Game Theory Tells Us How To Efficiently Use Institutions For Governing The Commons
Cooperation is imperative when humans deal with the consequence of collective actions, such as global warming, overfishing, or preserving natural resources. However, the collapse of cooperation happens too often in these situations, which predicts several undesired scenarios. A well-known example is the danger of overfishing. Fishermen are motivated to catch the maximum amount of fish without driving the fish to extinction, which is the worst scenario for everyone, thus ensuring a sufficiently high level of cooperation and maintaining sustainable use of common-pool resources are essential tasks for all human societies.
Renewable resources are generally believed to play key roles in achieving a sustainable human development, but the sustainable use of common-pool resources is strongly based on resource interdependence and social dynamics. More precisely, the shape of resources is influenced by human behaviors on how to use them. On the other hand, the actual resource amount is also determined by the resource intrinsic features. Indeed, resources, particularly renewable resources, are influenced by some ecological factors, such as the resource growth rate and the carrying capacity of the resource system. As a consequence, the actual shape of a dynamical resource also influences the prosperity of human well-being, which triggers frequency-dependent changes in individual strategies.
It is a crucial point that institutions are often used as control mechanisms to govern the common-pool resources in these coupled social-resource systems. Normally they provide incentives to enable humans to overcome the basic dilemma. Some related control mechanisms, like ostracism or voluntary enforcement, have been discussed as potential solutions to the original problem. More importantly, punishment and permanent monitoring are also used as a control mechanism for the forest commons management in human society. But it is still unclear how to efficiently use institutions for these coupled social-resource systems from a theoretical perspective. In particular, it remained hidden when these institutions are inefficient no matter they are used intensively.
The surprising efficiency of evolutionary game theory in understanding our complex world in widely different scales makes possible to predict the long-term consequences of control mechanisms on resource management in a coupled social-resource system. By using evolutionary game theory, we aim to develop a realistic model where there is a coupling between the behavior of players and the developing state of a common pool resource. In our proposed new feedback-evolving framework we consider not just exploitation of the resource but also take into account the fact that environmental is a living system and the common pool can be renewable. We further introduce a top-down-like control mechanism based on punishment and a permanent monitoring of participants.
We found that in addition to a delicately adjusted punishment regime, renewable resource’s growing capacity is a key feature for keeping those resources at a sustainable level. In particular, institutions based on punishment and inspection can efficiently solve the public goods dilemma when the growth capacity is intermediate. Otherwise, even the use of severe punishment cannot save the human community from an undesired end. We thus concluded that when designing a social control mechanism to solve the overexploitation problem in a coupled social-resource system, we should first pay attention to the system’s intrinsic features which can predetermine whether the designed control mechanism is capable of maintaining the level of common resource toward the desired direction.
These findings are described in the article entitled Punishment and inspection for governing the commons in a feedback-evolving game, recently published in the journal PLoS Computational Biology. This work was conducted by Xiaojie Chen from University of Electronic Science and Technology of China and Attila Szolnoki from the Hungarian Academy of Sciences.