Doctoral Dissertation Research: Designing Collaboration Networks to Optimize Collective Problem Solving

这个项目研究了协作网络的结构如何影响集体解决问题的成功。虽然直觉认为，支持有效传播信息的网络作为一个集体表现得更好，但理论工作已经提出了网络效率和成功解决问题之间的反比关系。 换句话说，它假设效率较低的沟通网络可能会促进更有效的问题解决，因为人们需要独立地寻找问题的解决方案。 信息的多样性增加，可能会增加工作组在达成共识之前找到更好解决办法的机会。 试图评估这一理论的经验一直是不确定的，由于其规模和设计的限制。 本研究使用新的在线资源，观察和实验，研究网络效率对集体解决问题的大型经验交流网络的影响。该项目对加强研究和教育领域的合作网络以及设计科学和工业领域的高效团队结构具有重要意义。该项目将深入了解科学研究人员之间的合作网络结构如何影响创新的速度和质量。 它将确定如何设计分布式在线协作网络，为决策者和行业管理人员提供改进团体和提高解决问题能力的新战略。

This project examines how the structure of collaboration networks affects the success of collective problem solving. Although intuition would suggest that networks which support the efficient diffusion of information perform better as a collectivity, theoretical work has proposed an inverse relationship between network efficiency and success in problem solving. In other words, it posits that less efficient communication networks may promote more effective problem solving because people need to search independently for solutions to problems. The increased diversity of the information might improve the chances that the group will find a better solution before arriving at a consensus. Attempts to evaluate this theory empirically have been inconclusive due to limitations of their scale and design. Using novel online resources, both observational and experimental, this research studies the effects of network efficiency on collective problem solving within large empirical communication networks. This project has implications for enhancing collaboration networks in research and education, and for designing efficient team structures in science and industry.This project will provide insight into how the structure of collaboration networks among scientific researchers can influence the rate and quality of innovation. It will identify the ways that distributed, online collaboration networks can be designed to provide policymakers and industry managers with new strategies for improving groups and for enhancing problem solving capacities.