IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0238541.html
   My bibliography  Save this article

Research on the invulnerability and optimization of the technical cooperation innovation network based on the patent perspective—A case study of new energy vehicles

Author

Listed:
  • Xia Cao
  • Chuanyun Li
  • Wei Chen
  • Jinqiu Li
  • Chaoran Lin

Abstract

This paper takes new energy vehicles as the research object, building the technical cooperation innovation network of new energy vehicles based on the patent perspective by establishing the related technology patent search expression, and analyzing the processes of the invulnerability and optimization in the actual technology cooperation innovation network by using the simulation analysis method. The research results show that the harmfulness of the degree value priority attack in the technical cooperation innovation network of new energy vehicles is stronger than the weighted degree value priority attack and random attack, and the attacks of the State Grid and other hub nodes have an important impact on the network invulnerability. During the network optimization process of three types of connection preferences, the “weak”-“weak” connection is the best connection mode given the situation of an unweighted network without considering the weight of the connected edge. However, the “strong”-“weak” connection is the best mode given the situation of a weighted network considering the weight of the connected edge. In addition, compared with the weighted network situation, the “strong”-“weak” connection has better network optimization results given the situation of an unweighted network. Finally, we propose counter measures and suggestions to promote the innovation network invulnerability capabilities of technical cooperation in new energy vehicles.

Suggested Citation

  • Xia Cao & Chuanyun Li & Wei Chen & Jinqiu Li & Chaoran Lin, 2020. "Research on the invulnerability and optimization of the technical cooperation innovation network based on the patent perspective—A case study of new energy vehicles," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-19, September.
  • Handle: RePEc:plo:pone00:0238541
    DOI: 10.1371/journal.pone.0238541
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0238541
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0238541&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0238541?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. H. Jeong & S. P. Mason & A.-L. Barabási & Z. N. Oltvai, 2001. "Lethality and centrality in protein networks," Nature, Nature, vol. 411(6833), pages 41-42, May.
    2. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
    3. Beygelzimer, Alina & Grinstein, Geoffrey & Linsker, Ralph & Rish, Irina, 2005. "Improving network robustness by edge modification," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 357(3), pages 593-612.
    4. Luo, Yugong & Feng, Guixuan & Wan, Shuang & Zhang, Shuwei & Li, Victor & Kong, Weiwei, 2020. "Charging scheduling strategy for different electric vehicles with optimization for convenience of drivers, performance of transport system and distribution network," Energy, Elsevier, vol. 194(C).
    5. Bellingeri, Michele & Cassi, Davide, 2018. "Robustness of weighted networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 47-55.
    6. Rezaei, Behnam A. & Sarshar, Nima & Roychowdhury, Vwani P. & Boykin, P. Oscar, 2007. "Disaster management in power-law networks: Recovery from and protection against intentional attacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 381(C), pages 497-514.
    7. Liu, Mengmeng & Ma, Yinghong & Liu, Zhiyuan & You, Xuemei, 2017. "An IUR evolutionary game model on the patent cooperate of Shandong China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 475(C), pages 11-23.
    8. Michael Fritsch & Martina Kauffeld-Monz, 2010. "The impact of network structure on knowledge transfer: an application of social network analysis in the context of regional innovation networks," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 44(1), pages 21-38, February.
    9. G. Paul & T. Tanizawa & S. Havlin & H. Stanley, 2004. "Optimization of robustness of complex networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 38(2), pages 187-191, March.
    10. Linares, Ian Marques Porto & De Paulo, Alex Fabianne & Porto, Geciane Silveira, 2019. "Patent-based network analysis to understand technological innovation pathways and trends," Technology in Society, Elsevier, vol. 59(C).
    11. Zhou, Hongli & Zhang, Xiaodong & Hu, Yang, 2020. "Robustness of open source product innovation community’s knowledge collaboration network under the dynamic environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    12. Niemann, Helen & Moehrle, Martin G. & Frischkorn, Jonas, 2017. "Use of a new patent text-mining and visualization method for identifying patenting patterns over time: Concept, method and test application," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 210-220.
    13. Wei, Shanting & Zhang, Zhuo & Ke, Ginger Y. & Chen, Xintong, 2019. "The more cooperation, the better? Optimizing enterprise cooperative strategy in collaborative innovation networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    14. Chen, Yu & Wang, Jiaoe & Jin, Fengjun, 2020. "Robustness of China’s air transport network from 1975 to 2017," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    15. Fan, Wenli & Huang, Shaowei & Mei, Shengwei, 2016. "Invulnerability of power grids based on maximum flow theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 977-985.
    16. Choe, Hochull & Lee, Duk Hee & Kim, Hee Dae & Seo, Il Won, 2016. "Structural properties and inter-organizational knowledge flows of patent citation network: The case of organic solar cells," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 361-370.
    17. Zhou, Hong-Li & Zhang, Xiao-Dong, 2018. "Dynamic robustness of knowledge collaboration network of open source product development community," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 601-612.
    18. Crucitti, Paolo & Latora, Vito & Marchiori, Massimo & Rapisarda, Andrea, 2003. "Efficiency of scale-free networks: error and attack tolerance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 320(C), pages 622-642.
    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. Xia Cao & Chuanyun Li & Jinqiu Li & Yunchang Li, 2022. "Modeling and simulation of knowledge creation and diffusion in an industry-university-research cooperative innovation network: a case study of China’s new energy vehicles," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 3935-3957, July.
    2. P.B., Divya & Lekha, Divya Sindhu & Johnson, T.P. & Balakrishnan, Kannan, 2022. "Vulnerability of link-weighted complex networks in central attacks and fallback strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    3. Yu, Yang & Deng, Ye & Tan, Suo-Yi & Wu, Jun, 2018. "Efficient disintegration strategy in directed networks based on tabu search," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 435-442.
    4. Peng, Guan-sheng & Wu, Jun, 2016. "Optimal network topology for structural robustness based on natural connectivity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 212-220.
    5. Stefano Martinazzi & Andrea Flori, 2020. "The evolving topology of the Lightning Network: Centralization, efficiency, robustness, synchronization, and anonymity," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-18, January.
    6. Lekha, Divya Sindhu & Balakrishnan, Kannan, 2020. "Central attacks in complex networks: A revisit with new fallback strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    7. Vodák, Rostislav & Bíl, Michal & Sedoník, Jiří, 2015. "Network robustness and random processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 368-382.
    8. Dong, Gaogao & Tian, Lixin & Du, Ruijin & Fu, Min & Stanley, H. Eugene, 2014. "Analysis of percolation behaviors of clustered networks with partial support–dependence relations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 370-378.
    9. Jisha Mariyam John & Michele Bellingeri & Divya Sindhu Lekha & Davide Cassi & Roberto Alfieri, 2023. "Effect of Weight Thresholding on the Robustness of Real-World Complex Networks to Central Node Attacks," Mathematics, MDPI, vol. 11(16), pages 1-12, August.
    10. Quayle, A.P. & Siddiqui, A.S. & Jones, S.J.M., 2006. "Preferential network perturbation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 823-840.
    11. Aybike Ulusan & Ozlem Ergun, 2018. "Restoration of services in disrupted infrastructure systems: A network science approach," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-28, February.
    12. Deng, Ye & Wu, Jun & Tan, Yue-jin, 2016. "Optimal attack strategy of complex networks based on tabu search," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 74-81.
    13. Zhou, Yaoming & Wang, Junwei, 2018. "Efficiency of complex networks under failures and attacks: A percolation approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 658-664.
    14. Zhao, Jianyu & Wei, Jiang & Yu, Lean & Xi, Xi, 2022. "Robustness of knowledge networks under targeted attacks: Electric vehicle field of China evidence," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 367-382.
    15. Yang, Zhirou & Liu, Jing, 2018. "A memetic algorithm for determining the nodal attacks with minimum cost on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1041-1053.
    16. Viljoen, Nadia M. & Joubert, Johan W., 2016. "The vulnerability of the global container shipping network to targeted link disruption," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 396-409.
    17. Laurienti, Paul J. & Joyce, Karen E. & Telesford, Qawi K. & Burdette, Jonathan H. & Hayasaka, Satoru, 2011. "Universal fractal scaling of self-organized networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3608-3613.
    18. Gao, Jianbo & Hu, Jing, 2014. "Financial crisis, Omori's law, and negative entropy flow," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 79-86.
    19. Morehead, Raymond & Noore, Afzel, 2007. "Novel hybrid mitigation strategy for improving the resiliency of hierarchical networks subjected to attacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(2), pages 603-612.
    20. Jalili, Mahdi, 2011. "Synchronizability of dynamical scale-free networks subject to random errors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4588-4595.

    More about this item

    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:plo:pone00:0238541. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.