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Capacity management and supply chain disruptions are the most challenging problems faced in high tech industries. This paper focuses on establishing a capacity reservation contract between a single supplier and two heterogeneous retailers in a two-stage supply chain, wherein the retailers purchase a product from the supplier and sell it to the customers. In this study, a mathematical model is built for all parties involved, incorporating numerous essential elements of a real contract. The proposed model aims to assist in determining the best solutions for the retailers’ reserved capacities to the supplier and the supplier’s constructed capacity. Analytical results and sensitivity analyses are presented to demonstrate how various cost elements, price, and uncertainty affect the optimal capacity decisions. [ABSTRACT FROM AUTHOR]

To deal with disruption at the supply side, the use of backup suppliers is among the commonly employed strategies. In this research, we derived a dual sourcing model using capacity reservation contracts for a supply chain consisting of a retailer, a primary supplier who may experience disruption, and a reliable backup supplier. This dual sourcing model is a reactive strategy that balances flexibility and redundancy to improve supply chain resilience. The aim of the proposed model is to help find optimal solutions for the reserved capacities of the retailer to the suppliers and the constructed capacities of the suppliers. It has been derived in this research that the above-mentioned reserved/constructed capacities exist uniquely. Sensitivity analyses were also conducted to examine the impact of contract parameters on decision variables. This research contributes to existing knowledge by providing deeper insights into the application of the capacity reservation contract to handle supply disruption. [ABSTRACT FROM AUTHOR]

We study the inventory review policy for a healthcare facility to minimize the impact of inevitable drug shortages. Usually, healthcare facilities do not rely on a single source of supply, and alternative mechanisms are present. When the primary supplier is not available, items are produced in-house or supplied through another supplier, albeit with additional cost. Our aim in this study is to determine how optimal inventory parameters are adjusted depending on the availability of the primary supplier. We show that an approximation provides trivial results, yet fails to capture the nuances therein. Our proposed Markov chain model overcomes these issues, and numerical results illustrate the significant economic impact of inventory parameter optimization. Furthermore, we simulate uncertainty scenarios and provide sensitivity analyses concerning fixed ordering cost for the secondary supplier, shortage frequency, shortage duration, and demand rates. [ABSTRACT FROM AUTHOR]

The driver shortage is a perennial problem in the trucking industry. The review of literature reveals currently there is a lack of holistic approach to address driver shortage problem. This paper presents a systems approach to understand the factors influencing the issue of truck driver shortages in an emerging economy context and their evolution over time. For this study, we define truck driver shortage as: "The shortfall in the market when the quantity of truck drivers supplied is below the number of truck drivers demanded". A system dynamic model has been developed to study a representative truck segment unit. The model is validated and simulated for ten years. The findings from the proposed model indicate that the current system and other environmental factors do not support the truck driver supply increase, drivers and shortages are likely to become acute in the coming years. The study proposes appropriate intervention for the government, and other stakeholders must design proper steps to fill the gap beyond a specific timeframe. The study contributes to the existing literature as a pioneering work on driver shortages in the emerging economy context. Also, the study is one of its kind in using a holistic, quantitative approach to modeling the driver shortage phenomenon. In the process, the study elicits complex relationships that prevail among the factors included in the study. • A system approach to understanding key issues for truck driver shortages. • The current systems and other environmental factors are not associated with the driver supply increase. • A pilot study examining driver shortages in the emerging economy context. [ABSTRACT FROM AUTHOR]

Supply chain disruptions can be costly and disruptive, and reducing supplier uncertainty through investments can be an effective strategy for mitigating these risks. In this study, we explore ordering and investment strategies in a downstream competitive environment, considering supply uncertainty. We consider two buyers ordering from a single supplier and competing in a Cournot market. Buyers must balance investment benefits against costs when making investment decisions. We find that without downstream competition, a relatively low investment proportion can yield a "win-win" outcome. Under downstream competition, an increased number of investors does not necessarily lead to higher supplier reliability. When both buyers invest at a high ratio, the significant decline in order quantities may results in lower supplier reliability. When there is only one investing buyer in the market, even though the competitor may benefit from spillover reliability enhancement — free-riding, the buyer may also be willing to provide an investment subsidy to improve the supplier's reliability. When both buyers invest at a moderate ratio, downstream competition may benefit all supply chain members. Moreover, increasing wholesale price differentiation and endogenous investment ratios can effectively reduce free-riding behavior of the non-investing buyer. These findings have practical implications for supply chain managers aiming to reduce supply risks and allocate investment resources efficiently. • Buyers invest in suppliers to improve reliability under downstream competition. • Without competition, lower investment proportion leads to a win-win outcome. • Buyers may invest in suppliers despite the potential for competitor free-riding. • All supply chain members may benefit from the investment with downstream competition. • Differential wholesale prices and endogenous investment ratios reduce free-riding. [ABSTRACT FROM AUTHOR]

Due to the prevalence of supply disruptions disturbing supply chain and logistics operations, a firm should tackle such disruptions using appropriate approaches. In this research work, a dual-sourcing approach is applied by a firm. The main decision regarding the firm sourcing from two unreliable suppliers is to derive an optimal ordering policy that maximizes the firm’s expected profit. Considering the stochastic ordering yield bridges a gap in the literature. The firm’s expected profit function is analytically formulated, and the viability of the developed mathematical expression is illustrated using numerical experiments and sensitivity analyses. Through the sensitivity analyses, the importance of considering the stochastic ordering yield is confirmed, as the optimal ordering policy varies on the variance of the ordering yield. Furthermore, failing to consider the stochastic ordering yield leads to incorrect conclusions regarding the optimal ordering policy; in addition, the increase in the variance of the ordering yield prevents the firm from benefiting from incremental profit. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this study, we investigate the replenishment decisions for firms that rely on multiple sources of supplies, including regular forward contracts, option contracts, and the spot market. Our research aims to tackle the challenges arising due to supplier disruptions and the volatility of spot market prices that are correlated with these disruptions. We develop and solve multi-stage stochastic programming models that incorporate demand and supplier disruption information updates, while considering both risk-neutral and risk averse (CVaR) objectives. These models assist organizations with varying risk attitudes in achieving maximum performance by optimally selecting a procurement portfolio based on the availability and quality of updated information. Through analytical solutions and extensive numerical studies, our findings offer novel insights to organizations and policymakers, empowering them to enhance their supply chain resilience during critical supply disruption situations. Therefore, this research has broader implications and aligns with the multiple sustainability objectives outlined in the Sustainable Development Goals (SDGs). [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this paper, we consider a make-to-stock producti-on-inventory system where a manufacturer's production may be entirely interrupted due to a supply disruption. Customers react dynamically to the subsequent inventory shortage, depending on factors including market condition, customer characteristic, and behavioral interaction. The manufacturer can adopt contingent sourcing to manage the disruption. Consequently, the postdisruption demand and inventory exhibit complicated dynamics in terms of customer behavior, demand recovery, and the adoption of contingent sources. We first model and forecast the postdisruption customer behavior. Customers are classified into two types based on brand loyalty and the interaction is captured as “demand learning” within each type. Using differential models, we analytically characterize customers’ postdisruption behavior in five possible scenarios, depending on customers’ constitution, transient reaction, brand loyalty, and competition intensity. Next, we propose dynamic contingent sourcing strategies to mitigate the supply disruption, and the optimal sourcing time is derived. Finally, by conducting numerical analysis, we obtain further managerial insights on how to adapt dynamic contingent sourcing strategies according to various contributing factors. [ABSTRACT FROM AUTHOR]

In the presence of stochastic supply disruption, the optimal variables of an inventory policy must be determined appropriately. Considering a two-echelon system comprised of a supplier and a retailer, the objective of this research is to help the retailer derives the optimal base stock level that achieves the minimum costs per unit of time regarding the stochastic unavailability of the supplier. The expression of the optimal base stock level is determined in closed-form in consideration of a continuous random variable of a disruption length together with a partial backorder of shortage inventory. A solution method which facilitates the retailer to derive the correct expression for the optimal base stock level is proposed. The applicability of the proposed solution method is illustrated through numerical experiments. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This study presents manufacturing and distribution network models for strategic supply chain planning. Where prices of intermediate products in the supply chain are not readily available, we study the influence on the formation of the supply chain of using either direct product costing or full absorption costing for setting internal prices. We develop a generalized Benders decomposition-based approach to solve the models. Problems representing a variety of scenarios that simulates different economic environments are solved. Our computational results show that the product costing method could influence the concentration of production activities at potential manufacturing locations, production and shipment quantities, product prices, and allocation of profits in the supply chain. [ABSTRACT FROM AUTHOR]

We consider a limited-liability firm that owns a finite single-product inventory subject to periodic-review replenishment and a corporate treasury that mediates the firm’s financial transactions related to inventory operations. The firm may elect to borrow money to purchase product via a revolving line of credit, secured by a compensating balance which determines the credit limit. The line of credit is subject to rollover risk, namely, each period the funding entity may, with some probability, refuse to roll over the line of credit. In response, the firm can search for an alternate funding entity, but in so doing it may incur search costs, primarily in the form of lost sales. The firm optimizes inventory replenishment order sizes and decides whether it should declare bankruptcy, as function of its inventory and available capital. The recent credit crunch has rendered illiquidity a critical concern for funding and operating decisions in enterprises. This paper addresses optimal inventory management in the face of liquidity shocks and supply disruptions. We show that rollover risk and supply disruption are important considerations for firms that rely on external funding. Rollover risk alone results in optimal inventory replenishment policies that differ materially from those specified by traditional supply chain models; differences manifest as state-dependent precautionary replenishment or cash hoarding. Inventory management models which fail to take rollover risk and supply disruption risk into account can prescribe suboptimal replenishment policies. Such policies would generate suboptimal profits for firms that rely on short-term financing to fund their working capital. [ABSTRACT FROM AUTHOR]

Managing highly evolved supply chains and maintaining environmental sustainability at the same time is not easy, especially when it is vulnerable to various disruption risks. In the event of a disruption, the sustainability of a supply chain will be compromised as a consequence of attempting to quickly recover from the disruption with minimal costs. However, a balance can be achieved between sustainability and recovery. Companies can maintain its sustainability, while recovering its operations with a comprehensive analysis of the decision criteria for the intended system. This study presents a recovery model of a two-stage serial supply chain subject to supply disruption with consideration of safety stock and carbon emission. The system consists of a single manufacturer and a single retailer, while the carbon emission consideration is from the transportation activities during the recovery cycle. The model is capable of determining the new recovery schedule of the manufacturer and the retailer, the optimal safety stock level, and the carbon emission cost impact during recovery. The results show that for a range of short disruption periods, the optimal safety stock level is significantly affected by the holding cost values. Furthermore, the cost of carbon emission is dependent on the number of recovery cycles, the distance between supply chain entities, and the social cost of carbon at the time of the disruption. A comparison of two disruption scenarios with different transportation arrangement illustrates a solution for a better recovery plan with faster recovery cycles, lower total recovery cost, and without any change to carbon emission cost impact. This study contributes to the supply disruption literature with the findings on how safety stock and environmental effect consideration affect the disruption recovery decision-making process in term of lot sizing and transportation arrangement. [ABSTRACT FROM AUTHOR]

This paper builds a dynamic supply chain network, where firms can select suppliers according to the trust, the selling price or just randomly. Simulation results show that the trust-based rule can significantly increase the aggregated working capital and decrease firm's likelihoods of bankruptcy. Moreover, firms' sizes under trust-based and price-based rules follow power-law distributions. The degree distribution of supply chain network under price-based rule follows a power-law distribution, while those under trust-based and randomly-choosing rules are similar to that of random network. Furthermore, results also indicate that trust-based rule is the most robust one against random and targeted disruptions. [ABSTRACT FROM AUTHOR]

In this paper, we study the multi-attribute multi-unit procurement mechanism design problem facing a set of potential suppliers who suffer from disruption risks. Each supplier's production cost depends on its disruption probability, and both are private information. We propose a Vickery-Clark-Groves auction with disruption risk (VCG-DR) for this problem and show that the mechanism is incentive-compatible, individual-rational and social efficient. Moreover, we compare the performance of the proposed mechanism and the popular single-attribute multi-unit forward auction (SA-MFV) with reserved attribute by numerical experiments. The results show that VCG-DR outperforms SA-MFV in both social efficiency and optimality. [ABSTRACT FROM AUTHOR]

Home-based records (HBRs) provide an effective, inexpensive mechanism for recording and tracking infant vaccinations, yet stock-outs prevent HBRs from fulfilling their intended function. We describe the annual occurrence of HBR stock-outs during 2014–2016 reported by national immunization programmes to the WHO and UNICEF on the Joint Reporting Form on Immunization. During 2014–16, 48 countries reported at least one HBR stock-out. Thirteen countries reported HBR stock-outs for two of the three years. Forty-four countries reported two or more HBR funding sources in 2016. Challenges persist in ensuring continuous availability of HBRs. HBR stock-outs have important implications as they may impact continuity-of-care, increase inefficiencies at the point-of-care and reduce the ability of caregivers to be effective health advocates. Identifying mechanisms for preventing stock-outs should be a focus of attention for programmes and development partners. Expanded efforts are required to better understand the underlying causes of HBR stock-outs and identify solutions. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of service constraints on the retailer's optimal ordering strategy under supply disruptions. Considering a single-period supply chain that consists of one supplier and one retailer, we first establish a nonbinding profit function model and prove the existence of an optimal order quantity at which the retailer's expected profit can achieve the optimal value. We then formulate the profit model with service constraints, i.e. fill rate and service level constraints, respectively. Through the analysis, we find that the expected value of the retailer's profit is a convex function of the order quantity and there exists a unique order quantity that makes the retailer's expected profit maximum under each service constraint. In numerical analysis we explain how the retailer can achieve the desired profit by changing the order quantity. [ABSTRACT FROM AUTHOR]

With today's growing number of geographically dispersed facilities amplifying the likelihood of supply disruptions, contingency planning has become an important strategic issue for manufacturers and distributors. This paper studies how the addition of reserve capacity in the supply chain-one of the most common strategies in contingency plans against supply disruption-can alleviate the effects of supply disruption on product and income streams and total supply chain profit. We also perform a preliminary study to find the potential implications of utilizing excess production capacity for alternative uses particularly when a firm tries selling some of its intermediate products to an external buyer who in turn could process them into finished products and compete with the firm in the same markets. We formulate a network design optimization model for supply chain contingency planning and present a decomposition procedure which exploits the natural separation between the logistics and pricing decisions in the model. Computational results are presented. [ABSTRACT FROM AUTHOR]

• Supply disruption and international trade risks of an offshoring-based global production network is studied. • System dynamics simulation is applied to simulate the disruption and trade risks. • Dynamic and static penalty mechanisms are proposed to mitigate disruption risk. • Cost-sharing mechanism for mitigating the trade risks is proposed. Owing to the uncertainties of international trade and economic environment, the supply chain risks of global production networks have substantially increased in recent years. In this study, we investigate the supply disruption and international trade risks of an offshoring-based global production network using system dynamics simulation and game theory. The production network is formed by two contract manufacturers (CMs) and one original equipment manufacturer (OEM) located in different countries. First, a system dynamics simulation model considering supply disruption risk is established to evaluate the impacts of different supply disruption modes on the profit of OEM. To counteract the supply disruption risk, dynamic and static penalty mechanisms are proposed. By applying game analysis, we theoretically and numerically demonstrate why and how the dynamic penalty mechanism is superior to the static penalty mechanism. Second, we apply system dynamics and game theory to analyze the international trade risks (tariffs and exchange rates) for the offshoring-based global production network, and a cost-sharing mechanism for mitigating the trade risks is proposed. Finally, based on the study, we summarize some important managerial implications that may be helpful for practitioners. [ABSTRACT FROM AUTHOR]

We consider a firm that procures a product from a regular supplier whose production is subject to both supply disruption and random yield risks and a backup supplier whose production capacity requires reservation in advance. Under both deterministic and stochastic demand, we study the impact of the two types of supply risks on the firm's optimal procurement decisions and the importance of correctly identifying the source of supply risks. We find that if the overall supply risk is unchanged but its main source shifts from random yield to supply disruption, the firm should order more from the regular supplier and reserve less capacity from the backup supplier. Ignoring the existence of supply disruption leads to under-utilization of the regular supplier and over-utilization of the backup supplier. Moreover, we examine the option value of the reserved capacity that is affected by the uncertainty of customer demand. We find that the option value increases/decreases in demand uncertainty if the reservation capacity is exercised after/before demand is realized. [ABSTRACT FROM AUTHOR]

Considering logistics service integrator (LSI) and functional logistics service provider (FLSP) with risk aversion， the logistics service quality control was studied under supply disruption. The quality-utility models and equilibrium solutions of LSI and FLSP with risk aversion were obtained under supply disruption and the Stackelberg game， respectively. Finally， a numerical simulation was conducted by the Matlab R2013a. The correlations among LSI's effort level of quality supervision， proportion of order allocation and main FLSP's quality defect warranties were analyzed. The impact of parameters on utilities of LSI， main FLSP and second FLSP were also discussed. [ABSTRACT FROM AUTHOR]

The paper considers a closed-loop supply chain inventory system involving a single-manufacturer and a single-retailer with stochastic market demand and random return of used item. The manufacturer produces the finished product by manufacturing from raw materials as well as remanufacturing from used product obtained from a collector. Used product's yield rate is assumed to be random. The raw materials may be sourced from two suppliers. The primary supplier is cheaper but unreliable in the sense that supply from this source may disrupt, whereas the secondary supplier is perfectly reliable but more expensive. The objective of this study is to determine the optimal quantity of finished product which is to be manufactured from raw materials so as to maximize the total profit of the integrated system. Results of numerical experiments are presented and sensitivity analysis is carried out to investigate the influence of model-parameters on the optimal solution. [ABSTRACT FROM AUTHOR]

The paper proposes a survey on three issues related to Strategic Petroleum Reserves (SPR) policy. Firstly, what are the optimal SPR acquisition, drawdown and refilling policy in response to various market risks? Secondly, how SPR policy or actions will affect the market factors, i.e. oil demand or price. Thirdly, in what extend a disruption may induce price shock. For the purpose, the study proposed a Markov Decision Process model (SPR-MDP). In the model, oil supply, disruption size and duration are considered to be highly stochastic. Oil price is determined by market fundamentals exclusively. According to the empirical study, we come to some interesting conclusions. Firstly, oil price and disruption risk show different ways in influencing the desirable SPR size. It is found that the SPR size increases with the decrease of oil price while increase of disruption risk. Secondly, SPR acquisition may increase oil price slightly by influencing the basic fundamentals. In given case, we find acquisition of 7 million barrels per month increase the price by 2.6%. But the influence weakens with decrease of acquisition size. Thirdly, disruption duration shows significant impact on SPR drawdown policy. In a two-month disruption case, it is found that 51% of SPR should be released in the first month. Another 40% is released in the following month. The other 9% SPR is left for forthcoming disruptions. Meanwhile, SPR drawdown shows high efficient in damping oil price in the disruption. In given case, after drawdown of SPR, the oil prices only increases by 0.7% in the second month though continue disruption. [ABSTRACT FROM AUTHOR]

Distortion in distribution and consumption of agricultural commodities is a result of disruptive shocks in prices and food value chains leading to a significant food loss as well as waste. We investigated the COVID-19 induced lockdown effects in India through an interrupted time series analysis coupled with a survey result of 729 consumers, 225 farmers and synthesis of the literature evidence on food loss as well as food waste. Our article complements the literature inventory on COVID-19 by estimating and tracking the effects on prices and consumer behaviour apart from discussing the implications for food loss and waste. Prices post-lockdown shot up immediately and significantly for chickpea (4.8%), mung bean (5.2%), and tomato (78.2%) corroborating the loss in highly perishable product – tomato – owing to its spiked price. We find no structural break in prices due to lockdown implying that lockdown-induced price change was not sufficient to alter the long-run price movement, and the prices of the major commodities reverted to the pre-lockdown levels. The pandemic induced lockdown did restrict the access to food markets and a majority of consumers (75.31%) experienced a price increase across COVID zones of different intensity of incidence leading to food loss along supply chain and wastage at consumers end. Consumers' livelihood affected from moderate (59.53%) to severe (3.3%) with 92 per cent reporting a change in shopping behavior. The Kruskal-Wallis test on consumption behavior change indicated a significant shift among the consumers reporting altered income, mostly in the downside, post-lockdown. Despite the relaxation for agricultural related activities during the lockdown, farmers reported disruption in disposing their winter produce barring wheat, bolstered by a record state procurement in 2020. The paper affirms that the pandemic has caused a significant price change and unprecedented panic purchase that led to the food wastage but subsided soon exhibiting the resilience in Indian agriculture. We strongly recommend for promoting the capacity and collective resilience of small-scale production systems through institutions, policies and reforms. Contract farming, farmer producer organizations, creation and functioning of social safety nets to overcome income, production and price shocks, access to digital national markets and capacity building on food waste management practices will insulate vulnerable section as well as reduce the loss of food across supply chain. [Display omitted] • Radical change in prices and consumption behaviour during COVID-19 induced lockdown. • Prices increased significantly for chickpea (4.8%), mung bean (5.2%) and tomato (78.2%). • Price rise felt by 75.31% consumers due to supply disruption has implications for food loss and waste. • As livelihood affected from moderate (59.53%) to severe (3.3%), 92% changed shopping behaviour. • Reforms with food loss and waste management practices will insulate vulnerable section. [ABSTRACT FROM AUTHOR]

Distortion in distribution and consumption of agricultural commodities is a result of disruptive shocks in prices and food value chains leading to a significant food loss as well as waste. We investigated the COVID-19 induced lockdown effects in India through an interrupted time series analysis coupled with a survey result of 729 consumers, 225 farmers and synthesis of the literature evidence on food loss as well as food waste. Our article complements the literature inventory on COVID-19 by estimating and tracking the effects on prices and consumer behaviour apart from discussing the implications for food loss and waste. Prices post-lockdown shot up immediately and significantly for chickpea (4.8%), mung bean (5.2%), and tomato (78.2%) corroborating the loss in highly perishable product – tomato – owing to its spiked price. We find no structural break in prices due to lockdown implying that lockdown-induced price change was not sufficient to alter the long-run price movement, and the prices of the major commodities reverted to the pre-lockdown levels. The pandemic induced lockdown did restrict the access to food markets and a majority of consumers (75.31%) experienced a price increase across COVID zones of different intensity of incidence leading to food loss along supply chain and wastage at consumers end. Consumers' livelihood affected from moderate (59.53%) to severe (3.3%) with 92 per cent reporting a change in shopping behavior. The Kruskal-Wallis test on consumption behavior change indicated a significant shift among the consumers reporting altered income, mostly in the downside, post-lockdown. Despite the relaxation for agricultural related activities during the lockdown, farmers reported disruption in disposing their winter produce barring wheat, bolstered by a record state procurement in 2020. The paper affirms that the pandemic has caused a significant price change and unprecedented panic purchase that led to the food wastage but subsided soon exhibiting the resilience in Indian agriculture. We strongly recommend for promoting the capacity and collective resilience of small-scale production systems through institutions, policies and reforms. Contract farming, farmer producer organizations, creation and functioning of social safety nets to overcome income, production and price shocks, access to digital national markets and capacity building on food waste management practices will insulate vulnerable section as well as reduce the loss of food across supply chain. [Display omitted] • Radical change in prices and consumption behaviour during COVID-19 induced lockdown. • Prices increased significantly for chickpea (4.8%), mung bean (5.2%) and tomato (78.2%). • Price rise felt by 75.31% consumers due to supply disruption has implications for food loss and waste. • As livelihood affected from moderate (59.53%) to severe (3.3%), 92% changed shopping behaviour. • Reforms with food loss and waste management practices will insulate vulnerable section. [ABSTRACT FROM AUTHOR]

The world is experiencing frequent extreme weather events like droughts, snowstorms, and shifting of seasons due to climate change. Increased frequency and severity of these extreme weather events threaten food security because agriculture depends on climate conditions. Impacts of climate change on the agricultural system not only occur at the grower's level, but also cascade to other levels along the supply chain. This study aims to quantify a wide range of economic impacts of different extreme climate events on different stages of a food supply chain. We chose the potato supply chain in Idaho as a case study. We developed a multi-echelon supply chain simulation model using an agent-based modeling (ABM) approach with five types of agents—farmers, shippers, processors, retailers, and logistics companies. In addition to the business-as-usual (BAU) scenario, we designed two climate-related disruption events—drought and snowstorm. We quantified the heterogeneous impacts at different stages of the supply chain for both fresh and processed potatoes using key performance indicators (KPIs) including revenues, prices, lead times, traded quantities, and food waste quantity. The impacts of the disruption events are different on different agents in the supply chain for different product categories. The price hike of fresh potatoes is far higher than processed potatoes during disruption events. This price hike makes consumers switch to processed potatoes, which require more fresh potatoes as an input that further reinforces the price hike. However, because processed potatoes have an elastic demand, once their prices go up due to higher input cost, their demand drops. Non-contracted farmers gain additional revenues from the disruption events, whereas contracted farmers incur a loss due to lock-in price and lower than usual harvest. The methodology developed in this study could be applied to other food and agricultural supply chains for understanding the vulnerabilities at agent levels due to climate change disruption events. The findings would help develop mitigation strategies or policies to improve the well-being of the overall supply chain. [Display omitted] • Simulated physical aspects, logistics, and market dynamics of a potato supply chain using agent-based modeling approach. • Quantified the heterogeneous impacts of climate change-related disruption events at agent and system levels. • Price hike of fresh potatoes was higher than processed potatoes during disruption events. • Contracted farmers lost more revenues than non-contracted farmers during disruption events. • Bad weather event impacted order delivery lead times, but there was no impact from drought. [ABSTRACT FROM AUTHOR]

Highlights: [•] We present a method to analyse material criticality of infrastructure transitions. [•] Criticality is defined as the potential for, and exposure to, supply disruption. [•] Our method is dynamic reducing the probability of lock-in to at-risk technologies. [•] We show that supply disruption potential is reducing but exposure is increasing. [ABSTRACT FROM AUTHOR]

Emergency is an important factor resulting in supply disruption risk. How to deal with emergency in supply chain arouses managers' and researchers' attention in recent years. In order to improve the effect of supply disruption risk management under this situation, this paper builds the supply disruption Emergency Management Model of supply chain from the angle of risk management and discusses whether the decision-making mechanism of the case-based reasoning can bring the better effect for supply disruption by using computational experiment. The results mainly show that the mechanism of risk assessment, risk identification, risk control and risk evaluation based on the case-based reasoning can effectively deal with supply disruption risk, and bring more profit and better service level for the members of supply chain. [ABSTRACT FROM AUTHOR]

This paper addresses the comparison and selection decision of reactive strategies for supply disruption management. We consider an assemble-to-order supply chain with one manufacturer who employs a single-sourcing strategy for each kind of component. The manufacturer assembles products for customers using components purchased from the suppliers in a just-in-time environment. Demand for the products is time-sensitive. We propose and compare three pure reactive strategies and two dynamic reactive policies for managing supply disruption. In the pure reactive strategies, only one kind of strategy is adopted during the disruption. But strategies adopted in the dynamic pure reactive policies change with the passage of time during the disruption. In the dynamic mixed strategy with customer choices, the manufacturer can use both backup source to offer on-time delivery and compensation policy to compensate customers for waiting in each period during the disruption. We find that the backup sourcing strategy is preferred at the beginning of the supply disruption, while the compensation strategy is preferred as time elapses. The dynamic pure strategy is superior to any other pure reactive strategies. The dynamic mixed strategy with customer choices is superior to the pure backup sourcing strategy. The backup cost and customer sensitivity are two determining factors in the manufacturer's choice of the reactive strategies. [ABSTRACT FROM PUBLISHER]

Abstract: Supply chain disruptions are unintended, unwanted situations resulting in a negative supply chain performance. We study the supply chain network design under supply and demand uncertainty with embedded supply chain disruption mitigation strategies, postponement with downward substitution, centralized stocking and supplier sourcing base. We designed an integrated supply-side, manufacturing and demand-side operations network in such that the total expected operating cost is minimized. We modeled it in a deterministic equivalent formulation. An L-shaped decomposition with an additional decomposition step in the master problem is proposed. The computational results showed that parallel sourcing has a cost advantage against single sourcing under supply disruptions. In addition, the build-to-order (BTO) manufacturing mitigation process has its greatest impact with high variations on demands and is integrated with the component downward substitution. Lastly, the manufacturer needs to order differentiated components to cover its requirement for maximal product demand to prevent the loss of sale, even with fewer modules in stock. [Copyright &y& Elsevier]

Abstract: This paper studies a buy-back contract between a buyer and a backup supplier when the buyer’s main supplier experiences disruptions. The expected profit functions and the optimal decisions of the contract players are derived through a sequential optimization process. The common properties of the contract as well as the differences under the demand uncertainty and the main supplier’s recurrent supply uncertainty are explored through comparative studies and numerical examples. The study contributes to the literature by providing a better understanding of the impacts of demand and supply uncertainties and by shedding insights on the value of a backup supply. [Copyright &y& Elsevier]

Abstract: In this paper, we study a single-product inventory system which involves a supplier, a retailer, and differentiated customers. The supplier provides products to the retailer which in turn sells products to its customers. The supplier is unreliable and is subject to random disruptions. The retailer adopts a periodic-review inventory policy, under which the retailer reviews its inventory position every a fixed period of time and decides whether a replenishment is needed or not. Partial backordering is applied when a stockout occurs. That is, under the situations of stockouts, customers can choose either to backorder products or to abandon the purchase. Customers are segmented into two classes according to their backordering probabilities. The customer class with high backordering probability is provided with high priority to receive backorders. In this paper we allow more than one outstanding orders to exist, which is not the case in the previous literature. We develop a simulation model for such an inventory system and investigate the impacts of supply disruptions and customer differentiation on this inventory system. [Copyright &y& Elsevier]

International commerce and travel have been restricted in order to limit the spread of COVID-19. The illegal trafficking in drugs, which is often concealed in other commercial activity, will be affected by these disruptions. This is particularly true for precursor chemicals, controlled substances of synthetic origin, and new psychoactive substances coming from Asia. China hosts large and under-regulated pharmaceutical and chemical sectors that provide many of the active ingredients used both in legitimate medicines and illicit fentanyl and methamphetamine. Unregulated producers and vendors in China have been supplying drug trafficking organizations in Mexico or using the internet and postal service to directly sell fentanyl to buyers in North America. The magnitude of supply shortages and interrupted trade of chemicals and synthetic drugs coming from China will depend on the breadth and depth of COVID-19's disruptions. In turn, this could impact vulnerable drug-using populations. Drawing on historical accounts of prior supply disruptions, this commentary offers some initial speculation as to the possible effects of COVID-19 on the supply of synthetic drugs like fentanyl and precursor chemicals supplied to North America from China, which may have important lessons for other parts of the globe. Prior supply disruptions coincided with elevated prices and reduced purities of street drugs as well as increases in the number of users entering treatment. However, it is challenging to predict how developments will unfold given the unprecedented nature of this pandemic. A short-term breakdown in supply chains, interrupted trade, or social distancing mandates may not have much of an effect on the availability of synthetic drugs. Yet, disruptions in trade for months or years could shape how drugs are supplied or used. Drug policy will need to evaluate market indicators as soon as they are available but responding now with expanded medication therapies, like methadone, may help save lives. The drug policy landscape could look different in a post-COVID world. [ABSTRACT FROM AUTHOR]

Background: Many nations place drugs into various "schedules" according to their risk of abuse and/or recognized medical value that vary in terms of their restrictions. To mitigate diversion or abuse, drugs sometimes get rescheduled or are scheduled for the first time. Until now, there have not been efforts to integrate lessons from across the range of such past events.Methods and Data: We searched for peer-reviewed evaluations of instances of (re-)scheduling drugs in the United States after 1969 and a comparably large set of instances from other countries. Those 109 articles were supplemented by 30 others found in other ways but not meeting those search criteria (e.g., because the information on rescheduling was a minor part of a more general article).Findings: Findings are reported for many outcomes and with diverse measures over different timelines, making standardization of outcomes difficult. For more than half of the events for which quantitative outcomes were reported, there were declines in use-related measures by at least 40 percent. It is common for there to be reports of increases in indicators pertaining to other substances, sometimes more dangerous but sometimes less dangerous; overall, substitution appears to occur, but be partial.Conclusion: Scheduling and up-scheduling can - though does not always - have substantial effects on a range of outcomes. Substitution to other substances is a possibility and so should be anticipated. [ABSTRACT FROM AUTHOR]