Facts and Figuring: An Experimental Investigation of Network Structure and Performance in Information and Solution Spaces

Abstract

Using data from a novel laboratory experiment on complex problem solving in which we varied the network structure of 16-person organizations, we investigate how an organization's network structure shapes performance in problem-solving tasks. Problem solving, we argue, involves both search for information and search for solutions. Our results show that the effect of network clustering is opposite for these two important and complementary forms of search. Dense clustering encourages members of a network to generate more diverse information, but discourages them from generating diverse theories: in the language of March (1991), 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 were able to 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 the challenges inherent in manipulating network structure to enhance performance, as the communication structure that helps one antecedent of successful problem solving may harm the other.

How intermittent breaks in interaction improve collective intelligence

“…Past research shows that social influence leads individuals to adopt their peers’ opinions and copy their solutions to problems ( 5 ), especially under conditions of network clustering ( 13 , 14 ), leading to a loss of aggregate diversity. Under certain conditions—performing simple estimation tasks or searching simple solution spaces with clear performance feedback—more efficiently connected networks of problem solvers can collectively outperform disconnected individuals ( 12 , 15 , 16 ) and inefficient networks ( 17 , 18 ), as people learn from each other and better solutions spread rapidly.…”

The balance of autonomous and centralized control in scheduling problems

“…In Shore et al (2015) the dependence of the problem solving perfomance on network architecture has been studied in more detail. Recently, in Becker et al (2017) the impact of social networks on the quality of a collective estimation challenge has been analyzed.…”

Collective Problem-Solving of Groups Across Tasks of Varying Complexity

“…Second, CSOPs are an abstraction of many resource allocation and optimization problems; thus, they capture important features of real-world group problem-solving exercises without requiring participants to have specialized skills. Third, as with other complex problems ( 31 ) , the payoff function for CSOPs can be described as a "rugged landscape" characterized by many locally optimal but globally suboptimal solutions. Correspondingly, CSOPs are amenable to potentially many solution strategies and styles, where no single strategy is universally superior ( 32 ) .…”