Motivating more people to engage in online green behavior: A multi-agent simulation study of Ant Forest

Abstract

With the rapid development of Internet technology, people's lives are increasingly embedded in online communities. The implementation scenarios of green behavior are extended from offline to online, and individual decision-making is more likely to be influenced by others in the group. However, little is known about the decision-making process of group participation in online green behavior (OLGB). To fill this gap, we took the online environmental project Ant Forest as an example and constructed a multi-agent simulation model incorporating members' gratification types, social network connectivity, and external incentives. Then, we analyzed the decision-making characteristics of groups participating in OLGB. The results showed that: (1) When the ratio of members seeking entertainment, social, and achievement gratifications was 3:3:4, more people chose to accept OLGB and it has the most stable decision status; (2) Under low network connectivity, the group was more inclined to accept OLGB, and the decision status was more stable; (3) When high-intensity financial incentives and medium-intensity non-financial incentives were coupled, the number of people choosing OLGB was the largest, and the decision-making status was the most stable. These findings provide suggestions for policymakers and online green project operators on how to promote more people to engage in OLGB.