Following The Information Footprint Of Firms

15 Pages Posted: 7 Dec 2022

See all articles by Edward Lee

Edward Lee

Complexity Science Hub Vienna

Alan Kwan

The University of Hong Kong

Rudolf Hanel

affiliation not provided to SSRN

Anjali Bhatt

affiliation not provided to SSRN

Frank Neffke

Complexity Science Hub Vienna

Date Written: October 14, 2022

Abstract

What a firm does is more revealing than how much it makes, but firms are often described with metrics for economic size. Instead, we characterize what firms know in terms of what they read, the information footprint, using a data set of hundreds of millions of records of news articles accessed by employees in millions of firms. We discover that the reading habits of firms are of limited diversity. This observation suggests that information constraints act on firms. To understand how, 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 reconstruct the topic space firms inhabit, finding that the space resembles a tangled "hairball" with a few dense knots of topics and many specialized strands sticking out. Some of the topics are ubiquitous, indicating inescapable demand regardless of firm size. Finally, we connect these pieces in a model of how firms grow in the space of topics. We show that diversity in firm reading habits can be explained by a mixed strategy of local exploration and recurrent exploitation on the topic graph. This shows that the constraints that the space of ideas imposes on firm growth provide a useful and new perspective on firm development.

Keywords: firms, collective knowledge, information, scaling, reading

Suggested Citation

Lee, Edward and Kwan, Alan and Hanel, Rudolf and Bhatt, Anjali and Neffke, Frank, Following The Information Footprint Of Firms (October 14, 2022). Available at SSRN: https://ssrn.com/abstract=4247351 or http://dx.doi.org/10.2139/ssrn.4247351

Edward Lee (Contact Author)

Complexity Science Hub Vienna ( email )

Josefstädter Straße 39
Vienna
Austria

HOME PAGE: http://https://eddielee.co

Alan Kwan

The University of Hong Kong ( email )

Pokfulam Road
Hong Kong, Pokfulam HK
China

Rudolf Hanel

affiliation not provided to SSRN

Anjali Bhatt

affiliation not provided to SSRN

Frank Neffke

Complexity Science Hub Vienna ( email )

Josefstädter Straße 39
Vienna
Austria

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