Modeling social norms in social-ecological systems: a systematic literature review

Abstract Social norms play a pivotal role in sustainability transitions by shaping human behavior and influencing responses to challenges such as climate change and natural resource management. They can facilitate or impede collective action. Although simulation models help to explore norm dynamics, modeling approaches remain scattered and lack synthesis specific to social-ecological systems. This systematic review aims to map existing computational approaches to modeling social norms within social-ecological systems, identifying trends, gaps and implications for research and policy. We conducted a systematic search of Web of Science and Scopus (search date: 15 November 2024), screened abstracts using validated large language models, and selected 153 relevant studies for analysis. Key aspects analyzed included publication trends, thematic focus, modeling methods, spatial scale, empirical data used behavioral theory incorporation and norm representation. Publications increased over 25 years, with most studies originating from Europe and North America. Two dominant themes emerged: common-pool resource management and individual consumption behavior. Agent-based and evolutionary game-theoretic models prevail, but many omit explicit behavioral theories beyond rational choice theory. Models are mostly local or regional in scale and theoretical in nature and often lack empirical data for the quantification of the social norm modeled. Norms are generally modeled on an observation base, meaning that the majority of models include norms based on what others do. Interactions between norm types and dynamic norm signaling remain under-explored. To strengthen social-ecological modeling and its policy relevance, future work should enhance geographic diversity, integrate behavioral theories more deeply and develop models that capture dynamically signaled norms in order to advance our understanding of human–environment interactions and sustainability transitions.