Journal article
Supply chain disruption propagation: a systemic risk and normal accident theory perspective
International journal of production research, Vol.56(1-2), pp.43-59
01/17/2018
DOI: 10.1080/00207543.2017.1355123
Abstract
When a disruption occurs in a firm, its effects are often felt throughout the supply chain. As supply chains expand globally and companies pursue velocity and efficiency, the probability of disruptions propagating throughout a chain grows. In this paper, we employ a qualitative, grounded theory case study approach to help understand what drives supply chain disruption propagation and to provide theoretical insights into this emerging area. For a more complete perspective, we study three interconnected tiers in seven unique supply chains. Each supply chain triad consists of (1) a focal firm (a manufacturer), (2) a supplier to the focal firm and (3) a customer of the focal firm allowing us to gain perspective from three levels in multiple supply chains. Three aggregate dimensions are defined which help explain the propagation of supply chain disruptions: the nature of the disruption, structure and dependence, and managerial decision-making. Within these dimensions, six themes are identified giving an increased level of granularity into disruption propagation: correlation of risk, compounding effects, cyclical linkages, counterparty risk, herding and misaligned incentives. Organisations should consider these themes and their interactions to effectively deal with supply chain disruptions.
Details
- Title: Subtitle
- Supply chain disruption propagation: a systemic risk and normal accident theory perspective
- Creators
- Kevin P Scheibe - Iowa State UniversityJennifer Blackhurst - University of Iowa
- Resource Type
- Journal article
- Publication Details
- International journal of production research, Vol.56(1-2), pp.43-59
- Publisher
- Taylor & Francis
- DOI
- 10.1080/00207543.2017.1355123
- ISSN
- 0020-7543
- eISSN
- 1366-588X
- Language
- English
- Date published
- 01/17/2018
- Academic Unit
- Business Analytics; Bus Admin Graduate Programs
- Record Identifier
- 9984201529602771
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