Reasoning within and between collective action problems

TL;DR

This study investigates how individuals make decisions within and between collective action problems, revealing that heuristic models predict choices in complex scenarios, while utility-based decisions dominate in real-time cooperation contexts.

Contribution

It demonstrates the conditions under which heuristic versus utility-based decision models best predict cooperative behavior in social systems.

Findings

Heuristic models predict decisions when choosing between multiple rules.

Real-time decisions align closely with objective utility.

Feedback frequency indicates the objective utility of rules.

Abstract

Understanding cooperation in social systems is challenging because the ever-changing rules that govern societies interact with individual actions, resulting in intricate collective outcomes. In virtual-world experiments, we allowed people to make changes in the systems that they are making decisions within and investigated how they weigh the influence of different rules in decision-making. When choosing between worlds differing in more than one rule, a naive heuristics model predicted participants decisions as well, and in some cases better, than game earnings (utility) or by the subjective quality of single rules. In contrast, when a subset of engaged participants made instantaneous (within-world) decisions, their behavior aligned very closely with objective utility and not with the heuristics model. Findings suggest that, whereas choices between rules may deviate from rational benchmarks, the frequency of real time cooperation decisions to provide feedback can be a reliable indicator of the objective utility of these rules.