Supply Chain Risk Management

The purpose of this chapter is to investigate recent research developments in supply chain risk management (SCRM) and to provide a comprehensive outline for researchers and practitioners who are trying to identify the existing state of research in the SCRM area. The importance of a literature review is to enhance the understanding of researchers by cataloging previous research in an area and clarifying the strengths and weaknesses of existing studies and what they might mean. Since the number of studies on SCRM has increased dramatically, several review papers of existing papers have been published. By finding significant number of review papers in the area, we convinced about the necessity of including summary of review papers. Therefore, we first summarize previous SCRM review papers. Second, we review recent papers that have not been mentioned in these review papers. Third, we develop a framework by which to categorize these papers. We conclude by presenting the observed pattern of SCRM research.

Risk treatment is an important stage of the risk management process involving selection of appropriate strategies for mitigating critical risks. Limited studies have considered evaluating such strategies within a setting of interdependent supply chain risks and risk mitigation strategies. However, the selection of strategies has not been explored from the perspective of manageability-the ease of implementing and managing a strategy. We introduce a new method of prioritising strategies on the basis of associated cost, effectiveness and manageability within a theoretically grounded framework of Bayesian Belief Networks and demonstrate its application through a simulation study. The proposed approach can help managers select an optimal combination of strategies taking into account the effort involved in implementing and managing such strategies. The results clearly reveal the importance of considering manageability in addition to cost-effectiveness within a decision problem of ranking supply chain risk mitigation strategies.

The present study aims to identify and formalize the structural and relational patterns, which account for risk emergence and propagation in buyer-supplier-customer service triads. Following the guidelines of the design science research approach and based on the existing literature, buyer-supplier-customer service triads are categorized into a coherent typology according to the role that each supply chain dyad plays in the emergence and propagation of risk within the triad it forms. In the context of this study, such triads are referred to as Risk-aware Service Triads (RaSTs). To explore all the feasible forms of RaSTs, including the ones that have not yet been addressed in the literature, this study adopts the formalism of weighted directed graphs. As a result, a typology based on thirty different types of RaSTs is suggested. This typology allows: (i) to systematize and formally represent a variety of hypothetical scenarios when each of the dyadic structures within buyer-supplier-customer service triads acts as risk trigger, risk taker or risk neutral component of the respective RaST; and (ii) to calculate the maximal and minimal risk index specific to each of the identified type of RaST, thereby facilitating the identification and assessment of risk exposures associated with buyer-supplier-customer service triads. An illustrative example of how the methodological approach underlying the suggested RaST typology facilitates risk assessment in service triads and service networks is presented.

In the face of ever expanding global markets, supply chain risks have become increasingly important. Most professionals are fully aware of the risks that have the potential to disrupt supplies such as minor design problems or even natural disasters. However, there is one kind of risk that has been often overlooked in supply chain management but is now becoming a threat: reputational risk. This chapter will explain the theoretical underpinnings of this vital management area and how to mitigate reputational risks in a practical supply chain setting.

This chapter describes the potential impact of Information Technology (IT) and cyber risks on the continuity and vulnerabilities of the supply chain. We propose a theoretical framework and direction to help organizations to manage these risks. The evidence gleaned from an empirical investigation will illustrate how organizations actually perceive, control, and manage IT and cyber risks within the supply chains. The findings will underline that managers tend to invest in few mitigation strategies; hence, they take risks that are much higher than their declared risk appetites. In addition, managers denounce a general lack of awareness regarding the effects that IT and cyber risks may have on supply operations and relationships.

In this chapter, the different types of potential risks in supply chains are described and the specific impacts of natural disasters such as the Great East Japan earthquake and tsunami on Japanese supply chains are outlined. Moreover, some strategies and developments on how to mitigate supply chain disruptions are presented.

Supply chain vulnerabilities have attracted little research attention despite being recognized as an important issue. To provide further insights into this issue, this chapter uses a simulation approach for analyzing supply chain vulnerability. Specifically, simulations are used to gain additional insights into multiechelon supply chains and the impact of supply disruptions. This study employs an integrated literature review of supply chain vulnerability and risk management and a discrete-event-simulation. The presented framework and simulation models provide important information about the feasibility of using a simulation for analyzing supply chain vulnerability. The results of this study suggest that supply chain vulnerability depends on both the complexity of the supply chain as well as the disruption risks inherent in it. To gain a more holistic view of an entire supply chain system, it is imperative to use proper tools to analyze vulnerabilities. Simulations can be used to model both the system complexity and the different levels of operation holistically and gain insights into managing supply chain vulnerability. By analyzing supply chain vulnerability, managers can ground their decisions in a more holistic understanding of the issue.

Supply chain risk management has recently seen extensive research efforts, but questions such as “How should a firm plan for each type of disruption?” and “What are the strategies and the total cost incurred by the firm if a disruption occurs?” continue to deserve attention. This chapter analyzes different disruption cases by considering the impacts of disruptions at a supplier, a firm’s warehouse, and at the firm’s production facility. The firm can prepare for each type of disruption by buying from an alternate supplier, holding more inventory, or holding inventory at a different warehouse. The Wagner-Whitin model is used to solve the optimal ordering strategy for each type of disruption. Since the type of disruption is uncertain, we assign probabilities for each disruption and use the Wagner-Whitin model to find the order policy that minimizes the firm’s expected cost.

Supply chain disruptions can lead to firms losing customers and consequently losing profit. We consider a firm facing a supply chain disruption due to which it is unable to deliver products for a certain period of time. When the firm is restored, each customer may choose to return to the firm immediately, with or without backorders, or may purchase from other firms. This chapter develops a quantitative model of the different customer behaviors in such a scenario and analytically interprets the impact of these behaviors on the firm’s post-disruption performance. The model is applied to an illustrative example.

The concept of risk management within the supply chain framework ought to involve indirect effects of disruptions. In other words, not only should it take into consideration the risk sources and their direct consequences, but also look into the indirect disruptions that may be transmitted and amplified in the supply chain structure. The transmission of disruptions means that the negative effects of risk are extended to a larger number of participants in a supply chain. If the negative risk effects are additionally magnified during the transmission, this suggests the occurrence of the amplification of disruptions. In other words, the subsequent links in a supply chain are exposed to a stronger impact of disruptions in the transmission. Thus, the supply chain management needs to apply a certain approach that enables to mitigate the negative consequences of the transmission and amplification of disruptions in supply chains. In this chapter, we review the extant literature on the essence, sources and factors of the transmission and amplification of disruptions in supply chains. In particular, we put emphasis on the issue of supply chain integration that may either drive or inhibit the transmission and amplification of disruptions. Having linked the obtained findings with the classical concepts of risk management, we develop and assess a framework of risk management that aims at mitigating the transmission and amplification of disruptions in supply chains.

Disruption in the upstream of any supply chain affects the productivity and reputation of suppliers in that chain. Supply disruption risk is prevalent and affects more suppliers especially since these suppliers tend to be grouped geographically or as clusters for greater economies of scale. With attention paid to disaster management and business contingency planning, many firms are reassessing their supply chain strategies to effectively handle such risks, contain cost, and maintain service levels. This chapter presents a Mixed Integer Linear Programming (MILP) model for supplier selection and order quantity allocation (SSOA) for suppliers who bear different disruption likelihood, capacity, upside flexibility and operate under different price discount regimes. The objective is to minimize the expected total cost comprising supplier management cost, purchasing cost, and an expected loss if a supplier’s reliability to serve is compromised by disruptions. As the SSOA problem under supply disruption risk is NP-hard, particle swarm optimization with time varying inertia weight and acceleration coefficients is applied. Numerical tests are conducted to illustrate the proposed approach and the results obtained are compared with Genetic Algorithm (GA). Sensitivity analysis is conducted on the disruption likelihood, supplier upside flexibility, and the price discount regimes.

With the rapid advancement of businesses into overseas markets in recent years, the scope of supply chain configuration is expanding globally. Supply chain disruption due to natural disasters such as the 2011 Great East Japan Earthquake and the flooding in Thailand has become a serious problem. Under the impact of these natural disasters, risk evaluation has been recognized as an important element of supply chain management. In this chapter, we consider disruption risk and develop a model by incorporating supplier decentralization that assumes a global supply chain spanning two countries and consisting of three levels: supplier, manufacturer, and customer. We assume three types of disruption of varying frequency and effectiveness, generated by random numbers by the Poisson process. We assess the global supply chain designed by verifying the effectiveness of supplier decentralization in response to disruptions.

This chapter provides a broad overview of the field of supply chain resiliency. First, we define the concept of resiliency from the perspective of a supply chain. Next the terms risk and vulnerability are defined in the context of a resilient supply chain. This connects previous studies in supply chain engineering to the emerging field of resiliency. The second section of the chapter outlines components that contribute to the resiliency of a supply chain. Supply chain flexibility, velocity, visibility, and collaboration are defined and references to additional sources are provided. The third section of the chapter outlines processes that are used for building resilient supply chains. A number of relationships between supply chain risk and profitability are explored, along with their impact on supply chain resiliency. This section further provides a unifying exploration of the various aspects and perspectives on supply chain engineering, including how they can be utilized for developing and measuring the resiliency of a supply chain. The chapter concludes with remarks ongoing research on supply resiliency and identifies knowledge gaps and topics for future research.

This chapter presents a methodology for designing resilient service supply chains. The approach combines system design methods with methods from risk assessment. Service supply chains consist of multiple assets, cooperating to fulfill an operation. Each asset has functionality to perform a set of tasks in the operation, and the combined functionalities of the fleet of assets must cover the activities the service supply chain are to perform. When a module in one asset in the fleet experiences loss of functionality, it constitutes a disruption in the service supply chain, a failure mode. The objective of the proposed methodology is to give decision support reducing the vulnerabilities of the service supply chain through design actions that can increase overall service supply chain resilience. The methodology consists of four steps. The first step includes breakdown of operation and service supply chain, mapping of modules to tasks, and selection of service supply chain configuration based on costs and utility. In the second step, failure modes are identified and their criticality assessed. In the third step, we propose design changes to reduce the impact of disruptions. These are evaluated in Step 4, where decisions regarding redesign are made. The recommendations from this methodology can be used to plan for how to redesign in the case of contingencies, or be used as part of an iterative process where the new information is incorporated in the evaluation of initial service supply chain design.

Although the significance of supply chain resilience has been well explored, there is much to be explained about its formation and composition. Using systems theory and the Family Resilience model, this chapter offers a series of organizational characteristics that combine to form supply chain resilience. These subsets of supply chain resilience are categorized into three. The first, inherent resilience, comes from the strength of resources that are already possessed, are permanent and inseparable from the supply chain itself. The second, anticipative resilience, are ones developed purposefully to face crises and disruptions. These are preparatory resources that come in the form of excess resources, business continuity plans, or insurance policies. The third type is adaptive resilience, which can come in the form of collaborative capabilities, collective decision-making, and leadership that combines care and concern with the ability to make on the spot decisions. The chapter explains how supply chains, as organizational systems, leverage these three sub-sets to face disruptions.

Today’s marketplace is characterized by intense competitive pressures as well as high levels of turbulence and uncertainty. Organizations require agility in their supply chains to provide superior value and also manage disruption risks and ensure uninterrupted service to customers. The cultivation of agility can be approached as a risk management initiative that enables a firm to anticipate as well as respond rapidly to marketplace changes and disruptions in the supply chain. Agility is thus of value for both risk mitigation and response. This chapter provides an updated perspective of an emerging body of literature devoted to supply chain agility. Next, based on our own research stream on this topic, we propose a set of supply chain initiatives as antecedents for cultivation of agility. These include internal integration measures, external integration with suppliers and customers, cultivation of external flexibility, and lean practices. We also provide more fundamental, cultural drivers for cultivating agility, which include market orientation, learning orientation and organizational culture types that are conducive for agility. These antecedents were established through empirical research, and we translate them into a set of managerial practices to address the cultivation of agility for both mitigation and response.

Supply chain risk management (SCRM) approaches suggest that actors in a supply chain network should consider different risk scenarios to address and mitigate supply chain risks in a better way. Overall performance of a supply chain could be severely affected by disruptions that are triggered by failures or service disruptions in the critical infrastructure (CI) systems that the supply chain relies on. Interdependencies among the CI systems and supply chains, particularly the so-called Key Resources Supply Chains (KRSC) such as food, worsen the effects as disruption and consequences propagate in the network. In order to understand such interdependencies and enhance SCRM approaches with a more holistic view, this chapter introduces a multilevel modelling approach. The economic loss impact of disruptions in CI systems and the potential effectiveness of different strategies to improve resilience in KRSC are modelled and assessed. A combination of Discrete Event Simulation and System Dynamics is used at the different levels of the simulation model. The proposed approach is demonstrated with an application case addressing the vulnerability and resilience analysis of a fast moving consumer goods supply chain against disruptions in underlying CI systems. Results of the multilevel simulation offered relevant insights toward a better understanding of the strength and dynamics of the interdependence between KRSC and CI, and consequently on resilience improvement efforts. Results help supply chain managers to prioritise resilience strategies, according to their expected benefits, when making decisions on the amount and location of resilience capabilities within a supply chain. The results strongly support the implementation of collaborative and coordinated resilience strategies among supply chain actors to direct efforts where they can be most effective.