Mobile banking use: A comparative study with Brazilian and U.S. participants

Evaluating Drivers of Fintech Adoption in the Netherlands

The development of smartphones and mobile internet technologies has promoted the development of mobile payments worldwide. The core purpose of this study is to ascertain what the main factors are which affect Dutch customers’ adoption and experience of mobile payments. This study first addresses the concepts of mobile payments and customer experience and then explores the current Dutch financial and banking systems, before attempting to understand the recent researches worldwide on mobile payments. Based on quantitative research methods, the study examines the factors that influence the adoption and experience of mobile payments and the impacts of the COVID-19 outbreak on payment methods due to social distancing rules in the Netherlands. It finds that perceived ease of use, perceived usefulness, safety and trust are the main factors that affect the adoption of mobile payments, and mobile-payment providers need to improve technical protection and offer some benefits to boost the mobile-payment business. The COVID-19 outbreak has caused the decline of cash payments and the increase of contactless payments in the Netherlands; mobile payments ensure people’s health and help slow down the spread of the virus.

Artificial intelligence tools utilized in nursing education: Incidence and associated factors

BACKGROUND

Artificial intelligence technology is among the most significant advancements that provide students with effective learning opportunities in this digital era. Therefore, the National League for Nursing states that it is necessary to reframe the nursing education process.

OBJECTIVE

This study aimed to determine the factors that affect the usefulness and sustainability of artificial intelligence tools used in nursing education.

DESIGN

A descriptive cross-sectional study was conducted among. Three models, including the Technological Acceptance Model (TAM), the Information System Success Model (ISSM), and the Online Learning Self-Efficacy (OLSE), were used.

PARTICIPANT

All of fourth- year undergraduate nursing students who were enrolled in nursing department regularly (N = 420), and who respond (n = 204).

SETTING

In the nursing department of the health professions faculty at AL-Quds University, in Palestine.

RESULTS

Among the 204 students who responded, 9.80 % employed simulation, 5.40 % utilized virtual reality, 19.10 % used Chat GPT, 42.20 % used mobile applications, and 23.50 % utilized PowerPoint AI as part of their learning process. The mean and standard deviation (SD) were computed for key parameters related to the information system success model (AI) (ISSM) (M = 4.52, SD = 1.17). Technology Acceptance Model (TAM) (M = 4.61, SD = 1.16). Online Learning Self-Efficacy (OLSE) (M = 4.55, SD = 1.28).

CONCLUSION

There is a need to adapt teaching strategies and integrate AI tools as useful learning tools, which have become essential for students to complete their learning activities through enhancing knowledge of the multimodal technological factors that should be taken into consideration while creating AI tools across several domains for universities and developers.

An integrated model of UTAUT2 to understand consumers' 5G technology acceptance using SEM-ANN approach

It has been a decade since the first extensive study on the internet's adoption and use was conducted. Circumstances have changed in the last decade internet has become an essential need for every human being. Socio-psychological, economic, and personal factors play a significant role in shaping human behaviour. But their role in shaping consumer behaviour toward 5G is still unexplored. In order to determine the impact of socio-psychological elements on 5G technology adoption intention, the study integrated curiosity, perceived value, functional value, and environmental awareness into UTAUT2 and analyzed how they interact. Instead of relying on linear models, this study employed a dual-stage SEM-ANN approach because customers' decision-making process to adopt new technology is complex. Valid responses from 840 respondents were collected, investigated, and ranked using the deep learning ANN approach. All predictors were found statistically significant except social influence. ANN sensitivity analysis revealed that newly integrated predictors (environmental awareness, curiosity) are surprisingly the most important predictors, followed by facilitating conditions and perceived satisfaction. SEM-ANN hybrid two-step deep learning approach explained 83.6% variance higher than the baseline model (UTAUT2). The study improved UTAUT2 by adding new variables and expanding its canvas to predict user technology adoption. This will show how consumers react to 5G services and help telecoms grow into new markets.

What insisted baby boomers adopt unified payment interface as a payment mechanism?: an exploration of drivers of behavioral intention

Purpose

The unified payment interface (UPI) is in its early stages of adoption for baby boomers. This study explores the factors affecting the behavioral intention of baby boomers to adopt UPI. UTAUT was adopted as theoretical lens of the study and extended with ubiquity, privacy risk and perceived security. The impact of an external factor – effect of COVID-19 was also examined in this study.

Design/methodology/approach

A consumer intercept survey was used to collect data from baby boomers via a self-administered structured questionnaire. Structural equation modeling was used to establish the relationships among latent variables. Further, using bootstrap re-sampling technique, the role of perceived security as a mediator between risk, ubiquity and behavioral intention was examined.

Findings

The study confirmed that COVID-19 was the most influential external factor for baby boomers to adopt UPI, followed by performance expectancy, social influence, ubiquity, effort expectancy and perceived security. Apropos of UPI adoption by baby boomers, privacy risk negatively influenced perceived security, whereas perceived security fully mediated the relationship between risk, ubiquity and behavioral intention.

Research limitations/implications

The study focused only on baby boomers and their intention to adopt UPI. Hence the results cannot be generalized to all age groups and are specific to the cohort.

Originality/value

The present study aims to establish research findings on predicting antecedents of adopting a newly introduced payment mechanism and an exemplary Indian digital innovation, UPI, by baby boomers. This study is first to empirically explore intention of baby boomers toward adoption of UPI.

Éclaircissement to Understand Consumers' Decision-Making Psyche and Gender Effects, a Fuzzy Set Qualitative Comparative Analysis

Consumers' decision-making is complex and diverse in terms of gender. Different social, psychological, and economic factors mold the decision-making preferences of consumers. Most researchers used a variance-based approach to explain consumer decision-making that assumes symmetric relationship between variables. We have collected data from 468 smartwatch users and applied a fuzzy set qualitative comparative analysis (fsQCA) to explain and compare male and female consumers' decision-making complexity. fsQCA assumes that an asymmetric relationship between variables can exist in the real world, and different combinations of variables can lead to the same output. Results explain that different variables have a core and secondary level of impact on consumer decision-making. Hence, we can not claim that certain factors are significant or insignificant for decision-making. fsQCA results revealed that cost value, performance expectancy, and social influence play a key role in consumers' buying decisions. This study has contributed to the existing literature by explaining consumer decision-making by applying configuration and complexity theories and identifying unique solutions for both genders. A major contribution to theoretical literature was also made by this research, which revealed the complexity of consumer purchasing decisions made for new products.

Factors Impacting Mobile Banking in India: Empirical Approach Extending UTAUT2 with Perceived Value and Trust

The aim of this research is to study the factors impacting usage of mobile banking (mBanking) by consumers in India. The study adopts the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) with Social Value (SV), Monetary Value (MV), Emotional Value (EV), Quality Value (QV), Trust and the moderation effect of gender. Online and offline survey methods were used to collect primary data from 457 Indian consumers using mBanking. SPSS AMOS was utilized to empirically validate the conceptual model, test research hypothesis and moderation effect. The factors effort expectancy (EE), monetary value (MV), emotional value (EV), quality value (QV) and trust (TR) were found to be significant on behavioural intent (BI), whereas performance expectancy (PE) and social value (SV) were not found to be significant. Banking organizations can formulate strategies to attract new consumers and continue to engage in retaining consumers in using these influencing factors to adopt mBanking and other related mobile financial services (MFS). The study integrates perceived value components and trust with UTAUT2 to form a comprehensive model for examining mBanking adoption.

An integrated fuzzy model for evaluation and selection of mobile banking (m-banking) applications using new fuzzy-BWM and fuzzy-TOPSIS

Mobile technology has revolutionised various business processes. Banking is one of them. Traditional banking operations are gradually changing with the introduction of efficient mobile technologies. Mobile banking (m-banking) has recently emerged as an innovative banking channel that provides continuous real-time customer service. It is expected that the market for m-banking will expand in the near future. There are currently various types of m-banking applications in the market. However, ranking and selecting efficient applications is difficult due to the involvement of multiple factors. As of now, very few studies have reported the m-banking application selection framework, left scope for further research. The current study proposes an m-banking application selection model based on a combined fuzzy best–worst method (fuzzy-BWM) and fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy-TOPSIS). The research was carried out in several stages, beginning with the identification of potential factors and progressing to pair-wise comparisons and the final ranking of the applications. The fuzzy set theory was applied to handle the ambiguity of the decision maker. In the first stage, fuzzy-BWM was used to determine the weight of the factors. Further, fuzzy-TOPSIS was applied to rank the m-banking applications. The present study has adopted a new fuzzy BWM, which differs significantly from the existing fuzzy-BWM, to solve the nonlinearity problem of optimisation. The applicability of the proposed model has been demonstrated through a real-life case study. The efficacy of the model has been further examined by performing a sensitivity analysis. The study observed application functionality, convenience, and performance expectancy as significant factors in selecting an m-banking application, followed by performance quality, security, and compatibility. The proposed model can assist financial institutions and customers to overcome the challenges of choosing an appropriate m-banking application. The proposed model can be used to benchmark the m-banking applications in the market.

An Artificial Intelligence-Based Model for Prediction of Parameters Affecting Sustainable Growth of Mobile Banking Apps

Nowadays, mobile banking apps are becoming an integral part of people lives due to its suppleness and convenience. Despite these benefits, yet its growth in evolving states is beyond expectations. However, using mobiles devices to conduct financial transactions involved a lot of risk. This paper aims to investigate customers’ reasons for non-usage of the new conduits in developing countries with distinct interest in Nigeria. The study adopts two methods of analysis, artificial intelligence-based methods (AI), and structural equations modeling (SEM). A feed-forward neural network (FFNN) sensitivity examination technique was used to choose the most dominant parameters of mobile banking data collected from 823 respondents. Four algebraic directories were used to corroborate the study AI-based model. The study AI results found risk, trust, facilitating conditions, and inadequate digital laws to be the most dominant parameters that affect mobile banking growth in Nigeria, and discovered social influence and service quality to have no influence on Nigerians’ resolve to use moveable banking apps. Moreover, the results proved the superiority of AI-based models above the classical models. Government and pecuniary institutes can use the study outcomes to ensure secured services offering, and improve growth. Finally, the study suggests some areas for future studies.

e-Banking Adoption: An Opportunity for Customer Value Co-creation

The development of information and communication technologies offers innovative opportunities to establish business strategies focused on customer value co-creation. This situation is especially notable in the banking industry. e-Banking activities can support competitive advantages. However, the adoption of e-banking is not yet well-established among consumers. In this sense, the technology acceptance model (TAM) is considered essential in studying consumer behavior applied to adopt a particular technology. According to the TAM model, this study analyses the factors which influence bank customers to adopt e-banking to facilitate their banking services and support the process of value co-creation. Consequently, the authors examine five main aspects of the technology adoption model to provide a broad understanding of bank customers’ consumption of e-banking. A partial least squares structural equation modeling (PLS-SEM) analysis is conducted to evaluate proposed relationships between factors and customers’ e-banking adoption.

Factors Impacting Mobile Banking in India: Empirical Approach Extending UTAUT2 with Perceived Value and Trust

The aim of this research is to study the factors impacting usage of mobile banking (mBanking) by consumers in India. The study adopts the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) with Social Value (SV), Monetary Value (MV), Emotional Value (EV), Quality Value (QV), Trust and the moderation effect of gender. Online and offline survey methods were used to collect primary data from 457 Indian consumers using mBanking. SPSS AMOS was utilized to empirically validate the conceptual model, test research hypothesis and moderation effect. The factors effort expectancy (EE), monetary value (MV), emotional value (EV), quality value (QV) and trust (TR) were found to be significant on behavioural intent (BI), whereas performance expectancy (PE) and social value (SV) were not found to be significant. Banking organizations can formulate strategies to attract new consumers and continue to engage in retaining consumers in using these influencing factors to adopt mBanking and other related mobile financial services (MFS). The study integrates perceived value components and trust with UTAUT2 to form a comprehensive model for examining mBanking adoption.

A Comparative Study of Trust in Mobile Banking

With the rapid growth of mobile phone usage, mobile services have influenced many industries including banking. Mobile banking has become a popular service as it offers a convenient channel for customers to perform banking transactions. Nevertheless, not all customers feel safe performing financial transactions online. Trust has become a crucial element on whether customers choose to use mobile banking. As a comparative study, this research examines factors and bank customers' characteristics that influence trust in mobile banking between U.S. and Thai mobile banking customers. Three hundred and eight USA consumers and two hundred and fifty-two Thai consumers participated in this study. The results found multiple significant factors influencing trust and usage of mobile banking. This study expands on previous trust and mobile banking usage research and provides practical implications for cross-cultural strategies in mobile banking.

Investigating the role of leader-member exchange for goal commitment in system implementation

Purpose

Although Leader-Member Exchange (LMX) has been studied within the domain of organizational psychology, it has not received major attention from information systems literature and researchers. Drawing on LMX theory and the theory of reasoned interaction, this study investigates the roles of LMX, individual member's attitude toward system adoption, supervisor influence and goal commitment on mandatory system implementation. Specifically, our model investigates the moderating role of LMX and how it can be interpreted for an individual member's system adoption in an organization.

Design/methodology/approach

Partial least square (PLS) technique with the field survey of 148 participants was used for this analysis.

Findings

The empirical test results in the field setting show that attitude and supervisor influence positively affect goal commitment in the system implementation. Furthermore, LMX is a significant moderator between attitude and goal commitment within organizations, but this moderating effect is not valid in the relationship between supervisor influence and goal commitment since it is a more complex process influenced by variables other than supervisor influence.

Originality/value

The results showed that the model in this research has high explanatory and predictive power and is valuable in offering insights and guidance for implementers initiating technology-related changes within organizations.

Role of Personalization in Continuous Use Intention of Mobile News Apps in India: Extending the UTAUT2 Model

The aim of this study was to empirically examine the extended unified theory of acceptance and use of technology 2 (UTAUT2) model by adding “personalization” as one of the antecedents, as well as a moderator to determine the key factors for the continuous use intention of mobile news applications (apps). For this study, an online and manual sample survey of 309 respondents, who had used the news app earlier, was collected and analyzed, using quantitative methods such as explanatory and confirmatory factor analysis, structural equation modeling, and Hayes process for finding moderating effects among variables. The findings of the direct effect demonstrated that performance expectancy (PE) has the most influential effect on continuous use intention, followed by habit (HT), hedonic motivation (HM), and facilitating conditions (FC). Furthermore, the outcome of tests for the moderating effect of personalization between UTAUT2 constructs and continuous use intention (CUI) showed that personalization has a significant moderating effect on performance expectancy and habit. Therefore, this research establishes the key role of PE, HT, HM, and FC as main factors that trigger the users’ continuous use intention of news apps and provides an integrated framework to assess the moderating effect of personalization on technology acceptance. The findings of the research expand the existing literature on news applications and provide foundation for future research studies in the area of mobile news apps.

Understanding the determinants of mobile banking continuance usage intention

Purpose

The quality of people life and efficiency of banks can be improved by mobile banking (m-banking). The long-term success of m-banking depends on its constant use. The purpose of this paper is to investigate the determinants of m-banking continuance intention to use, using the technology continuance theory (TCT) by including the self-efficacy and channel preference.

Design/methodology/approach

Empirical data from 369 Malaysian users who had prior experience with mobile banking were analysed, using partial least squares technique.

Findings

The results confirmed that the TCT model had a high exploratory power in explaining users’ perceived usefulness (PU), satisfaction, attitude and intentions to continue to use m-banking. Furthermore, self-efficacy and channel importance were important drivers of continuance intention in the context of m-banking. According to the results, perceived ease of use has no effect on PU and attitude in the post-adoption stage.

Practical implications

The findings help bank managers to understand the importance of meeting customers’ needs and expectations as a prerequisite in enhancing their satisfaction and favourable attitude towards m-banking and consequently their continuance intention.

Originality/value

Based on the TCT model, this study contributes to the limited body of research on continuance intention to use m-banking. Furthermore, self-efficacy and channel preferences were added to the TCT model and the results confirmed the importance of enriching the TCT model to explain continuance intention to use information systems by adding contextual factors.

Understanding the Sustainable Usage Intention of Mobile Payment Technology in Korea: Cross-Countries Comparison of Chinese and Korean Users

Mobile payment (m-payment) enables consumers to perform their payment tasks via a mobile technology platform. In this study, we summarized, evaluated, and expanded upon the literature about m-payment usage intention by synthetically integrating the advantages of three information systems theories into an integrated model, which details the complementary relationship between the objective measures, subjective perception of m-payment services, and m-payment technology–task fit characteristics. Based on a sample of 908 individuals in two different Kakaopay user groups (467 Chinese Kakaopay users in Korea and 441 local Korean Kakaopay users) and the three-model integrated optimization, we integrated the unified theory of acceptance and use of technology model (UTAUT), the information systems success model (D&M ISS), and the task-technology fit model (TTF), considering moderating variables (Chinese and Korea experienced consumers) and multi-group analysis. We chose the factors influencing Chinese and Korean consumers' usage intention as the research objects, and ultimately achieved our purpose of more accurately predicting consumer behavior patterns to expand the scale of potential Chinese consumers. The empirical results theoretically contribute to academic and practical solutions for the Korean m-payment product and help technology suppliers to stimulate the sustainable growth of Korean mobile payment consumer groups in Korea.

A(n) (a)symmetric perspective towards task-technology-performance fit in mobile app industry

Purpose

The purpose of this paper is to examine (a)symmetric features of task-technology-performance characteristics that are most relevant to fit, satisfaction and continuance intention of using apps in mobile banking transactions.

Design/methodology/approach

Exploratory factor analysis was used with maximum likelihood extraction and Varimax rotation on a separate sample of 183 mobile banking apps users prior to the main data collection. The theoretical model was tested applying a factor-based structural equation modelling approach to a sample of 250 experienced mobile banking apps users.

Findings

The study unveiled that the task and performance characteristics are more relevant compared to technology characteristics when doing transactions via apps. In addition, the findings uncovered that user satisfaction and continuous intention to use apps stem from the degree of fit in online transactions. The findings of moderation analysis highlighted that users in the lower income group are more concerned about the performance characteristics of banking apps, and there are no differences across age and gender groups. Surprisingly, technology characteristic has a nonlinear nature and this study shows potential boundary conditions of technology characteristics in degree of fit, user satisfaction and continuance intention to use apps.

Practical implications

Findings from the conditional probabilistic queries reveal that with 83.3 per cent of probability, user satisfaction is high when using apps for banking transactions, if the levels of fit, task, performance and technology characteristics are high. Furthermore, with 72 per cent of probability, continuance intention to use apps is high, if the levels of performance and task characteristics are high.

Originality/value

Contributing to task-technology fit theory, this study shows that performance characteristics need to be aligned with task and technology characteristics in order to have better fit when using apps for online banking transactions.

Extended Technology Acceptance Model to Predict Mobile-Based Money Acceptance and Sustainability: A Multi-Analytical Structural Equation Modeling and Neural Network Approach

This research is a pioneering study into the adoption of mobile-based money services for financial inclusion and sustainability in developing countries like Togo. Owing to their differences from more usual mobile-based banking and payment services, such technology is being aggressively promoted by providers of network telecommunication companies. However, the factors influencing its sustainable acceptance remain largely unknown. This paper extends the original Technology Acceptance Model (TAM), by integrating self-efficacy (SEMM), technology anxiety (TAMM), and personal innovativeness (PIMM). The research model is assessed with survey data of 539 actual and prospective mobile money users employing structural equation modeling–artificial neural networks (SEM–ANN) approach. A feed-forward-back-propagation (FFBP) multi-layer perceptron (MLP) ANN with significant predictors obtained from SEM as the input units and the root mean square of errors (RMSE) indicated that the ANN method achieves high prediction accuracy. The results present conclusive evidence that perceived ease-of-use (PEMM) is the most significant factor affecting consumers’ attitudes to mobile-based money. While perceived usefulness (PUMM) and PIMM affect adoption decisions, their impact is much lower. Consumer attitudes and intentions were found to have a significant relationship with TAM. SEMM and TAMM; however, they showed mixed results. These findings will be useful to retain prevailing users and attract new ones.