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Effects of awareness and policy on green behavior spreading in multiplex networks

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  • Gao, Xingyu
  • Tian, Lixin

Abstract

As green behavior plays an increasingly important role today, in this paper, we aimed at investigating the spreading process of city resident green behavior. We applied classical threshold model and modified contagion model into a multiplex network to illustrate this dynamic process. Since people always act in conformity with the majorities when they make decisions or take actions, we consider the effects on negative individuals from their positive friends. Only when the proportion of centrist’s positive friends surpassed the local awareness ratio α, will he become positive. Also, we consider the influence from green awareness, which facilitate the green behavior. Last but not least, compulsory policy is also taken into account because it will force specific negative individuals to take such green behavior. The theoretical analysis is conducted by microscopic Markov chain approach and the numerical simulations are performed based on the Monte Carlo simulation. The results show that the intensity of policy regulation θ plays a vital role in both spreading threshold and final green behavior size. We attain a new explanation on the extinction of some behaviors and may provide advice on policy modification.

Suggested Citation

  • Gao, Xingyu & Tian, Lixin, 2019. "Effects of awareness and policy on green behavior spreading in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 226-234.
  • Handle: RePEc:eee:phsmap:v:514:y:2019:i:c:p:226-234
    DOI: 10.1016/j.physa.2018.09.067
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    References listed on IDEAS

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    1. Licheng Sun & Qunwei Wang & Shilong Ge, 2018. "Urban resident energy-saving behavior: a case study under the A2SC framework," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(2), pages 515-536, March.
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    4. Tian, Zihao & Dong, Gaogao & Du, Ruijin & Ma, Jing, 2016. "Non-consensus opinion model with a neutral view on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 601-608.
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    Cited by:

    1. Huo, Liang’an & Yu, Yue, 2023. "The impact of the self-recognition ability and physical quality on coupled negative information-behavior-epidemic dynamics in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    2. Cao, Junwei & Liu, Feng & Shang, Meng & Zhou, Xiaotong, 2021. "Toward street vending in post COVID-19 China: Social networking services information overload and switching intention," Technology in Society, Elsevier, vol. 66(C).

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