Abstract
We propose a simple yet effective theoretical model for the evolutionary threshold public goods game with binary contributions (the fair personal share or nothing), incorporating the effect of collective risk. We distinguish two distinct public goods games according to whether to return the contributions when the target is not collected. For the two cases, in order to study the impact of collective risk on cooperation, we analyze dynamics of the population which can be represented by the replicator equations. It shows that high rate of loss can enhance the emergence of social cooperation and the provision of public goods. Furthermore, other elements also can promote the cooperation, such as large initial endowment and small threshold. Interestingly, for large group size, it has a positive impact on cooperation in the case of returning the donation amount, whereas a negative impact in the case of no return.
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Wang, J., Ren, F., Zhu, M., Wang, L. (2009). Information Dynamics and Intelligent Cooperation in Networked Societies. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5551. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01507-6_12
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DOI: https://doi.org/10.1007/978-3-642-01507-6_12
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