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Auteurs principaux: Li, Juyi, Wu, Xiaoqun, Su, Qi
Format: Preprint
Publié: 2025
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Accès en ligne:https://arxiv.org/abs/2504.10910
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author Li, Juyi
Wu, Xiaoqun
Su, Qi
author_facet Li, Juyi
Wu, Xiaoqun
Su, Qi
contents Efficient allocation and use of limited resources are fundamental to advancing collective welfare and achieving long-term societal sustainability. This challenge involves not only how policymakers distribute scarce resources among individuals, but also how individuals strategically utilize them. The complexity deepens when individuals are embedded in networks of social interactions, where outcomes are interdependent and future decisions are shaped by a dynamic tension between cooperation driven by collective long-term benefit and self-interest motivated by short-term personal gain. Here, we introduce a novel framework of generalized public goods games on hypergraphs to capture the multifaceted nature of real-world social interactions. Using Nash equilibrium analysis, we reveal how full cooperation (all individuals contribute all their resources to maximize collective benefit) emerges from the interplay between resource allocation strategies, individual usage behaviors, and the structure of interactions. We find that equal resource distribution enhances cooperation in homogeneous networks but may suppress it in heterogeneous ones, indicating that equity in allocation does not universally lead to optimal collective outcomes. To address this, we propose two complementary optimization strategies: one to guide policymakers in designing effective resource allocation schemes, and the other to support individuals in making sustainable use decisions. We validate the effectiveness of both approaches across a range of synthetic and empirical cases. Our findings provide actionable insights for designing governance frameworks and resource management policies that promote sustainable cooperation in complex socio-environmental systems.
format Preprint
id arxiv_https___arxiv_org_abs_2504_10910
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Fostering Sustainable Cooperation through Strategic Resource Allocation and Utilization on Social Networks
Li, Juyi
Wu, Xiaoqun
Su, Qi
Computer Science and Game Theory
Efficient allocation and use of limited resources are fundamental to advancing collective welfare and achieving long-term societal sustainability. This challenge involves not only how policymakers distribute scarce resources among individuals, but also how individuals strategically utilize them. The complexity deepens when individuals are embedded in networks of social interactions, where outcomes are interdependent and future decisions are shaped by a dynamic tension between cooperation driven by collective long-term benefit and self-interest motivated by short-term personal gain. Here, we introduce a novel framework of generalized public goods games on hypergraphs to capture the multifaceted nature of real-world social interactions. Using Nash equilibrium analysis, we reveal how full cooperation (all individuals contribute all their resources to maximize collective benefit) emerges from the interplay between resource allocation strategies, individual usage behaviors, and the structure of interactions. We find that equal resource distribution enhances cooperation in homogeneous networks but may suppress it in heterogeneous ones, indicating that equity in allocation does not universally lead to optimal collective outcomes. To address this, we propose two complementary optimization strategies: one to guide policymakers in designing effective resource allocation schemes, and the other to support individuals in making sustainable use decisions. We validate the effectiveness of both approaches across a range of synthetic and empirical cases. Our findings provide actionable insights for designing governance frameworks and resource management policies that promote sustainable cooperation in complex socio-environmental systems.
title Fostering Sustainable Cooperation through Strategic Resource Allocation and Utilization on Social Networks
topic Computer Science and Game Theory
url https://arxiv.org/abs/2504.10910