A Simulation-based Analysis of Supply Chain Resilience

TitleA Simulation-based Analysis of Supply Chain Resilience
Publication TypeConference Paper
Year of Publication2015
AuthorsGüller, M, Koc, E, Henke, M, Noche, B, Hingst, L
EditorKersten, W, Blecker, T, Ringle, CM
Title of ProceedingsInnovations and Strategies for Logistics and Supply Chains
Volume20
Page533
Publisherepubli
Conference LocationHamburg
ISBN Number978-3-7375-7805-9
Other NumbersISSN (print) 2365-4430, ISSN (online) 2365-5070
KeywordsFlexibility, Simulation, Supply Chain Resiliency, Supply Contract
Abstract

The increased interest in supply chain risk management (SCRM) is not only a consequence
of recent natural disasters, but moreover the recognition that even small incidents
can have a severe impact on the entire supply chain (SC). Instead of making
high investments in eliminating every potential risk, it is much more appreciated to
incorporate the concept of resilience in supply chain design and operations that provides
the ability to reduce the consequences of disruptions and to reduce the time
to recover normal performance. However, as resilience significantly increases the
ability to adapt quickly and efficiently to changes in the environment, it comes along
with an increase in costs in most cases. Moreover, achieving resilience in supply
chains and agile response requires a holistic approach, which contributes to the
complexity of decision making processes in supply chains. Since most of the researches
has been discussed the resilience of supply chains from a qualitative point
of view in the literature, there is a lack of research concerning the resilience from a
quantitative perspective. In this context, the main purpose of this paper is to provide
a simulation-based decision support framework for assessing supply chain resilience
and evaluating the cost and resilience trade-off with different mitigation strategies
in an uncertain environment. The decision framework incorporates the supply chain
resilience metrics and argues their relationship to the impacts of those disruptions
on the performance and to the time required for recovery.

DOI10.15480/882.1264