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.
Blockchain is a digital ledger distributed across numerous computers globally, eliminating the need for intermediaries. Platforms such as Ethereum leverage blockchain technology to facilitate not only financial transactions but also Smart Contracts. Running these Smart Contracts incurs gas fees, which are influenced by the complexity of the operations. This research explores various methods to design and organize Smart Contracts to reduce gas usage on the Ethereum network. The study identifies key strategies for optimizing Smart Contract design, resulting in significant reductions in gas costs. These strategies include optimizing data structures, minimizing storage operations, and efficient coding practices. By implementing the proposed methods, developers can create more cost-effective and efficient Smart Contracts, ultimately enhancing the overall usability and sustainability of the Ethereum network.
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, through its secure distributed ledger technology, has been heralded as an important enabler of consumer and business applications. In addition to cryptocurrency, there are many examples of existing and planned implementations of blockchain-enabled systems in organizations, such as in the supply chain. However, what is unclear from the literature, are the mechanisms driving the acceptance of blockchain systems and the extent to which salient models of technology acceptance are capable of explaining adoption behavior. This research employs large-scale meta-SEM analysis using 37,865 respondents from 142 data sets to examine critically a variety of competing models of blockchain technology acceptance. The results identify two new models that help to explain a significant amount of variance in behavioral intention to use blockchain systems, trust-risk model (TRM) and a TRM/UTAUT2 hybrid TRAUT. Thus, although we find support for the standard models of acceptance, the paper suggests that new models incorporating trust and risk are essential in the blockchain context. The models are robust to tests using a variety of moderators of relationships.
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 integration of blockchain technology, specifically smart contracts, to revolutionize supply chain management. By leveraging smart contracts, the flow of products from farmers to consumers is securely recorded and verified on an immutable ledger, bolstering transparency and trust throughout the supply chain. Furthermore, the research addresses blockchain scalability challenges by proposing an adaptive algorithm to adjust gas fees based on network congestion, optimizing block confirmation times and transaction processing efficiency. A robust software architecture is outlined, emphasizing scalability to effectively handle large-scale supply chain operations. Through this interdisciplinary approach, the thesis aims to advance supply chain management practices by harnessing blockchain’s transformative capabilities, laying the groundwork for resilient and efficient supply chain ecosystems in the digital age.
In the realm of environmental data management, ensuring data integrity and accessibility is paramount. This paper presents the implementation of blockchain technology enhanced with Dynamic Smart Contract Interaction (DSCI) to effectively manage NOAA weather and environmental data. The proposed system leverages blockchain’s decentralized nature to secure data, while DSCI facilitates real-time updates, automated processes, and dynamic interactions within the blockchain. This combination ensures data authenticity, integrity, and secure access, providing fishermen with reliable data for strategic decision-making. The system addresses specific challenges in the fisheries sector by integrating NOAA data into a secure blockchain framework, preventing data leakage and manipulation. Key contributions of this study include a detailed explanation of the encryption algorithms and frameworks used, the step-by-step integration process of NOAA data into the blockchain, and quantitative results substantiating the system’s efficiency and robustness. The system’s functionality was rigorously tested through unit, integration, performance, and security testing, demonstrating significant improvements in data management practices, offering enhanced security, transparency, and operational efficiency. Comparative analysis with existing solutions highlights the advantages of the proposed system.
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.
K. E. Purushothaman, N. Ragavendran, S. P. Ramesh, V. Ganesh Karthikeyan · 6 authors
This research explores the potential of blockchain and edge AI to revolutionize smart city planning and management. By incorporating these emerging technologies, cities can address current urban challenges, including traffic congestion, energy management, and data security. This research study highlights the benefits of blockchain, such as simplified processes, reduced costs, enhanced security, and transparency. Additionally, this study reviews the applications of edge AI in smart transportation, focusing on vehicle detection, counting, and identification algorithms. The potential of blockchain technology in smart energy trading, vehicle transfer, and encrypted communication is also discussed. Overall, this research study provides valuable insights for researchers to explore new application areas for blockchain and edge AI in the context of smart cities.
Ticket industry faces persistent challenges including forgery, unlawful resale, and theft. With over half of Norway's population and a significant portion in the USA purchasing tickets online, the need for secure transaction processes is evident. Typically, two layers of trust are involved between the client and the host, leading to complexities and frustrations for consumers. Moreover, certain entities monopolize event sites, potentially engaging in unethical pricing practices. Resale of tickets among participants exacerbates the issue, risking fraudulent or duplicate tickets. Implementing smart contracts on Ethereum blockchain offers a promising solution. This study advocates for leveraging Ethereum's decentralized platform to enhance efficiency, transparency, and security in ticket sales. By doing so, common issues such as fraud, scalping, and counterfeiting can be mitigated, addressing concerns of both buyers and sellers in the ticketing ecosystem.
This paper investigates the integration of blockchain technology into e-procurement, assessing its advantages and challenges. A framework is introduced, encompassing smart contracts, digital identity verification, and consensus mechanisms tailored for procurement needs. Through case studies, blockchain’s transformative impact on trust, fraud prevention, and procurement efficiency is demonstrated. Additionally, the transition to blockchain based e-tendering is explored, promising enhanced transparency, decentralization, and security in procurement processes. The framework not only facilitates cost reduction but also enhances public trust, emphasizing the socio-economic benefits of blockchain adoption in procurement
T. B Sivakumar, E. Angel Anna Prathiba, Shweta Sharma, Rashmi Saket Prasad · 6 authors
Modern finance and HR businesses have challenges in exchanging data due to centralized systems that are subject to hacking and lack transparency. The study proposes employing blockchain technology and machine intelligence (ML) to address these issues holistically. The proposed system enhances integrity and resilience to assaults by utilizing a decentralized ledger for secure data exchange. ML algorithms enable predictive analytics, risk management, and personalized insights. The proposed system outperforms the existing system in terms of accuracy, security, and efficiency. The accuracy of fraud detection increases from 0.75 to 0.90, as does the estimate of staff turnover from 0.80 to 0.95. The proposed system achieves an overall accuracy of 95%, surpassing the existing system's 85%. Blockchain and ML integration can alter data management methods in finance and HR industries, with improved security measures resulting in a risk score of 2 compared to 7 in the existing system.
Financial markets exhibit complex, nonlinear dynamic behavior that is often challenging to interpret using traditional linear analysis methods. Risk assessment and, accordingly, portfolio management are the most important tasks for investors in order to avoid big losses. Gold trading is considered a safe haven, but it shows slow growth. In contrast, bitcoin or cryptocurrency trading is being proliferated. Many established financial institutions, like PayPal and Fidelity, are making it easier than ever for individuals to buy and sell Bitcoin. While Bitcoin trading can be potentially lucrative, it’s crucial to understand the significant risks involved before diving The volatile nature of Bitcoin can be emotionally stressful, leading to anxiety and poor decision-making. High-risk activity like stock trading requires a strong understanding of the market, particularly in high-risk assets like Bitcoin and gold, which demands a deep comprehension of market dynamics and the ability to tolerate volatility. Through this study, we delve into the application of machine learning algorithms to comprehend correlations, causality, and predict volatility in stock trading. Specifically, we focus on analyzing the trading behavior of cryptocurrency (bitcoin) vs. physical assets (gold) in terms of their volatility and comparing them in correlation with the stock index of crude-oil, S&P 500, and the dollar. This structured study aims to shed light on the effectiveness of machine learning algorithms in understanding and predicting volatility in stock trading, with a specific focus on Bitcoin and gold as high-risk assets.
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.
Cryptocurrency is a digital asset created using blockchain technology and it has different properties from money that we have known such as US Dollar, Rupiah, Yen, etc. Right now, people use cryptocurrency as an investment instrument. However, choosing a cryptocurrency as an investment instrument is challenging because investors need to consider many attributes of a cryptocurrency project. Also, the number of cryptocurrencies is growing each day. Currently, there are at least 20,000 cryptocurrencies to choose from. Developing a recommender system can shorten investors' cryptocurrency screening process. The recommendation system uses Knowledge Graph Convolutional Network (KGCN). It is a model that effectively reveals the relationship between items by mining the attributes of the items in the knowledge graph. Thus, KGCN is suitable for creating a personalized recommendation. The cryptocurrency knowledge graph used in the study is based on the cryptocurrency dataset on the CoinGecko website crawled using its API. The output from the system is in the form of the top 3 cryptocurrency recommendations for specific users and AUC evaluation scores. The research results show that KGCN can provide relevant recommendation results based on investor's preferences up to 17.55% better evaluation scores compared to other models such as RippleNet.
The rapid advancement of smart contract innovation in online commerce has initiated significant discussions on enhancing the effectiveness of digital transactions. This research investigates the complexities of smart contract innovation within Indonesia’s e-commerce landscape, focusing on issues such as inaccuracies and behaviors that could negatively impact buyers. The primary objective is to provide clarity on legal matters in Indonesia’s evolving legal and technological environment. Employing a normative juridical approach, the study analyzes current laws and regulations to ensure the protection of participants in online transactions. Furthermore, it explores the concept of Cyberpreneurship using internet media for business—aiming to identify new business opportunities and improve e-commerce outcomes. Structural Equation Modeling (SEM) is utilized to understand the relationships among variables related to smart contracts and e-commerce. The findings reveal that smart contract innovation (SCI) significantly affects cyberpreneurship (CP) with an estimated parameter of 0.45 (t-value = 4.50, p < 0.001). Legal certainty (LC) also significantly affects CP with an estimated parameter of 0.30 (t-value = 3.75, p < 0.001). Furthermore, CP has a positive and significant impact on e-commerce efficiency (EE) with an estimated parameter of 0.60 (t-value = 6.67, p < 0.001). These results indicate that smart contracts improve transaction speed, reduce costs, and ensure legal protection, thereby fostering a more secure and reliable e-commerce environment. This research aspires to contribute to the development and regulation of e-commerce in Indonesia and serve as a foundation for future studies. By addressing the legal and technological challenges, the study aims to provide recommendations for policymakers and business practitioners to enhance the adoption and implementation of smart contracts in e-commerce, ultimately contributing to a more robust and efficient digital economy.
Electronic Medical Records (EMRs) offer significant benefits but are vulnerable to security breaches. Blockchain technology, with its inherent security, transparency, and decentralization, presents a promising solution for protecting sensitive patient data. This research proposes a blockchain-based EMR system that employs private keys generated using the SHA256 algorithm for enhanced security. By storing medical records as bytecode, we aim to create an immutable and tamper-proof record-keeping system. This approach has the potential to revolutionize healthcare data management and ensure patient privacy.
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.