How AI models should deal with political topics has been discussed, but it remains challenging and requires better governance. This paper examines the governance of large language models through individual and collective deliberation, focusing on politically sensitive videos. We conducted a two-step study: interviews with 10 journalists established a baseline understanding of expert video interpretation; 114 individuals through deliberation using InclusiveAI, a platform that facilitates democratic decision-making through decentralized autonomous organization (DAO) mechanisms. Our findings reveal distinct differences in interpretative priorities: while experts emphasized emotion and narrative, the general public prioritized factual clarity, objectivity, and emotional neutrality. Furthermore, we examined how different governance mechanisms - quadratic vs. weighted voting and equal vs. 20/80 voting power - shape users' decision-making regarding AI behavior. Results indicate that voting methods significantly influence outcomes, with quadratic voting reinforcing perceptions of liberal democracy and political equality. Our study underscores the necessity of selecting appropriate governance mechanisms to better capture user perspectives and suggests decentralized AI governance as a potential way to facilitate broader public engagement in AI development, ensuring that varied perspectives meaningfully inform design decisions.
Athit Rodpangtiam, Smith Boonchutima, Ibtesam Mazahir
With retail investors playing a significant role in driving market adoption, cryptocurrency investment has gained widespread popularity recently. However, the perceived value of cryptocurrency investments and the perceived risk associated with investments have not been thoroughly examined. To address this gap in this research field, we surveyed 200 social media users active on social networking paltform - Reddit to unravel the intricate interplay of perceived value, perceived risk, and demographic factors that shape the decision-making process among social media users engaged in cryptocurrency investments. Our findings suggest that the acceptance of cryptocurrency investments is positively influenced by perceived value, whereas perceived risk exerts a negative influence. We also found that certain demographic elements which include age, education, gender, monthly income, and investment experience can moderate the relationship between perceived value, perceived risk, and the adaptation of cryptocurrency investments. The findings from our study offer valuable perspectives for retail investors and industry stakeholders aiming to enhance their understanding of the determinants that impact the acceptance of cryptocurrency investments among social media users.
The rise in popularity of cryptocurrencies such as Bitcoin across various platforms has attracted the attention of young investors, making it easier for them to invest. However, due to the volatile nature of Bitcoin, this type of investment carries a high risk. Therefore, this research conducts an analysis of stock return prices to minimize losses and help investors make effective investment decisions through stock price prediction. The focus of this study is on predicting Bitcoin stock returns by analyzing closing price data over the past five years (2019-2024). The methods used are a comparison between Integrated Moving Average (IMA) and Autoregressive Integrated Moving Average (ARIMA) with a quantitative approach using R Studio software. One of the main focuses of this research is the comparison of error estimation values between the two methods, namely Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The data analyzed comprises the daily closing prices of Bitcoin over the last five years, which is publicly accessible data. The best model for predicting the daily return of Bitcoin stock is the ARIMA (1,0,1) model. The predicted values for the next five days, from May 27, 2024, to May 31, 2024, are 0.0016632438, 0.0007991618, 0.0013415932, 0.0010010794, and 0.0012148386. The ARIMA (1,0,1) model has error measurement values with an MAE of 2.3% and an RMSE of 3.5%. It is hoped that this research will provide a better understanding of the effectiveness and relative advantages of the IMA and ARIMA methods in forecasting cryptocurrency returns, thereby offering more accurate guidance for investors in making investment decisions.
Blockchain technology (BCT) is regarded as one of the most important and disruptive technologies in Industry 4.0. However, no comprehensive study addresses the contributions of BCT adoption (BCA) on some special business functionalities projected as financial variables like BCA integrity, transparency, etc. Therefore, the primary objective of this study was to close this theoretical gap and determine how BCA has contributed to the four business sectors that were selected since FinTech had the greatest potential in these domains. The PRISMA approach, a systematic literature review model, was used in this work to make sure that the greatest number of studies on the topic were accessed. The PRISMA model’s output helped identify relevant publications, and an analysis of these studies served as the foundation for this paper’s findings. The findings reveal that BCA for companies with a disrupting financial technology (FinTech) attitude can help in securing corporate transaction transparency; offer knowledge, same-data, and information sharing; enhance fidelity, integrity, and trust; improve organizational procedures; and prevent fraud with cyber-hacking protection and fraudulence suspension. Moreover, blockchain’s smart contract utilization feature offers ESG and sustainability functionality. This paper’s novelty is the projection to four business sectors of the three-layer research sequence: (i) financial variables operated as BCA functionalities, (ii) issues, risks, limitations, and opportunities associated with the financial variables, and (iii) implications, theoretical contributions, questions, potentiality, and outlook of BCA/FinTech issues. And the ability of managers or practitioners to reference this sequence and make decisions on BCA matters is considered a key contribution. The proposed methodology provides business practitioners with valuable insights to reevaluate their economic challenges and explore the potential of blockchain technology to address them. This study combined a systematic literature review (SLR) with qualitative analysis as part of a hybrid research approach. Quantitative analysis was carried out on all 835 selected papers in the first step, and qualitative analysis was carried out on the top-cited papers that were screened. The current work highlights the key challenges and opportunities in established blockchain implementations and discusses the outlook potentiality of blockchain technology adoption. This study will be useful to managers, practitioners, researchers, and scholars.
Blockchain technology has attracted considerable attention from both academicians and industry players in different industries, such as accounting and finance, because of its transformative potential of re-engineering the process of operation and enhancing the level of required transparency in these industries. However, despite the various possibilities of transforming the accounting and finance sectors, there are still numerous challenges that hinder the further development of blockchain technology in the domain. The various obstacles to the adoption of blockchain in accounting and finance are interconnected and include a diverse set of issues related to technology, organization, regulations, and knowledge. To overcome these obstacles, it is necessary to take a comprehensive approach that includes improving technical proficiency, encouraging cooperation among stakeholders, negotiating intricate regulations, and cultivating a culture of innovation and adaptation within enterprises.
This study delves into the world of cryptocurrency financial reporting (CFR) research, exploring the connections between researchers, their institutions, and the countries they represent, considering the context in which cryptocurrencies financial reporting practices remain uncertain. Data from the Web of Science Core Collection were employed, mainly publications from 2016 to 2023, using the term “cryptocurrency financial reporting” to identify publications regarding this topic. By leveraging tools like VOSviewer, Biblioshiny, and Microsoft Excel, we pinpointed influential research on CFR, collaboration networks among researchers, thematic groupings, and research trends. A unique aspect of the study is the classification of findings into three themes: “financial reporting” in 100% of the manuscripts, “asset evaluation” 61%, and “asset recognition” 72%. Our results suggest that while collaboration among researchers in this field is still developing, the innovative nature and growing recognition of CFR have the potential to attract more researchers. The limitation consists in the fact that the timeframe is limited, as data was gathered in March 2024, and the key term was found in a low number of publications. Given the dynamic nature of CFR, this bibliometric analysis might benefit from updates to capture the latest developments.
With the widespread adoption of smart contracts in automated financial transactions, the accurate and efficient processing of image data related to financial transactions has become a critical challenge.The successful execution of smart contracts relies on the precise verification of transaction voucher images, yet existing image processing technologies still face limitations in dealing with background complexity, noise interference, and text extraction accuracy.To address these issues, this study proposes a comprehensive image processing approach aimed at enhancing the automation of financial transaction verification.The research focuses on four key areas: separation of table lines and text regions in images, application of Sauvola local adaptive binarization, table detection and reconstruction, and text extraction and fracture restoration techniques.Through these efforts, the study aims to provide more efficient and reliable technical support for financial transaction verification in smart contracts, thereby advancing the development of smart contract technologies.
Smart contracts are widely utilized in cross-chain interactions, where their results are transmitted from one blockchain (the producer blockchain) to another (the consumer blockchain). Unfortunately, the consumer blockchain often accepts these results without executing the smart contracts for validation, posing potential security risks. To address this, we propose a method for validating cross-chain smart contract results. Our approach emphasizes consumer blockchain execution of cross-chain smart contracts of producer blockchain, allowing comparison of results with the transmitted ones to detect potential discrepancies and ensure data integrity during cross-chain data dissemination. Additionally, we introduce the confirmation with proof method, which involves incorporating the chain of blocks and relevant cross-chain smart contract data from the producer blockchain into the consumer blockchain as evidence (or proof), establishing a unified and secure perspective of cross-chain smart contract results. Our verification results highlight the feasibility of cross-chain validation at the smart contract level.
Refika Komala, B. R. Arun Kumar, Mahadeshwara Prasad, A Shreyas
Legal consideration hold significant importance in the cloud migration process, encompassing contractual arrangements, data sovereignty concerns, and liability matters. Organizations need to make sure that their contracts with cloud service providers (CSPS) cover important aspects such as data ownership, usage rights, and indemnification clauses. In the ever-changing world of smart cities, the importance of ensuring secure, compliant, and efficient data migration across international borders has become more crucial than ever. This paper introduces a new framework that combines natural language processing (NLP), and blockchain smart contracts to tackle the intricate legal issues involved in moving data across borders in cloud settings. The framework starts by utilizing an NLP model to ensure compliance with data protection regulations, such as GDPR, CCPA, and DPDPA, which are specific to the destination jurisdiction of the data. After confirming the verification, the smart contract initiates the data transfer process, securely recording metadata such as file hash, timestamp, and transfer details on the blockchain, guaranteeing transparency and immutability. After the transfer, an international vendor at the destination verifies the data against the relevant legal requirements, guaranteeing compliance before storing it in the destination cloud. By adopting this approach, we can ensure the legal validity of cross-border data transfers, while also promoting trust and accountability among all parties involved in smart city ecosystems. The findings indicate that this framework has the potential to greatly reduce the risks associated with data sovereignty, liability, and contractual obligations when moving data to the cloud.
The aim of this paper is to synthesize and analyze existing evidence on interconnected sensor networks and digital urban governance in data-driven smart sustainable cities. The research topic of this systematic review is whether and to what extent smart city governance can effectively integrate the Internet of Things (IoT), Artificial Intelligence of Things (AIoT), intelligent decision algorithms based on big data technologies, and cloud computing. This is relevant since smart cities place special emphasis on the involvement of citizens in decision-making processes and sustainable urban development. To investigate the work to date, search outcome management and systematic review screening procedures were handled by PRISMA and Shiny app flow design. A quantitative literature review was carried out in June 2024 for published original and review research between 2018 and 2024. For qualitative and quantitative data management and analysis in the research review process, data extraction tools, study screening, reference management software, evidence map visualization, machine learning classifiers, and reference management software were harnessed. Dimensions and VOSviewer were deployed to explore and visualize the bibliometric data.
Bringing Bitcoin ETFs into traditional financial markets is like inviting a digital newcomer to an old-school financial party.This exploration aims to simplify and uniquely address what happens when the digital currency world, with all its buzz and unpredictability, crashes into the steady, established realm of traditional finance.I am especially curious about three things: how smooth trading becomes (or doesn't), how much prices start dancing around, and whether investors start changing their tunes.First up, Trading Ease.Think of this as how quickly you can buy or sell something without causing a big scene in the price department.With Bitcoin ETFs stepping onto the scene, we might see more action in trading spaces because they could pull in a crowd of investors, making everything more fluid.Then again, Bitcoin's wild ways could throw in some twists, challenging the smooth flow we're used to.Next, we've got Price Moves.Bitcoins got a reputation for rollercoaster rides in its pricing.Tossing Bitcoin ETFs into the mix with more traditional setups has us wondering: Are we in for smoother rides, or should we brace for bigger loops?This investigation digs into whether these new ETFs will steady the ship or rock it harder.And then there's Investor Moves.Adding a new move to the financial floor, like Bitcoin ETFs, could really change how investors groove.Will they cling to their classic steps, or are they ready to swing to a digital beat?This part looks at whether investors are going to lean more into the digital craze or stick with their old favorites, and what that means for institutional investors and individual investors alike.But this isn't just about the here and now.This change has bigger implications for the DJs of the financial world (regulators), the party organizers (financial institutions), and the stakeholders.As digital currencies shimmy into the spotlight of traditional finance, getting the rhythm right between innovation, safety, and growth becomes key.In essence, this paper takes a fresh, simplified look at what happens when the digital and traditional financial worlds start collaborating.By breaking down the effects on trading ease, price dynamics, and investment strategies, it aims to offer clear, unique insights for everyone from casual investors to the big shots making the rules.
Chibuikem Michael Adilieme, Rotimi Boluwatife Abidoye, Chyi Lin Lee
Purpose Blockchain is an emerging digital technology proposed and trialled among different built environment professions. The technology has been proposed to introduce transparency, security and trust in property transactions. Despite this proposition, few studies have analysed the barriers and prospects in property valuation, especially in markets plagued by low transparency and a lack of stakeholder trust. Using Nigeria as a case study, this study assesses the barriers and prospects for adopting blockchain technology in property valuation. Design/methodology/approach Data was collected from 180 valuers practising in Nigeria through an online survey, and the data was analysed using mean score ranking and the chi-square (χ2) test of independence. Findings Firstly, there was a low awareness of the application of blockchain technology and an association between the number of valuation jobs executed annually and awareness of the application of blockchain technology. The most important barriers revolved around the knowledge, technical know-how of blockchain and the cost of implementing such technology. The prospects for blockchain are very high as all identified prospects were considered important, with transparency being the most crucial factor for its adoption, followed by the monitoring activities in real time and the permanence in storing records. Research limitations/implications This study's implications lie in the potential benefit of transparency identified for blockchain, which could act as a tool to introduce transparency into valuation industries that battle key issues surrounding transparency and trust. Furthermore, this study can be utilised by policymakers and property industry players in mapping strategies to adopt the beneficial use of blockchain as one among the suite of proptech tools disrupting the property valuation scene, in their practice. This also presents an opportunity to draw upon insights from this study to better prepare for using blockchain in property valuation. Originality/value This study appears to be the first to empirically assess barriers and prospects for blockchain in property valuation practice. It contributes to the literature by identifying key factors that will deter and/or promote the application of blockchain, an emerging and disruptive digital technology.
Blockchain provides a decentralised, tamper-proof and trustworthy distributed database technology that is widely used in finance and economics, IoT and big data. Artificial intelligence (AI) provides a technology that can mimic human intelligence, learn autonomously and automate decision-making, which plays a major role in enhancing productivity, solving complex problems and improving decision-making. The two represent two of the major driving forces in technology today, and their integration is redefining our digital world. The aim of this paper is to explore the integration of these two technologies and the innovations, challenges, and future prospects they bring. First, we trace their history and evolution, introduce the basic characteristics of blockchain and AI, and explain in detail how they work. We then delve into the integration of blockchain and AI, highlighting their importance and significance in areas such as finance, supply chain and healthcare. We analyse the applications and implications of this integration for these areas, as well as the challenges and dilemmas faced, including issues of security, privacy, data leakage, and technical feasibility. Finally, we explore future trends and related work, highlighting the importance of global community collaboration and innovation to realize the potential of blockchain and AI.
Great technological developments are taking place around the world. These developments are taking place in different areas of technology. While some of them take place within the framework of Industry 4.0, others are known by their own names. This study was prepared in this context.Blockchain is one of the emerging technologies. It draws attention with its features such as distributed ledger structure, unalterable and indelible records, low-cost high-speed processing. Blockchain technology is becoming widespread worldwide thanks to these features and more. As it becomes widespread, the areas it affects are also expanding. One of these areas is accounting. Blockchain affects the accounting field from different angles and shapes accounting as it is basically a ledger.Artificial intelligence is among the emerging technologies. Artificial intelligence is known for its ability to mimic human behaviour. The ability to imitate human behaviour in virtual or physical environments is important for accounting science. In this context, the roles and duties of accounting professionals shape the role of Artificial intelligence in accounting auditing.These technologies make it possible to perform activities such as budgeting, purchasing raw materials or finished goods, maintenance and repair scheduling of production machines and near real-time accounting audits at low cost and high speed.
Purpose This study investigates the factors that lead to the adoption of blockchain technology through payment transactions and how this not only affects real estate (RE) and blockchain transparency but also RE performance. Design/methodology/approach Data gathered across RE firms in the United Arab Emirates (UAE) were employed to test the model. The measurement model and structural equation modeling (SEM) were used to test the items and the hypotheses illustrated in the proposed model. Findings Perceived financial benefits, competitive pressure and top manager support were demonstrated to successfully influence blockchain adoption (BA). Despite blockchain’s early stages of development, its impact on RE operations cannot be ignored and should be more objectively examined in order to gain a better understanding of it. UAE blockchain-based companies could be seen as having a competitive advantage that maximizes resource consumption. Originality/value This study introduces the positive influence of blockchain technology on RE payment transactions and may advance information on how blockchain technology has the potential to change the RE sector. The paper finds its significance in exploring how RE payment systems must change to remain competitive in the market amid emerging digitalization trends.
PURPOSE – Financial technology, also known as “FinTech,” has evolved to disrupt nearly every aspect of traditional financial services and it has become increasingly important in the world’s economic system. The main purpose of the study is to explore the relationship between Financial Technology (Fintech) and Entrepreneurial Intentions. It focuses on the impact of specific Fintech innovations such as Crowdfunding, Mobile Payments, Blockchain, Cryptocurrency, and Artificial Intelligence (AI), on Entrepreneurial Finance. The study examines how these Fintech advancements have affected the overall entrepreneurial ecosystem, fostering innovation, supporting startups, and driving economic growth. Using mixed-methods, the research combines qualitative interviews and quantitative surveys to reveal key factors that have completely shaped the entrepreneurial ecosystem in the context of fintech. EXECUTIVE SUMMARY – Financial technology revolution unleashing a wave of technological innovations has transformed the entrepreneurial landscape. Crowdfunding, cryptocurrency, blockchain, mobile payments, and artificial intelligence (AI) play key roles in empowering aspiring entrepreneurs, fueling financial inclusion, and driving economic growth. This report examines the impact of these fintech advancements on entrepreneurial intentions, exploring their benefits, challenges, and future prospects.
This study explores the influence of financial technology (Fintech) innovations, environmental, social, and governance (ESG) reporting, and blockchain technology on financial transparency and accountability through a qualitative literature review. By examining a diverse range of academic papers, industry reports, and case studies, this research aims to provide a comprehensive understanding of how these factors contribute to enhancing financial transparency and accountability in the modern financial landscape. The literature review reveals that Fintech innovations, including mobile banking, peer-to-peer lending, and automated investment services, significantly improve financial transparency by providing more accessible and real-time financial information to stakeholders. These innovations enhance accountability by enabling more efficient and accurate tracking of financial transactions and performance. ESG reporting, which involves disclosing information related to a company's environmental impact, social practices, and governance structures, plays a crucial role in promoting financial transparency. It ensures that stakeholders are informed about the non-financial aspects of a company’s operations, thereby fostering greater accountability and ethical business practices. The integration of blockchain technology further enhances transparency and accountability by offering a decentralized and immutable ledger system that ensures the integrity and traceability of financial transactions. This technology reduces the risk of fraud and corruption, providing a transparent and accountable framework for financial reporting. Despite these benefits, the study also highlights challenges such as regulatory hurdles, the need for technological infrastructure, and concerns over data privacy and security. The findings suggest that the combined use of Fintech, ESG reporting, and blockchain technology has the potential to significantly improve financial transparency and accountability, provided that these challenges are addressed. This research offers valuable insights for financial institutions, policymakers, and technology developers aiming to enhance financial practices through innovative solutions.
Abdelatif Hafid, Maad Ebrahim, Ali Alfatemi, Mohamed Rahouti · 5 authors
The rapid growth of the stock market has attracted many investors due to its potential for significant profits. However, predicting stock prices accurately is difficult because financial markets are complex and constantly changing. This is especially true for the cryptocurrency market, which is known for its extreme volatility, making it challenging for traders and investors to make wise and profitable decisions. This study introduces a machine learning approach to predict cryptocurrency prices. Specifically, we make use of important technical indicators such as Exponential Moving Average (EMA) and Moving Average Convergence Divergence (MACD) to train and feed the XGBoost regressor model. We demonstrate our approach through an analysis focusing on the closing prices of Bitcoin cryptocurrency. We evaluate the model's performance through various simulations, showing promising results that suggest its usefulness in aiding/guiding cryptocurrency traders and investors in dynamic market conditions.
Raymond Wahyudi, Nanik Linawati, Farrell Ionwyn Eduardo
Cryptocurrency investment is a phenomenon that has gained popularity among Indonesian youth. However, the factors that influence their intention to invest in this digital asset class are not well understood. This study aims to identify and evaluate these factors using the Fuzzy Analytical Hierarchy Process (FAHP) method, which can handle uncertainty and ambiguity in decision making. The study applies the Unified Theory of Acceptance and Use of Technology (UTAUT) model as the theoretical framework, and considers six factors: social influence, financial literacy, facilitating condition, performance expectancy, effort expectancy, and hedonic motivation. The results show that social influence, financial literacy, and facilitating condition are the most important factors, while hedonic motivation is the least important. The study also ranks the sub-criteria within each factor according to their relative importance. The findings provide valuable insights for policymakers, investors, and educators in the field of cryptocurrency and blockchain technology.
Cryptocurrency, a relatively new financial innovation, has sparked widespread interest in recent years, particularly among younger demographics such as college students. As digital currencies such as Bitcoin and Ethereum continue to dominate headlines, college students' familiarity and impression of cryptocurrency has become essential for assessing its future adoption and investment opportunities. This study investigates the level of investor awareness, interest, and perception of cryptocurrencies among college students, a demographic that represents the future of technical and financial advancement.College students are often seen as technologically adept and open to new technologies, making them an ideal group for researching cryptocurrency awareness. However, the complexity, volatility, and lack of legal structures surrounding cryptocurrencies have piqued interest while also raising concerns. This study looks at how students comprehend important cryptocurrency concepts such as blockchain technology, decentralized finance (DeFi), digital wallets, and the risks of investing in these digital assets.The findings indicate that, while a considerable majority of college students are aware of cryptocurrencies, their level of understanding differs. Many students have a shallow understanding based on media exposure or peer discussions, with a lesser fraction having participated in actual trading or investment. Factors such as field of study, access to financial education, and socioeconomic status all influence the level of awareness. Students in technology-related professions have a better understanding of the underlying blockchain technology, but those in finance and economics are more aware of the investment opportunities and hazards.Despite increased interest, many students are concerned about the volatility and unpredictability of the bitcoin market. Regulatory uncertainty and the possibility of fraud or hacking are highlighted as major causes for hesitation. Furthermore, the absence of formal financial instruction on bitcoin in college curricula inhibits students' capacity to make sound investment decisions.This study emphasizes the need for improved educational programs to give college students a thorough understanding of bitcoin. Colleges can help students navigate the evolving financial world with greater confidence by addressing knowledge gaps and concentrating on appropriate investment practices. The development of cryptocurrencies as a mainstream asset class may be heavily reliant on the understanding and preparedness of young investors, making it critical to cultivate a well-informed student body.
The exponential growth of digital banking transactions has intensified the demand for robust consensus mechanisms that can ensure transaction integrity while maintaining scalability and security in distributed ledger systems. Traditional Byzantine Fault Tolerant (BFT) consensus algorithms in banking blockchain networks suffer from limited throughput, high computational overhead, and vulnerability to sophisticated adversarial attacks in high-frequency trading environments. This paper introduces a novel Deep Learning-Enhanced Blockchain Consensus Mechanism (DL-EBCM) that integrates adaptive smart contracts with a hybrid Byzantine fault tolerance approach specifically designed for secure banking transaction processing. The proposed methodology employs a dual-layer consensus architecture combining Delegated Proof of Stake (DPoS) with Deep Reinforcement Learning (DRL) optimization for validator selection and transaction validation. The system incorporates Convolutional Neural Networks (CNN) for transaction pattern recognition, Long Short-Term Memory (LSTM) networks for fraud detection, and Generative Adversarial Networks (GAN) for synthetic transaction generation during stress testing. Experimental validation using real-world banking transaction datasets from multiple financial institutions demonstrates superior performance with 99.8% transaction validation accuracy, 2.3 seconds average consensus time, and 15,000 transactions per second throughput while maintaining Byzantine fault tolerance up to 33% malicious nodes. The framework achieves 45% reduction in energy consumption compared to traditional Proof of Work systems and 67% improvement in consensus finality compared to existing BFT implementations. The proposed approach successfully addresses scalability limitations while ensuring regulatory compliance and maintaining cryptographic security standards required for critical banking infrastructure.
Blockchain is revolutionizing the field of financial services by presenting a secure and decentralized framework that enhances efficiency and trust. This framework spans the entire spectrum of finance and financial services, from simple transfers to complex management and regulation. This technology has the potential to reduce the need for intermediaries while also lowering the cost of doing business and potential fraud avenues and fostering greater express transactions. The very design of this open, shared record ensures that all networks have access to the same document, which cannot be altered. Blocks validate transactions, and users have a say over it. Smart contracts provide the most convenient transaction process by eliminating human error and spike earnings. Furthermore, the integration of blockchain in the financial sector confronts several problems. Some of those are dependency, variation, and stability. Nevertheless, this technology makes financial markets more secure, effective, and open which results in new goods and business environments.
The dynamic progression of technology has induced a profound metamorphosis within the realm of commerce, ushering in novel prospects and trials for enterprises spanning diverse sectors. In contemporary times, the rise in non-fungible tokens (NFTs) and the conception of the Metaverse have ensnared the focus of corporate entities and visionary proprietors alike. This article explores the transformation of business frameworks during the era of NFTs and the Metaverse. It delves into traditional paradigms, clarifies the unique characteristics of NFTs, and examines their potential impacts on commerce. This article investigates the convergence of virtual reality (VR), augmented reality (AR), and blockchain technology within the Metaverse. To investigate these transformations, this study undertakes a comprehensive literature evaluation. The findings highlight how NFTs and the Metaverse have introduced new avenues for generating revenue and creating value. These advancements are achieved through the utilization of smart contracts and adaptable strategies that cater to evolving consumer behaviors. This article also addresses significant challenges in this landscape and provides a forward-looking perspective on the anticipated trajectory.