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Fraught with tension? A machine-learning approach to termination traits of public corporations in English and German local governments

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  • Maike Rackwitz

Abstract

Corporatization has gained scholarly attention in recent years, yet little is known regarding why many corporations are eventually terminated, and what happens to their form and functions thereafter. Reinternalizing services is one option local governments may pursue. This paper focuses on the impact of tensions (systemic contradictions) on this final resolution reached: Do local governments choose or refuse reinternalization? Conducting machine learning, I predict termination outcomes based on an original dataset of 244 ceased English and German companies (2010–2020). The results show that macrosystemic tensions are more relevant for resourcing decisions and reinternalization is less likely to be caused by formal ownership issues.

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  • Maike Rackwitz, 2024. "Fraught with tension? A machine-learning approach to termination traits of public corporations in English and German local governments," Public Management Review, Taylor & Francis Journals, vol. 26(6), pages 1631-1657, June.
    • Handle: RePEc:taf:rpxmxx:v:26:y:2024:i:6:p:1631-1657
    DOI: 10.1080/14719037.2023.2204323
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