Allocation flexibility for agribusiness supply chains under market demand disruption

This paper develops a multi-commodity multi-period optimisation model to analyse market demand disruption risk in agribusiness supply chains. It investigates the role of allocation flexibility and the effectiveness of multiple risk management strategies for achieving allocation flexibility. A robust optimisation formulation is used to obtain risk-averse solutions for an objective combining expected profit and risk. Numerical results are presented for a real-life case study of Zespri’s kiwifruit supply chain. The results show that allocation flexibility is effective for mitigating market demand disruption risk. Three proposed risk management strategies, namely diversified demand market, backup demand market and flexible rerouting, improve both expected profit and risk measures. While diversified demand market and backup demand market strategies are equally important for all decision-makers, flexible rerouting is especially significant for less risk-averse decision-makers.     

Roles of inventory and reserve capacity in mitigating supply chain disruption risk

This research focuses on managing disruption risk in supply chains using inventory and reserve capacity under stochastic demand. While inventory can be considered as a speculative risk mitigation lever, reserve capacity can be used in a reactive fashion when a disruption occurs. We determine optimal inventory levels and reserve capacity production rates for a firm that is exposed to supply chain disruption risk. We fully characterise four main risk mitigation strategies: inventory strategy, reserve capacity strategy, mixed strategy and passive acceptance. We illustrate how the optimal risk mitigation strategy depends on product characteristics (functional versus innovative) and supply chain characteristics (agile versus efficient). This work is inspired from a risk management problem of a leading pharmaceutical company.     

Mitigating supply disruption with a backup supplier under uncertain demand: competition vs. cooperation

In case of supply disruption following major disasters, many supply chains tend to break down due to stock-outs and take a long time to recover. However, by keeping emergency sources of supply, some supply chains continue to function smoothly even after a major disaster. In this work, using a game-theoretic-framework, we consider a two-suppliers-one-retailer supply chain with price-dependent stochastic demand in which suppliers are prone to disruption. To investigate the impact of supply disruption we consider two models: SC model, in which the retailer does not maintain any emergency sources of supply against any supply disruption, and SCB model, in which the retailer maintains a backup supplier to mitigate the impact of supply disruption. We mainly focus on the pricing strategies of the suppliers and the mitigating strategies of the retailer under supply and demand uncertainty. We address two coordinating mechanisms to enhance supply chain performance. Our results indicate that in the presence of supply disruption, even with lower probabilities, the retailer would always prefer to take the advantage of a backup supplier and the optimal reserve quantity increases with disruption probabilities. We further investigate the scenario in which the suppliers would always prefer to cooperate with each other.     

Coordination of dual-channel supply chains under demand disruptions management decisions

This paper examines optimal decisions and coordination models for a dual-channel supply chain when the two end competition market demands are simultaneously disrupted. Firstly, we developed the pricing and production decisions models without demand disruptions and propose a revenue sharing contract to coordinate the dual-channel supply chain where the manufacturer is a Stackelberg leader and the retailer is a follower. We derived the conditions under which the maximum profit can be achieved in detailed. We compared the profits under normal case and disrupted case and quantified the information value of knowing demand disruptions. We proposed an improved revenue sharing contract to coordinate the dual-channel supply chain with demand disruptions. The results indicate that the adjusting prices and production quantity are the optimal decisions whether the demand disruptions case or normal case. We also find that the original revenue sharing contract is a special case of improved revenue sharing contract and the market scale change, channel substitutability and deviation cost affected the improved revenue sharing contract under demand disruptions. Finally, we further conduct numerical experiments to show how the demand disruption affects the decisions.     

供应中断和需求扰动下供应链竞合关系研究

考虑供应中断和需求扰动情境下2个供应商和1个零售商组成的两级供应链系统,构建了合作、静态非合作、嵌套式静态非合作3个博弈模型,分析集中式、分散式供应商竞争与合作情形下的零售商采购策略与供应商定价策略。研究表明,当市场需求增大时,分散式供应商合作情形下供应链整体利润最高;当市场需求减少时,集中式供应链整体利润最高。当权衡供应商订货成本与产品供应稳定性时,零售商倾向与相对稳定的供应商合作;当供需同时不确定时,仅较稳定的供应商受影响。     

Information management strategies and supply chain performance under demand disruptions

The operations management literature presents inadequate comprehensive understanding on information management strategies of mitigating supply chain disruption risks. By using control theory modelling and simulation, this study compares the disruption mitigation effects of three information management strategies. From the aspect of stability, the existing stability boundaries are revised by a new method in a two-echelon case. It shows that supply chains (SC) with popular information management strategies are not evidently more stable than traditional ones. From the aspect of disruption recovery time, an innovative two-echelon swiftest response problem under these information management strategies is formulated and solved. Results show that a collaborative planning, forecasting and replenishment (CPFR) SC with complete SC information performs the best. However, in a later operational risk mitigation test, an information sharing (IS) SC with partial information has the smallest bullwhip effect. From the aspect of demand amplification and frequency response, an innovative frequency–response plot of order amplification is proposed in a time-continuous SC with moving average forecasts. It implies the best frequency response for concurrently mitigating both operational and disruption risks coming from a CPFR SC. But for a certain SC structure there is still a balance between mitigating bullwhip effect and quick response. Moreover, it also implies that anti-bullwhip should exist in a certain condition, as realised in our numerical experiments.     

A hybrid risks-informed approach for the selection of supplier portfolio

In conventional supplier selection approaches, cost consideration is usually emphasised and it renders a vulnerable supply chain with various risks. This article aims to develop a quantitative approach for modelling both supply chain operational risks and disruption risks to support decision-making with regard to order allocation and risk mitigation. We introduce two types of risk evaluation models: value-at-risk (VaR) and conditional value-at-risk (CVaR). Specifically, VaR is used to measure operational risks caused by improper selection and operations of a supplier portfolio to the stochastic demand, which may frequently occur but result in relatively small losses to supply chains; CVaR is used to evaluate disruption risks that are less frequent and tend to cause significant damage. After incorporating risk factors into a probability-based multi-criteria optimisation model, different methods and parameters are compared and tested to determine the factors that may influence the supplier selection process. Computational examples by simulation are presented to illustrate the approach and how decision-makers make trade-offs between costs and hybrid risks.     

需求和成本同时发生偏差时供应链协调研究

研究一个供应商和一个零售商组成的供应链,分别在一体化供应链、分散化供应链发生突发事件的情况下,使用收益共享合约协调该供应链。研究发现,收益共享合约在稳定条件下能实现该供应链的协调;当突发事件导致价格敏感系数和供应商的生产成本同时与其预测值发生偏差时,原有的协调被打破,改进的收益共享合约可协调价格敏感系数和成本偏差的分权供应链。     

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.     

A dynamic system model for proactive control of dynamic events in full-load states of manufacturing chains

Risk management is a major concern in supply chains that have high levels of uncertainty in product demand, manufacturing process or part supply. The uncertainties frequently manifest as dynamic events that pose a threat to interrupting supply chain operation. Depending on the nature and severity of uncertainty, the impact of dynamic events can be distinguished into three categories: deviation, disruption, and disaster. Many studies in literature addressed modelling of deviation events. In this paper, a dynamic system model of supply chains is described which can be applied to managing disruptive events in full-load states of manufacturing chains. An example of disruptive events is given which arises from demand shocks in distribution channel. The procedure to construct full-load production functions of complex manufacturing nodes with internal queuing delay is described. Analytic optimal solution is derived for the dynamic model. Given an unordinary event of demand shock, this model can be used to determine if demand shock can be absorbed by a manufacturing chain and the level of contingent resources that must be synchronously activated in multiple nodes of the chain. This model can be used to reduce what could have been a disruptive event into a deviation event, thus enhancing risk management.     

Two-period vs. multi-period model for supply chain disruption management

A novel two-period modelling approach is developed for supply chain disruption mitigation and recovery and compared with a multi-period approach. For the two-period model, planning horizon is divided into two aggregate periods: before disruption and after disruption. The corresponding mitigation and recovery decisions are: (1) primary supply and demand portfolios and production before a disruption, and (2) recovery supply, transshipment and demand portfolios and production after the disruption. In the multi-period model, a multi-period planning horizon is applied to account for a detailed timing of supplies and production. The primary and recovery portfolios are determined simultaneously and for both approaches the integrated decision-making, stochastic mixed integer programming models are developed. While the simplified two-period setting may overestimate (for best-case capacity constraints) or underestimate (for worst-case capacity constraints) the available production capacity, it can be easily applied in practice for a fast, rough-cut evaluation of disruption mitigation and recovery policy. The findings indicate that for both two- and multi-period setting, the developed multi-portfolio approach leads to computationally efficient mixed integer programming models with an embedded network flow structure resulting in a very strong linear programming relaxation.     

The Ripple effect in supply chains: trade-off ‘efficiency-flexibility-resilience’ in disruption management

This study aims at presenting the Ripple effect in supply chains. It develops different dimensions of the Ripple effect and summarises recent developments in the field of supply chain (SC) disruption management from a multi-disciplinary perspective. It structures and classifies existing research streams and applications areas of different quantitative methods to the Ripple effect analysis as well as identifying gaps in current research and delineating future research avenues. The analysis shows that different frameworks already exist implicitly for tackling the Ripple effect in the SC dynamics, control and disruption management domain. However, quantitative analysis tools are still rarely applied in praxis. We conclude that the Ripple effect can be the phenomenon that is able to consolidate research in SC disruption management and recovery similar to the bullwhip effect regarding demand and lead time fluctuations. This may build the agenda for future research on SC dynamics, control, continuity and disruption management, making supply chains more robust, adaptable and profitable.     

Modelling a complex supply chain: understanding the effect of simplified assumptions

The benefits of coordinating activities and consolidating distribution points in supply chains are well highlighted and intuitively logical. However, the impact of these decisions on the overall performance of a complex supply chain may not be as obvious as usually perceived. This study models a relatively complex supply chain and evaluates the impact of simplifying demand and lead time assumptions under various supply chain configurations. Of particular interest is the investigation of the effect of risk pooling and the synchronization of production cycles in a multi-level multi-retailer supply chain under the influence of various parameters such as batch size, delivery frequency and ordering cycle. This study highlights the extent of complicated interaction effects among various factors exist in a complex supply chain and shows that that the intricacy of these effects can be better understood with a simulation model.     

An object-oriented simulation meta-model to analyse supply chain performance

This paper proposes a meta-model, which allows automatic building of simulation models of supply chains. The proposed meta-model is made up from a user interface (to define the characteristics of the supply chain), an ad hoc objects library and a software application, to build the simulation model. The meta-model can dramatically reduce to a few minutes or even seconds the time required to test a specific configuration of a supply chain and/or a specific management policy and, since the simulation model is automatically built, neither the personnel skills nor the time available to build the simulation model represent significant hurdles anymore. The meta-model has been applied to represent a simplified supply chain according to six different scenarios, where demand is deterministic. For each scenario a simulation campaign has been performed and the outputs of the model (built through the proposed meta-model) correspond to the predicted results.     

回购契约下应对突发事件的供应链协调策略

在基本回购契约模型基础上,分析了回购契约下实现供应链协调的条件,并针对突发事件造成零售商面临的需求分布变化时供应链协调被打破的问题,提出了具有抗突发事件性的回购契约。这个契约主要将增加的供应商成本考虑进回购价格,使得供应商新增加的成本能够在供应商和零售商之间分配,从而使新的回购契约实现对突发事件的协调应对。应用一个算例对比加以说明。     

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.     

Information sharing and coordination mechanisms for managing uncertainty in supply chains: a simulation study

The study aims to investigate the effectiveness of information sharing and coordination mechanisms in reducing uncertainty. Supply chains are constantly subject to unpredictable events that can adversely influence its ability to achieve performance objectives. This paper primarily aims at managing uncertainties originating from unexpectedly large demand spikes. The supply chain literature is full of effective supply chain uncertainty management practices. This paper reviews the different practices for improving management of uncertainty and proposes several combinations of information sharing and coordination mechanism for reducing the uncertainty in supply chains. Next, the proposed combinations are tested on the make-to-stock supply chain of a paper tissue manufacturer using an agent-based simulation approach to show how the use of different levels of information sharing and coordination can be effective in managing uncertainty under daily operations facing a huge mismatch of actual and forecast demand. The findings of this research suggest that, a centralised information structure without widespread distribution of information and coordination is not effective in managing uncertainty of supply chain networks, even with increased frequency of information flow. Similarly, coordinating material flows without widespread information sharing does not improve supply chain uncertainty management. Central coordination of material flows with supply chain wide information sharing across different members is found to be essential in managing supply chains effectively under uncertainty.     

Competition in two-tier serial and assembly supply chains with general consumer utility functions

We consider two-tier serial supply chains with multiple entrants at each tier and investigate the existence of an equilibrium under a general consumer utility function corresponding to a general inverse price-demand function. In the case of a polynomial inverse price-demand function, we obtain closed-form expressions for the equilibrium prices, the production quantities and the profits of the supply chain entrants. We conclude that the quantity of finished goods supplied to the market, the maximum total operating profit accrued by all supply chain entrants, and the elasticity of the (imputed) demand are all sensitive to the elasticity of slope of the polynomial inverse price-demand function. We then extend our analysis to two-tier assembly supply chains and conclude that most of our results extend to them as well.     

市场需求预测偏差下供应链协调

分两阶段研究了产品市场需求预测存在偏差情况下供应链协调问题。第一阶段，给出市场需求预测下的最优生产批量；第二阶段，首先给出需求预测偏差下的最优供给批量和供应链整体最考掣润，然后提出一种使供应链整体最大利润得以实现的协调机制。最后给出算例加以说明。     

A portfolio approach to supply chain disruption management

A new, computationally efficient portfolio approach to supplier selection in the presence of supply chain disruption risks is proposed, where the selection of supply portfolios for parts is combined with production scheduling of finished products. Unlike most of reported research on the supply chain risk management which focuses on the risk mitigation decisions taken prior to a disruption, the proposed portfolio approach combines decisions made before, during and after the disruption. The two decision-making approaches are considered: an integrated approach with the perfect information about the future disruption scenarios, and a hierarchical approach with no such information available. In the integrated approach, which accounts for all potential disruption scenarios, the primary supply portfolio that will hedge against all scenarios is determined along with the recovery supply portfolio and production schedule for each scenario. In the hierarchical approach, first the primary supply portfolio is determined, and then, when a primary supplier is hit by a disruption, the recovery supply portfolio is selected. For the integrated and the hierarchical decision-making, mixed integer programming models are developed with the two risk-neutral conflicting objectives that account for both time and cost of recovery: minimising expected cost or maximising expected service level. The findings indicate that for both objectives, the integrated decision-making selects a more diversified primary supply portfolio than the hierarchical approach and when all primary suppliers are shutdown by disruption, a single sourcing recovery portfolio is usually selected.