol. 12(6), pages 1-28, March.
    14. Antonio Zinilli & Yujie Gao & Thomas Scherngell, 2024. "Structural Dynamics of Inter-city Innovation Networks in China: A Perspective From TERGM," Networks and Spatial Economics, Springer, vol. 24(3), pages 707-741, September.
    15. Mario Maggioni & Teodora Uberti, 2011. "Networks and geography in the economics of knowledge flows," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(5), pages 1031-1051, August.
    16. Haisen Wang & Gangqiang Yang & Jiaying Qin, 2020. "City Centrality, Migrants and Green Inovation Efficiency: Evidence from 106 Cities in the Yangtze River Economic Belt of China," IJERPH, MDPI, vol. 17(2), pages 1-21, January.
    17. Kai Zhu & Zhiling Gu & Jingang Li, 2023. "Analysis of the China’s Interprovincial Innovation Connection Network Based on Modified Gravity Model," Land, MDPI, vol. 12(5), pages 1-19, May.
    18. Jie Zhang & Bindong Sun & Chuanyang Wang, 2024. "Interplay between Network Position and Knowledge Production of Cities in China Based on Patent Measurement," Land, MDPI, vol. 13(10), pages 1-17, October.
    19. Ying Jiang & Jin Xu & Guofei Wang, 2024. "Trade in green patents: How do green technologies flow in China?," The Journal of Technology Transfer, Springer, vol. 49(3), pages 823-856, June.
    20. Viktor Květoň & Josef Novotný & Jiří Blažek & David Marek, 2022. "The role of geographic and cognitive proximity in knowledge networks: The case of joint R&D projects," Papers in Regional Science, Wiley Blackwell, vol. 101(2), pages 351-372, April.
    21. Li, Junwei & Liu, Wenxiao & Du, Lei & Xiao, Jin, 2024. "High-tech industry agglomeration and regional green development: An analysis of spatial Durbin model," Technological Forecasting and Social Change, Elsevier, vol. 205(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:11:y:2022:i:5:p:597-:d:796915. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.