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Inter-firm Networks pp 33–61Cite as

Overview on the EU28 Aerospace Industry Network and Its Neighbors

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Part of the Relational Economics and Organization Governance book series (REOG)

Abstract

This chapter outlines the main traits of the EU28 Aerospace Industry network (EASIN) and its neighbors in terms of the main statistical and structural features. We will provide the crucial data to have the basic idea of the importance of this industry in terms of turnover, employees, equity capital and assets, as well in geographical and structural terms. We will show the distributions of both the connected and the isolated companies that operate within this industry and the efforts of people-based coordination that the former employ. We will further present a precise quantitative relevance the three types of coordination, which will be deepened in the following chapters. Finally, we will give the essential data about the two types of coordinators who issue those three types: managers and directors.

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Notes

  1. 1.

    This first section of overview draws mostly from Alfonso-Gil (2007), Biggiero & Angelini (2015), Biggiero & Magnuszewski (2021), Giuri et al. (2007).

  2. 2.

    We address the reader to the Methodological Appendix to know how HHI is calculated and normalized. Anyway, see Curry & George (1983) and Tirole (1988).

  3. 3.

    Besides the partially different samples, part of the discrepancy could be due to the fact that we could apply the calculation only to those 40% of companies for whom we have TURN (turnover or operating revenues) data.

  4. 4.

    The values in brackets in the tables indicate the % of companies, out of total companies in that specific country, for which the data of that variable are available. As it can be seen, the situation changes considerably per variable and per country: the worst degree of reliability occurs for cash flow where for two key-players like the Netherlands and the UK available data concern only 3 and 11% of companies, respectively.

  5. 5.

    A further problem in comparing these and other sources’ data is that related to the degree of diversification of some companies—especially, but not exclusively, the largest ones—into other sectors. Indeed, it is possible that data on which Aerospace and Defense Industries Association and EU Commission built their statistics do take into account only the Aerospace part of such companies, while Orbis (the database from where our data come from—see Methodological Appendix) in no way does such a distinction.

  6. 6.

    All abbreviations are explained in the list of abbreviations at the beginning of the book.

  7. 7.

    Though the term “capital” could be referred to many firm’s variables, in this paper, it is referred only to equity capital and its shares represent ownership links. Of course, in case that a company is self-owned, its entire capital is not shared with any other company (while it could be with single individuals), thus without any in- or out-flow of capital.

  8. 8.

    We remind that we chose to assimilate all executives to managers to simplify the analysis, which otherwise would have to consider six types of relationships. Further, this choice is legitimate by the fact that executives involved in inter-firm relationships are, in this industry, anyway very few: about few dozens.

  9. 9.

    The reason is that, in the binary ALL version, if two companies had both a DINT and a BINT link, only one link would be considered in the end—its either companies are connected at all or not, does not matter in how many ways, in consequence only one of the links is considered dropping the other. Therefore, the total number of binary links of the ALL version is somehow underestimated. In the present tab, we decided, for the purpose of correspondence, to keep the values of binary links that result in the network outline tabs of Chaps. 4, 5, 6 and 7, but also to add a column Sum which shows sums of networks’ binary absolute density—which we then use to show distribution of networks. Additionally, the M2M and D2D networks’ links are symmetric, and thus if they were treated as traditionally undirected those numbers would be halved, see the Methodological Appendix for more details. We also remind, that links of MC in the ALL networks and sum of links of all individual MCs put together are two entirely different things, creating different structures and so different numbers of nodes and links.

  10. 10.

    We provide here additional information that cannot be extracted by the reader himself from the attached tables.

  11. 11.

    To explain differences in numbers compared to the EU Commission, please consider the differences in interpreting what an Aerospace Industry actually is and its definition and fact that apparently our study got a broader definition of it.

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  1. University of L’Aquila, L’Aquila, Italy

    Lucio Biggiero & Robert Magnuszewski

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  1. Lucio Biggiero
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Correspondence to Lucio Biggiero .

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Biggiero, L., Magnuszewski, R. (2023). Overview on the EU28 Aerospace Industry Network and Its Neighbors. In: Inter-firm Networks. Relational Economics and Organization Governance. Springer, Cham. https://doi.org/10.1007/978-3-031-17389-9_3

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