The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
Supply chain variability, organizational structure, and performance: The moderating effect of demand unpredictability
Abstract
Supply chain process variability is the level of inconsistency, or volatility, in the flow of goods into, through, and out of a firm. The research investigates the links among organizational structure (formalization and integration), supply chain process variability, and performance as moderated by environmental uncertainty. We found that in a predictable demand environment, only formal control affects supply chain process variability, leading to improved financial results; but in an unpredictable demand environment, only cross‐functional integration affects supply chain process variability, leading to improved financial performance. We also examined whether supply chain process variability is a complete or partial mediator of the relationship between organizational structure and performance, and found that: (1) in a predictable demand environment, supply chain process variability completely mediates the relationship between formal control and performance and (2) in an unpredictable demand environment, supply chain process variability partially mediates the relationship between integration and performance. Supply chain process variability has an inverse relationship with financial performance, regardless of the demand environment; and organizational structure provides managers with the mechanisms to mitigate this variability's detrimental impact on financial performance.
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Herne, H., Cooley, W. W., & Lohnes, P. R. (1973) · Journal of the Royal Statistical Society. Series A (General) · doi:10.2307/2344428 · Cited by 35,697
Exploration and Exploitation in Organizational Learning
March, J. G. (1991) · Organization Science · doi:10.1287/orsc.2.1.71 · Cited by 21,942
(1997) · Chemometrics in Environmental Analysis · doi:10.1002/352760216x.ch5 · Cited by 18,653
Toward a knowledge-based theory of the firm
Grant, R. M. (1996) · Strategic Management Journal · doi:10.1002/smj.4250171110 · Cited by 16,157
Deming, W. E. (1982) · Medical Entomology and Zoology · Cited by 7,297
Burns, T., & Stalker, G. M. (1994) · doi:10.1093/acprof:oso/9780198288787.001.0001 · Cited by 7,250
LISREL 7 : user's reference guide
Jöreskog, K. G., & Sörbom, D. (1989) · Medical Entomology and Zoology · Cited by 6,783
The Economics of Organization: The Transaction Cost Approach
Williamson, O. E. (1981) · American Journal of Sociology · doi:10.1086/227496 · Cited by 6,438
Information Distortion in a Supply Chain: The Bullwhip Effect
Lee, H. L., Padmanabhan, V., & Whang, S. (1997) · Management Science · doi:10.1287/mnsc.43.4.546 · Cited by 4,698
Organizational Strategy, Structure, and Process
Miles, R. E., Snow, C. C., Meyer, A. D., & Coleman, H. J. (1978) · Academy of Management Review · doi:10.5465/amr.1978.4305755 · Cited by 4,527
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Firm's resilience to supply chain disruptions: Scale development and empirical examination
Ambulkar, S., Blackhurst, J., & Grawe, S. (2015) · Journal of Operations Management · doi:10.1016/j.jom.2014.11.002 · Cited by 1,400
Wong, C. Y., Boon‐itt, S., & Wong, C. W. Y. (2011) · Journal of Operations Management · doi:10.1016/j.jom.2011.01.003 · Cited by 1,083
On Theory in Supply Chain Uncertainty and its Implications for Supply Chain Integration
Flynn, B. B., Koufteros, X., & Lu, G. (2016) · Journal of Supply Chain Management · doi:10.1111/jscm.12106 · Cited by 357
Data-driven supply chain capabilities and performance: A resource-based view
Yu, W., Chavez, R., Jacobs, M. A., & Feng, M. (2018) · Transportation Research Part E: Logistics and Transportation Review · doi:10.1016/j.tre.2017.04.002 · Cited by 300
Chuang, H. H., Oliva, R., & Heim, G. R. (2019) · Production and Operations Management · doi:10.1111/poms.13055 · Cited by 101
Metadata
- Authors
- Germain, R., Claycomb, C., & Dröge, C.
- Venue
- Journal of Operations Management
- Publisher
- Wiley
- Published
- 2007-10-13
- Volume
- 26
- Issue
- 5
- Pages
- 557-570
- ISSN
- 0272-6963 (ISSN-L)
- 1873-1317
- OpenAlex
- W1976605938
- Cited by
- 268
- References
- 51
- FWCI
- 14.15
- Type
- journal article
- Language
- en
- Open access
- closed
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- Germain, R., Claycomb, C., & Dröge, C. (2008). Supply chain variability, organizational structure, and performance: The moderating effect of demand unpredictability. Journal of Operations Management. https://doi.org/10.1016/j.jom.2007.10.002
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.