Retailer’s sourcing strategy under consumer stockpiling in anticipation of supply disruptions

We study a retailer’s sourcing strategy under consumers’ stockpiling behaviour and the factors associated with the selection of an optimal strategy in multi-tier supply chains in the presence of supply disruption risk. Stockpiling behaviour occurs when consumers attempt to mitigate the negative impact of a supply shortage. We prove that those behaviours become stronger if consumers have experienced similar problems before and weaker as more inventories are hoarded. Based on these findings, numerical analysis is carried out to compare the superiority of single sourcing versus dual sourcing from retailer’s perspective. Our results suggest that the superiority is highly dependent on factors such as supplier’s volume flexibility, retailer’s purchasing price, and supplier reliability.     

Review of supplier diversification and pricing strategies under random supply and demand

Uncertainties of supply and demand are two major sources of risk in any supply chain. As a result, the companies are implementing different strategies to mitigate the effects of these risks. Supplier diversification and responsive pricing are two of the main strategies that are used to mitigate the supply and demand risks. In supplier diversification, a firm uses multiple channels of sourcing while in responsive pricing, a firm manipulates demand through pricing to mitigate supply and demand risks. In this paper, we review lot-sizing problems when supply and demand are random. We focus on studies that have considered supplier diversification or responsive pricing as a mitigation strategy. We classify the studies based on their main assumptions and summarise their major findings. Finally, we present some directions for future research. Part of what we have found is that most studies that use multiple decision makers have focused on cases where information is complete and non-cooperative. There is a need to consider more realistic situations when there is information asymmetry between the decision makers. In addition, we have found that there is a lack of studies that look at the impact of joint ordering and pricing in the existence of multiple suppliers.     

Flexible strategies under supply disruption: the interplay between contingent sourcing and responsive pricing

Due to possible supply disruptions because of a low-cost unreliable supplier, a firm may use a high-cost reliable supplier as an additional regular supplier (dual sourcing) or an emergency backup supplier with an extra emergency cost (contingent sourcing). We consider the firm's sourcing problem when the pricing decision is made before any supply uncertainty is resolved (committed pricing) or after the supply state is realised (responsive pricing). By comparing the relative value of responsive pricing in contingent sourcing to that in dual sourcing, we study the relationship between contingent sourcing and responsive pricing in mitigating supply disruption risks. We show that the emergency cost and potential lost sales caused by disruption probability jointly impact the interplay of these two strategies. More specifically, when the emergency cost is low and the potential lost sales are lower under contingent sourcing than that under dual sourcing, contingent sourcing and responsive pricing are substitutes; otherwise, they are complements. Furthermore, we examine how disrupted capacity, i.e. the quantity that the unreliable supplier can deliver when disrupted, impacts the interplay, and find that the probability of the substitution relationship becomes higher when the disrupted capacity increases. We also find that under committed pricing, contingent sourcing is not optimal for any value of disruption probability when the emergency cost is high, a phenomenon that does not exist under responsive pricing.     

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.     

Managing supply disruption through procurement strategy and price competition

When facing supply disruptions, the emergency procurement strategy and the optimal allocation procurement strategy are widely used strategies to manage supply risks. In this paper, buyers use these types of procurement strategies under the threat of supply disruption and engage in price competition. The structural properties of the procurement strategies are characterised by their reliability thresholds. We find that reliability thresholds play a critical role in buyer procurement strategy choices, which are related to the sales price, underage cost and differentials in unit procurement cost. A solution procedure is proposed to determine the equilibrium strategy profile. The effects of reliability levels and costs on the equilibrium prices, expected profits and equilibrium strategy profiles are explored. We extend the basic model to investigate the case of symmetric competition where buyers can freely choose their procurement strategy. The results show that in most cases, the competing buyers will choose the same strategy, whether an optimal allocation strategy with single sourcing or an emergency procurement strategy with dual sourcing. In a special parameter setting, the buyers will choose either strategy because they yield identical expected profits; this leads to multiple equilibria. We also find the equilibrium to be Pareto efficient.     

Developing a resilient supply chain through supplier flexibility and reliability assessment

In this study, we examine the optimal allocation of demand across a set of suppliers in a supply chain that is exposed to supply risk and environmental risk. A two-stage mixed-integer programming model is used to develop a flexible sourcing strategy under disruptions. Our model integrates supplier selection and demand allocation with transportation channel selection and provides contingency plans to mitigate the negative impacts of disruptions and minimise total network costs. Finally, a numerical example is presented to illustrate the model and provide insights. The findings suggest that developing contingency plans using flexibility in suppliers’ production capacity is an effective strategy for firms to mitigate the severity of disruptions. We also show that flexibility and reliability of the suppliers and regions play a significant role in determining contingency plans for during disruption. Findings generally show that highly flexible suppliers receive less allocation, and their flexible capacity is reserved for disruptions. For firms that do not incorporate risk management into supplier selection and allocation, the recommendation is to source from fewer, more reliable suppliers with less risk of disruption. Our findings also emphasise that the type of disruption has important implications for supplier selection and demand allocation. This study highlights the supply chain risk management strategy of regionalising as a means for minimising the impact of environmental disruptions.     

Using backup supply with responsive pricing to mitigate disruption risk for a risk-averse firm

We consider a risk-averse firm’s sourcing problem with two suppliers: a dedicated one and a backup one. The dedicated supplier charges a lower wholesale price, but faces potential disruption risk. The backup supplier is assumed to be perfectly reliable, but charges a higher wholesale price. To mitigate the disruption risk, the firm uses a joint backup supply and responsive pricing strategy. We consider three common backup strategies between the firm and the backup supplier: advance purchase, reservation and contingency purchase. We derive under what conditions each strategy could be optimal. The results show that the thresholds that determine the optimal backup supply strategy are affected by the risk aversion level. When the risk aversion level is not extremely high, the firm should choose among the three backup suppliers by considering the disruption probability and the reservation fee. Firms with a higher risk aversion level tend to rely more on ex-ante preventive efforts (i.e. reservation or advance purchase strategies). When the risk aversion level is extremely high, the firm never considers the contingency purchase strategy, even for a low-probability disruption event. Additionally, market conditions yield non-negligible influences on the firm’s strategic choices due to the existence of risk aversion.     

Development and evaluation of the interactive bidding strategies for a demander and its suppliers in supplier selection auction market

Supplier selection strategy is a critical issue in a supply chain management (SCM) system. Selecting the correct suppliers can have a significant impact on the competitiveness of firms. This research is concerned with the development of the interactive bidding strategies for a demander and its multiple suppliers in a supplier selection auction market (SSAM). The objective of this paper is to investigate the negotiation efficiency for the various bidding strategies the demander employed in different order conditions. The negotiation efficiency is assumed as the required negotiation times to achieve an agreement, agreed price and the procurement costs. Further, this paper runs the experiments of SSAM and provides a bidding strategy guideline for a demander to achieve its goals of supplier selection in varying order conditions. To this end, the negotiation efficiency of this proposed bidding strategy model is compared with other research.     

Procurement decisions and information sharing under multi-tier disruption risk in a supply chain

We consider a manufacturer's procurement decision in a three-tier supply chain (SC) under disruption risk. The manufacturer sources components from a single first-tier supplier (FT). The FT, in turn, sources raw materials from a single second-tier supplier (ST). Suppliers in both tiers are unreliable, i.e. prone to disruption risk. Increasing SC visibility through information sharing is a potential disruption management strategy for the manufacturer. While the manufacturer can obtain disruption risk information for the FT, disruption risk information for the ST is not easily accessible to the manufacturer except through the FT, who may not be willing to share ST information. We study different mechanisms under which the manufacturer can obtain ST information, and its impact on manufacturer's and FT's decisions and potential profits. We show that information sharing makes the manufacturer's procurement decisions more conservative, i.e. carrying more inventories, but the FT's procurement decision is contingent on the ST's reliability; more proactive (conservative) when ST is unreliable (reliable), i.e. carrying less (more) inventories. We demonstrate that there are two ways to induce the FT to share its information, and numerically show that their effectiveness is contingent on multiple factors, including FT and ST reliabilities and information sharing costs.     

Blockchain adoption or contingent sourcing? Advancing food supply chain resilience in the post-pandemic era

In the post-pandemic era, food supply chains and firms therein are facing unprecedented severe challenges, because once infection is detected, numerous products must be recalled or abandoned, and both suppliers and retailers in the supply chain suffer enormous loss. To survive under the pandemic, retailers have adopted different sourcing strategies, such as contingent sourcing, which, in turn, affect the upstream suppliers and hence the resilience of the whole supply chain. With the rapid development of digital technologies, retailers nowadays can utilize blockchain as a reliable and efficient way to reduce product risk and hence advance the resilience of food supply chains by improving product traceability and inspection accuracy, and making sourcing transparent. In this paper, we develop a game-theoretic model to investigate the interrelation between the retailer’s decisions on blockchain adoption and sourcing strategies. We consider that a retailer originally orders from a risky supplier while conducting an imperfect inspection to detect infected products before selling. The retailer may speculatively keep on ordering from the risky supplier or adopt contingent sourcing by ordering from an alternative safe supplier. The retailer also has an option to implement blockchain to improve the inspection accuracy and product traceability. We derive the optimal retail prices under different sourcing strategies with and without blockchain adoption and then analyze the incentives for sourcing strategy and blockchain adoption. Then, we identify the conditions of an all-win situation for food retailer, supplier, supply chain resilience, and consumers with/without government subsidy. Finally, we extend to consider the situation that some consumers have health-safety concerns and preferences for blockchain adoption.     

供应中断情况下动态混合应急策略研究

动态刻画市场需求中断反应行为:自动留存订单、等待制造商应急采购延迟完成订单、由安全库存完成订单、取消订单。综合考虑应急采购的提前期及成本、安全库存储备量、企业恢复能力,构建以中断负面影响最小化为目标的最优控制模型。应用最大值原理,提出三种最优的制造商动态响应策略,包含一种纯库存与两种混合策略,决策如何基于库存量、中断持续时长等相关因素实时消耗库存,同时进行应急采购。     

Incorporating risk aversion and fairness considerations into procurement and distribution decisions in a supply chain

This paper considers a three-tier supply chain in which a manufacturer uses raw materials sourced from multiple suppliers to produce an item and sells it through multiple distributors. We develop an integrated optimisation model to study supply chain procurement and distribution decisions incorporating the manufacturer’s aversion to risk and the distributors’ concern for fairness in a climate of uncertain supply and demand. Resilient strategies, such as alternative sourcing and transshipment, are also considered when optimising the supply chain cost and service level. To solve the problem, a Monte Carlo simulation-based multi-objective stochastic programming model is built. It uses the CVaR (Conditional Value-at-Risk) and unfairness aversion utility function to reflect the decision maker’s risk aversion and the customer’s concern for fairness, respectively. A Normalised Normal Constraint based algorithm is adopted to obtain the Pareto Frontier. In addition, the numerical analysis provides some valuable insights for supply chain managers.     

The optimal technology licensing strategy under supply disruption

We study the problem of whether and how a patent-holding firm (supplier S1) should license its technology patent to a potential rival (supplier S2). If the license is given, the two suppliers both produce a critical component for their downstream manufacturer simultaneously (sequentially) when the manufacturer adopts a dual (contingent) sourcing mode. However, both suppliers face risks of complete supply disruptions. In the study, we examine how the supply risk affects S1's technology licensing willingness and under which conditions royalty or fixed-fee licensing is its optimal strategy. The results show that when the manufacturer adopts contingent sourcing, S1 is always willing to license its technology to S2 and fixed-fee licensing is the optimal strategy. However, when dual sourcing is adopted, either royalty and fixed-fee licensing could be S1's optimal licensing strategy, depending on the reliability degree of the suppliers’ productions. Our findings extend the conclusion from previous researchers about royalty and fixed-fee licensing in a Cournot duopoly model.     

Newsvendor problem with multiple unreliable suppliers

This paper focuses on supplier-related decisions in a newsvendor setting. We build upon the current literature by analysing the newsvendor problem with multiple unreliable and non-identical suppliers. We also incorporate both fixed ordering costs and capacity limits for supplier selection. We develop an exact algorithm to solve the problem optimally and a heuristic algorithm to solve the problem efficiently. Through structural properties of the optimal solution and a numerical study, we provide useful managerial implications regarding optimal sourcing strategies in complex supply chains. Previous literature concludes that with multiple unreliable (independent) suppliers, cost is the order qualifier and reliability is the order winner. We found that when fixed ordering costs and supply capacities exist, this insight no longer holds. We also examine the sensitivity of the sourcing decisions to supplier capacity levels, demand uncertainty, salvage value and shortage cost. Our results show that high levels of demand uncertainty lead firms to turn to a single-sourcing strategy whereas high salvage values and high shortage cost suggest multi-sourcing strategy.     

Distribution planning for multi-echelon networks considering multiple sourcing and lateral transshipments

Nowadays, due to the increasing complexity of business environment, especially demand uncertainty, supply chain managers need to establish more-effective sourcing and distribution strategies to ensure high customer service and low stock costs. To overcome this challenge multi-echelon network structures and alternative distribution strategies such as lateral transshipments and multiple sourcing should be considered in inventory optimisation models. In this article, we propose a scenario-based modelling approach to solve a two-stage multi-echelon inventory optimisation problem with a non-stationary demand. The model is based on a distribution requirements planning (DRP) approach and minimises the expected total cost that is composed of the fixed allocation, inventory holding, procurement, transportation, and back-ordering costs. Alternative inventory optimisation models, including the lateral transshipment strategy and multiple sourcing, are thus built, and the corresponding stochastic programmes are solved using the sample average approximation method. Through a numerical investigation conducted with several generated instances and an empirical investigation based on the case of a major French retailer’s distribution network, we show the substantial benefit of lateral transshipments and multiple sourcing in reducing the expected total costs of the distribution network.     

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.     

Aggregate procurement,production, and shipment planning decision problem for a three-echelon supply chain using swarm-based heuristics

Supplier selection is deemed as a crucial strategic decision-making activity in building a competitive edge. Firms prefer to operate with a few trusted suppliers, selected from a bigger pool of vendors. The chosen suppliers are the ones whose commitments are best oriented in realising the business goals of the company. At the same time enterprise targets cannot be achieved in the absence of cost-effective inventory management policies. This has created the inevitable need for aggregate production and distribution planning. Even more competitive strategy would be integrating procurement planning with production-distribution scheduling. We address the problem of integrated procurement, production and shipment planning for a supply chain, spanning over three echelons. Supplier order scheduling is combined with a production-shipment planning process to realise a minimum cost operations policy. Two recently developed swarm heuristics are employed to search for the near optimal solution of the mathematical model, which is developed to capture the aggregate planning problem.     

An optimal ordering strategy for a third-party managed supply chain

The rapid pace of new product introduction and global sourcing of raw materials and manufacturing facilities have created a complex and fragmented supply chain. Retailers in many consumer product industries are relying on third-party supply-chain managers (SCMs) to manage the global supply chain cost-effectively with short production lead times. To meet delivery requirements, the SCM must start the production process before receiving a firm order from retailers. We assume a two-stage production process where, in stage 1, a base product is produced. In stage 2, the base product is customised. The SCM absorbs the penalties associated with over- or underestimating retailers’ demand. Hence, the SCM has to decide on (a) the optimal production quantity of the base products and (b) the number of base products to be customised without delay. We develop a profit maximisation model for this strategy using a nonlinear objective function with two decision variables and one constraint. Applying Kuhn–Tucker conditions, closed-form solutions are obtained for the two decision variables. Also, formulations are given for two additional strategies: postpone customisation of all products and produce customised products only. An example illustrates the use of our model. We also examine the impact of demand variability on the effectiveness of the three strategies. Results show that postponement may not always be the best strategy for an SCM.     

竞争环境下新创企业的供应链管理模式选择——应急采购VS饥饿营销

考虑需求不确定下,新创企业和在位企业两条异质供应链竞争对供需匹配策略的影响,运用Bertrand模型比较新创企业供应链实施应急采购和饥饿营销两种策略下的均衡价格和均衡销量,以及供应链的期望利润随市场基本需求和产品替代系数的变化情况。研究发现,当实现的需求不确定性小时,饥饿营销策略下需求响应时间不会影响新创企业供应链的均衡价格和均衡销量;而当实现的需求不确定性大时,实施饥饿营销策略的新创企业供应链里零售商的最优定价会高于应急采购策略的均衡价格,而最终的销量会低于应急采购策略的均衡销量。即使应急采购的额外成本为零,新创企业供应链的期望利润在实施了饥饿营销策略之后,也会比应急采购策略下的期望利润大,并且期望利润的增加率随市场基本需求单调递增,随产品替代系数单调递减。这也意味着新创企业供应链可以有效实施饥饿营销策略。