Search Results (272)

Background: Fintech companies have revolutionized the financial services industry in India in recent years. This is especially true for the growth of digital payment methods. India’s unbanked are being introduced to banking by fintech companies. Despite the country’s strong banking system, many residents find it difficult to get government financial services. This is particularly true for rural or low-income people. This vacuum has been addressed by fintech solutions including digital banking, micro-lending applications, mobile wallets, and UPI platforms. Objectives: to study the impact of financial technology businesses on increasing financial inclusion for India’s underbanked and unbanked population and Challenges encountered by financial technology enterprises in their endeavors to access unbanked populations, encompassing concerns of infrastructure with special reference to western Uttar Pradesh. Method: This mixed-methods study examines how FinTech is narrowing the financial gap for unbanked people using quantitative econometric analysis and qualitative case study assessments. Results: Digital financial innovation and regulatory support encourage inclusive growth in underdeveloped economies, whereas rich nations benefit from sophisticated banking institutions. This is indicated by the small influence of GDP per capita (β = 0.22–0.32, p < 0.05). Findings: The study found that inclusive finance is revolutionized when FinTech is used with the help of robust regulatory frameworks and digital infrastructure. Policymakers should prioritize cybersecurity, public-private partnerships to improve digital literacy, and rural connection if they want more people to take part in the digital financial ecosystem. Implications: FinTech can remove obstacles to accessing financing. The proper coordinated improvements in regulatory frameworks, digital infrastructure and financial literacy among the people are necessary to achieve full financial inclusion. Full article

This study explores the digital transformation and public value created through the target city’s smart city Mobile Payment APP and digital city token system within the context of sustainable governance in Taiwan. Adopting a convergent mixed-methods research design, this research integrates quantitative Importance–Performance Analysis (IPA) surveys of 632 users with qualitative in-depth semi-structured interviews involving eight key stakeholders (namely, government officials, system developers, affiliated merchants, and citizen representatives). This methodology assesses service quality, user satisfaction, and cross-sector collaboration effects. The findings reveal that the mobile payment platform significantly enhances digital service delivery; fosters user engagement; and supports sustainable urban development goals, particularly net-zero carbon emissions. However, the IPA results highlight critical service gaps in the “Priority Improvement Zone,” specifically regarding the insufficient number of affiliated merchants and inconvenient information search functions. Qualitative findings attribute these gaps to cross-departmental administrative barriers and security-focused design trade-offs. This study contributes empirical evidence on the integration of financial technology and public service innovation as a means to advance smart governance and sustainable urban ecosystems. The results provide actionable insights for policymakers, city planners, and service designers focused on promoting digital public services that facilitate economic vitality, environmental sustainability, and collaborative governance. Full article

The rapid expansion of digital payment channels has significantly widened the financial transaction attack surface, exposing ecosystems to sophisticated, polymorphic threat vectors. This study introduces an AI-powered cybersecurity mesh that unites Generative AI (GenAI), federated reinforcement learning, and zero-trust principles, with a forward-looking architecture designed for post-quantum readiness. The architecture ingests high-velocity telemetry, coordinates self-evolving agent collectives, and anchors model provenance in a permissioned blockchain to guarantee verifiability and non-repudiation. Empirical evaluations across two production-scale environments—a mobile wallet processing two million transactions per day and a high-throughput cross-border remittance rail—demonstrate a 95.1% threat-detection rate, a 62% reduction in false positives, and a 35.7% latency decrease compared to baseline systems. These results affirm the feasibility of a generative cybersecurity mesh as a scalable, future-proofed blueprint for next-generation payment security. Full article

As a financial center of Asia, Hong Kong has been the leading edge of fintech innovation, with the a leading ranking of the Global Innovation Index, which only ranked the fifth among all the payment methods in 2023 whereas mainland China achieved 90% acceptance in 2018. Since Hong Kong is part of China and shares similar origins and cultures, we found the need to study consumer behaviors in both of the two regions. We use comparison study methodology to find out the reasons of the difference in the usage. This research aims to investigate the factors influencing the acceptance of mobile payment services in Hong Kong and its difference in mainland China. In this research, we use the Partial Least Square Structural Equation Modeling methodology which discovers several significant factors influencing the actual use of mobile payment systems in Hong Kong and mainland China and tries to explain this. The findings will contribute to a better understanding of user behaviors and preferences, assisting stakeholders to address the challenges, develop effective strategies to increase the acceptance and use of mobile payment services, and promote payment convenience in Hong Kong. Full article

Due to the mobility of many pest species, effective integrated pest management (IPM) requires spatial coordination of management actions. This paper examines how the consideration of spatial dynamics, spatially coordinated collaboration, and supportive policy instruments improve pest management in agricultural landscapes. We consider empirical studies that explore the effects of spatial structure and processes on pest dynamics; conceptual frameworks that address larger spatial scales, such as Area-Wide Pest Management (AWPM); and policy instruments such as Payments for Ecosystem Services (PES) that have an impact on the land use in agricultural landscapes. The aim is to highlight how these three pillars of effective pest management are interrelated. Challenges and approaches for the establishment of spatial collaboration in agricultural pest management are identified and avenues for future research are presented. Full article

Although the use of mobile payments has become increasingly prevalent, understanding the factors that persuade users to continue to rely on the transaction method remains limited. This study applied the Uses and Gratifications Theory and a contingency perspective to examine the relationship between personalized artificial intelligence and users’ intention to continue using mobile payments. Drawing on the contingency perspective, we also assessed four moderating factors: age, educational level, social network, and technological diversity. Using survey data collected from 515 Chinese users and applying hierarchical regression analysis, our results reveal that personalized artificial intelligence significantly enhances users’ intention to continue using mobile payments. Educational level, social network, and technological diversity also have a positive influence but age has a deterring effect. Our empirical findings constitute an academic contribution to a deeper understanding of the dynamics that persuade mobile payment users not to change their routine. Full article

Customer satisfaction (CS) is a cornerstone of competitiveness in the hospitality sector, particularly in restaurants, where service interactions are highly sensory and time-sensitive. Traditional measurement instruments, such as SERVQUAL, SERVPERF, and the American Customer Satisfaction Index, provide valuable diagnostic insights but remain limited by recall bias, social desirability, and delayed feedback. Advances in deep learning now enable non-intrusive, real-time monitoring of customer experience. This study evaluates the feasibility of using a convolutional neural network (CNN) to automatically classify customer satisfaction based on facial expressions captured at the point of payment in a restaurant. From an initial dataset of over 5000 images, 2969 were validated and labeled through a binary self-report mechanism. The CNN, implemented with transfer learning (MobileNetV2), achieved robust performance, with 93.5% accuracy, 92.8% recall, 91.0% F1-score, and an area under the ROC curve of 0.93. Comparative benchmarks with Support Vector Machine and Random Forest classifiers confirmed the superiority of the CNN across all metrics. The findings highlight CNNs as reliable and scalable tools for continuous CS monitoring, complementing rather than replacing classical survey-based approaches. By integrating implicit, real-time signals with traditional instruments, restaurants can strengthen decision-making, enhance service quality, and co-create personalized experiences while addressing challenges of explainability, external validity, and data ethics. Full article

Privacy enhancement technologies are significant in the development of digital payment systems. At present, multiple innovative digital payment solutions have been introduced and may be implemented globally soon. As cyber threats continue to increase in complexity, security is a crucial factor to consider before adopting any technology. In addition to prioritizing security in the development of digital payment systems, it is essential to address user privacy concerns. Modern digital payment solutions offer numerous advantages over traditional systems; however, they also introduce new considerations that must be accounted for during implementation. These considerations go beyond legislative requirements and encompass new payment methods, including transactions made through mobile devices regardless of internet connectivity. A range of regulations and guidelines exist to ensure user privacy in financial transactions, with the General Data Protection Regulation (GDPR) being particularly notable, while technical reports have thoroughly examined the differences between various privacy-enhancing technologies. Additionally, it is important to note that all legal payment systems are required to maintain information for audit purposes. This paper introduces a comprehensive framework that integrates all critical considerations for selecting appropriate privacy enhancement technologies within digital payment systems, while it utilizes a detailed scoring system designed for convenience and adaptability, allowing it to be employed for purposes such as auditing. Thus, the proposed scoring framework integrates security, GDPR compliance, audit, privacy-preserving technical measures, and operational constraints to assess privacy technologies for digital payments. Full article

Mobile payments and e-commerce, along with credit cards, have become deeply embedded in people’s daily business and economic activities. However, the increase in transaction volume has also led to a rise in fraudulent activities. To address challenges such as extremely low fraud sample ratios, highly imbalanced data distributions, significant noise interference, and strong sequence dependencies, this paper proposes a multi-module collaborative framework for credit card fraud detection. This framework includes four core components: anomaly-aware cleaning, structure-preserving resampling, multi-indicator feature governance, and dual-channel modelling. A multi-attribute decision method based on TOPSIS is introduced for feature selection. Additionally, a dual-channel detection model is developed, comprising a static channel (random forest) and a dynamic channel (LSTM), to model non-sequential and sequential patterns, respectively. Compared with this state-of-the-art method, our results achieve 99.98% accuracy, 90.46% F1 score, and 96.39% AUC, improving both model accuracy and generalisation capabilities while maintaining structural integrity. Full article

This study is to explore information synthesis on research topics and emerging trends in privacy within the context of technology adoption. A search for the terms privacy and technology adoption in the Web of Science database yielded information on 2910 publications from 2005 to 2025. The analysis was conducted using CiteSpace, incorporating cluster analysis, timeline analysis, and burst detection to identify key patterns and developments. Fifteen sub-areas of privacy related to technology adoption were identified, including health information exchange, blockchain adoption, artificial intelligence, Internet banking, smart home devices, location-based services, mobile commerce, ubiquitous commerce adoption, tracing apps, metaverse adoption, and facial recognition payment. Timeline analysis provided insights into the growth or decline of these research clusters over time. Based on the findings, a framework was developed to illustrate key insights and their interconnections, offering guidance for future research. The study concludes by discussing its implications, limitations, and recommendations for further research. Full article

Background/Objectives: Unpaid medical expenses incurred by foreign nationals represent a growing concern for healthcare systems amid increasing international mobility. Japan, which lacks mandatory public insurance coverage for non-resident visitors, faces particular vulnerability in terms of uncompensated hospital care. This study aims to identify factors contributing to unpaid medical charges among uninsured, non-resident foreign patients hospitalized at a tertiary care facility in Tokyo. Methods: This retrospective observational analysis was conducted using medical and administrative data from patients admitted between January 2023 and February 2025. Patients who received elective medical tourism care were excluded. Data on demographics, length of hospital stay, care intensity, payment status, and third-party financial assistance were analyzed. Logistic regression models were applied to assess predictors of nonpayment. Results: Among 153 eligible cases, 9 patients (5.9%) had outstanding hospital bills upon discharge. Compared with those with completed payments, the unpaid group experienced longer admissions, more intensive care utilization, and higher total charges. Notably, the absence of third-party financial support (primarily travel insurance) was significantly associated with unpaid charges. Multivariate analysis identified this factor as the main independent predictor (adjusted odds ratio [OR]: 0.12; 95% confidence interval [CI]: 0.02–0.915; p = 0.040). Total amount of billing was also statistically significant (adjusted odds ratio [OR]: 1.01; 95% confidence interval [CI]: 1.00–1.01; p = 0.039). Conclusions: These findings highlight the importance of private insurance in mitigating financial risk in hospitals. Implementing policy measures to promote or require insurance enrollment, along with streamlined reimbursement systems, may contribute to sustainable care delivery for international patients. Full article

In this study, we review recent research on how digital payment technologies (DPTs) promote financial inclusion (FI) across the world. Drawing on empirical studies from the past decade, we show that digital payment systems have helped reduce financial exclusion—particularly in developing economies—by expanding access to essential financial services for underserved groups. The paper also highlights the role of demographic factors such as age and gender, with evidence of higher adoption among youth and women. We identify the main indicators used to measure digital payment adoption and FI, providing a foundation for future empirical analysis. To deepen understanding, we call for combining macroeconomic data with rigorous econometric approaches to better capture how DPTs contribute to inclusive financial systems. The paper further discusses how emerging innovations—including blockchain, artificial intelligence, cloud computing, and biometric authentication—are improving the efficiency, security, and accessibility of digital payments. Together, these technologies are likely to accelerate the transition toward fully digital financial ecosystems and expand the potential for inclusive and sustainable growth. Full article

This paper proposes a coalition-based framework for the coordinated operation of multi-regional power systems subject to extreme uncertainty in demand surges, renewable variability, and resource mobilization delays. Methodologically, we integrate Bayesian learning with distributionally robust optimization (DRO), embedding dynamically updated scenario posteriors into a Wasserstein ambiguity set. This construction captures both stochastic variability from renewable and load realizations and epistemic uncertainty from incomplete knowledge of probability distributions. To align individual incentives with system-level efficiency, we design a risk-adjusted utility mechanism that combines VCG transfers, Shapley allocations, and nucleolus refinements. These mechanisms explicitly consider agent heterogeneity, risk aversion, and coalition stability, ensuring that cooperation remains both efficient and sustainable. The optimization model maximizes expected social welfare while incorporating constraints on transmission corridor capacities, mobilization logistics, demand–response rebound effects, and mobile energy storage operations. A hierarchical decomposition algorithm integrates the Bayesian-DRO dispatch layer with cooperative game-theoretic allocations to maintain tractability and robustness at large scale. A case study on a six-province interconnected system with 14–26 GW peak demand, 10.2 GW solar, 8.6 GW wind, 14 GW peaking units, and 6.8 GW mobile storage demonstrates the effectiveness of the approach. Results indicate that the proposed framework raises expected welfare by nearly 10% relative to a non-cooperative baseline, reduces the probability of unserved energy exceeding 1.5% from almost 2% to negligible levels, and narrows payment disparities across provinces to strengthen coalition stability. Demand response peaks at 250–300 MW with rebound averaging 25%, while mobile BESS units cycle frequently to enhance local reliability. Overall, the findings highlight a robust and incentive-compatible pathway for resilient inter-provincial operation, providing both methodological advances and policy-relevant insights for multi-regional energy governance. Full article

This paper presents preliminary findings on the effectiveness of a citizen science initiative that engages local communities in rural Kalimantan in collecting wildlife observations within their village forests. By leveraging the power of community participation, the initiative aims to build on local knowledge, promote sustainable management practices, and collect valuable data on species distribution. Through a combination of focus group discussions, training workshops, field surveys, and mobile app-based data collection from 2023 to 2025, the initiative successfully mobilized community members, particularly those with limited technological experience, to actively participate in biodiversity monitoring. We recently introduced a small ‘payment for wildlife observations’ system that significantly boosted observations. The initial results highlight the potential for citizen science to generate valuable species trend data and foster a sense of pride, ownership, and stewardship among community members. While the current manuscript does not provide statistical analyses of the wildlife data, we describe how we plan to overcome data biases that are inherent to opportunistic, unstructured survey efforts. The project continues, but the lessons learned thus far can inform future citizen science initiatives and contribute to the development of sustainable, long-term, low-cost and effective community-based conservation strategies in the region. Full article