Facts and Figuring: An Experimental Investigation of Network Structure and Performance in Information and Solution Spaces
通过16人网络实验，发现网络聚类对信息探索和方案探索有相反影响：密集聚类促进信息多样性但抑制理论多样性，为组织知识工作提供结构优化启示。
Using data from a novel laboratory experiment on complex problem solving in which we varied the structure of 16-person networks, we investigate how an organization’s network structure shapes the performance of problem-solving tasks. Problem solving, we argue, involves both exploration for information and exploration for solutions. Our results show that network clustering has opposite effects for these two important and complementary forms of exploration. Dense clustering encourages members of a network to generate more diverse information but discourages them from generating diverse theories; that is, clustering promotes exploration in information space but decreases exploration in solution space. Previous research, generally focusing on only one of those two spaces at a time, has produced an inconsistent understanding of the value of network clustering. By adopting an experimental platform on which information was measured separately from solutions, we bring disparate results under a single theoretical roof and clarify the effects of network clustering on problem-solving behavior and performance. The finding both provides a sharper tool for structuring organizations for knowledge work and reveals challenges inherent in manipulating network structure to enhance performance, as the communication structure that helps one determinant of successful problem solving may harm the other.