Search Results (297)

The Montado, a traditional Mediterranean agro-silvopastoral system, has historically sustained ecological and economic functions through the integration of trees, livestock, and crops. Today, its multifunctionality is increasingly threatened by climate variability, market volatility, and evolving policy frameworks. While previous research has examined Montado dynamics at landscape or plot scales, less attention has been paid to sustainability trajectories at the farm level, where management decisions are made. This study bridges that gap by assessing the sustainability dynamics of farms through a participatory, typology based, scenario approach grounded in a regional typology. We characterized three representative farm archetypes (forestry-focused, mixed agro-silvopastoral, and livestock-focused) and evaluated their trajectories under plausible future scenarios driven by climate, market, and policy pressures. Scenario outcomes were assessed using expert-based scoring (five-point scale), revealing score differences of up to two points across sustainability dimensions between farm archetypes and scenarios. Findings reveal marked trade-offs: Tree-focused farms maintain high environmental value but remain vulnerable to market and labor constraints, while livestock-specialized farms achieve higher economic output at the expense of ecological integrity. Mixed systems demonstrate greater resilience through diversification but face significant labor intensity challenges. We conclude that current “one-size-fits-all” policies generate contradictory incentives. Therefore, adaptive governance frameworks (e.g., results-based payment schemes) are essential to realign farm economics with ecological stewardship. Beyond the Montado, the approach provides insights relevant to other Mediterranean agroforestry systems facing similar sustainability challenges. Full article

Cryptocurrencies are widely recognised for catalysing distributed ledger technologies and tokenisation, innovations that are transforming payment systems globally. However, their role as money is often contested and the subject of intense academic and policy debate. Nevertheless, new taxonomies of money allocate a unique place for cryptocurrencies. Described based upon a few high-level features, cryptocurrencies, except for stablecoins, are assumed to be a uniform group that can indeed be studied and categorised as such. Moreover, the logic of their creation is often looked at from a broad decentralisation and disintermediation perspective and remains ambiguous and questionable at best. This paper reports the findings of a clinical investigation into the top 30 cryptocurrencies representing 95.5% of the total crypto market capitalisation. This study is primarily concerned with their logic of creation, and how they compare with that of fiat money and central bank digital currencies. The findings reveal that, unlike fiat money, and CBDCs, crypto mechanics depict a diverse assortment of logics. The evidence suggests that despite widespread technical innovations, the crypto ambition to provide an alternative to centrally controlled debt-based fiat money has managed to add a combination of transaction validation, mathematical guesswork, pseudo-randomness, and size dependent probability as alternative logics of creation and allocation. While centrally managed bank-controlled debt-based fiat money leaves a lot to be desired, protocol-managed, code-controlled, size-dependent probabilistic money does not seem like much of an upgrade. This paper addresses the limits of tokenisation as a transformational tool and argues that cryptocurrencies may have helped trigger improvements in the technology of money, but not in its logic of creation. Indeed, to compete in the emerging monetary landscape it has helped create, i.e., the ubiquitous tokenisation of debt and debt-based fiat money, the crypto revolution will have to extend its value proposition beyond technology and pseudo-randomness. Full article

Green FinTech involves facilitating sustainable payments, banking, and investment; nevertheless, it is subject to consumer trust and perceptions of ‘green’ value. The literature on this topic is fragmented, with information systems literature typically considering trust as a broad acceptance construct, while sustainable literature considers it as a risk of ‘greenwashing’ without integrating credibility into adoption models. This systematic review aggregates 15 empirical studies and addresses five research questions. RQ1 examines the theoretical models applied to examine trust in green/sustainable FinTech adoption. RQ2 examines the conceptualization and measurement of trust across different contexts, distinguishing institutional/provider trust, platform/tech trust, and sustainability claim credibility trust. RQ3 examines the function of trust within behavioral models (predictor, mediator, moderator). RQ4 examines methodological characteristics and quality indicators (research design, sampling frame, reliability, and bias). RQ5 examines the direct relationship between trust and adoption intention using meta-analysis. The systematic review follows a set of PRISMA guidelines, where we searched Scopus and Web of Science (2015–2026) and applied an RQ-based coding scheme to peer-reviewed articles. Measures of trust varied significantly (unidimensional, integrity–competence–benevolence, and technology-specific scales), limiting cross-study comparability. Using random effects, we found a significant positive relationship between trust and intention (pooled standardized direct path coefficient β = 0.27, 95% CI [0.14, 0.41]) with considerable heterogeneity (I² = 88%) and a wide prediction interval including near-zero effects. Literature essentially endorses trust as a significant yet context-dependent construct, emphasizing the necessity for measurement standardization, a more distinct differentiation between sustainability trust and general platform trust, regular reporting of reliability and bias assessments, and focused evaluations of boundary conditions (e.g., environmental skepticism, regulatory framework, and FinTech type). Full article

As cross-border e-commerce expands in emerging economies, consumer participation increasingly depends on perceived transaction risk linked to digital payments, settlement, dispute resolution, and institutional enforceability. This study reconceptualizes online purchase intention (OPI) as a decision embedded in retail international finance. Extending the Theory of Planned Behavior (TPB), it integrates Internet Trustworthiness Behavior (ITB) and Country of Origin (COO) as risk-relevant signals shaping consumer judgment under cross-border uncertainty. Survey data from 390 digitally active consumers in the Dominican Republic were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that ITB strengthens perceived behavioral control, attitudes toward online purchasing, and subjective norms, while also exerting a direct positive effect on OPI. COO emerges as a strong direct predictor of OPI, functioning as a heuristic indicator of country credibility when formal safeguards appear weak. Contrary to standard TPB expectations, perceived behavioral control negatively predicts OPI, suggesting that greater digital competence may heighten awareness of expected losses and limited recourse in high-risk environments. The findings advance international business and finance research by showing how micro-level trust practices and macro-level country signals jointly shape consumer risk management in cross-border digital markets, with implications for inclusive participation and consumer protection. Full article

Identity-based communities that share common characteristics, beliefs, and experiences (e.g., Black LGBTQ+ communities) have historically been conceptualized as protective bubbles that buffer Black LGBTQ+ individuals against the deleterious effects of systemic racism and cisheterosexism. However, this monolithic narrative often masks the internal power dynamics that divide belonging. This study explores the exclusionary dynamics embedded within these safe spaces, examining how internal hierarchies of skin tone, socioeconomic status, and gender performance function as proximal stressors. Guided by a critical constructivist paradigm, this study utilized Reflexive Thematic Analysis to analyze open-ended survey responses from 74 Black LGBTQ+ adults. Data were drawn from a larger mixed-methods study and analyzed using a six-phase recursive process to identify latent patterns of intragroup gatekeeping. The analysis revealed that the sanctuary of the community is restricted. Three primary themes emerged: (1) Phenotypic Capital and the Politics of Authenticity, where lighter skin tone triggered authenticity scrutiny and darker skin tone faced rejection based on physical appearance; (2) Socioeconomic Gatekeeping, where belonging was stratified by the cost of participation and protective insularity within working-class spaces; and (3) Policing the Binary, where rigid adherence to gender archetypes created a landscape of performance surveillance. Access to community resilience is not a universal right but a negotiated status contingent upon the payment of a resilience tax. To promote genuine health equity, researchers and practitioners working with this population must move beyond the uncritical referral to “community” and actively dismantle the internalized systems of oppression that fracture collective survival. Full article

Quantum computing threatens the security foundations of global financial systems, exposing long-lived data and signed digital assets to “harvest-now, decrypt-later” attacks. While the timeline for cryptographically relevant quantum computers remains uncertain, regulatory signals from the USA, UK, EU, Canada, and Australia converge: financial institutions and payment infrastructures must begin migrating to post-quantum cryptography (PQC) now to preserve confidentiality, integrity, and systemic stability. This paper maps emerging standards and roadmaps, contrasting binding requirements like the EU’s DORA crypto-agility provisions with non-binding guidance from NIST, ENISA, and ETSI. Despite a shared intent to secure high-risk use cases by 2030–2031 and complete migration by 2035, divergences in enforcement and milestones create uncertainty for cross-border banks and financial market infrastructures. In parallel, technical adoption is advancing: major browsers, cryptographic libraries (OpenSSL/BoringSSL), and CDNs (e.g., AWS CloudFront) have deployed hybrid PQC key exchange in TLS 1.3, proving confidentiality defenses are viable at internet scale. The paper synthesizes historical transition lessons, sector-specific regulatory drivers, and operational constraints in payment infrastructures to derive a new, principle-based migration: crypto-agility, risk-prioritized scoping, hybrid deployment, vendor and supply-chain alignment, independent testing, and proactive supervisory engagement. Acting now reduces long-tail exposure and ensures readiness for imminent compliance and interoperability deadlines. Full article

Informal food trading is a cornerstone of urban livelihoods and food security in Namibia, yet traders operate under fragile conditions marked by limited capital, policy exclusion, and exposure to shocks such as COVID-19. Despite this vulnerability, traders exhibit resilience through everyday forms of social innovation. This study investigates how adaptive pricing, customer credit, and digital communication and e-payment practices function as pathways of resilience among 470 informal food traders in Windhoek, using Structural Equation Modelling to assess gender-differentiated determinants and outcomes. The analysis reveals that women’s adoption of adaptive pricing and digital tools is driven primarily by education and startup capital, while men’s innovation practices are shaped by vendor type and access to financing. Social innovations mediate the effects of these structural factors on enterprise growth, demonstrating that innovation acts as a critical mechanism linking resources and resilience. The study concludes that enhancing informal traders’ resilience requires policies that strengthen human and financial capital, improve digital inclusion, and recognize gendered differences in access to opportunity. It recommends targeted support for women’s entrepreneurial training, affordable credit, and digital infrastructure to transform the informal food sector into a more equitable and sustainable component of Namibia’s urban economy. Full article

Digitalization is increasingly central to economic growth strategies, yet robust macro-level evidence on the role of SME-led e-commerce remains limited. Drawing on the Resource-Based View, this study examines how SME digitalization, internet finance, and platform-based activities influence regional economic growth in China, and how these effects depend on digital infrastructure readiness (DIR). We construct an annual panel of 30 provincial-level regions in China over 2015–2024 and estimate dynamic relationships using two-step system GMM to address endogeneity and growth persistence. The results show that SME digitalization, supply-chain efficiency, mobile payment penetration, tech-driven employment growth, platform-economy contribution, and DIR all exert statistically significant positive effects on GDP growth. Quantitatively, a 10-percentage-point increase in SME digitalization is associated with approximately 0.3-percentage-point higher regional GDP growth, while a 10-point increase in DIR corresponds to about 0.4-percentage-point higher growth. Moderation analyses reveal that DIR significantly amplifies the growth effects of e-commerce expansion, mobile payments, and digital marketing, whereas its moderating role is weaker or insignificant for cross-border payments and supply-chain efficiency. These findings reconceptualize digitalization as a coordinated bundle of complementary resources and position DIR as a critical enabling capability for translating SME digital transformation into macroeconomic growth. The study offers policy-relevant evidence for targeting infrastructure investment and digital-economy strategies in emerging platform economies. Full article

As a core support for the integration of new energy and smart grids, Vehicle-to-Grid (V2G) networks face a core contradiction between user privacy protection and transaction security traceability—a dilemma that is further exacerbated by issues such as the quantum computing vulnerability of traditional cryptography, cumbersome key management in stateful ring signatures, and conflicts between revocation mechanisms and privacy protection. To address these problems, this paper proposes a post-quantum revocable linkable ring signature scheme based on SPHINCS+, with the following core innovations: First, the scheme seamlessly integrates the pure hash-based architecture of SPHINCS+ with a stateless design, incorporating WOTS+, FORS, and XMSS technologies, which inherently resists quantum attacks and eliminates the need to track signature states, thus completely resolving the state management dilemma of traditional stateful schemes; second, the scheme introduces an innovative “real signature + pseudo-signature polynomially indistinguishable” mechanism, and by calibrating the authentication path structure and hash distribution of pseudo-signatures (satisfying the Kolmogorov–Smirnov test with $D\le 0.05$), it ensures signer anonymity and mitigates the potential risk of distinguishable pseudo-signatures; third, the scheme designs a KEK (Key Encryption Key)-sharded collaborative revocation mechanism, encrypting and storing the $(I,pk,RID)$ mapping table in fragmented form, with KEK split into $KE{K}_1$ (held by the Trusted Authority, TA) and $KE{K}_2$ (held by the regulatory node), with collaborative decryption by both parties required to locate malicious users, thereby resolving the core conflict of privacy leakage in traditional revocation mechanisms; fourth, the scheme generates forward-secure linkable tags based on one-way private key updates and one-time random factors, ensuring that past transactions cannot be traced even if the current private key is compromised; and fifth, the scheme adopts hash commitments instead of complex cryptographic commitments, simplifying computations while efficiently binding transaction amounts to signers—an approach consistent with the pure hash-based design philosophy of SPHINCS+. Security analysis demonstrates that the scheme satisfies the following six core properties: post-quantum security, unforgeability, anonymity, linkability, unframeability, and forward secrecy, thereby providing technical support for secure and anonymous payments in V2G networks in the quantum era. Full article

Low-income individuals are unlikely to save relatively large sums on a regular basis; however, many still fall short of even the modest threshold required for long-term financial security. This study examines the determinants of benchmark-defined undersaving among retail e-payment agents (REAs) operating in the urban slums of Lagos, Nigeria. We use a contingent valuation survey, descriptive analysis, and logistic regression to examine how selected behavioural and demographic factors, alongside a 60-day experimental intervention—the Programmed Microsaving Scheme (PMSS), a hard daily commitment savings device—affect the likelihood of undersaving, defined as saving less than 12% of each REA’s average daily income. While the PMSS appears to have contributed to improvements in post-treatment saving participation and performance among REAs, it did not significantly increase the likelihood of reaching or exceeding the benchmark savings threshold. Consistent with this, average daily income, age, gender, marital status, education, and religion are statistically insignificant predictors of benchmark-defined undersaving. In contrast, self-control, measured using a literature-validated instrument, exhibits a statistically significant negative association with benchmark-defined undersaving, indicating that higher self-control reduces the likelihood of failing to meet the benchmark. Measured risk aversion similarly shows no significant association. Notably, this study introduces a novel 60-day PMSS, co-designed with REAs and neobanks to accommodate daily income savings—a characteristic of the informal sector largely overlooked in the literature on commitment savings devices. From a policy perspective, the findings suggest that while short-horizon commitment devices (such as the 60-day PMSS) and financial literacy are associated with improvements in microsavings among low-income daily earners, achieving benchmark-level saving might require longer-term and more adaptive mechanisms that address income volatility and mitigate other inherent risks. Full article

Centralized UAV logistics controllers can achieve strong navigation performance in controlled settings, but they do not capture key deployment factors in crowdsourcing-enabled emergency logistics, where heterogeneous UAV owners participate with unreliability and dropout, and incentive expenditure and fairness must be accounted for. This paper presents a decentralized crowdsourcing multi-UAV emergency logistics framework on an edge-orchestrated architecture that (i) performs urgency-aware dispatch under distance/energy/payload constraints, (ii) tracks reliability and participation dynamics under stress (unreliable agents and dropout), and (iii) quantifies incentive feasibility via total payment and payment inequality (Gini). We adopt a hybrid decision design in which PPO/DQN policies provide real-time navigation/control, while GA/ACO act as planning-level route refinement modules (not reinforcement learning) to improve global candidate quality under safety constraints. We evaluate the framework in a controlled grid-world simulator and explicitly report stress-matched re-evaluation results under matched stress settings, where applicable. In the nominal comparison, centralized DQN attains high navigation-centric success (e.g., 0.970 ± 0.095) with short reach steps, but it omits incentives by construction, whereas the proposed crowdsourcing method reports measurable payment and fairness outcomes (e.g., payment and Gini) and remains evaluable under unreliability and dropout sweeps. We further provide a utility decomposition that attributes negative-utility regimes primarily to collision-related costs and secondarily to incentive expenditure, clarifying the operational trade-off between mission value, safety risk, and incentive cost. Overall, the results indicate that navigation-only baselines can appear strong when participation economics are ignored, while a deployable crowdsourcing system must explicitly expose incentive/fairness and robustness characteristics under stress. Full article

Root-cause analysis (RCA) in large-scale microservice-based payment systems is challenging due to complex failure propagation along service dependencies, limited availability of labeled incident data, and heterogeneous service topologies across deployments. We propose ServiceGraph-FM, a pretrained graph-based model for RCA, where “foundation” denotes a self-supervised graph encoder pretrained on large-scale production cluster traces and then adapted to downstream diagnosis. ServiceGraph-FM introduces three components: (1) masked graph autoencoding pretraining to learn transferable service-dependency embeddings for cross-topology generalization; (2) a temporal relational diffusion module that models anomaly propagation as graph diffusion on dynamic service graphs (i.e., Laplacian-governed information flow with learnable edge propagation strengths); and (3) a causal attention mechanism that leverages multi-hop path signals to better separate likely causes from correlated downstream effects. Experiments on the Alibaba Cluster Trace and synthetic PayPal-style topologies show that ServiceGraph-FM outperforms state-of-the-art baselines, improving Top-1 accuracy by 23.7% and Top-3 accuracy by 18.4% on average, and reducing mean time to detection by 31.2%. In zero-shot deployment on unseen architectures, the pretrained model retains 78.3% of its fully fine-tuned performance, indicating strong transferability for practical incident management. Full article

This study aims to explain what drives consumers to adopt e-tipping in restaurants and determine whether interface-based manipulation reduces perceived autonomy, lowers satisfaction, and weakens brand favorability. Prior research indicates that when autonomy is undermined through manipulative design, satisfaction declines. This study integrates UTAUT2 and Self-Determination Theories to examine the determinants of consumers’ e-tipping intention, satisfaction, and brand favorability in Saudi restaurants. Four UTAUT2 motivators (performance expectancy, facilitating conditions, social influence, hedonic motivation) and service quality were modeled as antecedents, cultural attitude as mediator, and inferred manipulation as moderator. An online survey of restaurant consumers in Saudi Arabia who had previously engaged in e-tipping generated 607 valid responses, providing adequate sample power for PLS-SEM testing. Results show that performance expectancy, social influence, hedonic motivation, and service quality significantly predict intention; cultural attitude mediates several effects; and manipulation weakens the intention–satisfaction relationship, negatively impacting brand favorability. This research offers a theoretical contribution by extending UTAUT2 to the e-tipping context through integrating service quality as an antecedent and positioning satisfaction and brand favorability as core outcomes. It advances theory by demonstrating how technology-driven manipulation within payment interfaces influences cultural attitudes, behavioral intentions, and post-experience evaluations in a high-context, non-tipping society. Managerial and policy implications for responsible e-tipping designs are discussed. Full article

E-commerce retailers bear substantial additional costs arising from high product return rates due to lenient return policies and consumers’ impulsive purchasing. This study aims to accurately predict product return behavior before payment, supporting proactive return management and reducing potential losses. Based on the Graph Transformer, we proposed a novel return prediction model, Returnformer, which focuses on capturing user–product connections represented in topological structures of bipartite graphs. The Returnformer first integrates global topological embeddings into original node features to alleviate structural information loss caused by graph partitioning. It then employs a Graph Transformer to capture long-range user–item dependencies within local subgraphs. In addition, a graph-level attention mechanism is introduced to facilitate the propagation of global return patterns across different subgraphs. Experiments on a real-world e-commerce dataset show that the Returnformer outperforms four machine learning models in terms of prediction accuracy, demonstrating superior performance compared to the state-of-the-art models. The proposed model enables retailers to identify potential return risks prior to payment, thereby supporting timely and proactive preventive interventions. Full article

High-quality, interoperable biodiversity information is a prerequisite for effective conservation policy, compliance with European Union (EU) reporting obligations, and efficient environmental decision-making. Greece’s LIFE EL-BIOS (LIFE20 GIE/GR/001317) developed the first National Biodiversity Information System, aiming to aggregate, standardise, and disseminate spatial and non-spatial data for species, habitats, pressures, and trends. This paper provides an economic valuation of this information system as a public, non-market good. We designed a two-stage stated-preference study: (i) a short pre-survey to calibrate initial bids and (ii) the main survey employing double-bounded dichotomous choice (DBDC) contingent valuation with a spike-logit specification. The payment vehicle was a hypothetical monthly subscription in a post-LIFE scenario. The instrument measured time savings (hours), perceived reliability (Likert 1–5), and key demographics/roles. A total of 167 valid responses were collected in September 2025. Participants reported an average of 5.2 h saved per use (median 4; max 14). Among those expressing willingness to pay (WTP), 77% rated EL-BIOS reliability as “High/Very high”. Econometric results indicate time savings as the strongest positive determinant of WTP; perceived reliability is positive and marginally significant; years of experience are negatively associated with acceptance; and cost has a strong negative effect. Mean WTP is estimated at €6.7 per month (median €3.5). Notably, 64% of those unwilling to pay declared protest motives (data should remain public and free). Accordingly, non-payment is decomposed into true zero WTP versus protest-based refusal, i.e., refusal to pay despite acknowledging value. This high protest share reflects principled opposition to paying for public biodiversity data rather than low perceived value of the system. The EL-BIOS database generates measurable productivity gains and social value both through positive WTP and principled protest responses supporting open public data. These findings inform policy on sustainable financing, governance, and long-term operation of national biodiversity information systems. Full article