Strategic cooperation with a backup supplier for the mitigation of supply disruptions

We study optimal sourcing decisions for a firm with a dedicated supplier and a backup supplier. The dedicated supplier charges a lower wholesale price but faces a potential disruption risk. The backup supplier is assumed to be perfectly reliable but charges a higher wholesale price. The primary question we address is how the firm should cooperate with the backup supplier to hedge against the disruption risk. We consider three common cooperation options: advance purchase, reservation and contingency purchase. Our basic results show that the firm should choose advance purchase strategy if the disruption probability is high, while contingency purchase strategy benefits the firm more if the disruption probability is low. Under an intermediate disruption probability, the firm should choose reservation strategy only if the reservation fee is sufficiently low. Then, we explore the optimal backup strategy under partial disruption risk. The results show that the advance purchase and the reservation strategy should be adopted more widely when the dedicated supplier guarantees a relatively high yield rate after disruption.     

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.     

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.     

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.     

Evaluation mechanism for structural robustness of supply chain considering disruption propagation

This paper aims to develop a novel evaluation mechanism for assessing the structural robustness of a supply chain considering disruption propagation. Disruption propagation means that the impact of risks propagates to the whole supply chain along the connected structure. Based on the propagation model, a structural robustness evaluation mechanism is devised by integrating two quantitative metrics, average path length and in degree-out degree. To validate the proposed mechanism, the result of the quantitative assessment of the structural robustness on random networks is compared with the probability of network disruption due to the random risk. From the results of the statistical verifications and sensitivity analysis, it can be said that the proposed mechanism is better at explaining the robustness of a supply chain. In other words, all components of a network, such as nodes and arcs, and their relationships should be considered altogether, in order to more accurately measure the robustness. It may be possible to apply the proposed mechanism to the very first step of designing the supply chain. Especially, in the case of it being hard to redesign a supply chain structure after practically launching and operating the designed network, the proposed mechanism may be utilised to verify whether the planned supply chain is robust to risks or not.     

Random yield and coordination mechanisms of a supply chain with emergency backup sourcing

This paper considers a supply chain in which a buyer purchases finished items from a contracting supplier to satisfy a stochastic market demand, where the supplier’s production is subject to random yield. We assume that the buyer can make up the shortage by sourcing from an emergency backup supplier. We develop two Stackelberg game models, i.e. buyer-Stackelberg (BS) model and supplier-Stackelberg (SS) model, and find that the decentralised BS model results in a higher stocking factor of supplier’s input than the decentralised SS model. Compared with BS model, the buyer in SS model performs more explicit order plan, and we find that only when the actual yield of the supplier is insufficient, the buyer would use emergency backup sourcing to make up the shortage. When the manufacturing operation of the supplier is in the good state, the buyer only orders a certain amount and has some leftover. When the actual yield of the supplier is moderate, the buyer uses up every item produced from the supplier regardless of the yield rate. Comparing both channel structures, SS operation is a more effective way of controlling both inventory cost and backup sourcing cost, and it can be beneficial for each player as well as for the whole channel. Finally, we develop the coordination mechanism for each channel to investigate the issues of risk handling and risk sharing for uncertain demand and uncertain yield.     

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.     

Equilibrium markup pricing strategies for the dominant retailers under supply chain to chain competition

Markup pricing policies have been widely employed in the retailing industry. Under such policies, a retailer requires a retail margin over the wholesale price charged by the supplier to guarantee her profitability. This paper investigates and compares the performance of two commonly used markup pricing policies, namely, fixed-dollar markup and percentage markup, for the dominant retailers facing chain-to-chain competition. Our results demonstrate that the equilibrium pricing strategy for the dominant retailers seeking to maximise their respective profits is [PP]-strategy (i.e. both retailers select the percentage markup pricing policy), no matter what the demand curve and the level of chain-to-chain competition are. Unfortunately, this equilibrium will get in the prisoner’s dilemma since the percentage markup pricing strategy might yield lower profits for the retailers and suppliers compared to its fixed-dollar counterpart when the level of chain-to-chain competition is high enough under the linear demand, which is contrast to the literature. If the criteria for the dominant retailers to select which markup pricing policy to offer is the whole channel’s profit obtained under the decentralised decision-making scenario instead of themselves, [PP]-strategy is the dominant strategy and the unique Nash equilibrium of the pricing policy choice game regardless of the competitive intensity under the iso-elastic demand. This result holds true for the linear demand only when the level of chain-to-chain competition is below certain threshold; otherwise, both [FF] (i.e. both retailers select the fixed-dollar markup pricing policy) and [PP] can be the equilibrium pricing strategy.     

Enhanced joint pricing and lotsizing problem in a two-echelon supply chain with logit demand function

In retail supply chains, ordering and pricing policies for the retailer and shipment plan for the supplier are the most important decisions. These policies are often conducted either individually or sequentially with poor overall performance for the whole supply chain resulting to extra inventory and other deficiencies. In this paper, an integrated marketing-inventory model in a two-echelon supply chain model is developed involving discount promotion, customer behaviour more realistically and operations aspects to determine optimal ordering, shipping and pricing quantities simultaneously. An efficient analytical solution procedure and a Particle Swarm Optimisation solution algorithm are also developed. Finally, a number of numerical tests are conducted to approve the interesting theoretical results of the analytical approach.     

A pricing/ordering model for a dyadic supply chain with buyback guarantee financing and fairness concerns

The paper investigates pricing/ordering issues in a dyadic supply chain, in which a core supplier sells products through a budget-constrained retailer. The retailer faces stochastic demand and is fairness-concerned as well. If needed, the retailer can get financing support from bank by means of buyback guarantee financing (BGF) mode, which is often used in China. By introducing Nash bargaining solution as the fairness reference point, we formulate the retailer’s fairness-concerned utility function and develop a two-echelon pricing/ordering game model. We then study the combined impacts of fairness concerns and BGF on two members’ equilibrium strategies and supply chain performance. We also discuss the corresponding issues under no budget constraint, no financing service and bank financing. Our results show that: (1) two members’ equilibrium strategies are significantly influenced by the retailer’s fairness-concerned behaviour and initial budget; (2) as compared to no budget constraint, BGF can bring the whole supply chain more performance, which means that BGF can yield value-added; (3) When the retailer takes the risk of uncertain market solely, the retailer’s fairness concerns are beneficial for supply chain to improve the performance.     

Pricing decisions for a supply chain with refurbished products

This paper considers a supply chain consisting of a supplier and a retailer where a fixed portion of new products sold will be returned to the retailer and then be repaired and resold as refurbished products at a lower price. Using the utility model, we formulate how consumers will make their choices when facing both new and refurbished products. Then, using the divide-and-conquer method, we derive the supplier and retailer's equilibrium decisions, including the supplier's wholesale price and the retailer's prices for both the new and refurbished products. The main findings include the following. First, refurbished products will be sold in the market only when the refurbishing cost is small. In this situation, as the refurbishing cost increases, most of the negative impact on the retailer will be transferred to the supplier. Second, in the same condition, as the refurbishing cost increases, the wholesale price and retail price of the new product will change in opposite directions. This result contrasts with the traditional pass-through effect. Third, when the repair cost is moderate, the retailer will eventually not sell refurbished products, but its profit can be significantly improved and the double marginalisation effect can be mitigated.     

Collection channel and production decisions in a closed-loop supply chain with remanufacturing cost disruption

Enterprise risk management (ERM) focuses on managing functions of an entire business, with special attention to supply chain uncertainty. Managing supply chain through effective ERM will mitigate firm exposure to risk in operations and ensure the success of the business. We study collection channel and production decisions in a closed-loop supply chain (CLSC) with one dominant manufacturer and one retailer, from the perspective of both firm profit and system robustness. A robust system is desired as only minimal changes in production plan are necessary when facing disruption, and is valuable for enterprise risk reduction. We find that without disruption the indirect (retailer) collection channel achieves higher profit than that of the direct (manufacturer) channel, which is also true under some disruption cases. However, the direct channel is more robust when facing disruption, and generates more profits for manufacturers when the positive disruption is large. We also find that the revenue-sharing contracts are effective in coordinating members of the CLSC. Finally, we conduct numerical studies to validate the models and derive managerial insights.     

Methods for mitigating disruptions in complex supply chain structures: a systematic literature review

Supply chain risk management is extremely important for the success of a company. Due to the increasing complexity of supply chains, avoiding and mitigating the effects of disruptions is very challenging. This article presents the results of a systematic literature review and content analysis in order to provide a comprehensive overview of the methods that are currently used for mitigating supply chain disruptions. The results of the review indicate that research in this field is interdisciplinary and that no common modelling language has emerged thus far. Prior research mostly redraws to graph theory and/or social network analysis, although a few methods have been developed recently specifically for supply chain risk management. We observe that prior contributions addressed risk and structure mostly separately and that only a few works focused on their intersection. The results of this review are consolidated in a research agenda that calls for research on the risk-structure-interface and the development of proxy methods.     

Optimal ordering policy for a price-setting newsvendor with option contracts under demand uncertainty

In this article, we investigate the newsvendor problem in a joint ordering and pricing setting in the presence of option contracts under demand uncertainty. At the beginning of a single selling season, the newsvendor who faces additive stochastic demand can obtain goods through two ways: ordering from a firm or purchasing and exercising call options. Single ordering (ordering from a firm only or purchasing and exercising call options only) and mixed ordering (ordering from a firm and purchasing and exercising call options simultaneously) cases are investigated. We find that the newsvendor’s optimal pricing and ordering strategies exist and are unique for both cases, respectively. In addition, when both cases are available, mixed ordering is the newsvendor’s optimal ordering policy. If only single ordering is available, the newsvendor prefers ordering from a firm when demand risk is low, while enjoys purchasing and exercising call options when demand risk is high. We also find that with option contracts, the newsvendor’s optimal order quantity and maximum expected profit are all decreasing in the option price and exercise price of product, while the optimal retail price in terms of option price and exercise price of product are intricate. Moreover, we show that, mixed ordering is more capable to deal with supply price volatility risk.     

Using speeding detections and numbers of fatalities to estimate relative risk of a fatality for motorcyclists and car drivers

Precise estimation of the relative risk of motorcyclists being involved in a fatal accident compared to car drivers is difficult. Simple estimates based on the proportions of licenced drivers or riders that are killed in a fatal accident are biased as they do not take into account the exposure to risk. However, exposure is difficult to quantify. Here we adapt the ideas behind the well known induced exposure methods and use available summary data on speeding detections and fatalities for motorcycle riders and car drivers to estimate the relative risk of a fatality for motorcyclists compared to car drivers under mild assumptions. The method is applied to data on motorcycle riders and car drivers in Victoria, Australia in 2010 and a small simulation study is conducted.