Conference Agenda

Natural resource systems often exhibit tipping points: If consumption exceeds a

tipping point, the system collapses. The location of these tipping points is almost

always unknown. Hence, receiving an early warning signal (EWS) about the lo-

cation of a tipping point appears to be very valuable. Recent progress in natural

sciences has shown that (a) many natural systems indeed have the potential to show

such early warning signals but (b) detection is often unreliable. Here, we present a

theoretical model and a behavioral experiment representing such a situation. A de-

cision maker chooses consumption to maximize her payoff, subject to not exceeding

an unknown tipping point, in one of three decision environment: without an early

warning system (EWSys), with a reliable EWSys and with an unreliable EWSys.

We derive optimal choices and the value of information in each case and compare

them to the behavior observed in the experiment.

Common pool resource (CPR) use is shaped by intertemporal dynamics, resource collapse thresholds, and user heterogeneity - complex features that affect sustainable CPR management but are rarely examined together. We theoretically develop a dynamic CPR game that incorporates all three features, and we empirically test the model using a laboratory experiment focused on groundwater depletion. Our theoretical model predicts behavior at equilibrium under homogeneous and heterogeneous resource collapse thresholds, with players exiting the game upon collapse. The experiment compares observed behavior to these predictions. We find that participants consistently under-extract relative to the Markov perfect equilibrium. Heterogeneous thresholds lead to lower aggregate extraction and higher social efficiency, even though high-risk users remain active longer than predicted. These findings suggest that making heterogeneity more salient among users and targeting high-risk users with conservation incentives may contribute to more sustainable and efficient CPR management outcomes.

The resolution of collective-action problems often depends on social norms and pressure to conform to group behaviour, yet individuals typically differ in how strongly they perceive and internalise these norms. While existing models of norm change and social tipping often assume homogeneous and static normative expectations, recent evidence suggests substantial heterogeneity in the perceived norm strength. We study how different compositions of such heterogeneity within a community shape the emergence and internalisation of cooperative behaviour. We develop a spatial agent-based model in which agents follow a conditional-cooperation norm but differ in norm strength, characterised as either tight or loose. Agents interact locally and update their cooperation thresholds endogenously through a combination of payoff-driven learning and social learning from experiencing group behaviour. Our results show that introducing a moderate share of loose-norm individuals into otherwise tight-dominated communities can facilitate the emergence of cooperative tipping points by enabling cooperation to seed and spread locally, even when agents place zero weight on social-relative-to-financial learning. However, whether cooperation becomes internalised and persists depends critically on the relative weight given to social and financial learning. A higher weight on social learning amplifies local behavioural feedbacks, sharpens tipping-point dynamics, and allows agents with tight social norms to internalise cooperation such that it can be sustained with fewer cooperating group members. Once cooperation spreads, conformity pressure stabilises cooperative behaviour among loose-social-norm agents. Taken together, our findings highlight the importance of community composition and norm-strength heterogeneity for collective-action dynamics, and show how heterogeneity in perceived norm strength can generate abrupt and persistent transitions in cooperative behaviour.