IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i2p740-d1570056.html
   My bibliography  Save this article

The Formation of Knowledge Flow Networks in the Yangtze River Delta, China: Knowledge Implicitness and Proximity Effect

Author

Listed:
  • Pengcheng Zhu

    (Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 211135, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Jianglong Chen

    (Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 211135, China)

  • Feng Yuan

    (Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 211135, China)

  • Weichen Liu

    (Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 211135, China)

Abstract

Knowledge flow as the key to facilitating new technology production and diffusing innovation is crucial for achieving sustainable development. However, previous studies pay less attention to the type of knowledge in knowledge flow network construction, possibly leading to the deviation of conclusions. To fully show the panorama of knowledge flow, this study distinguishes between explicit and tacit knowledge based on the transfer of patent rights data and talent flow data, describes the spatial characteristics of flow networks and uses a multiple regression quadratic assignment procedure model to analyze the proximity mechanism of network formation in the Yangtze River Delta. We find that knowledge flow networks in the Yangtze River Delta cover a wide range but are extremely uneven, mainly concentrated along the Yangtze River and around Hangzhou Bay. In addition, the spatial structures of different types of knowledge flow networks vary. Different dimensions of proximity act in relatively consistent directions for both types of knowledge flows, with geographical and organizational proximity found to exert positive effects on facilitating knowledge flows while cognitive proximity has a negative impact. There is also a substitution effect between geographical proximity and organizational proximity, and a complementary effect with cognitive proximity. These findings provide significant implications for optimizing knowledge flow networks and promoting sustainable development.

Suggested Citation

  • Pengcheng Zhu & Jianglong Chen & Feng Yuan & Weichen Liu, 2025. "The Formation of Knowledge Flow Networks in the Yangtze River Delta, China: Knowledge Implicitness and Proximity Effect," Sustainability, MDPI, vol. 17(2), pages 1-21, January.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:2:p:740-:d:1570056
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/2/740/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/2/740/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Crescenzi, Riccardo & Nathan, Max & Rodríguez-Pose, Andrés, 2016. "Do inventors talk to strangers? On proximity and collaborative knowledge creation," Research Policy, Elsevier, vol. 45(1), pages 177-194.
    2. Jaffe, Adam B, 1986. "Technological Opportunity and Spillovers of R&D: Evidence from Firms' Patents, Profits, and Market Value," American Economic Review, American Economic Association, vol. 76(5), pages 984-1001, December.
    3. David J. Teece, 2008. "Technology Transfer By Multinational Firms: The Resource Cost Of Transferring Technological Know-How," World Scientific Book Chapters, in: The Transfer And Licensing Of Know-How And Intellectual Property Understanding the Multinational Enterprise in the Modern World, chapter 1, pages 1-22, World Scientific Publishing Co. Pte. Ltd..
    4. Kiiski, Sampsa & Pohjola, Matti, 2002. "Cross-country diffusion of the Internet," Information Economics and Policy, Elsevier, vol. 14(2), pages 297-310, June.
    5. Leon Oerlemans & Marius Meeus, 2005. "Do Organizational and Spatial Proximity Impact on Firm Performance?," Regional Studies, Taylor & Francis Journals, vol. 39(1), pages 89-104.
    6. Mancusi, Maria Luisa, 2008. "International spillovers and absorptive capacity: A cross-country cross-sector analysis based on patents and citations," Journal of International Economics, Elsevier, vol. 76(2), pages 155-165, December.
    7. Ron Boschma, 2005. "Proximity and Innovation: A Critical Assessment," Regional Studies, Taylor & Francis Journals, vol. 39(1), pages 61-74.
    8. Carmen Contreras Romero, 2018. "Personal and business networks within Chilean biotech," Industry and Innovation, Taylor & Francis Journals, vol. 25(9), pages 841-873, October.
    9. Todtling, Franz & Trippl, Michaela, 2005. "One size fits all?: Towards a differentiated regional innovation policy approach," Research Policy, Elsevier, vol. 34(8), pages 1203-1219, October.
    10. David Dekker & David Krackhardt & Tom Snijders, 2007. "Sensitivity of MRQAP Tests to Collinearity and Autocorrelation Conditions," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 563-581, December.
    11. Linda Argote & Bill McEvily & Ray Reagans, 2003. "Managing Knowledge in Organizations: An Integrative Framework and Review of Emerging Themes," Management Science, INFORMS, vol. 49(4), pages 571-582, April.
    12. John Seely Brown & Paul Duguid, 1991. "Organizational Learning and Communities-of-Practice: Toward a Unified View of Working, Learning, and Innovation," Organization Science, INFORMS, vol. 2(1), pages 40-57, February.
    Full references (including those not matched with items on IDEAS)

    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. Marrocu, Emanuela & Paci, Raffaele & Usai, Stefano, 2013. "Proximity, networking and knowledge production in Europe: What lessons for innovation policy?," Technological Forecasting and Social Change, Elsevier, vol. 80(8), pages 1484-1498.
    2. Rosina Moreno & Ernest Miguélez, 2012. "A Relational Approach To The Geography Of Innovation: A Typology Of Regions," Journal of Economic Surveys, Wiley Blackwell, vol. 26(3), pages 492-516, July.
    3. Nicola Cortinovis & Frank van Oort, 2017. "Between spilling over and boiling down: network-mediated spillovers, absorptive capacity and productivity in European regions," Tinbergen Institute Discussion Papers 17-118/VI, Tinbergen Institute.
    4. Britta Glennon, 2020. "How Do Restrictions on High-Skilled Immigration Affect Offshoring? Evidence from the H-1B Program," NBER Working Papers 27538, National Bureau of Economic Research, Inc.
    5. Andrés Rodríguez-Pose & Marco Di Cataldo, 2015. "Quality of government and innovative performance in the regions of Europe," Journal of Economic Geography, Oxford University Press, vol. 15(4), pages 673-706.
    6. Franco, Chiara & Montresor, Sandro & Vittucci Marzetti, Giuseppe, 2011. "On indirect trade-related R&D spillovers: The "Average Propagation Length" of foreign R&D," Structural Change and Economic Dynamics, Elsevier, vol. 22(3), pages 227-237, September.
    7. Blanca L. Delgado-Márquez & Marcos García-Velasco, 2018. "Geographical Distribution of the European Knowledge Base Through the Lens of a Synthetic Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(2), pages 477-496, April.
    8. Sheen S. Levine & Michael J. Prietula, 2012. "How Knowledge Transfer Impacts Performance: A Multilevel Model of Benefits and Liabilities," Organization Science, INFORMS, vol. 23(6), pages 1748-1766, December.
    9. Jiuling Xiao & Yuting Bao & Jiankang Wang, 2023. "Which neighbor is more conducive to innovation? The moderating effect of partners’ innovation," The Journal of Technology Transfer, Springer, vol. 48(1), pages 33-67, February.
    10. Gabriel Szulanski & Dimo Ringov & Robert J. Jensen, 2016. "Overcoming Stickiness: How the Timing of Knowledge Transfer Methods Affects Transfer Difficulty," Organization Science, INFORMS, vol. 27(2), pages 304-322, April.
    11. Pranpreya Sriwannawit & Ulf Sandström, 2015. "Large-scale bibliometric review of diffusion research," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1615-1645, February.
    12. Lina Bjerke & Sara Johansson, 2015. "Patterns of innovation and collaboration in small and large firms," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 55(1), pages 221-247, October.
    13. Horváth, Márton & Hau-Horváth, Orsolya, 2014. "A földrajzi közelség szerepe az innovációs együttműködésekben - illúzió vagy valós tényező?. Szakirodalmi áttekintés [The role of geographical proximity in efforts to cooperate on innovation - illu," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(12), pages 1419-1446.
    14. 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.
    15. Christopher Esposito & David Rigby, 2017. "When Buzz and Pipelines Fail," Papers in Evolutionary Economic Geography (PEEG) 1701, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jan 2017.
    16. Sriwannawit, Pranpreya & Sandström, Ulf, 2013. "Review of Diffusion Research," INDEK Working Paper Series 2013/1, Royal Institute of Technology, Department of Industrial Economics and Management.
    17. Kristina Jespersen & Damiana Rigamonti & Morten Berg Jensen & Rune Bysted, 2018. "Analysis of SMEs partner proximity preferences for process innovation," Small Business Economics, Springer, vol. 51(4), pages 879-904, December.
    18. Francesco Quatraro, 2016. "Co-evolutionary Patterns in Regional Knowledge Bases and Economic Structure: Evidence from European Regions," Regional Studies, Taylor & Francis Journals, vol. 50(3), pages 513-539, March.
    19. Mei Han & Bilin Xu, 2021. "Distance with Customers Effects on Green Product Innovation in SMEs: A Way Through Green Value Co-creation," SAGE Open, , vol. 11(4), pages 21582440211, December.
    20. Guan, Jian Cheng & Yan, Yan, 2016. "Technological proximity and recombinative innovation in the alternative energy field," Research Policy, Elsevier, vol. 45(7), pages 1460-1473.

    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:jsusta:v:17:y:2025:i:2:p:740-:d:1570056. 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.