Purpose This study aims to explore the potential of blockchain technology for venture capital and entrepreneurship. We hypothesize that the adoption of blockchain in finance has vast potential for research in entrepreneurship and venture capital. Design/methodology/approach We conducted a bibliometric study of 416 articles retrieved from the Web of Science database, and performed descriptive and evaluative analyses. We also used factor analysis to identify discussion questions for the intersection of blockchain and entrepreneurship. Additionally, we employed bibliometric techniques and VOSviewer software to generate scientific maps highlighting current research streams and identifying gaps. Findings While blockchain-related topics are widely documented in industry reports, we found a clear void in academic literature, particularly in the areas of venture capital and entrepreneurship. Several factors may explain this finding: the lack of integration between technological and financial research, the collapse of ICOs and the tendency for adoption primarily in response to crises. Our analysis reveals three dominant research streams: (1) technological adoption, (2) entrepreneurial funding (including Initial Coin Offerings, ICOs) and (3) decentralized finance (DeFi). We identified gaps and opportunities for research on decentralized autonomous organizations (DAOs), the democratization of entrepreneurial finance, trust-enabling mechanisms through smart contracts and the development of standards and taxonomies for firms. Originality/value Unlike existing bibliometric reviews, this study specifically examines the intersection of blockchain, DeFi, entrepreneurship and venture capital, and identifies regulatory and adoption-related research gaps. Our findings underscore the interdisciplinary nature of the domain, highlight the need for deeper inquiry into these evolving topics and contribute to the development of future literature.
Abdu A. Adamu, Kamal A. Ibrahim, Hyelhirra Adamu, Firdausi Umar-Sadiq
Abstract Under Nigeria’s 2014 National Health Act, the Basic Health Care Provision Fund (BHCPF) was created as a key health financing mechanism to bolster primary healthcare and promote progress towards Universal Health Coverage (UHC). The BHCPF, disbursed through four gateways, has catalyzed important health systems gains, including improved facility financing predictability and the nationwide creation of State Social Health Insurance Agencies. However, persistent bottlenecks, including weak oversight, lax fiduciary controls, poor accountability, and disparities in implementation quality, have constrained progress. These challenges precipitated a comprehensive set of reforms outlined in the 2025 BHCPF guidelines (BHCPF 2.0). These reforms introduce performance-linked disbursement, tiered direct facility financing, capitation-plus payment systems, and strengthened governance structures. Yet policy reform alone does not guarantee equitable and effective implementation, particularly in Nigeria’s complex, decentralized, and heterogeneous health system. This Commentary argues that institutionalizing implementation research in BHCPF’s governance framework offers a structured, evidence-driven pathway to bridge the gap between reform intent and real-world outcomes. Specifically, implementation research can: build theory-driven understanding of why and how reforms succeed or fail across diverse subnational contexts; monitor implementation fidelity and outcomes during rollout; distinguish necessary adaptations from fidelity drift; and test context-specific strategies to overcome barriers and promote facilitators. Ultimately, country-led, integrated implementation research is essential for fully realizing the transformative potential of BHCPF.
I Nyoman Teja Kusuma, Ika Devy Pramudiana, Nihayatus Sholichah
The enactment of Law Number 1 of 2022 concerning Financial Relations between the Central and Regional Governments (HKPD Law) introduced a pivotal shift in Indonesia’s fiscal decentralization through the Motor Vehicle Tax (PKB) "opsen" (option) mechanism. This study analyzes the impact of HKPD Law implementation on local revenue (PAD) strengthening in Probolinggo City and Regency. Utilizing a qualitative comparative case study approach, the research evaluates administrative readiness and policy impacts derived from Ministry of Finance Regulation (PMK) Number 3 of 2024. The findings reveal an asymmetrical transition, where fiscal effectiveness is highly contingent on digital infrastructure maturity and geographical constraints. Probolinggo City demonstrates successful host-to-host system integration, ensuring daily liquidity and bureaucratic efficiency. Conversely, Probolinggo Regency faces "geospatial gaps," characterized by transaction data delays and high collection costs in remote areas. This study identifies a lack of target alignment between provincial and local governments and emphasizes the necessity of "budget tagging" for road infrastructure to enhance the social contract with taxpayers. This research contributes to fiscal decentralization theory by proposing a "geographic coefficient" model for operational cost distribution in developing regions.
Cryptocurrencies have received long-term interest among investors because of the features of Bitcoin since its introduction in 2009. However, it is the same features that pose serious and diverse threats. These risks are very dangerous to the security of investors and the integrity of the market. Although their urgency is immense, there are very few systematic analyses that incorporate both regulatory and technological views. In this research, the mixed-method design is used, and an empirical investigation of high-profile security events is combined with the critical analysis of regulatory and technical literature in order to define, classify, and track the causes of the most widespread risks. The article explores the weaknesses and strengths of the existing laws and strategies that would curb identified risks that cryptocurrencies present. It also suggests practical and tangible solutions, which would make use of new technologies to minimize the damages and risks of cryptocurrencies to a greater extent. The analysis in this study proves that properly reducing risks should be performed in a two-faceted way; it should be done with the help of the regulation gaps in action and the utilization of new, protocol-infused technological limits. This study presents a moderate structure that is meant to achieve market security that does not suppress the dynamism and transparency of the cryptocurrency ecosystem. This study analyzes the problem of cryptocurrency security, financial regulation, blockchain technology, risk mitigation, and decentralized finance.
The financial landscape in developed countries, including the United States, China, Japan, and Europe, experienced a significant transformation due to the rapid emergence of cryptocurrencies, decentralized finance, Central Bank Digital Currencies (CBDCs), and Fintech innovations. This chapter delved into the profound implications of these technological advancements on financial systems, with a particular focus on stability, security, and regulation. Notably, these transformative changes posed distinctive challenges in Muslim-majority countries, largely due to the absence of Shariah-compliant financial services. The study took a qualitative approach, utilizing structured questionnaires for data collection and investigating the potential of CBDCs in payment settlements through thematic analysis. Respondents stressed the need for clear legal and regulatory frameworks to strike a balance between innovation and consumer protection, cautioning against excessive regulation that could stifle innovation. For financial inclusion and economic growth, emerging economies with Muslim majorities harnessed financial innovations by adapting regulatory frameworks, enhancing digital payment infrastructure, promoting education, and fostering collaborations between traditional financial institutions and Fintech start-ups, aligning these solutions with Islamic finance principles to address unique local challenges. Blockchain technology was identified as having significant potential to enhance supply chain and trade finance in Muslim-majority nations, offering advantages such as transparency, traceability, fraud reduction, and automation for cross-border trade. However, challenges like regulatory uncertainty, educational requirements, infrastructure needs, and security concerns had to be addressed for this potential to be fully realized. In conclusion, the research underscored the importance of learning from the experiences of developed countries and advocated for inclusive regulation, public-private collaboration, education, data security, and international cooperation to achieve financial inclusion and sustainable economic growth in emerging economies. Embracing and integrating new financial technologies could help these nations overcome hurdles and effectively foster development.
The financial sustainability of small and medium-sized enterprises (SMEs) has become increasingly important in the context of economic volatility, technological disruption, and growing sustainability demands. However, existing studies remain fragmented and often examine financial, organizational, technological, and environmental factors in isolation. This study systematically reviews 49 articles indexed in the Scopus and Web of Science databases published between 2014 and 2026 to identify the dominant determinants, thematic patterns, and conceptual structure of financial sustainability in SMEs. Using the PRISMA protocol and NVivo-based bibliometric and thematic analyses, this study examines publication trends, geographic distribution, lexical structures, and thematic relationships across the literature. The results show that research is concentrated primarily in Asia and Europe, reflecting increasing scholarly attention to financial literacy, governance quality, resilience, digital transformation, FinTech adoption, ESG practices, and green finance. Thematic synthesis reveals three interconnected pillars—Internal Capability, Adaptive Resilience, and Digital–Green Transformation—which collectively form an architecture of endurance framework that explains how SMEs maintain financial viability under conditions of uncertainty and change. This framework advances prior reviews by integrating organizational capability, resilience-building mechanisms, and sustainability-oriented transformation into a unified model of financial sustainability for SMEs. Practically, the findings highlight the importance of strengthening financial literacy, governance quality, risk management capability, digital adoption, and sustainability-oriented financing, while emphasizing the role of policy support and financial inclusion in fostering SME resilience. Future research should further explore the implications of generative artificial intelligence, blockchain-based finance, and decentralized finance (DeFi) on SME financial sustainability.
This research provides an in-depth evaluation of current academic studies and advancements in the fields of cryptocurrencies, financial technology, blockchain-based decentralized finance (DeFi), stablecoins, state-owned digital currencies, and Central Bank Digital Currencies (CBDCs). The rapidly evolving Fintech environment, as well as the growing significance of DeFi, Bitcoin, and CBDCs, are critical in the current financial landscape. The study delves into several areas of the Fintech development, such as the overall Fintech experience, digital banking tools, payment methods, and Fintech-based lending practices. It also provides insight into the current status of CBDC programs and pilot projects in different countries. Furthermore, the study looks into how the emergence of cryptocurrencies, Fintech, and DeFi on the blockchain has resulted in revolutionary changes inside industrialized nations such as the United States, China, Japan, and several European countries. It also discusses the wide-ranging implications of these changes for financial stability, security, and regulatory measures. This comprehensive analysis provides valuable insights into the current financial landscape and its potential future directions.
Terrorist financing is a major fuel for political violence and extremist operations in the world. The increasing advancement of digital technologies, cryptocurrencies, crowdfunding platforms, and social media has significantly transformed how extremist groups raise, transfer, and conceal funds, yet little has been done to examine the broader digital transformation of terrorist financing and its implications for the United States. This scoping review examined evolving trends, financing strategies, and operational challenges associated with terrorist financing networks and assessed their implications for the United States counterterrorism agenda. Following the Arksey and O’Malley guidelines for scoping reviews, relevant studies were identified through systematic database searches and screened using predefined inclusion and exclusion criteria. Ten studies were selected and analyzed thematically. The findings underscored four major themes: the digitalization of terrorist financing, the fusion of lawful and unlawful funding mediums, administrative and institutional weaknesses, and the growing need for collaborative and intelligence-driven disruption strategies. The review found that extremist financing increasingly operates within ordinary digital and financial ecosystems, making detection more difficult for regulators, financial institutions, and law enforcement agencies. The study concludes that terrorist financing has become more decentralized, adaptive, and technologically sophisticated than many existing counterterrorism frameworks are prepared to address. Hence, strengthening United States national security will require a more proactive digital financial monitoring, sophisticated regulatory systems, and stronger inter-sectoral collaborations to disrupt evolving extremist financing networks before they escalate into acts of violence.
Open access
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Terrorism, Counterterrorism, and Political Violence
Background: Indonesia’s simultaneous regional elections (Pilkada serentak) constitute a key component of post-Reformasi decentralization. While designed to strengthen democratic local governance, recent fiscal rationalization policies have increased central control over election financing, raising concerns about their impact on substantive democratic representation. Objectives: This study examines whether fiscal rationalization in Pilkada implementation supports or undermines constitutional principles of democratic, participatory, and accountable local government. It analyzes the constitutional framework of Pilkada, identifies key fiscal rationalization mechanisms, and evaluates their effects on local political representation. Methods: A qualitative normative empirical approach was employed. Normative analysis examined the 1945 Constitution, electoral and regional governance laws, fiscal decentralization regulations, and Constitutional Court decisions. Empirical analysis was conducted through comparative case studies of regional election budget management. Results: Four major mechanisms were identified: NPHD budget revisions, APBD burden-shifting, compressed electoral timelines, and intensified central fiscal steering under Law No. 1 of 2022. These mechanisms reduced electoral capacity, limited voter-candidate engagement, and disproportionately affected less-resourced regions. Although elections formally complied with constitutional requirements, substantive representation was weakened, creating a persistent gap between procedural legality and democratic quality. Conclusion: Fiscal rationalization has strengthened formal compliance but constrained substantive democratic representation. Greater fiscal stability and regional autonomy are needed to ensure competitive, equitable, and accountable local elections. Keywords: fiscal rationalization; Pilkada serentak; constitutional compliance; democratic representation; decentralization.
Smart contracts deployed on blockchain platforms are immutable once deployed, making correctness and security critical concerns that have led to substantial financial losses due to vulnerabilities. A significant proportion of these vulnerabilities stem from human-written code rather than blockchain infrastructure or cryptographic primitives. This observation motivates a paradigm shift from manual code development to model-driven approaches that generate semantically correct smart contracts from formal specifications. This thesis presents EDAM (Enhanced Data-Aware Machines), a behavioural model for specifying smart contracts that balances expressiveness with tractability. The framework extends traditional data-aware finite state machines [3] with essential features for a wide range of smart contract applications: dynamic role-based access control enabling runtime role assignment and revocation, participant management supporting unbounded and varying participants, and explicit modelling of inter-contract interactions through call tries with success and failure handling. The formal semantics of EDAM are grounded in established techniques from behavioural type theory, process calculi, and finite state machine theory, enabling rigorous reasoning about contract behaviour. The thesis contributes a comprehensive toolchain that integrates modelling, code genera- tion, test generation, and validation in a unified methodology. We develop a code generation engine that automatically produces Solidity smart contracts from EDAM specifications. The generated code faithfully implements the formal model, ensuring that the behaviour established at the model level is preserved in the executable code. The code generation process uses an intermediate JavaScript Object Notation (JSON) representation, which enables platform-agnostic code generation with ongoing extensions to support additional blockchain platforms such as Aptos. We present an automated test generation methodology that produces executable test suites from EDAM specifications. The approach combines symbolic trace generation using the formal semantics implemented in OCaml with randomized exploration of the Finite State Machine (FSM) network, enabling concrete trace derivation through random value assignment and Satisfiability Modulo Theories (SMT) constraint solving. This methodology systematically explores the state space to generate traces that exercise transitions, guards, and role constraints, producing executable test suites for standard testing frameworks such as Hardhat. The process is fully automated and can be integrated into the development workflow. Our evaluation demonstrates the expressiveness and practicality of the approach through a diverse benchmark of smart contracts, including contracts from the Azure repository [148], standard token contracts (Ethereum Request for Comments 20 (Token Standard) (ERC20)), Decentralized Finance (DeFi) protocols (Automated Market Makers (AMMs)), and multi- coordinator systems. The evaluation demonstrates expressiveness through the modelling of essential features, showing that the approach is able to model a wide range of smart contract features. The validation methodology employs a multi-faceted approach that combines code coverage analysis, mutation testing to validate the correctness of the generated code and the effectiveness of the test suites, and cross-validation by applying the generated tests to other established implementations. This cross-validation approach shows that our generated test suites are applicable to validate existing smart contract implementations, providing evidence of the quality and correctness of both the generated code and the testing methodology. The results empirically indicate that our model-driven approach produces contracts and test suites that preserve the structure and semantics of the formal model and can be applied to validate existing smart contract implementations. Unlike existing approaches that address isolated phases of the development lifecycle, EDAM provides an integrated toolchain that ensures consistency between specifications, vii generated code, and test suites. The framework shows that behavioural types provide a solid foundation for smart contract modelling and verification, enabling the development of unified frameworks that integrate modelling, code generation, test generation, and val- idation. Although our implementation targets blockchain platforms, the methodology is platform-agnostic and may generalise to other service-oriented and distributed architectures. The results show that model-driven approaches can produce high-quality smart contracts and comprehensive test suites, contributing to the advancement of secure smart contract development practices.
Blockchains are distributed ledgers that let mutually distrustful parties agree on an append-only transaction history without relying on a central authority. By combining cryptographic hashing, digital signatures, and consensus mechanisms, blockchains provide tamper evidence, auditability, and agreement among nodes. Modern blockchain systems significantly vary in consensus design (e.g., Proof of Work, Proof of Stake, Proof of Author- ity, and Byzantine Fault Tolerance mechanisms), access model (open vs. permissioned), and execution layers (from simple asset transfers to expressive smart-contract virtual machines). The related architectural choices shape decentralization, fault tolerance, and the attainable latency-throughput envelope. As blockchain deployments expand to payments, tokenization, decentralized finance, supply chain traceability, and digital identities, comparing these systems has become an urgent necessity. Unfortunately, rigorous blockchain evaluation remains difficult. On the one hand, measurements are confounded by fluctuating network conditions, heterogeneous infrastructures, and rapidly evolving software. On the other hand, results are too often collapsed to a single number (such as transactions per second) without dispersion or methodological details; economic assessments of crypto-assets lack a unified and interpretable index that captures the balance of core economic parameters and their trade-offs (usage, liquidity, stability, and security) rather than market price sentiment; and experimental studies rarely address the dimensions of experimental repeatability (same setup, same results) and performance predictability (stable expectation). The consequence is an evidence gap: how to assess and compare the efficiency of blockchains – spanning performance, energy, economics, and result stability – in different scenarios? This dissertation aims at reducing this gap with a coherent yet modular approach that combines topology-controlled benchmarking with an orthogonal, entropy-based economic analysis, delivering four contributions. First, it introduces Lilith, a system-agnostic benchmarking framework that couples workload generation with network emulation to run controlled, repeatable experiments under explicit overlay topologies (i.e., the logical peer- to-peer connectivity graphs) and link properties such as latency, bandwidth, and packet loss. Lilith orchestrates deterministic deployments (pinned artifacts, controlled boot order, and CPU core pinning and memory binding), integrates power probes, and provides a uniform client interface; this underpins a comparison based on typical performance metrics. Second, Lilith is employed to quantify blockchain energy consumption under realistic conditions. Third, Lilith is adopted for a network-controlled, multi-run measurement campaign to produce a public dataset. By combining dispersion metrics (e.g., worst-case deviation) with analysis of variance and intraclass correlation, we quantify run-to-run variability and performance predictability across blockchains, topologies, workloads, and node-set sizes. Fourth, in addition to Lilith, the dissertation introduces the Entropy Balance index (EB-index), which aggregates heterogeneous on-chain indicators into a single, interpretable score of economic efficiency. ii As for the first three contributions, we set up the experimental baseline by considering five network topologies (fat-tree, full mesh, hypercube, scale-free, torus) and five industry- grade blockchains (Algorand, Diem, Ethereum Clique, Quorum IBFT, Solana), exercised with transfer transactions and smart-contract workloads (DDoS, FIFA, GAFAM, gaming, PayPal, VISA) across two node-set sizes (10 and 40). In the performance study, the network topology emerges as the primary factor de- termining throughput and latency. Full mesh, hypercube, and torus deliver higher performance under heavy load. The performance of Algorand and Diem is stable with respect to topology changes, while Ethereum is less sensitive but remains slower. In the energy study, fat-tree and full mesh turn out to be the most energy-efficient topologies, especially at high load. Algorand and Diem exhibit the lowest energy per transaction, Ethereum Clique the highest across topologies; Quorum IBFT and Solana become costlier as workload intensity and network size increase. The experimental repeatability and performance predictability study shows low per- formance variance (transactions per second, block latency, energy consumption) for Algorand and Diem and pronounced sensitivity for Solana and Quorum IBFT, especially as workloads, node-set size, and geo-latency conditions vary. The released dataset and the accompanying analysis templates, which are based on clusters instead of public-cloud testing, enable thorough checks that go beyond point estimates by quantifying dispersion and confidence in comparative results. Finally, in the economic study, the EB-index aggregates heterogeneous on-chain indicators – such as user activity (transactions, active addresses), token distribution (balance concentration), and supply turnover/velocity – by using the normalized Shannon entropy and its weighted Beliş-Guiaşu variant. When applied to the capitalization-based leading crypto-assets Bitcoin, Ethereum, Ripple, USD Coin, Dogecoin, and Cardano, the EB-index separates volume-driven bursts from structurally balanced ecosystems and reveals differences that price, total value locked, or raw activity may blur. Overall, this dissertation delivers a topology-aware blockchain benchmarking frame- work, empirical evidence that network structure materially affects performance and energy, a public multi-run dataset together with analysis templates that promote experimental repeatability and performance predictability, and an entropy-based index for assessing economic efficiency.
This PhD thesis examines risks, opportunities and socio-technical innovation in blockchain-based financial systems, combining network analysis, empirical market data, and institutional analysis. As the crypto ecosystem and decentralized financial infrastructures continue to expand and interact with traditional monetary systems, understanding how risk propagates across assets, platforms, and institutional designs has become increasingly important for market participants and policymakers. The first two chapters focus on systemic risk in crypto assets (cryptocurrencies and stablecoins) using a network-based approach. The first paper analyzes major crypto assets and constructs dynamic networks based on return co-movements to study the evolution of interconnectedness and contagion risk over time. Network centrality measures (degree, closeness, betweenness, and eigenvector) are used to identify systemically important nodes (cryptocurrencies and stablecoins) and to assess how these measures affect their systemic risk contributions, particularly during market stress episodes. Results showed that the systemic risk contribution of crypto assets decreases over time as their connectedness in the system increases. This impact is more pronounced for cryptocurrencies than for centrally issued, managed, and governed stablecoins. Our findings suggest that pure network interconnectedness plays a diminished role in tail risk propagation in the crypto market. The second paper extends this framework to token pairs traded on centralized and decentralized exchanges (CEXs and DEXs), allowing for a comparison of market structure and risk transmission across trading platforms. By incorporating data from CEXs and DEXs, this chapter highlights differences in network topology and the role of liquidity concentration in shaping systemic risk. Results showed that centrality values significantly impact systemic risk contribution of token pairs listed on centralized exchanges. Conversely, insignificant results were found for all token pairs traded on decentralized exchanges. The token pairs on centralized exchanges exhibited a negative association with centrality values, consistent with the findings reported in the first paper. These findings imply that systemic risk in cryptocurrency markets is not solely driven by interconnectedness, but by how that interconnectedness is structured. In particular, the negative relationship between centrality and systemic risk suggests that higher network integration, supported by transparency and decentralized architectures, may enhance risk sharing and reduce systemic vulnerability. These results highlight the potential of blockchain based financial systems to contribute to more resilient, efficient, and inclusive financial ecosystems, while also offering new insights for the design of risk management and regulatory frameworks. The third paper shifts the focus from market level risk to protocol level risk management in leading Decentralized Finance (DeFi) lending platforms. It examines the determinants of liquidation events and evaluates the effectiveness of protocol design features as risk management tools. Exploiting the transition from earlier to newer protocol versions across different blockchain layers, the empirical analysis employs panel fixed effect regression models to assess how changes in risk control measures 3 affect liquidation dynamics and protocol’s performance. The findings emphasize that protocol level design choices play a critical role in mitigating risk beyond asset price volatility alone. The architectural evolution from v2 to v3, characterized by granular risk parameters, isolation modes, and enhanced risk management mechanisms has systematically improved protocol resilience, with liquidations in v3 serving as positive signals of stability rather than distress. The fourth paper broadens the scope of the thesis by examining blockchain based complementary currencies in comparison with traditional complementary currency systems, with a particular focus on their potential role in universal basic income schemes. It investigates the socio-technical evolution of Complementary Currencies for Basic Income using a data-driven approach to different case studies (Fiat and Blockchain based models). It highlights how technological choices influence scalability, transparency, and risk exposure in social and monetary innovations by employing mix method approach. Finally, based on the trade-offs of each system, a hybrid model for UBI is proposed for financial inclusion and poverty elimination. Taken together, the four papers provide an integrated perspective on risks and opportunities in emerging financial ecosystems, spanning asset markets, trading infrastructure, decentralized protocols, and alternative monetary arrangements. Overall, the results suggest that the core features of blockchain based markets, e.g., decentralization, transparency, accessibility, low transaction costs and automated risk management, are not merely technological innovations but may serve as mechanisms for improving system resilience and inclusive financial architectures. This thesis also contributes to the literature by demonstrating how network structures and institutional design jointly shape systemic risk and resilience in DeFi, offering insights relevant for researchers, protocol designers, and policymakers navigating the evolving digital financial landscape.
ABSTRACT Financial innovation profoundly reshapes the financing mechanisms, risk structures, and resilience of agricultural value chains. Based on 40 high‐quality English studies (2018–2026), this review identifies five core agricultural financial innovations: digital payments, digital credit, supply chain finance, blockchain, and decentralized finance, as well as climate derivatives and blended finance. These innovations enhance financial inclusion for smallholders and agribusinesses by mitigating information asymmetry and easing financing constraints. The integration of green finance and digital inclusive finance lifts agricultural green total factor productivity and promotes eco‐friendly technology adoption. The synergy of supply chain finance, AI, and blockchain strengthens the shock resistance, recovery, and adaptive transformation capabilities of agricultural value chains. Constraints include the digital divide, technological uncertainty, insufficient regulation, and unsustainable business models. This paper constructs a “technology–institution–value” framework to illustrate transmission pathways and puts forward future research directions and policy implications.
This study examines whether green finance promotes green development across Chinese prefecture-level cities from 2005 to 2019. We find a positive association between green finance and green development using panel regressions with city and year fixed effects. This result remains robust after accounting for potential endogeneity and implementing a series of robustness checks. Further heterogeneity analysis shows that this positive effect is stronger in regions characterized by high fiscal capacity and within the Yangtze River Economic Belt. Additionally, green finance drives regional green development by promoting green innovation. Environmental decentralization moderates the relationship, with a stronger positive effect at higher levels of decentralization. This study offers empirical evidence regarding how green finance shapes green development outcomes.
Privacy-preserving systems have traditionally faced a fundamental tradeoff between data utility and confidentiality. Selective Disclosure Credentials (SDCs) enable users to prove specific attributes without revealing underlying personal information, while Fully Homomorphic Encryption (FHE) enables arbitrary computation on encrypted data without exposing plaintext. Although both technologies address critical privacy challenges, they solve different problems and are rarely integrated into a unified architecture. This paper introduces the concept of Composable Privacy, a layered framework that combines selective disclosure credentials, zero-knowledge proofs, and fully homomorphic encryption into a cohesive privacy architecture. The framework separates privacy concerns into three functional layers: an authentication layer using selective disclosure and zero-knowledge proofs, a computation layer using homomorphic encryption for confidential processing, and a verification layer that provides cryptographic assurances of computation correctness. The paper examines the cryptographic foundations of BBS+ signatures, Coconut threshold credentials, lattice-based homomorphic encryption schemes, and post-quantum security considerations. It further evaluates the practical feasibility of the architecture through applications in decentralized finance, healthcare federated learning, confidential governance systems, and blockchain-based identity infrastructure. Performance trends, scalability challenges, interoperability requirements, and future hardware acceleration pathways are also analyzed. The proposed Composable Privacy framework demonstrates how selective disclosure and encrypted computation can be combined to create privacy-preserving digital systems that maintain verifiability, confidentiality, and regulatory compliance simultaneously. The work provides a conceptual foundation for next-generation privacy architectures in blockchain, decentralized identity, and distributed computing environments.
Objective: This study examines the legal and procedural challenges posed by decentralised finance (DeFi) technologies to the anti-money laundering framework in Iraq, The research problem lies in the clear regulatory gap resulting from the decentralised nature of these platforms, which relies on smart contract technology and blockchain to eliminate the need for traditional financial intermediaries; this decentralised nature hinders the ability of Iraq’s Anti-Money Laundering and Counter-Terrorist Financing Law No. 39 of 2015 to control cryptocurrency flows and establish criminal liability in this context,، Method: The study adopted a comparative analytical approach, analysing the text of Iraqi legislation and comparing it with the operating mechanisms of decentralised finance platforms, whilst also examining the extent to which it complies with the updated international standards issued by the Financial Action Task Force (FATF) In particular, with regard to Recommendation No. 15, Results: the study reached a number of important conclusions, the most notable of which is that the current legal definitions of funds and financial institutions in Iraq are outdated, thereby limiting the ability of regulatory bodies to track virtual assets, Novelty: The study also identified procedural shortcomings in the handling of encrypted digital evidence and recommended urgent legislative reforms, including the regulation and oversight of Virtual Asset Service Providers (VASPs) through the establishment of a dedicated institutional framework.
Adina Litriwani, Shafwatul Hilwa, Muhammad Alvin, Dini Vientiany
This study aims to analyze the differences, roles, and contributions of central and regional taxes within the Indonesian taxation system. Taxes serve as the primary source of state revenue and play a crucial role in financing development and improving public welfare. Along with the implementation of fiscal decentralization, local governments are granted authority to manage regional taxes in order to enhance fiscal independence. This research employs a qualitative method with a descriptive approach, utilizing library research from various sources such as books, academic journals, and legal regulations. The results indicate that central taxes still dominate state revenue compared to regional taxes, reflecting disparities in regional fiscal capacity. Central taxes function to finance national programs and maintain economic stability, while regional taxes support local development and public services. To optimize tax revenue, strategies such as tax intensification, digitalization of the tax system, regulatory simplification, and improvement of taxpayer compliance are necessary. Therefore, an effective, transparent, and fair taxation system is expected to promote economic growth and equitable development in a sustainable manner.
Shivaratri Narasimha Rao, Mohammed Ali Shaik, Dr. Imran Qureshi, Salman Ali Syed
The chapter examines the speedy innovations and overlaps of three disruptive technologies, blockchain, generative artificial intelligence (AI), and computer vision (CV) and how they can transform industries. The innovations of blockchain have been developed past cryptocurrencies to include consensus mechanisms, scalability and finance, supply chain, and healthcare applications. The discussion brings out the focus on decentralized finance (DeFi), smart contracts, and nonfungible tokens (NFTs), with a focus on new paradigms of transparency, ownership, and trust. Generative adversarial networks (GANs) and variational autoencoders (VAEs) are used to create generative AI, which can produce realistic text, images, video, and sound but can revolutionize entertainment, advertising, and art and poses an ethical challenge, including such issues as deepfakes and misinformation. With the support of deep learning and neural networks, CV is now capable of human-like performance in image recognition, object detection, and facial recognition to support the application in autonomous vehicles, medical imaging, and smart cities. This chapter also looks into the application of blockchain, generative AI, and CV to provide more data protection, model interpretability, and immersive virtual environment.
United Nations Department of Economic and Social Affairs
Subsidiarity, one of the principles of effective governance for sustainable development, supports the exercise of public functions at the lowest effective level. It is key to advancing the 2030 Agenda for Sustainable Development by helping ensure that public authority is exercised where it can respond most effectively to people’s needs. Subsidiarity and decentralization are closely linked, as decentralization can provide the administrative, fiscal and political arrangements needed to make this possible. For subsidiarity to contribute meaningfully to the Sustainable Development Goals (SDGs), mandates, financing and capacities must be aligned so that sub-national authorities have the authority, resources and skills required to carry out their roles. Applying subsidiarity in support of the 2030 Agenda also requires clear roles and coordination across levels of government, effective mechanisms for joint planning and accountability, and sustained investment in local governance, finance, and resilience. These elements are becoming more important as cities grow and local governments face increasing demands to deliver services, manage risks and support inclusive development. To support the application of subsidiarity, the Committee of Experts on Public Administration (CEPA) has identified five strategies for its implementation, including: multi-level governance; fiscal federalism and decentralization; strengthening urban governance; municipal and local finance; and enhancing local capacity for prevention, adaptation and mitigation of external shocks. This policy brief distills key insights from five UN CEPA strategy guidance notes to illustrate how subsidiarity can be operationalized to strengthen the engagement of subnational authorities in advancing the 2030 Agenda. It highlights the institutional, fiscal and capacity-related conditions required for effective implementation. The brief concludes with twelve policy recommendations for aligning authority, resources and capacities at the appropriate level of government.
The advent of decentralized cryptocurrencies has reignited fundamental debates in monetary economics about the nature and future of money. Proponents of digital currencies argue that decentralized, algorithmically governed assets can supplant central banks in managing monetary conditions and stabilizing economic outcomes. This chapter critically examines this proposition by evaluating cryptocurrencies against the classical functions of money and the core instruments of monetary policy. Grounded in monetary theory – from Friedman’s monetarism and Mises’ Austrian framework to Modern Monetary Theory – and extended through a behavioral finance lens, the analysis reveals that widespread belief in cryptocurrency as a viable monetary policy alternative is driven not merely by technological innovation but by deeply embedded cognitive biases, including overconfidence, narrative-driven speculation, and institutional distrust. The chapter also treats money as an economic asset subject to market competition. Drawing on Austrian economic theory and classical competition principles, the analysis evaluates whether decentralized currencies can realistically compete with sovereign money in an open monetary market. By integrating monetary economics with strategic competition frameworks, the chapter explores whether cryptocurrencies can achieve monetary dominance through efficiency, cost advantages, or differentiated value propositions. Based on principles from strategic business theories such as differentiation and cost-leadership, the chapter treats money as a competitive good subject to market dynamics, ultimately concluding that while cryptocurrencies represent a significant financial innovation, they fundamentally lack the institutional architecture and behavioral predictability required to replace central bank monetary policy.
This chapter presents a comprehensive overview of the historical trajectory and classification of financial technology (FinTech), tracing its growth from foundational digital innovations to the current era of intelligent, data-driven financial solutions. By contextualizing the evolution of FinTech through clearly defined developmental phases – from FinTech 1.0 to FinTech 3.5 – the chapter captures the significant milestones that have redefined how financial services are created, delivered, and consumed. The narrative begins with the early digitization of financial services (FinTech 1.0), progressing through the emergence of online banking and e-commerce (FinTech 2.0), the rise of mobile technologies and decentralized finance (FinTech 3.0), and the ongoing phase (FinTech 3.5), characterized by embedded finance, AI, blockchain, and hyper-personalized offerings. Each phase reflects broader shifts in technological capability, consumer behavior, and regulatory adaptation, painting a dynamic picture of FinTech’s evolutionary journey. A critical component of the chapter is the typology of FinTech entities, providing a structured classification of players in the ecosystem. These include: Infrastructure providers (e.g., cloud computing, cybersecurity, payment gateways), FinTech startups (innovators developing customer-facing solutions in lending, payments, wealth tech, etc.), and TechFins , or large technology companies (like Google, Amazon, and Alibaba) that leverage their digital dominance to enter financial services. The chapter also offers a focused analysis of FinTech growth in emerging economies, where mobile-first strategies, regulatory experimentation (such 92 as sandboxes), and high rates of digital adoption open up both immense opportunities and unique structural challenges. Financial inclusion limited traditional infrastructure, and supportive government initiatives often accelerate FinTech penetration in these markets, though obstacles like digital illiteracy, data privacy concerns, and capital access persist. Finally, the chapter explores how regional and global FinTech ecosystems are shaped by the interplay of innovation, regulation, and technology adoption. It emphasizes that FinTech growth is not uniform but rather influenced by cultural norms, infrastructure readiness, policy frameworks, and market maturity – necessitating localized strategies within a globally interconnected digital financial landscape. In essence, this chapter equips readers with a deep understanding of where FinTech has come from, how it is categorized, and what forces drive its proliferation across diverse economic and geographic environments.
This chapter delves into the evolving landscape of cryptocurrencies and digital assets, offering a comprehensive understanding of their foundations, functions, and financial implications. It begins by distinguishing between cryptocurrencies and stablecoins, unpacking their technological frame-works, value mechanisms, and economic roles within the broader digital finance ecosystem. As decentralized currencies gain mainstream traction, the chapter critically examines the legal and regulatory complexities that differ widely across jurisdictions – highlighting challenges such as investor protection, anti-money laundering (AML) compliance, and central bank policies. Furthermore, the chapter explores the behavioral economics of crypto investors, shedding light on psychological drivers like speculation, herd behavior, and risk perception. Various valuation models, including network value-to-transactions (NVT) and sentiment analysis, are discussed to understand how digital assets are priced in volatile and often opaque markets. Lastly, the chapter evaluates the risks and opportunities of investing in digital assets, balancing concerns over security breaches, market manipulation, and regulatory uncertainty with the potential for high returns, diversification, and financial democratization. Through this multidimensional lens, the chapter equips readers with the analytical tools and critical perspective necessary to navigate the dynamic world of digital finance.
Deniz Erer, Tuna Can Güleç, Özge Korkmaz, Elif Erer
Rapid developments in blockchain, decentralized finance, and tokenization have raised the question of whether Sukuk can complement technology-based financial assets. This study compares the time-varying efficiency and multifractal dynamics of Sukuk indices, DeFi tokens, lending and borrowing tokens, and a FinTech index from May 25, 2020, to November 29, 2023. Using TGARCH, nonlinearity and long-memory tests, MF-DFA, and MF-DCCA, the study examines shock persistence, asymmetric volatility, market efficiency, and cross-market dependence. The findings show that negative shocks increase volatility more strongly than positive shocks and that all markets display nonlinear and multifractal behavior. Sukuk indices, particularly RMENA and RDJSUKUK, show lower market deficiency values than most technology-based assets. However, persistent cross-correlations indicate that Sukuk is not a direct substitute for these assets. Rather, Sukuk may serve as a relatively stable and efficient complementary asset in technology-exposed portfolios.Key Words: Sukuk, DeFi assets, Tokenization, Financial Economics, MF-DFA, MF-DCCAJEL Classification: F65, E44, G15, C58
This chapter examines how emerging technologies – Internet of Things (IoT), Augmented and virtual reality (AR/VR), and advanced cybersecurity – are reshaping FinTech by enabling smarter, more secure, and customer-focused services. IoT supports real-time data collection for personalized banking, usage-based lending, and smart payment systems. AR/VR introduces immersive experiences such as virtual bank branches, 3D investment tools, and interactive financial advisory, enhancing engagement and accessibility. Alongside these innovations, the chapter addresses escalating cybersecurity threats and highlights solutions like biometric authentication, AI-driven threat detection, and encryption to build digital trust. It also critically evaluates the ethical and governance challenges in FinTech, including algorithmic bias, data privacy, and the risks of digital exclusion. The discussion emphasizes fair finance principles, responsible AI deployment, and the complexities of decentralized finance (DeFi) governance. Ultimately, the chapter advocates for integrating innovation with ethical safeguards to create inclusive, transparent, and resilient financial systems.