As global economic integration deepens, supply chain finance plays a crucial role in optimizing corporate cash flow and promoting the coordinated development of industrial chains. However, issues such as information asymmetry and credit assessment difficulties in traditional models have hindered its growth. Blockchain technology, with its decentralized nature, data immutability, and automated smart contracts, offers innovative solutions for credit risk management in supply chain finance. This article systematically analyzes the application logic, typical scenarios, and implementation effects of blockchain technology in credit risk management within supply chain finance. It also explores the technical bottlenecks, regulatory challenges, and coordination issues faced by the practical implementation of these technologies, and propose targeted optimization strategies. The aim is to provide theoretical support and practical references for the deep integration of blockchain technology with supply chain finance.
Rural and underprivileged areas continue to grapple with the availability of affordable and dependable healthcare funding.Community based health insurance mechanisms are rife with inefficiencies including long delays in claim processing, fraudulent reporting, lack of transparency, and weak guardrails.This paper suggests a smart village-focused blockchain-based system on community health insurance.The platform is built on top of permissioned blockchain, smart contracts, and decentralized identity management to secure policy issuance, transparent premium collection, automated claims settlement, and community-based network governance.A prototype was implemented based on Hyperledger Fabric with off-chain storage of medical data and a mobile app for rural access.A simulation study was implemented to evaluate the performance of the proposed framework on a synthetic claim data, which have shown to significantly decrease the claim processing time, increase the rate of fraud detection, and raise the trust perception by all the involved users.Contribution -The proposed study aims to contribute towards designing and implementing (blockchain-enabled) healthcare financing models to pave the way for the promotion of sustainable healthcare for equitable benefits in rural smart village ecosystems.
K. Nirmala Devi, Lakshmi Narasimha, N. Sujatha, Y. Geetha · 6 authors
The integration of blockchain technology into financial markets has sparked significant scholarly interest, particularly in the context of stock market prediction. This bibliometric analysis aims to provide a comprehensive overview of research trends, influential publications, and emerging themes within this interdisciplinary domain from 2018 to 2025. Drawing data from Scopus the study utilizes bibliometric tools such as Biblioshiny and VOSviewer to analyse publication outputs, citation patterns, co-authorship networks, and keyword co-occurrence. The findings reveal a consistent growth in academic contributions, especially after 2019, reflecting blockchain’s increasing relevance in financial prediction and its convergence with machine learning, deep learning, and artificial intelligence. Key research clusters identified include algorithmic trading, decentralized finance (DeFi), cryptographic modelling, and predictive analytics. The analysis also highlights leading journals, authors, and institutions contributing to the advancement of this field. However, certain limitations are acknowledged. The focus on selected databases may have excluded valuable contributions from platforms such as IEEE Xplore, SSRN, or non-indexed proceedings. Additionally, the keyword-based search strategy may have overlooked studies using alternative terminologies. The temporal scope may also bias the analysis toward recent developments while underrepresenting foundational research. The study offers a valuable reference point for scholars and practitioners, mapping the intellectual structure and thematic progression of blockchain-based stock prediction research. Future studies are encouraged to adopt multi-database approaches, combine quantitative and qualitative methods, and explore regulatory and regional variations to enrich understanding and guide practical implementation.
Against the backdrop of integrating the dual carbon strategy with the digital economy, retail enterprises' green supply chains face challenges such as difficult-to-trace carbon emission data, low efficiency in low-carbon collaboration, and imperfect green supplier certification mechanisms. This study leverages blockchain technology to empower retail enterprises, advancing their supply chains toward low-carbon and green development pathways. By utilizing distributed ledgers, it enables real-time sharing and traceability of carbon data across the entire chain, addressing issues of chaotic and distorted data collection. leveraging smart contracts to predefine emission reduction rules and allocate benefits, thereby balancing divergent objectives among supply chain participants to enhance collaborative efficiency; utilizing consensus mechanisms and immutability to establish a transparent, traceable green supplier certification and dynamic oversight system, tackling certification fraud and regulatory loopholes. This provides a feasible solution for the green and low-carbon transformation of retail enterprises, supporting their journey toward sustainable development.
Many industries, including banking, government, energy, healthcare, etc., have taken an interest in blockchain technology since its inception in the last decade. A comprehensive overview of blockchain's potential uses in the healthcare industry is provided in this article. Research in this field is indeed progressing at a breakneck pace. Thus, we have discovered several cutting-edge applications of blockchain technology, such as medicine supply chain management, electronic medical record sharing, remote patient monitoring, etc. We have also highlighted the shortcomings of the methods that have been examined, and we have wrapped off by delving into some unanswered questions and potential spots for more study. The new Internet of Things applications in Industry 4.0 include blockchain technology, which is immutable, cryptographically secure, distributed ledgers, and a component of decentralized systems. Various entities or parties maintain and distribute exact copies of a succession of transaction lists using this technology. Blockchain technology's capacity to link disparate systems and improve the accuracy of electronic health data, together with a patient-centric approach to healthcare, make it an area with enormous promise.
Under the wave of digital transformation, traditional accounting processes face challenges in audit risk control. Blockchain technology, with its unique advantages, offers a new approach to addressing this issue. Through case studies, this paper conducts an in-depth exploration of the application value of blockchain in accounting processes from the perspective of audit risk assessment. It provides a detailed analysis of the advantages and disadvantages. At the same time, by understanding the definitions, relationships, and differences between accounting and auditing, and by examining the traditional accounting process, it is found that there are audit risks in terms of information accuracy and completeness. By comparing and analyzing the distributed ledger feature of blockchain technology, it can be seen that the application of blockchain technology enhances the confidentiality of information. Research also shows that the application of blockchain technology in accounting processes can significantly enhance the credibility and authenticity of audit evidence, reduce audit inspection risks, and better assist auditors in identifying problems in accounting. The main research results of this paper are to explore the application value of blockchain technology in accounting processes from the perspective of audit risk assessment, thereby better addressing the drawbacks of traditional accounting processes.
The emergence of the metaverse has opened up new possibilities for businesses, entrepreneurs, and consumers, reshaping the way industries operate and interact with their audiences. As the virtual world expands, new business opportunities have emerged, allowing entrepreneurs to create innovative products, services, and experiences in entirely digital spaces. However, the potential of the metaverse for entrepreneurship remains underexplored. This research aims to examine how the metaverse offers new business opportunities and challenges for entrepreneurs in various sectors. The study utilizes a qualitative research design, conducting in-depth interviews with entrepreneurs and industry experts who are actively engaging with the metaverse. Data was gathered through semi-structured interviews and analyzed thematically to identify key trends, business models, and challenges faced by startups in virtual environments. The findings reveal that the metaverse provides entrepreneurs with access to a global market, greater consumer engagement, and new forms of monetization through virtual goods and services. However, challenges such as technical barriers, user adoption, and regulatory concerns persist. Entrepreneurs leveraging the metaverse tend to adopt business models that include virtual real estate development, NFTs (non-fungible tokens), and immersive experiences. In conclusion, the metaverse presents significant business opportunities, but entrepreneurs must navigate various challenges related to technology, market dynamics, and consumer behavior.
Weiming Xie, Zhaomin Yao, Xiaozhou Bai, Lang Mai · 10 authors
Nowadays, the global digital transformation of healthcare is advancing rapidly with the help of technologies such as electronic medical records, telemedicine, and mobile medical applications. However, there are still challenges in EMR interoperability, security, and data exchange. To address these existing limitations, This study proposes a voice electronic medical record system driven by artificial intelligence and blockchain, which is designed to improve clinical records and nursing coordination. This system adopts a dedicated deep learning architecture. It transcribe the conversations between doctors and patients into text, and then uses natural language processing to extract the relevant medical information. At the same time, it also provides diagnostic prompts, which can reduce the risk of misdiagnosis. Doctors can view and edit these summaries generated by artificial intelligence. Then safely record them on the decentralized crypto blockchain ledger. With federated learning, the model can be continuously improved in multiple centers without infringing on data privacy. This solution integrates automatic speech recognition, distributed ledger technology, and collaborative deep learning, aiming to enhance the EMR efficiency, security, data integrity, and care continuity of medical institutions. The combination of blockchain technology and artificial intelligence technology holds great potential. It can transform fragmented health data into portable and interoperable records under patient control, thus bringing strategic advantages to the health system that is undergoing a comprehensive digital transformation.
This study investigates the application of blockchain technology in cross-regional agricultural product traceability platforms to address challenges such as information silos, data tampering risks, and inefficient regulatory coordination in traditional systems. Using blockchain's distributed ledger, smart contracts, and consensus algorithms, a framework is proposed to boost transparency, collaboration, and data security. Pilot case analysis in East China shows production data completeness improved from 72.4% to 98.6%, logistics real-time update rate reached 95.3%, cross-regional collaboration time reduced by 81.3%, data tampering incidents dropped by 96.7%, and quality safety incidents fell by 77.9%. The integration of cross-chain technology, multi-center collaboration mechanisms, and privacy protection techniques further ensures end-to-end traceability and stakeholder trust. Results highlight blockchain's potential to foster a secure, transparent, and efficient agricultural supply chain for cross-regional circulation.
Medical big data holds significant value in promoting precision medicine, disease prediction, and public health management. However, issues such as sensitivity, decentralization, and privacy security limit its in-depth application. This study proposes a collaborative computing framework based on blockchain and Apache Spark, aiming to address the challenges of privacy protection, cross-institutional sharing, and efficient analysis of medical data. By designing an access control mechanism based on smart contracts and an anonymization scheme utilizing zero-knowledge proofs, combined with Spark's distributed memory computing advantages, a secure and trustworthy platform for medical data analysis is constructed. Experiments demonstrate that this framework improves data processing efficiency by 3.5 times compared to the traditional Hadoop architecture on the MIMIC-III dataset, while also meeting HIPAA privacy standards. This study provides theoretical support and practical pathways for the application of "blockchain + big data" technology in the medical field.
With the increasingly turbulent political situation and the outbreak of public health events without warning, it will not only affect people’s physical health, but also affect the global financial market, causing the market to fall into a huge crisis, thus leading to a continued decline in the worldwide economy. During periods of financial market turmoil, many investors fall into panic and urgently need a “haven” to protect their assets. With the rise of the digital economy, gold no longer seems to be the only safe-haven option. Bitcoin has gradually entered the investors’ field of vision. Some investors believe that Bitcoin can become an emerging safe-haven asset that is as important as or surpasses gold. Based on an analysis of the safe-haven properties of Bitcoin and gold during major political and historical events and public health events, this article will clarify which of the two is more suitable as a reliable contemporary safe-haven asset and provide advice to investors.
Atish Peshattiwar, A. P. Mohanraj, Anand Gerald A, Dharmalingam S · 6 authors
Blockchain Technology in Supply Chain Management Blockchain can help scale to preparedness and enhance scalability, transparency, interoperability, security, and cost-efficiency. Existing implementations are facing significant challenges, such as considerable computational expense, scalability constraints, issues with interoperability, energy waste, and regulatory compliance. In response, this research presents a next-gen blockchain framework leveraging hybrid blockchain architectures, AI-integrated smart contracts, green consensus algorithms, and cross-platform interoperability strategies to bridge the gaps of the existing systems. In this paper, we present an architecture that incorporates Zero-Knowledge Proofs (ZKP), Homomorphic Encryption, and Decentralized Identifiers (DIDs) for upholding data transparency and privacy without compromising on regulatory compliance. Furthermore, in order to facilitate the cost-effective adoption of blockchain for supply chain firms, the study presented BaaS (Blockchain-as-a-Service). AI-powered adaptive smart contracts to automate logistics operations in real-time are also included in the framework. This research proves that the proposed blockchain framework helps to increase the supply chain security level, decrease operational costs, improve transaction efficiency, and conformity with the regulations of global trade through the case study analysis and simulation testing approaches. The outcome indicates the comparative analysis demonstrating the improvement– a 40% reduction in latency, a 30% decrease in computational costs, and a 50% higher transaction processing speed compared to the existing blockchain technologies with respect to hybrid blockchain model. This research addresses major roadblocks to significant adoption of blockchain, and provides a robust, cost-efficient, and privacy-protective, scalable blockchain solution which can guarantee resilience and transparency of supply chain in current-day logistics networks.
Jamil Raja, D Hema Ruba, Sai Krishna, K Manasa · 6 authors
Blockchain technology has become a disruptive force that is quickly reshaping supply chain management by providing greater transparency, security, and efficiency. As promising as the Blockchain is, previous research fails to provide solutions for bringing Blockchain into real-world practice, for getting it up to mass scale, and for ensuring that it meets the regulators’ requirements and these factors limit a more widespread adoption of Blockchain. By offering a review of blockchain-based supply chain management initiatives, their pros and cons, and addressing under-researched topics related to optimized consensus mechanisms, interoperability solutions, and AI-driven solutions integration, this research fills the gaps to decrease inefficiencies in supply chains. As part of the latter, the study presents zero-knowledge proofs, decentralized identity verification and cross-chain protocols as potential solutions to address security concerns and enhance interoperability among multiple chains. Also, a deeper implementation roadmap is provided, enabling pragmatic applicability in real business operations across the global supply chain. By analyzing cases, the study emphasizes the practical contributions of blockchain in traceability, fraud prevention, inventory optimization, and automated contract execution. The results highlight blockchain as a scalable, secure, and legally compliant technology for solving modern supply chain problems, filling the gap between theory and practical adoption.
With the government’s emphasis on the blockchain and supply chain industry and increased policy support, the field shows a bright future. Nonetheless, the traditional supply chain finance model faces numerous challenges. This paper aims to explore how blockchain technology can be utilized to mitigate and control credit risk in supply chain finance. It will also detail the principles and characteristics of blockchain technology, including its decentralized architecture, encryption algorithms, resistance to tampering, smart contract functionalities, and more. At the same time, this paper will also analyse the shortcomings of traditional supply chain finance. Distributed ledger technology is utilized through blockchain to ensure the transparency and traceability of information, while smart contracts optimize the credit execution and supervision process, playing a key role in preventing and controlling credit risks. The article concludes by proposing innovative strategies based on blockchain technology, including constructing a credit information sharing platform, improving the credit assessment model, and establishing a risk early warning and monitoring system, with the aim of improving the efficiency and credit level of supply chain management and further promoting the healthy development of supply chain finance.
Michael Olumuyiwa Adesuyi, Olawole Akomolafe, Babajide Oluwaseun Olaogun, Victor Ukara Ndukwe · 5 authors
The global payment infrastructure faces unprecedented challenges from escalating geopolitical tensions, economic sanctions, cyber warfare, and technological disruptions that threaten the stability and continuity of cross-border financial transactions. This study presents a comprehensive resilience and continuity model designed to enhance the robustness of global payment systems against geopolitical risks while maintaining operational efficiency and regulatory compliance. Through systematic analysis of existing payment infrastructure vulnerabilities and emerging risk factors, this research develops a multi-layered framework incorporating distributed ledger technologies, artificial intelligence-driven risk assessment, and adaptive governance mechanisms to ensure payment system continuity during geopolitical crises. The proposed model integrates blockchain-based interoperability protocols, real-time threat intelligence systems, and dynamic routing algorithms that enable automatic rerouting of payment flows when traditional channels are compromised. Key innovations include a geopolitical risk scoring system that continuously monitors political stability indicators, regulatory changes, and sanctions regimes across jurisdictions, providing early warning capabilities for payment service providers. The framework also incorporates federated learning approaches for cross-border fraud detection while preserving data sovereignty requirements mandated by different regulatory jurisdictions. Implementation analysis reveals that the proposed resilience model can reduce payment disruption incidents by 67% during moderate geopolitical tensions and maintain 85% operational capacity even during severe international crises. The system's adaptive architecture enables real-time reconfiguration of payment routes based on geopolitical risk assessments, ensuring compliance with evolving sanctions regimes while minimizing transaction delays. Cost-benefit analysis demonstrates that implementing this resilience framework reduces operational losses from payment disruptions by approximately $2.4 billion annually across major financial institutions. The research methodology employed mixed-methods approaches, combining quantitative analysis of historical payment disruption data from 2015-2024 with qualitative assessment of expert opinions from central banks, payment processors, and fintech institutions across 15 countries. Validation testing using Monte Carlo simulations and stress testing scenarios confirms the model's effectiveness in maintaining payment continuity under various geopolitical crisis scenarios including trade wars, financial sanctions, and regional conflicts. This study contributes to the literature by providing the first comprehensive framework specifically designed to address geopolitical risks in global payment infrastructure, offering practical implementation guidelines for financial institutions, central banks, and payment service providers seeking to enhance their operational resilience in an increasingly volatile geopolitical environment.
This study conducts a performance evaluation of a blockchain-based Human Resource Management System (HRMS) utilizing smart contracts to enhance organizational efficiency and scalability. Despite blockchain’s transformative potential through decentralization, transparency, and immutability, empirical research on its scalability for large-scale HRMS applications remains limited. This research addresses this gap by designing, implementing, and testing a blockchain-based HRMS prototype with a simulated dataset of 5000 users across five core HR modules: recruitment, employee management, payroll, leave, and exit/retirement. Leveraging the Ethereum development network, Solidity for smart contract development, and Hyperledger Caliper for performance benchmarking, the study evaluates transaction latency and throughput under escalating transaction loads (5 to 5000 transactions). Results demonstrate exceptional scalability, with consistently low average latency (0.07 - 2.11 seconds) and high throughput (2.4 - 78.1 TPS), affirming the system’s robustness for high-volume HR operations. The findings provide evidence-based insights and recommendations for designing scalable blockchain solutions, contributing to advanced HR practices and organizational performance optimization.
T A Mohanaprakash, Ranganayaki V.C, M. S. Minu, D. A. · 5 authors
Many have long aimed to create a safe electronic voting system that maintains the confidentiality and integrity of traditional voting methods while using the convenience and openness of modern technology. Ballot paper or electronic voting machines are the current voting schemes in every nation, and democratic voting is a significant event in every country. Problems with these procedures abound, including lack of openness, poor voter turnout, vote manipulation, mistrust of the election body, forgery of unique identification (voter ID card), delays in disseminating results, and, most importantly, security breaches. Prioritizing the security of digital voting is of utmost importance when contemplating implementing a digital voting system. The article assesses the objective of building a blockchain-based e-voting system [BC-E-VOT] that uses digital voting technology. Electronic voting methods that leverage the distributed ledger attract much attention because they can make digital voting more transparent, secure, and honest. As shown in this research, a successful strategy for electronic voting may be achieved by using Blockchain's cryptographic underpinnings and transparency. Due to its complete transparency, the suggested approach satisfies the essential criteria for electronic voting systems. Since Blockchain employs a decentralized mechanism for data storage rather than storing all of the data in one central place, it becomes challenging to tamper with the data when utilizing this technology to build a decentralized application. By creating a decentralized system using the WSN platform, a third party is no longer needed to oversee the election's access control. This article provides a system for electronic voting that guarantees privacy, trustworthiness, and security. The suggested approach is practical and secure, according to the findings.
This study aims to examine the function of blockchain technology to detect fraud in health insurance. we consider the literature on fraud in health insurance, blockchain, and smart contracts to to test a newly structured software system based on blockchain technology for this purpose. Different blockchain platforms, consensus algorithms, and structures have been used to pick the proposed system’s best structure based on blockchain. Eventually, the best techniques to put the system to the test and evaluate the findings were assessed. we propose a standardized system, where blockchain is applied to store data and smart contracts are used to automate insurance policies. Furthermore, a web-based application, which acts as core insurance software, is proposed for all stakeholders to communicate with the blockchain and smart contracts. Therefore, the proposed system comprises a blockchain, web app, and standardized smart contracts. The proposed system mainly focuses on fraud detection in insurance claims while maintaining a standard data storage and transfer structure. The system proved to be thriving once claim data can be created, read, and analyzed (i.e. fraudulent data are caught) effectively in a standard way. The web app consists of a front-end and back-end section. The front-end enables users to interact with the proposed system, and the back-end allows the insurance company to store records on the blockchain and increase the chances of detecting fraud in insurance claims, especially Digital Insurance Claims. Finally, a blockchain-based web application that can be used as core insurance software for any health insurance company is proposed.
In the era of sharing economy, the tourism market is increasingly characterized by personalized demand, mobile consumption and product segmentation. This paper aims to apply big data mining technology in the field of smart tourism. Firstly, it focuses on image summary selection and collaborative filtering technology based on big data mining. It then demonstrates the integration of blockchain in smart tourism, emphasizing the use of decentralized structures and smart contracts to achieve data security and transparency, and describes the testing process of smart tourism platforms, including data preparation and platform operational efficiency testing. Finally, the research results of this paper are summarized, and the development potential and practical application value of smart tourism are demonstrated. The results show that in the smart tourism big data mining model, the minimum support for the data set is 10 % and 20 %, respectively. Moreover, with the increase of the number of nodes in the same data set, the running time decreases gradually. It can be seen that smart tourism big data mining has strong scalability.
The financing of innovative entrepreneurial projects within colleges and universities presents a unique challenge due to the inherent risks associated with nascent ideas and the limitations of traditional funding channels. Blockchain technology, with its decentralized architecture and transparent ledger system, offers a promising solution to these challenges. By leveraging blockchain, academic institutions can enhance the efficiency, transparency, and accessibility of the financing process for entrepreneurial ventures. This paper explores the application of blockchain technology in the financing model of university-based entrepreneurial projects, examining its potential benefits, challenges, and implications. Through a comprehensive review of literature, case studies, and theoretical frameworks, we elucidate the mechanisms through which blockchain can facilitate funding, foster collaboration among stakeholders, and democratize access to capital. Moreover, we discuss the unique characteristics of blockchain technology and its alignment with the values and objectives of academic entrepreneurship. While blockchain holds immense potential to transform the financing landscape, its adoption also presents regulatory, scalability, and governance challenges that require careful consideration. By contributing to the discourse on blockchain, entrepreneurship, and academia, this paper aims to inform policymakers, educators, and entrepreneurs about the transformative potential of blockchain in shaping the future of innovation and education.
In the tourism industry, big data has emerged as a revolutionizing the way businesses operate and travelers experience destinations. With the vast amount of data generated from online bookings, social media interactions, and mobile applications, tourism companies can gain valuable insights into traveler preferences, behavior patterns, and market trends. This paper proposes a development strategy for the tourism industry in the post-epidemic situation, leveraging network big data analysis with Multi-Factor Hashing Ethereum Classification (MFH-EC). By harnessing the power of network big data, this strategy aims to provide insights into changing traveler preferences, market dynamics, and risk factors in the wake of the pandemic. The MFH-EC model facilitates the classification and analysis of diverse factors influencing tourism development, including economic indicators, health and safety measures, environmental conditions, and traveler sentiment. Through simulated experiments and empirical validations, the effectiveness of the proposed strategy is assessed, demonstrating significant improvements in predictive accuracy and decision-making capabilities. For instance, the MFH-EC model achieved an 80% accuracy rate in predicting tourism demand shifts and a 30% reduction in forecasting errors compared to traditional methods. These results underscore the potential of network big data analysis with MFH-EC in guiding strategic decision-making and fostering sustainable recovery and growth in the tourism industry post-epidemic.