Mitigating Supply Chain Disruptions Research Articles

The impact of R&D investment on mitigating supply chain disruptions: Empirical evidence from U.S. firms

The purpose of this paper is to examine the moderating effect of a firm's R&D investment in mitigating supply chain disruptions. We use four categories of disruption risks in a supply chain: demand, process, supply, and environmental. Building upon dynamic capability theory, we examine the relationships among a firm's R&D investment, supply chain disruption risk drivers, supply chain performance, and firm performance, using data collected from manufacturing and service organizations in the U.S. Our findings show that a firm's R&D investment can be regarded as enhancing the firm's resilience capability. R&D investment significantly mitigates the effects of process disruption, supply disruption, and demand disruption on firm performance. R&D investment significantly mitigates the effects of process disruption and environmental disruption on supply chain performance. Our study provides one of the early empirical findings of the role of a firm's investment in innovation as a means of improving the firm's resilience to supply chain disruptions.

An examination of the impact of flexibility and agility on mitigating supply chain disruptions

This paper examines the effect of flexibility and agility on improving supply chain responsiveness. We examine a supply chain with multiple sites, multiple transportation channels, and multiple product planning, over multiple periods, under supply risk and demand risk. Using a numerical example, we determine the relationship between three objective functions related to responsiveness, risk, and the cost of new and seasonal products, then discuss the impact of flexibility and agility on mitigating supply chain disruptions. To show a trade-off among objective functions in our numerical example, we solve the multi-objective mixed integer programming (MOMIP) model using three multi-objective optimization methods: the weighted goal programming (WGP) method, the augmented ε-constraint (AUGMECON) method, and the non-dominated sorting genetic algorithm (NSGA-Ⅱ). Our findings help decision makers with these two tasks: anticipate how much improvement in flexibility and agility will lead to an improvement in responsiveness; and create an investment plan to minimize the negative impact of supply chain disruptions by an examination of the trade-offs among responsiveness, risk, and cost. The results show that the NSGA-Ⅱ method outperforms the AUGMECON method in several metric indexes: the spacing metric, the diversity metric, and simple additive weighting.

Real options approach to evaluate postponement as supply chain disruptions mitigation strategy

The purpose of this paper is to assess the value of postponement as strategy for mitigating supply chain disruptions. To accomplish this objective, we develop a real option computational model that quantifies the value of postponement in mitigating both supply and demand disruptions by taking into account the value of managerial flexibility to decide whether exploiting or not the strategy, if and when disruptions occur, and whenever product differentiation proves valuable based on information available at that time. Numerical experiments show the importance of incorporating an option valuation method when pricing the value of postponement. This ensures managers implement postponement only when it is valuable, thus avoiding burdening the company with its initial sunk costs. By modelling the postponement implementation under different conditions, we identify the situations in which postponement performs better as supply chain disruptions mitigation strategy. We derive the operational configurations, in terms of decoupling point position, and external conditions, in terms of riskiness of the environment, which make the postponement an effective mitigation strategy.

Effectiveness of resilience capabilities in mitigating disruptions: leveraging on supply chain structural complexity

PurposeThis study aims to investigate the influence of supply chain (SC) complexity on the effectiveness of resilience capabilities in mitigating SC disruptions. Hypotheses about direct and moderating influences of complexity on resilience capabilities and performance change after disruption are built and quantitatively tested.Design/methodology/approachPartial least square-based structural equation modelling with formative constructs was used as an overall approach. Secondary data on SC disruptions, related performance change and resilience practices were collected from multiple sources through a predefined procedure. The collected data were systematically encoded prior to performing statistical analysis.FindingsSC structural complexity is found to have a significant positive relation with performance improvement after disruption, along with resilience capability; it also positively moderates the resilience–performance link.Research limitations/implicationsThe SC complexity factors the authors considered in this study do not include dynamic forms because of the nature of data collected. Future research may attempt to include and test whether the results of this study also hold when additional complexity parameters are taken into account.Practical implicationsManagers are often trying to reduce SC complexity. This study implies that some level of complexity is beneficial also for a better recovery of operational performance affected because of disruption. Resilience capabilities become more effective when leveraged on complexity in the SC.Originality/valueThis is the first study to empirically investigate the influence of SC complexity on the resilience–performance link.

Stages of Supply Chain Disruption Response: Direct, Constraining, and Mediating Factors for Impact Mitigation

ABSTRACTIt is well established that supply chain disruptions can have a severe negative impact on firms and general wisdom suggests that this impact can be mitigated by quick responses. Aside from a few anecdotes, however, little is known about the decision‐making process that leads to speedy responses and about its impeding and supporting antecedents. Using the organizational information‐processing perspective, this empirical study unravels the disruption management process along a sequence of four stages—disruption recognition, disruption diagnosis, response development, and response implementation—and hypothesizes constraining and mediating effects of these stages. The findings contribute to an improved understanding of the role that the decision stages play in mitigating supply chain disruptions, and confirm the prediction that the speed with which information is processed and the stages are worked through positively affects supply chain performance. In addition, the findings suggest that one of the stages, diagnosis, acts as a constraining factor to the other stages. The stages also play a mediating role between the impact that the disruption has and a firm's readiness (prior to a disruption), dependence on a key supplier, and supply chain complexity. This provides guidance to decision makers in the application of resources both prior to a negative event and during a disruption recovery.

Mitigating supply chain disruptions through interconnected logistics services in the Physical Internet

This paper investigates the resilience of inventory models using interconnected logistics services in the Physical Internet (PI). With traditional supply chain network design, companies define and optimise their own logistics networks, resulting in current logistics systems being a set of independent heterogeneous logistics networks. The concept of PI aims to integrate independent logistics networks into a global, open, interconnected system. Prior research has shown that new inventory models enabled by and applied to PI could help reduce inventory levels thanks to its high flexibility. Continuing along these lines, this paper examines how inventory models applying PI deal with disruptions at hubs and plants. To attain this, a single product inventory problem with uncertain demands and stochastic supply disruptions is studied. A simulation-based optimisation model is proposed to determine inventory control decisions. The results suggest that the PI inventory model, with greater agility and flexibility, outperforms the current classic inventory models in terms of resilience. Moreover, the difference in performance increases when the product value, penalty costs and disruption frequency increases. This paper indicates a novel approach to build a resilient supply network.

Performance Improvement of Inventory Management System Processes by an Automated Warehouse Management System

This study investigates the impact of a warehouse management system on supply chain performance that provides less resources effort, more efficient, and reliable inventory management system. The supply chain procedures carried out in the warehouse were reviewed before customizing a software that can handle the necessary transactions. The software was tested for enhancing the work flow and providing a timely and efficient handling. Data was collected from the warehouse of a leading telecommunications service provider in Jordan. Furthermore, the facility layout was studied and we introduced a production station within the warehouse, which resulted in better space optimization/utilization of the warehouse. The production station consists of three steps: bundling, labelling, and repackaging. The system handles three phases of product lifecycle: receiving, processing, and distribution of SIM and prepaid scratch cards. Each phase of the product lifecycle was discussed in detail and the process/procedure gaps were identified. This work can serve both as a practical guide and industrial example for some researchers to compare the software inventory management system with the traditional manual system in the telecommunications sector in Jordan. It also highlights the gap between theory and practice; to motivate researchers to develop and customize new systems for mitigating supply chain disruptions.

Mitigating supply chain disruptions through the assessment of trade-offs among risks, costs and investments in capabilities

One of the central questions in supply chain design is how to properly invest in supply chain capabilities in order to be more responsive to supply chain disruptions. This new perspective in supply chain design requires an understanding of the relationships among costs, supply chain risk drivers, and investments in supply chain capabilities. In this paper, we develop a multi-objective stochastic model for supply chain design under uncertainty and time-dependency. Sources of risk are modeled as a set of scenarios, and the risk of the system is determined. The objective is to examine the trade-offs among investments in improving supply chain capabilities and reducing supply chain risks, and to minimize cost of supply chain disruptions. Due to the NP-hard nature of the problem, a heuristic algorithm based on a relaxation method is designed to determine an optimal or near-optimal solution. To examine the efficiency of the heuristic algorithm, a numerical example is provided. Our findings suggest that increasing supply chain capabilities can be viewed as a mitigation strategy that enables a firm to reduce the total expected cost of a supply chain subject to disruptions.

Application of an Agent-based Supply Chain to Mitigate Supply Chain Disruptions

With the advent of globalization, mitigating supply chain disruptions is the differential for any company. However, mitigating supply chain disruption-related risks in companies is a difficult task. There are some ISO norms that provide standards that can make systems to deal with supply chain disruptions and there are some modeling techniques that ensure that supply chain disruptions be mitigated. Although both approaches do not eliminate supply chain disruptions, they have a fundamental importance for supply chain mitigation. In this context, this paper presents an agent-based with the support of some supply chain and risk norms to mitigate supply chain disruptions. The objective of the proposed method is to identify possible hidden supply chain risks, often highlighting previous hidden or overlooked areas of high risk. An example application for a manufacturing firm demonstrates that this model is feasible and can be replicated to different sectors.

A comprehensive contingency management framework for supply chain disruption risk management

With globalisation and the advancement of information and communication technology, supply chain network structure has become more and more complicated with operational uncertainties and disruptions increasingly exacerbated. In this paper, we propose a comprehensive emergency management framework to manage supply chain disruption risks. Our framework integrates risk identification, risk assessment, and a combination of two contingency strategies. These two strategies are robust inventory control and virtual dual sourcing which can effectively mitigate supply chain disruptions. We then present a case study where Delphi Co. managed the disruptions in its supply chains during the 2008 Olympic Games in Beijing, China. Through this case study, we show the validity of our comprehensive emergency management framework. Finally, our framework can improve supply chain sustainability. For example, its strategy of virtual dual sourcing can keep a supply chain sufficiently lean while minimising the effect of supplier disruption.

Mitigating supply chain disruptions – a normal accident perspective

Purpose– Existing supply chain literature provides examples of countermeasures that firms can adopt to mitigate abnormal or catastrophic supply chain disruptions. However, none address reducing interactive complexity prior to adopting countermeasures to mitigate everyday or normal supply chain disruptions. Most mitigation strategies focus on adding capabilities or resources to protect an organization. Here, the authors aim to consider an alternative strategy of examining current processes to determine whether processes can be simplified by using the normal accident theory and its constructs of interactive complexity and coupling as a theoretical basis.Design/methodology/approach– The authors develop a model based on the normal accident theory and use logistic regression to test their propositions in the context of a steel processing plant and its customers.Findings– The findings show the importance of reducing interactive complexity to mitigate supply chain disruptions. However, high inventory is not considered a significant countermeasure, and high inventory levels may increase the likelihood of causing a disruption downstream. These findings support the lean management approach of operating under low inventory levels while eliminating complexity to make problems more visible, causing fewer disruptions.Originality/value– While others have examined the impact of mitigation strategies conceptually, no study has captured information from actual supply chain disruptions to assess how interactive complexity and inventory levels affect disruption potential at downstream customers' facilities. Capturing information from supply chain disruptions enables managers to assess the situation as the disruption is occurring. The authors suggest a strategy in which countermeasures that increase slack in the system should be considered only after the system is sufficiently simplified to mitigate disruptions.

Product substitution and dual sourcing under random supply failures

Product substitution can mitigate supply chain disruptions. However, it may not be very effective without multiple sourcing. In this paper, we consider a supply chain with two downward substitutable products. The products can be ordered from an unreliable supplier or a reliable but more expensive supplier. It is found that in an optimal sourcing policy the higher-grade product should be preferred over the lower-grade product. A sufficient condition is given for an optimal policy where only the higher-grade product is dual-sourced. The effect of substitution is contrasted with the non-substitution case. Numerical study shows the impact of demand variability and correlation on the effect of product substitution and the corresponding optimal sourcing policy.

Postponement in supply chain risk management: a complexity perspective

While the poor response implications of supply are often not elaborated on in the literature, postponement has recently been mentioned as a useful tool for managing supply risk and disruptions. To interpret this in a more complete manner, this paper has attempted to explore the role of postponement in supply chain risk management from a complexity perspective. After a review of the relevant literature, it first draws insights emerging from normal accident theory that addresses the system characteristics of catastrophic accidents and applies them to supply chain disruptions. This is followed by the utilisation of normal accident theory to explain the role of postponement in supply chain risk management. Building on this, this paper also investigates the complexity implications of some commonly recommended measures to mitigate supply chain disruptions. In certain circumstances, the introduction of those measures may add to the complexity of a system and thus become inherently infeasible. The paper concludes with a summary and some suggestions for further research.

Perspectives in Supply Chain Risk Management: A Review

To gain cost advantage and market share, many firms implemented various initiatives such as outsourced manufacturing and product variety. These initiatives are effective in a stable environment, but they could make a supply chain more vulnerable to various types of disruptions caused by uncertain economic cycles, consumer demands, and natural and man-made disasters. In this paper, we review various quantitative models for managing supply chain risks. We also relate various supply chain risk management strategies examined in the research literature with actual practices. The intent of this paper is three-fold. First, we develop a unified framework for classifying supply chain risk management articles. Second, we hope this review can serve as a practical guide for some researchers to navigate through the sea of research articles in this important area. Third, by highlighting the gap between theory and practice, we hope to motivate researchers to develop new models for mitigating supply chain disruptions.

Robust strategies for mitigating supply chain disruptions

When major disruptions occur, many supply chains tend to break down and take a long time to recover. However, not only can some supply chains continue to function smoothly, they also continue to satisfy their customers before and after a major disruption. Some key differentiators of these supply chains are cost-effective and time-efficient strategies. In this paper, certain “robust” strategies are presented that possess two properties. First, these strategies will enable a supply chain to manage the inherent fluctuations efficiently regardless of the occurrence of major disruptions. Second, these strategies will make a supply chain become more resilient in the face of major disruptions. While there are costs for implementing these strategies, they provide additional selling points for acquiring and retaining apprehensive customers before and after a major disruption.