Supply chain risk and resilience: theory building through structured experiments and simulation
被引:155
作者:
Macdonald, John R.
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机构:
Colorado State Univ, Dept Management, Ft Collins, CO 80523 USAColorado State Univ, Dept Management, Ft Collins, CO 80523 USA
Macdonald, John R.
[1
]
Zobel, Christopher W.
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机构:
Virginia Polytech Inst & State Univ, Dept Business Informat Technol, Blacksburg, VA 24061 USAColorado State Univ, Dept Management, Ft Collins, CO 80523 USA
Zobel, Christopher W.
[2
]
Melnyk, Steven A.
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机构:
Michigan State Univ, Dept Supply Chain Management, E Lansing, MI 48824 USAColorado State Univ, Dept Management, Ft Collins, CO 80523 USA
Melnyk, Steven A.
[3
]
Griffis, Stanley E.
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机构:
Michigan State Univ, Dept Supply Chain Management, E Lansing, MI 48824 USAColorado State Univ, Dept Management, Ft Collins, CO 80523 USA
Griffis, Stanley E.
[3
]
机构:
[1] Colorado State Univ, Dept Management, Ft Collins, CO 80523 USA
[2] Virginia Polytech Inst & State Univ, Dept Business Informat Technol, Blacksburg, VA 24061 USA
[3] Michigan State Univ, Dept Supply Chain Management, E Lansing, MI 48824 USA
The research literature of supply chain risk and resilience is at a critical developmental stage. Studies have established the importance of these topics both to researchers and practitioners. They also have identified factors contributing to risk, the impact of risk and disruptions on performance, and the strategies and tactics used to build the capacity for supply chain resilience. Although these efforts can provide support for constructing a theory of risk and resilience, researchers are currently restricted in their ability to build such a theory by the difficulty of collecting the necessary data. This paper contributes to this literature development effort by summarising prior research reviews and developing a three-component framework aimed at helping researchers to build better theories. This is accomplished through combining structured experimental design with discrete-event simulations of supply chains. The result is a methodology that allows researchers to develop better understanding of the factors that link a disruption to its impact on supply chain performance through both direct and interaction effects. Following the methodology development, the paper concludes with an example using the factors of shock interarrival time, supply chain connectivity and buffer stocks to illustrate the potential for contributing to the theory-building process.
机构:
Iowa State Univ, Coll Business, Supply Chain & Informat Syst Dept, Ames, IA 50011 USAIowa State Univ, Coll Business, Supply Chain & Informat Syst Dept, Ames, IA 50011 USA
Blackhurst, Jennifer
;
Dunn, Kaitlin S.
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机构:
Penn State Univ, Smeal Coll Business, University Pk, PA 16802 USAIowa State Univ, Coll Business, Supply Chain & Informat Syst Dept, Ames, IA 50011 USA
Dunn, Kaitlin S.
;
Craighead, Christopher W.
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机构:
Penn State Univ, Smeal Coll Business, University Pk, PA 16802 USAIowa State Univ, Coll Business, Supply Chain & Informat Syst Dept, Ames, IA 50011 USA
机构:
Iowa State Univ, Coll Business, Supply Chain & Informat Syst Dept, Ames, IA 50011 USAIowa State Univ, Coll Business, Supply Chain & Informat Syst Dept, Ames, IA 50011 USA
Blackhurst, Jennifer
;
Dunn, Kaitlin S.
论文数: 0引用数: 0
h-index: 0
机构:
Penn State Univ, Smeal Coll Business, University Pk, PA 16802 USAIowa State Univ, Coll Business, Supply Chain & Informat Syst Dept, Ames, IA 50011 USA
Dunn, Kaitlin S.
;
Craighead, Christopher W.
论文数: 0引用数: 0
h-index: 0
机构:
Penn State Univ, Smeal Coll Business, University Pk, PA 16802 USAIowa State Univ, Coll Business, Supply Chain & Informat Syst Dept, Ames, IA 50011 USA