Impact of negative information diffusion on green behavior adoption

Abstract 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.