Conspiracy of Corporate Networks in Corruption Scandals

Corruption in public procurement transforms state institutions into private entities where public resources get diverted for the benefit of a few. On this matter, much of the discussion centers on the legal fulfillment of the procurement process, while there are fewer formal analyses related to the...

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Main Authors: J. R. Nicolás-Carlock, I. Luna-Pla
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-06-01
Series:Frontiers in Physics
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fphy.2021.667471/full
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spelling doaj-76197fe5f36746ad896cd1e3978cf75e2021-06-09T06:41:46ZengFrontiers Media S.A.Frontiers in Physics2296-424X2021-06-01910.3389/fphy.2021.667471667471Conspiracy of Corporate Networks in Corruption ScandalsJ. R. Nicolás-CarlockI. Luna-PlaCorruption in public procurement transforms state institutions into private entities where public resources get diverted for the benefit of a few. On this matter, much of the discussion centers on the legal fulfillment of the procurement process, while there are fewer formal analyses related to the corporate features which are most likely to signal organized crime and corruption. The lack of systematic evidence on this subject has the potential to bias our understanding of corruption, making it overly focused on the public sector. Nevertheless, corruption scandals worldwide tell of the importance of taking a better look at the misuse and abuse of corporations for corrupt purposes. In this context, the research presented here seeks to contribute to the understanding of the criminal conspiracy of companies involved in public procurement corruption scandals under a network and complexity science perspective. To that end, we make use of a unique dataset of the corporate ownership and management information of four important and recently documented cases of corruption in Mexico, where hundreds of companies were used to embezzle billions of dollars. Under a bipartite network approach, we explore the relations between companies and their personnel (shareholders, legal representatives, administrators, and commissioners) in order to characterize their static and dynamic networked structure. In terms of organized crime and using different network properties, we describe how these companies connect with each other due to the existence of shared personnel with role multiplicity, leading to very different conspiracy networks. To best quantify this behavior, we introduce a heuristic network-based conspiracy indicator that together with other network metrics describes the differences and similarities among the networks associated with each corruption case. Finally, we discuss some public policy elements that might be needed to be considered in anti-corruption efforts related to corporate organized crime.https://www.frontiersin.org/articles/10.3389/fphy.2021.667471/fullcorruptionconspiracycorruption networkssocial network analysis (SNA)complex networkscomplex systems
collection DOAJ
language English
format Article
sources DOAJ
author J. R. Nicolás-Carlock
I. Luna-Pla
spellingShingle J. R. Nicolás-Carlock
I. Luna-Pla
Conspiracy of Corporate Networks in Corruption Scandals
Frontiers in Physics
corruption
conspiracy
corruption networks
social network analysis (SNA)
complex networks
complex systems
author_facet J. R. Nicolás-Carlock
I. Luna-Pla
author_sort J. R. Nicolás-Carlock
title Conspiracy of Corporate Networks in Corruption Scandals
title_short Conspiracy of Corporate Networks in Corruption Scandals
title_full Conspiracy of Corporate Networks in Corruption Scandals
title_fullStr Conspiracy of Corporate Networks in Corruption Scandals
title_full_unstemmed Conspiracy of Corporate Networks in Corruption Scandals
title_sort conspiracy of corporate networks in corruption scandals
publisher Frontiers Media S.A.
series Frontiers in Physics
issn 2296-424X
publishDate 2021-06-01
description Corruption in public procurement transforms state institutions into private entities where public resources get diverted for the benefit of a few. On this matter, much of the discussion centers on the legal fulfillment of the procurement process, while there are fewer formal analyses related to the corporate features which are most likely to signal organized crime and corruption. The lack of systematic evidence on this subject has the potential to bias our understanding of corruption, making it overly focused on the public sector. Nevertheless, corruption scandals worldwide tell of the importance of taking a better look at the misuse and abuse of corporations for corrupt purposes. In this context, the research presented here seeks to contribute to the understanding of the criminal conspiracy of companies involved in public procurement corruption scandals under a network and complexity science perspective. To that end, we make use of a unique dataset of the corporate ownership and management information of four important and recently documented cases of corruption in Mexico, where hundreds of companies were used to embezzle billions of dollars. Under a bipartite network approach, we explore the relations between companies and their personnel (shareholders, legal representatives, administrators, and commissioners) in order to characterize their static and dynamic networked structure. In terms of organized crime and using different network properties, we describe how these companies connect with each other due to the existence of shared personnel with role multiplicity, leading to very different conspiracy networks. To best quantify this behavior, we introduce a heuristic network-based conspiracy indicator that together with other network metrics describes the differences and similarities among the networks associated with each corruption case. Finally, we discuss some public policy elements that might be needed to be considered in anti-corruption efforts related to corporate organized crime.
topic corruption
conspiracy
corruption networks
social network analysis (SNA)
complex networks
complex systems
url https://www.frontiersin.org/articles/10.3389/fphy.2021.667471/full
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