Journal article
An Empirically Derived Framework of Global Supply Resiliency
Journal of business logistics, Vol.32(4), pp.374-391
12/2011
DOI: 10.1111/j.0000-0000.2011.01032.x
Abstract
In today's global business environment, supply chains have increased in both length and complexity. This increase in length and complexity coupled with a focus on improving efficiency, such as lean manufacturing practices, may lead to higher levels of supply chain risk where the likelihood of a disruption severely impacting supply chain performance increases. Resilient supply chains have been touted as a means to reduce the likelihood and severity of supply chain disruptions. However, there is little empirical evidence relative to the factors that contribute to or detract from supply resiliency. Using systems theory and the resource-based view of the firm as the theoretical underpinnings, this study provides an in-depth systematic investigation of supply resiliency. Adopting a theory-building approach based on a multi-industry empirical investigation, this study derives empirical generalizations linking 19 supply chain characteristics to supply resiliency. The study culminates in a framework that could be used to assess the level of resiliency in a supply base. Building on this framework, the study also provides a supply resiliency matrix that can be utilized to classify supply chains, or supply chains segments according to the level of resiliency realized. This article concludes by proposing several future research directions and issues that may be investigated in more detail. © Council of Supply Chain Management Professionals.
Details
- Title: Subtitle
- An Empirically Derived Framework of Global Supply Resiliency
- Creators
- Jennifer Blackhurst - Iowa State UniversityKaitlin S Dunn - Pennsylvania State UniversityChristopher W Craighead - Pennsylvania State University
- Resource Type
- Journal article
- Publication Details
- Journal of business logistics, Vol.32(4), pp.374-391
- Publisher
- Blackwell Publishing Ltd
- DOI
- 10.1111/j.0000-0000.2011.01032.x
- ISSN
- 0735-3766
- eISSN
- 2158-1592
- Number of pages
- 18
- Language
- English
- Date published
- 12/2011
- Academic Unit
- Business Analytics; Bus Admin Graduate Programs
- Record Identifier
- 9984201528602771
Metrics
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