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Varieties of Capitalism and Investments in Human Capital

Authors

  • MARC GOERGEN,

  • CHRIS BREWSTER,

  • GEOFFREY WOOD,

  • ADRIAN WILKINSON

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    •  The authors’ affiliations are, respectively, Professor of Finance at the Cardiff Business School and Research Associate at the European Corporate Governance Institute (ECGI). E-mail: goergenm@cf.ac.uk; Professor of International HRM, Henley Business School, University of Reading. E-mail: c.j.brewster@henley.reading.ac.uk; Professor of HRM at the University of Sheffield Management School, all in the UK. E-mail: g.t.wood@sheffield.ac.uk; Professor and Director of the Centre of Work, Organisation and Wellbeing, Griffith University, Australia. E-mail: adrian.wilkinson@griffith.edu.au. The authors wish to thank their colleagues from across Europe who were involved in the collection of the Cranet data and Cranfield School of Management who coordinate the network. They are also grateful to participants at a conference on the role of financial institutions in corporate governance organized by the Wharton Financial Institutions Center, the Amsterdam Center for Research in International Finance (CIFRA), and sponsored in part by the Millstein Center for Corporate Governance and Performance (MCCGP) at the Yale School of Management. In particular, they would like to thank Franklin Allen, Pepper Culpepper, Peter Gourevitch, Eugene Kandel, and Kenichi Ueda. Finally, we are extremely grateful to the insightful comments of the anonymous referees.


Abstract

This paper explores the relationship between national institutional archetypes and investments in training and development. A recent trend within the literature on comparative capitalism has been to explore the nature and extent of heterogeneity within the coordinated market economies (CMEs) of Europe. Based on a review of the existing comparative literature on training and development, and comparative firm-level survey evidence of differences in training and development practices, we both support and critique existing country clusters and argue for a more nuanced and flexible categorization.

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