Blockchain Papers

Venice Lei De Luna Lucto

No abstract is available for this record.

Risqy Pradana Putra, Fara Triadi -, Ahmad Rofiq Hakim

Perkembangan teknologi informasi mendorong penerapan sistem yang lebih efisien dan transparan dalam manajemen gudang. Penelitian ini bertujuan merancang sistem manajemen gudang berbasis QR Code dan Blockchain untuk meningkatkan akurasi, keamanan, dan efisiensi pelacakan barang. Sistem mengintegrasikan mikrokontroler ESP32, modul GM65 barcode scanner, printer thermal, dan UPS sebagai sumber daya mandiri. QR Code digunakan untuk identifikasi dan pelacakan barang secara real-time, sedangkan Blockchain memastikan data transaksi tersimpan secara aman, transparan, dan tidak dapat diubah. Penelitian menggunakan metode Waterfall yang meliputi analisis kebutuhan, perancangan, implementasi, dan pengujian sistem. Hasil pengujian menunjukkan bahwa sistem mampu melakukan pencatatan, pemindaian, dan pembaruan data stok secara real-time dengan tingkat akurasi yang tinggi. Sistem ini memberikan solusi yang efektif untuk meningkatkan efisiensi operasional, keamanan data, dan transparansi dalam pengelolaan gudang berbasis Internet of Things (IoT).

Liang Guo

Game-based teaching (GBT) has gained widespread adoption in modern education, yet teachers bear heavy burdens in designing GBT activities and interpreting student learning performance, while centralized educational data storage brings prominent security and credibility risks. To tackle the above bottlenecks, this paper proposes SmartTA, an integrated teaching assistant system combining GBT recommendation modules, automated machine learning (AutoML), and blockchain. Specifically, SmartTA supplies customized GBT cases and exam scoring suggestions for teachers, and leverages AutoML to automatically mine student learning behaviors with zero coding requirements. Three groups of experiments are conducted to validate the system: AutoML achieves a maximum prediction accuracy of 93% on six public educational datasets; the Hyperledger Fabric-based blockchain prototype enables data insertion with an average latency of approximately 2.2 seconds and query latency of approximately 150 ms; 20 frontline educational practitioners provide 85% positive user feedback. The experimental results suggest that SmartTA may help reduce teachers’ lesson preparation workload, support improved instructional quality, while enabling tamper-resistant data storage via blockchain. This study realizes the practical fusion of AutoML and blockchain for GBT scenarios, and establishes a novel, secure, data-driven teaching assistance paradigm that is accessible to non-technical educators.

X. L. Li, D. H. Chen, Y. F. Liu

In blockchain-enabled supply chain finance, traditional credit risk assessment models suffer from conflicts between data sharing and privacy protection, reliance on static evaluation methods, and limited data credibility. To overcome these challenges, this paper proposes a blockchain-based dynamic credit risk assessment model that integrates privacy computing and intelligent risk monitoring. First, blockchain’s immutability and traceability ensure the authenticity and transparency of supply chain transaction data, effectively mitigating information asymmetry and data tampering. Second, privacy-preserving technologies, including homomorphic encryption based on the Paillier algorithm and zk-SNARKs, enable secure data sharing and validity verification without exposing sensitive enterprise information, thereby improving assessment reliability. Third, a dynamic risk monitoring framework is constructed by combining smart contracts, long short-term memory (LSTM) networks, and an improved dynamic graph neural network (DGNN). LSTM models temporal risk evolution in transaction data, while DGNN captures risk propagation among upstream and downstream enterprises. Smart contracts synchronize transaction states in real time, allowing continuous updates of credit risk levels. The proposed secure information processing and dynamic graph modeling strategy also provides a valuable reference for trustworthy data interaction and intelligent decision-making in distributed electromagnetic sensing and communication networks, where reliable information propagation and adaptive resource management are essential. Experimental results based on a textile supply chain dataset show that the proposed model achieves approximately 94% credit assessment accuracy, outperforming traditional static models by 15%–20%, while maintaining excellent response speed and throughput for dynamic financial decision-making. The proposed framework provides a practical and secure solution for blockchain-based credit risk management and offers methodological insights for data-driven engineering systems requiring secure information fusion and dynamic network analysis.

Dušan Mitrović, Ivan Milenković, Miroslav Minović

The growing use of blockchain in e-commerce has produced hybrid environments in which private enterprise ledgers and public blockchain networks operate side by side. Consequently, efficient and secure interoperability between these networks has become increasingly important. This study presents a cross-chain interoperability framework that links a permissioned Hyperledger Fabric network with a public Ethereum network. The framework provides attestations of selected business events rather than moving assets. An interoperability smart contract on Fabric emits cross-chain events; an off-chain validator enforces uniqueness and replay protection; and a public verification contract on Ethereum records an immutable, publicly verifiable attestation of each event. The framework uses a two-of-three validator threshold to attest events, so safety holds as long as no more than one of the three validators is compromised. The prototype was evaluated by processing 21,000 events across sequential, concurrent, and peak-load workloads. On the local network, message validation averaged approximately 12 ms per event, and the interoperability layer added less than 200 ms of overhead per attestation. Sustained throughput ranged from 13.2 to 14.2 attestations per second, while the validator used approximately 16% mean CPU and less than 194 MiB of memory, with no sustained memory growth during the full experiment. On the Ethereum Sepolia public testnet, 55 transactions were confirmed with a 100% success rate and a mean confirmation time of 10,676.62 ms. Gas consumption stayed stable at about 51,743 gas per verification on the local network and about 189,092 gas on Sepolia, and the mean public testnet transaction cost was 0.000692 Sepolia ETH. Five adversarial tests were conducted, covering replay, forgery, malicious relayers, concurrent replay, and denial-of-service attacks. All five tests passed, including the rejection of 500 concurrent replay attempts with zero double registrations. The results show that the framework provides efficient, verifiable, and replay-resistant cross-chain interoperability suited to hybrid e-commerce ledgers.

De-Graft Johnson Dei, Karim Awudu

The rapid expansion of institutional repositories (IRs) has heightened concerns about digital rights management (DRM), copyright protection, content authenticity, and long-term digital preservation, particularly in developing countries where institutional and technological capacities remain constrained. This study examines the feasibility of adopting blockchain technology as a DRM solution for Ghanaian institutional repositories and evaluates whether its application is transformative or largely aspirational. Guided by the Technology–Organization–Environment (TOE) framework and Diffusion of Innovations (DOI) theory, the study employed a sequential explanatory mixed-methods design that integrated quantitative survey data with qualitative interviews with ICT directors, repository managers, academic librarians, systems librarians, and faculty members from eight Ghanaian universities. The findings reveal low DRM maturity across institutional repositories. 40% of participating institutions lacked formal DRM mechanisms. Although awareness of blockchain technology was moderately high among respondents, substantial disparities existed across stakeholder groups, with ICT personnel demonstrating higher levels of understanding than faculty members and academic librarians. Institutional readiness for blockchain adoption remained generally poor, constrained by inadequate infrastructure, funding limitations, insufficient technical expertise, weak policy frameworks, and low organizational preparedness. Despite these limitations, stakeholders expressed strong support for blockchain’s potential to strengthen tamper-proof authorship verification, enhance content authenticity and integrity, improve transparency through immutable audit trails, and automate copyright management through smart contracts. The study further suggests that capacity building, phased implementation strategies, open-source platforms, interdisciplinary collaboration, and institutional policy alignment are critical pathways for integrating blockchain into institutional repositories. The study concludes that blockchain-enabled DRM in Ghanaian IRs is a promising, emerging innovation and that its successful implementation depends on sustained investment in digital infrastructure, institutional reforms, technical training, and supportive regulatory frameworks.

Wiranto, Faisar Ananda, Heri Firmansyah

The rapid development of blockchain technology has introduced new forms of digital assets, including Non-Fungible Tokens (NFTs) and metaverse virtual land, creating legal uncertainty regarding their status as inheritable property under Indonesian Islamic Family Law. This study examines the legal status of these digital assets as inheritance objects, analyzes their distribution based on fiqh al-mawārīth and Indonesian positive law, and proposes a legal framework to strengthen legal certainty in digital inheritance. This research employs a normative legal method using statutory, conceptual, and Islamic jurisprudential approaches. Legal materials were analyzed through descriptive and deductive legal reasoning. The findings demonstrate that NFTs and metaverse virtual land satisfy the Islamic legal characteristics of māl because they possess lawful ownership, measurable economic value, legal control, and transferability, thereby qualifying as al-tirkah (inheritance estate). Their distribution should follow the principles of fiqh al-mawārīth while accommodating the technical characteristics of blockchain-based assets, particularly digital wallets and private-key access. The study also identifies a regulatory gap in Indonesian positive law concerning digital asset inheritance. Unlike previous studies that primarily discuss digital assets from commercial or general legal perspectives, this research develops an integrated framework combining Islamic inheritance law, Indonesian positive law, and digital estate planning to strengthen legal certainty, protect heirs' rights, and contribute to the development of Islamic Family Law in the digital era.

Hebat Allah Adel, sayed abdelgaber, Wessam H. El-Behaidy

Ensuring transparency and security in digital recruitment systems remains a critical challenge. This study proposes BC-XAIA, a unified framework that integrates blockchain, smart contracts, explainable artificial intelligence (XAI), and agile methodology to enable consistent, secure, and traceable recruitment decision-making. Smart contracts, implemented in Solidity and deployed using the Remix Ethereum IDE, automate key processes such as identity verification, data access control, and behavior monitoring, reducing reliance on centralized intermediaries. To support intelligent decision-making, multiple machine learning models, including Random Forest, Logistic Regression, and Support Vector Machine (SVM), were trained and evaluated on a recruitment dataset, with Random Forest achieving the highest performance, reaching an accuracy of 93%. To enhance transparency, SHAP and LIME were employed to provide both global and local interpretability of model predictions. Furthermore, agile methodology is embedded to drive continuous adaptation, iterative development, and stakeholder feedback throughout the recruitment lifecycle. Unlike existing recruitment systems that treat blockchain, AI, and explainability separately, BC-XAIA unifies these technologies within an agile and decentralized architecture. Overall, BC-XAIA establishes a secure, transparent, and explainable decentralized recruitment ecosystem that enhances trust, fairness, and intelligent decision-making in next-generation HR systems.

Jaume Martin Bosch, Marco Combetto, Luca Tangi, A. Paula Rodriguez Müller

Introduction Blockchain technology (BCT) has been widely discussed as a potentially valuable technology for advancing sustainable development in the public sector. Its core features, including transparency, immutability and decentralisation, may contribute to more accountable, efficient and inclusive public services. However, limited empirical evidence exists on how BCT-based public sector initiatives align with the United Nations Sustainable Development Goals (SDGs). Methods This study examines 306 public sector BCT-based use cases across the EU, compiled by the Public Sector Tech Watch observatory. We apply a GPT-4o-based AI text classification pipeline to assess the degree of alignment between project descriptions and the 17 SDGs. The pipeline combines refined SDG descriptors, structured prompting and documented model parameters. Its outputs are benchmarked against a human-coded subset to assess validity. Results The results show strong alignment with SDG 9 (Industry, Innovation and Infrastructure) and SDG 17 (Partnerships for the Goals), followed by more moderate alignment with SDG 8 (Decent Work and Economic Growth). By contrast, goals such as SDG 2, SDG 6 and SDG 14 remain weakly represented. These findings provide an empirical overview of how BCT applications in EU public administrations are framed in relation to the SDGs. Discussion By highlighting patterns of alignment between BCT adoption and the SDGs, this study offers evidence to inform policymakers, practitioners and future research on sustainability-oriented public sector innovation. It also demonstrates the value of AI-assisted classification for mapping large corpora of digital government initiatives, while recognising that the results capture stated or perceived alignment rather than verified sustainability impacts.

Marco Dautaj, Jinhua Xiao, Mónica Rossi, Satoru Goto · 5 authors

Industry 5.0 emphasises human-centric technologies (HCTs) as essential drivers of sustainable and resilient production. However, their specific contributions to Circular Economy (CE) strategies and the associated skill requirements are not well-defined. This paper investigates how HCTs support Circular Economy practices (CEPs) and which skills and competencies are needed for their effective implementation. A systematic literature review was conducted using Scopus and Web of Science, following established guidelines. The search employed a string that links Industry 5.0, human-centricity, and the 10 R framework of CE. After a multi-stage screening and snowballing process, 41 peer-reviewed contributions published between 2015 and 2025 were selected for analysis through a combination of bibliometric and qualitative content analysis. The review maps the main HCTs, such as AI, digital twin, XR, robotics, blockchain, and IoT, to CEPs and specific 10 R strategies. It identifies seven clusters of skills ranging from analytical and decision-making abilities to human-machine collaboration, CE-specific expertise, and green human resource management practices. A Sankey diagram visualises the primary linkages between technology and strategy. Then, the authors developed a framework (TSC framework) that links skill clusters, CE practices, and enabling technologies and validated it through an illustrative case study. Interpreting the findings through the Resource-Based View, the paper argues that value arises from socio-technical bundles that integrate technologies, circular practices, and human capabilities. The study concludes with implications for policymakers, educators, and practitioners and outlines potential avenues for future research on skills for human-centred circularity.

Narendra Kumar Dewangan, Padmavati Shrivastava

This chapter presents the concept of a Smart Rice Mill as an intelligent, connected, automated, and traceable rice-processing ecosystem. It integrates IoT sensors, computer vision, deep learning, Edge AI, cloud analytics, predictive maintenance, intelligent control, and blockchain to improve rice-processing operations. The chapter discusses automated grain inspection, variety classification, defect detection, broken-rice estimation, milling-quality prediction, machine monitoring, process optimization, and digital recording of batch history. It also examines implementation challenges involving legacy machinery, hardware and sensor reliability, cybersecurity, staff training, integration, and economic feasibility. The proposed future direction is a closed-loop Smart Rice Mill capable of sensing paddy and machine conditions, predicting quality, adjusting processing parameters, verifying output, and maintaining complete traceability.

Sathy Akter*

Currently, the most significant threat to the validity of academic credentials in the United States is the advanced forgery of transcripts along with diploma mills. This research study addresses the potential of blockchain technology as a decentralized means to protect academic credentials. By integrating recent academic research and technical frameworks, this study analyzes the shift from centralized databases to immutable, distributed ledgers. The integration of various perspectives, including advanced zero-knowledge proof architectures as well as legal frameworks for transnational data circulation, is a major innovation of this study. Using a systematic literature review and a case study approach, the research indicates that though blockchain's potential to enhance security and automate processes through smart contracts is indeed great, a number of legal, compliance, and technical barriers have to be removed for it to be a viable option. This study proposes that the combination of artificial intelligence (AI), along with blockchain technology, provides the most secure option for U.S. higher education institutions.

Goldy Soni

This chapter proposes an integrated Blockchain–IoT–AI framework for secure and intelligent quality traceability, particularly in agricultural and rice supply chains. It explains how IoT sensors can continuously collect physical and environmental information, AI models can analyze images and sensor data for quality assessment, and blockchain can securely record important quality events and processing information. The framework supports unique digital identities for rice batches, quality monitoring, defect detection, moisture estimation, quality scoring, and QR-based access to traceability information. The chapter examines applications in rice quality certification, smart rice mills, food safety, warehouses, export-quality monitoring, consumer verification, and government procurement. Challenges related to data quality, sensor reliability, interoperability, stakeholder participation, scalability, and regulatory coordination are also addressed.

Rashon Rahming

The programmable economy lacks a universal computational layer capable of interpreting, translating, verifying, and simulating the mathematical and cryptographic operations that underpin digital assets. Existing tools are fragmented: wallet software provides only rudimentary transaction signing, portfolio trackers offer aggregated views without evidence, and specialized calculators address isolated problems. No general-purpose, cryptographically verifiable, language-native computational environment exists for digital value. KHOTOR is designed to fill this gap. It is a universal, deterministic runtime that interprets the anti-entropic linguistic protocol Kryptophon, transforms plain-language queries into executable computational expressions, and performs multi-domain financial mathematics across asset conversion, transaction analysis, decentralized finance, tokenomics simulation, cryptographic proof generation, and risk assessment. Every output carries an epistemic classification — verified, observed, inferred, simulated, or uncertain — and can be exported as a Gamma-Proof: a cryptographically signed, independently verifiable artifact. This paper presents the complete KHOTOR architecture: a ten-layer computational engine, a formal abstract machine for Kryptophon evaluation, a tiered adoption model that makes the programmable economy accessible to non-technical users while creating a new domain of expertise for professionals, and a product family spanning a public cloud API, a web platform, a handheld consumer device, and integration with dedicated hardware instruments. All components are designed around a single governing principle: every calculation shows its work, every output carries a truth label, and no inference is ever presented as fact.

Beacon Kit

Beacon Kit: Ecosystem epoch heartbeat @ the world game (s). Block-time arbitrage tokenized commodity index, adaptive procedural template @ system of federated DeFi cryptocurrency quantum - AI systems consensus

G. Weerasinghe, M. M. S. A. Karunarathna

The rapid growth of cryptocurrencies and increasing instability in traditional financial systems have significantly transformed global investment behaviour in recent years. In developing countries experiencing economic crises and currency depreciation, investors increasingly seek alternative financial assets that can preserve value and generate higher returns. Sri Lanka has recently experienced severe economic instability characterised by inflation, foreign-exchange shortages, sovereign debt problems, and rapid depreciation of the Sri Lankan rupee. Under these conditions, interest in cryptocurrency investment has increased, particularly among younger and technologically aware investors. Therefore, this study examines whether fiat currency devaluation shifts investment from the stock market to the cryptocurrency market among university students in Sri Lanka. The study adopts a quantitative research approach and uses primary data collected through a structured questionnaire from 150 final-year undergraduate students at the University of Sri Jayewardenepura. Stratified random sampling was used to select respondents from the Faculty of Humanities and Social Sciences, the Faculty of Management Studies and Commerce, and the Faculty of Applied Sciences. Descriptive statistics, chi-square analysis, and binary logistic regression were employed to analyse the relationship between rupee depreciation and cryptocurrency investment behaviour. The findings reveal that depreciation of the Sri Lankan rupee significantly influences investment decisions among university students. Most respondents perceived cryptocurrency investment as more profitable than stock-market investment during periods of economic uncertainty. The chi-square analysis identified significant relationships between cryptocurrency investment behaviour and age, income, stock-market investment, and perceptions of rupee depreciation. Furthermore, the binary logistic regression results confirmed that rupee depreciation positively and significantly affects cryptocurrency investment, whereas stock-market investment had a negative relationship with cryptocurrency investment behaviour. The study concludes that economic instability, declining confidence in fiat currency, and increasing awareness of digital financial systems encourage university students in Sri Lanka to shift their investment preferences from the traditional stock market to cryptocurrency.

Kiryl Minkin, Dariusz Drążkowski

This systematic review synthesises empirical research on individual-level cryptocurrency adoption, distinguishing adoption intention, actual adoption and use, and continuance intention and use. We searched Scopus and Web of Science for English-language empirical studies published between 2019 and 2025 and synthesised findings using a structured narrative approach. Eighty-five studies were included, with reported sample sizes summing to 56,054 participants. No formal study-level risk-of-bias assessment was conducted. The literature was dominated by cross-sectional quantitative studies and technology-adoption frameworks, particularly UTAUT, TAM, TPB, and DOI. Evidence was strongly concentrated on adoption intention (n = 75), whereas actual adoption and use (n = 16) and continuance intention and use (n = 8) were examined much less frequently. Across studies, adoption was associated with psychological, technological, social, economic, knowledge-related, institutional, and individual factors, with no single determinant consistently dominating across outcomes. The synthesis further distinguished direct predictors, mediating mechanisms, moderators, drivers, and barriers. The evidence base is limited by its reliance on self-reported, cross-sectional designs and uneven coverage of realised and continued engagement. Future research should more clearly specify adoption outcomes and use longitudinal, behavioural, and post-adoption designs.

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.

Shazpreet Kaur, Anjani Srivastava, Kirti Khanna

PurposeThe enhanced consolidation of cloud accounting models within geographical boundaries of India has established latest standards in financial auditing, reporting, compliance procedures and virtual accessibility. Nonetheless the legal framework in the nation is evolving simultaneously to accentuate audit trails, nationalized storage of data and sovereignity of data. Latest modifications under the companies act 2013; the company’s fourth amendment rules and the new policies issued by RBI for data localization have radically shifted the compliance framework for all the accounting professionals and the service providers in the country. Regardless of the mounting academic discussion on adaptability of cloud accounting around the globe, meagre research has highlighted hoe nationalized legal requirements have modified the framework infrastructure, risks involved and acceptability of accounting professionals in india which will be investigated in this study. This study will further identify the pros and cons for adoption of cloud accounting and will come out with suggestive cloud accounting models for Indian scenario. Design/Methodology/ApproachAn empirical and analytical research design has been adopted for the study and snowball and convenient sampling has been used for primary data collection..A sample size of 140 has been calculated using G-power. The research is confined to chartered accountants of agra district to whom a well structured questionnaire was sent using google forms.stastical tools used in this study is chi square test. FindingsCloud accounting is a tremendous shift towards triple entry system wherein a transaction is verified by a third party using cryptography and blockchain technology thereby increasing authenticity and trust by piling all entries in a public ledger. As a result of this more businesses are adopting virtual workforce models. Introduction of cloud based models in accounting profession has enhanced the roles of key processing indicators in the business.Cloud technology magnifies employees networking and association thereby increasing efficiency and effectiveness. Chartered accountants who will accept this change will have new opportunities open for them and those who will look at this technology with ostrich approach will be left behind. OriginalityThe findings will be valuable for further research work to be done in this area. The findings will help various researchers, chartered accountants, accounting professionals etc to understand the implementation of cloud accounting in developing countries like India and to understand in depth the implementation and adoption of cloud based accounting in the Indian scenario.

Robert Daniel Zebua, Oei Fuk Jin

Background: Despite the growing adoption of hybrid contract models in construction, energy, and agricultural procurement, there remains a significant gap in understanding how lump-sum and unit-price contracts differentially allocate risk across sectors and country contexts. This study addresses this gap by examining risk mitigation strategies through document analysis and thematic synthesis. Objective: The aim of this study was to identify key risk allocation strategies, contractual mechanisms, and the effectiveness of hybrid models in managing uncertainty across developed and developing country contexts. Methods: A qualitative approach based on thematic analysis and cross-case comparison was applied, drawing on 48 peer-reviewed sources published between 2015 and 2025, alongside relevant sector documents and procurement reports. Results: The analysis identified that hybrid contracts reduced cost overrun variability by incorporating performance-based incentives aligned with Expected Utility Theory and Principal-Agent Theory, while developing economies such as Indonesia and Bangladesh exhibited distinct risk profiles requiring adaptive contract mechanisms. However, significant gaps remain, particularly regarding the empirical validation of blockchain-enabled contract enforcement and AI-driven risk prediction, as well as the underrepresentation of developing economy contexts in existing research. Conclusion: The findings carry both scientific and practical implications. Theoretically, this study advances an integrative multi-theory framework combining Expected Utility Theory, Game Theory, and Principal-Agent Theory to analyse contract risk across diverse contexts. Practically, the results provide evidence-based guidance for procurement professionals and policymakers in selecting and designing contract structures that balance cost certainty with adaptive flexibility.

Omar Al-Jamili, Abdulaziz Fahmi Omar Faqera, Mohd Adan Omar, Shehu M. Sarkintudu · 8 authors

Open Government Data (OGD) has become central to digital transformation and data-driven governance, yet scholarly understanding of how OGD initiatives progress from initial adoption to sustained institutionalization remains fragmented. This study aims to synthesize the existing literature and develop an integrative framework that explains the socio-technical mechanisms underpinning the long-term sustainability and value creation of OGD initiatives. The study integrates bibliometric analysis with a systematic literature review of 481 peer-reviewed articles published between 2010 and 31 December 2024. Quantitative science-mapping techniques are combined with qualitative thematic synthesis to capture the intellectual structure, technological evolution, and theoretical foundations of OGD research. The findings reveal rapid growth and thematic diversification in OGD scholarship, with increasing attention to advanced technologies such as artificial intelligence and blockchain. However, the literature remains theoretically fragmented across behavioral, institutional, and public-value perspectives. Two critical gaps are identified: insufficient theorization of institutional legitimacy as a driver of continuity, and limited exploration of user-centric governance mechanisms shaping sustained data reuse. To address these gaps, the study proposes the Socio-Technical Institutionalization Model (STIM), which conceptualizes OGD sustainability as the dynamic alignment of technological infrastructures, institutional arrangements, and user ecosystems. By combining quantitative science mapping with systematic thematic synthesis and proposing the STIM lifecycle framework, this study offers an integrative synthesis that extends prior OGD reviews. The framework bridges fragmented theoretical perspectives and explains how open data initiatives may evolve from adoption to institutionalized value creation within complex digital governance ecosystems.

Stephen Oko Gyan Torto, Rupendra Kumar Pachauri, Jai Govind Singh, Shubham Tiwari · 7 authors

Global projects are mobilizing technologies to fight power generation curtailment and smooth demand by exploiting excess energy via transactive energy management and control. Sharing and transferring energy between microgrids helps manufacturers and businesses create energy autonomously. The transition to Multi-Vector Multi-Agent Energy Systems (MMV-ES) demands a paradigm shift from traditional centralized control to decentralized, market-based coordination. Transactive Energy Management (TEM) has emerged as a key enabler in this context, supporting local flexibility, peer-to-peer (P2P) trading, and integrated energy vectors across distributed assets. This review systematically decomposes and classifies the existing state of TEM from several perspectives: the market topology, the interaction of the agent, game-theoretic models and the real deployment challenges. Moreover, two game-theory formulations (cooperative and non-cooperative) were given special attention and a detailed comparison between Shapley value and Nucleolus was provided as approaches for fair cost allocation. To enhance the adaptability of the market and the overall efficiency of the system, we introduce the Transactive Energy Reformulation Model (TE-RM), a hybrid model combining AI-powered congestion pricing with coalition formation and fairness-based incentives. The comparative tables in this paper summarize TEM and TE-RM's strengths and weaknesses and compare it to the centralized and conventional DSM methodologies. Lastly, key research gaps including scalability, regulatory fit, and AI model interpretability are reviewed, and future directions are proposed for the integration of future advanced technologies (e.g., reinforcement learning, blockchain, IoT) to enable stable, fair and interoperable energy markets.

Cahya Kamila Maharani, Relit Nur Edi, Ismail Septayanto Utama

The 4.0 Industrial Revolution has transformed the global economic landscape through the digitalization of financial services, trade, and industrial activities. This transformation has accelerated the growth of the Halal Market, making it one of the fastest-growing economic sectors, driven by the expanding Muslim population, increasing awareness of halal consumption, and rising demand for ethical and sustainable products. In this context, Islamic Fintech has emerged as a strategic innovation that integrates digital financial technologies with the principles of Islamic law and economics. Although studies on Sharia Fintech and the halal industry have grown substantially, research integrating these two domains from the perspectives of Islamic law and Islamic economics remains limited. This study aims to examine the strategic role of Islamic Fintech in strengthening the global Halal Market through an interconnective analytical framework. Employing a qualitative library research approach, the study critically analyzes scholarly literature, regulatory documents, international reports, and previous empirical studies. The findings indicate that Sharia Fintech enhances financial inclusion, transparency, halal traceability, value chain efficiency, and digital governance through the adoption of blockchain, artificial intelligence, smart contracts, and digital payment systems. These innovations contribute to the realization of Maqashid al-Shariah, particularly the protection of wealth (ḥifẓ al-māl) and the promotion of public welfare (maṣlaḥah). The novelty of this study lies in the development of a comprehensive conceptual framework that integrates Islamic law, Islamic economics, digital financial innovation, and Halal Market governance into a unified analytical model.

Rejaul Karim, Md. Mustaqim Roshid, Bablu Kumar Dhar, Abdul Waaje

This study explores the evolving role of green financial technology (Fintech) in sustainability-oriented financial innovation, with a particular focus on climate finance, digital innovation, and environmental governance. Using bibliometric methods, we analyze 72 peer-reviewed publications indexed in Scopus from 2019 to 2024 to map the intellectual structure and emerging trends of green Fintech research. Key technological domains, including blockchain-based carbon markets, AI-powered ESG analytics, and green digital payment systems, are frequently associated in the literature with several Sustainable Development Goals (SDGs), notably SDG 13 (Climate Action), SDG 12 (Responsible Consumption and Production), and SDG 8 (Decent Work and Economic Growth). This analysis reveals how digital financial innovations are conceptualized as mechanisms for facilitating access to green capital, strengthening carbon credit ecosystems, and enhancing transparency in climate-aligned investment. However, persistent barriers such as fragmented regulatory frameworks, cybersecurity risks, and digital divides are recurrently identified in the literature as constraints, particularly in emerging economies. Interpreted through Institutional Theory and Stakeholder Theory, the study highlights the importance of coordinated policy innovation, inclusive digital infrastructure, and harmonized ESG standards in shaping the diffusion and governance of green Fintech solutions. By positioning theory as an interpretive lens rather than an empirical test , this research offers a theory-informed, data-driven synthesis that contributes to the growing interdisciplinary discourse on digital finance as a potential enabler of low-carbon, inclusive, and resilient sustainability transitions.