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The antecedents of supply chain agility of a firm: Scale development and model testing
Abstract
In a constantly changing global competitive environment, an organization's supply chain agility directly impacts its ability to produce, and deliver innovative products to their customers in a timely and cost effective manner. While the beneficial impact of supply chain agility is generally acknowledged, very little research exists to date addressing how an organization can achieve supply chain agility. This study first presents a framework of an organization's supply chain process flexibilities as an important antecedent of its supply chain agility, and then establishes the key factors that determine the flexibility attributes of the three critical processes of the supply chain—procurement/sourcing, manufacturing, and distribution/logistics. Using empirical data, we develop flexibility and agility scales related to our supply chain agility model, and then test the model. Findings reveal that supply chain agility of a firm is directly and positively impacted by the degree of flexibility present in the manufacturing and procurement/sourcing processes of the supply chain; while it is indirectly impacted by the level of flexibility within its distribution/logistics process. The results also support our view that a firm's supply chain agility is impacted by the synergy among the three process flexibilities in its internal supply chain.
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Cites
Structural equation modeling in practice: A review and recommended two-step approach
Anderson, J. C., & Gerbing, D. W. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.3.411 · Cited by 41,941
Estimating Nonresponse Bias in Mail Surveys
Armstrong, J. S., & Overton, T. S. (1977) · Journal of Marketing Research · doi:10.2307/3150783 · Cited by 12,222
Estimating nonresponse bias in mail surveys
Armstrong, J. S., & Overton, T. S. (1977) · Journal of Marketing Research · doi:10.1177/002224377701400320 · Cited by 10,390
Moore, G. C., & Benbasat, I. (1991) · Information Systems Research · doi:10.1287/isre.2.3.192 · Cited by 9,150
A Beginner's Guide to Structural Equation Modeling: Fourth Edition
Schumacker, R. E., & Lomax, R. G. (2015) · doi:10.4324/9781315749105 · Cited by 6,604
An updated paradigm for scale development incorporating unidimensionality and its assessment
Gerbing, D. W., & Anderson, J. C. (1988) · Journal of Marketing Research · doi:10.1177/002224378802500207 · Cited by 6,293
A Beginner's Guide to Structural Equation Modeling
Schumacker, R. E., & Lomax, R. G. (2004) · doi:10.4324/9781410610904 · Cited by 6,235
Reliability of Nominal Data Based on Qualitative Judgments
Perreault, W. D., & Leigh, L. E. (1989) · Journal of Marketing Research · doi:10.2307/3172601 · Cited by 1,575
Cited by
Eckstein, D., Goellner, M., Blome, C., & Henke, M. (2015) · International Journal of Production Research · doi:10.1080/00207543.2014.970707 · Cited by 581
Dubey, R., Gunasekaran, A., & Childe, S. J. (2019) · Management Decision · doi:10.1108/md-01-2018-0119 · Cited by 480
Altay, N., Gunasekaran, A., Dubey, R., & Childe, S. J. (2018) · Production Planning & Control · doi:10.1080/09537287.2018.1542174 · Cited by 426
Kim, M., & Chai, S. (2017) · International Journal of Production Economics · doi:10.1016/j.ijpe.2017.02.007 · Cited by 367
Delic, M., & Eyers, D. R. (2020) · International Journal of Production Economics · doi:10.1016/j.ijpe.2020.107689 · Cited by 325
Metadata
- Authors
- Swafford, P. M., Ghosh, S., & Murthy, N.
- Venue
- Journal of Operations Management
- Publisher
- Wiley
- Published
- 2005-07
- Volume
- 24
- Issue
- 2
- Pages
- 170-188
- ISSN
- 0272-6963 (ISSN-L)
- 1873-1317
- OpenAlex
- W2048413439
- Cited by
- 1,001
- References
- 8
- FWCI
- 27.59
- Type
- journal article
- Language
- en
- Open access
- closed
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- Swafford, P. M., Ghosh, S., & Murthy, N. (2006). The antecedents of supply chain agility of a firm: Scale development and model testing. Journal of Operations Management. https://doi.org/10.1016/j.jom.2005.05.002
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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