Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/287136 
Authors: 
Year of Publication: 
2021
Citation: 
[Journal:] Journal of Management and Governance [ISSN:] 1572-963X [Volume:] 26 [Issue:] 2 [Publisher:] Springer US [Place:] New York, NY [Year:] 2021 [Pages:] 519-550
Publisher: 
Springer US, New York, NY
Abstract: 
This paper seeks to understand the structure of corporate networks in the period following the dissolution of Deutschland AG ("Germany Inc."). For this purpose, affiliation networks among chief executive officers (CEOs) that are based on common membership in various societal organizations will be examined. I apply an innovative mix of methods for studying a sample of CEOs from the 100 top companies in Germany in the 2010s. Based on social network analysis, I show that the overall affiliation network has all features of a small-world network, i.e., a high clustering coefficient and a short path length among the CEOs. The average degree of separation among German CEOs is only two steps. Another innovative contribution of this paper is its study of the linkage between affiliation network features and patterns of corporate recruitment. Using multiple correspondence analysis, I show that different subgroups of the overall affiliation network have their specific network characteristics and recruitment patterns. Within the network, managers from automotive and technical engineering often assume brokerage positions, while managers from the trade branch are largely isolated. This study shows that the affiliation networks and corporate recruitment patterns are interlinked; the transformation of corporate networks is a dynamic outcome of interrelations among different subgroups within the network, each with distinct educational, professional, and network characteristics.
Subjects: 
Corporate governance
Affiliation network
Small world network
Chief executive officers (CEOs)
Social network analysis
Germany
Multiple correspondence analysis
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.