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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.

The infrastructure required for international natural gas trade is considerable, which often leads to hold-up problems and supply disruptions. This study discusses disruptions of gas supply from Algeria, Indonesia, Russia, and Turkmenistan since the early 1980s. The novelty of this study is its focus on the issues related to transit countries, which are rarely considered in the literature. The results of the study classify supply disruptions into six types, show the evolution of supply disruptions over time, and discuss mitigation strategies. The six types of disruptions include political change, price demands, debts, technical issues, transit fees, theft of gas. The evolution of the disruptions shows that the issues related to transit countries have become more frequent in the last two decades. Mitigation strategies tailored to transit countries include using an international organisation, designing contracts with price mechanisms that might reduce the possibility of disputes and reducing the number of parties involved in the trade.

This paper presents a recovery strategy in manufacturing supply chains that copes with long-term supply disruptions such as those caused by the recent global outbreak of COVID-19 through a combination of product composition changes and safety inventory. A mixed integer programming model is developed for alternative supplier purchase order allocations and manufacturer production order allocations to minimize the profit loss caused by product composition changes after supply disruptions. A solution method that combines the ILOG CPLEX and MATLAB to be used to solve the model. The computational results show that the proposed recovery strategy can effectively reduce the loss of manufacturer after prolonged supply disruptions. The proposed model can help managers consider the optimal recovery strategy when the manufacturing supply chain experiences a long-term disruption.

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.

The US Food and Drug Administration (FDA) is currently seeking information from the clinical community about existing and anticipated disruptions in the supply of medical devices related to COVID-19. This information is important to FDA's fulfillment of its mission to ensure that healthcare providers and patients have continued access to safe and effective medical products. Insights from the clinical community, including clinical engineers and biomedical equipment technicians, bring device supply issues experienced on the front lines to FDA's attention so that the FDA can develop effective strategies to prevent and mitigate medical device supply concerns in its continued response to the COVID-19 public health emergency. Here, we describe the public health impact of the clinical perspective and the type of information that the FDA is seeking regarding current or anticipated medical device supply concerns. Information about how to have your voice heard on this important matter is included at the end of this article.

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...

We consider a supply chain consisting of a supplier and a buyer. The buyer faces demand as a function of the selling price. There is risk of supply disruption, but the supplier can rebuild his capacity if he has invested for the capacity restoration before a disruption. To motivate the supplier to invest, the buyer can use one of two incentive contracts, namely direct and indirect . With a direct contract, the buyer provides a financial subsidy to share the supplier's capacity restoration cost when disruption occurs. With an indirect contract, the buyer adjusts the wholesale price in the case of disruption to stimulate the capacity restoration. Both contracts allow the buyer to adjust the order quantity in the case of disruption. We analyze decisions of each supply chain member under the two contracts with different commitment strategies (the ex ante commitment (EA) strategy under which the contract is signed before disruption and the ex post commitment (EP) strategy under which the contract is signed after disruption), and study how the supply disruption affects the buyer's selling price to end customers. We show that, from the perspective of either the supplier or the buyer, the incentive contract under the EA strategy is preferred by leading to a greater profit. Further, through numerical experiments, we recognize conditions for the fixed investment cost, probability of disruption, and regular wholesale price, under which each incentive contract encourages the supplier to invest for the capacity restoration, and brings greater profit to each supply chain member.

The trade dispute between the US and China has reached a point where export restrictions on rare earths have become a possible means for sanction. This contribution provides a succinct analysis of the current dependency of the US on rare earths from China and draws parallels to the events during the rare earth crisis of 2010 and 2011, which was caused by geopolitical tensions between Japan and China. Respective risks associated with restrictions on the trade of rare earths are considered. Findings suggest that Europe could be affected as well and should be better prepared to mitigate supply disruptions in rare earth trade. Potential mitigation strategies and consequences of the current developments for Europe are also discussed.

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.

Volatile foods are a concern because this group is a significant contributor to inflation. Food production is very vulnerable to supply disruptions such as El Ni˜no weather and other weather disturbances. This study analyzes the influence of El Ni˜no on food Commodities and, inflation, in 25 provinces in Indonesia in 2008–2015 using the data panel method. The dependent variable in this study is inflation. While the independent variables are food commodities such as Prices of Chili, Onions, Rice, Soybeans, Corn, El Ni˜ no, and Inflation. El Ni˜no and the price of food commodities have a positive and significant effect on inflation.

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.

This paper focuses on coordinating contingent assistance between two lateral suppliers controlled by a central firm, when one supplier is exposed to supply disruption. By comparing two scenarios where the central firm can/cannot coordinate contingent assistance, we find the coordination of contingent assistance is more efficient, thus the central firm should do that. In the scenario without coordination, if the holding cost of the disrupted supplier is low, while the opportunity cost of the reliable supplier is high relatively, allowing the reliable supplier to hold decision power of assistance price can generate more assistance quantity for the disrupted supplier and bring more profits for the central firm. However, if the holding cost is high, and the opportunity cost is low relatively, the disrupted supplier can receive more assistance quantity, and the central firm can get more profits, by letting the disrupted supplier have the power to decide assistance price.

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.

The selection of a sourcing strategy plays a vital role in managing supply disruptions. The choice regarding the number of suppliers is one of the most important decisions in mitigating supply side risks. In this paper, we analyze single versus dual sourcing strategies of a buying organization in a multi-period setting where the low-cost supplier is exposed to disruption risks. We incorporate supplier ratings based on the performance of the suppliers in a dynamic setting and use them in the sourcing decisions. We develop a stochastic dynamic programming model to formulate the dual-sourcing problem. Our results show that dual sourcing provides maximum cost–benefit under high probability of supply disruption and high-cost differential between the reliable and the unreliable suppliers. The findings of this paper will help supply chain managers formulate optimal sourcing strategies when exposed to supply disruption risks by integrating performance metrics of the suppliers dynamically.

In recent years, there has been a very active debate about the stability of drug products especially after exceeding the expiry dates. The regulatory authorities require comprehensive stability data for market approval. The shelf-life obtained determines the expiry date, which is typically between 1 and 5 years and commonly set in a conservative manner. Conducting stability studies is a resource- and time-consuming matter for the pharmaceutical manufacturer. Short shelf-lives of drug products are also a challenge for managers of hospitals, nursing homes, and strategic national stockpile agencies which have to dispose of large quantities of outdated medicines every year. This conflict raises the question whether shelf-lives are often longer than the labeled one. In the past years, the FDA has launched several programs for shelf-life extension in order to defer replacement costs and to prevent drug shortages due to supply disruption. The aim of this review was to bring together the available literature of expired drug products as well as historical pharmaceutical relicts with an age of more than 80 years and to discuss the actual shelf-life with regard to the respective dosage form and the affiliation of the drug class. It seems to be reasonable for a large portion of drugs to extend the expiry dates far beyond five years.

Due to recent supply disruptions, there has been a rapid increase in panic buying. This study considers a wholesaler selling two brands of a product with multiple weights and produced by different manufacturers to multiple retailers. The products are substituted based on weight (same brand) and a competitor’s brand over two periods. In the first period (panic situation), the wholesaler attempts to retain the inventory to satisfy the retailer. In the second period (supply disruption), retailers are willing to accept the substitute products. The wholesaler segregates the retailers into high and low indexed customers, where the high indexed retailers (provide higher profit) order greater quantities than the low indexed retailers. The objective of this model is to determine the optimal numbers for ordering quantities and substitutions to maximize total profit. Moreover, supply disruption for both single and multiple brands is analyzed, along with the influence of different degrees of supply disruption and panic rate on decisions and profits. Finally, we compare the models with and without customer-segmented substitution and brand substitution. In addition, other model extensions are discussed, such as an increase in the price in the second period.

The continuous flow synthesis of a model phenothiazine antipsychotic is presented herein, using 3-chloropropionyl chloride as a central building block. The basic phenothiazine-derived scaffold is (atom)-efficiently and mildly synthesized with the aim to present continuous flow technology as a contributor to fast and efficient syntheses of challenging APIs, that are nowadays experiencing supply disruptions and global shortages.

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.

Supply chain disruptions resulted from various disasters may cause awesome loss; therefore, corresponding operational policies should be designed to mitigate the negative effect. In industrial goods supply chain, customers are segmented and have different contributions and significances to manufacturers, which have to be considered when adopting mitigation policies. From the customer heterogeneity perspective, the models of a three-stage supply chain with a single supplier and two suppliers are established, and sensitivity analysis is carried out to investigate scenario parameters' impact on optimal mitigation policies. The numerical experiments find that safety stocks are suitable for low disruption probability situation. Meanwhile, strategic reserves with lower holding cost are attractive and efficient to handle a fairly highly disruptive situation or high key customer loss. The results also indicate backup supplier should be adopted if there is a low disruption probability or the backup supplier's price is not significantly higher. This paper extends the supply disruption research and leads some managerial implications and insights that might be useful for disruption mitigation in industrial goods supply chain.

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.

We briefly review the literature on the effect of the COVID-19 pandemic on supply chain decisions. We first review virus diffusion models to be able to understand COVID-19 virus behavior. Then, we review the related literature on modeling supply disruptions, emphasizing those related to pandemics such as COVID-19. We pay special attention to reviewing inventory management models, especially those based on the economic order quantity models, as they seem to offer a good starting point. Finally, we present ideas for future research.

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.

Summary Material resources each face different levels of risks in terms of supply disruption, vulnerability, and environmental and social impacts. Countries and companies apply criticality assessments to select or prioritize material resources requiring attention and measures to mitigate their associated supply risks. This Primer gives an overview of typical use cases and frequently used indicators in the criticality dimensions supply risk, vulnerability, and social and environmental aspects. We illustrate the basics of criticality assessments by the examples of copper and indium. We also provide practical guidance in conducting a criticality assessment. It is good practice to follow four steps to enable a coherent evaluation: defining the goal and scope, selecting and evaluating indicators, selecting an aggregation approach, and interpreting and communicating the results.

Recent developments and collaborations of pharmaceutical manufacturers, hospitals, and government funded research bodies using 3D printing technology have been highlighted for the management of the healthcare crisis 3D printing is a process of converting virtual 3D models developed by computer aided design into physical forms upon addition of material layer-by-layer (also known as additive manufacturing) This 3D printing is supposed to revolutionize significantly the healthcare system in the coming years This process involves a tailored deposition of biomaterials layer by layer such as polylactic acid (PLA), polyvinyl alcohol (PVA), or other suitable pharma-grade polymers, copolymers, and their combinations to formulate three-dimensional custom designs with controlled architecture and composition Food and Drug Administration (FDA) is currently thinking on regulation to ease the import restrictions for products intended for the detection and diagnosis of COVID-19 to ensure the timely availability of test kits

In many industries, future demand is driven by past sales, and the inability to sell today can decrease future market size. While the dependence of demand on sales has been addressed in several streams of Operations literature, such a setting has not been studied in the disruptions literature. Yet, we find that when supply disruption can decrease future demand, risk mitigation strategies become quite different from those presented in the existing disruptions literature, where demand is largely independent of sales. For example, there may exist distinct values of probability of disruption at which the order quantity from an unreliable supplier increases in probability of disruption, when the OEM either single or even dual sources from the unreliable and reliable suppliers. We consider a multi-period setting with demand in each period a multiple of sales in the previous period. The OEM can obtain supply from a reliable (not subject to disruption) and unreliable supplier (subject to disruption). We characterize optimal policies analytically and visualize them with numerical simulations. Our study is particularly relevant nowadays as many industries where future demand is driven by sales (i.e. consumer electronics) frequently experience supply disruptions.

This paper quantifies the finance uncertainty multiplier (i.e., the magnifying effect of the real impact of uncertainty shocks due to financial frictions) by relying on two historical events related to the US economy, i.e., the large jump in financial uncertainty occurred in October 1987 (which was not accompanied by a deterioration of the credit supply conditions), and the comparable jump in financial uncertainty in September 2008 (which went hand-in-hand with an increase in financial stress). Working with a VAR framework and a set-identification strategy which focuses on - but it is not limited to - restrictions related to these two dates, we estimate the finance uncertainty multiplier to be equal to 2, i.e., credit supply disruptions are found to double the negative output response to an uncertainty shock. We then employ our model to estimate the overall economic cost of the COVID-19-induced uncertainty shock under different scenarios. Our results point to the possibility of a cumulative yearly loss of industrial production as large as 31% if credit supply gets disrupted. Liquidity interventions that keep credit conditions as healthy as they were before the COVID-19 uncertainty shock are found to substantially reduce such loss.

Considering the supply interruption in supply chain network, a closed-loop supply chain network model with dual objectives including total profit and total carbon emissions based on recycling mechanism was proposed. In this paper, we considered not only the elasticity of supply chain network but also the recycling prices. The model investigated the impact of the recycling mechanism on the supply interruption. The numerical results revealed the relationship between the degree of supply disruption and the recovery price, as well as the influence of the loss of suppliers’ supply capacity and the tolerance coefficient of shortage on the planning results.

Due to its impact on nominal firm profits, price rigidity amplifies the response of entry and exit to adverse supply shocks, such as COVID-19. This “entry-exit multiplier” triggers substantial magnification of the welfare losses due to negative supply shocks—even in an efficient-entry benchmark. In addition to those second-order effects, price rigidity also induces first-order amplification under external returns, when entry is no longer efficient. Endogenous entry-exit thus radically changes the consequences of nominal rigidities: in addition to the aggregate-demand amplification of supply disruptions, it also reconciles the response of hours worked across the benchmark New Keynesian and RBC models.