Accession Number:



Supply Chain Resilience: Development of a Conceptual Framework, an Assessment Tool and an Implementation Process

Descriptive Note:

Doctoral thesis

Corporate Author:


Personal Author(s):

Report Date:


Pagination or Media Count:



The business environment is always changing and change creates risk. Managing the risk of the uncertain future is a challenge that requires resilience the ability to survive, adapt and grow in the face of turbulent change. Academics and industry leaders have seen the need to supplement traditional risk management techniques with the concept of resilience that is better designed to cope with extreme complexities, unpredictable events and adaptive threats. However, without standardized definitions, accepted variables or measurement tools, supply chain resilience is merely a theoretical concept. This dissertation will explore the current thought on supply chain resilience and develop the construct into a managerial process for implementation. In Phase I, the Supply Chain Resilience Framework was developed to provide a conceptual framework based on extant literature and refined through a focus group methodology. Findings suggest that supply chain resilience can be assessed in terms of two dimensions vulnerabilities and capabilities. Research identified seven vulnerability factors composed of 40 specific attributes and 14 capability factors from 71 attributes that facilitate the measurement of resilience. Phase II created an assessment tool based on this framework the Supply Chain Resilience Assessment and Management SCRAMTM. Data gathered from seven global manufacturing supply chains was used to assess their current state of supply chain resilience. The tool was validated using a qualitative methodology comparing assessment scores to 1,369 items recorded from discussions of 14 recent disruptions. Phase III concluded the research project by identifying critical linkages between the inherent vulnerability factors and controllable capability factors.

Subject Categories:

  • Manufacturing and Industrial Engineering and Control of Production Systems

Distribution Statement: