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Managing uncertainty – an empirical analysis of supply chain risk management in small and medium-sized enterprises

Thun, Jörn-Henrik, Drüke, Martin, Hoenig, Daniel·2011·International Journal of Production Research

Abstract

Uncertainty and the need for lean processes forces manufacturing companies to intensively deal with supply chain risk issues. The purpose of this article is the empirical investigation of supply chain risk management in small and medium-sized enterprises (SMEs). Using data from 67 manufacturing plants from the German automotive industry, differences between large-scale enterprises and SMEs are identified. After addressing the general question whether SMEs consider their supply chain as vulnerable, the key drivers of supply chain risks are analysed. Furthermore, instruments of supply chain risk management are investigated in terms of their suitability for creating a resilient supply chain by comparing SMEs with large-scale companies. Finally, this article examines existing differences with respect to how companies deal with risk. The analyses show that SMEs predominantly focus on reactive instruments that absorb risks through the creation of redundancies instead of preventing risks.

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Metadata

Authors
Thun, J.-H., Drüke, M., & Hoenig, D.
Venue
International Journal of Production Research
Published
2011-09-15
Volume
49
Issue
18
Pages
5511-5525
ISSN
  • 0020-7543 (ISSN-L)
  • 1366-588X
OpenAlex
W2110746978
Cited by
185
References
0
FWCI
16.97
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Managing uncertainty – an empirical analysis of supply chain risk management in small and medium-sized enterprises. https://app.cochat.ai/papers/10.1080/00207543.2011.563901
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Thun, J.-H., Drüke, M., & Hoenig, D. (2011). Managing uncertainty – an empirical analysis of supply chain risk management in small and medium-sized enterprises. International Journal of Production Research. https://doi.org/10.1080/00207543.2011.563901

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.