Maximizing the Spread of Stable Influence: Leveraging Norm-driven Moral-Motivation for Green Behavior Change in Networks

In an effort to understand why individuals choose to participate in personally-expensive pro-environmental behaviors, environmental and behavioral economists have examined a moral-motivation model in which the decision to adopt a pro-environmental behavior depends on the society-wide market share of that behavior. An increasing body of practical research on adoption of pro-environmental behavior empha-sizes the importance of encouragement from local social contacts and messaging about locally-embraced norms: we respond by extending the moral-motivation model to a social networks setting. We obtain a new decision rule: an individual adopts a pro-environmental behavior if he or she observes a certain threshold of adoption within their local social neighborhood. This gives rise to a concurrent update process which describes adoption of a pro-environmental behavior spreading through a network. The process evolves according to a set of difference equations in an exponentially large space that describes all possible patterns of adoption. The original moral-motivation model corresponds to the special case of our network version in a complete graph. In parallel with the original moral-motivation work, we examine issues of stability of adoption (which now depends intimately on the spatial distribution of adoption within the network), bounds on the conver