IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i13p2078-d1427816.html
   My bibliography  Save this article

Coupled Simultaneous Evolution of Policy, Enterprise Innovation Awareness, and Technology Diffusion in Multiplex Networks

Author

Listed:
  • Jingyi Wang

    (Ministry of Education Key Laboratory of NSLSCS, Nanjing Normal University, Nanjing 210023, China)

  • Rui Hu

    (College of Mathematics and Computer Science, Tongling University, Tongling 244061, China)

  • Hua Xu

    (Department of Mathematics, Nanjing Normal University Taizhou College, Taizhou 225300, China)

Abstract

This study comprehensively examines the coupling effect of government policies, enterprise behavior, and existing technology on the diffusion of innovative technology. Utilizing multiplex network theory, a multiplex network model is constructed to couple policy incentives, enterprise innovation consciousness, and technology diffusion. Both global- and local-order parameters are introduced to characterize the interaction mechanisms between new and old technologies. By employing the microscopic Markov chain approach (MMCA), the threshold for technology diffusion is derived, theoretically revealing the mechanisms behind the diffusion of innovative technology. Considering the heterogeneity of enterprises, a numerical simulation is conducted on a scale-free network. The results indicate that, as the intensity of policy incentives increases, the threshold for technology diffusion decreases, promoting the spread of innovative technology. Additionally, the coupling relationship between existing technology and innovative technology influences the diffusion scale of the latter. The innovation behavior of enterprises further facilitates the adoption and dissemination of innovative technology.

Suggested Citation

  • Jingyi Wang & Rui Hu & Hua Xu, 2024. "Coupled Simultaneous Evolution of Policy, Enterprise Innovation Awareness, and Technology Diffusion in Multiplex Networks," Mathematics, MDPI, vol. 12(13), pages 1-19, July.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:13:p:2078-:d:1427816
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/13/2078/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/13/2078/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Valentina Bosetti & Carlo Carraro & Romain Duval & Alessandra Sgobbi & Massimo Tavoni, 2009. "The Role of R&D and Technology Diffusion in Climate Change Mitigation: New Perspectives Using the WITCH Model," OECD Economics Department Working Papers 664, OECD Publishing.
    2. Wu, Qingchu & Chen, Shufang, 2022. "Coupled simultaneous evolution of disease and information on multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    3. Zhan, Xiu-Xiu & Liu, Chuang & Zhou, Ge & Zhang, Zi-Ke & Sun, Gui-Quan & Zhu, Jonathan J.H. & Jin, Zhen, 2018. "Coupling dynamics of epidemic spreading and information diffusion on complex networks," Applied Mathematics and Computation, Elsevier, vol. 332(C), pages 437-448.
    4. Dror Kenett & Shlomo Havlin, 2015. "Network science: a useful tool in economics and finance," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 14(2), pages 155-167, November.
    5. Han, Zhongya & Tang, Zhongjun & He, Bo, 2022. "Improved Bass model for predicting the popularity of product information posted on microblogs," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    6. Li, Jiarong & Jiang, Haijun & Yu, Zhiyong & Hu, Cheng, 2019. "Dynamical analysis of rumor spreading model in homogeneous complex networks," Applied Mathematics and Computation, Elsevier, vol. 359(C), pages 374-385.
    7. An, Kangxin & Wang, Can & Cai, Wenjia, 2023. "Low-carbon technology diffusion and economic growth of China: an evolutionary general equilibrium framework," Structural Change and Economic Dynamics, Elsevier, vol. 65(C), pages 253-263.
    8. GRABISCH, Michel & RUSINOWSKA, Agnieszka & VENEL, Xavier, 2022. "Diffusion in large networks," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    9. Guseo, Renato & Guidolin, Mariangela, 2010. "Cellular Automata with network incubation in information technology diffusion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(12), pages 2422-2433.
    10. Elena Verdolini & Valentina Bosetti, 2017. "Environmental Policy and the International Diffusion of Cleaner Energy Technologies," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 66(3), pages 497-536, March.
    11. Skoczkowski, Tadeusz & Verdolini, Elena & Bielecki, Sławomir & Kochański, Max & Korczak, Katarzyna & Węglarz, Arkadiusz, 2020. "Technology innovation system analysis of decarbonisation options in the EU steel industry," Energy, Elsevier, vol. 212(C).
    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. Witajewski-Baltvilks, Jan & Verdolini, Elena & Tavoni, Massimo, 2017. "Induced technological change and energy efficiency improvements," Energy Economics, Elsevier, vol. 68(S1), pages 17-32.
    2. Huang, He & Chen, Yahong & Ma, Yefeng, 2021. "Modeling the competitive diffusions of rumor and knowledge and the impacts on epidemic spreading," Applied Mathematics and Computation, Elsevier, vol. 388(C).
    3. Bosetti, Valentina & Carraro, Carlo & Duval, Romain & Tavoni, Massimo, 2011. "What should we expect from innovation? A model-based assessment of the environmental and mitigation cost implications of climate-related R&D," Energy Economics, Elsevier, vol. 33(6), pages 1313-1320.
    4. Wu, Qingchu, 2024. "A hybrid one-vertex model for susceptible–infected–susceptible diseases on networks with partial connection information," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    5. Lai, N.Y.G. & Yap, E.H. & Lee, C.W., 2011. "Viability of CCS: A broad-based assessment for Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(8), pages 3608-3616.
    6. Julien Lefevre, 2018. "Modeling the Socioeconomic Impacts of the Adoption of a Carbon Pricing Instrument – Literature review," CIRED Working Papers hal-03128619, HAL.
    7. Yin, Fulian & Jiang, Xinyi & Qian, Xiqing & Xia, Xinyu & Pan, Yanyan & Wu, Jianhong, 2022. "Modeling and quantifying the influence of rumor and counter-rumor on information propagation dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    8. Sofia Priazhkina & Samuel Palmer & Pablo Martín-Ramiro & Román Orús & Samuel Mugel & Vladimir Skavysh, 2024. "Digital Payments in Firm Networks: Theory of Adoption and Quantum Algorithm," Staff Working Papers 24-17, Bank of Canada.
    9. Zhu, Hongmiao & Jin, Zhen & Yan, Xin, 2023. "A dynamics model of coupling transmission for multiple different knowledge in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    10. Guseo, Renato, 2016. "Diffusion of innovations dynamics, biological growth and catenary function," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 464(C), pages 1-10.
    11. Lionel Nesta & Elena Verdolini & Francesco Vona, 2018. "Threshold policy effects and directed technical change in Energy Innovation," SciencePo Working papers Main hal-03475570, HAL.
    12. Jingbo Cui & Zhenxuan Wang & Haishan Yu, 2022. "Can International Climate Cooperation Induce Knowledge Spillover to Developing Countries? Evidence from CDM," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 82(4), pages 923-951, August.
    13. Shekhtman, Louis M. & Danziger, Michael M. & Havlin, Shlomo, 2016. "Recent advances on failure and recovery in networks of networks," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 28-36.
    14. X. Zhang & L. D. Valdez & H. E. Stanley & L. A. Braunstein, 2019. "Modeling Risk Contagion in the Venture Capital Market: A Multilayer Network Approach," Complexity, Hindawi, vol. 2019, pages 1-11, December.
    15. Yu, Shuzhen & Yu, Zhiyong & Jiang, Haijun, 2024. "A rumor propagation model in multilingual environment with time and state dependent impulsive control," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    16. Nabernegg, Stefan & Bednar-Friedl, Birgit & Muñoz, Pablo & Titz, Michaela & Vogel, Johanna, 2019. "National Policies for Global Emission Reductions: Effectiveness of Carbon Emission Reductions in International Supply Chains," Ecological Economics, Elsevier, vol. 158(C), pages 146-157.
    17. Heyen, Daniel, 2015. "Strategic Conflicts on the Horizon: R&D Incentives for Environmental Technologies," Working Papers 0584, University of Heidelberg, Department of Economics.
    18. Chen, Jie & Hu, Mao-Bin & Li, Ming, 2020. "Traffic-driven epidemic spreading dynamics with heterogeneous infection rates," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    19. Chen, Zheng & Wu, Yong-Ping & Feng, Guo-Lin & Qian, Zhong-Hua & Sun, Gui-Quan, 2021. "Effects of global warming on pattern dynamics of vegetation: Wuwei in China as a case," Applied Mathematics and Computation, Elsevier, vol. 390(C).
    20. Guilherme Ferraz de Arruda & Lucas G. S. Jeub & Angélica S. Mata & Francisco A. Rodrigues & Yamir Moreno, 2022. "From subcritical behavior to a correlation-induced transition in rumor models," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

    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:jmathe:v:12:y:2024:i:13:p:2078-:d:1427816. 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.