Network Structure & Information Advantage

We investigate the long held but empirically untested assumption that diverse networks drive performance by providing access to novel information. We build and validate an analytical model of information diversity, develop theory linking network structure to the distribution of novel information among actors and their performance, and test our theory using a unique ten month panel of email communication patterns, message content and performance data from a medium sized executive recruiting firm. While our theory and results demonstrate that network structures predict performance due to their impact on access to information, we also find important theoretically driven non-linearities in these relationships. Novel and diverse information are increasing in network size and network diversity, but with diminishing marginal returns. There are also diminishing marginal productivity returns to novel information, consistent with theories of cognitive capacity, bounded rationality, and information overload. Network diversity contributes to performance even when controlling for the performance effects of novel information, suggesting additional benefits to diverse networks beyond those conferred through information advantage. Our theory and results suggest subtle nuances in relationships between networks, information and economic performance, and the methods and tools developed are replicable, opening a new line of inquiry into these relationships.