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This paper studies two-stage disruption exposure minimization problems, motivated by the supply disruption issues in the energy and water supply systems. In particular, we address the ambiguity in both the probability distribution and risk preference of decision-makers towards disruption exposures. First, we propose a two-stage distributionally robust model with adjustable uncertainty sets, which solves a supply system solution with the least possible disruption exposures. We show that this two-stage robust disruption exposure model can be reduced to a computationally attractive single-stage mixed-integer linear program. We then propose an extended almost-robust disruption guarantee model to account for the ambiguity in the risk preference of decision-makers. We demonstrate that this almost-robust guarantee model can reveal clear preferences of most decision-makers under limited distribution information, which however does not resort to any particular disutility function specification and can be solved efficiently using a binary search algorithm. A decision support framework is also developed to guide users on how to apply the proposed disruption exposure models. Finally, we apply the proposed models to a distributed energy supply system design problem. Numerical results show that our models significantly outperform a risk-neutral model in hedging against a broad set of supply distributions. Moreover, the almost-robust guarantee model exhibits its advantages in hedging against high disruption levels, and performs the best under the vast majority of distributions regarding all tested statistical criteria.

In the current global market, managing supply is not a straightforward process and it becomes even more complex as uncertainty and disruptions occur. In order to mitigate their impact, the selectio...

International audience; The contribution of this paper is threefold: first, it introduces a new geopolitical risk index that incorporates recent geopolitical events ignored in Caldara and Iacoviello (2018)’s index. In addition to war threats and acts, terrorist threats and acts and nuclear threats, the new indicator accounts for global trade tensions, the changing fundamentals of U.S.-China relations, the escalated U.S.-Iran conflict, Saudi Arabia’s uncertainty, Venezuela’s crisis, and OPEC news that rise in response to important OPEC meetings and events connected with OPEC production levels. Second, it addresses how the volatility of six oil prices (the Nigerian Bonny Light, Brent, Dubai, OPEC, Tapis, and WTI) behave when the developed geopolitical risk index unexpectedly changes. Third, it examines whether OPEC maintains a buffer of spare capacity that it uses to respond to potential crises that reduce oil supplies. We show that an increase in the geopolitical risk index is significantly associated with unanticipated oil price changes, though with varying sensitivities. Our findings also reveal that OPEC’s use of spare capacity reduces the reaction of oil price to geopolitical risks but moderately, thus suggesting a limited stabilizing influence on the oil market. The limited amount of spare production capacity leaves the oil market on a knife’s edge as it deals with a host of potential supply disruptions stemming from geopolitical issues.

Load shedding (LS) is implemented by distribution utilities (DUs) in addressing power supply insufficiency problems to avoid DU system damages. This is commonly implemented by the installation of LS relays in every DU feeder. However, in either scheduled or unscheduled supply disruptions, a huge amount of unnecessary de-loading is taking place in a feeder level LS implementation. In addition, the consumers connected to a de-loaded feeder are in total blackout, that is, consumers have no choice over which appliances to spare from being de-loaded. This study proposes an LS implementation that replaces feeder-level de-loading by a finer consumer-appliance-level de-loading and allows consumers to have some control over their de-loading. In this method, consumers can set an appliance priority level to their selected connected loads at a given time, to avoid a total blackout. Furthermore, to deal with the enormous data involved in this proposed method, both centralised and distributed optimisation approaches are employed to expedite the system processing response. Simulations are conducted to verify the proposed method's functionality. Lastly, economic analysis is done to assess the proposed method's viability.

In this study, a multi-period contingent sourcing model for sustainable sourcing is developed to mitigate the ripple effect caused by supply disruption. In this model, the manufacturer's main suppl...

Enterprise captures market share from competitors through brand advertising and increases consumer demand for this category of products through general advertising. In this paper, considering a sup...

When a disruption caused by human or environmental accident occurs in production systems, it may cause a shortage of the supply, and thus the buyers’ procurement behaviors will be influenced. This paper studies a supply chain comprised of a buyer and two types of suppliers: one is cheap but unreliable and the other is reliable but expensive. If there is a major disruption, the unreliable supplier may not be able to fully satisfy the buyer’s order, despite the fact that it exerts additional effort to rebuild capacity; at the same time, the reliable supplier cannot fulfill extra orders from the buyer due to capacity constraints. In this way, the buyer should strategically allocate its order between the two types of suppliers by offering different contracts at the very beginning, and then the unreliable supplier chooses its optimal restoration effort according to the contract if a disruption occurs. The model is built based on the real-life cases such as Walmart and Apple such that it is the buyer who determines the wholesale price of the unreliable supplier’s products. The results show the optimal contracts provided by the buyer under different circumstances, which aims to help managers design their contracts under disruption risks to maximize the company’s profit.

This article describes using a nonlinear APVIOBPCS to model the resilience response to the failure of one of the suppliers of a two-tier supply chain comprising a retailer and two suppliers. The second supplier then supplies all the goods required by the retailer. The model is chosen as the simplest case to examine resilience. Time to recover from disruption to ship all goods required by customers is slightly worse when the order rate when it reaches capacity limits but is less than the delay in the system from supplier to final shipment. Just over one weeks' maximum shipments stock at each tier guarantees shipments impervious to the collapse of one supplier, controller type has little effect on the performance of the model. These results agree with other researchers in general trend but not in detail. The response does not match the ‘Resilience Triangle.'

In this paper, a mixed-integer linear programming model is discussed to provide joint decision making for facility location and production–distribution across countries for both forward and reverse logistics. A hybrid facility network is considered for cost-cutting and equipment sharing where the facilities of forward logistics are also equipped to provide reverse logistics services. The model considers the dynamic production and storage capacity of the facilities which can be expanded if required. Furthermore, the effectiveness of the model is tested to deal with disruptions due to man-made or natural disasters. The dynamic facility allocation enables the model to withstand the demand/supply disruptions in a disaster-affected zone. Besides this, the model considers carbon emissions caused due to manufacturing, remanufacturing, repair, storage and transportation. These emissions are regulated using cap and trade policy Thus, the proposed model balances resilience and sustainability under uncertain market demand and product returns. The chance-constrained approach is used to obtain the deterministic equivalence of the stochastic demand and returns. The paper also investigates the changes in emission and production level in each country under demand and supply disruptions. The parameters of the model are mapped with the various dimensions of big data such as volume, velocity and variety. The proposed model is solved using randomly generated data sets having realistic parameters with essential big data characteristics.

Rare earth elements (REEs) are important high-tech materials with widespread industrial applications and a high risk of supply disruption. Current physico-chemical methods for REE recovery are energy intensive, complex, and costly. Thus, it is crucial to undertake measures to secure future REE demand and protect the environment as well. Bioleaching as an alternative technology for the recovery and recycling of REEs from a variety of primary and secondary sources has been increasingly explored. The present review provides an overview on REE content of various primary and secondary sources, applied bioleaching microorganisms and methods, reactor setups, as well as a detailed description of known REE leaching mechanisms. The effects of different process parameters including temperature, pH, medium composition, pulp density, and particle size on efficiency of REE leaching are also evaluated in detail. acceptedVersion

This paper studies a continuous-review stochastic inventory problem for a firm facing random demand and random supply disruptions. The supplier experiences operational (on) and disrupted (off) periods with exponentially distributed durations. The firm adopts an order-up-to level policy during the on period and additionally can release an emergency order based on the inventory level just before disruption. This inventory policy is described by a continuous-time Markov chain model. We analyze the model for two different lead time scenarios and suggest solution approaches yielding the optimal policy parameters. In a numerical study, we explore the value of exercising such a policy and show that an emergency ordering opportunity at the disruption time brings substantial cost savings in cases with high lost sales cost, long off period, and low percentage of supplier’s availability.

Supply risk assessments are an integral part of raw material criticality assessments frequently used at the country or company level to identify raw materials of concern. However, the indicators used in supply risk assessments to estimate the likelihood of supply disruptions vary substantially. Here, we summarize and evaluate the use of supply risk indicators and their normalization to supply risk scores in 88 methods published until 2020. In total, we find 618 individual applications of supply risk criteria with 98 unique criteria belonging to one of ten indicator categories. The most often used categories of supply risk indicators are concentration, scarcity, and political instability. The most frequently used criteria are the country concentration of production, depletion time of reserves, and geopolitical risk. Indicator measurements and normalizations vary substantially between different methods for the same criterion. Our results can be used for future raw material criticality assessments to screen for suitable supply risk indicators and generally accepted indicator normalizations. We also find a further need for stronger empirical evidence of widely used indicators.

In a modern economy, international trade is an important factor in the development of various regions. Shipping is one of the most important elements of the global supply chain. However, after the economic crisis of 2008, global shipping revenues plummeted. One way to restore profitability is the consolidation of shipping routes and the globalization of shipping lines. As container transport lines move to larger ships, the structure of the delivery route becomes a structure with intermediate points. This trend put forward higher demands on the port infrastructure, which aggravated the competition between regional ports, as well as ports that could degrade into a large cargo consolidation port. The economic advantage is enhanced by cooperation between shipping lines and ports. Thus, ports and shipping lines in the same supply chain can be mutually beneficial partners. The study analyses the effectiveness of horizontal and vertical cooperation between ports and carriers. As a source of information, a review of the literature on this issue, expert opinions, and statistical data is taken. Next, a mathematical model is built on the basis of cooperative game theory, and numerical analysis is carried out. The results show that the strategy of cooperation of shipping lines strongly depends on the situation with the supply and demand of vessels. A port that interacts with shipping lines will significantly reduce port charges, which creates the advantage of receiving more port requests. However, cooperation may lead to losses for the port, so a redistribution of profits is necessary to maintain the coalition.

Supply disruption is a common phenomenon in business activities. For the case where the supply disruption is predictable, the retailer should make an emergency procurement beforehand to decrease the inventory cost. For the scenario such that the happening time of the supply disruption obeys a certain common probability distribution but the ending time of the supply disruption is deterministic, based on minimizing the inventory cost and under two possible procurement strategies, we establish an emergency procurement optimization model. By considering the model solution in all cases, we establish a closed-form solution to the optimization model and provide an optimal emergency procurement policy to the retailer. Some numerical experiments are made to test the validity of the model and the effect of the involved parameters on the emergency procurement policy.

Giant retailers sell their store brands and (re)sell substitute national brands for manufacturers (suppliers) simultaneously, which becomes an important sourcing and selling supply chain strategy i...

When product recalls happen, firms not only have to incur additional logistics costs but also suffer from a damaged reputation. Besides, they may also supply disruption risk, under which a supplier could fail to deliver the quantity ordered at all. In this study, we discuss how to mitigate supply disruption and recall risks in the perspective of (outbound) product distribution strategy in joint with (inbound) sourcing decision. Specifically, we compare the dedicated and uniform distribution strategies as follows: in the dedicated strategy, the firm divides its market into several regions, and ships products from different suppliers based on the regions; whereas, in the uniform strategy, the firm serves the entire market by randomly shipping the products from several suppliers without distinguishing their sources. Through the comparison of both strategies, we show that the role of recall risk is different from that of supply disruption on the sourcing and distribution decision. In particular, single sourcing is optimal when both recall risk and disruption probability are low; dual sourcing with the dedicated strategy is optimal when the disruption probability is moderate and the recall risk is high; dual sourcing with the uniform strategy is optimal when the disruption probability is high. We also find that the positive correlation in recalls improves (undermines) the performance of the uniform (dedicated) strategy. In contrast, the positive correlation in supply disruptions only undermines the performance of the uniform strategy.

In the actual context of climate change threats, lithium batteries fulfil lot of expectations in order to achieve a cleaner and more sustainable solution for transports, embodied by electric vehicles. According to different studies that identified a noticeable discrepancy between consumption and production, undersupply should be expected until 2045 in the European Union. Thus, ensuring lithium supply for the growth of energy-sustainable industrialised countries is crucial, and different approaches should be undertaken as for the purpose of technological transition, time matters. This paper focuses in analysing lithium prices and their expected evolution. It also studies in deep five ready-to-go lithium mining investment projects worldwide: Whabouchi Project in Canada, Keliber Project in Finland, Cauchari-Olaroz Salars Project in Argentina, Sonora Project in Mexico, and Pilgangoora Project in Australia. The main purpose being to provide an exhaustive analysis of lithium mining investment in order to facilitate the development of preliminary economic assessments of future mining projects, fighting again supply disruption and accelerating the transition to sustainable energy. Conclusions state in first place that prices are expected to return to a more stable behaviour, mainly based on a ramping up of the production by miners, as there are sufficient lithium recoverable resources in order to ensure the demand of future electric vehicles. Moreover, recycling of lithium batteries will represent a significant supply for the future. In second place, an order of magnitude both technical and economic of this mining industry is given. Two aspects can be highlighted: (1) it was possible to establish a linear correlation between the capital expense of the lithium mining investment projects and their expected production of lithium carbonate; and (2) continental brine deposits, where the extraction of lithium is conducted by evaporation processes in man-made ponds, will not represent a push out of the market for the lithium extracted from hard rocks and clays using conventional mining methods as they have almost the same operating costs.

On the whole, research into energy security falls into one of three perspectives: The political perspective, the engineering and geologic perspective, or the economic perspective emphasising market resilience. Common to these perspectives is the emphasis upon examining exposure to supply disruption, but not its probability of occurrence. As petroleum markets have shown themselves generally resilient to secular events and actual disruptions rare, despite perennial concerns, we ask if our understanding of security cannot be improved? We apply financial option theory to three eventful periods to learn the expectations of market participants on the probability of disruptions. We find the forward-looking views of petroleum market participants to be accurate with regard to both price persistence and the resilience of markets in absorbing shocks. Our results cast doubt upon the need for emergency inventories unless justified to dampen market volatility on public good grounds. Keywords: Energy security, Strategic inventories, Financial options and risk neutral density functions

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, som...

The increase in supply network disruptions has shown that many companies have been caught by surprise and were not able to quickly, if at all, recover from these disruptions. In this paper we propose models for optimal recovery from major unpredictable disruptions in a supply network. We consider a supply network that is comprised of customers and production facilities where disruption may occur at any of the facilities and can cause partial failure or complete shutdown of the supply facilities. The novelty of our model is that it incorporates dynamic pricing as a lever to manage demand during such disruptions. In addition to pricing we also incorporate recovery strategies that are based on inventory, transshipment and outsourcing. We allow for the recovery duration and the disrupted capacity to be uncertain and use pricing to reflect temporary impacts of disruption on demand. Demand is price sensitive and accounts for uncertainty in the customers’ willingness to pay during the recovery period. We investigate the cases of multi-sourcing and single-sourcing. The multi-sourcing model is a convex programming model which is easy to solve using commercial solvers. An accelerated Benders decomposition method with valid inequalities is proposed and tested for solving the more complex single-sourcing model. Using a US case study we find that a dynamic pricing recovery strategy can improve profits during recovery from major supply disruptions. Furthermore, we find that a dynamic pricing recovery strategy is more efficient in single-sourcing networks than multi-sourcing networks.

A growing need for global sourcing has forced firms to manage more complex supply chains with increasing risks of supply disruptions. Multi sourcing is a common method to hedge against these risks. In the presence of demand uncertainties and supply disruptions, minimizing the downside risk is necessary. Hence, in this paper a new multi-period and scenario based supply chain model consists of a number of unreliable suppliers and a number of retailers is developed in the form of a multi-period newsvendor problem with a risk averse objective function. In the model, there are two types of retailers both faced uncertain demands: risk sensitive and risk neutral. Retailers have three choices to respond to the customer demand: a forward contract, and two option contracts include reserving a certain capacity in the secondary supplier and buying from the spot market. The problem has also developed as an agent-based system. As a solution approach in the large scale problem instances, a simulation-optimization algorithm is developed. Two kinds of heuristics are compared in order to optimize the simulation procedure: genetic algorithm and q-learning. Results showed the efficiency of the q-learning algorithm.

There are circumstances that one firm will outsource (purchase) products to its competitor in the common market when experiencing an unexpected supply disruption. Such strategies to hedge against the unexpected supply disruption commonly suffers from the higher wholesale price charged by its competitor although it helps maintain its presence on the market. Its competitor also is concerned about encroachment to sell the products to the firm as a rival in the common market. Mathematical models are formulated to maximize each party's profit in both cases of outsourcing and not outsourcing under decentralization and centralization. The results show that both parties benefit from the strategy of outsourcing at the time of disruption. More interestingly, the results also show that the competitor's centralized decision-making is preferred.

This paper studies a dynamic cooperative advertising under supply disruptions. Cooperative (Co-op) advertising is a widely used marketing tool which affects advertising effort policy and advertising subsidy policy throughout the supply chain. First, the manufacturer announces the participation rate of cooperative advertising which specifies the percentage of the retailer’s advertising expenditure that it will provide, then the retailer determines its advertising effort policy. We model this supply chain problem as a Stackelberg differential game, and provide the optimal advertising effort policy and advertising subsidy policy for the manufacturer and the retailer. Based on a Co-op advertising scenarios, we consider the supply disruption. When a supply disruption occurs, the initial cooperative advertising policy need to be revised. To solve this problem, the change of margin of manufacturer and retailer and market scale of product caused by supply disruption must be explicitly considered. This paper discusses how to model the supply disruptions and their impacts, and how to design cooperative advertising scheme under supply disruption.

Supply disruption is a common phenomenon in industry, and loss-aversion has been recognized as an inherent behavior for decision makers. This paper combines these two factors by considering a loss-averse firm facing a random demand and sourcing from two suppliers. One supplier is cheaper but subject to potential disruption possibility, while the other one is reliable but more expensive to purchase from. We establish a stochastic programming to maximize the expected utility under loss-aversion criterion, and characterize the optimal solutions of the order quantities submitted to the two suppliers. It is found that the unreliable supplier is always used with positive order quantity due to its economical advantage, while the reliable supplier can be useless under some condition. We conduct computational experiments which illustrate that the optimal order quantity from the unreliable supplier, as a main supply source, may manifest a distortion from that under risk neutrality. In addition, we investigate the scenario of sequential ordering and formulate the problem as a two-step stochastic dynamic programming. We prove that the order strategy in this scenario can be characterized by two single-sourcing optimal order points, and provide numerical results on parameter sensitivities of the value of flexibility given by the sequential ordering opportunity.

Sufficient supplies of critical raw materials (CRMs) for rapidly developing technologies, e.g., Li-ion batteries, wind turbines, photovoltaics, digitization, etc., have become one of the main economic challenges for the EU. Due to growing import dependency and associated risk of supply disruptions of these raw materials from third countries, there is a need to encourage their domestic production. This is an important starting point for EU value chains crucial for the sustainable economic growth of the whole Union. This contribution has evaluated the possibilities of CRMs supply from the EU’s primary sources. A three-step approach, including an assessment of CRMs’ importance for the EU’s economic growth, their significance in at least two of the three strategic industrial sectors (i.e., renewable energy, e-mobility, defense and aerospace), and their potential availability from EU mineral deposits, has been applied. Results of the analysis have shown that, of 29 critical mineral raw materials (according to the 2020 EC list), the potential to develop manufacturing from the Union mineral deposits exists for 11 CRMs, i.e., cobalt, graphite (natural), HREE, LREE, lithium, magnesium, niobium, PGMs, silicon metal, titanium, and tungsten, while some other CRMs, namely gallium, germanium, indium, and vanadium can be recovered as by-products. Measures to mitigate EU import dependency have been also proposed.

The performance of a power grid after a disaster is associated with the grid’s ability to meet electricity demand under supply disruption. Prior studies primarily focused on reducing risk t...

The growing number of Electric Vehicles poses a serious challenge at the end-of-life for battery manufacturers and recyclers. Manufacturers need access to strategic or critical materials for the production of a battery system. Recycling of end-of-life electric vehicle batteries may ensure a constant supply of critical materials, thereby closing the material cycle in the context of a circular economy. However, the resource-use per cell and thus its chemistry is constantly changing, due to supply disruption or sharply rising costs of certain raw materials along with higher performance expectations from electric vehicle-batteries. It is vital to further explore the nickel-rich cathodes, as they promise to overcome the resource and cost problems. With this study, we aim to analyze the expected development of dominant cell chemistries of Lithium-Ion Batteries until 2030, followed by an analysis of the raw materials availability. This is accomplished with the help of research studies and additional experts’ survey which defines the scenarios to estimate the battery chemistry evolution and the effect it has on a circular economy. In our results, we will discuss the annual demand for global e-mobility by 2030 and the impact of Nickel-Manganese-Cobalt based cathode chemistries on a sustainable economy. Estimations beyond 2030 are subject to high uncertainty due to the potential market penetration of innovative technologies that are currently under research (e.g. solid-state Lithium-Ion and/or sodium-based batteries).

Supply chain is virtually an open complex giant system. Given nonlinearity, uncertainty and dynamics in supply chains, the case of supply disruptions caused by natural disasters, terrorist attacks and other kinds of accidents is increasing. A throughput-based analysis reveals that cloud-based mechanism improves the information sharing and quality controlling during the process of supply chain management when supply disruption occurs. In this regard, we investigate how supply disruption affects supply chain performance in traditional supply chain and cloud-based supply chain system. Applying system dynamics simulation, this paper established a two-echelon supply chain simulation mode and analyzes how each of these sub-structures responds to a supply disruption. Result shows that cloud-based system is an advanced supply chain management model, compared to traditional mode, it can effectively decline inventory, reduce cost, improve to be out of stock and raise service levels when experiencing supply disruption.

The large mining companies usually outsource the blasting service. There are two options regarding the management of the stocks of the explosives: first, the mining company management; second using Vendor Managed Inventory [VMI], which means that the supplier responsible for the management of the stock and all the logistics of delivery of the material. The present work has the objective of studying the effectiveness of this VMI in a supplier of a transnational mining company. Logistics costs are accounted for the period from January to September 2018. They are compared to the cost that the miner would have if the material requests were made on their account. The VMI in this mining company is very effective with a total saving of BRL 676.801,92 concerning logistics and BRL 7,356,295.36 about inventories. Furthermore, it was identified that there was no supply disruption, the stocks were in equilibrium according to the maximum and minimum limits and there was a low obsolescence percentage of products.

Alternative measures to deal with supply disruptions exist. We consider a make-to-order (MTO) supply chain with one manufacturer who sources from a single supplier. When a supply disruption occurs, the manufacturer can choose to satisfy some demand by either maintaining production through safety stocks or through a secondary contingent source, and turn some unmet demand into backorders on the basis of compensation. An optimal control model under consideration of the customers’ dynamic reactions to the joint implementation of these strategies is formulated with the objective of minimising the cost of disruption. Through the application of Pontryagin's Maximum Principle, optimal mitigation strategies are established in closed form. They provide analytical guidance on how to dynamically and jointly adapt the quantity of contingent sourcing, the price of compensation, and the speed of safety inventory consumption. The results indicate how cost and time-related factors impact these strategies. We also demonstrate that pure strategies are only effective in tackling short supply shortages. For long disruptions, it is superior to adopt combined strategies that simultaneously incorporate two countermeasures in certain periods.

International audience; The ripple effect could occur when a disruption in supplier base cannot be localised and its consequences propagate downstream the supply chain (SC) adversely affecting the performance. While stress-testing of SC designs and assessment of their vulnerability to disruptions in single-echelon-single-event setting is desirable and indeed critical for some firms, modeling the ripple effect impact in multi-echelon-correlated-events systems is becoming increasingly important. Notably, ripple effect assessment in multi-stage SCs is particularly challenged by consideration of both vulnerability and recoverability capabilities at individual firms in the network. We construct a new model based on integrating Discrete-Time Markov Chain (DTMC) and Dynamic Bayesian Network (DBN) model to quantify the ripple effect. We use DTMC to model the recovery and vulnerability of suppliers. The proposed DTMC model is then equalized with a DBN model in order to simulate the propagation behavior of supplier disruption in the SC. Finally, we propose a metric that quantifies the ripple effect of supplier disruption on manufacturer in terms of total expected utility and service level. The ripple effect measure constructed is examined and tested using two case-studies. The findings suggest that our model can be of value in revealing latent high-risk paths in the SC, analysing the performance impact of both a disruption and its propagation, and prioritizing the contingency and recovery policies.

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.

Practically, supply disruption may lead production process to entirely halt (completely disrupted) or the output to differ in the order size (partially disrupted), which makes it more difficult for the retailer to satisfy stochastic market demand. Under the circumstance, the retailer is likely to procure products from two suppliers to effectively alleviate the demand-supply mismatches. Thus, under supply disruption and stochastic demand, this paper develops both backup sourcing and simultaneous sourcing (SS) strategies to analyze the retailer’s performance, where backup sourcing includes wholesale price priority (WPP) and supply reliability priority (SRP). Specifically, (1) under WPP, when the selling price is relatively lower (higher), the retailer is suggested to activate the reliable backup supplier after the realization of supply disruption (demand uncertainty). (2) Under SRP, two scenarios including minor disruption and major disruption can be identified, where the retailer’s order quantity from the reliable (unreliable) supplier under minor disruption scenario is more (less) than that under major. (3) Finally, this paper systematically compares the retailer’s preferences among WPP, SRP, and SS via theoretical results and numerical examples. That is, when the unreliable supplier is more likely to work normally or shortage cost (selling price) is relatively lower, the retailer prefers SPR regarding the unreliable supplier as backup sourcing due to its lower wholesale price and acceptable supply disruption. Otherwise, the retailer is inclined to WPP regarding the reliable supplier as backup sourcing for ensuring all market demand to be satisfied. In addition, unless the emergency prices of two suppliers are extremely higher, backup sourcing strategies could perform better than simultaneous sourcing strategy.

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 ...

Supply disruption is a common phenomenon in many industries. Motivated by the cases of “Nokia and Ericsson” and “HP”, our study investigates how a core firm utilizes the option contract and the order commitment contract to share and mitigate the supply disruption risk. In a decentralized supply chain, we establish the Stackelberg game models to explore the option and order commitment contracts in single and dual sourcing cases, respectively. We obtain the optimal production and procurement strategies under the two types of contracts, after which we investigate the value of the option contract and the optimal contract selection strategy of the core firm. The results demonstrate that the firm is insulated from the supply disruption risk, and that its profit is independent of the disruption risk and production investment under the option contract. In the single or dual sourcing case, the preference of the core firm for the two contracts depends on the disruption risk level and switches back and forth as the probability of disruption increases. A relatively low option price or a medium-risk operational environment heightens the value of the option contract; hence, the core firm is likely to choose the option contract correspondingly. When a reliable supplier is available, the existence of a reliable supplier is always beneficial to the core firm, however is a threat to an unreliable supplier.

As the technologies we use as a society have advanced, so have the materials used in these technologies. Some of these materials are exotic and highly specialized, making them particularly vulnerable to supply disruptions and supply disruptions particularly impactful. Such materials are designated as “critical” materials. Their level of criticality can be identified by accounting for a number of factors related to their supply risk and the extent to which a supply disruption would impact business operations or society at large. We highlight current methodologies used to assess materials criticality, how these assessments are used to reduce materials-related risk and to what extent there is room for improvement. Particularly, this paper reviews critical materials designations from the United States Department of Energy, the European Union, and the General Electric Company, and how they have changed over the period from 2008 to 2014. The changes suggest that the factors considered in criticality ratings have different natural time scales, and that criticality changes occur both due to supply-side risk mitigation as well as demand-side responses. Response options, whether on the supply or demand side, also span a range of time scales and the interaction between factors with different time scales can play a significant role in the dynamics. To date, many published analyses are snapshots in time. A detailed understanding of how risk profiles evolve remains an open question. The importance and impact of demand-side responses such as recycling, substitution and new technological development are discussed.

An oil supply disruption in OPEC member countries or in the Persian Gulf region may have unusually large effects on crude oil prices because such a disruption may escalate into wider disruptions within these volatile regions. This analysis reviews and updates several past studies to identify specific events that can be linked to oil supply shocks that remove oil production while increasing world oil prices. Using historical data, it finds that a 10% cut in world oil supplies arising from abrupt and large monthly disruptions of OPEC and Persian Gulf crude oil production correlates with a 35–43% increase in inflation-adjusted crude oil prices. The data also reveal that almost all sudden and large oil supply disruptions occurred prior to 2004, which raises some interesting issues about how to interpret the evidence from studies evaluating the impact of future oil disruptions on either prices or the economy.

This article describes pervasive supply disruptions and their impacts on supply chain performance. The retailer sources from two suppliers, one supplier is subject to disruptions and the other supplier is perfectly reliable, but more expensive. According to availability of the disruption information, the authors present four information acquirement models. The research conclusions are as follows: The effect of backup supplier is reduced with the increases of reliability coefficient; The value of information is more sensitive to reliability coefficient but less sensitive to potential market capacity; The earlier the information is available, the higher the profit of vendor is; The value of information is lower when reliability coefficient is close to 0 or 1, while information value is significant when reliability coefficient is 0.5; predetermined amount of backup supplier has nothing to do with the cost of strategic supplier, and predetermined amount of strategic supplier is also no connection with backup supplier's predetermined cost and execution cost.

This paper develops a cooperative emergency inventory model to deal with supply disruptions. To achieve a cooperative state between the two sides in supply chain, the game theory is used and three coordination mechanisms are proposed. With the emergency inventory method which has been established, many tests of numerical experiments are made. The aim is to find the optimal mechanism so that the conditions of three mechanisms need to meet are analyzed. Results show that the total profits of the whole supply chain are unchanged in return mechanism. In cost-sharing mechanism, the manufacturer’s profits are smaller than the profits before coordination, and the supplier’s profits are greater than the former, but total profits of the whole supply chain become larger. The proposed model with the introduction of a second manufacturer mechanism performs best, which can make up the expenses by using the new joined manufacturers. It also can help the manufacturers respond to the supply disruptions effectively and that will not harm the profits of both sides.

Supply disruption has become a critical concern for businesses around the world. The extant literature has dealt mainly with the sourcing decision for a price-taking retailer. In this paper, we study how a retailer can use pricing decisions along with sourcing strategies under disruption risk while competing against another retailer with a more reliable supply chain. The retailer uses two decision levers namely, price adjustment, and split of order between reliable but expensive supplier and/or cheap but unreliable supplier to compete in the end market. Our analyses show that the competitive dynamics is shaped by the cost structure of the players, relative market potential and disruption risk. We find that the retailer focuses on reliable supplies with less price adjustment when it enjoys procurement cost advantage and higher market potential. On the other hand, as the procurement cost advantage and market potential shifts to the competitor; the retailer opts for cheaper but risky supplies and relies on drastic price adjustments. These results have important managerial implications and provide critical guidelines for retailers involved in pricing and sourcing decisions under the threat of supply disruptions.

In recent years, the United States has become much more self-reliant in producing oil, and a newer economics literature suggests that oil demand may be more elastic and U.S. GDP may be less sensitive to world oil price shocks than was previously estimated. These developments suggest somewhat lower security costs may be associated with U.S. oil consumption. This analysis provides updated estimates of the security premiums for U.S. consumption of imported oil, U.S. consumption of domestically produced oil, and the substitution of imported oil for domestically produced oil. Estimates of the expected security costs of U.S. oil consumption are provided over the time horizon from 2015 to 2040, while taking into account projected world oil market conditions, the probabilities and sizes of world oil supply disruptions, the response of world oil prices to those supply disruptions, and the response of U.S. real GDP to those oil price shocks. The estimated oil security premiums suggest that U.S. oil security has become less of a policy concern.

To mitigate supply disruption risks, some manufacturers consider a flexible sourcing strategy, where they have an option of sourcing from multiple suppliers, including regular unreliable suppliers and backup reliable ones. Our objective is to evaluate the costs and benefits associated with flexible sourcing when suppliers are strategic price setters. We show that when each supplier announces a single (wholesale) price, such a game leads to a conflict of incentives and is not realistic in most practical settings. Therefore, we focus on a contingent-pricing game, with wholesale prices contingent on the manufacturer’s sourcing strategy. We describe the resulting equilibrium outcomes corresponding to the manufacturer’s different sourcing and inventory strategies. We show that in equilibrium, inventories are carried either by the manufacturer or by the unreliable supplier, but not both. The manufacturer does not necessarily benefit from the existence of a backup supplier and, in fact, is typically worse off. Similarly, supply chain performance may degrade. Thus, an up-front commitment to sole sourcing may be beneficial. Interestingly, suppliers may benefit from flexible sourcing even though the manufacturer does not. The main results extend to cases when partial backup sourcing is allowed, both suppliers are unreliable, recovery times are non-memoryless, an unreliable supplier may provide a richer set of contingent prices, or the supplier may be risk averse. The online supplementary document is available at https://doi.org/10.1287/mnsc.2016.2626 . This paper was accepted by Yossi Aviv, operations management.

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. ...

Spare parts supply chains are highly dependent on the dynamics of their installed bases. A decreasing number of capital products in use increases the nonstationary supply-side risk especially towards the end-of-life of capital products. This supply-side risk appears to present itself through varying lead times coupled with supply disruptions. To model the nonstationary supply-side risk we consider an exogenous Markov chain that modulates random lead times and disruption probabilities. Assuming that order crossovers do not occur we prove the optimality of a state-dependent base stock policy. Later we conduct an impact study to understand the value of considering stochastic lead times and supply disruption risk in spare parts inventory control. Our results indicate that the coupled effect of random lead times and disruptions can be larger than the summation of individual effects even for moderate lead time variances. Also the effect of nonstationarity on total cost can be as large as the summation of all risk factors combined. In addition to this managerial insight we present a procedure for supply risk mitigation based on an empirical model and our mathematical model. Experiments on a real business case indicate that the procedure is capable of reducing costs while making the inventory system more prepared for disruptions. (C) 2018 Elsevier B.V. All rights reserved.

Supply disruption may cause strong complaints of customers, which is a cost loss for the firms in the supply chain. Obviously, if realizing that there is the disruption risk, the members in a supply chain will adjust their decisions. For analyzing the influence, we consider a popular supply chain mode with dual channels, where one manufacturer has its direct sales channel and one traditional retailer channel. The manufacturer may suffer a supply disruption so that all ordered products by the retailer or the direct retail channel will be lost, and the members in supply chain will bear the corresponding disruption penalty from the customers. By considering four structures with different market power relations, the closed-form optimal price decisions of the four models are given. We found that the disruption factor improves the sales prices for any member structure as compared to the supply chain without the disruption. And the direct retail prices in the different modes are the same as each other, but the price of the traditional channel is influenced by the market share. And the sorts of the sales prices under different structures are given. We also conduct some extensive numerical analysis and compare the results under different structures. We observe that the expected optimal profits of considering the external penalty are smaller than those of no external penalty, and we give a sort of the optimal expected profits. And we also provide the effects of some parameters on the optimal decisions and the optimal expected profits.

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...

Supply chain disruptions can occur at any node if there is a vast array of triggers. A common trigger for manufacturing disruptions is supply interruptions. This paper considers a single-stage supply chain with single manufacturer sourcing from a single supplier, where supply disruptions lead to a production pause and the demand is deterministic. In view of different hitting times and durations of disruptions, this paper compares and selects proactive and reactive strategies for supply disruption management via a cost minimization model. Based on the comparison, two types of dynamic strategies are proposed to guide the mitigation approaches as the disruptions continue. One is a dynamic reactive strategy for a non-prevention system and is called passive-backup, and the other is a dynamic combination strategy that contains reactive and proactive strategies for the prevention system and is called recovery-backup. How the lead time of backup sources, disruption starting time, cost of lost sales, backup costs and backorder rate impact the dynamic strategies is also explored in this paper.

Effective evaluation facilitates the implementation of production quota policy and establishment of future policy directions. However, reliable evaluations of the long-term impacts of production quota policies on critical minerals remain scant. In this study, we first derive hypotheses about the production quota policy and sustainable supply capacity of critical minerals. Based on the theoretical analysis, we apply the generalized synthetic control method to a balanced panel of critical minerals for the years 1999–2017 to analyze the average policy effect and the effects for different minerals. Subsequently, we explain why the policy lacks lasting effects on the economic performance. Our main findings are that the effects of the production quota policy that are not obvious in the initial stage become significant at a later stage and that implementing the policy effectively can lower the supply disruption risk. With policy implementation and an increase in supervision intensity, the production quota policy has a positive impact on improving the sustainable supply capacity for critical minerals but a negative effect on profitability, thereby causing a horizontal change or even decline in the policy effects in the long term. Policy implications are proposed to enhance the sustainable supply capacity of critical minerals for China and other countries seeking supply security.

In this paper, we consider a closed-loop supply chain (CLSC) consisting of two suppliers, one manufacturer, one risk-averse retailer and one fair-caring third-party in the presence of supply disruption. We focus on establishing a dynamic Stackelberg game model with bounded rational expectation and analyzing the game evolution process. The effects of key parameters on the Nash equilibrium solutions and their stability are investigated, as well as the complex dynamical behaviors of the CLSC system are explored by using the stability region, bifurcation graph, the largest Lyapunov exponent (LLE), strange attractors, etc. Moreover, the performance of channel members under different values of parameters is researched by utilizing the (average) expected profits or utilities index. The analysis results reveal that the excessive fast adjustment speed of the manufacturer will lead to the system losing stability and falling into chaos. Also, the retailer’s risk aversion and the third party’s fairness concerns have a destabilization effect on the Nash equilibrium point, while the possibility of supply disruption has different effects on the scope of the adjustment speed of decision variables of the manufacturer. Furthermore, in most cases, an over the top adjustment speed of the manufacturer is disadvantageous to all the channel members for more expected profits, but the third-party can achieve a better performance when the system is in periodic state. Finally, the time-delay feedback control method is proposed to eliminate the system chaos.

This paper provides new quantitative perspectives on energy security. We conduct an analysis in the event of energy resource supply disruption in exporting countries for Japan. The study showed that oil stockpiling by the government and firms plays an important role in energy security; the analysis shows that oil supply disruption does not cause latent demand of oil products — except naphtha — after the supply disruption. However, we found that the supply interruption of town gas caused by liquefied natural gas supply disruption is a possible weak point in Japan's energy security. This would mainly impact a variety of non-energy intensive sectors such as the customer sector. We also show that the energy security of the supply is degraded by the unplanned outage of nuclear power stations, as seen from the disaster at the Fukushima Daiichi Nuclear Power Station. Nuclear power generation and renewable energy power generation can mitigate the impact of energy resource supply interruption in the power generation sector.