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Impact of negative information diffusion on green behavior adoption

机译:负面信息扩散对绿色行为采用的影响

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Apart from the technical improvements, inducing the green citizen behavior is also a key way to reduce carbon emissions. Various studies have tried to identify the determinants of green behavior. Hitherto, there lacks a quantitative analysis directed to the effects of some factor on the outbreak of green behavior and the final adopted fraction. To fill this gap, this paper propose a Heterogeneous Green Behavior Spreading (HGBS) model to explore the impacts of negative information diffusion (about the green behavior) that effects on the spreading of green behavior. Simulations are performed on top of the two-layer multiplex networks, in which individuals are involved in two processes, the information diffusion in information layer and the green behavior spreading in physical contact layer. Based on the Microscopic Markov Chain Approach (MMCA) and the Monte Carlo (MC) simulations, we find the slight impact of information layer would make the green behavior harder to break out and reduce the adopted fraction. Moreover, the diversity of information diffusion ways makes it worse. It suggests that the control of negative information diffusion would be helpful in contributing to low-carbon city. Another effective way is to encourage individuals having more neighbours in real world to behave pro-environmentally since the adopted fraction is increased for small degree of the individuals in physical contact layer. It is essential to consider the heterogeneity in spreading activity if one wants to model the green behavior spreading.
机译:除了技术改进之外,诱导绿色公民行为也是减少碳排放的关键途径。各种研究试图确定绿色行为的决定因素。迄今为止,缺乏定量分析,导致某些因素对绿色行为爆发的影响和最终采用的分数。为了填补这种差距,本文提出了异构的绿色行为传播(HGBS)模型,以探讨负面信息扩散(关于绿色行为)对绿色行为扩散的影响。在双层多路复用网络的顶部执行模拟,其中各个是两个过程,信息层中的信息扩散和在物理接触层中扩展的绿色行为。基于微观马尔可夫链条方法(MMCA)和蒙特卡罗(MC)模拟,我们发现信息层的略有影响将使绿色行为更加难以突破并减少所采用的分数。此外,信息扩散方式的多样性使得它变得更糟。它表明,对负面信息扩散的控制将有助于为低碳城市提供贡献。另一种有效的方法是鼓励在现实世界中具有更多邻居的个人在较小的物理接触层中所采用的分数增加,因为所采用的分数增加。如果想要模拟绿色行为传播,则必须考虑传播活动中的异质性。

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