团队中相互知识的前因后果

Sinan Aral, E. Brynjolfsson, Marshall W. Van Alstyne
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引用次数: 8

摘要

关于团队表现的两种公认的文学流派之间存在着紧张关系。一种观点认为,具有不同背景、社会结构、知识和经验的团队更有效地发挥作用,因为他们能带来新的信息,解决同质个体无法解决的问题。相反,关于互知的文献认为,共享信息和经验对于团队成员之间的有效沟通、信任、理解和协调至关重要。此外,已经假设了相互信息和知识的几个不同的先决条件,这使得管理团队中的信息重叠变得困难。在本文中,我们使用了一个独特的数据集,从1382个高管招聘团队观察到的电子邮件内容和详细的会计数据,他们的生产力来检查共享与多样化信息的前因和绩效影响。我们发现了相互信息与团队生产力之间存在倒u型关系的明显证据。团队成员之间的大量信息重叠与更高的绩效相关,而相互信息太少或太多的极端情况会阻碍绩效。我们还发现,地理分散和社会网络距离是相互知识失效的强预测因子,而人口统计学差异和组织距离不能预测数据中的相互信息程度。我们的工作有助于汇集关于相互知识、信息多样性和团队绩效管理的不同文献流。
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Antecedents and Consequences of Mutual Knowledge in Teams
A tension exists between two well-established streams of literature on the performance of teams. One stream contends that teams with diverse backgrounds, social structures, knowledge, and experience function more effectively because they bring novel information to bear on problems that cannot be solved by groups of homogeneous individuals. In contrast, the literature on mutual knowledge contends that shared information and experience is essential to effective communication, trust, understanding and coordination among team members. Furthermore, several distinct antecedents of mutual information and knowledge have been hypothesized, making it difficult to manage information overlap in teams. In this paper, we use a unique data set of observed email content from 1382 executive recruiting teams and detailed accounting data on their productivity to examine both the antecedents and performance effects of shared versus diverse information. We find clear evidence of an inverted-U shaped relationship between mutual information and team productivity. A significant amount of information overlap among team members is associated with higher performance while extremes of too little or too much mutual information hamper performance. We also find that geographic dispersion and social network distance are strong predictors of mutual knowledge failures, while demographic dissimilarity and organizational distance do not predict the degree of mutual information in our data. Our work helps bring together the divergent streams of literature on mutual knowledge, information diversity, and the management of team performance.
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