Matching Supply Research Articles

How does the digital economy impact green manufacturing: A new perspective from the construction of a unified large market in China

In the context of the global move into the digital economy (DEC) era and the accelerated development of the green industry, constructing a unified large market provides a powerful accelerating effect for the green transformation and upgrading of the manufacturing industry (GTUM) empowered by DEC. This study employs panel data combining China’s provincial level with the level of manufacturing subsectors from 2011 to 2020. It examines the impact of DEC and the construction of a unified large market on GTUM and its action mechanism at the theoretical and empirical levels by combining the traditional econometric models with geographic information systems, machine learning models, and other advanced technologies. Results indicate that DEC significantly enhances GTUM. Relative to the efficiency aspects of GTUM, the impact of DEC is more pronounced on energy consumption and environmental protection. Mechanism tests reveal that DEC primarily facilitates GTUM by reducing market segmentation effects, stimulating market potential effects, and matching market supply and demand effects. Heterogeneity analysis finds that in regions with higher levels of trade openness, technological innovation, and public environmental awareness, DEC more effectively promotes GTUM. Analyzing the temporal dynamics of this influence, the impact of DEC on GTUM aligns with Metcalfe’s Law, which posits a non-linear characteristic. Furthermore, the construction of a unified large market amplifies the effect of DEC empowering GTUM. This study offers a novel pathway for China to fully leverage DEC and the advantages of an ultra-large market to enhance the level of GTUM. It also provides valuable insights for the green development of industries globally.

Design and simulation analysis of electromagnetic gun feeding and conveying device

Abstract The electromagnetic gun is a new type of weapon equipment powered by electric energy. Compared with the traditional artillery, the electromagnetic gun has the obvious advantages of high and controllable initial velocity, no explosive in the bore, and high safety. It is a new concept weapon that will be developed in the future. At present, there are many researches on the launching mechanism of electromagnetic gun, but the related research on the matching ammunition supply system is not yet mature. Therefore, in this paper, aiming at the characteristics of electromagnetic gun without propellant, through the comparison and selection of various ammunition supply system schemes, the ammunition supply scheme of horizontal magazine was determined, and the structural design and strength check were carried out to complete the model of each component and the overall assembly of ammunition supply system. After that, the finite element method was used to check the strength of the sprocket, and the dynamic simulation analysis of the ammunition supply system was carried out, so as to complete the design work of the whole ammunition supply system. This paper provides a certain reference for the development of electromagnetic gun feeding system.

Supply Chain Analytics, Definitions, Characteristics and Applications: A Systematic Literature Review

While there is a high uptake of BDA in the realm of supply chain management, in the view of automation supply chains and improving their value proposition by providing more accurate data for demand forecasting. There are material knowledge gaps on the SC-specific analytics applied to match demand, albeit the existing knowledge could be more amorphous. From this backdrop, the study endeavored to analyze extant literature within the ambit of BDA to unpack the current trends and possible future research directions to foster the application of BDA in SC contexts. The study adopted a systematic literature review of the extant literature published between 2014-2023. The study adopted the five-stage iterative procedure used in the systematic review methodology. The review's findings depict extensive use of big data analytics in matching demand and supply and supply chain optimization. The findings of this study adduce almost non-rebuttable evidence that big data analytics can be applied in procurement, inventory control, logistics, and order processing. Under the auspices of BDA is the SCA. Arguably, extant research has demonstrated the capability of SCA in mitigating contemporary SC risks such as mismatches between demand and supply, sub-optimal SCs, and underutilization of the supply chain infrastructures at the cusps of various echelons.

Blockchain-based information sharing and supply and demand matching cloud platform for automotive manufacturing supply chain

PurposeThis study aims to propose a cloud platform architecture considering information sharing based on blockchain to realize the security and convenience of enterprise information sharing in the automotive supply chain.Design/methodology/approachA bilateral matching model considering enterprises information contribution stimulates information sharing and improves the efficiency and quality of supply and demand matching. Three smart contracts are used to complete the information sharing process and match supply and demand in the automotive supply chain.FindingsThe system is tested on the local Ganache private chain, and the decentralized web page is designed based on the architecture prototype.Originality/valueSolve the problem of information island in automobile supply chain.

An iterative price-based combinatorial double auction for additive manufacturing markets

The increasing adoption of additive manufacturing (AM) in the industrial sector is leading to an imbalance between supply and demand of additively manufactured subcomponents: companies demanding AM services require very specific products and AM suppliers differ widely in their capabilities. Some existing proposals aim to help match supply and demand by merely making customer–supplier allocations. Only a few recent works go beyond allocation issues and propose market mechanisms to also address pricing aspects. However, we observe that these mechanisms do not fully exploit the potential of additive manufacturing techniques. The aim of this paper is to design a market mechanism that considers the particularity of AM techniques, wherein suppliers can benefit from manufacturing multiple heterogeneous parts from multiple customers in the same build area to increase production throughput. This market mechanism has been implemented as an iterative combinatorial double auction that adapts to this feature of the AM market: customers will bid to get their orders produced and suppliers will submit asking quotes to win the production of combinations of those orders. The mechanism solves the allocation and pricing of AM orders while seeking the maximization of social welfare. The procedure is simulated in a theoretical environment to evaluate its performance and to identify the most appropriate conditions for its implementation in a real environment. Unlike other existing proposals for client-supplier allocation mechanisms in additive manufacturing, the proposed mechanism allows a single supplier to produce a combination of orders from different clients, leading to a pricing system that maximizes social welfare without participants disclosing sensitive information.

Asymmetric Nash bargaining model for operation optimization of multi-integrated energy systems considering peer-to-peer energy trading

Energy interactions across integrated energy systems constitute crucial means to enhance energy efficiency and match supply and demand. However, the cooperative operation and benefit distribution among multiple integrated energy systems still need in-depth exploration. To fill this gap, this paper presents an asymmetric Nash bargaining optimization model for multiple integrated energy systems considering peer-to-peer trading. First, a scheduling model for multi-integrated energy systems is formulated considering carbon trading. Then, the model is incorporated into Nash bargaining framework and transformed into the alliance cost minimization subproblem and peer-to-peer trading payment bargaining subproblem. The bargaining power factor is introduced to measure the contribution of participants in energy sharing. The alternating direction multiplier method is utilized to handle the proposed model. Finally, a case study is carried out to validate the validity of the proposed strategy. The results show that compared with the independent operation mode, the performances of three integrated energy systems in collaborative operation mode are enhanced by 11.7 %, 9.0 %, and 4.8 % respectively. The distributed algorithm can reduce the computation time by 30 % and obtain highly efficient solutions while protecting private information of each participant. This research provides support and practical tools for conducting peer-to-peer transactions of multiple integrated energy systems.

Governance and obstacles in the reception and social and labour integration of asylum seekers in Spain

Changes in migratory flows have transformed Spain from a country of emigration to one of the main destinations for international migration. And it has also become one of the most important European countries in the reception of asylum seekers and refugees in the last decade. With an unprepared reception system, the State has faced this challenge by decentralising socio-labour integration responsibilities to third sector entities. This article aims to analyse the institutional approach to the management and integration of asylum seekers, studying changes in the management of the reception and integration system for this group. Through documentary analysis and descriptive statistics, we observe a greater streamlining of certain processes, particularly after the arrival of asylum seekers from Ukraine in 2022. However, structural deficiencies remain, hindering the processes of matching labour supply and demand.

Optimal Policies and Heuristics to Match Supply with Demand for Online Retailing

Problem definition: We consider an online retailer selling multiple products to different zones over a finite horizon with multiple periods. At the start of the horizon, the retailer orders the products from a single supplier and stores them at multiple warehouses. The retailer determines the products’ order quantities and their storage quantities at each warehouse subject to its capacity constraint. At the end of each period, after random demands in the period are realized, the retailer chooses the retrieval quantities from each warehouse to fulfill the demands of each zone. The objective is to maximize the retailer’s expected profit over the finite horizon. Methodology/results: For the single-zone case, we show that the multiperiod problem is equivalent to a single-period problem and the optimal retrieval decisions follow a greedy policy that retrieves products from the lowest-cost warehouse. We design a nongreedy algorithm to find the optimal storage policy, which preserves a nested property: Among all nonempty warehouses, a smaller-index warehouse contains all the products stored in a larger-index warehouse. We also analytically characterize the optimal ordering policy. The multizone case is unfortunately intractable analytically, and we propose an efficient heuristic to solve it, which involves a nontrivial hybrid of three approximations. This hybrid heuristic outperforms two conventional benchmarks by up to 22.5% and 3.5% in our numerical experiments with various horizon lengths, fulfillment frequencies, warehouse capacities, demand variations, and demand correlations. Managerial implications: A case study based on data from a major fashion online retailer in Asia confirms the superiority of the hybrid heuristic. With delicate optimization, the heuristic improves the average profit by up to 16% compared with a dedicated policy adopted by the retailer. The hybrid heuristic continues to outperform the benchmarks for larger networks with various structures. Funding: X. Li is supported by the Singapore Ministry of Education [Tier 1 Grant 23-0619-P0001]. Y. F. Lim is grateful for the support from the Singapore Management University under the Maritime and Port Authority Research Fellowship and the Singapore Ministry of Education [Tier 1 Grant MSS23B001]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0394 .

Auctions to reveal consumers’ willingness to pay for low-carbon hydrogen projects: combining lessons from renewables and natural-gas industries

Abstract Low-carbon hydrogen is expected to play a key role in realizing net-zero and sustainable development plans. Nonetheless, there is a gap between the cost of producing low-carbon hydrogen and its potential users’ willingness to pay for such hydrogen. To implement support for the development of the industry, we propose using low-carbon hydrogen long-term agreements allocated through auction mechanisms. The objectives are 2-fold: (i) matching supply and demand volumes considering the time horizon and geographical delivery point specification and (ii) allocating the subsidy. This perspective article innovates by proposing a reference price indexed to liquid to natural-gas prices, which is the main product that low-carbon hydrogen aims to substitute. The premium and the production cost are defined through a double-sided auction. This aims to minimize the public policy funds required to incentivize the low-carbon hydrogen market while facilitating long-term agreements and mitigating price risks that may hinder investment.

INFLUENCE OF TRANSPORTATION PROCESS ON SUPPLY CHAIN PERFORMANCE OF SELECTED MANUFACTURING INDUSTRIES IN RWANDA A CASE OF ADMA INTERNATIONAL

Background: This research aimed to assess the influence of transportation on supply chain performance of manufacturing industries in Rwanda, a case study of ADMA International. This research: examined the effect of fleet management process on supply chain performance in ADMA International assessed the effect of route planning on supply chain performance in ADMA International and determined the effect of order processing on supply chain performance in ADMA International. Materials and Methods: Both descriptive survey and correlational research designs were used in this study in order to facilitate the accomplishment of the aforementioned goals. The target population of this project was 141 people that included 21 ADMA International employees working at the head office and 120 customers (suppliers and distributors) of ADMA International that operate in each of the secondary cities in the country including Kigali city. The other cities were: Huye, Musanze, Nyagatare and Rubavu. This study made use of a variety of methods, including surveys, interviews, written records, and other institutional reports, in order to collect research data. SPSS, a software used for descriptive statistics, was used to examine the data in order to determine whether transportation has an impact on supply chain performance of manufacturing industries in Rwanda. In this study, we considered both inferential and regression analyses in order to assess the strength of the link that exists between the study variables. Results: From the findings, the following were discovered: (β1= 0.410, t=2.108, p = 0.013<0.05 β2= 0.206, t= 1.779, p =0.017<0.05 β2= 0.425, t= 1.214, p =0.011<0.05). This refers to the fact that 1 per cent increase in transportation practices in form of fleet management, route planning and order processing will lead to 0.410, 0.206, 0.425 and 0.558 increase in supply chain performance of ADMA International. Therefore, the regression model showed that supply chain performance was 1.347+ 0.410 Fleet management + 0.206 Route planning + 0.425 Order processing. From these findings, all the hypotheses were rejected. In accordance with the studys conclusions, the researcher suggested that ADMA management be engaged for the supply chain and prerequisite in order to handle the complexity and rising customer expectations. The supply chain processs planning and control should be strengthened by ADMA management. Furthermore, ADMA management ought to keep developing a competitive infrastructure, utilizing global logistics, and matching supply and demand. In summary, the research findings suggest that raw material transportation has an impact on the supply chain of manufacturing businesses at ADMA based on an analysis of the data collected there. Conclusion: While ADMAs product quality and quantity are important competitive advantages in the market, the research shows that competitive transit times and dependable raw material suppliers that dont require longer than four weeks for delivery, depending on the source, should distinguish the ADMA supply chain. The transportation of raw materials is correlated with the supply chain of manufacturing industries at ADMA, according to research using the Pearson correlation.

Multi-objective integrated optimization of geothermal heating system with energy storage using digital twin technology

Heat energy storage technology plays a significant role in energy systems, and the various technological solutions brought about by digitalization are especially valuable in the field of energy storage. This article proposes an innovative model based on digital twin technology to solve the supply–demand mismatch problem in geothermal heating systems. This model achieves multi-objective optimization of comprehensive cost, geothermal energy utilization rate, and carbon emission by constructing a heat storage geothermal heating system. Digital twin technology integrates data and information models of public buildings and facilitates their sharing and transmission throughout the entire lifecycle of the geothermal heating system. Initially, the proposed method employs a machine learning-based approach to accurately predict heating demand. Subsequently, the operation of the heat storage water tank and heat pump units is optimized to resolve difficulties in matching energy supply and demand. Finally, the method takes full advantage of time-of-use electricity pricing policies to reduce costs. The data utilized were collected from an office building in China over a period of six months. Experimental results demonstrate that: (1) In terms of predicting heating demand, the improved neural network proposed in this study achieved a prediction accuracy of 98%, which is a 10% improvement over comparative algorithms. Additionally, the experimental comparison of four types of errors showed that the machine learning method proposed had smaller errors across the board. (2) The method realized collaborative multi-objective optimization, and in five scenarios, the comprehensive performance index increased by up to 38.03% compared to the benchmark system. This indicates that intelligent technology is an effective means of enhancing the energy sustainability of geothermal heating systems, and the use of geothermal energy as a clean energy source effectively addresses issues related to the storage, utilization, management, and energy conservation of buildings.

Integrating blockchain and strategic alliance in renewable energy supply chain toward sustainability: A comparative decision framework under uncertainty

Renewable energy development is important in the current era due to the attention paid to environmental issues and energy demand growth. On the other hand, the growth and expansion of the use of RE requires cooperation and participation in the Renewable Energy Supply Chain (RESC). The strategic alliance between the parties involved in the field of RE can play an important role in reducing risk and significant growth in RESC. Also, due to various capabilities such as transparency, traceability, decentralization, security, and immutability of information, blockchain plays an important role in improving trust and strengthening cooperation in strategic alliances between partners in RESC. Therefore, this study proposes a decision-making framework under uncertainty for integrating blockchain and strategic alliance in RESC. The proposed framework involves the CRiteria Importance Through Intercriteria Correlation (CRITIC) and Fuzzy Combined Compromise Solution (F-CoCoSo) techniques. Also, validation and sensitivity analysis are performed using several fuzzy decision-making techniques. The findings indicated that matching energy supply and demand through information sharing on the blockchain platform and cooperating with companies in the RESC was recognized as the most important solution.

Load management design and techno-economic analysis for an islanded hybrid Pv-Teg microgrid

Integration of various renewable energy sources (RES) is one of the critical factors behind microgrid (MG) capacity development and MG expansion. Distributed energy resources with and without RES, electrical loads, controllers, and storage units constitute the essential components of MGs. On the other hand, with the addition of different power generation sources, load prediction on the user side of the MG becomes an important issue. Demand response solutions and changing end-user behavior are the other sources of uncertainty in the performance of MGs. Therefore, matching supply and demand is a very important issue that must be done immediately at every moment of the operation. A load management system (LMS) in a community MG is essential to ensure the system’s adaptability. Fuzzy logic (FL) controllers and energy management systems will ensure optimum use of energy resources and efficient operation of MG and reduce energy waste. In this study, an 85 kW photovoltaic (PV) and thermoelectric generator (TEG) hybrid MG system (PVTEG-MG), which can operate as an island grid in all regions of the World with hot water resources, has been designed for the first time and its techno-economic analysis has been made. The state of charge (SOC) for the proposed PVTEG-MG remained stable at 40% charge state by adding charge management. The average value of the Levelized Cost of Energy (LCOE) is $0.456/kWh for PV, $0.456/kWh for TEG, and 0.399/kWh over the total energy produced, 219,000 kWh for the PV and 493,650 kWh for the TEG. Overall, this PVTEG-MG system is a promising solution for hot water regions that can be used as an island grid to reduce electricity costs, increase efficiency and reliability, and provide a more sustainable energy source.

Coupling and Coordination Research on Green Finance and Ecological Civilization Construction in Xinjiang

Since the national proposal to construct a green financial system, Xinjiang has three pilot areas for green finance. The connotation of green finance shares similarities with the basic requirements of ecological civilization construction. This paper analyzes the coupling mechanism between green finance and ecological civilization construction, and conducts research based on the coupling coordination model. Through the study, it is found that the ecological civilization construction in Xinjiang is improving year by year, while the development of green finance fluctuates significantly. However, the overall trend of both tends to be of high-quality coordinated development. Green finance and ecological civilization construction can promote each other, fundamentally being a complementary relationship. Therefore, from the perspective of promoting the development of green finance, it is believed that Xinjiang should promote the development of green finance from three dimensions: broadening the sources of green finance funds, improving the mechanism of matching supply and demand of funds, and enhancing the efficiency of fund allocation.

Linking red blood cell functional phenotypes to environmental tolerance in high-altitude adapted deer mice

Oxygen (O2) is essential for vertebrate life, and complex cardio-respiratory systems have evolved to transport the gas from the environment to each individual cell. Even short disruptions of this O2 flux can have deleterious effects that are linked to numerous disease states. Animals that have adapted to hypoxic environments, such as deer mice ( Peromyscus maniculatus) native to high altitude, can provide valuable insight into naturally evolved solutions to O2 deprivation. Previous work has shown that high-altitude deer mice have evolved a higher hemoglobin O2 affnity and other coordinated changes across the O2 transport cascade that enable higher metabolic rates in hypoxia. Red blood cells (RBC) are the functional unit of O2 and carbon dioxide transport in the blood and play central roles in matching O2 supply and demand in the microcirculation by releasing signaling molecules such as ATP and gasotransmitters; but how these cellular mechanisms respond to hypoxic environments has not been studied. We hypothesized that high-altitude adaptation in deer mice has improved the function of RBCs for cardiovascular gas transport in hypoxia. Lab-raised breeding colonies of deer-mice were established from wild mice caught at low altitude (~400 m in the Great Plains of Nebraska) and at high altitude (~4300 m in the Rocky Mountains of Colorado). Using a common-garden experimental design, third-generation deer mice from high- and low-altitude populations were acclimated to warm normoxia (21°C, 21 kPa O2) or cold hypobaric hypoxia (5°C, 12 kPa O2) for 8 weeks. Blood samples were collected for measurements of hematocrit, hemoglobin concentration, RBC volume, plasma erythropoietin concentration, RBC contents of membrane transport and channel proteins (anion exchanger, aquaporin 1 and rhesus associated glycoprotein) by immunocytochemistry and western blotting, and carbonic anhydrase activity using biochemical techniques. The release of ATP from RBCs was measured in tonometers at decreasing levels of O2 by luminometry, and the vascular sensitivity to ATP was determined by wire myography on second-order mesenteric arteries. Finally, bone marrow samples were collected from the femurs to measure gene expression levels in the erythropoietic tissue. Our experimental design allowed us to examine the interactive effects of cold hypoxic environments on RBC phenotype, by untangling environmentally-induced plasticity from the signatures of adaptation that are unique to high-altitude natives. This work is providing a better understanding of how RBC function participates in matching cardiovascular O2 supply and demand in extreme hypoxia, which has important applications in animal and human health. This work was supported by a NSERC Canada Banting Postdoctoral Fellowship to TSH and a Discovery Grant to GRS. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Research on matching supply of power and cold energy of liquid hydrogen cold chain logistics vehicles

Liquid hydrogen cold-chain logistics vehicle (LHCCLV) is a special vehicle using liquid hydrogen (LH2) as the source of both power and cold energy. A significant weakness of LH2 is its high energy consumption during the hydrogen liquefaction process, thus the utilization of cold energy in LHCCLV can improve the economic performance and competitiveness of LH2. Because of the high energy storage density of LH2 and the relatively high efficiency of fuel cells, we find that cold energy can not meet the demand of LHCCLV. Therefore, we consider enlarging the cold energy by efforts including the para-ortho hydrogen conversion (POC), whose reverse reaction consumes an energy level exceeding 20% during the hydrogen liquefaction process. In this paper, numerical models of discharging hydrogen from the LH2 and subcooling hydrogen tank are established, and the influence of POC and other efforts on the supply of cold energy is analyzed. The changes in instantaneous and total cold energy supply under different working conditions are analyzed, and the important influence of POC and other efforts is confirmed. The beneficial effect of POC is quantified in the paper, especially for the cold energy supply. This paper provides an essential reference for the research and development of LHCCLV. Also, it guides the comprehensive utilization of cold energy in other situations to promote the improvement of the economy of hydrogen energy utilization routes in the form of LH2.

Model of a Prototype Expert System for the Formation of a Simple Classifier of Competencies

The purpose of the research is to describe the process of creating an expert system that compares competency models and professional standards with the current needs of the labor market.Methods are based on an analysis of the principles of developing competencies and include a systematic analysis of labor market requirements, the use of methods for comparative analysis of graduates’ competencies and the needs of employers using statistical data. Тhe research is aimed at solving the fundamental problem of matching the skills of specialists with the needs of the labor market. Аs part of this work, an extensive search of data sources was carried out, including an analysis of graduate employment reports and requirements for specialists, during which a discrepancy between the competencies of graduates and the needs of employers was identified.Results. Аs a result of the research, a unified database was created containing information about universities, their areas, competencies and graduates, as well as requirements for the future expert system were formulated, its architecture was developed, and a model for representing knowledge about compliance was described. Тhis system will be able to provide recommendations for improving competencies based on a comparison of labor market requirements.Conclusion. Тhe expert system created on the basis of this work provides operational capabilities for solving issues of matching supply and demand in the labor market, will increase the effectiveness of training, and will help meet the needs of employers for experienced specialists. Тhis concept has several positive aspects, such as increasing the efficiency of training, reducing time resources, publicity and accessibility. Such a system will increase the competitiveness of applicants, as well as satisfy organizations in need of experienced specialists.

A study on matching supply and demand of ecosystem services in the Hexi region of China based on multi-source data.

To achieve the best management of the ecosystem and sustainable socioeconomic development, it is crucial to clarify the matching relationship between the supply and demand of ecosystem services (ESs). Four types of ESs were chosen for the Hexi region in this study: food supply, carbon sequestration, water yield, wind erosion control and sediment retention. We assessed the supply-demand and matching relationships of different ESs using the Integrated Valuation of Ecosystem Service and Tradeoffs (InVEST) model, the ESs supply-demand ratio and the four-quadrant model. Moreover, we also analyzed the supply-demand ratio of integrated ESs and their cold spots. The findings suggest that (1) from 2000 to 2020, the average supply of food supply, carbon sequestration, water yield, wind erosion control and sediment retention increased by 44.31t/km2, 128.44t/hm2, 14,545.94m3/km2 and 0.14kg/m2 respectively, which showed a spatial pattern of "high in the southeast and low in the northwest". The average demand for food supply and carbon sequestration increased by 1.33t/km2 and 0.32t/hm2 respectively, while the average demand for water yield and wind erosion control and sediment retention decreased by 2997.25m3/km2 and 1.19kg/km2 respectively. The spatial distribution is consistent with the layout of population density, production and residential areas, and fragile ecological areas. (2) The supply-demand ratio of food supply, carbon sequestration and water yield is greater than 0.095, which is in a state of oversupply, and the supply-demand ratio of wind erosion control and sediment retention is less than 0, which is in a state of shortage; all ESs are mainly in low-low spatial matching areas, mainly concentrated in the desert areas of the northwest in the Hexi region. (3) The supply-demand ratio of integrated ESs increased by 0.024, and the proportion of cold spots and sub-cold spots was more than 50% and concentrated in the northwest, while hot spots and sub-hot spots accounted for only about 16%, mainly distributed in the southern Qilian Mountains and some oasis areas.

When and How to (Mis-)match Supply and Demand: Managing Variable Environments

When and How to (Mis-)match Supply and Demand: Managing Variable Environments

The Role of the Patient Advocate During a Pandemic: The Case of Convalescent Plasma.

The onset of the COVID-19 pandemic confronted medicine with several difficulties, including a lack of specific therapeutic options, the absence of out-of-hospital testing facilities to diagnose the condition, and the sudden extraordinary need for intensive medical care that overwhelmed most hospitals. Early in the pandemic, many physicians recognized that using antibodies harvested from recovering patients was a treatment that had a proven track record for many diseases and that might be used to manage the disease at least as a stopgap until more specific medicines for COVID-19 were developed. But using convalescent plasma raised many additional complications, most especially the logistics that needed to be put in place to collect and distribute such plasma. Unlike drugs ordered from a pharmacy, plasma and other blood products are procured by a complex process that depends intensely on interaction with the public, the provider of all blood products that are directly provided to patients. Blood components such as convalescent plasma, intended to be used immediately without major processing, are entirely supplied by donations from the public. This form of treatment can therefore benefit from patient advocates, especially if they are experienced in solving problems of logistics and in the process of matching supply to demand that is more commonly encountered in the business world than in medicine. In this chapter, one patient advocate, Chaim Lebovits, describes the process of mobilizing the population, interacting with blood banks and hospitals, and successfully channeling thousands of units of plasma from volunteers recovering from COVID-19 to patients in hospitals. Starting in New York City in early 2020 and initially working with communities with which Mr. Lebovits was familiar, the efforts steadily spread across many parts of the US. The model described here, which uses patient advocates to serve as a link between patients, blood banks, and hospitals in the service of gathering and distributing high-titer convalescent plasma to patients is likely to be relevant to the next pandemic.