Abstract
AbstractAccording to United Nations, corruption is a systemic and adaptive phenomenon that requires comprehensive and multidisciplinary approaches for its effective prevention and combat. However, traditional approaches lack the analytical tools to handle the structural and dynamical aspects that characterize modern social, political and technological systems where corruption takes place. On this matter, complex systems science has emerged as a comprehensive framework to study highly adaptive phenomena from natural to socio-technical settings. Thus, in this article we present an empirical approach to model corruption using the concepts and tools of complexity science, mainly, complex networks science. Under this framework, we describe a major corruption scandal that took place in Mexico involving a network of hundreds of shell companies used to embezzle billions of dollars. We describe the structure and dynamics of this corporate network using available information related to their personnel and the date of the companies’ creation. We measured some global parameters, such as density, diameter, average path length, and average degree in order to provide systematic evidence on which corporate characteristics are likely to signal corruption. Moreover, this analysis also provides an objective perspective of the systemic nature of events where companies are abused for corrupt purposes, and the shortcomings of reductionistic analyses. Major corruption scandals comprise both legal and illegal deeds, in addition to several parties acting simultaneously over extended time periods. As a whole, such scandals pose enormous challenges for the study of law and put the legal design of administrative and criminal controls to the test.
Funder
Universidad Nacional Autónoma de México
Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,Computer Networks and Communications,Multidisciplinary
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