Search Results (69)

How individuals and organizations interface with the digital economy has been largely influenced by transformations ushered in on the global financial map by the rapidly expanding Financial Technology (FinTech). This paper seeks to shed light on the successes of FinTech, namely on how it contributed to sustainability through financial inclusion, reduction in reliance on cash and the promotion of an innovation-driven economy known for being paperless. Based on contributions from students at Taif University in Saudi Arabia, determinants of FinTech adoption intentions are analyzed using data from n = 544. Our study focuses on evaluating the effects of financial, technical and external factors on adoption behavior by using a two-prong approach: first, we use the DeLone and McLean IS Success Model; then we employ a Second-Order Construct using Structural Equation Modelling (SEM). The results indicated that the strongest effects on attitudes stem from technical factors—information, system and service quality. Additionally, they also show that adoption intention is considerably shaped by financial as well as external dimensions. The Saudi Vision 2030 has set national goals of digital transformation, financial inclusion and human capital empowerment. This study provides a modest contribution to those goals by fostering FinTech adoption among the youth. Furthermore, its findings also offer educators, policymakers and Fintech providers a platform to enhance literacy, strengthen trust and develop sustainable digital finance ecosystems in line with the Kingdom’s Vision 2030 objectives. Full article

This study examines the role of the supply chain finance (SCF) ecosystem as an innovative financial framework in driving the high-quality development of rural industries. Using panel data from 31 Chinese provinces (2004–2022), we employ a fixed-effects model to analyze this relationship, confirming that the SCF ecosystem has a significant promoting effect. Mechanism analysis reveals that this positive effect operates primarily through two channels: enhancing rural industrial integration and stimulating technological innovation. Furthermore, we identify significant regional heterogeneity, with the most substantial positive spillover effects observed in the Southwest and South China. These results underscore the critical importance of the SCF ecosystem in rural revitalization and provide a basis for formulating regionally tailored financial policies. Full article

Floating and offshore photovoltaic (FPV) installations present a promising solution for addressing land-use conflicts while enhancing renewable energy production. With an estimated global offshore PV potential of 4000 GW, FPV systems offer unique advantages, such as increased efficiency due to water cooling effects and synergy with other offshore technologies. However, challenges related to installation costs, durability, environmental impacts, and regulatory gaps remain. This review provides a comprehensive and critical analysis of FPV advancements, focusing on inland, nearshore, and offshore applications. A systematic evaluation of recent studies is conducted to assess technological innovations, including material improvements, mooring strategies, and integration with hybrid energy systems. Furthermore, the economic feasibility of FPVs is analysed, highlighting cost–benefit trade-offs, financing strategies, and policy frameworks necessary for large-scale deployment. Environmental concerns, such as biofouling, wave-induced stress, and impacts on aquatic ecosystems, are also examined. The findings indicate that while FPV technology has demonstrated significant potential in enhancing solar energy yield and water conservation, its scalability is hindered by high capital costs and the absence of standardised regulations. Future research should focus on developing robust offshore floating photovoltaic (OFPV) designs, optimising material durability, and establishing regulatory guidelines to facilitate widespread adoption. By addressing these challenges, FPVs can play a critical role in achieving global climate goals and accelerating the transition to sustainable energy systems. Full article

The integration of artificial intelligence (AI) and blockchain technology opens new avenues for decentralized, transparent, and secure data-driven systems. However, ensuring privacy and verifiability in collaborative AI environments remains a key challenge, especially when model updates or decisions must be recorded immutably on-chain. In this paper, we propose a novel privacy-preserving framework that leverages an ElGamal-based aggregate signature scheme with aggregate public keys to enable secure, verifiable, and unlinkable multi-party contributions in blockchain-based AI ecosystems. This approach allows multiple AI agents or data providers to jointly sign model updates or decisions, producing a single compact signature that can be publicly verified without revealing the identities or individual public keys of contributors. The design is particularly well-suited to resource-constrained or privacy-sensitive applications such as federated learning in healthcare or finance. We analyze the security of the scheme under standard assumptions and evaluate its efficiency in different terms. The study and experimental results demonstrate the potential of our framework to enhance trust and privacy in AI collaborations over decentralized networks. Full article

Early survival is critical for sustainable startups to deliver environmental and social value, yet evidence on its predictors is limited. Drawing on resource-based and institutional perspectives, this study examines 140 university-affiliated green startups from 24 European countries in the “Stage Two” finals (2021–2023). Exploratory logistic regression links survival to financing structure, sustainable business-model archetypes, and public visibility. Non-equity grants and awards emerge as the strongest predictor, with equity capital and a Crunchbase profile adding smaller benefits. Economic-value archetypes outperform purely environmental or social ones, while technology-intensive B2B firms show the highest resilience. By combining resource sufficiency with legitimacy signaling, the study advances sustainable entrepreneurship theory and offers practical levers: mission-aligned grants, credible digital footprints, and archetype-specific funding strategies to support founders, investors, and policymakers in strengthening Europe’s sustainability-driven startup ecosystem. Full article

The digital economy creates new opportunities for micro, small, and medium enterprises (MSMEs) in Indonesia to enhance their competitiveness through the adoption of financial technology. This study examines how digital financial inclusion (DFI) mediates the effects of digital financial literacy (DFL) and government support (GS) on MSME performance. This mediating relationship remains underexplored in developing countries, offering new insights into how it drives business advancement. A quantitative approach was applied using partial least squares structural equation modeling (PLS-SEM) based on survey data from 260 culinary MSME owners. The results indicate that knowledge-based resources and institutional support positively influence performance through DFI. DFI drives improvement by expanding market reach, increasing operational efficiency, facilitating transactions, optimizing the value of financial activities, and broadening access to financing. These findings underline the importance of policies that promote inclusive digital ecosystems and strengthen digital capability. Future research approaches should emphasize the integration of behavioral factors, institutional support, and business performance within the evolving MSME ecosystem and can be further developed through longitudinal or cross-sectoral studies to understand the sustainable dynamics of digital transformation. Full article

With the growth of digital economies, data quality forms a key factor in enabling use and delivering value. Existing research defines quality through technical benchmarks or provider-led frameworks. Our study shifts the focus to actual users. Thirty-seven distinct data quality dimensions identified through a comprehensive review of the literature provide limited applicability for practitioners seeking actionable guidance. To address the gap, in-depth interviews of senior professionals from 25 organizations were conducted, representing sectors like computer science and technology, finance, environmental, social, and governance, and urban infrastructure. Data are analysed using content analysis methodology, with 2 level coding, supported by NVivo R1 software. Several newer perspectives emerged. Firstly, data quality is not simply about accuracy or completeness, rather it depends on suitability for real-world tasks. Secondly, trust grows with data transparency. Knowing where the data comes from and the nature of data processing matters as much as the data per se. Thirdly, users are open to paying for data, provided the data is clean, reliable, and ready to use. These and other results suggest data users focus on a narrower, more practical set of priorities, considered essential in actual workflows. Rethinking quality from a consumer’s perspective offers a practical path to building credible and accessible data ecosystems. This study is particularly useful for data platform designers, policymakers, and organisations aiming to strengthen data quality and trust in data exchange ecosystems. Full article

The Science and Technology Finance ecosystem plays an increasingly important role in shaping the sustainable development of new quality productive forces (NQPF). This study, based on the perspective of complex systems and using a multi-period fsQCA approach, takes 31 provinces, municipalities, and autonomous regions in mainland China as cases to analyze the relationship between the Science and Technology Finance ecosystem and NQPF from 2017 to 2022. The findings are as follows: first, the antecedent configurations of NQPF are multiple, with the variables of the Science and Technology Finance ecosystem jointly matching and working together to drive its development. Second, in 2017–2018, there were three configurations: the “Bank–Enterprise” collaborative-driven type, the Bank-led type, and the Enterprise-led type; in 2019–2020, there were three configurations: the “Bank–Enterprise” collaborative-driven type, the “Bank–Enterprise–Market” collaborative-driven type, and the “Enterprise–Market” collaborative-driven type; in 2021–2022, there was one configuration, namely the Multi-Actor collaborative-driven type. Third, the development of NQPF across the three stages underwent an evolution from being dominated by core financial resources, to coordinated driving by core finance and the market, and finally to multi-stakeholder collaborative promotion. Fourth, in the configurations where high-level NQPF was not achieved, insufficiency of Enterprise Self-owned Funds (ESOF) was identified as a common problem. These findings provide theoretical references and policy implications for optimizing the Science and Technology Finance ecosystem in line with local conditions. Full article

Blockchain technology has rapidly evolved beyond cryptocurrencies, underpinning diverse applications such as supply chains, healthcare, and finances, yet its security vulnerabilities remain a critical barrier to safe adoption. However, attackers increasingly exploit weaknesses in consensus protocols, smart contracts, and network layers with threats such as Denial-of-Chain (DoC) and Black Bird attacks, posing serious challenges to blockchain ecosystems. We conducted anomaly detection using two independent datasets (A and B) generated from simulation attack scenarios including hash rate, Sybil, Eclipse, Finney, and Denial-of-Chain (DoC) attacks. Key blockchain metrics such as hash rate, transaction authorization status, and recorded attack consequences were collected for analysis. We compared both class-balanced and imbalanced datasets, applying Synthetic Minority Oversampling Technique (SMOTE) to improve representation of minority-class samples and enhance performance metrics. Supervised models such as Random Forest, Gradient Boosting, and Logistic Regression consistently outperformed unsupervised models, achieving high F1-scores (0.90), while balancing the training data had only a modest effect. The results are based on simulated environment and should be considered as preliminary until the experiment is performed in a real blockchain environment. Based on identified gaps, we recommend the exploration and development of multifaceted defense approaches that combine prevention, detection, and response to strengthen blockchain resilience. Full article

Blockchain technologies have profoundly transformed information systems by providing decentralized infrastructures that enhance transparency, security, and traceability. Ethereum, in particular, supports smart contracts and facilitates the development of decentralized finance (DeFi), non-fungible tokens (NFTs), and Web3 applications. However, its openness also enables illicit activities, including fraud and money laundering, through anonymous wallets. Identifying wallets involved in large transfers or abnormal transactional patterns is therefore critical to ecosystem security. This study proposes an AI-based framework employing XGBoost, LightGBM, and CatBoost to detect suspicious Ethereum wallets, achieving test accuracies between 95.83% and 96.46%. The system provides near real-time predictions for individual or recent wallet addresses using a pre-trained XGBoost model. To improve interpretability, SHAP (SHapley Additive exPlanations) visualizations are integrated, highlighting the contribution of each feature. The results demonstrate the effectiveness of AI-driven methods in monitoring and securing Ethereum transactions against fraudulent activities. Full article

Climate change is intensifying droughts, heatwaves, dust storms, and rainfall variability across Eastern Europe, undermining yields and soil stability. In Ukraine, decades of underinvestment and wartime damage have led to widespread degradation of field shelterbelts, while the adoption of agroforestry remains constrained by tenure ambiguity, fragmented responsibilities, and limited access to finance. This study develops a policy-and-technology framework to restore agroforestry at scale under severe fiscal and institutional constraints. We apply a three-stage approach: (i) a national baseline (post-1991 legislation, statistics) to diagnose the biophysical and legal drivers of shelterbelt decline, including wartime damage; (ii) a comparative synthesis of international support models (governance, incentives, finance); and (iii) an assessment of transferability of digital monitoring, reporting, and verification (MRV) tools to Ukraine. We find that eliminating tenure ambiguities, introducing targeted cost sharing, and enabling access to payments for ecosystem services and voluntary carbon markets can unlock financing at scale. A digital MRV stack—Earth observation, UAV/LiDAR, IoT sensors, and AI—can verify tree establishment and survival, quantify biomass and carbon increments, and document eligibility for performance-based incentives while lowering transaction costs relative to field-only surveys. The resulting sequenced policy package provides an actionable pathway for policymakers and donors to finance, monitor, and scale shelterbelt restoration in Ukraine and in similar resource-constrained settings. Full article

Meeting global forest restoration targets by 2030 requires a transition from labor-intensive and opaque practices to scalable, intelligent, and verifiable systems. This paper introduces a cyber–physical digital twin architecture for forest restoration, structured across four layers: (i) a Physical Layer with drones and IoT-enabled sensors for in situ environmental monitoring; (ii) a Data Layer for secure and structured transmission of spatiotemporal data; (iii) an Intelligence Layer applying AI-driven modeling, simulation, and predictive analytics to forecast biomass, biodiversity, and risk; and (iv) an Application Layer providing stakeholder dashboards, milestone-based smart contracts, and automated climate finance flows. Evidence from Dronecoria, Flash Forest, and AirSeed Technologies shows that digital twins can reduce per-tree planting costs from USD 2.00–3.75 to USD 0.11–1.08, while enhancing accuracy, scalability, and community participation. The paper further outlines policy directions for integrating digital MRV systems into the Enhanced Transparency Framework (ETF) and Article 5 of the Paris Agreement. By embedding simulation, automation, and participatory finance into a unified ecosystem, digital twins offer a resilient, interoperable, and climate-aligned pathway for next-generation forest restoration. Full article

In an era marked by volatility, uncertainty, complexity, and ambiguity, constructing resilient regional innovation ecosystems is identified as a critical strategic imperative for achieving high-quality development and advancing sustainable development goals. Drawing on the Technology–Organization–Environment (TOE) integrative framework, this study examines six antecedent conditions of ecosystem resilience from the perspective of digital transformation: digital infrastructure, digital innovation capacity, digital human capital, digital government governance, digital attention, and digital finance. A sample of 48 prefecture-level cities from the Beijing–Tianjin–Hebei, Yangtze River Delta, and Pearl River Delta urban agglomerations in China between 2018 and 2022 is selected. Through the application of dynamic Qualitative Comparative Analysis (QCA), the study explores the multiple configurations across temporal and spatial dimensions through which technological, organizational, and environmental factors contribute to enhancing regional innovation ecosystem resilience. The results indicate that ecosystem resilience is jointly driven by multiple interacting factors, and no single condition is found to be necessary. Four distinct causal pathways are identified as sufficient to enhance resilience: (1) a triadic synergy of technology, organization, and environment; (2) a technology-driven, talent-supported configuration; (3) a technology-driven, government-supported configuration; and (4) a dual technology–environment-driven model. While none of the configurations exhibit consistent temporal effects, some are influenced by unobserved factors in specific years. Moreover, cities do not converge on a single dominant configuration when achieving high levels of ecosystem resilience. Full article

The convergence of decentralized artificial intelligence (DAI), blockchain technology, and smart contracts is reshaping the design and governance of intelligent systems. As these technologies rapidly evolve, addressing privacy within their architecture, usage models, and associated risks has become increasingly critical. This systematic literature review examines architectural patterns, governance frameworks, real-world applications, and persistent challenges in DAI systems. It identifies prevailing designs such as federated learning integrated with consensus protocols, smart contract-based incentive mechanisms, and decentralized verification methods. Drawing from a diverse body of recent literature, the review highlights implementations across sectors, including healthcare, finance, IoT, autonomous systems, and intelligent infrastructure, each demonstrating significant contributions to privacy, security, and collaborative innovation. Despite these advancements, DAI systems face ongoing obstacles such as scalability limitations, privacy trade-offs, and difficulties with regulatory compliance. The review emphasizes the need for integrative governance approaches that balance transparency, accountability, incentive alignment, and ethical oversight. These elements are proposed as co-evolving pillars essential to establishing trustworthiness in decentralized AI ecosystems. This work offers a comprehensive review for understanding the current landscape and guiding the development of responsible and effective DAI systems in the Web3 era. Full article

As urbanization progresses rapidly, cities face growing challenges of land resource scarcity and the pressure on green ecological spaces. This not only affects the sustainable development of cities but also presents a major challenge to the resilience of urban ecosystems (UER). As an emerging land use model, land financialization (LF), which involves the circulation and financing of land as a financial asset, has become an important means to promote UER. Therefore, this paper examines 221 prefecture-level cities across mainland China to explore the impact of land financialization on urban ecological resilience and aims to reveal the specific pathways through which land financialization improves urban ecological resilience through mechanisms like resource reallocation, industrial structure rationalization, green innovation, green signals, and environmental regulation. This paper employs a two-way fixed effects model, robustness tests, and endogeneity tests, supplemented by mechanism and heterogeneity analysis, to explore the impact of LF on UER. The findings show that LF plays a significant role in improving UER. Mechanism analysis reveals that LF significantly boosts UER by optimizing the distribution of land and financial resources, as well as enhancing the rationalization of the industrial structure. Additionally, enterprise green technology innovation, green value, and the intensity of environmental regulation play a positive moderating role in this process. In addition, the heterogeneity analysis reveals the inclusive characteristics of LF on urban ecological transformation. In cities with higher levels of land price distortion, as well as in old industrial cities, small cities, and peripheral cities with poorer resource characteristics and administrative resources, LF has a more significant impact on promoting the improvement of UER. Based on the findings, this paper proposes policy recommendations to promote the improvement of urban green ecology and support the innovation of land financialization. These insights contribute to the theoretical discourse on greenization and provide essential, practical guidance for optimizing the allocation of land and financial resources, as well as establishing a framework for green and high-quality development. Full article