TY - JOUR
T1 - Ripple Effect Quantification by Supplier Risk Exposure Assessment
AU - Kinra, Aseem
AU - Ivanov, Dmitry
AU - Das, Ajay
AU - Dolgui, Alexandre
PY - 2019
Y1 - 2019
N2 - Supply chain (SC) disruptions are considered events that temporarily change the structural design and operational policies of SCs with significant resilience implications. The SC dynamics and complexity drive such disruptions beyond local event node boundaries to affect large parts of the SC. The propagation of a disruption through a SC and its associated impact is called the ripple effect. Previous approaches to ripple effect modelling have mainly focused on estimating the likelihood of a disruption; our study looks at the disruption consequences. We develop a new model to assess the ripple effect of a supplier disruption, based on possible maximum loss. Our risk exposure model quantifies the ripple effect, comprehensively combining features such as financial, customer, and operational performance impacts, consideration of multi-echelon inventory, disruption duration, and supplier importance. The ripple effect quantification is validated with simulations using actual company data. The findings suggest that the model can be of value in revealing latent high-risk supplier relations, and in prioritising risk mitigation efforts when probability estimations are difficult. The performance indicators proposed can be used by managers to analyse disruption propagation impact and to identify the set of most critical suppliers to be included in the disruption risk analysis.
AB - Supply chain (SC) disruptions are considered events that temporarily change the structural design and operational policies of SCs with significant resilience implications. The SC dynamics and complexity drive such disruptions beyond local event node boundaries to affect large parts of the SC. The propagation of a disruption through a SC and its associated impact is called the ripple effect. Previous approaches to ripple effect modelling have mainly focused on estimating the likelihood of a disruption; our study looks at the disruption consequences. We develop a new model to assess the ripple effect of a supplier disruption, based on possible maximum loss. Our risk exposure model quantifies the ripple effect, comprehensively combining features such as financial, customer, and operational performance impacts, consideration of multi-echelon inventory, disruption duration, and supplier importance. The ripple effect quantification is validated with simulations using actual company data. The findings suggest that the model can be of value in revealing latent high-risk supplier relations, and in prioritising risk mitigation efforts when probability estimations are difficult. The performance indicators proposed can be used by managers to analyse disruption propagation impact and to identify the set of most critical suppliers to be included in the disruption risk analysis.
KW - Supply chain dynamics
KW - Supply chain resilience
KW - Supply chain disruptions
KW - Ripple effect
KW - Risk assessment
KW - Performance management
KW - Supply chain dynamics
KW - Supply chain resilience
KW - Supply chain disruptions
KW - Ripple effect
KW - Risk assessment
KW - Performance management
U2 - 10.1080/00207543.2019.1675919
DO - 10.1080/00207543.2019.1675919
M3 - Journal article
SN - 0020-7543
VL - 58
SP - 5559
EP - 5578
JO - International Journal of Production Research
JF - International Journal of Production Research
IS - 18
ER -