|By:||Jesse Shore (Boston University – Department of Information Systems)
Ethan Bernstein (Harvard Business School, Organizational Behavior Unit)
David Lazer (Harvard University – Harvard Kennedy School (HKS))
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 structure 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 inconsistent conclusions about the value of network clustering. By adopting an experimental platform on which information was measured separately from solutions, we were able to reconcile past contradictions and clarify the effects of network clustering on problem-solving 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.
|Keywords:||networks, experiments, clustering, problem solving, exploration and exploitation, knowledge, information, communication, search|
==Notes by yinung==
從賽局理論的角度看, 集體決策較個人決策來得理性 (rational), 因其可避免認知錯誤與限制。
不過集體決策也因此不見得會提高社會福利 (集體決策比較 self-interest)
the optimal size of the group ( A useful starting point here is Forsyth’s (2006) work)
In this paper, we describe what economists have learned about differences between group and individual decision-making. This literature is still young, and in this paper, we will mostly draw on experimental work (mainly in the laboratory) that has compared individual decision-making to group decision-making, and to individual decision-making in situations with salient group membership. The bottom line emerging from economic research on group decision-making is that groups are more likely to make choices that follow standard game-theoretic predictions, while individuals are more likely to be influenced by biases, cognitive limitations, and social considerations. In this sense, groups are generally less “behavioral" than individuals. An immediate implication of this result is that individual decisions in isolation cannot necessarily be assumed to be good predictors of the decisions made by groups. More broadly, the evidence casts doubts on traditional approaches that model economic behavior as if individuals were making decisions in isolation.
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