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A recent global pandemic, known as coronavirus disease 2019 (COVID-19), affects the manufacturing supply chains most significantly. This effect becomes more challenging for the manufacturers of high-demand and most essential items, such as toilet paper and hand sanitizer. In a pandemic situation, the demand of the essential products increases expressively; on the other hand, the supply of the raw materials decreases considerably with a constraint of production capacity. These dual disruptions impact the production process suddenly, and the process can collapse without immediate and necessary actions. To minimize the impacts of these dual disruptions, we aim to develop a recovery model for making a decision on the revised production plan.

In this paper, the authors use a mathematical modeling approach to develop a production recovery model for a high-demand and essential item during the COVID-19. The authors also analyze the properties of the recovery plan, and optimize the recovery plan to maximize the profit in the recovery window.

The authors analyze the results using a numerical example. The result shows that the developed recovery model is capable of revising the production plan in the situations of both demand and supply disruptions, and improves the profit for the manufacturers. The authors also discuss the managerial implications, including the roles of digital technologies in the recovery process.

This model, which is a novel contribution to the literature, will help decision-makers of high-demand and essential items to make an accurate and prompt decision in designing the revised production plan to recover during a pandemic, like COVID-19.

Enormous numbers of people suffer from the effects of disasters and humanitarian crises in Africa, including medical and healthcare emergencies. International response to the 2014–2016 Ebola pandemic in West Africa and COVID 19 pandemic vividly demonstrates the need for efficient and effective logistics and supply chain systems in bringing succor to impacted and vulnerable communities. This paper critically reviews the academic literature on logistics models for sourcing, delivery and distribution of medical and healthcare products for humanitarian emergencies in Africa from 1990 to 2018. The paper suggests areas for further research and proposes an effective logistics model useful for international and national humanitarian organizations as well as public health authorities in Africa and developing areas.

The viewpoint paper draws upon a structured comprehensive and critical review of the academic literature on logistics and supply chain management and a qualitative analysis of the literature in 13 leading academic databases covering over 5,550 articles.

The paper finds significant gaps in the body of logistics and supply chain management research on practical deployable logistics models for sourcing, delivery, and distribution of medical and healthcare products for humanitarian emergencies. The paper suggests a model worthy of consideration by humanitarian and disaster response stakeholders as well as public health authorities in developing countries.

This is a critical literature review paper based on a comprehensive literature research and analysis for the period from 1990 to 2018 from which a viewpoint is formed.

This paper advocates for further research on appropriate models of logistics for the sourcing, delivery and distribution of medical and healthcare products to enhance the basic human rights and dignity of vulnerable people in developing countries.

The paper contributes directly to policy on logistics, humanitarian aid, disaster management, public health and health security policy in the developing world including Africa.

Proactive planning strategies for “slow-onset” disruptions that affect humanitarian supply chains (SC) developed to address chronic pressing societal problems, can have a significant impact on boosting the operational and financial performance of these chains. The purpose of this paper is to develop a methodology that quantifies the impact of a risk mitigation strategy widely employed in commercial SCs, namely emergency sourcing (ES), on the performance of humanitarian SCs taking into account backorders’ clearance time, unsatisfied demand, and cost.

Discrete event simulation is employed in order to evaluate alternative ES strategies based on a total cost criterion, which incorporates inventory-related costs, as well as premium contract costs paid for emergency replenishment. Backorders’ clearance time and time-to-recovery are also employed as a design parameters.

The results document the significant impact of disruptions on expected total cost, and the beneficial role of ES in hedging against disruptions. To that end, the proposed methodology determines the optimal emergency contracted capacity for a given premium, or alternatively the maximum premium cost value that ensures the feasibility of the implemented ES strategy in the long-run, along with the associated cost and time savings, and reduction of the unsatisfied demand.

The fundamental objective is to provide a decision-making support methodology for deciding on whether to implement an ES strategy or not in humanitarian SCs, and the level of the optimal contracted reserved capacity. The results could be of great value to aid providers, policy-makers, and regulators.

The purpose of this paper is to provide small and medium-sized enterprises (SMEs) in emerging markets with an updated Purchasing Portfolio Matrix (PPM) specifically for international sourcing. This data-driven PPM matrix is designed to provide a dynamic and process perspective that can help SMEs survive the disruptions caused by emergency situations such as the global COVID-19 pandemic.

This research reports on qualitative interviews with experienced informants from 15 SMEs in the manufacturing industry. The authors follow process-based research using a combination of retrospective and real-time case study approaches to gradually unveil the dynamics in segmentation and sourcing strategies in the international sourcing context during the COVID-19 pandemic.

The findings reveal the dynamics of segmentation and international sourcing strategies during global disruptions and unpack the underlying logic behind the dynamics that is specific to SMEs in emerging economies.

Existing literature on PPM predominantly focuses on static and normal sourcing circumstances. This paper addresses this gap by adopting a dynamic approach to study how sourcing strategies of SMEs from emerging economies evolve in a highly volatile environment from an international sourcing perspective.

The coronavirus disease (COVID-19) pandemic has emerged as an unprecedented health crisis worldwide and heavily disrupted the healthcare supply chain. This study focuses on analysing the different types of disruptions occurring in personal protective equipment (PPE) supply chains during the COVID-19 pandemic and on proposing mitigation strategies that are fit to the global scale and many interdependencies that are characteristic for this pandemic. The authors construct a conceptual system dynamics model (SD) based on the literature and adjusted with the use of empirical data (interviews) to capture the complexity of a global supply chain and identify leverage points (mitigation strategies).

This research follows a mix-methods approach. First, the authors developed a conceptual framework based on four types of disruptions that usually occur during health emergencies (direct effect, policy, supply chain strategy, and behaviourally induced disruptions). Second, the authors collected and analysed data from interviews with experts in the PPE supply chain. Based on the interviews data, the authors developed a conceptual system dynamics (SD) model that allows to capture the complex and dynamic interplay between the elements of the global supply chain system, by highlighting key feedback loops, delays, and the way the mitigation strategies can impact on them. From this analysis, the authors developed four propositions for supply chain risk management (SCRM) in global health emergencies and four recommendations for the policy and decision makers.

The SD model highlights that without a combination of mitigation measures, it is impossible to overcome all disruptions. As such, a co-ordinated effort across the different countries and sectors that experience the disruptions is needed. The SD model also shows that there are important feedback loops, by which initial disruptions create delays and shortages that propagate through the supply chain network. If the co-ordinated mitigation measures are not implemented early at the onset of the pandemic, these disruptions will be persistent, creating potential shortages of PPE and other critical equipment at the onset of a pandemic – when they are most urgently needed.

This research enriches the understanding of the disruptions of PPE supply chains on the systems level and proposes mitigation strategies based on empirical data and the existing literature.

The purpose of this paper is to provide a taxonomy of strategic sourcing using the defense forces from a developing world context as a testing ground. This study builds upon the current resource-based conceptualization of strategic sourcing as a construct to introduce the institutional orientation.

This study adopts a descriptive and analytical research design of cross-sectional nature to collect data from a sample of 120 respondents to examine the taxonomy of strategic sourcing for defense forces in sub-Saharan Africa. Data were collected using an interviewee administered questionnaire and analysed using a confirmatory factor analysis (CFA). The conceptualization of strategic sourcing is presented using a CFA.

Findings reveal that strategic sourcing is a multidimensional construct composed of: information sharing and risk management, strategic purchasing, institutions for sourcing, internal integration and performance assessment, supplier management and sourcing professionalism and ethics.

The study used cross-sectional research design which limits monitoring behaviour over time. Cross-sectional data do not allow control in the analysis for residual heterogeneity. Additionally, all item scales adapted in this study were developed in either manufacturing or profit-oriented sector.

A taxonomy for strategic sourcing within the defense forces is presented. This study is based on the observation that despite increased research, there remains a certain level of confusion surrounding the conceptualization of “strategic sourcing”. Researchers attach a startling diversity of definitions and measures to the strategic sourcing concept. Its conceptualization and stability remains an important task for scholars to undertake. Besides, much research in strategic sourcing, are conceptual frameworks identifying key elements and procedures or processes to implement strategic sourcing with sparse empirical studies. The results of the study will be used for further research on strategic sourcing in the defense forces in sub-Saharan Africa.

This paper proposes a two-level supply chain including suppliers and manufacturers. The purpose of this paper is to design a resilient fuzzy risk-averse supply portfolio selection approach with lead-time sensitive manufacturers under partial and complete supply facility disruption in addition to the operational risk of imprecise demand to minimize the mean-risk costs. This problem is analyzed for a risk-averse decision maker, and the authors use the conditional value-at-risk (CVaR) as a risk measure, which has particular applications in financial engineering.

The methodology of the current research includes two phases of conceptual model and mathematical model. In the conceptual model phase, a new supply portfolio selection problem is presented under disruption and operational risks for lead-time sensitive manufacturers and considers resilience strategies for risk-averse decision makers. In the mathematical model phase, the stages of risk-averse two-stage fuzzy-stochastic programming model are formulated according to the above conceptual model, which minimizes the mean-CVaR costs.

In this paper, several computational experiments were conducted with sensitivity analysis by GAMS (General algebraic modeling system) software to determine the efficiency and significance of the developed model. Results show that the sensitivity of manufacturers to the lead time as well as the occurrence of disruption and operational risks, significantly affect the structure of the supply portfolio selection; hence, manufacturers should be taken into account in the design of this problem.

The study proposes a new two-stage fuzzy-stochastic scenario-based mathematical programming model for the resilient supply portfolio selection for risk-averse decision-makers under disruption and operational risks. This model assumes that the manufacturers are sensitive to lead time, so the demand of manufacturers depends on the suppliers who provide them with services. To manage risks, this model also considers proactive (supplier fortification, pre-positioned emergency inventory) and reactive (revision of allocation decisions) resilience strategies.

Startups across all sectors are affected by the COVID-19 pandemic and are facing a formidable challenge in terms of marketing and operations. Most of the startups have experienced a downturn in demand and supply due to COVID-19 led disturbances in sourcing networks. This paper aims to identify, analyze and categorize the significant risks influencing sourcing operations in startups during the COVID-19 era in India, using the total interpretive structural modeling (TISM) approach.

Eight enablers were identified through literature review and expert opinions from various startups in India. This study adopted the TISM approach to analyze the inter-relationships between the enablers. Multiplication Applied to Classification (MICMAC) analysis was used to rank the sourcing risk enablers and classify them as autonomous, independent, linkage and dependent enablers.

The results indicate “insufficient fund” as the most critical enabler. Network issues and employee flexibility risk were among the other critical enablers that have a high driving power. Supplier risk, quality risk and demand risk were found to have highly dependent on other enablers for implementation.

This study mainly focuses on the sourcing risks in startup operations in India. This study can be extended to many other countries.

This study will help startup industry managers and practitioners understand the interactions of enablers and identify critical enablers to mitigate risks in startup sourcing operations in the COVID-19 era.

The present study identifies the sourcing risk enablers in the COVID-19 era. It is the first attempt to analyze the interrelationship among sourcing risks in startups using the TISM approach.

Emergency contracting has risen to the fore in both interest and importance in the US since September 11, 2001 (9/11). Most recently, the US government's response to Hurricanes Katrina and Rita piqued the interest of both the Executive and Legislative branches of the US government and their respective oversight bodies. This paper briefly reviews the literature of emergency contracting with special focus on the statutory and regulatory framework for emergency contracting, identifies some contracting solutions established by the US government to deal more effectively with emergency contracting, and pinpoints some problems faced by emergency contracting agencies and anomalies of their emergency contracting practices.

This study aims to examine the value of the call option contract in hedging the risks in the supply chain. The decentralized supply chain without call option contract is first studied as the criterion model for evaluations. This paper addresses several questions: What will be the optimal manufacturer’s production quantity, retailer’s ordering and pricing policies in the presence of random demand and random yield by applying the downconversion approach? How will the call option contract influence the optimal decisions for the members of the supply chain? Can the risk from randomness be divided among the members in the supply chain through the call option contract?

This paper considers a two-level decentralized supply chain under random yield and random demand in which the manufacturer takes advantage of the downconversion approach with two scenarios, with and without option contract. To the best of the authors’ knowledge, no article or study uses the downconversion approach in a supply chain regarding random yield and random demand. Furthermore, the paper considers pricing with option contract in the supply chain, which makes this article stands out significantly from other articles in the literature.

This study shows that the downconversion approach would reduce the risk caused by the random yield, which appears to be the appropriate method for the environmental goal of the supply chains. Moreover, adopting a call option contract can increase flexibility and mitigate risks, resulting in more expected members’ profits.

To simplify the model, the authors assume one manufacturer and one retailer, so extending the model to consider multiple retailers instead of one retailer and inventory sharing between them would be interesting. Considering the option and exercise prices as decision variables would be important future research topics. Put option and bidirectional option contracts could be investigated in the future. Another extension is modeling asymmetry of information in supply chain.

This paper provides managerial insights on dealing with both demand and yield risks in a manufacturer–retailer supply chain. The manufacturer has a random yield production and produces two types of vertical products: low-end and high-end. To reduce waste caused by the random yield, the manufacturer uses a downconversion approach in which low-end products are made by converting the defective high-end products. The manufacturer purchased a shortage of high-end products from the secondary market (i.e. emergency sourcing). High-end products are sold through the retailer, and low-end products are sold directly by the manufacturer. The customer demand for high-end products in the end market is random and depends on the selling price, and the customer demand for the low-end products in the secondary market is independent and random. The retailer contracts the manufacturer with the call option to obtain high-end products to meet a random demand; in fact, by using the call option contract, the authors try to balance the risks between two members. Two scenarios of with and without call option contract are proposed. After the high-end product demand is observed, the retailer would exercise the option order quantity in the call option contract scenario and then place an instant order with the manufacturer if necessary. In each scenario, the manufacturer and the retailer make their decisions simultaneously (static game) to determine the retailer’s optimal ordering and pricing policies and the optimal production quantity of the manufacturer (Nash equilibrium) by maximizing their expected profits. Finally, the impact of the model parameters on the supply chain is expressed through numerical examples. The numerical analysis shows that the call option contract provides greater profit than the wholesale price contract.