Elucidating user behavior of mobile learning

Using an extended technology acceptance model to investigate facial authentication

Evolving transnational consumer behaviors under COVID-19: determinants of students’ intention to use Web 3.0

Examining differences and similarities between graduate and undergraduate students' user satisfaction with digital libraries

Purpose Virtual try-on (VTO) technology offers consumers a shopping experience comparable to direct product examination by providing detailed product information and enhancing enjoyment during online shopping. Against this backdrop, this study extends the technology acceptance model (TAM) to investigate the factors influencing consumers’ attitudes toward VTO technology and their willingness to purchase online. Design/methodology/approach Data were collected through an online survey of 228 Italian respondents. The proposed research model was tested through an exploratory factor analysis (EFA) and a confirmatory factor analysis (CFA), followed by a structural equation model (SEM) with an ordered Probit approach. Findings The results highlight the significant impact of perceived enjoyment (PE), innovativeness and perceived environmental benefits (PEBs) on consumer attitudes toward VTO and their online purchase intentions. This study underscores the role of VTO in enhancing online shopping experiences, leveraging both utilitarian and hedonic values, ultimately encouraging technology adoption. Research limitations/implications The findings offer valuable insights for retailers seeking to encourage online shopping using VTO technology, fostering PE, stimulating interest in innovative solutions and promoting responsible consumption choices. Originality/value This research extends the TAM by integrating external variables – innovativeness and PEBs – into the analysis, while accounting for the mediating role of PE on consumer behaviour.

With the growing use of technology in medical education, a framework is needed to evaluate learners' and educators' acceptance of these technologies. In this context, the Technology Acceptance Model (TAM) offers a valuable theoretical framework, providing insights into the determinants influencing users' acceptance and adoption of technology. This review aims to systematically synthesize the body of research in medical education that uses the TAM. An electronic literature search was conducted using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach in February 2024 on the Embase, MEDLINE, PsycINFO, PubMed, and Web of Science databases, yielding 680 articles. Upon elimination of duplicates and applying the exclusion criteria, a total of 39 articles were retained. To evaluate the quality of the study, the Medical Education Research Study Quality Instrument score was calculated for each analysis with a qualitative component. Studies using TAM in medical education began in 2010, with the model's application relatively rare up to 2016. Most of the studies were quantitative, operationalizing the TAM as a survey instrument, but it was also used as a research framework in qualitative data analysis. Structural equation modeling, descriptive analysis, and correlation analysis were the most common data analysis approaches in the studies. E-learning and mobile learning were the predominant learning interventions explored, but there were indications that novel learning technologies such as augmented reality, virtual reality, and 3D printing were being investigated. The study's findings reveal an expanding scholarly engagement with using TAM in medical education. Although the TAM has been mostly used as a survey instrument, it can also be adapted as a qualitative research framework to analyze data. This systematic review provides a foundation for future research to understand the factors influencing users' acceptance of technology, especially in medical education.

Given the pandemic that hit the world, there was suddenly an increased focus on E-learning. This study aimed at determining the various factors that influence the youth of India to opt for E-learning. This study was conceptualized based on the technology acceptance model and integrating social influence (SI) and perceived enjoyment (PE) as additional constructs to determine the attitude (AT) and behavioural intention (BI) towards E-learning. The study also proposes a basic framework of knowledge for E-learning, a shift from traditional classroom learning, which is not researched adequately in previous literature. The sample for this research study were postgraduate students drawn by non-probability judgment and snowball sampling. Data analysis was performed using structural equation modelling, cross-tabulation and Pearson correlation with the help of SPSS Amos software. The results of the study concluded that AT significantly mediates between perceived usefulness, perceived ease of use, SI, PE, and BI. Additionally, the study determined the classroom and E-learning preferences of students comparatively.

This study examines the factors influencing seniors’ adoption of virtual reality (VR) cognitive training games by integrating the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM). Beyond the traditional constructs of these models, the research incorporates perceived enjoyment (PE), personal innovativeness (PI), and computer anxiety (CAX) to address seniors’ cognitive health needs and explore VR-based non-pharmacological interventions. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the study analyzed direct and indirect effects on adoption within a questionnaire-based framework. The research was conducted at community care centers in Taoyuan City, Taiwan, with 150 seniors aged 65–80. Participants engaged in a 20-min session with Nintendo Switch VR games and subsequently completed a questionnaire assessing their experiences. Results revealed that perceived ease of use (PEOU), PE, and subjective norms (SN) significantly shaped attitudes toward VR adoption, which strongly influenced behavioral intention (BI). BI emerged as a robust predictor of actual usage behavior (AUB), while CAX negatively impacted BI, highlighting the need to address emotional barriers. This study underscores the importance of designing intuitive, engaging, and accessible VR cognitive training games tailored for seniors. It also highlights the pivotal role of family and caregivers in fostering adoption, alongside the necessity of providing social and emotional support. These findings contribute to the theoretical understanding of VR-based games adoption in older adults and offer practical guidance for developers and healthcare providers aiming to create effective interventions for cognitive health.

The successful of developing and implementation of information sistem is dependon the user acceptance. SIPADU-STIS is an academic information system that support academic’s bisnis process. Technology Acceptance Model (TAM) will be employed for analysing of SIPADU-STIS system. Validation of TAM model will estimate using Structural Equation Model (SEM). The model shows that SIPADU-STIS has a high user’s acceptance .

Purpose This study aims to investigate the intention to use blockchain technology (BT) in the context of supply chain (SC) operations through an integrated technology adoption framework using two well-known models, the unified theory of acceptance and use of technology (UTAUT) and the technology acceptance model (TAM). Moreover, the study looked at the direct effect of TAM and UTAUT elements on attitude toward BT, as well as the role of attitude toward BT as a mediator between TAM and UTAUT elements and intention to use BT. Design/methodology/approach The study used a quantitative research method, and a structured questionnaire was used to gather primary data. The final sample, drawn using a convenience sampling that consisted of 273 managers from the Jordanian manufacturing sector. Structural equation modeling statistical method was conducted using the Smart PLS program to test hypotheses in the proposed study framework. Findings The study has provided intriguing results. It found that two UTAUT elements, namely performance expectancy and social influence and one TAM element, namely perceived usefulness, have a significant impact on the attitude toward BT. Besides that, the study found that attitude toward BT significantly mediated the relationship between UTAUT-TAM elements and intention to use BT. The findings revealed that three elements namely performance expectancy, social influence and perceived usefulness have statistical significance on intention to use BT through the mediation of attitude. Finally, there is a direct significant positive relationship between the attitude toward BT and intention to use it. Research limitations/implications The study helps decision-makers, South Carolina practitioners and academics recognize the fundamental factors that increase manufacturing firms’ intentions to use blockchain in their SCs. This gives decision-makers a better understanding of why users accept or reject BT, as well as how to improve user acceptability through technological design. Future studies should seek for a bigger sample size and use random sampling techniques. Furthermore, the study should be replicated in other industries or developing countries to validate the findings. Originality/value There is a scarcity of studies identifying the factors that increase blockchain adoption intention in SCM and developing countries. This study differs in that it examines BT intention to use in the context of SC using an integrated technology adoption framework that uses two well-known models, UTAUT and TAM, whereas other studies typically use only one model/theory. Moreover, given the importance of attitude in behavior, this study also investigated the effect of TAM-UTAUT elements on attitude toward BT, as well as the role of attitude toward BT as a mediator between TAM and UTAUT elements and intention to use BT.

Successful implementation of Information Technology can be judged or predicted from the user acceptance. Technology acceptance model (TAM) is a model that is built to analyze and understand the factors that influence the acceptance of the use of technologies based on the users perspective. In other words, TAM offers a powerful explanation related to acceptance of the technology and its behavior. TAM model has been applied widely to evaluate various information systems (IS) or information technology (IT), but it is the lack of research related to the evaluation of the TAM model itself. This study aims to determine whether the model used TAM is still relevant today considering rapid development of information communication technology (ICT). In other words, this study would like to test whether the TAM measurement indicators are valid and can represent each dimension of the model. The method used is quantitative method with factor analysis approach. The results showed that all indicators valid and can represent each dimension of TAM, those are perceived usefulness, perceived ease of use and behavioral intention to use. Thus the TAM model is still relevant used to measure the user acceptance of technology.

IntroductionThis study explores the application of generative artificial intelligence (AI) art in digital art therapy, focusing on how it influences adolescents’ interest-driven participation. With mental health concerns rising among youth, understanding motivational mechanisms in AI-assisted therapeutic tools is both timely and essential.MethodsA cross-sectional survey was conducted with 444 junior and senior high school students in Hubei Province, China. The study integrated Emotional Design Theory and the Technology Acceptance Model (TAM) to construct a predictive model. Structural equation modeling (SEM) and artificial neural network (ANN) analyses were employed to validate the model and identify key predictors of engagement.ResultsSEM results indicated that perceived usefulness (PU), perceived ease of use (PEOU), perceived fun (PF), and perceived trust (PT) significantly influenced users’ attitudes toward use (ATT) (p < 0.001). ATT, PF, and PT were strong predictors of interest-driven participation, while the behavioral level had no direct effect on perceived enjoyment (PE). ANN analysis further highlighted ATT as the most influential predictor (100% normalized importance), notably exceeding PE (19.3%).DiscussionThese findings emphasize the importance of intuitive design, seamless interaction, and trust-building in sustaining adolescents’ engagement with AI-based art therapy. The study provides a theoretical foundation for understanding interest formation in youth and offers practical implications for improving emotional design, digital therapeutic tools, and mental health interventions.

Driven by market competitiveness enhancement, service improvement, and working effectiveness promotion, more and more organizations have realized their potentials and paid a lot of attentions to them (Chau &amp; Hu, 2002). As estimated, about 50% of new capital investment has been put in information technology (Westland &amp; Clark, 2000). Despite its great potentials, users’ acceptance or adoption of these technologies does not live up to the initial expectations (Sun &amp; Zhang, 2004). It is obvious that ITs are useless unless users accept and subsequently use them. Therefore, user technology acceptance becomes a hot topic and much effort has been made in order to obtain a deep understanding of how and why users accept certain technologies. Several models have been proposed in the last 2 decades and subsequent studies tested them (Table 1). New virtual technologies, especially collaborative technologies, enable some new forms of interaction. For example, members in virtual teams can work simultaneously on a document together as a distributed team, remotely access shared information from anywhere, or record team activities (Majchrzak et al., 2000). Virtual technologies, like other types of technology, have to be accepted and used by users first. However, virtual technologies, while sharing certain characteristics with other technologies, have special features. Therefore, this article is an attempt to identify the structure and factors influence user acceptance of virtual technologies based on existing user technology acceptance models. In general, the existing technology acceptance models can still be used for virtual technologies. Prior studies have confirmed that users accept virtual technologies in a similar way as other technologies (Moon &amp; Kim, 2001; Yager, 1999; Chen et al., 2002). For example, Moon and Kim (2001) studied the acceptance of the World Wide Web (WWW). According to their study, the results about key factors in extant models are consistent with prior studies, which means that the factors influencing user acceptance of general technologies, although a little different, are also suitable for virtual technologies. Another example is Yager’s study (1999), in which many factors, such as usefulness, ease of use that are traditionally considered to be important for technology acceptance in general, are still valid for virtual technologies. Therefore, we can borrow factors from existing models. However, virtual technologies have their own characteristics. Therefore the factors contributing to user acceptance are likely to be different (Moon &amp; Kim, 2001). So we need to propose new factors pertaining to the new type of technology. For example, playfulness is considered as an additional factor that is especially influential for virtual technologies (Moon &amp; Kim, 2001). In summary, we can refer to existing models while considering the characteristics of virtual technologies. Actually, it is a highly valid approach (Chen et al., 2002).

One common model utilized to understand clinical staff and patients' technology adoption is the technology acceptance model (TAM). This article reviews published research on TAM use in health information systems development and implementation with regard to application areas and model extensions after its initial introduction. An electronic literature search supplemented by citation searching was conducted on February 2017 of the Web of Science, PubMed, and Scopus databases, yielding a total of 492 references. Upon eliminating duplicates and applying inclusion and exclusion criteria, 134 articles were retained. These articles were appraised and divided into three categories according to research topic: studies using the original TAM, studies using an extended TAM, and acceptance model comparisons including the TAM. The review identified three main information and communication technology (ICT) application areas for the TAM in health services: telemedicine, electronic health records, and mobile applications. The original TAM was found to have been extended to fit dynamic health service environments by integration of components from theoretical frameworks such as the theory of planned behavior and unified theory of acceptance and use of technology, as well as by adding variables in specific contextual settings. These variables frequently reflected the concepts subjective norm and self-efficacy, but also compatibility, experience, training, anxiety, habit, and facilitators were considered. Telemedicine applications were between 1999 and 2017, the ICT application area most frequently studied using the TAM, implying that acceptance of this technology was a major challenge when exploiting ICT to develop health service organizations during this period. A majority of the reviewed articles reported extensions of the original TAM, suggesting that no optimal TAM version for use in health services has been established. Although the review results indicate a continuous progress, there are still areas that can be expanded and improved to increase the predictive performance of the TAM.

This study examines the use of the Metaverse platform to increase student interest in education. The focus of the study is the development of the CipherSphere learning platform, developed through the Spatial.io platform, as well as its functionality and implementation. This study investigates how elements of Technology Acceptance Model (TAM), including Perceived Ease of Use (PEU), Perceived Usefulness (PU), and Perceived Enjoyment (PE), affect the goals of students using the Metaverse platform in the learning process. The study involves fifty Form Three students from a secondary school in Southern Malaysia. This study uses a design development research approach. The Metaverse platform uses TAM factors to teach the topic of Columnar Transposition in Fundamental Computer Science subjects. The findings show that Perceived Enjoyment does not have a significant impact on students’ willingness to use the Metaverse platform. In contrast, Perceived Ease of Use and Perceived Usefulness have a significant impact. This study provides great benefits to educators and educational technology developers as they think about and implement digital learning methods. To ensure students accept and engage, ease of use must be considered. The results of this study also suggest that further research is needed to understand the elements that influence the acceptance of the Metaverse platform in various educational contexts.

Factors Influencing the Behavioural Intention to use the Internet as a Teaching-Learning Tool in Home Economics