Articles
DOI DOI: 10.5281/zenodo.18442616

Supply Chain Resilience Metrics: Optimization under Multi-Risk Shocks

Mehmet A. Begen1
  1. 1 Western University, Ivey Business School, London, Canada

Abstract

Background: Modern supply chains are exposed to multi-risk shocks that
interact across demand, supply, logistics, finance, and cyber domains. These
interactions challenge resilience scorecards that rely on isolated indicators.
Methods: This review synthesizes definitions of supply chain resilience, operational
resilience metrics, and robust and risk-averse optimization frameworks. We develop
a measurement-to-decision pipeline that links stress scenarios to policy choices.
Results: We identify a compact and operationally meaningful metric set—time-to-survive
(TTS), time-to-recover (TTR), service continuity, and cost-to-serve—and show how these
metrics can be embedded in robust, minimax, and CVaR-based optimization formulations.
We describe how structured multi-risk stress scenarios translate metrics into decisions
on inventory buffers, backup capacity, sourcing diversification, and logistics routing.
Conclusions: Conclusions: Resilience metrics become operationally useful when tied to
explicit decision levers and validated through structured stress tests, not treated as standalone scorecards.

How to Cite

Begen, M. A. (2026). Supply Chain Resilience Metrics: Optimization under Multi-Risk Shocks. Transnational Academic Journal of Economics, 2(2), 152–156. https://doi.org/10.5281/zenodo.18442616
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