Resilience definitions in logistics and supply chain management research
| Source | Definition/understanding |
|---|---|
| Brandon-Jones et al. (2014, p. 58) | Supply chain resilience is defined as the ability of a system to return to its original state within an acceptable period of time after being disturbed |
| Ponomarov and Holcomb (2009, p. 131) | The adaptive capability of the supply chain to prepare for unexpected events, respond to disruptions and recover from them by maintaining continuity of operations at the desired level of connectedness and control over structure and function |
| Sheffi (2005, p. 2) | In the corporate world, resilience refers to the ability of a company to bounce back from a large disruption – this includes, for instance, the speed with which it returns to normal performance levels (production, services, fill rate, etc.) |
| Tukamuhabwa et al. (2015, p. 8) | The adaptive capability of a supply chain to prepare for and/or respond to disruptions, to make a timely and cost-effective recovery, and therefore progress to a post-disruption state of operations – ideally, a better state than prior to the disruption |
| Definition/understanding | |
|---|---|
| Supply chain resilience is defined as the ability of a system to return to its original state within an acceptable period of time after being disturbed | |
| The adaptive capability of the supply chain to prepare for unexpected events, respond to disruptions and recover from them by maintaining continuity of operations at the desired level of connectedness and control over structure and function | |
| In the corporate world, resilience refers to the ability of a company to bounce back from a large disruption – this includes, for instance, the speed with which it returns to normal performance levels (production, services, fill rate, etc.) | |
| The adaptive capability of a supply chain to prepare for and/or respond to disruptions, to make a timely and cost-effective recovery, and therefore progress to a post-disruption state of operations – ideally, a better state than prior to the disruption |