Using an extended technology acceptance model to investigate facial authentication

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.

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

To understand potential users' behavioral intention (BI) to adopt new energy vehicles (NEVs), a media-based perceptions and adoption model (MPAM) of NEVs geared toward potential NEV consumers was constructed based on social cognition theory, the technology acceptance model, the value acceptance model, perceived risk theory, and the MPAM of autonomous vehicles (AVs). A sample survey including 309 NEV potential users was conducted and the results were analyzed through SPSS 24.0 and SmartPLS 3.0 to test the model and verify the research hypotheses. The results show that mass media (MM) has a direct influence on users' social norms (SNs) and part of product perceptions, and an indirect influence on their BI to adopt NEVs; SNs have a direct influence on product perception, and also indirectly affect BI toward NEVs. Product perception directly and significantly affects BI; perceived usefulness (PU), perceived ease of use (PEOU), and perceived enjoyment (PE) have a positive and significant influence on BI, while both perceived cost (PC) and perceived risk (PR) have a negative and significant impact. This study is a theoretical extension of the technology acceptance model (TAM) to green product adoption scenarios, such as NEVs, in the face of the external stimuli from MM information; it proposes product perception variables and media information effects that are different from the MPAM of AVs. The results are expected to greatly promote NEV design and marketing.

With the global prevalence of diabetes among the elderly on the rise, integrating smart product technologies into daily healthcare offers a promising solution. This study examines the key variables influencing elderly individuals’ acceptance of smart products to develop an ageing-oriented smart product design framework. A literature review and questionnaire were conducted to identify determinants of technology acceptance. To ensure robustness and practical applicability, the proposed framework was subsequently validated through expert review. The findings reveal that behavioural intention (BI) serves as the central variable influencing elderly users’ acceptance, while perceived ease of use (PEOU), perceived usefulness (PU), perceived enjoyment (PE), and self-efficacy (SE) emerge as significant internal predictors of BI. Among the external variables, appearance design (AD), function design (FD), and interface design (ID) exert the strongest indirect effects on BI through their influence on PEOU. Based on these relationships, a smart product design framework tailored for diabetic elderly was constructed. This study advances the understanding of the structural relationships between TAM variables and product design factors, providing both theoretical insights and practical guidelines for the development of smart products for diabetic elderly, with broader implications for the ageing population. Future research will further explore the daily needs of diabetic elderly and incorporate usability testing in real-world settings to implement and refine the framework.

The self-built e-reserve database (SED) has still been considered an essential e-reserve service in Chinese academic libraries to resolve the issue of insufficient library copies and to support the future digital learning model. This study aims to examine the factors influencing users’ continuance intention to use SED in university libraries based on an integrative model that includes the Information System Success Model (ISSM), the Technology Acceptance Model (TAM), the Post-Acceptance Model of Information System Continuance, and the Stimulus-Organism-Response (S-O-R) model. A total of 384 valid responses were collected through a questionnaire-based survey across Chinese colleges and universities. The findings confirmed the direct influence of perceived usefulness (PU), perceived ease of use (PEOU), and personal innovativeness in IT(PIIT) on continuance intention to use SED. Additionally, the study highlighted the different mediating roles of the organism (i.e. PEOU, PU, and PIIT) between the stimulus (i.e. information quality, system quality, service information quality, and social influence) and continuance intention. Specifically, information quality and social influence were identified as the two primary antecedent variables influencing continuance intention through the mediating effects of PU and PIIT. This study could help library administrators identify areas of improvement and explore ways to increase the use and relevance of e-reserve services.

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.

Big Data Analytics and Artificial Intelligence (BDA-AI) integration revolutionizes Human-Machine Interaction (HMI) in E-commerce, enhancing user experience, operational efficiency, and decision-making. This study develops a conceptual framework examining technological and environmental factors influencing AI adoption through Flow Experience and Technology Acceptance Model (TAM) integration. It explores how Perceived Vividness (PV), Perceived Enjoyment (PE), and Feedback contribute to Flow Experience, influencing Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Satisfaction, and Continuous Intention. Using systematic literature review, this research identifies theoretical gaps and proposes a model for empirical validation. Findings provide insights for E-commerce developers, businesses, and policymakers to optimize AI-driven interfaces, enhance user engagement, and improve customer retention in Taiwan's digital commerce sector.

The study’s purpose is to investigate the impact of selected factors (Computer self-efficacy (CSE), subjective norms (SN), perceived enjoyment (PE), perceived usefulness (PU), perceived ease of use (PEOU), attitude) on university students’ intention to use e-learning. The objective of this paper is to advance a conceptual framework to better understand the factors that could affect the intention of students to use e-learning in Lebanese universities. The collection of the data was from 444 private universities students in Lebanon. The SEM analysis had been used to assess the influence of these components to intend e-learning system. All proposed relationships are accepted in the framework expected the relationships between Computer self-efficacy (CSE) and subjective norms (SN) on perceived usefulness are rejected. In addition, relationships between subjective norms and perceived enjoyment on perceived ease of use (PEOU) are rejected. Finally, results are discussed then conclusions and future research are presented.

Today, the novel COVID-19 pandemic has taken a significant toll on countries worldwide and impacted the lives and well-being of people across nations. Measures need to be taken to slow down the spread of such viruses, which can be reduced by taking proper precautions to avoid unnecessary contact and incurring hygienic habits. People can become infected by touching infected objects or surfaces, then touching their eyes, nose or mouth. We need proper and hygienic authentication systems for granting access to authorized users at various places such as companies, universities, banks, etc. Today there are multiple biometric systems that can serve this purpose, but to maintain hygiene we need systems that are contactless in nature thus to reduce spread of infections through touch. The palm vein pattern is distinctive biometric identity of individuals that is also a safe and reliable biometric authentication technique. The major advantage of palm vein biometric that we consider in our proposed system is that this kind of authentication can be done in a contactless way. Here, we propose an authentication system that uses palm vein pattern biometric to authenticate users in a contactless way. We have also added the functionalities of temperature detection and blood oxygen level detection to this system. These health symptoms are the major symptoms of various fatal virus infections such as the coronavirus. By checking the users for these symptoms before granting access, we can further limit the spread of infections and also help detect the infected patients. The proposed system does this in a contactless way.

The current study integrated the Extended Technology Acceptance Model (TAM) and included information system quality (ISQ), user interface (UI), knowledge sharing motivation (KSM), the expectation confirmation model (ECM), safety management practices (SMP), interface aesthetics (IA), and perceived value (PV) to evaluate the logistics couriers’ experience while using an Online logistics platform. This research examines the relationships of KSM, SMP, and ISQ on the TAM’s, perceived usefulness (PU), and perceived ease of use (PEOU). In addition, it explores the relationship between UI on PEOU. Furthermore, to explore the impact of ECM, it examines the impact of confirmation (CON) on PU and satisfaction (SAT). Finally, this research explores the impact of logistics couriers’ SAT on continuous intention (CI). According to the findings of this study, UI did not have a significant association with PEOU. Furthermore, KSM was found to significantly impact PEOU, while having no significant effect on PU. Moreover, SMP was found to have no significance on PEOU, however, SMP was discovered to be in a significant association with PU. In addition, ISQ was found to significantly impact PEOU, PU, and, PV. Moreover, CON was in a significant relationship with PU, while not having a significant impact on SAT. Furthermore, IA did not significantly impact PV. Also, SAT was significantly impacted by PU, while not having any significant impact from PEOU, and PV. Besides, PEOU was discovered to significantly impact PU. Finally, SAT was found to be in a significant relationship with CI.

PurposeThe purpose of this paper is to explore the impact of selected factors in adopting mobile-based online payment platforms (MOPP) in three Asian countries: China, India and Bangladesh through the application of Technology Acceptance Model (TAM). The factors considered were: perceived trust (PT), perceived risk (PR), social influence (SI), perceived ease of use (PEU) and perceived usefulness (PU).Design/methodology/approachThe authors purposively selected 1,289 individuals from those three countries who regularly use MOPP as the medium of monetary transactions. The authors utilized SPSS 24 for descriptive statistics and structural equation modeling (SEM) technique through AMOS 24 for testing the hypothesized relationships.FindingsThe authors found that four factors: PT, SI, PEU and PU have significant positive impact on the intention to adopt MOPP whereas PR has insignificant negative impact on the intention to adopt MOPP.Originality/valueAs per the authors' knowledge, this is the first study ever conducted to identify the factors impacting the adoption of MOPP in more than one country. Such an exploratory study can inspire the scholars to initiate further investigations as well as the service providers to extend their service effectiveness according to the users' opinion.

Indians are increasingly using mobile banking (m-banking) services, which shows a growing trend in financial inclusion. A major segment of demography is represented by the housewives but there hasn't been much study done on the consumer category of Indian housewives, especially in terms of how they use technology-driven services like m-banking services. Even more so, their adoption and usage of financial technology has found little space in literature. This research attempts to predict Indian housewives’ intention to adopt m-banking services. An extended Technology Acceptance Model (TAM) is used in this study as the conceptual framework to investigate the effects of independent variables on the behavioral intention (BI) of Indian housewives to adopt m-banking services. These include perceived usefulness (PU), perceived ease of use (PEU), social influence (SI), openness to change (OC), and perceived risk (PR). A survey of Indian housewives using a carefully designed questionnaire was utilized to collect the data for this study. Structural equation modelling (SEM) was employed for the following analysis on a final sample of 269 respondents. The results of the study showed that all considered independent factor had a substantial impact on the dependent factor BI. Notably, among these variables, OC was shown to be the most significant facilitator, closely followed by PEU, both of which had a favourable impact on housewives’ intention to utilie m-banking services. As a key barrier to adoption, PR was found to be the opposite. Since not much work has been done on the factors influencing Indian housewives’ BI to utilize m-banking services, hence this study is one of the initial efforts to investigate the matter. Lastly thorough consideration has been given to the consequences for both theoretical development and real-world implementations.

Aim: Medical training activities have been disrupted in many regions following the outbreak and rapid spread of the coronavirus disease 2019 (COVID-19) across the globe. The most affected areas include organizations’ process of leveraging high-tech medical equipment from abroad to facilitate a practical approach to learning. Also, as countries implemented COVID-19 safety regulations, it became difficult for organizations to conduct face-to-face training. Consequently, non-face-to-face learning methods have been introduced in the medical field to enable instructors to remotely engage with learners. The current research investigated the students' perceptions of the use of metaverse systems in medical training within the medical community of the United Arab Emirates (UAE). Methods: A conceptual model comprising the adoption properties of personal innovativeness, perceived enjoyment, and Technology Acceptance Model concepts was utilised. The current research targeted students in UAE medical universities. Data was obtained by conducting online surveys that were implemented in the winter semester of 2021/2022 between 15th February and 15th May 2022. 500 questionnaires were issued to students following their voluntary participation and 435 questionnaire responses were obtained i.e. an 87% response rate. The research team tested the measurement model employing Structural Equation Modeling using Smart Partial Least Squares Version (3.2.7). Results: Statistically significant associations were confirmed to exist between Personal Innovativeness (PI) influenced by both the Perceived Ease of Use (PEOU), and Perceived Usefulness (PU) (β= 0.456) and (β= 0.563) at P&lt;0.001. The statistically significant associations involving Perceived Enjoyment (EJ) and PEOU and PU (β= 0.554, P&lt;0.05), (β= 0.571, P&lt;0.05) were further confirmed. Additionally, PEOU had a relationship with PU (β= 0.863, P&lt;0.001). Eventually, PEOU and PU significantly influenced the participants’ inclination to use the metaverse technology with (β= 0.745, P&lt;0.001) and (β= 0.416, P&lt;0.001), respectively.

This paper examines mathematics teachers’ level of acceptance and intention to use the Augmented Reality Geometry Tutorial System (ARGTS), a mobile Augmented Reality (AR) application developed to enhance students’ 3D geometric thinking skills. ARGTS was shared with mathematics teachers, who were then surveyed using the Technology Acceptance Model (TAM) to understand their acceptance of the technology. We also examined the external variables of Anxiety, Social Norms and Satisfaction. The effect of the teacher’s gender, degree of graduate status and number of years of teaching experience on the subscales of the TAM model were examined. We found that the Perceived Ease of Use (PEU) had a direct effect on the Perceived Usefulness (PU) in accordance with the Technology Acceptance Model (TAM). Both variables together affect Satisfaction (SF), however PEU had no direct effect on Attitude (AT). In addition, while Social Norms (SN) had a direct effect on PU and PEU, there was no direct effect on Behavioural Intention (BI). Anxiety (ANX) had a direct effect on PEU, but no effect on PU and SF. While there was a direct effect of SF on PEU, no direct effect was found on BI. We explain how the results of this study could help improve the understanding of AR acceptance by teachers and provide important guidelines for AR researchers, developers and practitioners.