Experimentalist systems in manufacturing multinationals: German automobile and machinery examples

Abstract

Purpose

The purpose of this paper is to apply experimentalist framework to understand self-optimizing efforts within German manufacturing multinationals. Benefits and characteristic obstacles to diffusion are discussed. Mechanisms for combatting obstacles are outlined.

Design/methodology/approach

Qualitative case studies, interview-based research, processual and reflexive action theory are applied to the governance of manufacturing-based multinational enterprises.

Findings

Uncertainty is an ineradicable element in multinational companies (MNC) FDI operations. Self-optimizing systems, many with an experimentalist character, are a pervasive form of response to this uncertainty. Obstacles to the diffusion and effective operation of self-optimization are chronic and, indeed, endogenously generated. But as a result, so are superordinate efforts to undercut the continuous emergence of obstacles. MNC development is, thus, characterized by continuous self-recomposition.

Research limitations/implications

Implication is that managers and management theorists should focus as much on the management of dynamic process and learning that results in the recomposition of institutional rules as they do on the constraining and enabling effects of those rules.

Practical implications

Superordinate mechanisms for the disruption of incipient insulation and exclusion are crucial for the implementation of successful experimentalist (learning) systems.

Social implications

Transparency, stakeholder involvement in MNC governance processes has positive implications for learning, innovation and competitiveness.

Originality/value

This paper presents the application of experimentalist learning theory to MNC global governance.

Citation

Herrigel, G.B. (2018), "Experimentalist systems in manufacturing multinationals: German automobile and machinery examples", Critical Perspectives on International Business, Vol. 14 No. 4, pp. 362-382. https://doi.org/10.1108/cpoib-10-2017-0063