This review synthesizes theoretical and empirical insights from 1055 peer-reviewed articles on artificial intelligence (AI), corporate governance, and ethics. Situated in the corporate governance and accounting literature, it develops a computational framework to identify thematic patterns and conceptual links among AI, transparency, accounting, governance, and ESG. Using latent Dirichlet allocation, co-occurrence network analysis, sentence-level semantic similarity, and exploratory regression, the study identifies three recurring configurations of conceptual association: (1) Ethics, Governance, and Transparency; (2) Machine Learning, Finance, Blockchain, and Accounting; and (3) Corporate, ESG, and Accounting. The findings indicate that these themes are repeatedly connected within the scholarly literature.
With the rapid advancement of industrial Internet technologies and intelligent wireless sensing infrastructures, efficient data acquisition and information transmission have become fundamental to modern textile supply chain management. The integration of electromagnetic-enabled Internet of Things (IoT) devices, RFID technologies, and intelligent communication networks provides essential support for real-time financial monitoring and digital taxation services. Against this background, this paper investigates the application of intelligent finance and taxation in textile industry supply chains by proposing an integrated framework based on artificial intelligence, blockchain, cloud computing, and IoT technologies. The framework enables transparent financial management, automated tax compliance, dynamic supply chain finance, and end-to-end traceability through seamless integration of operational, financial, and logistics data. Key applications, including blockchain-based material provenance verification, AI-driven credit assessment, automated customs and tax processing, and intelligent risk management, are systematically analyzed. The proposed architecture improves supply chain transparency, operational efficiency, sustainability, and resilience while facilitating data-driven decision-making across textile production and distribution processes. Furthermore, the study demonstrates that intelligent finance and taxation can establish a unified digital ecosystem for financial governance and supply chain collaboration, providing valuable technical references for wireless industrial information acquisition, smart sensing, and communication-assisted digital management in future intelligent manufacturing environments.
Crypto currency is one of most interesting financial innovation of 21st century. Crypto currency trading not only involve financial literacy while trading but also there are psychological factors affecting the decision of traders. Keeping in view the psychological factors and investors’ decision, this research study is designed to investigate the complex interplay between psychological triggers and market dynamics in the cryptocurrency sector in Pakistan, specifically examining how these elements coalesce to drive investor behavior and market volatility. While traditional financial models often attribute asset fluctuations to technological or fundamental shifts, this study posits that cryptocurrency markets are fundamentally driven by human perception and emotional reactivity. Utilizing a quantitative methodological approach, data was collected from a sample of 175 experienced traders to analyze the impact of emotional states, market sentiment, and behavioral discipline on trading outcomes. The empirical results, derived through multiple linear regression analysis, reveal that the model possesses a high level of explanatory power, accounting for 56% of the variance in emotional trading behavior (R2=0.56R2=0.56). Market sentiment emerged as the primary determinant of impulsive trading (β=0.48β=0.48), demonstrating that external social cues often exert a stronger influence on decision-making than internal emotional states. Among specific psychological variables, Fear, Uncertainty, and Doubt (FUD) were identified as the most significant predictors of rash choices (β=0.34β=0.34), while the Fear of Missing Out (FOMO) also demonstrated a substantial, though secondary, effect (β=0.21β=0.21). Conversely, the study found that trading experience and the application of systematic strategies serve as vital moderating factors that decrease emotional reactivity and enhance behavioral stability (β=−0.19β=−0.19). The findings contribute to the fields of behavioral finance and digital economics by illustrating that the volatility inherent in digital assets is a systemic byproduct of individual psychological biases aggregated through digital narratives. The research concludes that achieving a sustainable financial ecosystem requires moving beyond purely technical regulations. Instead, it advocates for the implementation of behaviorally-informed safeguards, such as algorithmic "cooling-off" periods and sentiment-aware trading tools, to mitigate the risks associated with reactive investing. Ultimately, this work provides a blueprint for a more resilient digital financial future by prioritizing human factors in market governance.
AI-powered predictive systems for decision support are revolutionizing the way that smart enterprises and industrial organizations are analysing data, predicting future conditions, and making operational and strategic decisions. The systems include machine learning, deep learning, predictive analytics, prescriptive analytics, real-time monitoring, and intelligent recommendation systems to enhance decision-making accuracy, efficiency, and responsiveness. They are used in business forecasting, customer and financial analytics, supply-chain and inventory management, predictive maintenance, production optimization, quality control, energy management, workplace safety and asset monitoring. The addition of new technologies like the Internet of Things, Industrial Internet of Things, digital twins, cloud and edge computing, robotics, blockchain and next generation networks further improve system connectivity, scalability and real-time performance. The successful implementation of these steps needs a structured framework for problem identification, data collection, preprocessing, feature engineering, model selection, training, validation, system integration, deployment, and continual monitoring. Despite these progressions, data quality, interoperability, scalability, algorithmic bias, explainability, privacy, cybersecurity, organizational readiness, and regulatory compliance are all important challenges that still need to be addressed. There is still a need for human oversight, especially when dealing with safety-critical and high-impact decisions. It includes the technological foundations, system architecture, implementation processes, enterprise and industrial applications, performance evaluation, governance requirements, and future directions of AI-supported predictive decision support systems. It concludes that the systems that are trustworthy, secure, transparent, sustainable and intelligent are enterprise and industrial operations.
Among the various problems that have persisted in global supply chains include data silos, information asymmetry, and vulnerability to fraud. In this paper, a blockchain-based intelligent management of the supply chain model has been suggested, involving distributed ledger technology, smart contracts, and Internet of Things for real-time tracking. The model features a four-tiered architecture consisting of data ingestion, blockchain network, smart contract automation, and application tiers. Tasks that include registering stakeholders, verifying the authenticity of the goods, transferring ownership, and verifying compliance can be automated through smart contracts. The solution offers the ability to process up to 200 transactions per second with an 18% reduction in gas costs as opposed to conventional solutions. Trace back time reduces from 95 seconds to 8 seconds, and the consumer trust index grows by 70%.
Information and Communication Technologies such as blockchain can significantly contribute to achieving the Sustainable Development Goals (SDGs). Without a doubt, blockchain, as one of the most valuable technological advancements, has been introduced over the past decade and has played a significant role in the industrial revolution. Blockchain technology is progressively taking over the business world. Blockchain as a disruptive technology and a driver for social change has exhibited great potential to promote sustainable practices and help organizations and governments achieve the United Nations’ Sustainable Development Goals (SDGs). The emergence of other technologies derived from blockchain, such as decentralized finance (DeFi) and the Metaverse, has fundamentally transformed people’s daily lives and profoundly impacted future versions of digital businesses. The Blockchain technology revamped several industries, including Real Estate, Healthcare, Education, and Legal industry to name a few. It opened new doors of opportunities and profit for the entrepreneurs and established brands. The paper's main contribution is to advance knowledge about the role of blockchain for economic and sustainable development in countries of the world. Grounded in the innovation forecasting literature, this paper explores blockchain-based innovations and research in the context of economic and sustainable development.
Purpose: The rapid evolution of spatial computing has initiated a paradigm shift from traditional, two-dimensional e-commerce to immersive, three-dimensional virtual commerce (v-commerce). This paper conceptualizes the foundational drivers, structural mechanics, and strategic implications of consumer behavior within the emerging metaverse marketplace.Methodology/Approach: Synthesizing Social Presence Theory and the Technology Acceptance Model (TAM), this study provides a comprehensive conceptual framework analyzing how multi-sensory immersion, avatar-mediated identity expression, and decentralized economic frameworks alter consumer decision-making. Findings: The paper establishes that the metaverse fundamentally redefines digital consumer behavior by transforming standard transactions into identity-driven social expressions. It outlines how immersive experiential marketing stimuli (e.g., gamified storefronts, virtual try-ons) drive high emotional arousal and hedonic consumption patterns. Furthermore, the analysis maps the collapse of the traditional boundary between buyers and sellers via Play-to-Earn (P2E) and Create-to-Earn (C2E) models, re-contextualizing virtual consumers as active entrepreneurial producers within blockchain-secured economies. Research Implications: While presenting a robust conceptual blueprint for v-commerce engagement, the study highlights critical consumer inhibitors, including biometric data harvesting risks, infrastructural access barriers, and psychological virtual fatigue. Originality: This paper bridges the gap between conventional digital marketing theories and spatial mechanics. It provides actionable strategic imperatives for contemporary brands specifically detailing hybrid "phygital" retail systems, spatial analytics optimization, and community-centric governance via Decentralized Autonomous Organizations (DAOs) to effectively future-proof enterprise models.
Transaction monitoring and efficient audit management have become increasingly importantin modern financial systems. Traditional centralized databases and auditing methods often face challengesrelated to security vulnerabilities, fraudulent activities, and data manipulation. A blockchain-based financialtransaction monitoring system integrates smart contracts, decentralized ledgers, and audit trails to automatefinancial operations, enhance transparency, and reduce fraud risks. The proposed architecture is implementedon Ethereum and Hyperledger Fabric platforms, enabling automated transaction validation and executionthrough smart contracts. All transactions are stored in an immutable decentralized ledger, while audit trailsare generated and maintained automatically. Simulation results demonstrate a 40–60% reduction in fraudulentactivities and up to a 70% decrease in audit processing time compared with conventional approaches. Theapplication of cryptographic algorithms and Zero-Knowledge Proofs further strengthens data security andprivacy protection. The proposed solution contributes to the improvement of financial control and auditingsystems within the framework of the digital economy.
This study adopts a conceptual and design-oriented approach to investigate blockchain integration into accounting informatization for improving transparency, reliability, and intelligence in enterprise financial services. A blockchain-based big data model is developed using distributed ledger, consensus, and encryption mechanisms to support secure and consistent financial data sharing. A personalized feedback system empowered by smart contracts and data analytics delivers real-time customized accounting information for service-oriented decision-making. Exploratory independence and reliability assessments examine data consistency and system robustness. Preliminary evidence indicates that the proposed framework tends to reduce data deviations, support decision efficiency, and improve user satisfaction over conventional systems. This study contributes to the service-oriented transformation of accounting informatization and offers a design framework for intelligent data-driven financial management systems enabled by blockchain.
Abstract:The pervasive integration of digital technologies has fundamentally redefined the operational paradigms of commerce, finance, and accounting. This paper explores the multidimensional impact of Digital Transformation (DT) across these interconnected sectors, focusing on the adoption and efficacy of Artificial Intelligence (AI), Robotic Process Automation (RPA), and Blockchain technology. Through a systematic qualitative review of recent literature and industry frameworks, this study examines how traditional financial workflows are evolving into automated, data-driven ecosystems. The findings indicate that while DT significantly enhances real-time reporting, fraud detection, and transactional efficiency, organizations face substantial barriers, including high implementation costs, data security vulnerabilities, and a growing digital skills gap. The paper concludes that successful digital transformation requires not only technological investment but also a strategic realignment of organizational culture and regulatory compliance frameworks. Future research trajectories emphasize the need for standardized continuous auditing protocols and scalable decentralized finance (DeFi) architectures.
This research paper examines the structural and philosophical changes in global commerce and management required because of the "Third Wave" of digital transformation (DT). While earlier versions of DT dealt with the digitization of analog records and the uptake of cloud computing, the modern age of Agentic AI, Industrial Metaverse and Decentralized Autonomous Organizations (DAOs) is demanding a fundamental re-engineering of the firm. Through a methodical approach of analyzing current technological trajectories and management frameworks this study identifies the existence of a critical "Agility Gap" between legacy led organizations and the digital native enterprises. The research proposes Integrated Digital-Managerial Framework (IDMF) as strategic roadmap of 2026 and onwards. Key findings suggest that "Digital Maturity" is no longer a technology benchmark but comes instead as a cultural and structural imperative, one determining whether a company survives in the marketplace in an increasingly automated commerce landscape.
Deepa Parasar, Dr. Priyanka Mishra, Aman Kumar Hamilton, Snigdha Madhab Ghosh, Dhanashree Rohan Kedare, Dr. Atowar ul Islam
Among the most influential technologies that predetermine the current digital society, artificial intelligence (AI) and blockchain have emerged as fast as the digitalization of technologies. This review examines the conceptual and practical implications and applications of AI and blockchain with particular attention to how the two can be used in the framework of digital governance, cybersecurity, and socio-cultural change. The analysis synthesizes existing literature to explore how AI enhances data processing, predictive analytics, and automated decision-making, while blockchain strengthens transparency, decentralization, and data integrity in digital systems. Their integration is shown to support more efficient governance frameworks, improved policy decision-making, secure digital infrastructures, and reliable identity management. At the same time, the review highlights broader societal impacts, including changes in digital trust, ownership structures, and creative and media industries. Despite these opportunities, several challenges remain, including governance fragmentation, ethical concerns, privacy risks, and limitations related to interoperability and institutional readiness. New research directions are also outlined in the form of trustworthy and explainable AI, sustainable technological infrastructures, and the adoption of AI and blockchain systems of Web3 and decentralized digital ecosystems. Altogether, AI and blockchain convergence is an important change in the structure of the digital space, and it will need harmonized governance structures and responsible innovation to establish safe, transparent and inclusive digital societies.
Muxtorov Maqsudbek Sherzodbek o'g'li Almardanov Samariddin Abdixoliq o'g'li
This paper examines the comprehensive impact of digital transformation on the finance and accounting sectors. With rapid advancements in cloud computing, artificial intelligence, blockchain technology, and automation tools, traditional paradigms of financial reporting, auditing, and managerial accounting are being fundamentally redefined. The study analyzes how digital technologies enhance accuracy, efficiency, transparency, and scalability of financial operations across organizations of various sizes and industries. The findings demonstrate that digital transformation facilitates real-time financial reporting, automated bookkeeping, predictive financial analytics, fraud detection systems, and data-driven strategic decision-making through robotic process automation (RPA), machine learning, big data analytics, and distributed ledger technologies. The paper concludes with policy recommendations and organizational guidelines for effective and responsible digital transformation in financial management, emphasizing human oversight, continuous upskilling, and regulatory alignment.
As a core technology of blockchain ecosystems, smart contracts are fundamentally reshaping the operational logic and commercial landscape of the digital economy. This paper systematically analyzes the current economic ecosystem of smart contracts from four dimensions: business value creation, multi-dimensional industry applications, legal and regulatory challenges, and frontier technological evolution. Research indicates that smart contracts, by reducing transaction costs and enhancing trust mechanisms, have achieved maturity in financial applications (DeFi) and are demonstrating significant enabling effects in real-economy sectors such as supply chains, healthcare, and energy internet. However, their widespread implementation still faces institutional obstacles including ambiguous jurisdictional boundaries, compatibility between code and law, and liability attribution. Looking ahead, Layer-2 scaling solutions have significantly improved cost-effectiveness, while the integration of cross-chain interoperability and AI-driven intelligent decision-making will become key trends driving the expansion of "contractability" boundaries. Smart contracts are not merely technical tools but rather institutional infrastructure driving the transformation of business models from intermediary-dominated to algorithm-autonomous paradigms.
The environmental externalities of crypto-assets―particularly the substantial electricity demand inherent in the energy-inefficient consensus protocol known as Proof of Work（PoW）―have attracted increasing attention in sustainable finance. However, despite the growing interest in the environmental impact of crypto-assets, a comprehensive integration of technical energy analyses with environmental, social, and governance（ESG） investment, financial regulation, and corporate disclosure remains limited. This study addresses this gap by analysing how the environmental impact of crypto-assets can be incorporated into emerging sustainability frameworks, drawing on empirically verifiable sources such as the Cambridge Bitcoin Electricity Consumption Index, the Corporate Sustainability Reporting Directive of the European Union（EU）, the standards of the International Sustainability Standards Board, and disclosure information by major mining companies. The analysis is conducted along three dimensions:（1） market reactions and the evolution of ESG evaluation;（2） trends in disclosure regulation; and（3） case studies of corporate disclosure practices. Moreover, the transition to more energy-efficient alternative consensus protocols—as exemplified by Ethereum’s adoption of Proof of Stake—is examined as empirical evidence of technological innovation aimed at mitigating environmental externalities. By integrating market, institutional, and technological perspectives, the study elucidates persistent challenges concerning the reliability, comparability, and completeness of sustainability-related disclosures, as well as regulatory consistency across jurisdictions. It thereby contributes to the literature from both theoretical and practical perspectives.
Abstract The rapid evolution of the metaverse -a digital frontier characterized by the convergence of blockchain technology, artificial intelligence (AI) and extended reality (XR)- presents a profound normative dilemma regarding its ecological legitimacy. While virtualization offers significant opportunities to decouple economic growth from physical resource consumption, the intensive energy demands of decentralized infrastructures and high-bandwidth data processing pose systemic environmental risks. This study addresses the “accountability gap” inherent in decentralized ecosystems, where the fragmented identity of the polluter complicates the enforcement of the “polluter pays” principle and the state's constitutional obligation to protect the environment. To mitigate these challenges, this study proposes an original net emission balance model (E_{net}$) as a conceptual and regulatory tool to quantify the net climate impact of metaverse operations. The framework integrates blockchain-based “ green oracles ” and smart contracts to facilitate real-time, tamper-proof carbon tracking and automated offsetting. By synthesizing contemporary research and life cycle assessments (LCAs), this study evaluates the transition from energy-intensive proof-of-work (PoW) protocols to sustainable alternatives, such as proof-of-stake (PoS). Central to these policy solutions is the legal recognition of tokenized carbon credits as “digital assets” subject to property law, ensuring that environmental compliance is harmonized with digital tenure security. Furthermore, this study advocates for a shift toward “hard law” requirements through mandatory emission licensing, targeted fiscal instruments, such as deterrent taxes on energy-intensive PoW protocols and legally guaranteed cross-platform interoperability to prevent digital lock-in and regulatory arbitrage.
Deddy Rakhmad Hidayat, Dian Parawansa, Jusni Ambo Upe, Idayanti Nursyamsi
This study aims to conduct a bibliometric analysis of purchase intention research indexed in Scopus, focusing on trends and patterns from 2023 to 2025. Using Biblioshiny, the study identifies leading journals, authors, affiliations, countries, collaborations, highly cited articles, and main research themes. The Journal of Retailing and Consumer Services emerges as the most productive journal, with FPT University as the top affiliation and Zhang Y as the most prolific author. The most cited article is Treiblmaier H. (2023), Using blockchain to signal quality in the food supply chain: The impact on consumer purchase intentions and the moderating effect of brand familiarity, published in the International Journal of Information Management. China ranks first for corresponding author contributions. Dominant keywords include “purchase intention,” “sales,” and “purchasing.” Emerging research areas such as the metaverse, NFTs (Non-Fungible Tokens), VIS (Vote to Influence System), skincare, and tactics. This research offers a meaningful contribution that can inform and guide future bibliometric investigations undertaken by scholars within the scope of purchase intention by offering insights into key authors, journals, affiliations, countries, and dominant keywords. Additionally, it supports broader academic collaboration and knowledge development in this research domain.
Day after day, climate change intensifies, necessitating tracking solutions for carbon emissions that offer transparent operations and efficiency, alongside scalability and sustainable behavioural incentives. The proposition to track carbon emissions is not new, yet standard tracking systems present multiple deficiencies, including double reporting, fraud, high operational costs, and constrained access for small organisations. We have developed a blockchain system that follows a framework to track both carbon emissions and trading activities, using smart contracts and decentralised ledger technologies to establish security, trust, and automation. Our system requires IoT sensor integration and AI analytics to enable continuous monitoring and safe storage, along with direct carbon trading without third-party involvement. The proposed framework addresses blockchain energy consumption issues by examining Proof of Stake (PoS) and hybrid consensus models. The model presented facilitates a massive reduction in carbon emissions and enhances transparency and efficiency.
Nurgul Bakytbekovna Aiupova, Md Tota Miah, Krisztina Taralik
ABSTRACT Blockchain technology has emerged as a potential disruptor in non‐financial reporting practices for firms to publicly report their social and environmental impact with its promise of immutability and decentralization. In this context, this study employs a bibliometric analysis to explore the scientific advancements of blockchain applications in CSR reporting from 2015 to 2025. VOSviewer and Biblioshiny in Rstudio applications were employed to perform the required analysis. Drawing data from Scopus and Web of Science (153 articles), the results reveal a significant shift in focus from traditional corporate social responsibility (CSR) reporting mechanisms toward technology‐enabled sustainability reporting. The thematic analysis presents five significant areas for further exploration, including corporate governance and sustainability strategy, technology‐driven sustainable finance, CSR reporting and credibility, ESG performance and digital innovation, and blockchain for accountability and responsibility. The proposed conceptual framework suggests integration of technology‐organization‐environment (TOE) elements when introducing new technology within the organization. Future researchers can empirically test the framework's antecedents to assess the socio‐economic context of different types of non‐financial reporting.
Tan Khai Lian, Ismail Ahmad Al-Qasem Al-Hadi, Mohammad Ahmed Alomari, Mohammed Nasser Al-Andoli · 6 authors
Bitcoin has recently emerged as a leading asset in the cryptocurrency market. However, its significant price volatility presents challenges for accurate prediction. Due to this volatility, forecasting Bitcoin prices accurately is difficult and complicates decision-making for investors and traders in the cryptocurrency space. This research compares the accuracy of three prediction models: Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and Facebook's NeuralProphet, introduced in 2021, focusing on improving Bitcoin price forecasting accuracy. The study uses daily Bitcoin prices from the past five years to assess model performance. Results indicate that the LSTM model outperforms both NeuralProphet and RNN in prediction accuracy. This comparison holds substantial economic significance, as accurate predictions can assist investors and traders in making informed decisions within the cryptocurrency market.
Dr Mamata Jagannathji Rathi, Miss. Sanika Yogiraj Parankar
This research investigates the role of supply chain automation through the integration of Blockchain technology, Smart Contracts, and the Internet of Things (IoT). The study explores how decentralized ledgers can automate critical workflows, including instant payment release, real-time inventory reconciliation, and automated compliance auditing. By utilizing IoT sensors to feed environmental data into a blockchain-backed system, companies can trigger automated responses that reduce human error and operational overhead. The findings indicate that this transition accelerates "speed-to-market" and fosters a self-correcting, autonomous ecosystem capable of responding to disruptions in real-time. While the research acknowledges significant implementation barriers—such as high initial capital expenditure, cybersecurity risks, and the "SME gap"—it concludes that the evolution toward an automated, transparent, and green supply chain is essential for resilience. Ultimately, the paper argues that automation should not be viewed as a replacement for human labor, but as a tool to liberate workers for high-level system orchestration. This study provides a strategic roadmap for organizations navigating the shift from Industry 4.0 to a human-centric, sustainable Industry 6.0 framework