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

University Of Pennsylvania, Philadelphia PA

Investigators

Abstract

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.