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Coupled diffusion dynamics of competitive information and green behaviors on multiplex networks under policy intervention

Author

Listed:
  • Wang, Zhishuang
  • Wan, Yicong
  • Yin, Qian
  • Hong, Zhiyong
  • Xu, Qiuxia
  • Xia, Chengyi

Abstract

In addition to reducing greenhouse gas emissions from industrial production, individual green behaviors also play a significant role in alleviating the climate crisis. To quantitatively analyze the dynamic properties of the coupled diffusion of positive and negative information and green behaviors under policy intervention, we constructed a model based on a two-layer complex networks framework. Positive information promotes individual adoption of green behaviors, while negative information reduces individual willingness to engage in green behaviors, and policy intervention affects the probability of individuals abandoning green behaviors. We also considered the influence of individual hesitancy psychology in the competitive dissemination process of the two types of information. Utilizing compartmental models commonly used in infectious disease transmission, we characterized the diffusion processes of both types of information and green behaviors and described the transition mechanism of individual states using probability transition trees based on the coupled diffusion mechanism. Combining the topological structure of the two-layer complex networks, we further formalized the coupled propagation model into coupled diffusion dynamic equations. Based on the steady-state coupled diffusion dynamic equations, we derived the outbreak threshold expression for green behaviors in the proposed coupled diffusion model, indicating that both the density of information propagation and the intensity of policy intervention directly influence the diffusion threshold of green behaviors in the population. Extensive computer simulation results were used to further analyze the dynamic properties of coupled diffusion, showing that when the propagation rate of positive information exceeds that of negative information, it is conducive to the outbreak and diffusion of green behaviors. Policy intervention has a better promotional effect when negative information spreads widely. Moreover, the diffusion threshold of green behaviors may undergo a sudden change with the variation in the propagation rates of the two types of information.

Suggested Citation

  • Wang, Zhishuang & Wan, Yicong & Yin, Qian & Hong, Zhiyong & Xu, Qiuxia & Xia, Chengyi, 2025. "Coupled diffusion dynamics of competitive information and green behaviors on multiplex networks under policy intervention," Applied Mathematics and Computation, Elsevier, vol. 495(C).
  • Handle: RePEc:eee:apmaco:v:495:y:2025:i:c:s0096300325000554
    DOI: 10.1016/j.amc.2025.129328
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    References listed on IDEAS

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    1. Huo, Liang’an & Pan, Mengyu & Gu, Jiafeng, 2025. "Analysis of two-layer network SA1A2R1R2 model under the influence of competitive information and asymmetric activity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 676(C).
    2. Chen, Yahong & Huang, He, 2026. "Collaborated risk perception against multiple epidemics in a multiplayer network," Applied Mathematics and Computation, Elsevier, vol. 511(C).
    3. Zhan, Xiu-Xiu & Mei, Guangyuan & Xie, Chenwei & Lv, Fan & Liu, Chuang & Zhang, Zi-Ke, 2025. "Modeling the coevolution of information diffusion and garbage classification behavior on simplicial complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 199(P1).
    4. Chang, Xinghua & Wang, Jianrong & Liu, Maoxing & Yan, Xue, 2025. "An SIS infectious disease model with nonlinear incidence and disease awareness on complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 196(C).
    5. Polin, Sujana Azmi & Hasan, Md. Nahid & Islam, Saiful & Podder, Chandra Nath, 2025. "Behavioral influences on rumor dynamics: A compartmental model with hesitation, forgetting, and self-remembering mechanisms in complex heterogeneous social networks," Chaos, Solitons & Fractals, Elsevier, vol. 201(P3).

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