Jan 1, 2024·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
This study investigates ownership of blockchain-based digital assets in a decentralized metaverse platform enabled by Web3 and built on blockchain technology. Using the dual-process model of psychological ownership, the research examines factors influencing individuals' desire for ownership in this context. Through fsQCA analysis, necessary conditions and configurations driving ownership patterns are identified. Findings reveal a substitutive relationship between Transfer rights and Voting rights, as well as between Control usage and Voting rights. Additionally, a complementary relationship is observed between the presence of Self-investment and absence of Trade as core conditions within configurations. Notably, in the absence of Profits and Trade, possessing Transfer rights or Voting rights plays a crucial role in driving individuals to acquire higher levels of blockchain-based digital asset ownership. High profits are also highlighted as a motivator for digital asset ownership. These findings shed light on the psychological dynamics of ownership in decentralized metaverse platforms and DAOs.
Cryptocurrencies experienced a huge surge whose value reached more than US $ 191 million or Rp. 2.7 trillion. Interestingly, almost all types of cryptocurrencies do not have an underlying asset as a common underlying asset in ordinary investments. Bitcoin and Ethereum claims that its underlying asset is the coin miner charges from the amount of hardware and electricity used in the transaction. Tether and USDC claim that their underlying assets are in US dollars. This article examines Islamic law regarding the underlying assets in the form of coin mining fees and US Dollars. The questions that arise are, how is the study of Islamic law regarding the underlying asset in the form of coin mining fees and US Dollars? Furthermore, the ideal pattern of a cryptocurrency scheme that includes assets in the form of tangible goods refers to manafiul a’yan? This research uses the gate of legal philosophy approach, looks at the business scheme in terms of values and principles and then provides legal conclusions based on that assessment. From the research conducted, first, the underlying asset of coin mining costs cannot be said to be an underlying asset that is truly economically useful for coin owners, except for the technology access costs which are clearly experienced by all technologies. Second, the underlying asset in the form of US Dollars has clearer benefits, but this is contrary to Islamic law. Third, for the underlying asset in the form of tangible goods, ownership must always be included in every coin purchased.
The rapid digital transformation in fund accounting has reshaped how financial institutions, asset managers, and regulatory bodies manage operational compliance, transparency, and efficiency. Emerging technologies such as cloud computing, robotic process automation (RPA), artificial intelligence (AI), and distributed ledger technologies (DLT) have automated key accounting workflows, reduced manual errors, and improved data accuracy in fund valuation and reporting. This review critically examines how digital transformation initiatives are redefining fund accounting processes—ranging from transaction reconciliation to compliance monitoring and investor reporting—within a framework of evolving global regulatory standards such as IFRS, GAAP, and MiFID II. Furthermore, it explores how predictive analytics and integrated enterprise resource planning (ERP) systems enhance operational resilience and enable real-time risk assessment. Challenges related to cybersecurity, data governance, and interoperability are also analyzed, with emphasis on how organizations are balancing technological innovation with regulatory obligations. By synthesizing current academic and industry perspectives, the paper provides a comprehensive view of the transformative potential of digital technologies in improving transparency, accountability, and governance in fund accounting. The review concludes with recommendations for future research and policy frameworks that can strengthen digital compliance ecosystems across the financial sector.
Fraudulent activity detection within blockchain networks has become a critical concern due to the widespread adoption of decentralized technologies in financial and digital systems. The paper introduces a system that uses Blockchain and Machine Learning (ML)to strengthen the security of banks. Employing the services of the Ethereum blockchain dataset, the model applies a comprehensive methodology involving data preprocessing, feature engineering, Z-score normalization, and stratified data splitting. Genetic Algorithm-optimized Support Vector Machine (GA-SVM) and Artificial Neural Network (ANN) are constructed and tested, and their results are then compared with those from Generalized Autoregressive Conditional Heteroskedasticity (GARCH) and Convolutional Neural Network (CNN) models. Metrics of accuracy by using Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) as measures. It was found that the GA-SVM model achieved the best results compared to other models, with MAE at 0.1032 and MAPE at 4.6938 on test data, which confirms its usefulness in real-time fraud detection. When the model connects with smart contracts, it helps prevent fraudulent activities and supports both transparency and good operations in blockchain-based finance.
Two of the most exciting advancements concerning the internet could be web3 and the metaverse.In addition to affecting how we interact with each other and with institutions over the internet, this advancement could also have an impact on how assets are traded, how we invest, and how we borrow.Some key components of web3 are already making some waves, some big and some peculiar, in finance.These components include decentralized autonomous organizations (DAOs) and decentralized finance.
Existing big-tech platforms have controlled the sovereignty of digital services and user data, limiting the opportunities for users to experience platforms.These platforms' control policies were no exception in the content area of the platform.Users can only engage with content by viewing, commenting, emoticons, and sharing.Users were limited to engaging with content in the functions and areas designated by the platform, which meant they could not interact with opinion leaders or content creators equally.Consequently, concepts of Web 3 and MyData have emerged with the idea that the sovereignty of platform users should be restored to the user, not the platform.However, many papers on blockchain and smart contracts that can implement these concepts are mostly engineering or focused on laws such as content copyright.This study examines two purposes as a case study of qualitative research methods for a content platform named A3I®.First, this study identified the feasibility of implementing a blockchain-based content platform with universal value.It refers to the universal value that anyone can access information (data) securely and transparently in a Web 3.0 environment, including the concept of MyData, which empowers users to control their data.Second, this study highlighted that the Article Value Evaluation Mechanism (AVEM), including reward and revenue sharing systems, can enhance digital content activation through automatic payment programs of smart contracts in the platform.Furthermore, the study found that A3I platforms based on blockchain and smart contracts have stronger performance on technical and user-centric factors than other platforms without these technologies.In addition, the A3I platform with innovative technologies and AVEM shows better digital content activation by increasing "feedback frequency" than other platforms that increase "content frequency."Therefore, this study has academic and social significance by reflecting the universal values of Web 3.0 in platform design.It also has industrial significance by presenting a feasible blockchain platform business model.
Vignesh Ramamoorthy H, Spelmen Vimalraj Santhanam, V. Vibithrapriya, R. G. Harshini
Nowadays the quest for electronic payments has created a huge ambit among academicians and businesspeople. At the same time, transactions are repressed because of the intervention of third parties. To overcome this situation, the great as well as the puzzling imposter arose which is now the area of interest called cryptocurrency. Bitcoins, Ethereum, and ripple are some embodiments of cryptocurrency. Investors do not always have a bed of roses with cryptocurrency as the frequent oscillation of prices is hard to forecast. The paper here deals with the forecasting of cryptocurrency prices by using data mining algorithms such as Bagging, K-NN, Linear Regression, and Support Vector Machine. The outcome specifies the accuracy value gained from the cryptocurrency forecasting model from which we can predict the price of the cryptocurrency.
Dewi Khornida Marheni, Jenny Jenny, Isnaini Nuzula Agustin
Technological developments are increasing rapidly. This encourages increase the number of investors, especially in cryptocurrency. Investment decision considerations are influenced by investor behavior, including attitude, subjective norms, herd behavior, overconfidence, perceived risk, financial literacy, and investment intention. The purpose of this study is to determine the factors of financial behavior that influence investment decisions. The sampling technique used is snowball sampling by distributing questionnaires to Indonesian investors who are currently/already using cryptocurrency. Data was analyzed using the PLS-SEM method. The samples used as test material were 274 respondents who are currently or have used cryptocurrency. The results state that attitude, overconfidence, financial literacy, and investment intentions have a significant influence on investment decision variables. Future research is expected to be able to add other variables. The object of research used by the author is only in the territory of Indonesia. Therefore, the authors suggest that it can expand the object of research so that it can strengthen the results of the research. Most of the previous studies used quantitative methods in obtaining data. Thus, future research is expected to be able to expand the object of research so that it can strengthen the results of the research and use mixed methods, quantitative and qualitative methods (interviews and questionnaires).
The metaverse is undergoing a transformative shift with the introduction of Non-Fungible Token (NFT) avatars, offering users unique and tradable digital identities. This research paper explores the significance of NFT avatars in the metaverse, emphasizing their role in redefining digital ownership, self-expression, and user engagement. Additionally, the paper delves into the issues and challenges associated with the promotion of NFT avatars, considering factors such as market dynamics, technological barriers, and user adoption. This paper is considering different NFT that are developed by various NFT Brands. These NFT could be used in future in Metaverse. At the end of research paper a case study of “Sizzling monster” NFT has been made. This NFT has very limited supply and several NFT brands have bought it at initial stage from Young Parrot Platform.
Kuo-Hsien Lee, Wen-Hsien Tsai, Cheng-Tsu Huang, Jerry Tao · 8 authors
By using the machine learning of artificial intelligence to explore the application business opportunities of the Metaverse in the MMORPG (Massively Multiplayer Online Role-Playing Game) interactive game market, we study the supply and demand laws of buyers and sellers at the market economy level, future trends, and business opportunities. The feasibility of its new products and services is explored under a pragmatic, cooperative model of the game community platform “Key to the Desert” case for the application level and business opportunities of Taiwan’s Metaverse markets. Online and offline integration (OMO; Online Merge Offline), precision marketing, and the customer management data platform (Customer Data Platform) are also explored in the application business opportunities of the Metaverse market. By combining the NFT (Non-Fungible Token) Monopoly game and MMORPG interactive games, we study the laws of supply and demand of buyers and sellers at the market economy level to provide third-party payment, electronic payment, mobile payment, and other transaction method certifications such as NFT (Non- Fungible Token). We also evaluation the future and security issues of cryptocurrency.
This study explores the relationship between a company’s cryptocurrency holdings and its sustainable performance. The study also looks into how factors such as external financial crises, internal financial conditions, and cash shortages affect the link between possession of cryptocurrencies and company sustainable performance. The empirical findings showed that while holdings of cryptocurrencies may generally have a negative impact on a company’s performance, cryptocurrency holdings by businesses during an external financial crisis such as COVID-19 may have a positive relationship with the sustainable performance of the business. The findings support earlier research that suggested cryptocurrency ownership can have both positive and negative effects on a company, but that it can also boost firm performance in times of external financial hardship. By demonstrating a higher favorable connection for larger amounts of cryptocurrency holdings, these results can be further supported. The implications of holding cryptocurrencies on internal and external financial strain vary. Regarding internal financial issues, it was discovered that keeping cryptocurrencies had a favorable impact on sustainable performance for financially healthy businesses. It was also demonstrated that the company’s cryptocurrency holdings, which it keeps despite its cash shortage, had a detrimental impact on performance. Even in such a case, it was confirmed that holding cryptocurrencies has a favorable impact on a company’s sustainable performance when it is in good financial standing. The findings imply that, despite the unavoidable external financial challenges, the internal financial condition must be healthily maintained if a business engages in cryptocurrency.
The cryptocurrency market, specifically the non-fungible token (NFT) market, has been gaining popularity with the rise of social finance, game finance, metaverse, and web 3.0 technologies. With the increasing interest in cryptocurrency, it is essential to develop a comprehensive understanding of the market dynamics to aid investment decisions. This paper aims to analyze the impact of news sentiment on the prices of two cryptocurrencies, Green Satoshi Token (GST) and Green Metaverse Token (GMT). The sentiment analysis model used in this study is Finance Bidirectional Encoder Representations from Transformers (FinBERT), a pre-trained deep neural network model designed for financial sentiment analysis. Additionally, we introduce the use of the Extreme Gradient Boosting (XGBoost) algorithm to evaluate the sentiment result on the model’s performance. The study period covered from March 2022 to April 2022, and the sentiment score of the result generated by FinBERT on crypto, stock market, and finance news was found to be correlated with the prices of GST and GMT. The findings suggest that the sentiment score of GST reflects changes in the price earlier than GMT. These findings have significant implications for decision-making strategies and can aid investors in making more informed decisions. The research highlights the importance of sentiment analysis in understanding the market dynamics and its potential impact on the prices of cryptocurrencies. The use of FinBERT and XGBoost algorithms provides valuable insights into market trends and can aid investors in making informed decisions.
Blockchain technology has revolutionized the way in which financial transactions are conducted. It has made possible secure financial management and digital transaction systems that are faster, more secure, and more reliable than traditional payment methods. Blockchain technology offers increased efficiency, trustworthiness and transparency to its users. The Blockchain works by creating a shared, distributed ledger of transactions. Each transaction is cryptographically secure and immutable, and all participating nodes have identical copies of the ledger. This ensures that transactions are traceable and secure, eliminating traditional problems such as double spending or fraudulent activities. Through the integration of Blockchain, the system provides transparency, prevents fraud, and ensures accountability. The research focuses on optimizing performance by reducing processing times and transaction costs, while maintaining scalability and flexibility. Additionally, the system facilitates auditing and compliance processes, while promoting financial inclusion by providing access to unbanked individuals. The proposed system’s contributions lie in its novel approach to secure financial management, utilizing Blockchain’s features to address the challenges of modern digital transactions.
Decentralised Finance or DeFi has emerged as a transformative and disruptive force within the financial industry, offering innovative financial services powered by blockchain technology and smart contracts. This paper provides in-depth knowledge of DeFi, its evolution, applications, and their adoption. It identifies the opportunities brought about by DeFi, comparing it with the traditional CeFi (Centralized Financial) system, including financial inclusion, transparency, and programmable money. It highlights the potential of applications of DeFi for decentralized lending, decentralized exchanges, and yield farming as innovative and promising avenues within the DeFi space. A SWOT analysis comparing DeFi and CeFi was performed to delve into the strengths, weaknesses, opportunities, and threats associated with DeFi. This study explored the intricate challenges and inherent risks involved in the adoption of DeFi applications, offering insights into the hype, fear, and apprehensions among governments and the masses regarding its adoption. The findings offer a nuanced understanding of the current state of DeFi, providing valuable insights for researchers, policymakers, and industry practitioners.
<strong>Abstract: </strong>This paper aims to map the existing literature on risk and return management, in the crypto-currency portfolio to understand various strategies and methods investors use. This paper conducts a systematic review of the research done between 2012 and 2022 in the area of risk and return management in cryptocurrencies. In this paper PRISMA framework for the systematic literature review was used; 257 research articles specific to crypto-currency and risk and return were identified through a structured keyword search on the Scopus Database. It was observed that most of the authors had preferred the Markov-switching regime and support vector machines (SVM) for better risk management in crypto-currency. It was observed that the risk associated with one crypto is not the same as other currencies, and the magnitude of return also varies. So, most of the authors have favoured the mixed model of cryptocurrency to mitigate the risk and multiply the profits. Volatility in the cryptocurrency market is very high as compared to other financial markets but has improved due to leverage effects and volatility persistence. The additional impression of this article is that it has made a collective and comparative analysis of risk and return in cryptocurrency. However, the research was limited to only a few factors, databases, and timeframe, and many other factors may be the avenues for the upcoming studies. <strong>Keywords</strong>: Cryptocurrency, Portfolio, VOSviewer, Bitcoin, Risk and Return
In recent times, the utilization of cryptocurrencies in the Metaverse has garnered increasing attention, with the advent of blockchain technology and the surge in popularity of the Metaverse. This investigation endeavors to ex-amine the implementation of cryptocurrencies in the Metaverse, as well as its influence on the cryptocurrency market and the progression of the Metaverse. This study adopts the method of combining literature review and case analysis, first sorts out the application scenarios of cryptocurrencies in the Metaverse, including transactions, games, virtual assets, etc.; then sum-marizes the application scenarios of cryptocurrencies in the Metaverse through case analysis Advantages and challenges, including decentralization, security, traceability, etc.; Finally, the development trend and prospect of cryptocurrency in the metaverse are discussed, and the impact of this appli-cation on the cryptocurrency market and the development of the metaverse is analyzed. The results of the study show that cryptocurrencies have great application potential in the Metaverse. First of all, the decentralized nature of cryptocurrencies can guarantee the security and traceability of transac-tions and assets in the Metaverse. Secondly, the circulation and use of cryp-tocurrencies can also promote economic development and prosperity in the Metaverse. However, the application of cryptocurrencies in the Metaverse al-so faces many challenges, including transaction speed, user experience, and compliance.
In the evolving landscape of the insurance industry, the integration of advanced technologies offers transformative potential. This research explores the amalgamation of Blockchain technology, specifically through the Hyperledger platform, with AI-enhanced smart contracts to address prevailing challenges in the insurance sector. Utilizing a mixed-methods approach, the efficacy of Hyperledger-based systems in streamlining insurance operations and the augmentation of smart contracts with AI algorithms for improved automation and decision-making were examined. Preliminary findings indicate that the combined application of Hyperledger and AI-driven smart contracts can significantly enhance transparency, reduce fraudulent claims, and optimize risk assessment processes. However, the implementation of these technologies also presents certain technical and regulatory challenges. This study provides a foundational understanding for stakeholders in the insurance domain, emphasizing the strategic advantages and potential pitfalls of embracing this technological convergence.
The foundation of smart cities is based on an autonomous and decentralized architecture, which consists of sophisticated information and communication technologies (ICT) in convergence with technology enabled solution to improve the business management process in industry 4.0. This study tends to examine the adoption of blockchain technologies (DLT) in the human resource management (HRM) of organizations in building solutions for IOT (Internet of things) smart cities. The current study explores a unique set of factors selected from the extensive literature and acquired information from fifteen experts having significant experience of blockchain technology in their respective organizations. An integrated fuzzy analytic hierarchy process (F-AHP) is applied to prioritize the identified success factors. Further, the modified decision-making trial and evaluation laboratory (M-DEMATEL) method is utilized to represent the complicated causal relationships among different sub-factors on blockchain-HRM integration. The findings show the application of blockchain will foster a paradigm change in IOT based smart communities, where recruiters verify the candidate credentials including education, skills, and work experience. The payroll managers would determine the more effective way to make work less complex and moderate, enabling timelier payments to global employees. Furthermore, DLT would enhance the employee learning records and update the real-time information in HRM database technologies. Thus, providing a detailed guide for future Industry 4.0 developers about how blockchain can improve the next generation of industrial applications. The developed method can help the decision-makers and provide a foundational view to examine the benefits of implementing blockchain technology in the HRM setting of an organization before they choose to integrate in order to enhance Industry 4.0 technologies. This research will be a novel attempt to synthesize the key factors and subfactors about technology enabled solution within the intelligent HRM process, shedding light to rethink HRM strategies to incorporate blockchain technology in organizations.
This research was conducted with the aim of knowing whether there is an effect of risk tolerance on cryptocurrency investment decisions. In this study, data analysis used a simple regression analysis method using the SPSS Statistics 25 application. Data sources used primary and secondary data while data types used quantitative data with an associative approach. The research population that was conducted by the researchers were active and inactive investors in cryptocurrency investing with a sample of 96 people from a small number of sub-districts across Indonesia. With data collection techniques through a questionnaire using a Likert scale. Based on the results of the t test, there is a significant influence of the Risk Tolerance variable on Cryptocurrency Investment Decisions
BACKGROUND Healthcare insurance fraud is on the rise in many ways, such as falsifying information and hiding third-party liability. This can result in significant losses for the medical health insurance industry. Consequently, fraud detection is crucial. Currently, companies employ auditors who manually evaluate records and pinpoint fraud. However, an automated and effective method is needed to detect fraud with the continually increasing number of patients seeking health insurance. Blockchain is an emerging technology among businesses and is constantly evolving to meet their needs. With its characteristics of immutability, transparency, traceability, and smart contracts, it demonstrated its potential in the healthcare domain. In particular, smart contracts are essential to reduce the costs associated with traditional methods, which are mostly manual, while preserving privacy and building trust among healthcare stakeholders, including the patient and the health insurance networks. However, with so many blockchain options available, selecting the right one for healthcare insurance can be difficult. OBJECTIVE This paper aims to develop and implement smart contracts for detecting healthcare insurance fraud efficiently. Therefore, we provide a taxonomy of fraud scenarios and implement their detection using a blockchain platform that is suitable for healthcare insurance fraud detection. To automatically and efficiently select the best platform, we propose and implement a decision-map-based recommender system. For the aim of developing the recommender system, we propose a taxonomy of 102 blockchain platforms. METHODS We developed and implemented smart contracts for 12 fraud scenarios that we identified in the literature. We used the two top blockchain platforms selected by our proposed decision-making map-based recommender system, which is tailored for healthcare insurance fraud. In addition, we present a taxonomy of 102 blockchain platforms classified according to the application domains for which they can be used. RESULTS The developed decision-map-based recommender system demonstrates that Hyperledger Fabric is the best blockchain platform for identifying healthcare insurance fraud. We demonstrate the effectiveness of our recommender system by comparing the performance of the top two platforms selected by our system. The blockchain platforms taxonomy that we created for this revealed that 59 blockchain platforms are suitable for all application domains, 25 for financial services, and 18 for various application domains. We designed and implemented fraud detection based on smart contracts. CONCLUSIONS Our decision-map recommender system, which is based on our proposed taxonomy of 102 platforms, automatically selected the top two platforms, which are Hyperledger Fabric and Neo, for the implementation of healthcare insurance fraud detection. Our performance evaluation for the two platforms indicates that Fabric surpassed Neo in all performance metrics, as depicted by our recommender system. We provided an implementation of fraud detection based on smart contracts.
This paper examines factors affecting the adoption of cryptocurrency across 158 countries worldwide. To this end, we collected cryptocurrency adoption data from Chainalysis’s reports and macroeconomic data from the World Development Indicators platform. We find that greater import volumes, larger population size, more sufficient levels of the labor force, higher unemployment rate, and a higher level of electricity access are associated with a greater level of cryptocurrency adoption. On the other hand, a higher level of government spending and a greater level of domestic savings are associated with a lower level of cryptocurrency adoption. In addition, we also find that the population size and level of the labor force have a negative impact on the three subcomponents of the cryptocurrency adoption index including (i) centralized service value received (CeFi); (ii) the volume of exchange trading (P2P); and (iii) the received DeFi value (DeFi). We find that while the import volumes and level of electricity access have an opposite relationship with the centralized service value received and the DeFi value received, GDP has a negative effect on the DeFi value received. Meanwhile, greater government spending and higher domestic savings are associated with a greater level of exchange trade volume P2P. In terms of urbanization, whereas it shows a positive impact on the exchange trade volume P2P, it has the opposite effect on the DeFi value received.
Poor payment practices are perceived as one of the biggest challenges facing the construction industry. Since payments are issued according to project contract terms, the project's cash flow is inherently affected by the contract and how parties fulfill their obligations. This research proposes a framework for payment automation in construction projects to achieve smart construction contracts. Payments are automatically issued upon satisfying contract conditions using blockchain. Cryptocurrency is proposed to be utilized in the framework to execute the contract terms with no need for a third party to process project payments. 5D BIM is used to model the geometry of buildings and visualize project progress together with payment status using Autodesk Revit, Navisworks, and Primavera P6. The developed framework has the potential to reduce the consequences of poor payments. An actual case study for a construction project in Cairo, Egypt is worked out to demonstrate the main features of the proposed framework. The results of the case study reveal that project cash flow is secured and payments are instantly issued. Moreover, electronic records of payments are kept on the blockchain.
Cryptocurrencies have emerged as a popular investment option, characterized by their high volatility and potential for significant price fluctuations.The ability to accurately predict cryptocurrency prices is crucial for investors to make informed decisions.In this research paper, we conduct a comprehensive comparative analysis of three widely used forecasting models -Long Short-Term Memory (LSTM), Autoregressive Integrated Moving Average (ARIMA), and Linear Regression -for cryptocurrency price prediction.We evaluate and compare the performance of these models using historical cryptocurrency data, considering various evaluation metrics and scenarios.