Search Results (68)

This paper introduces a novel multi-objective optimization framework for sustainable portfolio rebalancing under uncertainty. The model simultaneously targets return maximization, downside risk control, and liquidity preservation, addressing the complex trade-offs faced by investors in volatile markets. Unlike traditional static approaches, the framework allows for dynamic asset reallocation and explicitly incorporates nonlinear transaction costs, offering a more realistic representation of trading frictions. Key financial parameters—including expected returns, volatility, and liquidity—are modeled using interval arithmetic, enabling a flexible, distribution-free depiction of uncertainty. Risk is measured through semi-absolute deviation, providing a more intuitive and robust assessment of downside exposure compared to classical variance. A core innovation lies in the behavioral modeling of investor preferences, operationalized through three strategic configurations, pessimistic, optimistic, and mixed, implemented via convex combinations of interval bounds. The framework is empirically validated using a diversified cryptocurrency portfolio consisting of Bitcoin, Ethereum, Solana, and Binance Coin, observed over a six-month period. The simulation results confirm the model’s adaptability to shifting market conditions and investor sentiment, consistently generating stable and diversified allocations. Beyond its technical rigor, the proposed framework aligns with sustainability principles by enhancing portfolio resilience, minimizing systemic concentration risks, and supporting long-term decision-making in uncertain financial environments. Its integrated design makes it particularly suitable for modern asset management contexts that require flexibility, robustness, and alignment with responsible investment practices. Full article

Digital agriculture has rapidly developed in the last decade in many countries where the share of agricultural production is a significant part of the total volume of gross production. Digital agroecosystems are developed using a variety of IT solutions, software and hardware tools, wired and wireless data transmission technologies, open source code, Open API, etc. A special place in agroecosystems is occupied by electronic payment technologies and blockchain technologies, which allow farmers and other agricultural enterprises to conduct commodity and monetary transactions with suppliers, creditors, and buyers of products. Such ecosystems contribute to the sustainable development of agriculture, agricultural engineering, and management of production and financial operations in the agricultural industry and related industries, as well as in other sectors of the economy of a number of countries. The introduction of crypto solutions in the agricultural sector is designed to create integrated platforms aimed at helping farmers manage supply lines or gain access to financial services. At the same time, there are risks of illegal use of computing power for cryptocurrency mining—cryptojacking. This article offers a thorough risk assessment of cryptojacking attacks on endpoint systems, focusing on identifying critical vulnerabilities within IT infrastructures and outlining practical preventive measures. The analysis examines key attack vectors—including compromised websites, infected applications, and supply chain infiltration—and explores how unauthorized cryptocurrency mining degrades system performance and endangers data security. The research methodology combines an evaluation of current cybersecurity trends, a review of specialized literature, and a controlled experiment simulating cryptojacking attacks. The findings highlight the importance of multi-layered protection mechanisms and ongoing system monitoring to detect malicious activities at an early stage. Full article

Cryptocurrencies have gained global recognition, yet their rapid expansion is accompanied by significant environmental concerns due to their energy-intensive operations. This study employs novel system thinking and system dynamics approaches to examine the impact of cryptocurrencies on energy use, water consumption, and carbon emissions. The findings underscore the significant negative environmental impact resulting from cryptocurrency mining. According to our results, in 2023, the water consumption and carbon emissions of cryptocurrencies amounted to 1859 × 10⁶ m³ and 90.6 × 10⁶ tons CO₂e (0.25% of global CO₂ emissions), respectively, linked to the consumption of 119.7 × 10⁶ MWh of electricity (0.5% of global electricity consumption). To provide context, this volume of water could fulfill the basic drinking water and sanitation needs of a global population that lacks access. Similarly, the electricity consumption equates to supplying a country like Argentina, which has a population of nearly 46 million. Without intervention, these figures are projected to increase sixfold by 2030. We recommend the adoption of renewable energy curtailment for Proof-of-Work cryptocurrency mining. Alternatively, technologies like the Pi network, based on the Stellar Consensus Protocol, offer a sustainable and energy-efficient solution. Full article

As cryptocurrency transactions continue to grow, detecting scams within transaction records remains a critical challenge. These transactions can be represented as dynamic graphs, where Neural Network Convolution (NNConv) models are widely used for detection. However, NNConv models suffer from model decay due to evolving transaction patterns, the introduction of new users, and the emergence of adversarial techniques designed to evade detection. To address this issue, we propose an automated, periodic hyperparameter optimization method based on proximal policy optimization (PPO), a reinforcement learning algorithm designed for dynamic environments. By leveraging PPO’s stable policy updates and efficient exploration strategies, our approach continuously refines hyperparameters to sustain model performance without frequent retraining. We evaluate the proposed method on a large-scale cryptocurrency transaction dataset containing 2,973,489 nodes and 13,551,303 edges. The results demonstrate that our method achieves an F1 score of 0.9478, outperforming existing graph-based approaches. These findings validate the effectiveness of PPO-based optimization in mitigating model decay and ensuring robust cryptocurrency scam detection. Full article

Cryptocurrencies are decentralized digital financial services that do not physically exist in the world of tangible products and goods, and therefore purportedly offer some positive environmental sustainability features. However, since they are based on blockchain technology, which requires a relatively large input of energy, their climatic impact is not benign. Furthermore, they are very volatile and characterized by low levels of transparency and control, thus creating some negative economic and social sustainability effects. Stablecoins, which are a pegged type of cryptocurrency, exhibit much less volatility and have higher levels of management and interoperability. This raises the following question: are stablecoins more sustainable compared to other cryptocurrencies? To explore this, a sustainability assessment was conducted, comparing cryptocurrencies and stablecoins across environmental, social, and economic dimensions while identifying the key characteristics of sustainability. It was found that stablecoins can mitigate the economic and social risks associated with cryptocurrencies and thus increase their overall sustainability. Moreover, since stablecoins are managed and governed to a greater extent, a key consideration in their development is the selection and implementation of more appropriate mechanisms that can reduce energy use and enhance sustainability. Finally, stablecoins offer more effective—and not just more efficient—solutions, based on value co-creation between several providers and a customer. Full article

This article conducts a comprehensive bibliometric analysis of 182 papers to trace the progression of research on cryptocurrency taxation. The study highlights prevailing patterns, influential contributors, and collaborative networks by utilising data from Scopus and the Web of Science Core Collection from 2002 to 2023. The findings underscore an interdisciplinary character, encompassing studies in legal frameworks, fiscal policy, economics, and technology. By employing analytical tools such as VOSviewer 1.6.20, Bibliometrix 4.0 and Microsoft Excel, the study identifies key themes and concepts focused on four main themes: international tax frameworks and regulatory variations, classification and reporting of crypto-related income, tax implications for emerging crypto segments, and issues surrounding compliance and enforcement. Tax treatment differs based on jurisdiction. Direct taxation may be levied as capital gains, income, or profit tax. Although cryptocurrency exchanges are not subject to value-added tax, intermediary services offered by platforms might incur this indirect tax. The insights generated are valuable for policymakers, scholars, and professionals aiming to comprehend the relationship between cryptocurrency and tax regulation. A limitation of the study is its exclusion of sources beyond the established timeframe. Given the fast-paced changes in cryptocurrency tax regulation, ongoing updates are crucial to capturing the full scope of this evolving field. Full article

Cultural organizations, such as museums, increasingly seek innovative ways to enhance their financial sustainability and attract diverse, global audiences. Implementing cryptocurrency payments and DeFi systems offers these institutions an opportunity to modernize their operations, streamline transactions, and boost digital marketing efforts, aligning with the growing demand for decentralized financial solutions. Using statistical analyses such as correlations and simple linear regression (SLR) models, combined with AnyLogic modeling, this study examines how integrating DeFi systems, including cryptocurrency payments, can improve the sustainable management of these institutions. The findings suggest that by adopting DeFi technologies, museums can enhance their digital marketing efficiency, increase engagement, and attract a broader audience. The analysis reveals that museums accepting cryptocurrency benefit from broader digital marketing factors, with referral and branded traffic significantly driving organic search, whereby paid social traffic correlates positively with paid strategies, and the authority score is largely influenced by organic traffic. In contrast, non-crypto museums rely more heavily on referral traffic and organic costs, with narrower marketing influences affecting their performance. Full article

Fintech prioritizes the progression of issues related to environmental conservation and the consequences of climate change. This study is among the first investigations exploring the relationship between fintech and sustainable energy. It presents potential financial models that might be developed to assist companies in remaining operational via the use of renewable and clean energy sources. We employ a bibliometric analysis as the statistical methodology to address the study topic. We extract bibliometric data from the Scopus database employing the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) approach, thereafter analyzing the data with the R statistical programming language and the bibliometric applications Biblioshiny and VOSviewer. The results of the research indicate that fintech companies are committed to achieving carbon neutrality and investing in strategies such as environmental, social, and corporate governance (ESG) which may help them reduce their carbon footprint and enhance their eco-efficiency. In contrast to the United Kingdom, which is frequently regarded as the world’s preeminent financial center, Chinese fintech enterprises appear to demonstrate a more fervent dedication to the improvement of their ecological transition. However, the results, ultimately, emphasize the transition of fintech to an alternative paradigm, namely greentech. Greentech is a new fintech-dependent paradigm which will help cryptocurrencies and fintech reduce their environmental impact and promote carbon-neutral financial institutions via investment. Greentech aims to decarbonize the financial industry by investing in renewable resources and clean energy, therefore enhancing the sector’s environmental sustainability. Full article

(1) Background: Cryptocurrencies have a substantial environmental impact. In particular, the mining procedure that is employed to produce and finalize the transaction is energy-intensive and generates carbon emissions. Consequently, the objective of the present investigation is to investigate the function of cryptocurrencies in a sustainable development. This research specifically investigates the function of stablecoins, a novel subject in finance and academia that has the potential to foster a sustainable business environment. (2) Methods: A bibliometric analysis was performed using the R statistical programming language together with the bibliometric tools Biblioshiny and VOSviewer to fulfill the research objective. Data were obtained from the Scopus database, and their selection was completed using the PRISMA methodology. (3) Results: The results of the current research highlight the crucial role of stablecoins in promoting an alternative decentralized financial sector, offering a unique opportunity for the market to create a more inclusive and environmentally friendly financial ecosystem. Moreover, research indicates that stablecoins might convert Ethereum into a stable currency and enhance their ecologically friendly path. (4) Conclusions: Stablecoins have become a crucial tool in the unpredictable bitcoin environment, offering stability in a tumultuous market. The research indicates that users need to acknowledge the sustainability of asset collateral, and so far, only the regulation of stablecoins is progressing in this area. Full article

Extent ecosystems of crypto financial assets (crypto-assets) lack parity and coherence across the globe. This asymmetry is further heightened with a knowledge gap in operational risk management, wherein the global landscape of crypto-assets is characterized by unprecedented external risks and internal vulnerabilities. In this study, we present a critical examination and comprehensive analysis of current crypto-asset operational guidelines across geographies. We benchmark these guidelines to the Basel Committee for Banking Supervision (BCBS) risk classification framework for crypto-assets, identifying gaps in the operations across organizations. We, hence, conceptualize a novel institutional framework which may help in understanding and mitigating the gaps in operational risks’ regulation of crypto-assets. Our proposed Crypto-asset Operational Risk Management (CORM) framework determines how operational risk associated with crypto-assets of financial institutions can be mitigated to respond to the increasing demand for crypto-assets, cross border payments, electronic money, and cryptocurrencies, across countries. Applicable to firms irrespective of their size and scale of operations, CORM aligns with global regulatory initiatives, facilitating compliance and fostering trust among stakeholders. Strengthening our argument of CORM’s applicability, we present its efficacy in the form of alternate hypothetical outcomes in two distinct real-life cases wherein crypto-asset exchanges succumbed to either external risks, such as hacking, or internal vulnerabilities. It paves the way for future regulatory response with a structured approach to addressing the unique operational risks associated with crypto-assets. The framework advocates for collaborative efforts among industry stakeholders, ensuring its adaptability to the rapidly evolving crypto landscape. It further contributes to the establishment of a more resilient and regulated financial ecosystem, inclusive of crypto-assets. By implementing CORM, institutions can navigate the complexities of crypto-assets while safeguarding their interests and promoting sustainable growth in the digital asset market. Full article

In recent years, consensus algorithms have gained significant importance in the context of blockchain networks. These algorithms play a crucial role in allowing network participants to reach agreements on the state of the blockchain without needing a central authority. The present study focuses on carrying out a systematic mapping of these consensus algorithms to explore in detail their use, benefits, and challenges in the context of blockchain networks. Understanding consensus algorithms is essential to appreciating how blockchain networks achieve the reliability and integrity of their distributed ledgers. These algorithms allow network nodes to reach agreement on the validity of transactions and the creation of new blocks on the blockchain. In this sense, consensus algorithms are the engine that drives trust in these decentralized networks. Numerous authors have contributed to the development and understanding of consensus algorithms in the context of blockchain networks. This revolutionary concept paved the way for numerous cryptocurrencies and blockchain systems. Despite advances in this field, significant challenges remain: centralization, fair token distribution, scalability, and sustainability. The energy consumption of blockchain networks, particularly those using algorithms such as Proof of Work, Proof of Stake, Delegated Proof of Stake, Proof of Authority, and hybrid algorithms (Proof of Work/Proof of Stake), has raised concerns about their environmental impact, motivating the scientific and technological community to investigate more sustainable alternatives that promise to reduce energy consumption and contribute to climate change mitigation. Furthermore, interoperability between different blockchains and security in specific environments, such as IoT, are areas that still require significant research attention. This systematic mapping not only seeks to shed light on the current state of consensus algorithms in blockchain, but also their impact on sustainability, identifying those algorithms that, in addition to guaranteeing integrity and security, minimize the environmental footprint, promoting a more efficient use of energy resources, being a relevant approach in a context in which the adoption of sustainable technologies has become a global priority. Understanding and improving these algorithms are critical to unlocking the full potential of blockchain technology in a variety of applications and industry sectors. Full article

The environmental impact of Bitcoin mining has raised severe concerns considering the expected growth of 30% by 2030. This study aimed to develop a Life Cycle Assessment model to determine the carbon dioxide equivalent emissions associated with Bitcoin mining, considering material requirements and energy demand. By applying the impact assessment method IPCC 2021 GWP (100 years), the GHG emissions associated with electricity consumption were estimated at 51.7 Mt CO₂ eq/year in 2022 and calculated by modelling real national mixes referring to the geographical area where mining takes place, allowing for the determination of the environmental impacts in a site-specific way. The estimated impacts were then adjusted to future energy projections (2030 and 2050), by modelling electricity mixes coherently with the spatial distribution of mining activities, the related national targeted goals, the increasing demand for electricity for hashrate and the capability of the systems to recover the heat generated in the mining phase. Further projections for 2030, based on two extrapolated energy consumption models, were also determined. The outcomes reveal that, in relation to the considered scenarios and their associated assumptions, breakeven points where the increase in energy consumption associated with mining nullifies the increase in the renewable energy share within the energy mix exist. The amount of amine-based sorbents hypothetically needed to capture the total CO₂ equivalent emitted directly and indirectly for Bitcoin mining reaches up to almost 12 Bt. Further developments of the present work would rely on more reliable data related to future energy projections and the geographical distribution of miners, as well as an extension of the environmental categories analyzed. The Life Cycle Assessment methodology represents a valid tool to support policies and decision makers. Full article

Green finance, defined as channeling money into sustainable development activities, is still far lower than needed to achieve net-zero emissions objectives. In this paper, we discuss the role of technologies in developing green finance. We identify that green finance faces three major challenges, including the risk management of green projects, the scarcity of innovative green financing products, and compliance with the regulations. Then, in the context of the existing literature, we explore recent technologies, including blockchain, artificial intelligence (AI), machine learning (ML), data analytics, Internet of Things (IoT), and robotics that are helping to deal with the challenges in green finance. We show that data-driven approaches utilizing AI and ML help in the risk assessment of green projects; FinTech-based crowdfunding platforms provide innovative green financial products and regulatory technologies (RegTech) support in compliance with regulations. We also identify that the environmental footprint of cryptocurrencies is an emerging area in the technologies and green finance domain. Our framework could be helpful to further extend the debate on the role of technology in green finance. Full article

Small and medium-scale enterprises (SMEs) need a platform that actively enables collaboration with research institutions and consultants as SMEs lack the financial resources to conduct independent research. Such a platform will require a verifiable manipulation-free system to enable, execute, and record collaboration activities and to track reputations among the organizations and individuals that use the platform. Blockchain provides an opportunity to build such a collaborative platform by enabling the verifiable recording of the results of the collaborations, aggregating the resulting reputation of the collaborating parties, and offering tokenized incentives to reward positive contributions to the platform. Cryptocurrencies from which blockchain tokens are derived are volatile, thereby reducing business organizations’ interest in blockchain applications. Hence, there is a need to design a self-sustaining valuable token model that incentivizes user behaviours that positively contribute to the platform. This paper explores the application of game theory in analyzing token-based economic interactions between various groups of users in an implemented blockchain-based collaboration platform to design and simulate a token distribution system that provides a fair reward mechanism for users while also providing a dynamic pricing model for the utility value provided by platform tokens. To achieve this objective, we adopted the design science research method, a running case of a blockchain collaboration platform that enables research collaboration, and extensive form games in game theory, first to analyze and simulate token outcomes of users of the collaboration platform. Secondly, the research used a logarithmic model to show the dynamic utility pricing property of the developed token model where the self-sustainability of the token is backed by the availability of an internal resource within the platform. Thirdly, we applied a qualitative approach to analyze potential risks in the designed token model and proposed risk mitigation strategies. Thus, the resulting models and their simulations, such as token distribution models and a dynamic token utility model, as well as the identified token risks and their mitigation strategies, represent the main contributions of this work. Full article

Blockchain consensus mechanisms play a critical role in ensuring the security, decentralization, and integrity of distributed networks. As blockchain technology expands beyond cryptocurrencies into broader applications such as supply chain management and healthcare, the importance of efficient and scalable consensus algorithms has grown significantly. This study provides a comprehensive bibliometric analysis of blockchain and consensus mechanism research from 2014 to 2024, using tools such as VOSviewer and R’s Bibliometrix package. The analysis traces the evolution from foundational mechanisms like Proof of ork (PoW) to more advanced models such as Proof of Stake (PoS) and Byzantine Fault Tolerance (BFT), with particular emphasis on Ethereum’s “The Merge” in 2022, which marked the historic shift from PoW to PoS. Key findings highlight emerging themes, including scalability, security, and the integration of blockchain with state-of-the-art technologies like artificial intelligence (AI), the Internet of Things (IoT), and energy trading. The study also identifies influential authors, institutions, and countries, emphasizing the collaborative and interdisciplinary nature of blockchain research. Through thematic analysis, this review uncovers the challenges and opportunities in decentralized systems, underscoring the need for continued innovation in consensus mechanisms to address efficiency, sustainability, scalability, and privacy concerns. These insights offer a valuable foundation for future research aimed at advancing blockchain technology across various industries. Full article