The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Strategy and Irreversibility in Supplier Relations: The Case of the U.S. Automobile Industry
Abstract
The purchasing strategies of the dominant U.S. automakers form a topic neglected by both economists and business historians. The following article examines the automakers' changing relations with their suppliers throughout the twentieth century. Using the exit/voice paradigm, it establishes a framework that can account for both current and past strategies, even when they seem to contradict the logic of economic theory.
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Cites
Teece, D. J. (1986) · Research Policy · doi:10.1016/0048-7333(86)90027-2 · Cited by 7,842
Rosenberg, N. (1976) · doi:10.1017/cbo9780511561313 · Cited by 1,185
Cited by
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Adler, P. S. (2001) · Organization Science · doi:10.1287/orsc.12.2.215.10117 · Cited by 1,512
Outsourcing in a Global Economy
Grossman, G. M., & Helpman, E. (2005) · Review of Economic Studies · doi:10.1111/0034-6527.00327 · Cited by 920
Value chains, networks and clusters: reframing the global automotive industry
Sturgeon, T., Van Biesebroeck, J., & Gereffi, G. (2008) · Journal of Economic Geography · doi:10.1093/jeg/lbn007 · Cited by 885
Lazzarini, S. G., Miller, G. J., & Zenger, T. R. (2008) · Organization Science · doi:10.1287/orsc.1070.0336 · Cited by 141
Metadata
- Authors
- Helper, S.
- Venue
- Business History Review
- Publisher
- Cambridge University Press (CUP)
- Published
- 1991
- Volume
- 65
- Issue
- 4
- Pages
- 781-824
- ISSN
- 0007-6805 (ISSN-L)
- 2044-768X
- OpenAlex
- W2161058174
- Cited by
- 254
- References
- 2
- FWCI
- 1.61
- Type
- journal article
- Language
- en
- Open access
- closed
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- Helper, S. (1991). Strategy and Irreversibility in Supplier Relations: The Case of the U.S. Automobile Industry. Business History Review. https://doi.org/10.2307/3117265
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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.