Search Results (168)

Digital financial inclusion (DFI) has become a central topic in financial inclusion research because digital payments, mobile money, internet banking, and platform-based finance can reduce access barriers and expand formal financial participation. Prior studies have documented the development relevance of financial inclusion and have constructed multidimensional financial inclusion and DFI indices, often using PCA and related composite-indicator methods. A remaining measurement gap concerns the equal observability of different digital-finance architectures within a common cross-country indicator set. This study addresses that gap by analyzing an existing PCA-based DFI score for 40 Organisation of Islamic Cooperation (OIC) countries over 2015–2024 through a channel-observability framework. The objective is to examine whether the observed DFI ranking is captured more directly through mobile-money indicators than through the available infrastructure-based representation of bank-led digital finance. The analysis decomposes the six available indicators into a bank-led visibility proxy, based on internet penetration and ATM density, and a mobile-money visibility proxy, based on mobile agents, mobile accounts, mobile transaction volume, and transaction value relative to GDP. The OIC-wide mean DFI score increased from 11.31 in 2015 to 31.24 in 2024, while dispersion widened and the 2015 and 2024 top-ten country groups had zero overlap. The channel diagnostics show that the highest observed DFI scores are concentrated among countries whose digital-finance activity is directly recorded through mobile-money indicators, whereas several financially advanced economies are visible mainly through the bank-led infrastructure proxy. Zero-coded mobile-money observations are interpreted as indicator-visibility signals for the standalone mobile-money channel and considered separately from broader digital-finance activity. The Random Forest analysis functions as a bounded internal sensitivity audit of the existing six-indicator score and shows that mobile-money transaction variables carry the largest within-score explanatory weight. The theoretical contribution is to frame DFI measurement as an architecture-dependent observability problem rather than only as a weighting problem. The practical implication is that cross-country DFI rankings should be interpreted together with channel diagnostics, especially when bank-led digital services such as mobile banking, card payments, POS transactions, QR payments, and instant-payment systems are outside the balanced indicator set. Full article

This study examines whether recognized intangible assets carry information about bank performance in an emerging market, and whether their information value is conditioned by the maturity of macro digital infrastructure. Using a balanced panel of 28 Indonesian commercial banks over 2015–2024 (280 firm-year observations), we estimate two-way fixed-effects models with macro digital infrastructure, an economy-wide principal component index of internet penetration, mobile and broadband subscriptions, and electronic payment volume as a cross-layer moderator. Intangible investment intensity, proxied by the ratio of reported intangible assets to total assets, shows weak direct associations with performance; only the operating efficiency ratio displays a marginally significant short-run cost, consistent with transition-cost dynamics. The central result is conditional: the interaction between intangible intensity and macro digital maturity is strongly significant for operating efficiency (β = −2.587, p = 0.005), with the implied efficiency cost contracting by a model-implied 88 percent across the observed range of digital maturity (an estimate computed from the estimated coefficients over the observed sample variation, not a structural causal magnitude). Heterogeneity is pronounced across regulator-defined bank tiers (KBMI): the four largest banks realize positive profitability effects, whereas mid-tier banks bear transition costs. Results are robust to Driscoll–Kraay standard errors, system GMM, sub-sample splits, and outlier exclusion. The findings show that the information value of recognized intangibles in banking is state-contingent, extending the intangible-asset and digitalization literature to emerging-market banking. Full article

Background: Generative artificial intelligence (GenAI) is diffusing among consumers at exceptional speed, yet little is known about how its adoption relates to households’ prior engagement with digital financial services, or about the barriers associated with non-adoption. Methods: Using individual microdata from the 2025 Spanish Survey on ICT Equipment and Use in Households (INE; 14,642 internet users aged 16 and older), we estimate survey-weighted logistic regressions of GenAI adoption on financial digital engagement, digital skills and sociodemographics, with autonomous community fixed effects and cluster-robust standard errors, complemented by average marginal effects, alternative variance estimators, and an analysis of all stated reasons for non-use. Results: GenAI adoption is 37.3% among internet users. Online banking users have 73% higher adjusted odds of adopting GenAI (OR = 1.73; 95% CI 1.53–1.97), and adoption rises monotonically from 18% to 79% across a 0–4 financial digital engagement index, although this gradient is driven mainly by the online banking (extensive) margin. A steep age gradient is present, but the financial digital advantage does not significantly widen with age. Among non-adopters, the most frequently stated reason for non-use is a lack of perceived need (67%); privacy or security concerns are also prominent (43%) and are cited disproportionately by online banking users, women, and older individuals. Conclusions: Prior financial digital engagement is a strong correlate, rather than a demonstrated cause, of consumer GenAI adoption, consistent with experience and facilitating condition constructs in UTAUT2. Among capable non-adopters, for whom access and skills are not the obstacle, privacy- and security-related concerns, rather than a broader deficit of trust in AI, emerge as the most salient barriers to adoption, underscoring these concerns as priorities for consumer-facing AI in financial services. Full article

Bluetooth Low Energy (BLE) is widely used in Internet of Things (IoT) devices due to its low power consumption and efficient wireless communication. However, BLE-based systems remain vulnerable to signal-level attacks, such as spoofing and signal forgery, which allow adversaries to impersonate legitimate devices and compromise system security. Existing security approaches mainly rely on cryptographic mechanisms or protocol-level features, while conventional signal fingerprinting methods often fail to capture subtle device-specific variations across the frequency spectrum. We propose a deep-learning-based BLE signal fingerprinting framework that uses emphasized spectral data to enhance device authentication. The proposed framework selectively highlights frequency regions exhibiting pronounced hardware-dependent variations using a hybrid filter bank design and extracts spectral features for anomaly-based device identification. Experimental evaluations conducted on BLE signals collected from multiple devices demonstrate that the proposed approach outperforms conventional methods, achieving superior authentication performance. By leveraging emphasized frequency-domain characteristics, we provide an effective authentication method for BLE-based IoT environments. Full article

Human development is increasingly expected to reflect progress in health, education, living conditions, and sustainability. Yet evidence on how specific Sustainable Development Indicators (SDIs) relate to such progress remains limited, especially in studies that jointly consider cross-income heterogeneity, high-dimensional indicators, and nonlinear relationships. This study examines the SDI–HDI relationship across low-, lower-middle-, upper-middle-, and high-income countries using 408 World Bank SDG indicators and UNDP HDI series for 1990–2020. An interpretable Random Forest framework, combined with SHAP rankings and Partial Dependence Plots, identifies the most influential predictors and marginal associations with HDI. The model shows strong predictive performance across income groups and marked heterogeneity in the predictors associated with HDI. In low-income countries, HDI is mainly associated with early-life health conditions and human capital; in lower-middle-income countries, electrification and service access become more prominent; and in upper-middle- and high-income groups, digital connectivity, higher education, and institutional factors gain importance. Mortality-related indicators are consistently associated with lower predicted HDI, whereas literacy, electricity access, and internet use are associated with higher HDI. These results highlight how AI-based analytical tools can support sustainable economic development by identifying income-specific development priorities and structural constraints. They also suggest that disparities in health, education, infrastructure, and digital connectivity may influence the conditions under which entrepreneurial opportunities emerge or remain constrained across development stages. Overall, the SDI–HDI relationship is nonlinear and income-specific, supporting more differentiated, data-driven development strategies. Full article

As mobility and transport activities declined during the COVID-19 lockdowns, transactions and operations became increasingly dependent on digitalisation. This shift reduced the need for carbon-emissions-intensive fossil-fuel-based transportation. Using a panel of thirteen (13) Southern African Development Community (SADC) countries over the period 2002–2021, the analysis captures financial inclusion through indicators of ATM density and commercial bank accessibility, while digital inclusion is measured using mobile phone subscriptions and internet penetration. On this basis, it investigates the effects of (a) financial and (b) digital inclusion, and (c) the moderation of financial and digital inclusion on transport-related carbon emissions. Employing the Panel Two-Stage Estimated Generalised Least Square (EGLS) analysis on data obtained from the World Bank database and Our World in Data, the findings reveal statistically significant outcomes. Increasing ATM accessibility, commercial bank branch accessibility and mobile phone subscription rates are associated with reduced transport-related emissions. In contrast, enhanced internet access does not contribute to transport-related carbon emissions. Moderation analyses further indicate that the interaction of the accessibility of ATMs or commercial bank branches with internet access do not lead to a further reduction in carbon emissions than the individual ones but might have a slightly opposing direction (that still do not annihilate the individual effects). Findings show that only the moderation of ATM accessibility and mobile subscriptions reduce transport-related carbon emissions further than the individual effects. Taking the economic development of most SADC countries in the last 20 years into account, the study recommends strategic investment in advanced digital innovations, particularly linked with mobile devices, to strengthen digital banking efficiency and improve customer service while supporting emission-reducing pathways. Full article

This study investigates the predictive contribution of digital infrastructure to GDP per capita growth across 27 European Union Member States over the period 1995–2024, using a balanced panel of 810 country–year observations and an explainable machine learning framework. An XGBoost model trained on six World Bank indicators—fixed broadband subscriptions, internet users, mobile subscriptions, patent applications, R&D expenditure, and secure internet servers—achieves a training R² of 0.804 and a test R² of 0.430 under temporal out-of-sample validation spanning the COVID-19 structural break. TreeSHAP decomposition identifies fixed broadband as the strongest predictor of model-estimated GDP per capita growth (mean |SHAP| = 0.948; bootstrap rank 1 in 78% of 50 resamples; Friedman Chi-square (5) = 168.16, p < 0.001), providing predictive support for Hypothesis H1. Innovation indicators, represented by patent applications and R&D expenditure, exceed the pre-specified materiality threshold, providing predictive support for H2, while SHAP dependence plots reveal pronounced non-linear threshold patterns consistent with S-curve diffusion theory, supporting H3. Temporal SHAP decomposition identifies three structural phases: broadband dominance (1995–2007), crisis-induced reconfiguration (2008–2013), and quality convergence (2014–2024). The framework reconciles contradictory findings from prior literature by visualizing the complete functional form of the broadband–growth relationship without imposing a parametric specification. Full article

The transition from cash to digital payment instruments is reshaping retail commerce across Europe unevenly, with Central and Eastern European (CEE) countries exhibiting both some of the fastest growth and some of the lowest baseline levels in online shopping participation. This study examines whether the development of digital payment infrastructure proxied by the share of individuals using internet banking (NetBank) is associated with e-commerce adoption across eleven CEE EU member states over the period 2014–2023, yielding a balanced panel of 110 country-year observations. Drawing on harmonised data from Eurostat, the World Bank, and the ITU, we estimate a two-way fixed-effects model with kernel-robust standard errors and a dynamic specification with a lagged dependent variable. The results indicate that a one-standard-deviation improvement in internet banking penetration is associated with a 6.2 percentage point increase in the share of online shoppers once country and year fixed effects are controlled for, a finding that is precisely estimated under kernel standard errors (p < 0.001). Income-group heterogeneity analysis suggests that this association may be substantially larger in lower-income CEE countries (β = 6.9, p = 0.006) compared to higher-income ones (β = 2.3, p = 0.554), consistent with the hypothesis that payment infrastructure improvements generate the highest marginal returns where baseline access is lowest. Romania, despite recording the steepest absolute growth in online shopping in the EU over the sample period (+33 percentage points), remains persistently below the CEE median, illustrating how payment infrastructure constraints can slow convergence even during periods of rapid digitisation. The findings should be interpreted as robust conditional associations rather than causal effects, given the limitations of macro-panel identification. Full article

Background: Utilizing internet-connected assistive devices is essential for completing instrumental activities of daily living (IADL) for people with disabilities. Globally, the COVID-19 lockdown restrictions resulted in drastic lifestyle changes. Methods: A global online survey was conducted to determine whether self-reported satisfaction with completing IADL using internet-connected assistive devices changed from pre-to-during the COVID-19 pandemic. Results: A cross-sectional analysis of the electronic instrumental activities of daily living satisfaction assessment survey of 700 participants from 32 countries revealed that during lockdown, people with disabilities had lower satisfaction for IADL domains of transportation, banking, shopping, health, nutrition, and leisure. Satisfaction with IADL domains, transportation, banking, and household and security needs was lower for people with disabilities compared to people without disabilities, both pre- and during lockdown. Additionally, for both people with and without disabilities, satisfaction with all IADL domains decreased during lockdown, except for the domains of household and security needs and memory needs. Pre-COVID-19, the employed individuals with disabilities were more satisfied with their performance of IADLs than those not employed, and no significant differences were found in the satisfaction levels during COVID-19. Conclusions: The pandemic had a measurable impact on IADL satisfaction, especially in people with disabilities. Full article

The study investigates the dual transitions of digitalization and renewable energy in Thailand to see if digital expansion facilitates the transition to renewable energy sources and greenhouse gas (GHG) mitigation. The study utilized data from the World Bank between 2000 and 2023 to reconstruct models for autoregressive distributed lag (ARDL) analysis for short-run and long-run dynamics under ecological modernization and technology diffusion theories. Contrary to expected synergies, empirical results revealed that a developing economy would find an ‘investment trade-off’ instead. Digitalization showed no significant immediate impact on renewable energy production; however, it exerted a significant negative lagged effect (coefficient = −0.593), suggesting that digital and energy infrastructures compete for limited financial resources. It was found that there is a 6.3% increase in greenhouse gas emissions for every 1% increase in internet usage. Thus, these results challenge the belief that increased internet usage will help improve the environment. Absent proper supportive policies about both digitalization and green transitions, such as investing in plants and machinery towards digitalization rather than green technology, the pacing effects of digitalization will affect the goals of converting to clean energy. This requires a policy coordination approach to ensure that funds earmarked for green infrastructure are safeguarded. Full article

Mental health disorders affect nearly one billion people worldwide, yet treatment gaps exceed 75% in low- and middle-income countries. Teletherapy has emerged as a scalable solution, but its adoption differs sharply by economic context. This comparative ecological policy analysis used secondary aggregate data from WHO, World Bank, ITU, and national reports to examine teletherapy adoption in low-income (Nigeria, Kenya), middle-income (South Africa, India), and high-income countries (Norway, Canada). Descriptive statistics and simple linear regression were applied, with findings interpreted through the Consolidated Framework for Implementation Research (CFIR), Technology Acceptance Model (TAM), and Diffusion of Innovations theory. High-income countries achieved widespread adoption (>70%), enabled by universal broadband, comprehensive regulation, and strong reimbursement. Middle-income countries showed moderate uptake (15–30%), constrained by rural–urban digital divides and inconsistent policies. Low-income countries reported minimal integration (<5%), limited by unreliable internet, severe workforce shortages, high data costs, and sociocultural barriers. Digital infrastructure, regulatory maturity, and mental health workforce density explained 78% of the cross-country variance in adoption rates (R² = 0.78). Equitable scale-up of teletherapy directly supports SDGs 3, 9, 10, and 17. Targeted investment and cross-income collaboration are essential to prevent digital mental health solutions from exacerbating existing inequities. 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

Interest in financial inclusion among academics has grown significantly over the past decade. The Sustainable Development Goals (SDGs), which aim to create enabling policies to mobilize financial resources, highlight key factors in poverty reduction and inclusive economic growth, particularly financial inclusion. This study focuses on 15 selected Asian economies. This research examines the role of fintech in promoting financial inclusion in Asia, employing a mixed-methods research design. The literature review part employs critical analysis based on the SciVal bibliometric tool. Quantitatively, it applies the Moments Quantile Regression (MMQR) technique to country-level panel data for 2011, 2014, 2017, and 2021. This study also uses a comparative analysis of digitalization indices provided by the World Bank (WB), specifically the Global Findex Database. The findings reveal that digital payments have the most substantial effect at higher quantiles (τ = 0.5 and 0.75), reflecting their role in deepening financial engagement. Mobile money exhibits significant influence at the lower quantile (τ = 0.25), indicating its role in facilitating initial access for underserved populations. Internet usage contributes positively, albeit moderately, while GDP per capita shows no strong direct effect. Qualitative insights highlight challenges such as regulatory gaps, cybersecurity risks, and digital inequality. Full article

Over the last decade, there has been a significant increase in banks’ investment in technology, alongside a substantial rise in CEO compensation. Research on executive compensation has primarily focused on traditional performance metrics, such as return on assets and return on equity, as well as governance factors. Investigating the nexus between fintech adoption and CEO compensation introduces a new perspective on the determinants of CEO pay and how technological transformation influences executive remuneration structures. This study investigated the relationship between Chief Executive remuneration and fintech adoption among banks listed on the Johannesburg Stock Exchange. There is a lack of literature on the impact of technology adoption on CEO compensation in developing and emerging economies. The quantitative longitudinal study, conducted over 15 years from 2010 to 2024, collected secondary data from the annual reports of six banks and the IRESS database. A panel data fixed effects regression analysis was employed to analyze the data. CEO compensation included both salary and total compensation. Fintech variables used for the study included automated teller machines, mobile banking, and internet banking. The findings revealed a positive relationship between CEO salary and the rollout of ATMs and mobile banking, while an inverse relationship was noted between salary and internet banking. Similarly, total compensation showed an inverse relationship with the adoption of ATMs and internet banking, whereas mobile banking had a positive effect on total compensation. Understanding how technology impacts CEO compensation can help remuneration committees ensure that CEO pay is linked to the value that infrastructure investments bring to an organization, rather than simply the number of innovations introduced. This understanding will also help solve the principal-agent problem, as it will ensure technology innovations that enhance firm performance are rewarded. In the context of emerging markets, the study’s findings suggest that organizations should recognize and formalize pay linked to digital transformation, rather than focusing solely on short-term financial metrics. This also suggests the need to develop guidelines for executive remuneration disclosure related to the technology sector. The close connection between fintech adoption and technological and regulatory risks highlights the need to balance incentive structures that reward innovation with risk-adjusted performance measures. Full article

Location-based services (LBSs) and positioning systems have spread worldwide due to the emergence of Internet of Things (IoT) and other application domains that require real-time estimation of the position of a person, tag, or asset in general in order to provide users with services and apps with added value. Whereas Global Navigation Satellite Systems (GNSSs) are well-established solutions outdoors, positioning is still an open challenge indoors, where different sensory technologies may be considered for that purpose, such as radio frequency, infrared, or ultrasounds, among others. With regard to ultrasonic systems, previous works have already developed indoor positioning systems capable of achieving accuracies in the range of centimeters but limited to a few square meters of coverage and severely affected by the Doppler effect coming from moving targets, which significantly degrades the overall positioning performance. Furthermore, the actual bandwidth available in commercial transducers often constrains the ultrasonic transmission, thus reducing the position accuracy as well. In this context, this work proposes a novel excitation and processing method for an ultrasonic positioning system, which significantly improves the transmission capabilities between an emitter and a receiver. The proposal employs a superheterodyne approach, enabling simultaneous transmission and reception of signals across multiple channels. It also adapts the bandwidths and central frequencies of the transmitted signals to the specific bandwidth characteristics of available transducers, thus optimizing the system performance. Binary spread spectrum sequences are utilized within a multicarrier modulation framework to ensure robust signal transmission. The ultrasonic signals received are then processed using filter banks and matched filtering techniques to determine the Time Differences of Arrival (TDoA) for every transmission, which are subsequently used to estimate the target position. The proposal has been modeled and successfully validated using a digital twin. Furthermore, experimental tests on the prototype have also been conducted to evaluate the system’s performance in real scenarios, comparing it against classical approaches in terms of ranging distance, signal-to-noise ratio (SNR), or multipath effects. Experimental validation demonstrates that the proposed narrowband scheme reliably operates at distances up to 40 m, compared to the 34 m limit of conventional wideband approaches. Ranging errors remain below 3 cm at 40 m, whereas the wideband scheme exhibits errors exceeding 8 cm. Furthermore, simulation results show that the narrowband scheme maintains stable operation at SNR as low as $-32$ dB, whereas the wideband one only achieves up to $-17$ dB, highlighting the significant performance advantages of the proposed approach in both experimental and simulated scenarios. Full article