On the quantification of operational supply chain resilience

Operational disruptions impact a supply chain’s ability to match supply and demand. To remain competitive, supply chains need to be resilient and thus capable of rapidly and effectively recovering from operational disruptions. Supply chain resilience is inherently multidimensional, as it spans across multiple tiers, and thus is difficult to quantify. Extant research has measured the transient response through a single-dimension or single-organisation as a proxy for operational resilience. Whilst this greatly simplifies the analysis, it is also potentially misleading, as an erroneous selection of metric(s) may lead to an inaccurate evaluation of the transient response. This research extends the understanding of operational resilience via quantitative evaluation of multiple transient response measures across multiple tiers; the objective being to construct a multidimensional, multi-echelon operational supply chain resilience metric. The study utilises disruptions as experimental inputs for a serial supply chain simulation model; results are obtained for individual measurements of the transient response across multiple supply chain tiers. Analysis indicates that individual dimensions of resilience can adequately explain the transient response at the single-firm level, whilst aggregation of multiple resilience dimensions across multiple tiers has greater capacity to holistically capture the performance response to supply chain disruptions.     

Structural-aware simulation analysis of supply chain resilience

Supply chain resilience (SCRES) refers to the ability of a supply chain (SC) to both resist disruptions and recover its operational capability after disruptions. This paper presents a simulation model that includes network structural properties in the analysis of SCRES. This simulation model extends an existing graph model to consider operational behaviours in order to capture disruption-recovery dynamics. Through structural analysis of a supply chain network (SCN), mitigation strategies are designed to build redundancy, while contingency strategies are developed to prioritise recovery of the affected SCN. SCRES indexes are proposed by sampling SC performance measures of disruption for each plant and aggregating the measures based on the criticality of the plants in the SCN. The applicability of this simulation model is demonstrated in a real-world case study of different disruption scenarios. The application of mitigation and contingency strategies is shown to both improve recovery and reduce the total costs associated with disruptions. Through such simulation-based analysis, firms can gain insight into the SCRES of their existing SCNs and identify suitable strategies to improve SCRES by considering recovery time and costs.     

Managing risks in the Indonesian seaweed supply chain

Seaweed supply chains in Indonesia, especially carrageenan and agar products, are subject to risks arising both inside the participating companies and in their external networks. Uncertainties in yield, quality, price, and infrastructure in one part of the supply chain can affect the whole chain. To ensure a sustainable seaweed industry, an appropriate supply chain risk management (SCRM) is needed. There are four critical steps in SCRM: identifying seaweed supply chains, identifying and categorizing risks, assessing risks, and mitigating risks. To identify seaweed supply chains, we conducted field research, in-depth interviews, and literature studies. The field survey was conducted in the Provinces of South Sulawesi, West Java, East Java, Banten, and West Nusa Tenggara. The seaweed supply chains were modeled by the software Umberto to get a better understanding of material and energy flows between the key members. To identify and categorize the risks, we started with the risks mentioned in the existing literature works, and then applied the Delphi method to analyze the potential risk sources, their causes, and their impacts. To assess risks, we used a semiquantitative approach through the face-to-face interviews to generate a risk map showing the likelihood, and impact of adverse events. Afterward, the risk intensity was categorized based on the value of the responses and classified into five categories: negligible, marginal, critical, most critical, and catastrophic risks. The mitigation strategies considered sustainability (environment, economy, and social) and risks criteria. Multi-criteria decision analysis was used to evaluate these strategies.     

Disruptive technologies for advancing supply chain resilience

Disruptive technologies provide a new paradigm for supply chain risk management and bring opportunities and challenges for the improvement of supply chain resilience (SCRes). This study summarizes the application cases of some disruptive technologies in the SCRes and analyzes the benefits and damages brought by disruptive technologies to the SCRes. The results show that disruptive technologies can provide the supply chain with flexibility, visibility, agility, and other capabilities at various stages of risk management. Hence, technology advancements greatly increase the level of the SCRes. Although disruptive technologies undermine the construction of SCRes, these damages can be eliminated through technology iteration or other disruptive technologies. Furthermore, disruptive technologies will provide better stability for the SCRes. The study also makes several suggestions for the use of disruptive technologies in the construction of the SCRes.     

Scheduling of recovery actions in the supply chain with resilience analysis considerations

Supply chain engineering models with resilience considerations have been mostly focused on disruption impact quantification within one analysis layer, such as supply chain design or planning. Performance impact of disruptions has been typically analysed without scheduling of recovery actions. Taking into account schedule recovery actions and their duration times, this study extends the existing literature to supply chain scheduling and resilience analysis by an explicit integration of the optimal schedule recovery policy and supply chain resilience. In particular, we compute a schedule optimal control policy and analyse the performance of this policy by varying the perturbation vector and representing the outcomes of variations in the form of an attainable set. We propose a scheduling model that considers the coordination of recovery actions in the supply chain. Further, we suggest a resilience index by using the notion of attainable sets. The attainable sets are known in control theory; their calculation is based on the schedule control model results and the minimax regret approach for continuous time parameters given by intervals. We show that the proposed indicator can be used to estimate the impact of disruption and recovery dynamics on the achievement of planned performance in the supply chain.     

A control engineering approach to the assessment of supply chain resilience

There is no consensus on the supply chain management definition of resilience. To aid in evaluating the dynamic behaviour of such systems we need to establish clearly elucidated performance criteria that encapsulate the attributes of resilience. A literature review establishes the latter as readiness, responsiveness and recovery. We also identify robustness as a necessary condition that would complement resilience. We find that the Integral of the Time Absolute Error (ITAE) is an appropriate control engineering measure of resilience when it is applied to inventory levels and shipment rates. We use the ITAE to evaluate an often used benchmark model of make-to-stock supply chains consisting of three decision parameters. We use both linear and nonlinear forms of the model in our evaluation. Our findings suggest that optimum solutions for resilience do not yield a system that is robust to uncertainties in lead-time. Hence supply chains will experience drastic changes in their resilience performance when lead-time changes.     

Managing demand uncertainty through fuzzy inference in supply chain planning

In this paper, we investigate methods for managing the irregular and uncertain demands involved in supply chain planning. We first build a supply chain planning model based on fuzzy linear programming, which defines demand as a fuzzy parameter. Next, we propose a fuzzy inference approach for converting fuzzy demand into crisp demand. In the proposed fuzzy inference-based approach, judgments of upcoming demand from both internal and external experts are used as input variables to reflect the expected demand irregularity. By adopting fuzzy inference, we can compensate for the limitations of the existing demand treatment approaches, which usually demonstrate poor forecasting performance in cases of irregular demand and thus reduce the accuracy of supply chain planning. To verify the feasibility of the proposed approach, we present an illustrative example of a Korean electronics company.     

A graph-based model to measure structural redundancy for supply chain resilience

Globalisation and lean initiatives increase the vulnerabilities of the supply chains (SC), where disruptions in any plant in a supply chain network (SCN) can propagate throughout the whole SCN. Redundancy is part of the SC re-engineering to improve supply chain resilience (SCRES). This paper presents a conceptual model of an SCN using graph theory, considering the relationships between plants and materials. Based on the model, the structural redundancy of the SCN is measured, which is used to assess SCRES. This assessment approach focuses on the resilience of the SCN against disruptions. Case studies are discussed to illustrate the applicability of this model and show that increasing structural redundancy of the SCN improves SCRES against disruptions.     

Revealing interfaces of supply chain resilience and sustainability: a simulation study

Dynamics of structures and processes is one of the underlying challenges in supply chain management, where multiple dimensions of economic efficiency, risk management and sustainability are interconnected. One of the substantiated issues in supply chain dynamics is resilience. Resilience has a number of intersections with supply chain sustainability. This paper aims at analysing disruption propagation in the supply chain with consideration of sustainability factors in order to design resilient supply chain structure in regard to ripple effect mitigation and sustainability increase. Ripple effect in the supply chain occurs if a disruption at a supplier cannot be localised and cascades downstream impacting supply chain performance. This simulation-based study helps to identify what sustainability factors mitigate the ripple effect in the supply chain and what sustainability factors enhance this effect. The results indicate that (i) sustainable single sourcing enhances the ripple effect; (ii) facility fortification at major employers in regions mitigates the ripple effect and enhances sustainability; and (iii) a reduction in storage facilities in the supply chain downstream of a disruption-risky facility increases sustainability but causes the ripple effect.     

A systematic literature review of the capabilities and performance metrics of supply chain resilience

ABSTRACT

Research on supply chain resilience (SCRE) capabilities and its performance measurement has been growing in recent years. However, the investigation of these concepts has primarily been conducted independently despite the interdependence of these concepts. A systematic literature review of 153 papers was conducted based on the principles of rigour, transparency and replicability required by the methodology. For the first time, we structurally reviewed the 11 SCRE performance metrics categories and its capabilities in SCRE Capabilities-Performance Metrics Framework (SCPM) developed based on the three resilience dimensions (readiness, response and recovery). The framework enables researchers to seek fundamental knowledge and to pursue further research regarding SCRE assessment. This study also provides practical value offering a guidance for decision-makers considering the trade-off among different capabilities and performance metrics.     

Managing product availability in an assemble-to-order supply chain with multiple customer segments

In this article, we propose a novel availability management process called Available-to-Sell (ATS) that incorporates demand shaping and profitable demand response to drive better supply chain efficiency. The proposed process aims at finding marketable product alternatives in a quest to maintain a financially viable and profitable product portfolio, and to avoid costly inventory overages and shortages. The process is directly supported by a mathematical optimization model that enables on demand up-selling, alternative-selling and down-selling to better integrate the supply chain horizontally, connecting the interaction of customers, business partners and sales teams to procurement and manufacturing capabilities of a firm. We outline the business requirements for incorporating such a process into supply chain operations, and highlight the advantages of ATS through simulations with realistic production data in a computer manufacturing environment. The models featured in this paper have contributed to substantial business improvements in industry-size supply chains, including over $100M of inventory reduction in IBM’s server computer supply chain.     

The value of nonlinear control theory in investigating the underlying dynamics and resilience of a grocery supply chain

In an empirical context, a method to use nonlinear control theory in the dynamic analysis of supply chain resilience is developed and tested. The method utilises block diagram development, transfer function formulation, describing function representation of nonlinearities and simulation. Using both ‘shock’ or step response and ‘filter’ or frequency response lenses, a system dynamics model is created to analyse the resilience performance of a distribution centre replenishment system at a large grocery retailer. Potential risks for the retailer’s resilience performance include the possibility of a mismatch between supply and demand, as well as serving the store inefficiently and causing on-shelf stock-outs. Thus, resilience is determined by investigating the dynamic behaviour of stock and shipment responses. The method allows insights into the nonlinear system control structures that would not be evident using simulation alone, including a better understanding of the influence of control parameters on dynamic behaviour, the identification of inventory offsets potentially leading to ‘drift’, the impact of nonlinearities on supply chain performance and the minimisation of simulation experiments.     

Managing warehousing in an agile supply chain environment: an F-AIS algorithm based approach

In recent years, application of the agile concept in the manufacturing sector has been researched extensively to reduce the varying effect of customer demands. However, most of the research work is focused on the shop floor of different manufacturing processes, while issues concerning the control of warehouse scheduling in a supply chain have been neglected so far. Realising this in the present research an attempt has been made to address the scheduling aspect of a warehouse in an agile supply chain environment. To resolve the warehouse problem in this paper, the authors have proposed a new Fuzzy incorporated Artificial Immune System Algorithm (F-AIS). This algorithm encapsulates the salient features of a fuzzy logic controller and immune system. The proposed algorithm has been compared with genetic algorithm (GA), simulated annealing (SA) and artificial immune system (AIS) algorithm to reveal the efficacy of the proposed F-AIS algorithm.     

Digitalization for supply chain resilience and robustness: The roles of collaboration and formal contracts

Black swan events such as the coronavirus (COVID-19) outbreak cause substantial supply chain disruption risks to modern companies. In today’s turbulent and complex business environment, supply chain resilience and robustness as two critical capabilities for firms to cope with disruptions have won substantial attention from both the academia and industry. Accordingly, this study intends to explore how digitalization helps build supply chain resilience and robustness. Adopting organizational information processing theory, it proposes the mediating effect of supply chain collaboration and the moderating effect of formal contracts. Using survey data of Chinese manufacturing firms, the study applied structural equation modelling to test the research model. Results show that digitalization has a direct effect on supply chain resilience, and supply chain collaboration can directly facilitate both resilience and robustness. Our study also indicates a complementary mediating effect of supply chain collaboration on the relationship between digitalization and supply chain resilience and an indirect-only mediation effect on the relationship between digitalization and supply chain robustness. Findings reveal the differential roles of digitalization as a technical factor and supply chain collaboration as an organizational factor in managing supply chain disruptions. Paradoxically, formal contracts enhance the relationship between digitalization and supply chain resilience but weaken the relationship between supply chain collaboration and supply chain resilience. The validation of moderating effects determines the boundary conditions of digitalization and supply chain collaboration and provides insights into governing supply chain partners’ behavior. Overall, this study enhances the understanding on how to build a resilient and robust supply chain.     

Blockchain technology for enhancing swift-trust,collaboration and resilience within a humanitarian supply chain setting

There has been tremendous interest in blockchain technology (BT) (also known as distributed ledger technology) around the globe and across sectors. Following significant success in the financial sector, other sectors, such as humanitarian sector, have started deploying BT at various levels. Although the use of BT in the humanitarian sector is in its infancy, donors and government agencies are increasingly calling for building BT-enabled swift-trust (ST) and more collaborative relationships among various humanitarian actors in order to improve the transparency and traceability of disaster relief materials, information exchanges and flow of funds in disaster relief supply chains. Our study, which is informed by organisational information processing theory and relational view, proposes a theoretical model to understand how BT can influence operational supply chain transparency (OSTC) and ST among actors engaged in disaster relief operations. Our model also shows how BT-enabled ST can further improve collaboration (CO) among actors engaged in disaster relief operations and enhance supply chain resilience (SCR). We formulated and tested six research hypotheses, using data gathered from international non-governmental organisations with the help of the Coordinator for Humanitarian Affairs (OCHA) database. We received 256 usable responses using a pre-tested survey-based instrument designed for key informants. Our results confirm that our six hypotheses were supported. Our study offers significant and valid contributions to the literature on ST, CO and SCR and BT/distributed ledger technology. We have also noted the limitations of our study and have offered future research directions.     

Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak

An intertwined supply network (ISN) is an entirety of interconnected supply chains (SC) which, in their integrity secure the provision of society and markets with goods and services. The ISNs are open systems with structural dynamics since the firms may exhibit multiple behaviours by changing the buyer-supplier roles in interconnected or even competing SCs. From the positions of resilience, the ISNs as a whole provide services to society (e.g. food service, mobility service or communication service) which are required to ensure a long-term survival. The analysis of survivability at the level of ISN requires a consideration at a large scale as resilience of individual SCs. The recent example of coronavirus COVID-19 outbreak clearly shows the necessity of this new perspective. Our study introduces a new angle in SC resilience research when a resistance to extraordinary disruptions needs to be considered at the scale of viability. We elaborate on the integrity of the ISN and viability. The contribution of our position study lies in a conceptualisation of a novel decision-making environment of ISN viability. We illustrate the viability formation through a dynamic game-theoretic modelling of a biological system that resembles the ISN. We discuss some future research areas.     

Counterfeit capacitors in the supply chain

Counterfeit electronic components have become a significant concern in the electronic parts supply chain. Original equipment manufacturers in particular are concerned about counterfeit components as there have been several recent reports of counterfeit parts entering the supply chain of the US military. This paper presents a case study of multilayer ceramic capacitors for use in a printed circuit assembly in an electronic system on a military aircraft. The capacitors failed during a high temperature screening test. Upon failure analysis it was revealed that the capacitors were not made to the correct specifications and were suspected to be counterfeit and not the authentic military grade capacitors manufactured by Kemet. Further investigation revealed that the suspect multilayered ceramic capacitors had entered into the electronics parts supply chain and were sold as authentic Kemet capacitors that met the higher military-specified requirements. The manufacturing and distribution of the counterfeit capacitors were traced to locations where, according to Kemet, its authentic capacitors are neither manufactured nor distributed.     

Examining the interrelationships between supply chain integration scope and supply chain management efforts

In this article, we study the concept of supply chain integration scope by comparing firms that involve immediate supply chain partners in their strategic efforts (narrow supply chain scope) versus firms that involve supply chain partners beyond the immediate level, for example second tier suppliers and end customers (broad supply chain scope). By relying on Coordination Theory and expanding upon Frohlich and Westbrook's (2001 Frohlich, MT and Westbrook, R. 2001. Arcs of integration: an international study of supply chain strategies. Journal of Operations Management, 19(5): 185–200.  [Google Scholar]) ‘arcs of integration’ principle, we propose that supply chain integration scope and the type of supply chain management efforts deployed by firms are correlated. We use data from a large sample of US and European firms to explore the association between supply chain integration scope and supply chain management efforts. The results show that supply chain integration scope can be predicted by a firm's supply chain management efforts. The implications of our results for practising managers are also offered. Our results suggest that supply chain managers should consider the practices identified in this study while deciding on the appropriate level of supply chain integration scope, i.e., which extended supply chain members to include in their strategic planning efforts.