An intelligent blockchain-based system for safe vaccine supply and supervision

Advancing sustainability in the food and nutrition system: a review of artificial intelligence applications

Promoting sustainability in food and nutrition systems is essential to address the various challenges and trade-offs within the current food system. This imperative is guided by key principles and actionable steps, including enhancing productivity and efficiency, reducing waste, adopting sustainable agricultural practices, improving economic growth and livelihoods, and enhancing resilience at various levels. However, in order to change the current food consumption patterns of the world and move toward sustainable diets, as well as increase productivity in the food production chain, it is necessary to employ the findings and achievements of other sciences. These include the use of artificial intelligence-based technologies. Presented here is a narrative review of possible applications of artificial intelligence in the food production chain that could increase productivity and sustainability. In this study, the most significant roles that artificial intelligence can play in enhancing the productivity and sustainability of the food and nutrition system have been examined in terms of production, processing, distribution, and food consumption. The research revealed that artificial intelligence, a branch of computer science that uses intelligent machines to perform tasks that require human intelligence, can significantly contribute to sustainable food security. Patterns of production, transportation, supply chain, marketing, and food-related applications can all benefit from artificial intelligence. As this review of successful experiences indicates, artificial intelligence, machine learning, and big data are a boon to the goal of sustainable food security as they enable us to achieve our goals more efficiently.

A global blockchain for recording high rates of COVID-19 vaccinations

Blockchain has been recently proposed to securely record vaccinations against COVID-19 and manage their verification. However, existing solutions may not fully meet the requirements of a global vaccination management system. These requirements include the scalability required to support a global vaccination campaign, like one against COVID-19, and the capability to facilitate the interoperation between the independent health administrations of different countries. Moreover, access to global statistics can help to control securing community health and provide continuity of care for individuals during a pandemic. In this paper, we propose GEOS, a blockchain-based vaccination management system designed to address the challenges faced by the global vaccination campaign against COVID-19. GEOS offers interoperability between vaccination information systems at both domestic and international levels, supporting high vaccination rates and extensive coverage for the global population. To provide those features, GEOS uses a two-layer blockchain architecture, a simplified byzantine-tolerant consensus algorithm, and the Boneh-Lynn-Shacham signature scheme. We analyze the scalability of GEOS by examining transaction rate and confirmation times, considering factors such as the number of validators, communication overhead, and block size within the blockchain network. Our findings demonstrate the effectiveness of GEOS in managing COVID-19 vaccination records and statistical data for 236 countries, encompassing crucial information such as daily vaccination rates for highly populous nations and the global vaccination demand, as identified by the World Health Organization.

VaccineChain: A checkpoint assisted scalable blockchain based secure vaccine supply chain with selective revocation

In the present era of the pandemic, vaccination is necessary to prevent severe infectious diseases, i.e., COVID-19. Specifically, vaccine safety is strongly linked to global health and security. However, the main concerns regarding vaccine record forgery and counterfeiting of vaccines are still common in the traditional vaccine supply chains. The conventional vaccine supply chains do not have proper authentication among all supply chain entities. Blockchain technology is an excellent contender to resolve the issues mentioned above. Although, blockchain based vaccine supply chains can potentially satisfy the objectives and functions of the next-generation supply chain model. However, its integration with the supply chain model is still constrained by substantial scalability and security issues. So, the current blockchain technology with traditional Proof-of-Work (PoW) consensus is incompatible with the next-generation vaccine supply chain framework. This paper introduces a model named "VaccineChain" - a novel checkpoint-assisted scalable blockchain based secure vaccine supply chain. VaccineChain guarantees the complete integrity and immutability of vaccine supply records to combat counterfeited vaccines over the supply chain. The dynamic consensus algorithm with various validating difficulty levels supports the efficient scalability of VaccineChain. Moreover, VaccineChain includes anonymous authentication among entities to provide selective revocation. This work also consists of a use case example of a secure vaccine supply chain using checkpoint assisted scalable blockchain with customized transaction generation-rule and smart contracts to demonstrate the application of VaccineChain. The comprehensive security analysis with standard theoretical proofs ensures the computational infeasibility of VaccineChain. Further, the detailed performance analysis with test simulations shows the practicability of VaccineChain.

A blockchain-based evaluation approach to analyse customer satisfaction using AI techniques

Due to technological advancements and consumer demands, online shopping creates new features and adapts to new standards. A robust customer satisfaction prediction model concerning trust and privacy platforms can encourage an organization to make better decisions about its service and quality. This study presented an approach to predict consumer satisfaction using the blockchain-based framework combining the Multi-Dimensional Naive Bayes-K Nearest Neighbor (MDNB-KNN) and the Multi-Objective Logistic Particle Swarm Optimization Algorithm (MOL-PSOA). A regression model is employed to quantify the impact of various production factors on customer satisfaction. The proposed method yields better levels of measurement for customer satisfaction (98%), accuracy (95%), necessary time (60%), precision (95%), and recall (95%) compared to existing studies. Measuring consumer satisfaction with a trustworthy platform facilitates to development of the conceptual and practical distinctions influencing customers' purchasing decisions.

Blockchain and COVID-19 pandemic: applications and challenges

The year 2020 has witnessed the emergence of coronavirus (COVID-19) that has rapidly spread and adversely affected the global economy, health, and human lives. The COVID-19 pandemic has exposed the limitations of existing healthcare systems regarding their inadequacy to timely and efficiently handle public health emergencies. A large portion of today's healthcare systems are centralized and fall short in providing necessary information security and privacy, data immutability, transparency, and traceability features to detect fraud related to COVID-19 vaccination certification, and anti-body testing. Blockchain technology can assist in combating the COVID-19 pandemic by ensuring safe and reliable medical supplies, accurate identification of virus hot spots, and establishing data provenance to verify the genuineness of personal protective equipment. This paper discusses the potential blockchain applications for the COVID-19 pandemic. It presents the high-level design of three blockchain-based systems to enable governments and medical professionals to efficiently handle health emergencies caused by COVID-19. It discusses the important ongoing blockchain-based research projects, use cases, and case studies to demonstrate the adoption of blockchain technology for COVID-19. Finally, it identifies and discusses future research challenges, along with their key causes and guidelines.

Blockchain-enabled supply chain operations and financing: the perspective of expectancy theory

Purpose

This study examines the cognitive factors of adopting blockchain technology in various supply chain scenarios and its role in reframing the distinctive values of supply chain financing. Based on expectancy theory, this study explores the different profiles underlying the components of expectancy, valence and instrumentality.

Design/methodology/approach

This is a multiple-case study of four Fintech companies using blockchain technology to promote the performance of supply chain operations and financing.

Findings

The results show that blockchain-enabled supply chain finance (BSCF) can be classified into four scenarios based on the scope and purpose of blockchain technology applications. The success of BSCF depends on the profiles of BSCF expectancy (the recognized purpose and scope of BSCF), instrumentality (identified blockchain attributes and other technology combinations) and valence (the perceived distinctive value of BSCF). Blockchain attributes help solve information asymmetry problems and enhance financing performance in two ways: one is supporting transparency, traceability and verification of transmissions and the other entails facilitating a transformation to new business models.

Originality/value

This research applies a new perspective based on expectancy theory to study how cognitive factors affect Fintech companies' blockchain solutions under a given supply chain operation or financing activity. It explains the behavioral antecedents for applying blockchain technology, the situations appropriate for the different roles of blockchain technology and the profiles for realizing the value of blockchain technology.

Vaccine supply chain management: An intelligent system utilizing blockchain, IoT and machine learning

Vaccination offers health, economic, and social benefits. However, three major issues-vaccine quality, demand forecasting, and trust among stakeholders-persist in the vaccine supply chain (VSC), leading to inefficiencies. The COVID-19 pandemic has exacerbated weaknesses in the VSC, while presenting opportunities to apply digital technologies to manage it. For the first time, this study establishes an intelligent VSC management system that provides decision support for VSC management during the COVID-19 pandemic. The system combines blockchain, internet of things (IoT), and machine learning that effectively address the three issues in the VSC. The transparency of blockchain ensures trust among stakeholders. The real-time monitoring of vaccine status by the IoT ensures vaccine quality. Machine learning predicts vaccine demand and conducts sentiment analysis on vaccine reviews to help companies improve vaccine quality. The present study also reveals the implications for the management of supply chains, businesses, and government.

A critical analysis of the integration of blockchain and artificial intelligence for supply chain

The integration between blockchain and artificial intelligence (AI) has gained a lot of attention in recent years, especially since such integration can improve security, efficiency, and productivity of applications in business environments characterised by volatility, uncertainty, complexity, and ambiguity. In particular, supply chain is one of the areas that have been shown to benefit tremendously from blockchain and AI, by enhancing information and process resilience, enabling faster and more cost-efficient delivery of products, and augmenting products' traceability, among others. This paper performs a state-of-the-art review of blockchain and AI in the field of supply chains. More specifically, we sought to answer the following three principal questions: Q1-What are the current studies on the integration of blockchain and AI in supply chain?, Q2-What are the current blockchain and AI use cases in supply chain?, and Q3-What are the potential research directions for future studies involving the integration of blockchain and AI? The analysis performed in this paper has identified relevant research studies that have contributed both conceptually and empirically to the expansion and accumulation of intellectual wealth in the supply chain discipline through the integration of blockchain and AI.

Pharmaceutical enterprises drug quality strategy Moran analysis considering government supervision and new media participation

The improvement of drug quality requires not only the supervision of government, but also the participation of new media. Therefore, this paper considers the impact of government regulation and new media reports on pharmaceutical enterprises, constructs a Moran Process evolutionary game model, and analyzes the evolution trajectory of pharmaceutical enterprises' choice of drug quality improvement strategy and drug cost reduction strategy. We obtain the conditions for the two strategies to achieve evolutionary stability under the dominance of external factors and the dominance of expected returns. To verify the theoretical results, we conduct a numerical simulation by the software MATLAB 2021b. The results show that, first of all, when the government penalty is high, the drug quality improvement strategy tends to become an evolutionary stable solution, increasing the penalty amount will help promote the improvement of drug quality. What's more, when the government penalty is low and the new media influence is low, the drug cost reduction strategy is easier to dominate. The higher the new media influence, the higher the probability that pharmaceutical enterprises choose the drug quality improvement strategy. Thirdly, when the number of pharmaceutical enterprises is lower than a threshold, the drug quality improvement strategy is easier to dominate. Finally, the drug quality improvement strategy is dominant when the quality cost factor is low and the government penalty is high, the drug cost reduction strategy is dominant when the quality cost factor is high and the government penalty is low. Above all, this paper provides countermeasures and suggestions for the drug quality improvement of pharmaceutical enterprises in practice.

A reliable vaccine tracking and monitoring system for health clinics using blockchain

Vaccines are delicate biological substances that gradually become inactive over time and must be kept under a recommended temperature range of 2-8 °C for both short and long-term storage. Exposure to heat or freezing temperatures can highly affect the immunological properties of these vaccines and make them completely ineffective. Research shows that vaccine exposure to temperatures outside the recommended range is 33% in developed countries and 37.1% in developing countries. In practice, vaccines are stored in refrigerators, while thermometers and data loggers are used to record and monitor temperatures. However, traditional systems are unreliable due to lack of battery backup, human error, periodic logging of temperatures, etc. Therefore, an effective and reliable vaccine tracking and monitoring system is urgently needed. This paper proposes a blockchain-based, smart contract enabled solution that ensures an enhanced level of security, transparency, and traceability of stored vaccines in a health clinic, and enables the complete history of every vaccine to be checked from the day the vaccine is received by the health clinic to the date it is used or expires. We also formally analyze the resiliency of the proposed system against several attacks and compare the system with existing blockchain and non-blockchain-based solutions.

Improving the distribution of covid-19 vaccines using the blockchain technology: the Italian case study

Vaccination is one of the most effective ways to prevent and control the outbreak of infectious diseases. The vaccine supply chain differs from the traditional supply chains because of the perishability of the products, which need strict transport and warehousing conditions to guarantee the health and safety of people. In addition, in case of pandemics, the big amount of doses requested for the implementation of a mass vaccination campaign forces governments to design a proper logistic network and plan a rapid and efficient distribution of vaccines. This paper studies the organization of allocation and distribution of the covid-19 vaccines in Italy. The main criticalities in managing the vaccine supply chain have been identified and, because of its peculiarities, the blockchain has been considered a suitable technology to solve them. A simulation model has been developed to reproduce the current distribution of vaccines in Italy, and a future scenario with blockchain has been studied. The findings show that it is possible to improve the performance of the vaccine supply chain and make it more resilient by implementing the blockchain technology.

Vaccine supply chain coordination using blockchain and artificial intelligence technologies

Currently, the global spread of COVID-19 is taking a heavy toll on the lives of the global population. There is an urgent need to improve and strengthen the coordination of vaccine supply chains in response to this severe pandemic. In this study, we consider a vaccine supply chain based on a combination of artificial intelligence and blockchain technologies and model the supply chain as a two-player dynamic game with inventory level as the dynamic equation of the system. The study focuses on the applicability and effectiveness of the two technologies in the vaccine supply chain and provides management insights. The impact of the application of the technologies on environmental performance is also considered in the model. We also examine factors such as the number of people vaccinated, positive and side effects of vaccines, vaccine decay rate, revenue-sharing/cost-sharing ratio, and commission ratio. The results are as follows: the correlation between the difficulty in obtaining certified vaccines and the profit of a vaccine manufacturer is not monotonous; the vaccine manufacturer is more sensitive to changes in the vaccine attenuation rate. The study's major conclusions are as follows: First, the vaccine supply chain should estimate the level of consumers' difficulty in obtaining a certified vaccine source and the magnitude of the production planning and demand forecasting error terms before adopting the two technologies. Second, the application of artificial intelligence (AI) technology is meaningful in the vaccine supply chain when the error terms satisfy a particular interval condition.

Artificial Intelligence and Blockchain Integration in Business: Trends from a Bibliometric-Content Analysis

Artificial intelligence (AI) and blockchain are the two disruptive technologies emerging from the Fourth Industrial Revolution (IR4.0) that have introduced radical shifts in the industry. The amalgamation of AI and blockchain holds tremendous potential to create new business models enabled through digitalization. Although research on the application and convergence of AI and blockchain exists, our understanding of the utility of its integration for business remains fragmented. To address this gap, this study aims to characterize the applications and benefits of integrated AI and blockchain platforms across different verticals of business. Using bibliometric analysis, this study reveals the most influential articles on the subject based on their publications, citations, and importance in the intellectual network. Using content analysis, this study sheds light on the subject's intellectual structure, which is underpinned by four major thematic clusters focusing on supply chains, healthcare, secure transactions, and finance and accounting. The study concludes with 10 application areas in business that can benefit from these technologies.

A Traceable Vaccine Supply Management System

Everyone should be vaccinated, but the eligibility and safety of the vaccine are always overlooked by most people. The outbreak of COVID-19 has led many countries to intensify the development and production of the COVID-19 vaccine. and some countries have even required universal vaccination against this epidemic. However, such popularization of vaccination has also exposed various flaws in vaccine management that existed in the past, and vaccinators have become more concerned about the effectiveness of their vaccinations. In this paper, we propose a blockchain-based traceable vaccine management system. First, the system uses smart contracts to store the records generated during the whole process, from vaccine production to vaccination. Second, the proposed scheme uses the Edwards-curve digital signature algorithm (EdDSA) to guarantee the security and integrity of these data. Third, the system participants can access the corresponding data according to their authority to ensure the transparency of the whole system operation process. Finally, this paper will also conduct a security analysis of the whole system to ensure that the system can resist potential attacks by criminals.

Blockchain technology in supply chain management: an organizational theoretic overview and research agenda

Blockchain technology is touted as a game-changer. Many experts consider blockchain technology as one of the disruptive innovations. Following significant success in the banking and finance sector, blockchain technology has found significant success in all fields, including health, manufacturing, transportation, disaster relief operations, and many others. Recently, the academician has contributed significantly towards understanding blockchain technology and its application in the management field. To understand how the literature on blockchain technology in the supply chain has progressed, we undertook an extensive review of the literature published in peer-reviewed journals using databases such as SCOPUS. We have further classified our literature into four stages (pre-adoption, adoption, implementation, and application). Finally, we synthesized the findings of the study and proposed a research framework to explain how an organization can build supply chain resilience and enhance supply chain performance with the help of blockchain technology. Finally, we have noted the limitations of the study and future research directions.

A Framework Based on Blockchain, Artificial Intelligence, and Big Data Analytics to Leverage Supply Chain Resilience considering the COVID-19

In the global supply chains era, firms are more connected, integrated, and interdependent, bringing along a set of benefits and a number of risks. It is clear that the singular COVID-19 epidemic outbreak has led to unparalleled disruptions and considerable challenges for supply chains (SCs). For example, the sluggish economic environment provoked by the COVID-19 has negatively impacted the flow of goods, generating shortages and interruptions through the SCs. At the global level, many markets are enduring the effects of these disruptions. In this challenging context, the firms and their SCs must apply useful and efficient strategies to minimize and adapt their operations during and after these disruptions. In this view, this study aims to propose a novel framework based on Artificial Intelligence, Blockchain, and Big Data Analytics, to bring useful ideas and contribute to overcoming such disruptions. Besides, we propose novel categorizations that can support new insights for scholars and practitioners about the use of cutting-edge technologies during and after severe disruptions.

Distributed Supervision Model for Enterprise Data Asset Trading Based on Blockchain Multi-Channel in Industry Alliance

Compared with traditional physical commodities, data are intangible and easy to leak, and the related trading process has problems, such as complex participating roles, lengthy information flow, poor supervisory coverage and difficult information traceability. To handle these problems, we construct a distributed supervision model for data trading based on blockchain, and conduct multi-party hierarchical and multi-dimensional supervision of the whole process of data trading through collaborative supervision before the event, at present and after the event. First, the characteristics of information flow in the data trading process are analyzed, and the main subject and key supervision information in the data trading process are sorted out and refined. Secondly, combined with the actual business process of data trading supervision, a multi-channel structure of distributed supervision is proposed by adopting an access-verification-traceability strategy. Finally, under the logical framework of the supervision model, the on-chain hierarchical structure and the data hybrid storage method of "on-chain + off-chain" are designed, and multi-supervisor-oriented hierarchical supervision and post-event traceability are realized through smart contracts. The results show that the constructed blockchain-based distributed supervision model of data trading can effectively isolate and protect sensitive and private information between data trading, so as to realize the whole process, multi-subject and differentiated supervision of key information of data trading, and provide an effective and feasible method for the controllable and safe supervision of data trading.

Blockchain Powered Vaccine Efficacy for Pharma Sector

Infectious and contagious diseases exist in humanity for many centuries which causes a curb in the growth of the population. Immunization plays a vital role to prevent mortality and morbidity against infectious diseases. COVID-19 pandemic continues to rage the urgency of developing a vaccine that should ensure the safety, efficacy, swift and fair deployment, implementation, and monitoring of vaccines across the globe. In the present context, the vaccine production to immunization campaign is a critical challenge. Therefore, an effective vaccine supply chain mechanism is required to address issues such as counterfeit vaccines, reduce vaccine wastages, and vaccine record fraud. In this paper, a blockchain-enabled vaccine supply chain is proposed to ensure the correctness, transparency, trust, and immutable log and improve the efficiency of vaccine distribution in the cold chain. The uniqueness of the proposed system is to provide distributed system to verify the reliability and efficacy of the vaccine from production to end beneficiaries' feedback about the vaccine. Our proposed system gives a clear view to the users as well as to the healthcare provider about the vaccination and ensures the anticounterfeit vaccine. The proposed system minimizes counterfeit vaccines and records, provides transparent communication between stakeholders in the supply chain, and improves the security of the vaccine supply chain and immutable feedback system about the vaccine.

Using FIWARE and blockchain in smart cities solutions

Nowadays, Blockchain has been widely used to store decentralized and secure transactions involving cryptocurrency, e.g., Bitcoin, Ethereum, etc. However, Blockchain can also store other types of information besides monetary transactions. On the other hand, innovative solutions for smart cities are concerned with how services and information can be safely stored and shared. For this reason, smart city systems can benefit from using Blockchain to integrate their data and services. These smart solutions also demand consistency and standardization across the industry. However, this Blockchain integration varies according to its implementation. FIWARE, a framework of an open-source platform for smart solutions, adopts NGSI Standards (Context Information Management (CIM); NGSI-LD API: Tech. Rep., CIM and ETSI Industry Specification Group (ISG), 2020) to enable the integration of components and provides the basis for interoperability and portability among smart solutions. Unfortunately, FIWARE does not support any integration with Blockchain technology. Hence, this paper proposes a set of new components to allow FIWARE to be integrated with Blockchain technology. With these proposed components, it is possible to support Blockchain technology with smart city applications via the FIWARE platform. For instance, we have designed and implemented a FIWARE Blockchain adapter to submit/listen to transactions from/to FIWARE Context Broker to/from any Blockchain implementation without human intervention. In addition, we present a global post-pandemic vaccination case study to evaluate the proposed approach in the Smart City context.

A two-stage decision-support approach for improving sustainable last-mile cold chain logistics operations of COVID-19 vaccines

The COVID-19 pandemic has become a global health and humanitarian crisis that catastrophically affects many industries. To control the disease spread and restore normal lives, mass vaccination is considered the most effective way. However, the sustainable last-mile cold chain logistics operations of COVID-19 vaccines is a complex short-term planning problem that faces many practical challenges, e.g., low-temperature storage and transportation, supply uncertainty at the early stage, etc. To tackle these challenges, a two-stage decision-support approach is proposed in this paper, which integrates both route optimization and advanced simulation to improve the sustainable performance of last-mile vaccine cold chain logistics operations. Through a real-world case study in Norway during December 2020 and March 2021, the analytical results revealed that the logistics network structure, fleet size, and the composition of heterogeneous vehicles might yield significant impacts on the service level, transportation cost, and CO2 emissions of last-mile vaccine cold chain logistics operations.

Public health events emergency management supervision strategy considering citizens’ and new media’s different ways of participation

Public health events have done great harm. Emergency management requires the joint participation of multiple parties including government department, pharmaceutical enterprises, citizens and new media. Then, what are the effects of different strategy choices in participation of citizens and new media on emergency management? To answer the question, we construct a four-party evolutionary game model, considering the citizens' two participation ways consisted of true evaluation and false evaluation, and the new media's two participation ways consisted of report after verification and report without verification. This is of more practical significance than simply studying whether citizens and new media participate in emergency management or not because citizen and new media participation does not represent the completely positive behavior. Then, we conduct the evolutionary stability analysis, solve the stable equilibrium points using the Lyapunov first method and conduct the simulation analysis with MATLAB 2020b. The results show that, firstly, the greater the probability of citizens making true evaluation, the more inclined the government department is to strictly implement the emergency management system; secondly, when the probability of citizens making true evaluation decreases, new media are more inclined to report after verification, and when new media lose more pageview value or should be punished more for reporting without verification, the probability that they report without verification is smaller; thirdly, the greater the probability of citizens making false evaluation, the less enthusiasm of pharmaceutical enterprises to participate in emergency management, which indicates that false evaluation is detrimental to prompt pharmaceutical enterprises to participate; what's more, the greater the probability of new media reporting after verification, the greater the probability of pharmaceutical enterprises actively participating, which shows that new media's verification to citizens' evaluation is beneficial to emergency management.

Blockchain as the "trust-building machine" for supply chain management

This paper aims to investigate the impact of blockchain application on trust levels in supply chains. Through the systematic review of the relevant literature, three dimensions of trust, i.e., the trustor-trustee perspective, forms of trust, and time orientation, are investigated. Our findings show that, first, there are three pairs of trustors and trustees involved in blockchain implementation: (a) the user and the blockchain, (b) two supply chain partners, and (c) the consumer/public and a supply chain unit. Second, the two forms of trust, namely cognition-based and institution-based trust, are likely to be enhanced by blockchain execution, while affect-based trust may not be directly impacted by the technology. Third, the presence of blockchain technology would facilitate swift trust-building between unknown supply chain partners under specific circumstances. Moreover, we also find contradicting assertions among scholars on the implications of blockchain for trust in supply chains. While some studies pointed out that blockchain will enable a trustless trusted scheme, others expected the reinforcement of interorganizational trust. To test these assertions, we develop the blockchain-entrusted supply chain models to present the three-step process of how trust is developed through the blockchain and diffused to supply chain partners and external stakeholders.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10479-022-04868-0.

Blockchain for Electronic Vaccine Certificates: More Cons Than Pros?

Electronic vaccine certificates (EVC) for COVID-19 vaccination are likely to become widespread. Blockchain (BC) is an electronic immutable distributed ledger and is one of the more common proposed EVC platform options. However, the principles of blockchain are not widely understood by public health and medical professionals. We attempt to describe, in an accessible style, how BC works and the potential benefits and drawbacks in its use for EVCs. Our assessment is BC technology is not well suited to be used for EVCs. Overall, blockchain technology is based on two key principles: the use of cryptography, and a distributed immutable ledger in the format of blockchains. While the use of cryptography can provide ease of sharing vaccination records while maintaining privacy, EVCs require some amount of contribution from a centralized authority to confirm vaccine status; this is partly because these authorities are responsible for the distribution and often the administration of the vaccine. Having the data distributed makes the role of a centralized authority less effective. We concluded there are alternative ways to use cryptography outside of a BC that allow a centralized authority to better participate, which seems necessary for an EVC platform to be of practical use.

A Study of Health Insurance Fraud in China and Recommendations for Fraud Detection and Prevention

Healthcare insurance fraud influences not only organizations by overburdening the already fragile healthcare systems, but also individuals in terms of increasing premiums in health insurance and even fatalities. Identifying the behavioral characteristics of fraudulent claims can help shed light on the development of artificial intelligence and machine learning technologies to detect fraud in health information system research. In this paper, a theoretical model of medical insurance fraud identification is proposed, which characterizes the judgment variables of fraud from the three dimensions of time, quantity, and expenses. The model is verified with large-scale, real-world medical records. Our study shows that, in comparison with claims made by normal people, fraudulent claims usually have a greater frequency of hospital visits, and more medical bills, accompanied by higher amounts of medical expenses. An interesting discovery is that the price per bill for fraudulent cases is not statistically different from the normal cases.

A Review and Classification Framework of Traceability Approaches for Identifying Product Supply Chain Counterfeiting

Counterfeiting is found today in many industries and in various forms with severe consequences for supply chain operations. Products counterfeiting can be detected in consumer goods such as clothing, food and beverages, accessories, pharmaceuticals, electronics, and luxury goods. The continuous violations in the supply chain have led to the need for mobilization of all involved stakeholders to overcome counterfeiting challenges. Effective traceability seems to be the only way to combat this phenomenon, ensuring safe and sustainable supply chain operations. This paper presents a structured literature review on traceability approaches for combatting the product supply chain counterfeiting phenomenon that led to forming a structured classification framework. The performed analysis aims to identify trends and good practices and can be used as a guideline for real-life projects against supply chain counterfeiting. The results show that traditional traceability methods are not effective as they can be easily falsified using today’s technological advancements. However, these same advancements also present valuable technologies such as blockchain and the internet of things to ensure safe and sustainable supply chain operations.

Improved Blockchain Technology for Performance Optimization Model Design of Sports Clubs

Professional sports clubs are an important part of professional sports, and their development has a certain role in promoting the strength of China's competitive sports and the prosperity of the sports industry. However, the development of professional sports clubs in China is still facing many challenges. Among them, the key to their long-term development is to improve their financing ability and solve their financing difficulties in order to improve the performance of professional sports club. At present, research on the financing methods and financing difficulties of professional sports clubs has achieved certain results, but no systematic research on the application of blockchain technology to solve the pain points of professional sports club financing has been established. This study systematically compares the current situation and development problems of financing for professional sports clubs in China from the new perspective of combining blockchain and professional sports club financing. In addition, this article proposes a solution for the application of blockchain technology to optimize the performance of professional sports club, which has important theoretical and practical significance for promoting the development of professional sports clubs.

Investigating the role of stakeholder engagement for more resilient vaccine supply chains during COVID-19

The complexity of the supply chains and the uncertainties in the processes cause business to become more vulnerable in the face of disruptions. Pandemic situations such as COVID-19 cause sudden disruptions in supply chains, causing processes to be disrupted. Especially in multi-stakeholder supply chains, the importance of stakeholder communication, motivation, and regulations i.e. comes to the forefront in order to ensure the resilience of supply chains. As learned with the COVID-19 pandemic, vaccine supply chains are also one of the multi-stakeholder supply chains and are extremely vulnerable to disruptions. In COVID-19 times, the importance of vaccine supply chain management and the resilience in vaccine supply chains increased. To have more resilient vaccine supply chains, stakeholder engagement is an essential issue. Therefore, the Graph Theory Matrix Approach has been used to determine factors of stakeholder engagement in multi-stakeholder vaccine supply chains and to specify the relationships between the factors of project and stakeholder engagement in vaccine supply chains to increase resilience in disruption times. The aim of the study is to identify the factors of project and stakeholder engagement that are necessary to ensure the resilience of multi-stakeholder vaccine supply chains and not be affected by disruptions such as COVID-19 as it is today. As a result of the study, innovativeness of stakeholders is the most important factor of stakeholder engagement in vaccine supply chains.

Research themes in machine learning applications in supply chain management using bibliometric analysis tools

Purpose

This paper conducts a Systematic Literature Review (SLR) of Machine Learning (ML) in Supply Chain Management through bibliometric and network analysis, the authors are able to grasp key features of the contemporary literature. The study makes use of state-of-the-art analytical framework based on a unified approach to reveal insights from the present body of knowledge and the potentials for future research developments.

Design/methodology/approach

Unlike standard literature reviews, in SLR, a structured approach is followed. The approach enables utilizing contemporary tools and software packages such as R-package “bibliometrix” and Gephi for exploratory and visual analytics. A number of clustering methods are employed to form clusters. Later, multivariate analysis methodologies are adopted to determine the dominant clusters for the influential co-cited references.

Findings

Using contemporary tools from Bibliometric Analysis (BA), the authors identify in an exploratory analysis, the influential authors, sources, regions, affiliations and papers. In addition, the use of network analysis tools reveals research clusters, topological analysis, key research topics, interrelation and authors’ collaboration along with their patterns. Finally, the optimum number of clusters computed for cluster analysis is decided using a systematic procedure based on multivariate analysis such as k-means and factor analysis.

Originality/value

Modern-day supply chains increasingly depend on developing superior insights from large amounts of data available from diverse sources in unstructured and semi-structured formats. In order to maintain a competitive edge, the supply chains need to perform speedy analysis of big data using efficient tools that provide real-time decision-making insights. Such an analysis necessitates automated processing using intelligent ML algorithms. Through a BA followed by a detailed data visualization in a network analysis enabled grasping key features of the contemporary literature. The analysis is based on 155 documents from the period 2008 to 2018 selected using a systematic selection procedure.

Reducing COVID-19 Cases and Deaths by Applying Blockchain in Vaccination Rollout Management

Goal: Because a fast vaccination rollout against coronavirus disease 2019 (COVID-19) is critical to restore daily life and avoid virus mutations, it is tempting to have a relaxed vaccination-administration management system. However, a rigorous management system can support the enforcement of preventive measures, and in turn, reduce incidence and deaths. Here, we model a trustable and reliable management system based on blockchain for vaccine distribution by extending the Susceptible-Exposed-Infected-Recovery (SEIR) model. The model includes prevention measures such as mask-wearing, social distancing, vaccination rate, and vaccination efficiency. It also considers negative social behavior, such as violations of social distance and attempts of using illegitimate vaccination proofs. By evaluating the model, we show that the proposed system can reduce up to 2.5 million cases and half a million deaths in the most demanding scenarios.

Management of COVID-19 vaccines cold chain logistics: a scoping review

Background

Successful mass vaccination programmes are public health achievements of the contemporary world. While pharmaceutical companies are actively developing new vaccines, and demonstrating results of effectiveness and safety profiles, concerns on COVID-19 vaccine management are under-reported. We aimed to synthesise the evidence for efficient cold chain management of COVID vaccines.

Methods

The scoping review’s conduct and reporting were based on the PRISMA–ScR 2018 checklist. We searched from April 2020 to January 2022 for publications in PubMed (LitCovid), Scopus and ScienceDirect. All review stages were pilot-tested to calibrate 2 reviewers. Articles on cold chain logistics and management were included, while publications solely describing COVID vaccines, their development and clinical aspects of the vaccine, were excluded. To capture relevant data, charting was conducted by one reviewer and verified by another. Results were analysed thematically and summarised descriptively in a table and in-text.

Results and discussion

We assessed 6984 potentially relevant citations. We included 14 publications originating from USA (n = 6), India (n = 2), Finland, Spain, Bangladesh, Netherlands, Switzerland and Ethiopia. They were reported as reviews (4), policy or guidance documents (3), experimental studies (2), case reports (2), expert commentary (1), phenomenological study (1), and decision-making trial and evaluation laboratory trial (1). The findings were presented in three themes: (i) regulatory requirements for cold-chain logistics, (ii) packaging and storage, and (iii) transportation and distribution. A conceptual framework emerged linking regulatory requirements, optimal logistics operation and formulation stability as the key to efficient cold chain management. Recommendations were made for improving formulation stability, end-product storage conditions, and incorporating monitoring technologies.

Conclusion

COVID-19 vaccines require special end-to-end supply cold chain requirements, from manufacture, and transportation to warehouses and healthcare facilities. To sustain production, minimise wastage, and for vaccines to reach target populations, an efficient and resilient vaccine supply chain which is assisted by temperature monitoring technologies is imperative.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40545-022-00411-5.

A Blockchain-Based Solution for COVID-19 Vaccine Distribution

The COVID-19 vaccine distribution chain faced multiple challenges associated with the lack of production capacity, security issues, and miscommunication between different actors. Blockchain technology has been shown to solve the security and miscommunication issues in other industries. We first identify distribution chain challenges via literature reviews and primary interviews. Case studies that solved these challenges in other industries also served as a source. This information allowed us to devise a blockchain framework for the vaccine distribution chain and evaluate its application feasibility. We present the framework using data flow diagrams. The proposed framework helps minimize the circulation of counterfeit vaccines and vaccination records, improves communication between stakeholders in the distribution chain, increases supply chain security, and simplifies vaccine inventorying and handling processes.

A Systematic Literature Review of Blockchain-Enabled Supply Chain Traceability Implementations

In recent years, traceability systems have been developed as practical tools for improving supply chain (SC) transparency and visibility, especially in health and safety-sensitive sectors like food and pharmaceuticals. Blockchain-related SC traceability research has received significant attention during the last several years, and arguably blockchain is currently the most promising technology for providing traceability-related services in SC networks. This paper provides a systematic literature review of the various technical implementation aspects of blockchain-enabled SC traceability systems. We apply different drivers for classifying the selected literature, such as (a) the various domains of the available blockchain-enabled SC traceability systems and relevant methodologies applied; (b) the implementation maturity of these traceability systems along with technical implementation details; and (c) the sustainability perspective (economic, environmental, social) prevalent to these implementations. We provide key takeaways regarding the open issues and challenges of current blockchain traceability implementations and fruitful future research areas. Despite the significant volume and plethora of blockchain-enabled SC traceability systems, academia has so far focused on unstructured experimentation of blockchain-associated SC traceability solutions, and there is a clear need for developing and testing real-life traceability solutions, especially taking into account feasibility and cost-related SC aspects.

Investigating the Integration of Industry 4.0 and Lean Principles on Supply Chain: A Multi-Perspective Systematic Literature Review

The development of digital technologies in all aspects of human life leads to increasing the necessity for investigating them in the Supply Chain (SC) as the main channel to provide products. Moreover, Lean principles, with the aim of reducing wastes, could be one of the main research streams in SC in recent years. Therefore, it is valuable to figure out the mutual effects of Lean principles and digital technologies as two growing areas in SC. Previous works did not pay attention to investigating this relationship at the SC level and were more focused on the production level. However, the present work addresses this issue by conducting a multi-perspective Systematic Literature Review (SLR). Additionally, in the present SLR, the impact of individual Industry 4.0 technologies in relation to Lean principles was investigated from various SC perspectives. The results reveal the necessity of studying single SC processes in Lean Digital SC. Moreover, the applicability of each technology should be illustrated to alleviate SC operational and organizational issues. The results provide useful insights about applying single digital technologies as well as a combination of them to each SC process to solve specific issues.

Industry 4.0 Technologies for the Manufacturing and Distribution of COVID-19 Vaccines

BACKGROUND

The evolutionary stages of manufacturing have led us to conceptualize the use of Industry 4.0 for COVID-19 (coronavirus disease 2019), powered by Industry 4.0 technologies. Using applications of integrated process optimizations reliant on digitized data, we propose novel intelligent networks along the vaccine value chain. Vaccine 4.0 may enable maintenance processes, streamline logistics, and enable optimal production of COVID-19 vaccines.

VACCINE 4.0 FRAMEWORK

The challenge in applying Vaccine 4.0 includes the requirement of large-scale technologies for digitally transforming manufacturing, producing, rolling-out, and distributing vaccines. With our framework, Vaccine 4.0 analytics will target process performance, process development, process stability, compliance, quality assessment, and optimized maintenance. The benefits of digitization during and post the COVID-19 pandemic include first, the continual assurance of process control, and second, the efficacy of big-data analytics in streamlining set parameter limits. Digitization including big data-analytics may potentially improve the quality of large-scale vaccine production, profitability, and manufacturing processes. The path to Vaccine 4.0 will enhance vaccine quality, improve efficacy, and compliance with data-regulated requirements.

DISCUSSION

Fiscal and logistical barriers are prevalent across resource-limited countries worldwide. The Vaccine 4.0 framework accounts for expected barriers of manufacturing and equitably distributing COVID-19 vaccines. With amalgamating big data analytics and biometrics, we enable the identification of vulnerable populations who are at higher risk of disease transmission. Artificial intelligence powered sensors and robotics support thermostable vaccine distribution in limited capacity regions, globally. Biosensors isolate COVID-19 vaccinations with low or limited efficacy. Finally, Vaccine 4.0 blockchain systems address low- and middle-income countries with limited distribution capacities.

CONCLUSION

Vaccine 4.0 is a viable framework to optimize manufacturing of vaccines during and post the COVID-19 pandemic.

Improving Shipping Efficiency Industry-Led Consortium Blockchain Smart Contact

COVID-19 has recently affected global trade flows, and the primary reason is that shipping failed to adapt rapidly to meet the need for on-time delivery. Given blockchain's “revolutionary” potential, this paper aims to understand how blockchain can address longstanding inefficiencies and challenges in the shipping industry. This analysis proposes a model of how an industrywide blockchain-based consortium powered by smart contracts could resolve end-to-end contract issues with trustworthiness, thus improving efficiency in terms of time and cost. A mixed-method approach was conducted. That included 27 surveys and 20 interviews with representatives of shipping industry members. This study contributes to the blockchain and shipping supply chain literature by offering empirical data about the application of an industry-led consortium blockchain with cost, scalability, and volatility perspectives. As for the managerial implications, incentives and education are required to stimulate collaboration and commitment to blockchain for more efficient and effective global shipping trade flows.

A Systematic Literature Review of Blockchain Technology for Smart Villages

According to the United Nations, Sustainable Development Goals are framed for improving rural health, hunger, poverty issues, environmental conditions, and illiteracy globally. With the upcoming technology, there have been many advances in the lifestyle of people all around the world. Comparatively, more emphasis has been given to the development of urban areas than rural. The sustainable development of a country depends on the growth of its rural areas. Countless technological and theoretical models, projects, and frameworks have been proposed and implemented to help overcome sundry issues and challenges faced by rural people in quotidian life. New technological methods are deemed to be the future of livability, therefore; a technologically advanced solution for sustainable rural development is called for. Blockchain Technology is the next step for innovation and development and it has far many applications in sustainable rural development that are yet to be discovered. The objective of this paper is to explicitly review research conducted in rural development to fill the undone work in the future with better research ideas, to make rural areas a livable and advanced place while also maintaining their integrity leading to sustainable development. To conduct such a review, a systematic research methodology is applied following regulations in the conduction of standardized but explorative analysis. Within the timeline of 2010-2021, 112 papers are carefully selected to perform the systematic review. This review will provide a comprehensible as well as concise research compendium for all applications proposed, implemented, and possible in the future to realize the concept of smart villages for the development of rural areas using blockchain technology.

Blockchain Enabled Transparent and Anti-Counterfeiting Supply of COVID-19 Vaccine Vials

The COVID-19 pandemic has profoundly affected almost all facets of peoples’ lives, various economic areas and regions of the world. In such a situation implementation of a vaccination can be viewed as essential but its success will be dependent on availability and transparency in the distribution process that will be shared among the stakeholders. Various distributed ledgers (DLTs) such as blockchain provide an open, public, immutable system that has numerous applications due the mentioned abilities. In this paper the authors have proposed a solution based on blockchain to increase the security and transparency in the tracing of COVID-19 vaccination vials. Smart contracts have been developed to monitor the supply, distribution of vaccination vials. The proposed solution will help to generate a tamper-proof and secure environment for the distribution of COVID-19 vaccination vials. Proof of delivery is used as a consensus mechanism for the proposed solution. A feedback feature is also implemented in order to track the vials lot in case of any side effect cause to the patient. The authors have implemented and tested the proposed solution using Ethereum test network, RinkeyBy, MetaMask, one clicks DApp. The proposed solution shows promising results in terms of throughput and scalability.

COVID-19 pandemics Stage II - Energy and environmental impacts of vaccination

The COVID-19 pandemic developed the severest public health event in recent history. The first stage for defence has already been documented. This paper moves forward to contribute to the second stage for offensive by assessing the energy and environmental impacts related to vaccination. The vaccination campaign is a multidisciplinary topic incorporating policies, population behaviour, planning, manufacturing, materials supporting, cold-chain logistics and waste treatment. The vaccination for pandemic control in the current phase is prioritised over other decisions, including energy and environmental issues. This study documents that vaccination should be implemented in maximum sustainable ways. The energy and related emissions of a single vaccination are not massive; however, the vast numbers related to the worldwide production, logistics, disinfection, implementation and waste treatment are reaching significant figures. The preliminary assessment indicates that the energy is at the scale of ~1.08 × 10¹⁰ kWh and related emissions of ~5.13 × 10¹² gCO_2eq when embedding for the envisaged 1.56 × 10¹⁰ vaccine doses. The cold supply chain is estimated to constitute 69.8% of energy consumption of the vaccination life cycle, with an interval of 26-99% depending on haul distance. A sustainable supply chain model that responds to an emergency arrangement, considering equality as well, should be emphasised to mitigate vaccination's environmental footprint. This effort plays a critical role in preparing for future pandemics, both environmentally and socially. Research in exploring sustainable single-use or reusable materials is also suggested to be a part of the plans. Diversified options could offer higher flexibility in mitigating environmental footprint even during the emergency and minimise the potential impact of material disruption or dependency.

A simulation-based analysis for effective distribution of COVID-19 vaccines: A case study in Norway

Since December 2020, the vaccines from several manufacturers, e.g., Pfizer/BioNTech, Moderna, etc., have been approved for mass vaccination to control the COVID-19 pandemic, which has caused more than 100 million infections and 2.4 million deaths. These vaccines are produced and transported in large quantities to suffice the needs of several countries. Before arriving at the end-users, the vaccines need to be stored at extremely low temperatures and distributed through reliable cold chain logistics networks. Thus, the timely and cost-effective distribution of COVID-19 vaccines via cold chain logistics has become a complex operational challenge. In this paper, we develop a simulation-based approach combining both route optimization and dynamic simulation to improve the logistics performance for COVID-19 vaccine distribution. A state-of-the-art simulation package called anyLogistix is used to perform a real-world case study in Norway. With the data of periodic vaccine demands, customer and warehouse locations, vehicle-related costs and emissions, and expected service levels, implications are obtained based on the analysis of several scenarios. Our experimental results reveal that the service level, cost-effectiveness, environmental performance, and equity of a cold chain vaccine logistics system can be significantly influenced by the fleet size, the fleet composition, the type of vehicle used, and the route optimization. Thus, these factors need to be holistically considered in the planning of an effective COVID-19 vaccine distribution system.