Doctoral Dissertation Research: Heterogenous Preferences and Dynamics of Cooperation in Networked Public Goods Games: A Dialogue Between Experimental and Computational Approaches

一系列的行为和计算实验研究机制，促进合作，在网络社区。社会群体通常是围绕某种形式的网络结构建立的，而群体内的合作和效率可能会受到网络结构所决定的信息流的强烈影响。此外，实验和观察研究表明，对于给定的网络结构，某些真实的世界群体比其他群体更能成功地维持合作。本研究探讨的假设，这种异质性是由于个人的社会偏好和网络结构，决定了一个社会群体内的合作动态之间的相互作用。实验经济学的结果表明，就个人而言，存在着很大的异质性。在群体困境情境中，人更倾向于合作。取决于这些合作社类型在群体中的构成，如果不付出代价，可能会也可能不会实现社会最佳合作。这表明，除了网络结构之外，网络中不同类型的分布和位置也会影响群体结果。虽然它已被证明，网络结构可以促进合作，这个建议调查的影响，合作类型的分布和他们在一个给定的网络结构中的位置对社会outcomes.This项目是一个不寻常的使用行为实验和计算模拟方法称为基于代理的建模。这种方法将使我们能够系统地研究网络结构对异质群体合作行为的影响。虽然观察数据存在于自然发生的网络中，但网络结构和参与网络的个体的行为通常是共同进化的。因此，识别结构对合作的影响将是有偏见的，因为个人选择的网络中进行交互。这项研究的优势在于使用实验室实验来识别个体的合作偏好，然后将它们策略性地放置在各种网络结构中，以研究这些类型如何相互作用以增强合作。该研究可以创建现有网络的反事实，以研究具有不同合作偏好水平的个人在他们没有选择的网络中的行为。实验和基于代理的建模之间的对话将使学者能够更有效地研究具有最大增强合作潜力的网络结构，并学习和校准模型，以更好地代表社会困境中的行为。

A series of behavioral and computational experiments examine mechanisms by which cooperation is promoted in networked communities. Social groups are typically built around some form of network structure, and cooperation and efficiency within a group can be strongly affected by the flow of information determined by the structure of the network alone. Furthermore, experimental and observational studies show some real world groups are more successful at sustaining cooperation than others for a given network structure. This research explores the hypothesis that such heterogeneity is due to the interaction between the social preferences of individuals and the network structure that determines the dynamics of cooperation within a social group. Results from experimental economics have shown that there is a great deal of heterogeneity in terms of an individual?s preference to cooperate in group-dilemma settings. Depending on the composition of these cooperative types in the group, socially optimal cooperation may or may not be achieved without costly sanctions. This suggests that, in addition to the network structure, the distribution and the placement of different types within the network can also affect group outcomes. While it has been shown that network structure can facilitate cooperation, this proposal investigates the impact of the distribution of cooperative types and their placement within a given network structure on social outcomes.This project is an unusual use of both behavioral experiments and the computational simulation methodology known as agent-based modeling. This approach will allow us to systematically investigate the effects of network structure on cooperative behavior in a heterogeneous population. While observational data exists on naturally-occurring networks, the network structure and behavior of the individuals participating in the network have typically co-evolved. Thus, identification of the effect of structure on cooperation would be biased with this data because of individuals choosing the network in which to interact. The strength of this research is to use laboratory experiments to identify the cooperative preferences of individuals and then strategically place them in various network structures to examine how these types interact to enhance cooperation. The research can create counterfactuals of existing networks to examine how individuals with different levels of cooperative preferences would behave in a network they did not choose. The dialogue between the experiments and agent-based modeling will allow scholars to more efficiently investigate the network structures that have the potential to most enhance cooperation and to learn and calibrate the models to better represent behavior in social dilemmas.