E-Payment Adoption

Background: The utilization of virtual healthcare services, particularly telemedicine, has been accelerated by the COVID-19 pandemic. Although the pandemic is no longer the primary concern, telemedicine still holds potential for long-term adoption. However, implementing telemedicine in Indonesia as an online platform for remote healthcare delivery still faces issues, despite its potential. Further investigation is required to identify the factors that affect its adoption and develop strategies to surmount implementation challenges. Objective: This study aims to examine and enrich knowledge about the adoption of telemedicine in Indonesia. Methods: A cross-sectional survey was conducted through an online questionnaire to collect data. Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) was employed by integrating with several factors, such as eHealth Literacy, Privacy Concerns, and Trust. Gender and age were considered as moderating variables. Data samples were analyzed using Partial Least Square – Structural Equation Modeling (PLS–SEM). Results: The findings suggest that performance expectancy, effort expectancy, social influence, eHealth literacy, and trust have a significant impact on adults’ behavioral intention to use telemedicine. However, facilitating condition, price value, and privacy concern do not show any significant effects on adults’ Behavioral Intention to Use Telemedicine. Conclusion: This study highlights the importance of understanding adoption factors to develop effective strategies. Results show performance expectancy, effort expectancy, social influence, eHealth literacy, and trust are significant factors, while facilitating condition, price value, and privacy concern are not. The UTAUT2 model is a good predictive tool for healthcare adoption. To increase usage intention, several aspects must be considered in the implementation of telemedicine. Keywords: Adoption, Behavioral Intention to Use, Telemedicine, UTAUT2, Virtual Healthcare.

This study investigates the factors influencing users’ satisfaction and trust in digital government services, focusing on the Technology Acceptance Model (TAM) (perceived usefulness, and ease of use) and the Unified Theory of Acceptance and Use of Technology (UTAUT) (effort expectancy, social influence, and performance expectancy). The study employs a quantitative research approach, utilizing snowball sampling to collect data from users of e-government services in Saudi Arabia. The data is analyzed using statistical techniques, including Structural Equation Modeling (SEM), to test the research hypotheses. Effort expectancy, usefulness, ease of use, and social influence drive user satisfaction, with effort expectancy being the key factor. Satisfaction boosts trust in digital platforms. Performance expectancy, however, does not appear to affect satisfaction, likely due to cultural or contextual factors specific to Saudi Arabia. Although this study is valuable, it has limitations, including potential sampling bias. Future research should consider additional contextual factors, diverse cultures, and moderators such as cultural influences and individual differences. Longitudinal and qualitative studies could enhance understanding of the user’s satisfaction and trust in digital government services in Saudi Arabia. This study integrates the Theory of Acceptance and Use of Technology (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) to examine factors influencing user satisfaction and trust in digital government services in Saudi Arabia. The findings that shape user satisfaction and trust contribute to the academic discourse on digital government services and provide practical implications for policymakers, IT developers, and government entities who are concerned with developing e-government services.

The purpose of this study is to examine the behavioral intention/actual behavior of adoption of Mobile Kasir Point of Sale (Moka POS) users using Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Micro, Small, and Medium Enterprises (MSME) have a major contribution to the Indonesian economy, especially MSMEs in Jakarta as an economic center of the nation. During the pandemic, MSMEs are increasingly aggressive in optimizing the use of digital technology in accounting such as Moka POS. The research method is a survey using electronics questionnaires to MSME owners in Jakarta who are using Moka POS. The data analysis technique used a Structural Equation Model (SEM) with the Smart Partial Least Square (PLS) software approach. The result shows that performance expectancy, effort expectancy, and social influence have a positive effect on behavioral intention, and behavioral intention also has a positive effect on actual behavior to use the Moka POS. Meanwhile, facilitating conditions did not positively affect actual behavior to use the Moka POS. This study contributed theoretical and practical contributions to behavioral accounting. Keywords: Micro, Small, and Medium Enterprises, Moka POS, Unified Theory of Acceptance and Use of Technology.

This study examines the relationship between technical readiness (TR) and the Unified Theory of Acceptance and Use of Technology (UTAUT) within the framework of Over-the-Top (OTT) media services, particularly Netflix. The study employs the UTAUT model and integrates the TR model's external factors of "optimism," "innovativeness," "inadaptability," and "insecurity" to examine their moderating influences on customer utilisation of Netflix. In 2024, 475 questionnaires were disseminated in this study, of which 453 were considered valid. The study revealed that customer trust in relationships significantly influences user involvement in 'Performance Expectancy' (PE), 'Effort Expectancy' (EE), 'Social Influence' (SI), and 'Facilitating Conditions' (FC). Furthermore, consumers' intention to interact with Netflix's 'Performance Expectancy' (PE), 'Effort Expectancy' (EE), and 'Social Influence' (SI) considerably and positively affects their behaviour. The research employed hierarchical regression analysis to assess the impact of customer willingness to "Intention to Use" on the UTAUT regarding Netflix consumption. The findings indicate that the Trustworthiness Rating of consumers substantially affects the UTAUT dimensions of Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions. Moreover, consumers' inclination to use Netflix is positively influenced by the constructs of Performance Expectancy, Effort Expectancy, and Social Influence. The results demonstrate that consumers' Trustworthiness Rating substantially influences the UTAUT aspects of Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions. Moreover, the constructs of performance expectancy, effort expectancy, and social influence positively affect customers' inclination to utilise Netflix. The results of this study may inform strategic approaches to improve user engagement and satisfaction in the competitive OTT market.

For the past two decades, e-government has become a part of government’s development programmes throughout the world. With the availability of e-government, public services can be accessed 24 hours a day, 7 days a week. Governments have put a lot of resources into implementing e-government platforms. Technology adoption scholars have paid serious attention towards understanding the factors that influence citizens’ usage of online services. However, despite the enormous research efforts that have been put forth and the use of egovernment services that has been examined widely, e-government services offered by the government agencies often remain underutilised. Malaysia has successful cases of implementing e-government services. However, a recent study about e-government adoption in Malaysia indicated that it was growing slowly with a low rate of adoption. Moreover, several studies also found that citizens were more likely to use e-information services than e-payment services, even with both services were offered online in the same webpage. As such, it is reasonable for this study to understand the reasons e-information usage was higher compared to e-payment services in e-government services.Evidence demonstrates that the Unified Theory of Acceptance and Use of Technology (UTAUT) conceptual model has been successfully employed to explain technology adoption by citizens. Furthermore, the predictors in these models have been validated by prior studies in various settings. By considering a variety of types and levels of e-government services, the present study is significant in that it examines the citizens’ attitudes towards different e-government system use. Thus, this study was conducted with the aim to identify the predictor factors in the usage of different e-government services and functions by: i) examining the main factors that influence usage of different e-government services (i.e., income tax, property tax, and traffic fines); and ii) identifying the factors leading to the usage between e-informational and e-payment services.This study involved two stages. First, interviews with participants that had used government online services were undertaken as a scoping study to get opinion about citizens’ attitudes about using e-government services. After using a template analysis, five factors were identified to be relevant in the Malaysian context: Relative Advantage; Effort Expectancy; Social Influence; Perceived Trust; and Perceived Risk. Following from the scoping study, the UTAUT model was modified for this study. The second stage involved a web-based survey to collect data from 294 Malaysian citizens in Selangor who had used at least one e-government service in the past two years. As the main objective of this study was to identify the factors associated with technology use, multiple linear regressions were utilised. Statistical software package STATA version 14 was used to analyse the relationship between the predictors and the outcome variables. As the main objective of this study was to identify the drivers of technology adoption, regression analyses were utilised. As the study involved six different e-government services, the research findings provided varied results according to the type of services. This study confirmed that Effort Expectancy was found to be the most common factor associated with e-government usage for all services under study. This implied that the ease of use and easy to learn of e-services was found to be relevant reasons for citizens to use the service. The findings also show that Perceived Risk was consistently associated with e-services usage, and indicating that this factor was also common in explaining the citizens’ usage on e-government services. Finally, as the newest service, the traffic fines system use was associated with Social Influence and Relative Advantage factors, indicating that peers’ opinions and citizens perceived on the benefits of the online service are important to attract citizens to use the online service.In addition, research findings identified differences in drivers between e-information and e-payment services. For e-information, Effort Expectancy and Perceived Risk were identified as dominant factors associated with the citizen’s usage for both type of e-services. While, Relative Advantage and Social Influence were also identified to be associated with traffic fines services. For e-payment services, interestingly, the effect of the factors that influenced the citizens’ usage of e-government services were slightly different with e-information service. Besides the Effort Expectancy and Social Influence factors, Relative Advantage also was found to be associated but in selected e-services.The current study has significant empirical and practical contributions. Empirically, it contributes to the body of knowledge as this study provides a model that explains the different determinants of different e-services usage by citizens. Further, by integrating the UTAUT model with new constructs retrieved from a scoping study, a variation of citizens’ usage in different settings of systems were identified. As practical implications, the research identified the main determinants leading to users to adopt e-government services. Furthermore, due to limited resources, it is crucial for governments in developing countries to understand the important determinants that lead to the usage of e-government services.

PurposeThis paper aims to develop and test a research model to explore the factors that influence pre-service teachers’ intention to use learning management system (LMS).Design/methodology/approachA cross-section study was conducted. A survey questionnaire was used to collect data from participants. The total number of participants was 361 pre-service teachers. Partial least square structural equation model was used to analyze the data.FindingsThe findings of this study found that the research model explained approximately 43% of the variance in behavioral intention. Also, the findings revealed that attitude and social influence had an effect on behavioral intention to use technology, but the facilitating condition had no effect on behavior intention to use technology. Finally, performance expectancy, effort expectancy and social influence had an effect on attitude while facilitating condition had no effect on attitude.Originality/valueIn technology acceptance research, unified theory of acceptance and use of technology (UTAUT) and technology acceptance model (TAM) have been broadly designed and empirically tested to elucidate the determinants that impact users’ intention to operate technology in the developed world. However, research on the validation of TAM and UTAUT to explain the determinants that influence preservice teachers’ intention to use a LMS in developing countries is insufficient. Therefore, it is important to evaluate the efficacy of the integrated model of TAM and UTAUT to explain preservice teachers’ intention to use technology and explore the influential determinants that explain preservice teachers’ intention to use LMS.

Objectives: Advances in technology have improved the lives of Indonesians. For example, the health sector. This is indicated by the emergence of telemedicine to facilitate health services. This study aims to test the effect of individual trust on the intention to use telemedicine applications. Therefore, the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) are used as the basis for answering the questions posed by this research. Methods: Sampling was conducted online and involved 402 respondents who all came from the Indonesian island of Java. Validity, reliability, and hypothesis testing used Structural Equation Modeling (SEM) with Smart-PLS 4 tools. Result: The results show that effort expectancy, performance expectancy, and social influence have a positive influence on individual belief; intention to use is influenced by individual belief and behavioral intentions. The results of the hypothesis testing show that behavioral intention has the greatest influence on intention to use with a t value of 31.315 and a β value of 0.801. Conclusion: The novelty of this study is that it includes individual belief variables that are influenced by variables from UTAUT, namely effort expectancy, performance expectancy, social influence, and facilitating conditions.

Purpose This study investigates the factors shaping Chinese university students' behavioral intentions to adopt artificial intelligence (AI) for English as a Foreign Language (EFL) writing development. Grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT) and second language acquisition principles, it aims to understand how performance expectancy, effort expectancy, social influence, facilitating conditions, perceived learning resources, perceived enjoyment, and attitude influence students' willingness to use AI in their writing processes. Design/methodology/approach Grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT) and second language acquisition principles, a cross-sectional survey was administered to 415 Chinese university students. Data were analysed using structural equation modeling (SEM) to examine the relationships among performance expectancy, effort expectancy, social influence, facilitating conditions, perceived learning resources, perceived enjoyment, attitude, and behavioral intention. Findings Path analysis revealed that performance expectancy, effort expectancy, facilitating conditions, and attitude significantly predict behavioral intention, with attitude being the strongest direct predictor. Surprisingly, social influence, perceived enjoyment, and perceived learning resources did not exert significant direct effects. Attitude fully mediated the effect of effort expectancy and partially mediated performance expectancy, while serving as an indirect-only mediator for social influence and perceived enjoyment. Originality/value This study challenges the universal applicability of Western technology acceptance models by highlighting the central role of attitude as a cultural-cognitive mediator in collectivist, exam-driven contexts. It proposes a cultural attunement model for AI adoption in EFL education and offers practical implications for pedagogy, policy, and culturally responsive AI tool design.

Research on technology adoption has identified a large number of factors that can affect individuals’ behavioral intentions to use various technologies, and many models have emerged. Venkatesh et al. (MIS Quarterly, 27(3), 425–478: 2003) aimed to develop an integrated model based on the idea that researchers may miss the opportunities offered by alternative models when they choose only one of the existing models. In the synthesis study, Theory of Reasoned Behavior, Technology Acceptance Model, Motivation Model, Theory of Planned Behavior, Unified Model of Technology Acceptance and Planned Behavior, PC Use Model, Diffusion Theory, and Social Cognitive Theory were discussed, their deficiencies and strengths were compared, and the Unified Theory of Acceptance and Use of Technology (UTAUT) was developed. According to UTAUT, using behavior is determined directly by behavioral intention and facilitating conditions, and performance expectation, which determines behavioral intention, is indirectly determined by effort expectancy, social influence, and facilitating conditions variables. In addition, age, gender, experience, and voluntariness of use variables were added as directing variables to the relationships in the model. To make the model more consumer-centric, Venkatesh et al. (MIS Quarterly 36, 157–178: 2012a) added hedonic motivation, price value, and habit variables to the model and removed the voluntariness of use moderator from the model, thus expanding the UTAUT model to UTAUT2. In this chapter, UTAUT, which examines the variables that affect individuals’ technology acceptance and use with a holistic approach, is examined in an educational context. The reader who completes the section will be able to (a) explain the general structure of the model and for what purpose it was developed (b) define the factors in the model and the relationships between factors (c) give an educational example of the acceptance and use of a technology (d) expand the UTAUT and UTAUT2 models in an educational context, formulate hypotheses/problems, collect and analyze data, and (e) discuss and evaluate the results of a study using the UTAUT and UTAUT2 models.KeywordsICT in educationBehaviorAcceptanceTechnology acceptanceUTAUT

PurposeThe purpose of this study is to investigate consumers’ cryptocurrency adoption through the unified theory of acceptance and use of technology (UTAUT) and complexity theory.Design/methodology/approachBy using a purposive sampling method, a configurational model was developed and a questionnaire-based survey was conducted to gather responses from a Malaysian sample. A total of 223 responses were obtained. Partial least square structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) were adopted to analyze the data.FindingsThe PLS-SEM indicated that performance expectancy, effort expectancy, social influence and affinity for technology interaction were positive cryptocurrency adoption predictors, whereas regulation was a negative predictor. Based on the fsQCA, cryptocurrency adoption could be explained by six configurational paths, which comprised combinations of the proposed causal conditions: the UTAUT factors (performance expectancy, effort expectancy, facilitating condition and social influence), environmental factor (regulation) and individual factors (financial knowledge and affinity for technology interaction).Research limitations/implicationsThis study offers contributions to the theoretical body of knowledge by articulating the relevance of extended UTAUT and extending the established UTAUT model by integrating external environment and personal factors, also showing the linear and nonlinear interplays of performance expectancy, effort expectancy, facilitating conditions, social influence, regulation, financial knowledge and affinity for technology interaction.Practical implicationsThe findings facilitated practitioners’ (cryptocurrency brokers, governments and businesses) fostering of cryptocurrency adoption through the joint consideration of different factors. The factors spanned technological attributes and individual characteristics to regulation. Practitioners should acknowledge that different combinations of the aforementioned antecedents can be equally effective to increase cryptocurrency adoption. The findings suggested that these causal conditions should be considered holistically and that there is no best predictor.Social implicationsIn social terms, the research is expected to contribute to the dissemination of cryptocurrencies and help governments and central banks to develop, regulate and supervise digital currencies, as well as in the implementation of a digital currency ecosystem aligned with sustainable development goals. Economically, the results might foster a high cryptocurrency adoption rate and stimulate crypto-token-based business models and investment opportunities that present new means of revenue generation at individual, organizational and national levels.Originality/valueThis study offers unique perspectives for the body of knowledge and practice in the cryptocurrency domain, using both symmetric and asymmetric methodologies, by delineating the configurational logic involving technological capabilities, social influences, regulation and individual characteristics in facilitating more efficacious dissemination of cryptocurrencies.

The Covid-19 pandemic has caused changes in human behaviour, including payment transaction methods from cash to non-cash. In addition, the National Non-Cash Program (GNTT) by Bank Indonesia (BI) also supports this new behaviour. This non-cash payment also occurs in donation payments, including zakat, infaq, alms and other Islamic social funds. This research analyses the factors influencing user behaviour (UB) towards the online donation from cash to non-cash. This study uses quantitative research within Partial Least Square – Structural Equation Modeling (PLS-SEM) tools. The data of this study is compiled by questionnaire on 124 respondents in East Java who made online donations during the Covid-19 pandemic (March 2020 – 2021). This research uses a technology adaptation model that is the UTAUT (Unified Theory of Acceptance and Use of Technology) model using the facilitating conditions (FC), performance expectancy (PE), effort expectancy (EE) and social influence (SI) variables. The results of this study indicate that (a) FC has a positive and significant effect on PE and SI, (b) PE and SI have a positive and significant effect on EE, and (3) PE and SI have a positive and significant effect on UB. Meanwhile, ease of donating online (Effort Expectancy) does not provide influence user behaviour of online donations. In addition, recommendations are also given to online donation organisations to improve collaboration, credibility and use of promotion media.

This study aims to analyze and compare two technology acceptance models Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT) in measuring user acceptance of the KAI Access mobile application in Surabaya. The research adopts a quantitative approach, using questionnaires distributed to 200 active users of the KAI Access app. Data were analyzed using Partial Least Square-Structural Equation Modeling (PLS-SEM) with SmartPLS software. Results show that all variables in the TAM model significantly influence behavioral intention, particularly perceived usefulness and perceived ease of use. Meanwhile, in the UTAUT model, only effort expectancy and facilitating conditions have a significant effect. The R-square and Q-square values indicate that TAM has stronger predictive capability than UTAUT in this context. These findings offer useful insights for improving the KAI Access application and can serve as a reference for future research on technology acceptance in public digital services.

The payment system of a country plays a crucial role in its economy; however, despite the benefits of e-Payment and efforts by financial authorities, Nigeria still has a low e-Payment adoption rate. In this regard, there is an urgent need to investigate the factors that affect individuals’ intention to adopt e-Payment. Drawing on the unified theory of acceptance and use of technology (UTAUT) model, this paper develops a theoretical model for e-Payment adoption in Nigeria. Additionally, a survey was conducted on 500 respondents with 213 complete responses received to test the model, and results show that perceived benefits, effort expectancy, social influence, trust, awareness, and demographic variables affected individuals’ intention to adopt e-Payments. Based on the findings, managerial and theoretical implications are deliberated.

The transformative potential of artificial intelligence (AI) in banking is widely acknowledged, yet its practical adoption often faces resistance from users. This study investigates the factors influencing AI adoption behavior among various stakeholders in the Greek semi-mature systemic banking ecosystem, addressing a critical gap in the relevant research. By utilizing the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2), and Partial Least Squares Structural Equation Modelling (PLS-SEM) models, data from 297 respondents (bank employees, digital professionals, and the general public) were analyzed. The results highlight the strong relevance of constructs such as Performance Expectancy, Effort Expectancy, and Hedonic Motivation, whereas Social Influence was deemed non-significant, reflecting a pragmatic stance toward AI. Demographic factors like gender and age were found to have no significant moderating effect, challenging traditional stereotypes. However, occupation and education emerged as significant moderators, indicating varying attitudes among professions and educational levels. This study is the first to develop a theoretical framework for AI adoption by Greek banking institutions, offering Greek banking practitioners actionable insights. The findings also hold relevance for countries with similar digital maturity levels, aiding broader AI integration in banking.

Malaysia's banking sector has undergone significant transformation driven by digital technologies, revolutionizing traditional banking operations and customer engagement strategies. The introduction of digital banking products has redefined the financial landscape, providing unparalleled convenience, accessibility, and financial control to consumers and businesses. Key advantages such as operational efficiency, cost savings, 24/7 accessibility, and real-time financial management have been crucial in driving the adoption and readoption of digital banking services across various demographic segments in Malaysia. The study leverages theoretical frameworks like the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) to understand user acceptance and behavior towards digital banking readoption. These models highlight constructs such as performance expectancy, effort expectancy, social influence, and facilitating conditions as essential factors influencing technology adoption. Recent research emphasizes the importance of service quality in mobile banking applications as a determinant of customer satisfaction and loyalty, reflecting the advanced expectations of tech-savvy Malaysian consumers. a rigorous methodological approach, the study examines the factors influencing the readoption of digital banking products among Malaysian consumers. Utilizing Smart Partial Least Squares Structural Equation Modelling (Smart PLS-SEM), the study validates the relationships between perceived benefits and digital banking readoption decisions. The findings reveal that effort expectancy, rather than performance expectancy, is a critical factor influencing readoption, underscoring the importance of usability and convenience. The model explains 66.4% of the variance in readoption behavior, highlighting the complexity of consumer decision-making in digital banking. This study concludes that banking institutions must continuously enhance digital platform functionality and security while prioritizing superior user experiences. Trust, perceived security, and customer service quality remain pivotal in shaping consumer attitudes towards digital banking adoption and readoption, reflecting the dynamic and evolving preferences within Malaysia's digital banking ecosystem.