Functional structure in production networks

Leiden Repository (Leiden University)

Abstract

Production networks are integral to economic dynamics, yet dis-aggregated network data on inter-firm trade is rarely collected and often proprietary. Here we situate company-level production networks within a wider space of networks that are different in nature, but similar in local connectivity structure. Through this lens, we study a regional and a national network of inferred trade relationships reconstructed from Dutch national economic statistics and re-interpret prior empirical findings. We find that company-level production networks have so-called functional structure, as previously identified in protein-protein interaction (PPI) networks. Functional networks are distinctive in their over-representation of closed squares, which we quantify using an existing measure called spectral bipartivity. Shared local connectivity structure lets us ferry insights between domains. PPI networks are shaped by complementarity, rather than homophily, and we use multi-layer directed configuration models to show that this principle explains the emergence of functional structure in production networks. Companies are especially similar to their close competitors, not to their trading partners. Our findings have practical implications for the analysis of production networks and give us precise terms for the local structural features that may be key to understanding their routine function, failure, and growth.

Authors 7

1. Carolina E. S. Mattsson corresponding Aachen Computational Network Science Lab Leiden Institute of Advanced Computer Science

   Leiden University

   Affiliation as printed

   Computational Network Science Lab, Leiden Institute of Advanced Computer Science, Leiden University, Leiden, Netherlands

   Network Science Institute, Boston, MA, United States

2. Frank W. Takes Aachen Computational Network Science Lab Leiden Institute of Advanced Computer Science

   Leiden University · University of Amsterdam

   Affiliation as printed

   CORPNET, University of Amsterdam, Amsterdam, Netherlands

   Computational Network Science Lab, Leiden Institute of Advanced Computer Science, Leiden University, Leiden, Netherlands

3. Eelke M. Heemskerk

   University of Amsterdam

   Affiliation as printed

   CORPNET, University of Amsterdam, Amsterdam, Netherlands

   Department of Political Science, University of Amsterdam, Amsterdam, Netherlands

4. Cees G. H. Diks

   Tinbergen Institute · University of Amsterdam

   Affiliation as printed

   Faculty Economics and Business, University of Amsterdam, Amsterdam, Netherlands

   Tinbergen Institute, Amsterdam, Netherlands

5. Gert Buiten

   Centraal Bureau voor de Statistiek

   Affiliation as printed

   Statistics Netherlands, The Hague, Netherlands

6. Albert Faber

   Ministry of Economic Affairs and Climate Policy

   Affiliation as printed

   Ministry of Economic Affairs & Climate, The Hague, Netherlands

7. Peter M. A. Sloot

   Nanyang Technological University · ITMO University · Complexity Science Hub · University of Amsterdam

   Affiliation as printed

   Complexity Institute, Nanyang Technological University, Singapore, Singapore

   Complexity Science Hub Vienna, Vienna, Austria

   Computational Science Lab, Faculty of Science, University of Amsterdam, Amsterdam, Netherlands

   Institute for Advanced Study, University of Amsterdam, Amsterdam, Netherlands

   National Center for Cognitive Research, ITMO University, Saint Petersburg, Russia