In todayâs fast changing digital world, the need for secure, transparent, and reliable financial transactions is more important than ever especially in areas where fraud, delays, and unauthorized access are common concerns. Traditional payment systems often depend on centralized middlemen, which can lead to slow processing, high fees, and risks of data tampering or cyberattacks. This work introduces an automated payment processing system powered by blockchain technology, designed to make digital transactions faster, safer, and more trustworthy without relying on third parties. The motivation for this system came from real-world frustrations with issues like payment fraud, slow transactions, and the lack of visibility in how money moves within traditional financial systems. To build this system effectively, the Structured Systems Analysis and Design Methodology (SSADM) was adopted. This method provides a clear, step-bystep approach for understanding problems and creating effective systems. With blockchain at its core, the system will support real-time transaction validation, ensure that data canât be altered, reduce costs, and remove central points of failure. Overall, it aims to build user confidence and create a more resilient payment infrastructure. By solving key problems found in conventional systems, this project hopes to contribute to the next generation of secure, scalable, and efficient financial technologies for businesses and organizations.
Abstract This study explores the transformative impact of artificial intelligence (AI) on enhancing demand forecasting and procurement efficiency within health commodity supply chains. It highlights the integration of advanced AI algorithms, including machine learning (ML), natural language processing (NLP) and optimisation techniques, which facilitate more accurate predictions, streamlined sourcing and improved inventory management. The analysis emphasises the essential interplay between technological innovation and ethical practices, underlining the importance of data privacy, transparency, fairness and accountability as foundational elements for trustworthy AI deployment in healthcare procurement. Implementation strategies take into account infrastructure requirements, change management and potential barriers to adoption. The investigation further examines organisational and workforce implications, scalability, sustainability and comparative experiences on both global and local scales, illustrating the complex challenges and opportunities presented by AI in health commodity procurement. Future directions suggest the convergence of AI with Internet of Things, blockchain and cloud computing, advocating for responsible innovation that adheres to ethical standards to optimise supply chain resilience, equity and operational performance in healthcare delivery.
Supply Chain Resilience and Risk Management
Artificial Intelligence in Healthcare and Education
The study aimed to investigate the perceived application of Blockchain technology among accountants, auditors, bankers, and other related professionals in Iraq and the statistical association between this perceived application and financial-information reliability, based on respondentsâ perceptions of financial-information reliability. The study was designed as a field study using a five-point Likert scale. The analysis was based on 150 valid responses. Blockchain application was measured using ten items, and financial information reliability was measured using another ten items. Cronbach's alpha coefficient, descriptive statistics, Pearson and Spearman correlation coefficients, and simple linear regression were used. The results of the Blockchain scale showed acceptable internal consistency (Îą = 0.775), while the financial information reliability scale showed very high internal consistency (Îą = 0.989). The mean scores were 4.232 and 4.221, respectively. Pearson's correlation coefficient was positive but not statistically significant (r = 0.146, p = 0.076), and the regression model was also not statistically significant (R² = 0.021, F(1, 148) = 3.203, p = 0.076). The results indicate positive perceptions of Blockchain technology and the reliability of financial information. However, the current data do not provide sufficient evidence at the 5% significance level that perceived Blockchain application is statistically significantly associated with financial-information reliability.
The content should be logically organized in a single paragraph, maintaining coherence and clarity throughout. Ensure that the abstract captures the research context, problem statement, approach, key results, and final conclusions in a balanced manner. It should provide enough detail to help readers quickly understand the scope and value of the study while encouraging them to read the full paper. The recommended length is between 150 and 250 words; however, it may extend up to 500 words if necessary to clearly communicate the research objectives, methods, findings, and significance. Keywordsâ Sustainable Logistics; Green Supply Chain Management; Artificial Intelligence; Smart Transportation; Digital Twins; Blockchain; Energy-Efficient Logistics; Quantum Computing; Supply Chain Resilience; FKF Analysis.
This study introduces an FKF-enabled intelligent supply-chain framework that integrates Artificial Intelligence (AI), Blockchain, Internet of Things (IoT), Digital Twins, and quantum optimization into a unified architecture. The FKF transform provides a mathematical spectral representation of supply-chain signals, enabling the identification of temporal shifts, modulation effects, multiscale patterns, demand fluctuations, and lead-time dynamics. These spectral features can be supplied to AI and machine-learning models to improve forecasting, anomaly detection, disruption prediction, and resilience assessment. IoT devices continuously provide real-time operational data from transportation, inventory, production, and logistics processes, while Blockchain supports secure data sharing, traceability, and transaction transparency across supply-chain participants. Digital Twins complement these technologies by creating dynamic virtual representations of physical supply-chain systems, allowing alternative scenarios, disruptions, and recovery strategies to be simulated before implementation. Quantum annealing is incorporated to address selected computationally intensive combinatorial decisions, such as routing, scheduling, resource allocation, and logistics configuration. By connecting FKF-based mathematical spectral intelligence with AI-driven analytics, trusted digital infrastructure, simulation capabilities, and emerging quantum optimization, the proposed framework provides an integrated pathway toward more predictive, adaptive, transparent, sustainable, and resilient supply-chain management. The content should be logically organized in a single paragraph, maintaining coherence and clarity throughout. Ensure that the abstract captures the research context, problem statement, approach, key results, and final conclusions in a balanced manner. Keywordsâ Quantum Computing; Quantum Annealing; Logistics Optimization; Unit Load Device Configuration; Supply Chain Management; Artificial Intelligence; Digital Twins; Blockchain; Supply Chain Resilience; FKF Transform.
Purpose This study investigates to investigate the main determinants of financial service industry adoption blockchain technology and their impact on financial transparency and efficiency. In particular, the paper looks at how technological readiness, organizational control and supporting regulations enable blockchain use among financial institutions working in the banks of Jordanian banking sector. Design/methodology/approach A quantitative research design based on a structured questionnaire was employed, which was distributed throughout Jordanian banks to senior and middle-level management. Responses were collected from senior executives, heads of divisions, IT managers and branch managers who are involved in both the financial and technological decision-making processes. SmartPLS was used to conduct Partial Least Squares Structure Equation Modeling (PLS-SEM) analysis using SmartPLS on 192 valid responses to check the measurement model and test the theorized relationships in proposed research framework. Results Results show that technological readiness, organizational governance and regulatory support play an important role in encouraging blockchain technology uptake by financial services. Furthermore, financial institutions adopting blockchain update general ledger journal records in an interactive way which is positively associated with the degree to which financial transparency and operational efficiency are attained. This underscores the part played by technological capabilities as well as governance frameworks and regulatory contexts in encouraging successful blockchain adoption while helping to improve institutional performance. Originality/value In articulating a new frame of analysis from a TOE perspective that takes into account technological, organizational, and environmental factors together, the paper contributes to an emerging literature on adoption of blockchain by financial services. Moreover, it carries out an empirical examination of the performance effects associated with introducing blockchain technology into the banks of Jordan the country which is focused on enhancing financial transparency and operational efficiency. JEL classification G32; K22; O16; L60.
Educational Leadership is a dynamic and strategic process through which educational institutions are guided toward achieving academic excellence, organizational effectiveness, innovation, and sustainable development. It encompasses the vision, values, competencies, and decision-making capabilities required to inspire individuals, manage institutional resources, promote continuous improvement, and respond effectively to the rapidly changing educational landscape. In contemporary higher education, leadership extends beyond administrative responsibilities to include fostering research excellence, encouraging innovation, strengthening institutional governance, supporting digital transformation, and creating inclusive learning environments. In the era of Artificial Intelligence (AI), Industry 5.0, globalization, and the knowledge economy, Educational Leadership has become an indispensable component of institutional success, enabling universities and colleges to prepare graduates who are capable of addressing complex societal, technological, and economic challenges.The primary objective of Educational Leadership is to establish a shared vision that promotes quality education, ethical governance, academic innovation, research excellence, student success, and institutional sustainability. Educational leaders guide faculty members, administrative staff, students, researchers, industry partners, policymakers, and community stakeholders toward achieving common institutional goals while fostering a culture of collaboration, accountability, creativity, and lifelong learning. Effective leadership ensures that educational institutions remain responsive to emerging technologies, evolving labour market requirements, societal expectations, and global educational standards.Artificial Intelligence has significantly transformed Educational Leadership by providing intelligent tools that support strategic decision-making, institutional planning, academic administration, and educational innovation. AI-powered analytics enable leaders to monitor student performance, faculty productivity, research outcomes, institutional rankings, financial management, and operational efficiency through real-time data analysis. Predictive analytics assist in identifying students at risk of academic failure, forecasting enrolment trends, optimizing resource allocation, and supporting evidence-based policy formulation. Natural language processing and intelligent virtual assistants further improve communication, administrative efficiency, and stakeholder engagement while reducing routine workloads and enabling leaders to focus on strategic institutional development.Digital transformation has fundamentally reshaped Educational Leadership by integrating advanced digital technologies into institutional governance, teaching, research, and administrative management. Cloud computing, digital learning management systems, enterprise resource planning platforms, institutional dashboards, virtual collaboration environments, blockchain-based credential management, and research information systems enable educational leaders to coordinate academic and administrative activities efficiently. Digital technologies also facilitate transparent governance, real-time communication, remote leadership, data-driven decision-making, and continuous quality assurance, thereby enhancing institutional effectiveness and resilience.Leadership in higher education increasingly requires interdisciplinary thinking and collaborative problem-solving because universities operate within complex educational, technological, social, and economic ecosystems. Educational leaders must integrate expertise from education, management, technology, finance, law, psychology, sociology, and public policy to address institutional challenges effectively. Interdisciplinary leadership promotes innovation by encouraging collaboration among diverse academic departments, research centres, industries, governments, and international organizations. Such collaborative approaches strengthen institutional capacity while supporting the development of comprehensive solutions to emerging educational and societal issues.Educational Leadership plays a critical role in promoting academic excellence by establishing policies that support high-quality teaching, research, innovation, curriculum development, faculty development, and student engagement. Leaders encourage the adoption of learner-centred pedagogies, technology-enhanced education, interdisciplinary programmes, competency-based learning, research-integrated teaching, and continuous professional development. By fostering supportive academic cultures characterized by intellectual curiosity, creativity, inclusiveness, and ethical responsibility, educational leaders create environments where students and educators can achieve their full potential.Research and innovation are central responsibilities of Educational Leadership within higher education institutions. University leaders establish research priorities, strengthen research infrastructure, secure funding opportunities, promote interdisciplinary collaboration, encourage international partnerships, and support technology commercialization. They create environments that foster scientific inquiry, entrepreneurial thinking, knowledge transfer, and responsible innovation while ensuring that research activities contribute to sustainable development, economic competitiveness, and societal well-being. Leadership in research management also involves maintaining ethical standards, promoting transparency, and ensuring responsible use of emerging technologies such as Artificial Intelligence.Student development remains a fundamental focus of Educational Leadership. Leaders design institutional policies that support academic achievement, personal development, mental well-being, employability, leadership skills, entrepreneurial competencies, and lifelong learning. Student support services, career guidance, mentoring programmes, counselling centres, digital learning resources, and inclusive educational practices contribute to holistic student development while ensuring equitable access to educational opportunities for learners from diverse backgrounds.Internationalization has become an increasingly important dimension of Educational Leadership. Institutional leaders establish strategic partnerships with universities, industries, research organizations, governments, and international agencies to strengthen academic collaboration, student and faculty mobility, joint research initiatives, and global learning opportunities. Such international engagement enhances institutional reputation, improves educational quality, strengthens cultural diversity, and prepares graduates to function effectively in multicultural and globally interconnected professional environments.Ethical leadership forms the moral foundation of Educational Leadership by emphasizing integrity, transparency, accountability, fairness, inclusiveness, and social responsibility. Educational leaders establish governance systems that promote ethical decision-making, academic integrity, responsible use of Artificial Intelligence, protection of intellectual property, equitable resource allocation, and respect for diversity. Ethical leadership also encourages open communication, participatory governance, conflict resolution, and responsible stewardship of institutional resources while strengthening stakeholder trust and organizational credibility.Sustainability has become an essential priority within Educational Leadership as higher education institutions increasingly align their missions with the United Nations Sustainable Development Goals (SDGs). Educational leaders integrate sustainability into institutional policies, curriculum development, research agendas, campus operations, community engagement, and strategic planning. Universities promote renewable energy initiatives, environmental conservation, responsible resource management, inclusive education, climate resilience, public health, social equity, and sustainable innovation through visionary leadership and collaborative governance.Assessment and quality assurance constitute important responsibilities of Educational Leadership. Leaders establish systems that continuously evaluate teaching effectiveness, research productivity, student learning outcomes, institutional performance, innovation capacity, governance effectiveness, and stakeholder satisfaction. Artificial Intelligence, learning analytics, institutional dashboards, accreditation frameworks, benchmarking studies, and performance indicators provide valuable evidence for strategic planning, policy improvement, and organizational development. Continuous assessment enables institutions to identify strengths, address weaknesses, and maintain academic excellence within competitive global educational environments.Institutional leadership also involves managing organizational change within rapidly evolving educational systems. Educational leaders guide institutions through curriculum reforms, digital transformation initiatives, accreditation processes, policy changes, financial challenges, technological advancements, demographic shifts, and emerging societal expectations. Effective leadership fosters resilience, adaptability, innovation, collaboration, and continuous improvement while ensuring that institutional transformation occurs in an inclusive, ethical, and sustainable manner.Despite its numerous contributions, Educational Leadership faces several contemporary challenges. Rapid technological change, financial constraints, increasing competition, faculty development needs, cyber security risks, ethical concerns related to Artificial Intelligence, regulatory complexity, changing student expectations, globalization, and demographic diversity require educational leaders to possess advanced strategic, technological, interpersonal, and organizational competencies. Univer
The rapid growth of urbanization in India has significantly increased the demand for efficient urban infrastructure, intelligent public services, and sustainable resource management. Cities are facing numerous challenges, including traffic congestion, rising energy consumption, water scarcity, environmental pollution, inefficient waste management, and increasing pressure on healthcare and public safety systems. Conventional urban management techniques are often inadequate for handling these complex and interconnected challenges because they rely heavily on manual monitoring and reactive decision-making. The Internet of Things (IoT), combined with smart electronic systems, has emerged as a transformative technology capable of addressing these issues by enabling real-time monitoring, automation, and intelligent decision-making. IoT-based smart electronics integrate sensors, embedded processors, wireless communication technologies, cloud computing, artificial intelligence, and data analytics to create interconnected systems that continuously collect, process, and exchange information. These technologies enable city administrators to monitor infrastructure, optimize resource utilization, improve service delivery, and enhance the quality of life for citizens. In India, the Smart Cities Mission has accelerated the adoption of IoT-enabled technologies across various sectors, including transportation, energy management, water distribution, environmental monitoring, healthcare, public safety, and digital governance. Smart electronics have enabled intelligent traffic control systems, smart street lighting, smart electricity meters, connected surveillance systems, and automated waste management solutions, thereby improving operational efficiency and reducing environmental impact. Despite significant progress, several challenges remain, including cybersecurity threats, interoperability issues, data privacy concerns, high deployment costs, and the need for standardized communication protocols. This paper presents a comprehensive discussion on the role of IoT-based smart electronics in building smart cities in India. It examines the technological architecture, key applications, implementation challenges, and future opportunities associated with IoT-driven urban development. The paper concludes that the integration of IoT with emerging technologies such as artificial intelligence, edge computing, fifth-generation (5G) communication, blockchain, and digital twin technologies will play a crucial role in achieving sustainable, resilient, and citizen-centric smart cities in India.
C. O. Enuma, Matthias D., V.I.E. Anireh, Bennett E.O.
Abstract The increasing adoption of cloud computing and blockchain-based smart contracts has transformed digital service delivery through decentralized automation, transparency, and trusted transaction execution. However, existing smart contract frameworks continue to face challenges related to privacy preservation, secure computation, intelligent access control, execution integrity, and auditability. Most existing solutions rely on isolated privacy-preserving mechanisms, exposing sensitive information during computation and limiting scalability and overall system performance. This study developed a Model for Privacy-Preserving Smart Contract in Cloud Computing by integrating Zero-Knowledge Proofs (ZKP), Secure Multi-Party Computation (SMPC), Trusted Execution Environments (TEE), Federated Learning (FL), Differential Privacy (DP), Autoencoder-based anomaly detection, GraphSAGE Graph Neural Networks (GNN), Proximal Policy Optimization (PPO), and Blockchain Smart Contracts within a unified architecture. The study adopted the Design Science Research Methodology (DSRM), while Object-Oriented Analysis and Design (OOAD) guided system implementation. The proposed model was evaluated using the CICIDS2017 cybersecurity benchmark dataset across privacy, security, execution integrity, auditability, scalability, computational performance, and cost efficiency. Experimental results achieved 96% privacy preservation, 94% security strength, 99% execution integrity, 98% auditability, and 90% scalability, while the Artificial Intelligence Privacy Engine attained 98.91% validation accuracy, 0.9962 ROC-AUC, 0.9490 Macro F1-score, and 0.9718 Matthews Correlation Coefficient (MCC). Comparative analysis against RBAC, ABAC, and blockchain-based frameworks demonstrated superior performance in privacy preservation, secure computation, intelligent authorization, and auditability. The proposed model provides a practical, scalable, and intelligent solution for secure smart contract execution in privacy-sensitive cloud computing environments. Keywords: Privacy-Preserving Smart Contracts, Cloud Computing, Blockchain, Zero-Knowledge Proofs, Secure Multi-Party Computation, Trusted Execution Environments, Federated Learning, Differential Privacy, Graph Neural Networks, Artificial Intelligence.
R. Priyadharsini, Ravikanth Reddy Vadamala, R. Raajalakshmi, K. Raghav Prasad ¡ 5 authors
The rapid transformation of global business environments driven by digitalization, technological advancement, changing consumer expectations, and competitive market dynamics has significantly altered traditional marketing practices and strategic business operations. Organizations operating in highly dynamic economic ecosystems are increasingly recognizing that conventional marketing frameworks alone are insufficient to sustain long-term growth, customer engagement, and market relevance. In this context, innovation-driven marketing models have emerged as a critical strategic approach that integrates creativity, data intelligence, technological innovation, customer-centric design, and adaptive business strategies to enhance organizational competitiveness and sustainable value creation. This research examines the growing significance of innovation-driven marketing models and their influence on consumer behavior, brand positioning, digital engagement, operational efficiency, and business sustainability across modern industries. The study explores how emerging technologies such as artificial intelligence, machine learning, big data analytics, blockchain, cloud computing, augmented reality, and social media ecosystems are transforming traditional marketing processes into highly personalized, predictive, and experience-oriented systems capable of responding to rapidly evolving market demands. The research further investigates how innovation-oriented marketing strategies support product differentiation, dynamic pricing, omnichannel communication, customer relationship management, and real-time market responsiveness in both online and offline commercial environments. Particular emphasis is placed on the role of innovation in enhancing customer engagement through interactive digital platforms, data-driven personalization, automated communication systems, influencer-based branding strategies, and experiential marketing campaigns. The study also evaluates how organizations leverage innovative business models to improve customer retention, market expansion, and strategic decision-making while simultaneously addressing challenges related to market uncertainty, consumer trust, technological adaptation, and ethical data utilization. A comparative assessment of traditional marketing approaches and innovation-driven marketing frameworks demonstrates that organizations adopting innovation-centric strategies experience stronger consumer loyalty, improved operational agility, enhanced brand visibility, and higher adaptability to changing economic conditions. Additionally, the research highlights the growing importance of sustainability-oriented marketing innovation, where businesses integrate environmental responsibility, social value creation, and ethical consumer engagement into their branding and communication practices. The findings indicate that innovation-driven marketing models not only contribute to commercial profitability but also strengthen organizational resilience and long-term strategic sustainability in highly competitive global markets. The study concludes that future business success increasingly depends on the ability of organizations to continuously innovate their marketing structures, technological capabilities, and customer engagement mechanisms in alignment with digital transformation and evolving consumer expectations. Therefore, innovation-driven marketing represents a transformative strategic paradigm capable of reshaping modern business ecosystems through intelligent, adaptive, and customer-focused value creation models.
Purpose This study aims to examine the feasibility of blockchain adoption during investment banksâ Know Your Customer (KYC) validation processes. It studies the role played by government in regulating the blockchain-based KYC process. Design/methodology/approach A framework based on the extended technology acceptance model (TAM) was conceptualised to formulate six hypotheses. Based on this, a structured questionnaire was developed and administered among the employees of investment banks through a multi-stage sampling technique. The final sample, comprising 605 responses, was analysed using a covariance-based structural equation modelling (Mediation Analysis) on JASP V.19. Findings The present research explains that the government, as a mediating variable, has a 45.7% direct impact and 54.3% indirect effect on investment banks in the adoption and actual usage of blockchain technology for KYC validation. The perceived ease of use, perceived usefulness and attitude to use technology are key factors that influence its adoption for front-office operations. Perceived ease of use is a dominant indicator within the model. Research limitations/implications This study contributes theoretically by extending the existing TAM model with its practical application in the KYC process during validation of customer documentation in the banking industry, adding practical relevance to the regulatory framework. Originality/value The research derives its originality from the mediating role of government regulation in implementing KYC through blockchain. It proposes a blueprint of a working model that can be internalised to optimise the processes, extending the existing theory and its application with practical relevance.
Hadeer Khayoon Ashour, Noor Salah Alramadan, Hamid Mohsin Jadah
There is growing interest in using blockchain technology to overcome the flaws of legacy payment systems and banking operations, few empirical efforts have examined the possible use of blockchain by large institutions. The study examines how blockchain is changing the payment systems and banking services with a focus on Citigroup (Citi) and various Citi blockchain projects, specifically Citi Token Services. The study aims to assess the impact of blockchainâs adoption on efficiency, cost reduction, customer confidence and service accessibility. A quantitative research study was conducted in a longitudinal design, and data were analysed using multiple linear regression in the SPSS program from 2020â2024 to check the relationship between variables. The results indicate that blockchain implementation offers considerable transaction speed, operational and transactional cost reduction (up to 80 percent), increased customer trust and broader service access with 24/7 transactions. The regression model explains 51.9 percent of the variance in performance. Although promising, blockchain for banking is still in its infancy and facing a variety of challenges that need to be solved for wider application, such as scalability, regulatory compliance, and integration with existing systems.
The construction industry faces several difficulties in warehouse management along with construction industry&s;s supply chain that is characterized by complex, multi-tiered interactions involving material suppliers, transporters, contractors, and on-site project managers. Traditional management systems suffer from delayed information exchange, lack of transparency, and vulnerability to fraud or errors, often leading to cost overruns and schedule delays. The purpose of the current paper is to suggest an Artificial Intelligence of Things (AIoT) and blockchain-based supply chain management model to be used in the construction industry. AIoT involves the use of IoT devices or RFID tags, GPS trackers, and environmental sensors along with AI algorithmic methods to conduct predictive analytics, anomaly detection, and automated decision-making in the edge or the cloud. Blockchain technology offers the benefit of immutable and transparent records that cannot be altered and is tamper resistant, which facilitates trust among the distributed stakeholders and automates the workflows of the contract through the use of smart contracts. The architecture that is proposed has three layers: 1 AIoT real-time data acquisition sensing and analytics, 2 Secure data storage blockchain ledger and smart contract execution, and 3 A stakeholder application dashboard. In order to test our framework, we conducted a simulation of a scenario with prefabricated steel parts as supply. We determined the effectiveness of the system in tracking items, recording events as swiftly as possible, the security of the process and the efficiency of the whole process. The findings were also staggering: the accuracy of the tracking increased by 92 percent, the reporting is 58 percent quicker, and the prevention of fraud is much more robust than the traditional ERP systems. Such results demonstrate that the convergence of the AIoT and blockchain technologies can contribute to the solution of current issues in the supply chain in construction, which will result in the improved and more data-driven project management. Second, we will experiment with this approach through real life projects and how it could be used with Building Information Modelling (BIM) platforms.
Tapasi Bhattacharjee, Amalendu Singha Mahapatra, Dipika Pramanik
Educational crowdfunding has emerged as a promising approach to provide educational resources to underprivileged communities. Conventional systems often suffer from a lack of transparency, weak accountability, inefficient allocation of funds, and inadequate traceability of resource use. To address these issues, the present study proposes an intelligent and efficient educational supply chain management system, âEduDonateBlock.â It uses a blockchain-based crowdfunding framework to ensure transparency, accountability, and efficiency. Decentralization, immutability, and verifiable transactions are supported in educational campaigns. The entire workflow is decomposed into modular smart contracts. These are the identity and access contract (IAC), campaign and donation contract (CDC), verification and allocation contract (VAC), and supply chain and tracking contract (SCTC). These contracts are designed to ensure traceability, accountability, and efficient resource allocation among donors, educational institutions, and administrators. The mathematical framework of EduDonateBlock determines the optimal level of blockchain transparency. This minimizes the Total Expected Cost (TEC) of smart-contract operations. Numerical analysis identifies an optimal transparency level of 87.16% on-chain integration. This finding underscores the economic trade-off between transaction costs and the benefits of automation, operational efficiency, and reduced fraud risk. The proposed framework achieves a campaign success probability of 89.45% and an institutional payoff of Rs. 11,335.99. Furthermore, executing smart contracts requires 0.0044 ETH, and the average latency remains at 6.25 s. The simulation results show that EduDonateBlock offers a more efficient, reliable, and transparent solution for decentralized educational crowdfunding and socially impactful digital supply chains.
Perkembangan Artificial Intelligence (AI) telah mendorong transformasi dalam Supply Chain Management (SCM) melalui peningkatan efisiensi operasional, kualitas pengambilan keputusan, dan ketahanan rantai pasok. Penelitian ini bertujuan untuk mengidentifikasi perkembangan penelitian AI dalam SCM, teknologi AI yang dominan, manfaat dan tantangan implementasinya, serta peluang penelitian pada periode 2021â2026. Metode yang digunakan adalah Systematic Literature Review (SLR) dengan menganalisis sepuluh artikel yang relevan dari berbagai sumber ilmiah. Data dianalisis menggunakan pendekatan narrative synthesis untuk mengidentifikasi pola, persamaan, dan perbedaan hasil penelitian. Hasil kajian menunjukkan bahwa Machine Learning merupakan teknologi AI yang paling banyak diterapkan, terutama pada demand forecasting, inventory management, optimasi logistik, dan manajemen risiko. Selain itu, perkembangan penelitian juga mengarah pada pemanfaatan Deep Learning, Computer Vision, Natural Language Processing, Digital Twin, dan integrasi AI dengan Internet of Things serta Blockchain untuk meningkatkan transparansi, fleksibilitas, dan ketahanan rantai pasok. Meskipun implementasi AI memberikan manfaat yang signifikan, masih terdapat tantangan berupa kualitas data, kesiapan infrastruktur digital, keamanan siber, dan kompetensi sumber daya manusia. Penelitian ini memberikan gambaran mengenai tren perkembangan AI dalam SCM sekaligus menjadi referensi bagi pengembangan penelitian dan implementasi AI pada berbagai sektor industri.
ABSTRACT Real Estate Tokenisation started with the introduction of blockchain technology. It is changing the worldâs way of investing in assets by providing proportional ownership, improving liquidity and basically giving retail investors access to HNI investment opportunities they didn't have before. This technology is getting a lot of global attention but institutional adoption is largely dependent on the environment that regulatory bodies set for digital assets and tokenized securities. This study help to present the role of regulation in institutional adoption of real estate tokenization through a comparative analysis of three main jurisdictions India, IFSC GIFT City and the United Arab Emirates (UAE). Using secondary data the study analysed regulatory documents, policy reports and academic literature through a qualitative comparative policy analysis and thematic content analysis. The research looks at the impact of regulatory certainty, recognition through laws, investor protection, licensing, digital marketplace infrastructure and frameworks for foreign investments on institutional confidence. The finding show that institutions are more likely to participate where regulatory certainty, licensing frameworks and innovation-friendly policies can coexist. India has shown increasing regulatory engagement with digital asset innovation with IFSC GIFT City has given a more progressive regulatory environment for international financial activities whereas the UAE has supported itself by dedicated virtual asset regulations and innovation based policies and has established itself as a leading jurisdiction for institutional tokenization initiatives. Proposed by this study is the Institutional Regulatory Readiness Framework (IRRF) which is an six dimensional conceptual framework for measuring the institutional readiness towards real estate tokenization in various jurisdictions. The paper proposes a Regulatory Readiness Framework that combines legal, technological and institutional dimensions to provide knowledge of jurisdictions for large-scale real estate tokenization. By comparing three regulatory ecosystems, the study offers practical advice for policymakers, regulators, financial institutions and market participants who are seeking to improve institutional adoption. Index Terms: Real Estate Tokenization, Institutional Adoption, Blockchain, Regulation, IFSC GIFT City, United Arab Emirates, India, Real-World Assets (RWA), Digital Assets, Regulatory Readiness.
Financial institutions depend on trusted employees, contractors and service accounts, yet this trust creates an attack surface that conventional perimeter controls cannot observe adequately. This paper develops an Explainable Adaptive Hybrid Artificial Intelligence (EAHAI) framework for insider threat detection and for assessing whether security awareness training is reducing measurable insider-risk behaviour. The framework combines Isolation Forest filtering, bidirectional long short-term memory sequence modelling, Shapley Additive explanations, adaptive behavioural risk scoring and Zero Trust policy enforcement. A socio-technical assessment layer is added to link training inputs to observable outcomes, including knowledge gain, phishing susceptibility, policy-violation rates, reporting delay, behavioural-risk reduction and analyst-confirmed events. The paper defines the measurement scales, evaluation criteria, validation procedures and analytical techniques required for institutional replication. Because production banking telemetry and labelled insider incidents are rarely available for publication, the empirical component is presented as a transparent synthetic proof-of-concept based on CERT-style behavioural variables rather than as evidence from a real bank. In a deterministic simulation of 17,280 user-day records and 2,880 test windows, the proposed hybrid score achieved an F1-score of 0.944, ROC-AUC of 0.993 and false-alarm rate of 0.017, while producing interpretable feature attributions and training-effectiveness estimates. The study contributes a scalable, explainable and ethically governed design for insider-risk analytics, and identifies the conditions under which it should be validated before operational deployment. Keywords: insider threat detection; explainable artificial intelligence; adaptive risk scoring; security awareness training; Zero Trust; financial cybersecurity.
The increasing adoption of blockchain technology has transformed digital transaction systems by providing secure, decentralized, and transparent data management. The vehicle procurement process, however, still relies heavily on conventional procedures involving multiple intermediaries, manual documentation, and lengthy verification mechanisms that often increase operational costs and expose transactions to fraudulent activities. This paper presents a blockchain-enabled smart vehicle procurement framework that modernizes the complete purchasing lifecycle while preserving transaction integrity and user trust. The proposed system utilizes blockchain technology as an immutable distributed ledger for securely storing vehicle records, ownership history, buyer credentials, and transaction information. Smart contracts are employed to automate critical activities including buyer verification, ownership transfer, payment authorization, and regulatory validation without requiring manual intervention. The decentralized architecture minimizes dependency on third-party agencies while improving transparency, reducing processing delays, and enhancing security against data manipulation. Since every transaction is permanently recorded on the blockchain, both buyers and sellers can independently verify the authenticity of vehicle records before completing a purchase. The proposed framework maintains the same operational workflow and implementation strategy as the reference system while offering improved documentation quality and technical presentation. Experimental observations demonstrate that blockchain-assisted procurement significantly improves transaction efficiency, strengthens security, simplifies ownership transfer, and establishes a reliable digital marketplace for modern automotive commerce. The framework represents a scalable solution capable of supporting future intelligent transportation systems and smart mobility applications.
The rapid digitalization of healthcare has led to the generation of vast amounts of sensitive patient information, increasing the need for advanced security solutions beyond traditional centralized systems. This study examines the integration of Artificial Intelligence (AI) and blockchain technology as a transformative approach to healthcare data security. Conventional electronic health record systems often face challenges such as single points of failure, limited transparency, and vulnerability to cyber threats. Blockchain addresses these issues by providing a decentralized and immutable ledger that ensures data integrity, traceability, and secure record management through cryptographic techniques and consensus protocols. In parallel, AI strengthens security by enabling intelligent threat detection, predictive analytics, and adaptive authentication mechanisms. Machine learning algorithms continuously analyze network activities and user behaviors to identify potential breaches and insider threats in real time. The combination of AI and blockchain creates a synergistic framework in which AI enhances blockchain efficiency, while blockchain provides a transparent and trustworthy environment for AI-driven data processing. The study further explores the role of blockchain-secured federated learning, which enables collaborative model training across healthcare institutions without exposing sensitive patient data. Key challenges, including interoperability, scalability, regulatory compliance, and integration with legacy systems, are also discussed. Additionally, patient empowerment is enhanced through self-sovereign identity models that grant individuals greater control over their personal health information. Despite challenges related to computational complexity and standardization, the convergence of AI and blockchain offers a proactive, resilient, and privacy-preserving security architecture for modern healthcare. Future research should focus on lightweight cryptographic solutions, quantum-resistant security mechanisms, and governance frameworks for decentralized healthcare ecosystems. Overall, this integration represents a significant step toward secure, transparent, and patient-centered digital healthcare systems.
This study investigates critical success factors crucial for the effective implementation of blockchain-based smart contracts in supply chain management. Through qualitative content analysis of expert interviews, diverse perspectives from industry professionals and blockchain technologists were synthesized. The findings emphasize critical dimensions such as technological infrastructure, stakeholder collaboration, regulatory compliance, data privacy, security, organizational culture, and change management. These factors collectively form a comprehensive framework essential for successful adoption. This research offers valuable guidance for organizations aiming to integrate blockchain-based smart contracts into supply chain operations. The insights derived from eight expert interviews provide strategic direction for practitioners, policymakers, and academics navigating the complexities of blockchain and smart contract technology in supply chain ecosystems.
This research paper aims to investigate the applications of blockchain technology and smart contracts in managing global supply chains, as well as their financial and economic implications. The study addressed the concept of supply chain management and the technologies of blockchain and smart contracts, with a focus on their applications in validating and tracking transactions, facilitating the flow and storage of information in international trade, supporting customs, shipping, and container management operations, and increasing transparency in commercial transactions. The most prominent digital supply chain platforms based on blockchain were also presented. The results showed that the application of these technologies contributes to reducing costs and fees, improving cash management, increasing transparency and reducing risks, and enhancing the economic and operational efficiency of exporting and importing companies. It also provides administrative bodies with the ability to track and verify transactions instantly, which supports more accurate financial and strategic decision-making.