The impact of digitalisation and Industry 4.0 on the ripple effect and disruption risk control analytics in the supply chain (SC) is studied. The research framework combines the results from two is...

The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics

Economic systems are increasingly prone to complexity and uncertainty. Therefore, making well-informed decisions requires risk analysis, control and mitigation. In some areas such as finance, insurance, crisis management and health care, the importance of considering risk is largely acknowledged and well-elaborated, yet rather heterogeneous concepts and approaches for risk management have been developed. The increased frequency and the severe consequences of past supply chain disruptions have resulted in an increasing interest in risk. This development has led to the adoption of the risk concepts, terminologies and methods from related fields. In this paper, existing approaches for quantitative supply chain risk management are reviewed by setting the focus on the definition of supply chain risk and related concepts.

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A critical review on supply chain risk – Definition, measure and modeling ☆

Supply chain resilience (SCR) manifests when the network is capable to withstand, adapt, and recover from disruptions to meet customer demand and ensure performance. This paper conceptualizes and comprehensively presents a systematic review of the recent literature on quantitative modeling the SCR while distinctively pertaining it to the original concept of resilience capacity. Decision-makers and researchers can benefit from our survey since it introduces a structured analysis and recommendations as to which quantitative methods can be used at different levels of capacity resilience. Finally, the gaps and limitations of existing SCR literature are identified and future research opportunities are suggested.

Review of quantitative methods for supply chain resilience analysis

We review the OR/MS literature on supply chain disruptions in order to take stock of the research to date and to provide an overview of the research questions that have been addressed. We first place disruptions in the context of other forms of supply uncertainty and discuss common modeling approaches. We then discuss nearly 150 scholarly works on the topic, organized into six categories: evaluating supply disruptions; strategic decisions; sourcing decisions; contracts and incentives; inventory; and facility location. We conclude with a discussion of future research directions.

https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=1689882

OR/MS Models for Supply Chain Disruptions: A Review

Viability is the ability of a supply chain (SC) to maintain itself and survive in a changing environment through a redesign of structures and replanning of performance with long-term impacts. In this paper, we theorize a new notion-the viable supply chain (VSC). In our approach, viability is considered as an underlying SC property spanning three perspectives, i.e., agility, resilience, and sustainability. The principal ideas of the VSC model are adaptable structural SC designs for supply-demand allocations and, most importantly, establishment and control of adaptive mechanisms for transitions between the structural designs. Further, we demonstrate how the VSC components can be categorized across organizational, informational, process-functional, technological, and financial structures. Moreover, our study offers a VSC framework within an SC ecosystem. We discuss the relations between resilience and viability. Through the lens and guidance of dynamic systems theory, we illustrate the VSC model at the technical level. The VSC model can be of value for decision-makers to design SCs that can react adaptively to both positive changes (i.e., the agility angle) and be able to absorb negative disturbances, recover and survive during short-term disruptions and long-term, global shocks with societal and economical transformations (i.e., the resilience and sustainability angles). The VSC model can help firms in guiding their decisions on recovery and re-building of their SCs after global, long-term crises such as the COVID-19 pandemic. We emphasize that resilience is the central perspective in the VSC guaranteeing viability of the SCs of the future. Emerging directions in VSC research are discussed.

/pdf/viable-supply-chain-model-integrating-agility-resilience-and-3a64nqwkq5.pdf

Viable supply chain model: integrating agility, resilience and sustainability perspectives-lessons from and thinking beyond the COVID-19 pandemic.

We review the Operations Research/Management Science (OR/MS) literature on supply chain disruptions in order to take stock of the research to date and to provide an overview of the research questio...

OR/MS models for supply chain disruptions: a review

This paper studies a strategic supply chain management problem to design reliable networks that perform as well as possible under normal conditions, while also performing relatively well when disruptions strike. We present a mixed-integer programming model whose objective is to minimize the nominal cost (the cost when no disruptions occur) while reducing the disruption risk using the p -robustness criterion (which bounds the cost in disruption scenarios). We propose a hybrid metaheuristic algorithm that is based on genetic algorithms, local improvement, and the shortest augmenting path method. Numerical tests show that the heuristic greatly outperforms CPLEX in terms of solution speed, while still delivering excellent solution quality. We demonstrate the tradeoff between the nominal cost and system reliability, showing that substantial improvements in reliability are often possible with minimal increases in cost. We also show that our model produces solutions that are less conservative than those generated by common robustness measures.

Reliable logistics networks design with facility disruptions

This paper studies a strategic supply chain management problem of designing robust networks which perform well under both normal condition and disruptions. A mix-integer programming model which incorporates p-robust measure is presented. The objective is to minimize the total nominal cost, while setting upperbounds on relative regrets in disruption scenarios. A GA-based hybrid metaheuristic algorithm is proposed and tested. Computational results demonstrate that system robustness can be substantially improved with little increase in cost. Our solution is also less conservative compared with common robustness measures.

Peng Peng

Papers

OR/MS Models for Supply Chain Disruptions: A Review

OR/MS models for supply chain disruptions: a review

Reliable logistics networks design with facility disruptions

A p-Robust Capacitated Network Design Model with Facility Disruptions

Research on incentive strategy based on service quality in spatial crowdsourcing task allocation