Network Structure and Performance
提出一个理论，将个人的网络结构（连接数量与聚类程度）与生产率和收入联系起来，并应用于解释性别绩效差异，发现男性在不确定性高的环境中表现更好。
Abstract We develop a theory that links individuals’ network structure to their productivity and earnings. While a higher degree leads to better access to information, more clustering leads to higher peer pressure. Both information and peer pressure affect effort in a model of team production, with each being beneficial in a different environment. We find that information is particularly valuable under high uncertainty, whereas peer pressure is more valuable in the opposite case. We apply our theory to gender disparities in performance. We document the novel fact that men establish more connections (a higher degree) whereas women possess denser networks (a higher clustering coefficient). We therefore expect men to outperform women in jobs that are characterised by high uncertainty in project outcomes and earnings. We provide suggestive evidence that supports our predictions.