Complexity Economics Seminar (in person and online)


Description

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What a firm does is more revealing than how much it makes, but many quantitative metrics for firms are economic. Here, we characterize what firms read, their information footprint, using a data set of hundreds of millions of records of news articles accessed by employees in millions of firms. We relate a firm's information footprint with economic variables, showing that the former grows superlinearly with the latter. This exaggerates the classic Zipf's law inequality in the economic size of firms and reveals an economy of scale with respect to information. Second, we discover that the reading habits of firms are of limited diversity. Firms above a certain size reduce the relative diversity of information they consume, indicating the sudden onset of a coordination cost. Third, we reconstruct the topic graph firms inhabit and propose a simple model of firm growth in this space. Firms adhere to a mixed strategy of local exploration and recurrent exploitation on the topic graph. This strategy is costly, and we predict that firms consume a prodigious amount of information over their lifetime because they cumulatively add to their information portfolio instead of diversifying. This shows that the costs of information and the structure of the space of ideas provide an illuminating perspective on firm growth.


About the speaker

Eddie Lee is an Austrian Science Fund ESPRIT Fellow at the Complexity Science Hub Vienna. After earning a PhD in Theoretical Physics from Cornell University in 2019, he was a postdoctoral fellow at the Santa Fe Institute before moving to Vienna. His work is highly interdisciplinary, and he studies the role of information in bio-social systems such as in the neural connectome, social cascades, niche construction, voting, and innovation/obsolescence dynamics.


Registration

Please register to attend online or in person by filling in the form at https://oxford.onlinesurveys.a...

This event will be in HYBRID format but will not be recorded. For more information, please email complexity@inet.ox.ac.uk if you need further information.

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