NGOs Funding Trust, Blockchain and RedChain Prof. Victor Alvarez, MBA ORCID iD: 0009-0001-7933-3830 Department Research in Economic , IEBS Business School, 08840 Barcelona, Spain Department of Humanitarian Economics and NGO Management ETU Institute, Birkirkara, Malta Abstract Persistent trust deficits between donor agencies and Non-Governmental Organizations (NGOs) continue to undermine the efficiency and effectiveness of humanitarian and development assistance, particularly in low-income and institutionally fragile environments. Concerns regarding fund diversion, beneficiary duplication, limited transparency, and weak accountability mechanisms have intensified demand for innovative governance solutions. This paper explores the potential of blockchain technology to strengthen trust in NGO funding through two complementary models: (1) a permissioned blockchain framework for beneficiary verification and aid tracking, and (2) RedChain, a privacy-preserving blockchain infrastructure for humanitarian assistance developed by the Spanish Red Cross. The proposed NGO Trust framework utilizes a distributed ledger to maintain immutable and auditable records of beneficiary registration and fund allocation. By recording encrypted identity credentials and digitally signed transactions, the system reduces the risk of duplicate beneficiary claims, fraud, and reporting inconsistencies across participating organizations. A participation and penalty mechanism further enhances network integrity by incentivizing honest behavior among stakeholders. RedChain extends this approach by integrating blockchain-based transaction recording with zero-knowledge proof technologies, enabling transparent aid distribution while preserving beneficiary privacy. With nearly one million registered transactions, the platform demonstrates the operational viability of blockchain-enabled humanitarian governance at scale. By synthesizing these approaches, this paper proposes an integrated framework for transparent NGO funding, combining beneficiary integrity verification, transaction traceability, privacy protection, and donor accountability. The findings suggest that distributed ledger technologies can significantly improve trust relationships between donors, NGOs, and beneficiaries, while supporting more efficient, transparent, and equitable aid distribution systems. The study contributes to the emerging literature on digital governance, nonprofit economics, and technology-enabled development finance by identifying blockchain as a foundational infrastructure for next-generation humanitarian and social-impact ecosystems. Keywords Blockchain; NGO governance; Humanitarian aid; Trust; Transparency; Beneficiary duplication; Zero-knowledge proofs; RedChain; Donor accountability; Privacy-preserving technology; Smart contracts; Aid distribution JEL Classification G30 â Corporate Finance and Governance: General L31 â Nonprofit Institutions; NGOs; Social Entrepreneurship O33 â Technological Change: Choices and Consequences; Diffusion Processes F35 â Foreign Aid H84 â Disaster Aid and Relief 1. Introduction Non-Governmental Organizations (NGOs) play a central role in delivering humanitarian assistance, poverty alleviation programs, disaster relief, education, health services, and sustainable development initiatives worldwide. According to the United Nations and international development agencies, NGOs have become increasingly important intermediaries between donors, governments, and beneficiaries, particularly in regions where state capacity is limited or institutional trust is weak. Despite their growing influence, concerns regarding transparency, accountability, and the efficient allocation of resources continue to challenge the nonprofit sector (Edwards & Hulme, 1996; Ebrahim, 2003; Najam, 1996). The economics of nonprofit organizations has long emphasized the importance of trust as a mechanism for overcoming information asymmetries between donors and service providers (Hansmann, 1980). Donors frequently lack direct information regarding how funds are allocated, whether intended beneficiaries actually receive assistance, and whether reported outcomes accurately reflect project performance. This information gap creates principal-agent problems in which monitoring costs are high and opportunities for misreporting, inefficiency, or fraud may arise (Pratt & Zeckhauser, 1985; Tirole, 2006). As charitable donations and development aid increasingly flow through complex international networks, maintaining donor confidence has become a critical governance challenge. A substantial body of research has documented accountability deficiencies within humanitarian and development organizations. Ebrahim (2005) argues that traditional accountability systems often emphasize upward reporting to donors while providing limited mechanisms for beneficiary participation and verification. Similarly, Gugerty and Prakash (2010) note that transparency initiatives frequently rely on self-reported information that is difficult to independently audit. In international aid programs, concerns have emerged regarding duplicate beneficiary registrations, diversion of funds, weak recordkeeping systems, and fragmented information sharing among organizations operating in the same geographic areas (World Bank, 2016; OECD, 2021). Digital technologies have increasingly been proposed as tools to address these governance challenges. The broader literature on e-governance and digital accountability suggests that information systems can reduce transaction costs, improve record accuracy, and strengthen institutional transparency (Heeks, 2002; Cordella & Tempini, 2015). Among emerging technologies, blockchain has attracted considerable attention due to its capacity to create immutable, distributed, and verifiable records without requiring centralized trust authorities (Nakamoto, 2008). Since the introduction of Bitcoin, blockchain applications have expanded far beyond digital currencies into supply chain management, public administration, healthcare, identity systems, and humanitarian operations (Tapscott & Tapscott, 2016; Casino, Dasaklis & Patsakis, 2019). Scholars have argued that distributed ledger technologies may improve transparency and accountability by creating tamper-resistant transaction histories accessible to multiple stakeholders (Swan, 2015; Treiblmaier, 2018). Within development economics, blockchain-based systems have been proposed to improve aid distribution, reduce corruption, facilitate identity verification, and enhance financial inclusion in underserved regions (Kshetri, 2017; Saberi et al., 2019). Recent humanitarian applications provide evidence of growing institutional interest in blockchain-enabled governance. The United Nations World Food Programme's Building Blocks initiative demonstrated the feasibility of blockchain-based refugee assistance by facilitating aid transfers while reducing administrative costs and improving transaction traceability. Similarly, studies by Juskalian (2018), Mikhaylov et al. (2020), and Wang et al. (2022) suggest that distributed ledger technologies may strengthen accountability mechanisms in humanitarian environments characterized by weak institutional infrastructure. Nevertheless, important challenges remain. Public transparency requirements often conflict with the need to protect sensitive beneficiary information. Humanitarian organizations must balance donor demands for accountability with ethical obligations regarding privacy, dignity, and data protection. The emergence of privacy-enhancing cryptographic techniques, particularly zero-knowledge proofs, offers a potential solution to this dilemma by enabling verification without revealing underlying personal information (Goldwasser, Micali & Rackoff, 1989; Ben-Sasson et al., 2014). These technologies have increasingly been incorporated into blockchain architectures seeking to combine transparency with confidentiality. This paper contributes to the growing literature on nonprofit governance and development finance by examining two complementary blockchain-based approaches to strengthening trust in NGO funding systems. The first is a permissioned blockchain framework designed to prevent beneficiary duplication and improve donor oversight through cryptographically verifiable registration and transaction records. The second is RedChain, a privacy-preserving humanitarian aid platform developed by the Spanish Red Cross that combines blockchain technology with zero-knowledge proofs to support transparent aid distribution while safeguarding beneficiary privacy. By integrating insights from these models, the study proposes a comprehensive framework for Transparent NGO Funding that addresses four persistent governance challenges: beneficiary verification, transaction traceability, privacy preservation, and donor accountability. The analysis contributes to the fields of nonprofit economics, digital governance, and development finance by demonstrating how blockchain technologies may reduce information asymmetries, lower monitoring costs, and strengthen trust among donors, NGOs, and beneficiaries. Ultimately, the paper argues that distributed ledger systems can serve as foundational infrastructure for a new generation of accountable, transparent, and privacy-respecting humanitarian ecosystems.
Conglomerates are among the most complex organizational forms in capitalism. They own multiple businesses, often across different industries, geographies, operating models, and risk profiles. Some conglomerates own insurance companies, manufacturers, railroads, energy utilities, retailers, banks, technology firms, industrial businesses, media assets, and consumer brands under one corporate umbrella. The central challenge is not only how to operate these businesses, but how to allocate capital among them. A conglomerate must answer a difficult question: Who decides where the money goes? Should capital allocation be centralized at head office, where senior executives and finance committees compare business units and approve investments? Or should capital decisions be decentralized, allowing subsidiary managers to operate autonomously while headquarters focuses only on major capital deployment? Should internal cash flows remain inside business units, or should they be swept to corporate headquarters and redeployed across the group? Should acquisitions be initiated by subsidiaries, by corporate development teams, or by the CEO? Should capital budgeting follow rigid committee processes or owner-oriented judgment? These questions define the capital allocation architecture of the conglomerate. Berkshire Hathaway represents one of the most successful decentralized conglomerate models in modern business history. Warren Buffett and Charlie Munger built Berkshire around autonomy, trust, permanent ownership, strong subsidiary managers, and centralized capital allocation at the highest level. Berkshireâs headquarters remains small, and its operating subsidiaries are largely left alone. Yet the most important capital allocation decisionsâlarge acquisitions, major equity investments, cash deployment, and insurance float allocationâhave historically been handled centrally by Buffett and, increasingly, Berkshireâs designated capital allocation successors. By contrast, many corporations use centralized capital committees. These structures often include formal budgeting processes, investment review boards, hurdle rates, discounted cash flow models, divisional competition for capital, strategic planning cycles, and executive approval layers. Centralization can improve control, risk management, consistency, and capital discipline. However, it can also create bureaucracy, slow decisions, distort incentives, and separate capital decision-makers from operating reality. This chapter compares decentralized and centralized capital allocation models in conglomerates. It argues that neither model is universally superior. The right model depends on business quality, management trust, governance, capital intensity, complexity, regulatory risk, and the competence of headquarters. However, the Berkshire model demonstrates a powerful lesson: decentralization can compound value when paired with exceptional managerial selection, strong culture, conservative financing, and disciplined central capital allocation.
Type of the article: Research ArticleAbstractShareholder voting in conventional corporate governance remains constrained by intermediated proxy systems, information asymmetries, and limited transparency. This study aims to systematically synthesize recent scholarly, legal, and policy literature to evaluate whether, and under what legal and institutional conditions, blockchain-based voting and decentralized autonomous organization (DAO) architectures can enhance shareholder democracy through hybrid âcode-plus-lawâ governance models. Adopting an interdisciplinary qualitative design, the paper combines a systematic literature review with doctrinal legal analysis, drawing on a broad corpus of recent scholarly, legal, and policy sources published from 2020 through 2025. Evidence is synthesized into six structured comparative tables covering voting auditability, shareholder participation, token concentration, legal recognition, DAO design features, and hybrid âcode-plus-lawâ governance models. The review highlights consistent improvements in three core dimensions compared to legacy proxy systems: enhanced auditability and end-to-end verifiability, speedier aggregation of voting outcomes, and broader feasibility of cross-border shareholder participation. Simultaneously, four risks keep appearing: token concentration (âwhale dominanceâ), technical and governance scalability limits, unequal digital literacy and access, and persistent gaps in the legal recognition and enforceability of DAOs. Overall, the findings suggest that hybrid arrangements that combine blockchain-based transparency and efficiency with conventional legal safeguards are more apt to provide for inclusive participation and durable legitimacy than purely code-based or purely traditional governance models.
This paper examines whether token design can serve as a signal of venture quality in decentralized fundraising environments. We develop a simple model in which an entrepreneur privately informed about project quality chooses between a neutral token and an incentive-compatible token embedding a milestone-contingent feature. While the latter increases the likelihood of attracting external funding, it imposes a private cost on the entrepreneur.Because token design is publicly observable prior to investment, it affects investor beliefs and financing decisions. The model shows that a separating equilibrium arises only for an intermediate range of design costs. If incentive-compatible features are too inexpensive, low-quality ventures mimic high-quality ones and the signal loses credibility. If they are too costly, even high-quality entrepreneurs refrain from adopting them, leading to pooling outcomes.The paper highlights how signaling can be embedded directly in token architecture through observable design choices that constrain entrepreneurial behavior. The model also yields testable empirical implications: token structures imposing meaningful constraints on founders should attract greater investor participation, whereas nearly costless features should not predict venture quality. These predictions are consistent with emerging evidence on token-based financing.
We document a sizeable disposition effect in the market for non-fungible tokens (NFTs). Using a comprehensive transaction dataset from OpenSea, we show that NFT holders systematically realize gains prematurely while holding onto losses, mirroring behavior documented in traditional equity markets. Consistent with a high participation rate of retail investors and the lack of clear fundamental values, the effect is significantly more severe than in equity markets. We further find that the magnitude of the disposition effect attenuates in December, consistent with end-of-year tax-loss harvesting incentives, suggesting that on-chain transactions can be monitored by tax authorities. Finally, to address the NFT market's episodic illiquidity, we introduce a novel measure of the disposition effect based on the time-to-sale of listed assets. Our findings extend behavioral finance theory to digital-asset markets and provide new tools for studying the disposition effect in illiquid trading environments.
This paper studies governance participation in Decentralized Autonomous Organizations (DAOs) to evaluate whether participation insights from corporate governance extend to token-weighted, decentralized voting systems. Using proposal-level data from 1,959 governance proposals across five major DAOs between July 2022 and December 2024, we examine two distinct dimensions of participation: voting-power mobilization and participation breadth. We test whether marginal procedural design featuresâspecifically voting-window durationâaffect participation once institutional identity is controlled for. Across linear and count-data specifications, voting-window duration has no statistically or economically meaningful association with either participation measure. In contrast, persistent DAO-level differences explain the vast majority of participation variation, indicating that persistent DAO-level heterogeneity accounts for substantially more variation in participation than marginal differences in voting-window duration. We further document dynamic participation patterns: later proposals mobilize greater voting power without expanding the participating electorate. By exploiting the transparency and proposal-level granularity of DAO governance (Yermack, 2017), this study directly observes participation patterns that are typically inferred in shareholder voting. The findings reinforce a central insight of corporate governance theory: participation is more closely associated with institutional identity than with marginal differences in voting window duration.
Purpose This paper reviews the application of game theory in finance, focusing on its role in modeling strategic interactions among market participants. It synthesizes classical models such as Nash equilibrium and signaling games while integrating emerging themes including behavioral finance, sustainability-linked decisions, decentralized finance (DeFi) and artificial intelligence (AI)-driven agents. The study aims to highlight how game-theoretic frameworks inform financial decision-making, market design and governance and to identify conceptual gaps and future research directions. Design/methodology/approach The study employs a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol, complemented by bibliometric mapping using VOSviewer. It analyzes 78 peer-reviewed articles published between 2000 and 2025 across five finance domains: asset pricing, corporate finance, investment strategies, financial markets and behavioral finance. Conceptual frameworks and taxonomies are developed to categorize game-theoretic models by strategic orientation and information structure, offering a structured synthesis of theoretical advancements and practical applications. Findings Game theory enhances understanding of strategic behavior in finance, particularly under conditions of asymmetric information and market complexity. Key findings include the relevance of signaling games in initial public offerings pricing, repeated games in environmental, social and governance commitments and mechanism design in DeFi governance. The review identifies gaps in behavioral integration, empirical validation and modeling of decentralized ecosystems. It proposes future research directions involving multi-agent learning, adaptive mechanism design and sustainability-linked financial strategies. Research limitations/implications The review is limited by its focus on published literature and may exclude emerging models in unpublished or proprietary research. Empirical validation of proposed frameworks remains a future research priority. Practical implications The paper offers actionable insights for regulators, investors and policymakers by applying game-theoretic tools to systemic risk management, portfolio allocation and financial regulation in digitized markets. Originality/value This study provides a novel synthesis of game theoryâs evolution in finance, introducing conceptual frameworks that integrate behavioral, technological and sustainability-linked dimensions.
We analyze 15,097 blocks proposed for inclusion in Ethereum's blockchain over an eight-minute window on December 3, 2024, during which 38 blocks were added to the chain. We classify transactions as exclusive -- appearing only in blocks from a single builder -- or private -- absent from the public mempool but included in blocks from multiple builders. We find that, depending on the methodology, exclusive transactions account for between 77.2% and 84% of the total fees paid by transactions in winning blocks. Moreover, we show that exclusivity cannot be fully attributed to persistent relationships between senders and builders: only between 7% and 8.4% of all on-chain exclusive transaction value originates from senders who route exclusively to one builder. Finally, we observe that transaction exclusivity is dynamic. Some transactions are exclusive at the start of a bidding cycle but later appear in blocks from multiple builders. Other transactions remain exclusive to a losing builder for two or three cycles before appearing in the public mempool. These transactions are therefore delayed and then exposed to potential attacks.
Given Vietnam's current anticorruption campaign and its distinctive context of decentralized governance and public sector dominance, this paper investigates how anticorruption efforts affect corporate investment behaviour during 2006 and 2019. Using a novel text-based measure of anticorruption and comprehensive firm-level datasets, we uncover a consistent pattern that firms tend to delay investments in response to heightened uncertainty triggered by anticorruption activities. This strategic hesitation reflects a rational response to avoid potential regulatory and political uncertainty, and holds across a wide range of robustness checks, including alternative model specifications, variable definitions, and advanced estimation techniques such as system GMM and entropy balancing. Our findings also reveal that anticorruption campaigns significantly reduce informal business costsâparticularly bribery, thus highlighting institutional improvements and a more transparent business environment. Notably, while public sector investment efficiency improves under the campaign, private firms show no significant efficiency gains, underscoring the asymmetry in how reforms affect different ownership structures. By bridging institutional reform with corporate finance, the study offers new insights into the channels through which anticorruption influences firm decision-making, governance, and political strategy. This research fills a critical gap in the literature, demonstrating that anticorruption is not merely a legal or ethical issue, but a transformative force in corporate investment dynamics.
The swift advancement of technology has transformed numerous sectors, particularly the financial services business, with Decentralised Finance (DeFi) emerging as a notable disruptor. To guarantee the sustained development and integration of DeFi, it is necessary to investigate and comprehend the emerging trends in this field. This study presents a bibliometric analysis of 181 Decentralized Finance articles published from 2010 to 2024 in the Scopus database The data were examined and illustrated utilising the VoS viewer platform and R software, yielding both descriptive and visual insights. Authored by 503 researchers across 418 universities, these works span 129 journals and cite 10,428 references. Publications show an annual growth rate of 29.2 %, with 2024 exhibiting unprecedented output. Frontiers in Blockchain leads with six publications, followed by the Journal of Risk and Financial Management. New Zealand tops the citation rankings, led by Auckland University with 338 citations. Bellavitis C. and Chen Y. are the most prolific authors each with 338 citations. The cluster analysis identifies six thematic areas, offering insights into various aspects of decentralized finance. This study offers critical insights for academics, policymakers, and industry practitioners by mapping DeFi's transition from conventional financial systems to decentralized ecosystems. The findings illuminate research gaps, propose future research avenues, and underscore the necessity of developing policies and cyber hygiene protocols to mitigate the risks of decentralized finance. This work thus serves as a valuable resource for advancing the discourse on DeFi and its implications for financial innovation.
The effect of competitive pressure on ESG may diverge. On the one hand, when competitive pressure increases, firms have incentives to increase moral capital by fulfilling ESG to hedge against risks, on the other hand, the decline in firm performance due to competition may weaken firms' ability to fulfill ESG. Research on this issue has important theoretical and practical significance. Based on data from Chinese listed companies from 2010 to 2022, we used business similarity as a proxy for competitive pressure and find it significantly improves corporate ESG performance, i.e., the risk hedging effect of ESG dominates. Corporate financing constraints negatively moderate this effect. The ability of firms to transfer risk increases as their business becomes more decentralized, which in turn weakens this effect. Conversely, when firms have more concentrated sales, their ability to transfer risk diminishes, amplifying this effect. Our study explores the measure of competitive pressure and business similarity, also expands the research on the impact of business characteristics on the non-economic consequences of firms and ESG motivations.
This paper empirically investigates the determinants and performance implications of capital structure for two dominant Indian conglomerates, Reliance Industries Limited (RIL) and the diversified Tata Group, utilizing annual data spanning the critical 2011â2021 period. The study addresses the ambiguity regarding optimal financing choices in large emerging market firms, focusing on the contrasting centralized, capital-intensive structure of RIL versus the industry-aligned, decentralized financing strategies of major Tata subsidiaries (TCS, Tata Steel, Tata Motors). A dynamic panel data approach, utilizing the System Generalized Method of Moments (Sys-GMM), is employed across the 11-year period to address issues of endogeneity, unobserved firm heterogeneity, and, critically, to accurately estimate the speed of leverage adjustment, given the observed persistence of financing decisions. The results confirm a dual-theory application dictated by corporate strategy and industry alignment. RILâs financing choices, particularly its aggressive leveraging followed by deleveraging toward zero net debt by 2021, are predominantly explained by the Pecking Order Theory (POT), where high profitability negatively predicts reliance on external debt. Conversely, the Tata Groupâs sub-entities strongly align with the Trade-Off Theory (TOT), with asset tangibility significantly dictating debt capacity (e.g., high debt for Tata Steel vs. minimal debt for TCS). Crucially, the analysis confirms that leverage generally showed a significant negative impact on RILâs operational performance [Return on Assets (ROA) and Return on Equity (ROE)], validating its strategic shift towards an equity-heavy model. The findings underscore the critical role of strategic corporate philosophy (centralized flexibility versus decentralized industry alignment) in shaping capital structure efficiency and shareholder value creation within complex conglomerates.
Open access
Working Capital and Financial Performance
Innovations and Analysis in Business and Education
Purpose Cryptocurrencyâs novelty and volatilityâcombined with the absence of standardized reporting prior to 2023âcreated an opaque information environment. This study explores whether such conditions enabled assertive impression management in corporate reporting. We examine how firms not only varied the volume of cryptocurrency disclosures over time, but also strategically manipulated their readability . Additionally, we use this context to demonstrate the utility of machine learning and natural language processing tools for consistent analysis of complex financial narratives. Study design We analyze full-text annual reports, MD&A sections, and proxy statements from five publicly traded U.S. firms with diverse cryptocurrency involvements. Our methodology includes machine learning-based topic modeling, readability assessment using standardized indices, and visualization tools. Findings (i) Information Demand: Google search trends for target firms are strongly associated with Bitcoin price movements, reflecting external attention cycles. (ii) Impression Management: Firms increase both the frequency and readability of crypto disclosures in favorable markets and reduce or obscure them in downturns, consistent with strategic impression management. (iii) Readability: Crypto-related disclosures are significantly more readable than non-crypto sections from the same reports suggesting deliberate simplification. Contributions This study advances the limited literature on cryptocurrency disclosure by offering a textual and behavioral lens on corporate impression management. A key contribution is the integration of readability metrics, public attention signals, and NLP tools into disclosure analysis. We highlight how firms use both narrative framing and readability engineering as tools to influence perceptionâespecially in periods of regulatory uncertainty. Implications Our findings have direct implications for policy and practice: (i) Policymakers should consider not only disclosure quantity but also its linguistic clarity and comparability, especially for volatile assets. (ii) Investors and analysts can use automated text analysis to detect subtle impression management tactics and to interpret the strategic use of clarity in disclosure narratives.
The emergence of Decentralized Autonomous Organizations (DAOs) presents a fundamental challenge to the traditional corporate form, which has dominated economic organization for over a century. Built on blockchain technology, DAOs propose a new model for coordinating economic activity. This study addressed the critical question of institutional efficiency by applying the lens of Transaction Cost Economics (TCE) to compare DAOs and traditional corporations. A comparative institutional analysis was conducted using a mixed-methods approach. We employed a multiple case study design, analyzing two representative DAOs and two analogous traditional corporations from Q1 2023 to Q4 2024. Data collection involved the systematic analysis of archival records, including 215 DAO governance proposals and corporate filings, and 32 semi-structured interviews with key participants. A novel analytical framework was developed to categorize transaction costs into ex ante (search, bargaining) and ex post (monitoring, enforcement), further distinguishing between 'on-chain' and 'off-chain' costs. The study revealed significant trade-offs between the two organizational forms. Traditional corporations exhibited high ex ante bargaining costs (legal, negotiation) and ex post monitoring costs (managerial overhead), but benefited from established legal frameworks that reduced enforcement uncertainty. Conversely, DAOs significantly lowered specific transaction costs through automation via smart contracts, particularly in on-chain bargaining and enforcement for codified tasks. However, DAOs incurred substantial, often hidden, new transaction costs related to off-chain social coordination, governance participation, and navigating legal ambiguity. This was termed the 'Governance Overhead Paradox'. In conclusion, DAOs do not represent a universally superior organizational form but rather a new point on an institutional possibility frontier. They are highly efficient for tasks that are global, permissionless, and computationally verifiable. Traditional firms retain advantages in contexts requiring complex, subjective decision-making and legal certainty. The future of the firm is likely not a replacement of one form by the other, but a pluralistic ecosystem where hybrid models emerge.
Hong Qu, Krzysztof Gogol, Florian GrÃķtschla, Claudio J. Tessone
Decentralized Finance (DeFi) lending enables permissionless borrowing via smart contracts. However, it faces challenges in optimizing interest rates, mitigating bad debt, and improving capital efficiency. Rule-based interest-rate models struggle to adapt to dynamic market conditions, leading to inefficiencies. This work applies Offline Reinforcement Learning (RL) to optimize interest rate adjustments in DeFi lending protocols. Using historical data from Aave protocol, we evaluate three RL approaches: Conservative Q-Learning (CQL), Behavior Cloning (BC), and TD3 with Behavior Cloning (TD3-BC). TD3-BC demonstrates superior performance in balancing utilization, capital stability, and risk, outperforming existing models. It adapts effectively to historical stress events like the May 2021 crash and the March 2023 USDC depeg, showcasing potential for automated, real-time governance.
This paper investigates the dynamic relationship between geopolitical uncertainty and decentralized finance (DeFi) token prices using a nonlinear, time-series-based framework. Leveraging the GPRD index as a proxy for global risk sentiment, the study examines seven prominent DeFi tokens representing diverse functional roles within the ecosystem. Through a layered empirical strategy - including Transfer Entropy, Mutual Information, Kernel-based Granger Causality, and Structural Time Series. Modeling - the analysis identifies both predictive and structural dependencies between GPRD and token valuations. The results reveal that tokens associated with financial-layer functions such as lending, collateralization, and liquidity rebalancing (e.g., Maker, Aave, BAL) exhibit stronger and more persistent exposure to geopolitical shocks than exchange-layer tokens like Uniswap or PancakeSwap. Kernel Granger causality confirms significant nonlinear predictive power of GPRD across all tokens, while structural decomposition shows that GPRD systematically depresses the long-term trend component of financial DeFi tokens. These findings indicate that global uncertainty operates not only through shortterm volatility, but also as a sustained driver of DeFi asset repricing. By combining information-theoretic and structural techniques, the study provides a comprehensive empirical lens through which to evaluate systemic risk transmission into DeFi markets. The results underscore the heterogeneous macro-financial sensitivity of decentralized protocols and suggest the need for differentiated risk assessment frameworks in crypto-asset research and governance.
We construct an empirically founded model of a repo trade intermediated by two broker-dealers and prove multiple equilibrium and the existence of equilibrium at the joint profit maximizing volume of trade. We then present a smart contract that resolves multiple equilibrium by requiring each broker-dealer to report its client schedule and its minimum hurdle spread, and implementing a selection rule that filters out hurdle-infeasible outcomes. Whenever there exists an equilibrium that exceeds both hurdle spreads, the protocol selects the joint profit maximizing feasible trade and thereby avoids a collapse to no trade. The smart contract is a machine executed algorithm which eliminates the need for trust. Hardware and cryptography are used to prevent leakage of broker-dealer client trade schedules, and to enable privacy-protected auditing with zero-knowledge proofs of the integrity of computations. The outcome can be implemented by a myopic strategy where a broker-dealer truthfully reports its own variables without anticipating its counterparty's reports. This minimizes cognitive and computational complexity, thereby making our smart contract suitable for real-world deployment.
Leonardo Henrique Lima de Pilla, Alketa Peci, Rodrigo de Oliveira Leite
ABSTRACT Corporatization in the public sector entails decentralizing the provision of public goods and services to more autonomous entities, including state-owned enterprises (SOEs). Research indicates that the decision to corporatize is driven, among other factors, by the pursuit of financial sustainability in public organizations. A continuing debate revolves around whether the political ideology of incumbents is linked to the creation of SOEs. However, limited attention has been given to understanding if incumbentsâ ideology shapes SOEsâ financial performance and, hence, financial sustainability. This is concerning because SOEs operate beyond political cycles, facing pressures from ideologically different governments over time. Herein, we investigate whether the incumbentsâ ideologies shape SOEsâ financial performance. We hypothesize that the more right leaning the incumbent, the greater the SOEsâ financial performance. However, given that incumbentsâ decisions are influenced by their political partiesâ behaviors, the effects of ideology may be contingent on these factors. Thus, we investigate whether the association of incumbentsâ ideology with SOEsâ financial performance is weaker when incumbentsâ political parties display non-policy behaviors (e.g., by prioritizing electoral outcomes or office occupation). We analyze a 2019â2022 panel of 317 SOEs controlled by 27 subnational governments in Brazil with both FGLS and instrumental variable regression approaches. The data comprising 1,116 SOE-year observations confirm our hypotheses. Our research contributes to scholarship on the drivers of public organizationsâ financial performance and sheds light on the role of political contingencies, such as incumbentsâ ideology and party predominant behaviors regarding SOEsâ financial performanceâa commonly overlooked gap in current research.
Decentralized finance (DeFi) lending platforms often require over-collateralization, excluding users without substantial crypto holdings. This paper introduces LFG, a novel DeFi protocol that leverages on-chain social profiles and tokenized reputation to assess creditworthiness. By integrating Ethereum smart contracts with Layer-2 solutions (Ethereum, Polygon), decentralized storage (IPFS) and zero-knowledge proofs, LFG enables undercollateralized loans while preserving privacy. We present a technical architecture, analyze security risks, and compare LFGs with traditional models using quantitative metrics. The results show a 40% reduction in collateral requirements for users with high reputation scores on the chain.
Ilan Alon, Haakon Stole Klemetsen, AuÅĄrinÄ Å ilenskytÄ, Ilan Gildin
Purpose This study aims to explore the innovative governance structures enabled by blockchain-based decentralized autonomous organizations (DAOs) in the context of international business (IB). As nonhierarchical entities managed through collective voting and peer-to-peer interactions, DAOs challenge traditional assumptions of multinational corporation (MNC) governance. Design/methodology/approach The authors perform a literature review, which combines qualitative content analysis of both academic papers on DAO and whitepapers with quantitative analysis of bibliometrics using VosViewer. Findings The findings highlight DAOsâ ability to generate new research questions and offer a foundation for future studies on decentralized governance in IB. Through a bibliometric analysis of 73 papers from Web of Science and qualitative content analysis, the authors identify four primary research streams in the DAO literature. A deep dive into financial DAOs, or DeFi DAOs, reveals insights into their governance mechanisms and implications for the studies in the field of IB. Research limitations/implications Research on DAOs is in its early stages, and the practice in IB is nascent. As the regulatory, economic and technological landscape for DAOs changes, more research will be needed on the governance mechanisms and their sustainability. Originality/value This paper advances the field by providing a multilevel analysis of DAOsâ potential impact on IB, considering macro (country), meso (MNC/DPE) and micro (multicultural team and individual) levels.
Enterprise innovation investment is influenced by the actions of innovation subjects, whereas regulating shareholders' equity pledge behavior facilitates innovation investment and finance but also carries dangers and affects enterprise innovation investment. Methods:This paper builds an unbalanced panel model to empirically analyze the impact of controlling shareholders' equity pledges on corporate innovation and its heterogeneous characteristics. It also looks at the moderating role of corporate financing constraints and the mediating role of equity incentives, using data from A-share listed companies in China's pharmaceutical manufacturing industry from 2015 to 2022. Innovation investment is substantially inversely correlated with controlling shareholders' equity pledge; that is, firms' creative behavior and intensity are inhibited by equity pledge. Results and conclusions:The results also show that controlling shareholders' equity commitments have a more pronounced negative impact on enterprises' ability to innovate than non-state-owned and decentralized equity firms. The relationship between company innovation and the equity pledge of controlling shareholders is somewhat mediated by equity incentives. The relationship between controlling shareholders' equity promises and enterprises' innovation is negatively moderated by financing limitations, which also reduces R&D expenditure and stifles innovation.