Mattsson, Carolina E S; Takes, Frank W; Heemskerk, Eelke M; Diks, Cees; Buiten, Gert; Faber, Albert; Sloot, Peter M. A. Functional structure in production networks Journal Article In: Frontiers of Big Data, vol. 4, no. 666712, 2021. @article{Sloot2021,
title = {Functional structure in production networks},
author = {Carolina E S Mattsson and Frank W Takes and Eelke M Heemskerk and Cees Diks and Gert Buiten and Albert Faber and Peter M.A. Sloot },
url = {doi:10.3389/fdata.2021.666712
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8176009/
},
doi = {10.3389/fdata.2021.666712},
year = {2021},
date = {2021-05-21},
journal = {Frontiers of Big Data},
volume = {4},
number = {666712},
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.},
keywords = {bipartivity, complexity economics, economic statistics, functional networks, inter-firm networks, production networks, trade linkages},
pubstate = {published},
tppubtype = {article}
}
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. |