{"title":"The General Ownership Structure of the European Aerospace Industry a Statistical and Network Analysis","authors":"L. Biggiero, Robert Magnuszewski","doi":"10.1142/s0219525921500120","DOIUrl":null,"url":null,"abstract":"In this paper, we investigate the ownership structure of the 3143 EU28 aerospace companies in 2019, and extend the analysis to the 2428 neighbor partners outside EU28 and/or aerospace. Different from the previous studies, we consider all equity capital flows regardless of their size, and their monetary value instead of the corresponding ownership share. We further innovate by applying new methods to measure degree of influence power and hierarchical structure. The resulting picture shows that between the pure EU28 aerospace companies: (i) ownership relationships concern only relatively few companies (10%), which trigger horizontal and vertical structures; (ii) density is extremely low; (iii) relationships are fully hierarchical with no cross-ownership; (iv) capital is seldom transferred across business groups; (v) most of the main topological parameters have a typically polarized scale-free structure. When including also the ownership neighbors, some of those traits change substantially: (i) the share of connected companies substantially grows up to 63%; (ii) size and length of the largest pyramidal structures will grow remarkably, reaching a top of 874 companies; (iii) the industry becomes a full small-world structure, thus allowing huge capital transfer across business groups. Finally, a dramatic financialization, meant as a pivotal and quantitatively heavy role of financial operators, emerges also as a clear characteristic of the extended network.","PeriodicalId":50871,"journal":{"name":"Advances in Complex Systems","volume":"15 1","pages":"2150012:1-2150012:47"},"PeriodicalIF":0.7000,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Complex Systems","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1142/s0219525921500120","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 2
Abstract
In this paper, we investigate the ownership structure of the 3143 EU28 aerospace companies in 2019, and extend the analysis to the 2428 neighbor partners outside EU28 and/or aerospace. Different from the previous studies, we consider all equity capital flows regardless of their size, and their monetary value instead of the corresponding ownership share. We further innovate by applying new methods to measure degree of influence power and hierarchical structure. The resulting picture shows that between the pure EU28 aerospace companies: (i) ownership relationships concern only relatively few companies (10%), which trigger horizontal and vertical structures; (ii) density is extremely low; (iii) relationships are fully hierarchical with no cross-ownership; (iv) capital is seldom transferred across business groups; (v) most of the main topological parameters have a typically polarized scale-free structure. When including also the ownership neighbors, some of those traits change substantially: (i) the share of connected companies substantially grows up to 63%; (ii) size and length of the largest pyramidal structures will grow remarkably, reaching a top of 874 companies; (iii) the industry becomes a full small-world structure, thus allowing huge capital transfer across business groups. Finally, a dramatic financialization, meant as a pivotal and quantitatively heavy role of financial operators, emerges also as a clear characteristic of the extended network.
期刊介绍:
Advances in Complex Systems aims to provide a unique medium of communication for multidisciplinary approaches, either empirical or theoretical, to the study of complex systems. The latter are seen as systems comprised of multiple interacting components, or agents. Nonlinear feedback processes, stochastic influences, specific conditions for the supply of energy, matter, or information may lead to the emergence of new system qualities on the macroscopic scale that cannot be reduced to the dynamics of the agents. Quantitative approaches to the dynamics of complex systems have to consider a broad range of concepts, from analytical tools, statistical methods and computer simulations to distributed problem solving, learning and adaptation. This is an interdisciplinary enterprise.