The state of play of blockchain technology in the financial services sector: A systematic literature review

Blockchain governance and trust: A multi-sector thematic systematic review and exploration of future research directions

This paper aims to critically examine the scholarly work conducted in blockchain (BC) governance. Without venturing into the wide range of governance paradigms, this research considers governance structures based on trust as a foundation for BC governance. A thematic systematic literature review is conducted to understand the literature on this topic, employing the SALSA (Search, Appraisal, Synthesis and Analysis) technique. An examination of 155 papers shows that using BC technology (BCT) replaces the cognitive attribution of trust in the material and human-independent code. It is also found that further research anchored to the 'trust' concept is required in building BC governance structures. To provide the direction in which the literature is travelling, future research questions on trust and governance are documented. In general, the literature review suggests that BC has the potential to revolutionize the way in which businesses operate. By improving transparency, efficiency, and security, BC can help businesses to reduce costs, improve customer satisfaction, and make better decisions. This research can help policymakers, industrialists, and researchers to identify where BC governance is being used and which aspects of governance are to be focused on. This paper is a general review of literature and evidence on contemporary developmental issues.

Efficient security level in wireless sensor networks (WSNs) using four-factors authentication over the Internet of Things (IoT)

With the increasing demand for the use of technology in all matters of daily life and business, the demand has increased dramatically to transform business electronically especially regards COVID-19. The Internet of Things (IoT) has greatly helped in accomplishing tasks. For example, at a high temperature, it would be possible to switch on the air conditioner using a personal mobile device while the person is in the car. The Internet of Things (IoT) eases lots of tasks. A wireless sensor network is an example of IoT. Wireless sensor network (WSN) is an infrastructure less self-configured that can monitor environmental conditions such as vibration, temperature, wind speed, sound, pressure, and vital signs. Thus, WSNs can occur in many fields. Smart homes give a good example of that. The security concern is important, and it is an essential requirement to ensure secure data. Different attacks and privacy concerns can affect the data. Authentication is the first defence line against threats and attacks. This study proposed a new protocol based on using four factors of authentication to improve the security level in WSN to secure communications. The simulation results prove the strength of the proposed method which reflects the importance of the usage of such protocol in authentication areas.

Digital accessibility in the era of artificial intelligence-Bibliometric analysis and systematic review

Introduction

Digital accessibility involves designing digital systems and services to enable access for individuals, including those with disabilities, including visual, auditory, motor, or cognitive impairments. Artificial intelligence (AI) has the potential to enhance accessibility for people with disabilities and improve their overall quality of life.

Methods

This systematic review, covering academic articles from 2018 to 2023, focuses on AI applications for digital accessibility. Initially, 3,706 articles were screened from five scholarly databases-ACM Digital Library, IEEE Xplore, ScienceDirect, Scopus, and Springer.

Results

The analysis narrowed down to 43 articles, presenting a classification framework based on applications, challenges, AI methodologies, and accessibility standards.

Discussion

This research emphasizes the predominant focus on AI-driven digital accessibility for visual impairments, revealing a critical gap in addressing speech and hearing impairments, autism spectrum disorder, neurological disorders, and motor impairments. This highlights the need for a more balanced research distribution to ensure equitable support for all communities with disabilities. The study also pointed out a lack of adherence to accessibility standards in existing systems, stressing the urgency for a fundamental shift in designing solutions for people with disabilities. Overall, this research underscores the vital role of accessible AI in preventing exclusion and discrimination, urging a comprehensive approach to digital accessibility to cater to diverse disability needs.

Drivers and influencers of blockchain and cloud-based business sustainability accounting in China: Enhancing practices and promoting adoption

The field of sustainability accounting aims to integrate environmental, social, and governance factors into financial reporting. With the growing importance of sustainability practices, emerging technologies have the potential to revolutionize reporting methods. However, there is a lack of research on the factors influencing the adoption of blockchain and cloud-based sustainability accounting in China. This study employs a mixed-methods approach to examine the key drivers and barriers to technology adoption for sustainability reporting among Chinese businesses. Through a systematic literature review, gaps in knowledge were identified. Primary data was collected through an online survey of firms, followed by in-depth case studies. The findings of the study reveal a positive relationship between company size and reporting behaviors. However, size alone is not sufficient to predict outcomes accurately. The industry type also has significant but small effects, although its impact on reporting behaviors varies. The relationship between profitability and reporting behaviors is intricate and contingent, requiring contextual examination. The adoption of blockchain technology is positively associated with capabilities, resources, skills, and regulatory factors. On the other hand, cloud computing adoption is linked to resources, management support, and risk exposures. However, the specific impacts of industry on adoption remain inconclusive. This study aims to offer empirical validation of relationships, shedding light on the intricate nature of interactions that necessitate nuanced conceptualizations incorporating contextual moderators. The findings underscore the importance of providing customized support and adaptable guidance to accommodate the evolving practices in sustainability accounting. Moreover, the assimilation of technology and organizational changes highlights the need for multifaceted stakeholder cooperation to drive responsible innovation and address the challenges posed by digital transformations in this field.

Is green FinTech reshaping the finance sphere? Unravelling through a systematic literature review

The revolutionary and transformative potential of FinTech has led to the Green Digital Finance Alliance, noting the dawn of a new era of FinTech-"the green FinTech", yet, surprisingly, the scholarly exploration surrounding climate finance in general and green FinTech and climate FinTech remains restrained. In our attempt to decode the intricate interlinkage between green finance and FinTech, the study wrestles with the theoretical complexity of the "green FinTech" concept through a systematic review of relevant studies and conceptual mapping. We develop a comprehensive grasp of the concept, how to leverage it to combat the pressing climate crisis, and its implications for the FinTech segment-the first of its kind in the scanty green FinTech literature. Based on the PRISMA analysis, we find that green FinTech promotes a green economy through its manifold impact on all aspects of the finance sphere, thereby channelling climate finance and promoting sustainability. It has the power to heighten inclusivity, disclosure, trust, and democratisation, thus reducing information asymmetry and greenwashing. Hence, FinTech integration can be game-changing in eliminating the hurdles before conventional green finance. However, the literature remains fragmented, along with a young, growing green FinTech market. Therefore, this study proposes a framework for future researchers by providing a holistic research agenda to fully integrate "green FinTech" into practical real-world applications.

Are Nursing Faculty Future-Ready? The Effects of Emerging Technologies on Nursing Education

BACKGROUND

Preparing the next generation of nurses requires consideration for the integration of emerging technologies. This refers specifically to technologies that will shape and affect how care is delivered-not in today's health care facilities but in facilities 20 years from now and beyond.

METHOD

A cross-sectional survey examining how seven emerging technologies were integrated into nursing curricula was developed and distributed to nursing faculty. A multiple linear regression model was used to analyze the data for the level of integration. The model was adjusted for all demographic measures, and the independent variables of interest were developed from unified theory of acceptance and use of technology (UTAUT) constructs.

RESULTS

Performance, attitude, social influence, and effort were insignificant. Education and training, costs, and complexity were noted as top barriers to adoption.

CONCLUSION

A literature gap regarding integrating emerging technologies in nursing curricula exists. Further research is warranted to understand factors influencing integration. [J Nurs Educ. 2023;62(12):689-700.].

How does blockchain technology affect the development of green finance? Theoretical analysis and empirical verification

Facing the problem of a lack of endogenous incentive mechanisms for the development of green finance, we regard blockchain technology as an institutional technology and elevate it to the height of governance mechanisms. Using a dynamic stochastic general equilibrium (DSGE) model framework, we compare and analyze its effects with traditional supportive policies such as fiscal subsidies. The modeling simulation results show that the blockchain green finance platform model is conducive to better promoting the development of green finance. Subsequently, we construct a financial technology development index centered on blockchain technology and empirically test the impact of blockchain financial technology on the level of green finance development from both the supply and demand sides. The results show that the development of blockchain financial technology has significantly increased the scale of green credit issuance and effectively eased the financing constraints of green enterprises, reducing financing costs. We conduct an economic analysis of the impact of blockchain financial technology on the development of green finance, providing a feasible path for the integration and development of green finance and financial technology.

Food manufacturer willingness to employ blockchain technology system under the social Co-governance framework: China's situation

The blockchain technology system has gradually come to be employed in the food supply chain system, and it has emerged that the system offers the unique function of effectively curbing counterfeiting by food manufacturers. Unlike previous research on adoption by enterprises of new technology, this paper probes into the specific evolutionary routes of game subjects from the perspective of the precondition for enterprises' willingness to employ blockchain technology on the basis of China's social co-governance framework and by establishing a tripartite evolutionary game model of food manufacturer, government and consumer. The study then tests and verifies the stability conditions of equilibrium points and the relationship between these equilibrium points and the social co-governance level through numerical simulation analysis. On the above basis, the expected market proceeds of food producers employing blockchain technology and the influence of government and consumer behavior on enterprises' selection of a behavior strategy and the level of social co-governance are analyzed. The results show that every subject selects their own behavior strategy on the basis of the balance of their respective interests, and the final stability condition of the system is independent of their initial intentions. Rather, the expected sales volume of foods employing blockchain technology, governmental behavior (e.g., supervision, casual inspection, economic punishment, and fiscal subsidies), and complaints made by consumers constitute the main factors that influence food enterprises' selection of a behavior strategy. The level of social co-governance and the behavior of both government and consumers will ultimately be accomplished by influencing enterprises' expected economic returns, and the selection of an enterprise behavior strategy internally depends on the expected economic returns from producing foods employing blockchain technology. Therefore, this paper makes relevant proposals in an attempt to assist the Chinese government to better promote and popularize the blockchain technology system among food manufacturing enterprises.

Role of Incentives in the Use of Blockchain-Based Platforms for Sharing Sensitive Health Data: Experimental Study

BACKGROUND

Blockchain is an emerging technology that enables secure and decentralized approaches to reduce technical risks and governance challenges associated with sharing data. Although blockchain-based solutions have been suggested for sharing health information, it is still unclear whether a suitable incentive mechanism (intrinsic or extrinsic) can be identified to encourage individuals to share their sensitive data for research purposes.

OBJECTIVE

This study aimed to investigate how important extrinsic incentives are and what type of incentive is the best option in blockchain-based platforms designed for sharing sensitive health information.

METHODS

In this study, we conducted 3 experiments with 493 individuals to investigate the role of extrinsic incentives (ie, cryptocurrency, money, and recognition) in data sharing with research organizations.

RESULTS

The findings highlight that offering different incentives is insufficient to encourage individuals to use blockchain technology or to change their perceptions about the technology's premise for sharing sensitive health data. The results demonstrate that individuals still attribute serious risks to blockchain-based platforms. Privacy and security concerns, trust issues, lack of knowledge about the technology, lack of public acceptance, and lack of regulations are reported as top risks. In terms of attracting people to use blockchain-based platforms for data sharing in health care, we show that the effects of extrinsic motivations (cryptoincentives, money, and status) are significantly overshadowed by inhibitors to technology use.

CONCLUSIONS

We suggest that before emphasizing the use of various types of extrinsic incentives, the users must be educated about the capabilities and benefits offered by this technology. Thus, an essential first step for shifting from an institution-based data exchange to a patient-centric data exchange (using blockchain) is addressing technology inhibitors to promote patient-driven data access control. This study shows that extrinsic incentives alone are inadequate to change users' perceptions, increase their trust, or encourage them to use technology for sharing health data.

Comprehensive review for healthcare data quality challenges in blockchain technology

There are several features inherent in blockchain, including decentralized storage, distributed ledger, immutability, security and authentication, and it has shifted away from the hype to be used practically in different industries, such as in the healthcare sector. The use of blockchain technology has allowed the provision of improved services to industries. The objective of this paper is to demonstrate how the use of blockchain is influenced by data quality issues in the healthcare industry. The article is structured as a systematic literature review study that uses several articles issued in various databases from 2016 onwards. In this review study, 65 articles were chosen and grouped into a single key aspect of the challenge in the healthcare sector. The findings obtained were analyzed based on factors in three domains, classified as issues pertinent to the adoption, operational and technological domains. This review study aims to use the findings to provide support to the practitioners, stakeholders and professionals, whose purpose is to carry out and manage transformation projects pertinent to blockchain in the field of healthcare. In addition, the organizations would be facilitated in their decision-making processes when the potential blockchain users are made to comprehend the implicit factors related to blockchain.

Optimization of Digital Information Management of Financial Services Based on Artificial Intelligence in the Digital Financial Environment

At present, society has entered the era of digital finance, and the information management system (IMS) of financial services has been developing rapidly, so the security of data has become particularly important. Firstly, some security techniques in IMS of financial services are introduced. Secondly, this study analyzes how to combine secure muti-party computation with blockchain technology to enhance the security of IMS. Finally, the feasibility and reliability of the scheme are verified by a comparative test. The experimental results reveal that the evaluation index score of the optimized scheme is higher than that of the traditional scheme. Meanwhile, in the comparative experiment of information data encryption, it can be seen that the running time of all schemes will improve with the increase of data. However, the increase rate of the optimized model in this study is much slower than that of the traditional model.

Abstracting Data in Distributed Ledger Systems for Higher Level Analytics and Visualizations

By design, distributed ledger technologies persist low-level data, which makes conducting complex business analysis of the recorded operations challenging. Existing blockchain visualization and analytics tools such as block explorers tend to rely on this low-level data and complex interfacing to provide an enriched level of analytics. The ability to derive richer analytics could be improved through the availability of a higher level abstraction of the data. This article proposes an abstraction layer architecture that enables the design of high-level analytics of distributed ledger systems and the decentralized applications that run on top. Based on the analysis of existing initiatives and identification of the relevant user requirements, this work aims to establish key insights and specifications to improve the auditability and intuitiveness of distributed ledger systems by leveraging the development of future user interfaces. To illustrate the benefits offered by the proposed abstraction layer architecture, a regulated sector use case is explored.

Leveraging machine learning and blockchain in E-commerce and beyond: benefits, models, and application

Blockchain technology (BT) allows market participants to keep track of digital transactions without central recordkeeping. The features of blockchain, including decentralization, persistency, and attack resistance, allow data security and privacy. Machine learning (ML) involves the analytical platform on a massive amount of data to provide precise decisions. Since data reliability, integration, and data security are crucial in machine learning, the emergence of blockchain technology and machine learning has become a unique, most disruptive, and trending research in the last few years, achieving comparable and precise performance. The combination of blockchain and machine learning (BT–ML) has been applied across different applications to assist decision-makers in retrieving valuable data insights while preserving privacy and integration. This paper summarizes the state-of-the-art research in combing BT and ML in e-commerce and other various applications, including healthcare, smart transportation, and the Internet of Things (IoT). The challenges and benefits of integrating machine learning and blockchain technologies are outlined in the paper. We also discuss the advantages and limitations of current algorithms in the BT–ML integration. This paper provides a roadmap for researchers to pave the way for current and future research directions in combing the BT and ML research areas.

A review of advanced technologies available to improve the healthcare performance during COVID-19 pandemic

Information technology (IT) has enabled the initiation of an innovative healthcare system. An innovative healthcare system integrates new technologies such as cloud computing, the internet of things, and artificial intelligence (AI), to transform the healthcare to be more efficient, more convenient and more personalized. This review aims to identify the key technologies that will help to support an innovative healthcare system. A case study approach was used in this research analysis to enable a researcher to closely analyze the data in a particular context. It presents a case study of the coronavirus (COVID-19) as a means of exploring the use of advanced technologies in an innovative healthcare system to help address a worldwide health crisis. An innovative healthcare system can help to promote better patient self-management, reduce costs, relieve staff pressures, help with resource and knowledge management, and improve the patient experience. An innovative healthcare system can reduce the expense and time for research, and increase the overall efficacy of the research. Overall, this research identifies how innovative technologies can improve the performance of the healthcare system. Advanced technologies can assist with pandemic control and can help in the recognition of the virus, clinical treatment, medical protection, intelligent diagnosis, and outbreak analysis. The review provides an analysis of the future prospects of an innovative healthcare system.

Spatial distribution of startup (Gojek and Grab) users in Palembang city, Indonesia

The emergence of startups in Indonesia contributes to increasing the number of those working as startup users. Startup users define those who make use of startup services and enterprises to perform their business. This research was designed to explain the spatial distribution of startup (Gojek and Grab) users in Palembang City, Indonesia. It employed spatial analysis with inverse distance weighting and kernel density. The results indicated that startup (Gojek and Grab) users who established their business before 2020 were in densely-populated parts of the city. However, based on the interpolation of their business locations, they were variably distributed in lowly to densely-populated areas whose economic activities were dominated by trade and services. Furthermore, the nearest neighbor analysis revealed that startup (Gojek and Grab) users were close to permanent markets (including semi-permanent ones, supermarkets, restaurants, and grocery shops) and had better access to online transportation and communication with good cell phone receptions.

Securing federated learning with blockchain: a systematic literature review

Federated learning (FL) is a promising framework for distributed machine learning that trains models without sharing local data while protecting privacy. FL exploits the concept of collaborative learning and builds privacy-preserving models. Nevertheless, the integral features of FL are fraught with problems, such as the disclosure of private information, the unreliability of uploading model parameters to the server, the communication cost, etc. Blockchain, as a decentralized technology, is able to improve the performance of FL without requiring a centralized server and also solves the above problems. In this paper, a systematic literature review on the integration of Blockchain in federated learning was considered with the analysis of the existing FL problems that can be compensated. Through carefully screening, most relevant studies are included and research questions cover the potential security and privacy attacks in traditional federated learning that can be solved by blockchain as well as the characteristics of Blockchain-based FL. In addition, the latest Blockchain-based approaches to federated learning have been studied in-depth in terms of security and privacy, records and rewards, and verification and accountability. Furthermore, open issues related to the combination of Blockchain and FL are discussed. Finally, future research directions for the robust development of Blockchain-based FL systems are proposed.

Design of Enterprise Financial Information Fusion Sharing System Based on Blockchain Technology

In the process of global economic integration, the rapid development of various industries not only brings various opportunities but also presents new challenges to enterprises. With the continuous expansion of enterprise scale, more and more enterprises join the trend of international competition, and the internal system of enterprise group organization is complex, resulting in the weakening of the management and control ability of the enterprise itself and the decline of operating efficiency. In order to improve this situation, the fusion and sharing of financial information has become a necessary development strategy to optimize management, strengthen internal control systems, and improve business performance in the era of big data. Technology promotes the development of productivity, and with the continuous maturity of computer technology, blockchain technology comes into being. Blockchain technology is of great significance in promoting industrial transformation and technological innovation. The development of the new era should strengthen the basic research of blockchain and regard blockchain as an important breakthrough for independent innovation of core technologies. This work first analyzes the necessity and feasibility of applying blockchain technology to the enterprise financial information fusion and sharing system. Then, it specifically describes how the blockchain technology is applied to the enterprise financial information fusion and sharing system, and improves the enterprise financial information fusion and sharing system through the blockchain technology. This forms an enterprise financial information fusion and sharing system between companies, which improves the limitations and disadvantages of the current financial sharing platform. Finally, using the AHP to analyze and compare the indicators of the traditional financial sharing model and the financial information fusion sharing model under the blockchain technology, it is concluded that the blockchain technology brings positive changes to the enterprise financial information fusion sharing model.

Application and Optimization of Luenberger Observer Phase-Locked Loop and Inductance-Free Vector Control Method for Aviation Three-Phase Converter in Wearable Equipment

This work aims to strengthen the comprehensive performance of the Luenberger observer in the application of aviation three-phase converter and in physical exercise wearable devices to effectively detect human physiological signals. Firstly, the use status and characteristics of three-phase converters are discussed. Then, the Luenberger observer and its optimization process are described. Finally, the Luenberger observer is optimized through phase-locked loop technology and the vector control method. The experimental results indicate that the PLL of the steady-state linear Kalman filter is applicable to the multielectric aircraft converter for the aviation variable frequency power supply. The phase-locked loop of the steady-state linear Kalman filter is complicated, and the output angular frequency is inconsistent with the angular frequency of the actual voltage of the aircraft variable-frequency power supply. Consequently, it does not have the function of frequency locking. On the contrary, the Luenberger observer phase-locked loop designed here is suitable for the multielectric aircraft converter for the aircraft variable-frequency power supply. In addition, it is simpler than the steady-state linear Kalman filter phase-locked loop and realizes the frequency-locking function. In addition, the vector control method significantly improves the control performance of the Luenberger observer. The control error of the original observer is about 0.24°, and the control error of the optimized observer is about 0.18°. This work provides technical support for the performance optimization of the Luenberger observer and contributes to the performance improvement of the aviation three-phase converter.

Information Dissemination Model in Rural Live Broadcasting under Blockchain in the Era of Artificial Intelligence

This work aims to improve the information dissemination atmosphere of rural live broadcasting and ensure its long-term development. First, it studies and analyzes the current situation and characteristics of rural live broadcasting. Then, it discusses the blockchain (BC) technology and information dissemination mode in the era of artificial intelligence (AI). Finally, the characteristics of BC technology (BT) and the information dissemination model are discussed. A BT-optimized susceptible exposed infected recovered (SEIR) information dissemination model is proposed. The results show that the BT-optimized SEIR model has no effect on the traditional information transmission characteristics and can ensure the conventional transmission of all information. Additionally, BT can effectively improve the overall transmission efficiency of the SEIR model for false information and accurate information and effectively shorten the duration. Specifically, the BT-optimized SEIR model’s maximum false information transmission proportion is reduced by about 13%. The duration is reduced by 15 days over the traditional model. By comparison, in positive information dissemination, the maximum transmission proportion of the proposed BT-optimized SEIR model is about 19% higher than the traditional model. The duration is about 30 days longer. The research provides technical support for controlling and improving the current situation and atmosphere of rural live broadcasting information dissemination.

Blockchain Technology for Renewable Energy: Principles, Applications and Prospects

Blockchain, or distributed ledger, is an innovative technology that is emerging in various sectors and industries across the globe. It has attracted the attention of different interest groups such as energy companies, SMEs and start-ups, information technology developers, financial institutions, national authorities, and the university community. Through, for example, the decentralization of authority in transactions, Internet of Things (IoT) implementation, and smart contracting, the improvement of the daily business operations is firmly forecasted. In the energy sector, digitalization is already present in solutions such as smart grids, smart meters, electric vehicles, etc. Moreover, a new concept of the Internet of Energy (IoE) has been introduced in the academic literature. In this article, the level of trust and maturity of Blockchain technology implementation is investigated through the Blockchain Maturity Questionnaire, developed by the authors. The database consists of responses from upper management professionals from the renewable energy industry. The analysis reveals the state of know-how about Blockchain, the main benefits and bottlenecks associated with its implementation as well as willingness to integrate this technology in the case companies’ future operations. The insight from the industry experts helped to provide a “Roadmap for Blockchain Adoption” in future energy systems. This curiosity study yields numerous applications not only for the renewable energy industry experts but also for the interest groups coming from different industries, as well as public authorities and researchers scrutinizing the fields taken into its scope.

The Impact of Digital Economy of Resource-Based City on Carbon Emissions Trading by Blockchain Technology

To reduce the carbon emission intensity of resource-based cities and strengthen the sustainable development of these cities, firstly, blockchain technology is analyzed. Secondly, the development of the digital economy is discussed in digital resource-based cities. Finally, according to blockchain technology, a model of carbon emissions trading in the digital economy is designed, and the specific impact of the digital economy on carbon emissions trading is studied according to the model. The research results show that the mean value of the development index of the digital economy (digital) is -0.0168, the maximum value is 4.2560, the minimum value is -1.3429, and the standard deviation is 0.9572, indicating that the quality of digital economy development varies greatly among different regions. And according to the results of the digital model, it is found that the regression coefficient of the variable digital is significantly negative at the 1% level, showing that the digital economy will obviously suppress the carbon emission intensity of cities. After replacing the explained variables, the coefficient of the digital economy is still significantly negative. It indicates that the development of the digital economy can effectively suppress the carbon emission intensity of urban. Therefore, the designed model of carbon emissions trading under the blockchain technology can not only provide a secure platform for carbon emissions trading but also provide more comprehensive trading reference information for carbon emissions trading. It provides technical support for reducing the carbon emission intensity of resource-based cities and also contributes to the development of resource-based cities.

A Review of Blockchain in Fintech: Taxonomy, Challenges, and Future Directions

The primary purpose of this paper is to bridge the technology gap between Blockchain and Fintech applications. Blockchain technology is already being explored in a wide number of Fintech sectors. After creating a unique taxonomy for Fintech ecosystems, this paper outlines a number of implementation scenarios. For each of the industries in which blockchain is already in use and has established itself as a complementary technology to traditional systems, we give a taxonomy of use cases. In this procedure, we cover both public and private blockchains. Because it is still believed to be in its infancy, especially when it comes to financial use cases, blockchain has both positive and negative aspects. As a result, it is critical to be aware of all of the open research issues in this field. Our goal is to compile a list of open research challenges related to various aspects of the blockchain’s protocol and application layers. Finally, we will provide a clear understanding of the applications for which blockchain can be valuable, as well as the risks associated with its use in parallel.

Blockchain Hyperledger with Non-Linear Machine Learning: A Novel and Secure Educational Accreditation Registration and Distributed Ledger Preservation Architecture

This paper proposes a novel and secure blockchain hyperledger sawtooth-enabled consortium analytical model for smart educational accreditation credential evaluation. Indeed, candidate academic credentials are generated, verified, and validated by the universities and transmitted to the Higher Education Department (HED). The objective is to enable the procedure of credential verification and analyze tamper-proof forged records before validation. For this reason, we designed and created an accreditation analytical model to investigate individual collected credentials from universities and examine candidates’ records of credibility using machine learning techniques and maintain all these aspects of analysis and addresses in the distributed storage with a secure hash-encryption (SHA-256) blockchain consortium network, which runs on a peer-to-peer (P2P) structure. In this proposed analytical model, we deployed a blockchain distributed mechanism to investigate the examiner and analyst processes of accreditation credential protection and storage criteria, which are referred to as chaincodes or smart contracts. These chaincodes automate the distributed credential schedule, generation, verification, validation, and monitoring of the overall model nodes’ transactions. The chaincodes include candidate registration with the associated university (candidateReg()), certificate-related accreditation credentials update (CIssuanceTrans()), and every node’s transactions preservation in the immutable storage (ULedgerAV()) for further investigations. This model simulates the educational benchmark dataset. The result shows the merit of our model. Through extensive simulations, the blockchain-enabled analytical model provides robust performance in terms of credential management and accreditation credibility problems.

Design of Optimal Scheduling Model for Emergency Medical Supplies by Blockchain Technology

The study aims to explore the scheduling plan for the emergency of blockchain technology in the medical industry. Network security architecture for medical supplies management based on the Hyperledger Fabric optimized consensus mechanism is established by studying the characteristics of blockchain technology and its data structure composition. The supply chain model for medical device scheduling based on intelligent contracts is selected for the particularity of the nature and shape of medical devices in medical supplies. Ant colony algorithm is used to solve it. Case analysis and verification results show that the improved Hyperledger Fabric consensus mechanism has better security performance. Under the condition of 10,000 transactions, the probability of an attacker with the optimized consensus mechanism successfully controlling the transaction is only 7.2%. The optimized solution is about 50% higher than the original solution in terms of transaction processing speed. Over 1000 transactions, the transaction latency optimization rate is more than doubled. The total order completion time of the medical device scheduling model adopted by the intelligent contract is 26.3% higher than the historical service time of 19 days. The performance of the medical emergency material scheduling program that is added to the supply chain technology is better.

Blockchain Technology for Enhancing Traceability and Efficiency in Automobile Supply Chain—A Case Study

A robust traceability system would help organizations in inventory optimization reduce lead time and improve customer service and quality which further enables the organizations to be a leader in their industry sector. This research study analyzes the challenges faced by the automotive industry in its supply chain operations. Further, the traceability issues and waiting time at different nodes of the supply chain are considered to be priority issues that affect the overall supply chain efficiency in the automotive supply chain. After studying the existing blockchain architectures and their implementation methodology, this study proposes a new blockchain-based architecture to improve traceability and reduce waiting time for the automotive supply chain. A hyper ledger fabric-based blockchain architecture is developed to track the ownership transfers in inbound and outbound logistics. The simulation results of the proposed hyper ledger fabric-based blockchain architecture show that there is an improvement in the traceability of items at different nodes of the supply chain that enhances the Inventory Quality Ratio (IQR) and the mean waiting time is reduced at the factory, wholesaler, and retailer, which thereby improves the overall supply chain efficiency. The blockchain embedded supply chain is more capable to eliminate the risks and uncertainties associated with the automotive supply chain. The benefits of adopting blockchain technology in the automotive supply chain are also described. The developed blockchain-based framework is capable to get more visibility into goods movement and inventory status in automotive supply chains.

Health Is Wealth: Study on Consumer Preferences and the Willingness to Pay for Ecological Agricultural Product Traceability Technology: Evidence from Jiangxi Province China

The application of traceability technology is an important way to solve food safety problems. Different traceability technologies bring different effects to consumers. Existing studies have not explored consumers’ preferences in regards to product traceability technology applications, and they have not analyzed their willingness to pay. Therefore, this study focused on organic rice, an ecological agricultural product. The study was based on a survey from Jiangxi Province, China. It used a selective experiment method in order to analyze consumer preferences and the willingness to pay for ecological agricultural product traceability technology. The results show that consumer preferences are as follows: blockchain technology application attributes, traditional traceability-technology-application attributes, high credit-supervision attributes, and international-certification attributes. In terms of willingness to pay, consumers have the highest willingness to pay for the application of blockchain technology, which they are willing to pay CNY 21.902 more per kg for this attribute. At the same time, consumers are also willing to make additional payments for traditional traceability-technology-application attributes, high credit-supervision attributes, and international-certification attributes. Their willingness to pay is CNY 20.426, CNY 17.115 yuan, and CNY 11.049, respectively.

Critical Dimensions of Blockchain Technology Implementation in the Healthcare Industry: An Integrated Systems Management Approach

In the digital era, almost every system is connected to a digital platform to enhance efficiency. Although life is thus improved, security issues remain important, especially in the healthcare sector. The privacy and security of healthcare records is paramount; data leakage is socially unacceptable. Therefore, technology that protects data but does not compromise efficiency is essential. Blockchain technology has gained increasing attention as it ensures transparency, trust, privacy, and security. However, the critical factors affecting efficiency require further study. Here, we define the critical factors that affect blockchain implementation in the healthcare industry. We extracted such factors from the literature and from experts, then used interpretive structural modeling to define the interrelationships among these factors and classify them according to driving and dependence forces. This identified key drivers of the desired objectives. Regulatory clarity and governance (F2), immature technology (F3), high investment cost (F6), blockchain developers (F9), and trust among stakeholders (F12) are key factors to consider when seeking to implement blockchain technology in healthcare. Our analysis will allow managers to understand the requirements for successful implementation.

Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing

Smart manufacturing systems are growing based on the various requests for predicting the reliability and quality of equipment. Many machine learning techniques are being examined to that end. Another issue which considers an important part of industry is data security and management. To overcome the problems mentioned above, we applied the integrated methods of blockchain and machine learning to secure system transactions and handle a dataset to overcome the fake dataset. To manage and analyze the collected dataset, big data techniques were used. The blockchain system was implemented in the private Hyperledger Fabric platform. Similarly, the fault diagnosis prediction aspect was evaluated based on the hybrid prediction technique. The system’s quality control was evaluated based on non-linear machine learning techniques, which modeled that complex environment and found the true positive rate of the system’s quality control approach.

Analysis of challenges for blockchain adoption within the Indian public sector: an interpretive structural modelling approach

Purpose

Blockchain is one of the most significant emerging technologies that is set to transform many aspects of industry and society. However, it has several major technical, social, legal, environmental and ethical complexities that offer significant challenges for mainstream use within the public sector. The coronavirus disease 2019 (COVID-19) pandemic has compelled many public sector employees to work remotely, highlighting a number of challenges to blockchain adoption within the Indian context signifying the pertinence of this research topic in the post-pandemic era. This study offers insight to researchers and policymakers alike on how such challenges are interdependent within this important subject.

Design/methodology/approach

We explored 16 unique sets of challenges selected from the literature and gathered data from nine experts from government settings, healthcare and education sectors and academia who have significant knowledge and experience of blockchain implementation and use in their respective organisations. The implementation of Interpretive Structural Modelling (ISM) and Matriced' Impacts Croise's Multiplication Appliquée a UN Classement (MICMAC) provided a precise set of driving, linkage and dependent challenges that were used to formulate the framework.

Findings

The developed ISM framework is split into six different levels. The results suggest that the bottom level consists of challenges such as “Lack of standards (C9)” and “Lack of validation (C10)” form the foundation of the hierarchical structure of blockchain adoption. However, the topmost level consists of a highly dependent challenge termed “adoption of blockchain in the public sector (C16)”. The research filters the selected set of five challenges to develop a parsimonious model and formulated six propositions to examine the impact of “lack of standard (C9)”, “lack of validation (C10)” on “security issues (C3)” and “privacy concerns (C2)”, which eventually determine individuals' “reluctance to use blockchain technology (C12)”.

Originality/value

This research fills a key gap in exiting research by exploring the key challenges in blockchain adoption within the public sector by developing a valuable framework to model this important topic. To the best of our knowledge, this is the first paper to address these challenges and develop a parsimonious model for challenges of blockchain adoption in the public sector settings.

Modeling of the Bitcoin Volatility through Key Financial Environment Variables: An Application of Conditional Correlation MGARCH Models

Since the launch of Bitcoin, there has been a lot of controversy surrounding what asset class it is. Several authors recognize the potential of cryptocurrencies but also certain deviations with respect to the functions of a conventional currency. Instead, Bitcoin’s diversifying factor and its high return potential have generated the attention of portfolio managers. In this context, understanding how its volatility is explained is a critical element of investor decision-making. By modeling the volatility of classic assets, nonlinear models such as Generalized Autoregressive Conditional Heteroskedasticity (GARCH) offer suitable results. Therefore, taking GARCH(1,1) as a reference point, the main aim of this study is to model and assess the relationship between the Bitcoin volatility and key financial environment variables through a Conditional Correlation (CC) Multivariate GARCH (MGARCH) approach. For this, several commodities, exchange rates, stock market indices, and company stocks linked to cryptocurrencies have been tested. The results obtained show certain heterogeneity in the fit of the different variables, highlighting the uncorrelation with respect to traditional safe haven assets such as gold and oil. Focusing on the CC-MGARCH model, a better behavior of the dynamic conditional correlation is found compared to the constant.

A review of challenges and opportunities of blockchain adoption for operational excellence in the UK automotive industry

Purpose

This paper aims to explore the challenges and opportunities of blockchain technology adoption from the lens of the technological–organisational–environmental (TOE) framework for operational excellence in the UK automotive industry context.

Design/methodology/approach

The research methodology of this study follows a systematic review approach, which analyses existing academic published research papers in the top 35 academic journals. There was no specific timeframe established for this study and shortlisting the articles through a set of used keywords. A sample of 71 articles was shortlisted and analysed to provide a discussion on technological and management challenges and opportunities of blockchain adoption from the lens of the TOE framework for operational excellence.

Findings

The findings of this study present significant theoretical and managerial implications and deep understanding for firms seeking to understand the challenges and opportunities of blockchain adoption for their operational excellence.

Research limitations/implications

The systematic literature approach was considered for the present study to explore existing academic papers on technological and management challenges and opportunities from the lens of TOE framework for operational excellence, whereas a more specified method meta-analysis can be considered for future research. The study has been explored in the UK automotive industry context, which has been considered as the limitation of generalisation across countries and industries.

Originality/value

This paper represents the most comprehensive literature study related to the technological and management challenges and opportunities of blockchain from the TOE framework angle for operational excellence.

Dynamic Adaptive Cross-Chain Trading Mode for Multi-Microgrid Joint Operation

The emerging blockchain technology has injected new vitality into the energy market, especially the peer-to-peer power trading of microgrid systems. However, with the increase of energy blockchain projects, the difficulty of data communication and value islands between blockchain networks have become open issues. Thus, in this paper, we propose a dynamic adaptive cross-chain trading mode for multi-microgrid joint operation. The novelty is to design a proof of credit threshold consensus mechanism to achieve effective information verification. This consensus mechanism can ensure the adaptive consistency of cross-chain information without changing the existing blockchain architecture of each system. At the same time, we design a corresponding key management interoperability protocol based on RSA algorithm and Chinese remainder theorem, which can realize data transfer and information consensus for cross-chain transactions. The theoretical analysis verifies that the cross-chain communication information is effective and the system is able to protect against the attack of malicious nodes. Finally, a cross-chain simulation experiment is established to analyze the operation efficiency. The result shows that this cross-chain trading takes place within seconds, which basically meets the response requirements for multi-microgrid joint operation.