New flexibility drivers for manufacturing,supply chain and service operations

Increasing product proliferation, customisation, competition and customer expectations, as well as supply side disruptions, pose significant challenges to firm operations. Such challenges require improved efficiency and resilience in manufacturing, service and supply chain systems. New and innovative flexibility concepts and models offer a prospective route to such operational improvements. Several emerging issues in flexibility, such as risk and uncertainty management, environmental sustainability, optimal strategies under competition, optimal operations with strategic consumer behaviours are being examined in this regard. This overview provides a concise review of these critical research issues, and discusses related papers featured in this special issue. Four major flexibility drivers are classified: disruption risks, resilience and the ripple effect in the supply chain; digitalisation, smart operations and e-supply chains; sustainability and closed-loop supply chains; and supplier integration and behavioural flexibility.     

Supply chain resilience for single and multiple sourcing in the presence of disruption risks

This paper investigates the use of sourcing strategies to achieve supply chain resilience under disruptions. The coping strategies considered are single and multiple sourcing, backup supplier contracts, spot purchasing, and collaboration and visibility. Collaboration and visibility, which affect suppliers’ recovery capabilities and a buyer’s warning capability, have not been similarly modelled in the past. A scenario-based mathematical model is developed such that it considers objectives under uncertainties including disruption risks and operational risks. A broad numerical study examines its output for various risk attitudes in a decision-maker, ranging from risk neutral to risk averse. The sensitivity of procurement strategies to other key parameters such as recovery and warning capabilities is examined. One of the major findings is that buyer’s warning capability plays a vital role in enhancing supply chain resilience. We seek to build on these efforts to further support disruption planning and mitigation and to obtain a deeper understanding of the relationship between supply chain characteristics and resilience.     

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.     

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.     

Sustainable procurement performance of large enterprises across supply chain tiers and geographic regions

Sustainable procurement is steering today’s supply chains towards responsible business practices. This research aims to examine the trend in the sustainability performance of large enterprises for supplier selection across supply chain tiers and geographic locations. Secondary data on 83 global, large enterprises discussing sustainable procurement practices are analysed using hierarchical multiple regression analysis. Dynamic capabilities view and stakeholder theory are utilised to develop the hypotheses. The results show that sustainable procurement performance for large enterprises varies across supply chain tiers and increases in the direction of the end customer. Due to standardisation of regulations and dynamic capabilities of global, large enterprises, no significant difference is observed across geographic regions.     

Industry 4.0 and resilience in the supply chain: a driver of capability enhancement or capability loss?

The purpose of this research is to develop a better understanding of smart systems and autonomous processes of the Industry 4.0 era. Does the implementation of Industry 4.0 processes and systems expose firms to higher levels of risk in the supply chain through capability loss or does Industry 4.0 spur capability enhancement and thereby increase supply chain resilience? Industry 4.0 is centred on the idea that certain tasks and decisions can be automated through smart systems and autonomous processes. However, is there a risk of losing critical capabilities and the ability to be flexible, agile and resilient to unexpected disruptions in the supply chain? In order to address these questions, this research presents results from semi-structured interviews across multiple industries to provide findings on firms’ uses of smart systems and capability development associated with these systems. Results from this exploratory study may be classified into two primary insights. First, although Industry 4.0 systems are new and, in many cases untested, firms are eager regarding the potential of smart systems to positively impact firm performance and to leverage Industry 4.0 processes for a competitive supply chain advantage. Second, companies did not claim any human capability loss associated with Industry 4.0. In fact, these smart systems may lead to increased supply chain resilience because of capability enhancement and new skill development.     

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.     

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.     

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.     

Supply chain disruption risk management through strategic information acquisition and sharing and risk-sharing contracts

In this paper, we develop a framework that captures the effects of information management and risk-sharing contracts in supply chain networks. In particular, we analyse the impact of strategic information acquisition and sharing on supply chain disruption risks and costs and we evaluate the supply chain performance of risk-sharing contracts. Risk-sharing contracts specify who needs to incur the costs when supply chain disruptions occur. We develop a model that consists of three tiers of multi-criteria decision-makers, manufacturers, retailers, and demand markets. We describe the behaviour or each decision-maker, derive the finite-dimensional variational inequality formulation of the equilibrium conditions of the supply chain and present numerical examples. The numerical examples highlight that it is not a priori clear which participant in the supply chain network will benefit from increased information-sharing activities. Our models indicate that the beneficiary of reduced information-sharing costs is in some cases dependent on the negotiation power of participants and that it is also dependent on the type of risk-sharing contract used. Furthermore, the numerical examples show that, in some cases, information-sharing and risk-sharing contracts are complements while in other cases they are substitutes.     

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.     

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.     

考虑水平竞争的农产品供应链结构设计

运用博弈论方法，建立了由农户、合作社、社会企业组成的三级农产品供应链，分析合作社和社会企业之间不同水平竞争程度对供应链的影响，以及合作社的益贫性。研究发现：合作社、社会企业之间的不同水平竞争程度，对供应链中所有成员的最优决策和各级成员的总利润均有影响；水平竞争更能体现合作社的益贫性。此外，还分析了合作社独占和共享供货农户对供应链的影响，发现合作社独占供货农户会抑制合作社之间的水平竞争。由此设计出对农户最有利的农产品供应链。     

‘A blessing in disguise’ or ‘as if it wasn’t hard enough already’: reciprocal and aggravate vulnerabilities in the supply chain

We investigate the interrelations of structural and operational vulnerabilities in the supply chain (SC) using discrete-event simulation for a real life case study. We theorise a notion of SC overlays and explore conditions surrounding their appearance. Such overlays occur if the negative consequences of changes in a SC structure as a result of a disruption are either amplified or mitigated by changes in the operational environment. We hypothesise that these overlays can be both reciprocal (i.e. complementary or mitigating) and aggravate (i.e. concurrent or enhancing). Our approach can be used for an efficient management of SC resilience capabilities by varying their levels over time. We show different ripple and bullwhip effect profiles, which lead to either reciprocal or aggravate overlays, and then we develop recommendations on the overlay-driven dynamic variation of resilience capability levels in order to enhance both SC resilience and efficiency through dynamic redundancy allocation. The results can be of value in selecting and deploying operational policies at the right time and scale during and after the recovery periods. Restricting analysis to the disruption period only and ignoring operational dynamics after capacity recovery can result in misleading or inefficient SC resilience and recovery policies.     

Coordinating a supply chain under demand and cost disruptions

In this paper, we investigate the coordination of a supply chain consisting of one manufacturer and n Bertrand competing retailers under disruptions of market demand and production cost. We present a coordination model of a supply chain under normal scenarios. Our findings demonstrate that the coordination scheme designed for the initial production plan should be revised when disruptions of market demand and production cost occur. To resolve this issue, we consider the possible deviation costs caused by disruptions and propose optimal decision models for different disruptions under centralised decision-making. We present an improved revenue-sharing contract model to coordinate the decentralised supply chain under disruptions. The proposed models are then further analysed through numerical examples.     

How do digital technologies improve supply chain resilience in the COVID-19 pandemic? Evidence from Chinese manufacturing firms

Digital technologies (DTs) can assist businesses in coping with supply chain (SC) disruptions caused by unpredictability, such as pandemics. However, the current knowledge of the relationship between DTs and supply chain resilience (SCR) is insufficient. This study draws on information processing theory to develop a serial mediation model to address this deficiency. We analyze a sample set consisting of 264 Chinese manufacturers. The empirical results reveal that digital supply chain platforms (DSCPs), as well as supply chain traceability (SCT) and supply chain agility (SCA), fully mediate the favorable association between DTs and SCR. Specifically, the four significant indirect paths indicated that firms can improve SCR only if they use DTs to directly or indirectly improve SCT and SCA (through DSCPs). Our study contributes to the literature on resilience by examining the possible mechanism of mediation through which DTs influence SCR. The findings also offer essential insights for firms to modify their digital strategies and thrive in a turbulent environment.     

Bottleneck identification in supply chain networks

In supply chain risk management, it is essential to identify firms that induce high losses due to supply chain disruptions in a focal firm or the supply chain network as a whole (bottlenecks). In this article, we describe supply chain networks as complex systems of firms and their suppliers. We revisit some established network measures and compare their predictions with a new methodology for detecting bottlenecks. In this bottom-up approach, production disruptions on the firm level are modelled with stochastic point processes, and a mechanism for the propagation of losses through the network is defined. The individual firms' emerging loss contributions to the total losses of the focal firm provide, then, an alternative risk-adjusted measure. Our methodology and findings enable more informed and transparent decisions to be made for optimal supply chain network design.     

The impact of supply base complexity on disruptions and performance: the moderating effects of slack and visibility

In the face of increasing supply base complexity, organisations have to develop new ways to manage or mitigate risk. This paper investigates the impact of four dimensions of complexity on the frequency of disruptions and plant performance. We apply insights from organisational information processing theory to understand how organisations can mitigate against the impact of more frequent disruptions. We test the moderating effects of slack resources as a means to absorb the effects of disruptions and supply visibility as a means to improve the ability to handle disruptions. The model is tested with data from 264 supply chain management professionals. Our findings broadly support the original hypotheses and suggest that supply base complexity can increase the frequency of disruptions and reduce plant performance but that slack resources and visibility can help to mitigate the effects. The study offers valuable insights into the management of supply base complexity.     

Bayesian network modelling for supply chain risk propagation

Supply chain risk propagation is a cascading effect of risks on global supply chain networks. The paper attempts to measure the behaviour of risks following the assessment of supply chain risk propagation. Bayesian network theory is used to analyse the multi-echelon network faced with simultaneous disruptions. The ripple effect of node disruption is evaluated using metrics like fragility, service level, inventory cost and lost sales. Developed risk exposure and resilience indices support in assessing the vulnerability and adaptability of each node in the supply chain network. The research provides a holistic measurement approach for predicting the complex behaviour of risk propagation for improved supply chain risk management.     

Supply chain risk and resilience: theory building through structured experiments and simulation

The research literature of supply chain risk and resilience is at a critical developmental stage. Studies have established the importance of these topics both to researchers and practitioners. They also have identified factors contributing to risk, the impact of risk and disruptions on performance, and the strategies and tactics used to build the capacity for supply chain resilience. Although these efforts can provide support for constructing a theory of risk and resilience, researchers are currently restricted in their ability to build such a theory by the difficulty of collecting the necessary data. This paper contributes to this literature development effort by summarising prior research reviews and developing a three-component framework aimed at helping researchers to build better theories. This is accomplished through combining structured experimental design with discrete-event simulations of supply chains. The result is a methodology that allows researchers to develop better understanding of the factors that link a disruption to its impact on supply chain performance through both direct and interaction effects. Following the methodology development, the paper concludes with an example using the factors of shock interarrival time, supply chain connectivity and buffer stocks to illustrate the potential for contributing to the theory-building process.