This paper investigates the impact of digital financial literacy on the use of financial technology (Fintech) among people living in rural areas of Vietnam. The study employs various theoretical frameworks, including the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM), to clarify factors influencing the intention and behavior of Fintech adoption. These factors include performance expectancy, perceived risk, subjective norms, behavioral control, convenience, security, personal motivation, financial attitude, and financial behavior. Based on the research findings, the authors propose several recommendations to improve digital financial literacy among rural populations in Vietnam, recognizing it as a key factor in expanding access to and usage of modern financial services in these areas.

In recent years, fintech has received much attention due to the introduction of new technologies in banking and electronic payment. For financial service providers to compete in the industries, they should apply the business model as a conceptual framework to improve performance. The current research is exploratory and tries to identify the factors influencing fintech design in electronic payment using the Osterwalder business model. This study aims to integrate three methods named DEMATEL, ISM, and ANP from MCDM techniques. To analyze the identified factors affecting the design of fintech in electronic payment, the indicators were examined in terms of influence and effectiveness by the DEMATEL method, then the levels of influence and effectiveness of the factors were investigated using the interpretive structural modeling method. Finally, the network analysis method was used to prioritize the factors. The findings showed that recognizing and identifying electronic payment customers is the most effective among the factors, and determining the type of relationship with customers is the most impressionable factor. In addition, after ranking the factors, the type of relationship with customers was the first rank, and the criteria of the company's cost structure and revenue streams were determined as the second and third, respectively.

Measuring the performance of Fintech services on mobile apps (FSMA) is considered a major key to sustain, develop, and improve financial services and their processes, depending on users’ standpoints on digital platforms. Public value aims at enhancing the performance of government institutions services. Throughout the current research, authors have suggested a novel way to evaluate the performance and management of FSMA by theorizing a new conceptual framework entitled Public Value of Fintech Services’ Mobile Apps (PV-FSMA). A quantitative approach was chosen to measure several factors influencing the use of FSMA and evaluate the degree of public value of FSMA among Jordanians. The structural equation model was conducted based on the results of the PV-FSMA model hypotheses. The results confirmed that FSMA-intention to use (FSMA-ITU) and its predictors: FSMA-usefulness (FSMA-US), FSMA-awareness (FSMA-AR), FSMA-security (FSMA-SE), FSMA-social influence (FSMA-IS), and FSMA-system quality (FSMA-SQ) except FSMA-ease of use (FSMA-ES) are valuable determinants of PV-FSMA. The article presents theoretical implications regarding financial services and public value theories and practical implications regarding public institution leaders, managers, and information technology specialists in the Fintech domain to improve the quality and performance of FSMA in Jordan.

The market share of peer-to-peer (P2P) has shifted from dominating the P2P lending for Micro, Small, and Medium Enterprises (MSME) to non-MSME. Meanwhile, non-MSME credit is an incumbent main market share banking which possibly makes it a complementary or substitution in P2P lending in non-MSME bank credit. Furthermore, optimizing and maintaining liquidity is important due to banks utilizing intermediation functions. The strictness of bank liquidity could determine the management’s response and policy in determining the best timing to utilize either the FinTech from the P2P platform or the customer’s existing funds first. This study aims to assess the empirical findings of the effect of P2P lending on banking credit that is divided between provinces with strict, normal, and lax liquidity. This study uses data from 33 provinces in Indonesia between January 2022 to December 2022. The study approach uses a regression data panel for the data analysis. The results of this study show that P2P lending positively and significantly impacts bank credits of non-MSMEs in provinces with lax bank liquidity. The stricter the banking the lower the compliments of P2P loans against the bank credits of non-MSME. To the author’s knowledge, no existing studies investigate the P2P lending of non-MSME banking credit that also consider the level of strictness of banking liquidity.

Despite the numerous advantages that different mobile payments can provide, their acceptance, and adoption rates are still relatively low. This study aims at investigating mobile payments and demonstrates how drivers and barriers that influence behavioral intentions to use mobile payments interact and support one another by combining the theory of planned behavior (TPB) and the innovation resistance theory (IRT). A self-administered online survey was employed to gather data from 341 users of mobile payments in the State of Kuwait. To test the proposed model and its hypotheses, responses were analyzed using a partial least square structural equation modeling approach (PLS-SEM). The results show that usage, value, risk, and tradition resistance-related factors are significant barriers towards behavioral intentions to use mobile payments, while the image barrier is insignificant. The findings also affirmed that perceived behavioral control and attitudes motivate and influence consumers’ behavioral intentions; however, the subjective norm was non-significant. The study’s findings have significant implications for scholars, mobile payments’ service providers, marketers, policymakers, and banks.

Although the critical success factors might be different between the pre and post-adoption stages of mobile wallets, there have been few studies conducted to examine those factors for the post-adoption stage when compared to the number of studies conducted to examine those factors for the pre-adoption stage. Yet, the post-adoption stage of mobile wallets is crucial to the success and sustainability of the mobile wallets’ ecosystem. Thus, this study developed and examined a model by integrating relevant factors into the Technology Acceptance Model 2 (TAM2). Data were collected from 578 mobile wallet users in Jordan using an electronic questionnaire. A structural equation modelling approach was utilized to analyze the data. The results revealed that perceived usefulness and perceived ease of use have statistically significant positive direct effects on the intention to continuous use of mobile wallets, while subjective norm does not. In addition to that, results indicated that trust, security, and ubiquity have statistically significant positive direct effects on perceived usefulness and perceived ease of use, and, in turn, on the intention to continuous use of mobile wallets. Moreover, this study found that perceived ease of use and subjective norms have statistically significant positive direct effects on perceived usefulness, and, in turn, on the intention of continuous use of mobile wallets. While risk does not have a significant effect on perceived usefulness, it has been found to have a statistically significant negative direct effect on perceived ease of use, and, in turn, on the intention to continuous use of mobile wallets. The findings of this study should help stakeholders to develop more effective consumer retention tactics and formulate appropriate marketing decisions.

The research paper at hand is devoted to the role of fintech practices in the municipal government institutions performance i.e. the role of organizational readiness on this performance, as seen by the municipal employees. The article quantifies the contribution of the digital innovations like automated payment systems on the efficiency and quality of administrative and services in a quantitative analytical scheme. The results show that fintech and positive institutional performance outcomes, such as lower operating costs, higher revenue collection, and higher levels of citizen satisfaction, have a strong positive association. Interestingly, the empirical findings indicate that preparedness in organizations consisting of technological infrastructure, workforce efficacy, and management support are some of the fundamental aspects in enhancing the association amid fintech and performance. Digital transformation will have a greater benefit on the more prepared departments, structure-wise and human resource-wise. On the same, but a different note, the inquiry warns against the necessity to create a compromise between innovation and high security measures to reduce the threat of fraud and data leaks. The government organizations should first coordinate their electronic infrastructure, use effective models, must focus on lifelong training of staff, not just buy software, and must also spend a specific budget on cybersecurity and fintech infrastructure to get such returns. This study offers a strategic road map through which the public institutions in the MENA region can use technology as a driving force in institutional excellence, and at the same time, remain financially stable on the national level.

This study aimed to analyse key managerial factors, including environmental, technological, and organisational aspects, which influence decision-makers' intentions in FinTech organisations to implement hybrid project management (HPM) methodologies. The study scope focused on online banking systems, financial payment system solutions, and system modernisation projects in the Malaysian FinTech context. The study applied a theoretical approach that integrated Technology-Organisation-Environment (TOE) to investigate the extent to which variation in one variable is associated with variation in another. Furthermore, the Theory of Planned Behaviour (TPB) was also applied in this study to examine the relationship between FinTech decision-makers' intentions to adopt HPM and the factors influencing their decisions, without imposing controls on the dependent variables. The findings revealed that the effect of business partner quality has a positive influence on an individual's attitude towards HPM adoption in FinTech Malaysia when the independent, dependent, and moderating variables are combined. Nevertheless, the findings revealed that, as hypothesised in the direct effect model, observability and organisation readiness have a negative influence on an individual's attitude towards HPM adoption. The authors also integrated attitudes as a mediator variable and perceived behavioural control as a moderator variable into the research framework.

FinTech has become a popular term which describes novel technologies adopted by the financial service institutions. This term covers a large scope of techniques, from data security to financial service deliveries. An accurate and up-to-date awareness of FinTech has an urgent demand for both academics and professionals. The goal of the study is to assess the impact of dynamic employee capabilities on fintech applications, employees’ innovation work behavior, thereby creating employee performance and supply chain finance performance for financial institutions in Vietnam. The data was collected through 189 mid-level managers of 189 financial institutions in Vietnam. The results of analysis using SPSS and Smart PLS software show that dynamic employee capabilities had a positive impact on fintech application, employees’ innovative work behavior and improve employee performance while improving supply chain finance performance of financial institutions in Vietnam.

This study develops an explainable ensemble machine learning framework for sustainable credit risk assessment in peer-to-business (P2B) lending, a rapidly expanding FinTech model that enhances access to financing for small and medium-sized enterprises (SMEs). The increasing reliance on algorithmic decision-making underscores the need for transparent and interpretable credit evaluation, particularly in environments characterized by information asymmetry and reliance on borrower-provided disclosures. To address these challenges, a heterogeneous ensemble model is proposed, integrating Random Forest (RF), Light Gradient Boosting Machine (LGBM), and deep learning classifiers within a soft-voting architecture. Feature selection and class balancing are guided by RF importance scores and resampling techniques, resulting in a compact and interpretable 12-feature set comprising pricing, contractual, and transaction-level variables derived from borrower disclosures. Using real-world transaction-level data from a UK platform, the proposed model achieves improved predictive performance (ROC-AUC = 0.767) compared to a neural network baseline (ROC-AUC = 0.717) under severe class imbalance. SHAP-based explainability analysis identifies Maturity Days, Annualised Gross Yield, Advance Rate, and Discount Rate as the most influential predictors, highlighting how disclosed information is translated into pricing and contractual terms in digital lending markets. The findings demonstrate that disclosure-informed features can enhance both predictive accuracy and interpretability, supporting more transparent, robust, and accountable credit risk assessment in FinTech lending environments.