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. 2020 Sep 15;232:107921. doi: 10.1016/j.ijpe.2020.107921

Table 3.

Outcomes and managerial insights from OR contributions to the ripple effect and structural dynamics.

Level of Analysis OR Methods Outcomes Managerial Insights
Network Level Graph Theory
  • Associations between network structures and risk propagation;

  • Analysis of critical network elements leading to supply chain discontinuities and collapses through cascading failure effects;

  • Modeling of interdependencies in SCs;

  • State dynamics within SC nodes;

  • Assessment of SC robustness and resilience to disruptions with considerations of ripple effect

  • Identification of disruption propagation scenarios of different severity

  • Stress-testing of SC designs

  • Propensity of specific SC designs to disruption risk propagation

  • Identification of critical suppliers and facilities for maintaining SC operations

  • Selection and proactive enhancements of SC designs to sustain certain levels of disruption propagation and structural dynamics

  • Adaptation of SC designs according to environmental changes

Complexity Theory
Entropy
Petri Nets
Bayesian Networks
Markov Chains
Reliability Theory/Statistical Analysis
Process Level Stochastic Optimization
  • Optimal reconfigurations of material flows according to disruption propagation scenarios

  • Impacts of ripple effect and structural dynamics on service level and costs

  • Optimal re-allocation of supply and demand under conditions of disruption propagation and structural dynamics

  • Stress-testing of SC production-distribution plans within differently disrupted network designs

  • Analysis of contingency-preparedness plans

  • Recovery plan selection

Robust Optimization
Linear/Mixed-Integer Programming
Control Level Optimal Control
  • Impacts of disruption propagation on service level, inventory levels, and costs

  • Time-dependent effect of disruption propagation on SC behaviors and performance in dynamics

  • Individual behavior of firms in SCs

  • Building resilient SCs for new, post-pandemic business models

  • Analysis of disruption propagation in dynamics with consideration of production and inventory control policies

  • Simulation of operation policies during disruption, in transition to recovery, and in post-recovery periods

Systems Dynamics
Agent-Based Simulation
Discrete-Event Simulation