A new resilience measure for supply networks with the ripple effect considerations: a Bayesian network approach

Hosseini, Seyedmohsen; Ivanov, Dmitry

doi:10.1007/s10479-019-03350-8

Cited by 107 publications

(63 citation statements)

References 87 publications

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“…An important contribution can be seen in detecting disruption scenarios and identifying critical nodes (or combinations of nodes), the failure of which would lead to SC discontinuities and operational collapse ( Zeng and Xiao, 2014 ; Tang et al, 2016 ; Deng et al, 2019 ; Pavlov et al, 2020 ). Another important application area consists of measuring SC robustness and resilience under disruption propagation and structural dynamics ( Han and Shin, 2016 ; Sokolov et al, 2016 ; Hosseini & Ivanov, 2019 ; Li and Zobel, 2020 ). Along with the stress-testing of existing SC designs, the network level analyses suggest directions to enhance the resilience, e.g., through supplier diversification ( Lei et al, 2020 ).…”

Section: Theories Major Outcomes and Managerial Insightsmentioning

confidence: 99%

“…At this stage, SCs are experiencing initial misbalances in supply and demand due to longer lead-times, demand drops, and supply unavailability due to facility closures. OR methods can support SC managers at this stage by stress-testing the existing and alternative SC configurations and production-distribution plans for some scenarios of structural dynamics in anticipation of, or as a reaction to, facility and market closure due to quarantines and lockdowns ( Hosseini & Ivanov, 2019 ; Tan et al, 2019 ; Li and Zobel, 2020 ; Sawik, 2020 ). OR methods can also help optimize contingency-preparedness plans for their efficient and timely deployment under different scenarios of epidemic propagation ( Liberatore et al, 2012 , Ghadge et al, 2013 , Ivanov et al, 2015 ; Sinha et al, 2020 ; Pavlov et al, 2019 ; Goldbeck et al, 2020).…”

Section: Directions For Managerial Applications and Future Research Imentioning

confidence: 99%

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OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications

Ivanov

Dolgui

2021

International Journal of Production Economics

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342

201

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The COVID-19 pandemic unveils unforeseen and unprecedented fragilities in supply chains (SC). A primary stressor of SCs and their subsequent shocks derives from disruption propagation (i.e., the ripple effect) through related networks. In this paper, we conceptualize current state and future research directions on the ripple effect for pandemic context. We scrutinize the existing OR (Operational Research) studies published in international journals dealing with disruption propagation and structural dynamics in SCs. Our study pursues two major contributions in relation to two research questions. First, we collate state-of-the-art research on disruption propagation in SCs and identify a methodical taxonomy along with theories displaying their value and applications for coping with the impacts of pandemics on SCs. Second, we reveal and systemize managerial insights from theory used for operating (adapting) amid a pandemic and during times of recovery, along with becoming more resistant to future pandemics. Streamlining the literature allowed us to reveal several new research tensions and novel categorizations and classifications. The outcomes of our study show that methodical contributions and the resulting managerial insights can be categorized into three levels, i.e., network, process, and control. Our analysis reveals that adaptation capabilities play the most crucial role in managing the SCs under pandemic disruptions. Our findings depict how the existing OR methods can help coping with the ripple effect at five pandemic stages (i.e., Anticipation; Early Detection; Containment; Control and Mitigation; and Elimination) following the WHO classification. The outcomes and findings of our study can be used by industry and researchers alike to progress the decision-support systems guiding SCs amid the COVID-19 pandemic and toward recovery. Suggestions for future research directions are offered and discussed.

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Section: Theories Major Outcomes and Managerial Insightsmentioning

confidence: 99%

Section: Directions For Managerial Applications and Future Research Imentioning

confidence: 99%

OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications

Ivanov

Dolgui

2021

International Journal of Production Economics

Self Cite

342

201

View full text Add to dashboard Cite

show abstract

“…However, the temporal nature of the disruption propagation is not considered. Hosseini and Ivanov (2019) further propose a metric, built on the BN approach, for quantifying the resilience of the SC under ripple effect. Incorporating the dynamics of the disruption propagation over a time horizon, Hosseini, Ivanov, and Dolgui (2019b) first propose a dynamic BN (DBN) approach to analyse the disruption propagation in an SC (with two suppliers and one manufacturer) over a time horizon.…”

Section: Sc Disruption Risk Managementmentioning

confidence: 99%

A new robust dynamic Bayesian network approach for disruption risk assessment under the supply chain ripple effect

Liu

Chu

et al. 2020

International Journal of Production Research

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“…Consequently, the BN's results show that the resilience capacity of an inland port is related to the three components of absorptive capacity (a means to withstand a disruptive event, or a reduction in vulnerability), adaptive capacity (a means to temporarily adapt to maintain performance), and restorative capacity (a means to restore performance in a long term manner, which with adaptive capacity constitutes recoverability). So, various pre-disaster and post-disaster strategies can improve the three capacities to varying extents, all combining to improve the resilience capacity of the port [7]; [17].…”

Section: ) Case Study: the Resilience Of An Inland Water Port The Pmentioning

confidence: 99%

A Review of Methods to Study Resilience of Complex Engineering and Engineered Systems

Naghshbandi¹,

Varga²,

Purvis

et al. 2020

IEEE Access

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Uncertainty and interconnectedness in complex engineering and engineered systems such as power-grids and telecommunication networks are sources of vulnerability compromising the resilience of these systems. Conditions of uncertainty and interconnectedness change over time and depend on emerging socio-technical contexts, thus conventional methods which can conduct normative, descriptive and prescriptive assessment of complex engineering and engineered systems resilience are limited. This paper brings together contributions of experts in complex engineering and engineered systems who have identified six methods, three each for uncertainty and interconnectedness, which form the foundational methods for knowing complex engineering and engineered systems resilience. The paper has reviewed how these methods contribute to overcoming uncertainty or interconnectedness and how they are implemented using case studies in order to illustrate essential approaches to enhancing resilience. It is hoped that this approach will allow the subject to be quantified and best practice standards to develop.

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A new resilience measure for supply networks with the ripple effect considerations: a Bayesian network approach

Cited by 107 publications

References 87 publications

OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications

OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications

A new robust dynamic Bayesian network approach for disruption risk assessment under the supply chain ripple effect

A Review of Methods to Study Resilience of Complex Engineering and Engineered Systems

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