This research investigated factors influencing Jordanian academics' intention to use virtual reality (VR) technology in higher-education institutions. Recognizing VR's transformative potential in education, the study integrated the unified theory of acceptance and use of technology with protection motivation theory to develop a comprehensive theoretical framework for VR adoption. An online survey collected data from Jordanian academics, analyzed using structural equation modeling. Findings revealed that threat appraisals, telepresence, effort expectancy, social influence, and facilitating conditions positively impacted academics' intention to use VR. Conversely, performance expectancy showed no correlation with VR usage intention within higher-education institutions. These results offered valuable insights into the conditions that both facilitate and hinder VR implementation in higher education, providing practical recommendations for institutions aiming for effective VR technology application in their educational practices.

The use of technology in education has rapidly developed, particularly in assessment methods. This study aims to analyze the acceptance of Quizizz in learning by applying the Technology Acceptance Model (TAM) and the Intrinsic Motivation Inventory (IMI) approaches. Data were collected from 222 respondents at SMPN 3 Susukan who actively used Quizizz and were analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. The analysis results show that in the TAM model, Attitude Toward Using (AM) had the strongest influence on Behavioral Intention (BI) (β = 0.744; p < 0.001), while Self-Efficacy (SE) and Technology Facilitating Conditions (TF) significantly influenced Perceived Ease of Use (PEU). However, Perceived Usefulness (PU) and PEU did not have a significant effect on BI. Meanwhile, the IMI model showed that intrinsic motivation has not formed a strong structural pattern in explaining technology acceptance. The study concludes that cognitive-perceptual factors are more dominant than affective-motivational factors in influencing acceptance.

This study aims to analyzes electric vehicle (EV) adoption in Palembang, Indonesia by extending the Technology Acceptance Model (TAM) with environmental concern and government support. EV adoption is increasingly important as cities seek to reduce transport emissions, but growing urban areas still face practical and behavioral barriers. A quantitative survey of 300 EV users in Palembang was conducted through an online questionnaire capturing daily experience, perceived benefits, ease of use, and views on government support. Data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM). The findings show that perceived usefulness and perceived ease of use have positive and significant effects on EV adoption. Perceived ease of use also has a positive and significant effect on attitude, and attitude further supports adoption. Environmental concern and government support likewise have positive and significant effects, indicating that care for the environment and supportive policies and infrastructure strengthen users’ decisions. Overall, the results suggest that EV adoption is shaped by both technology perceptions and wider policy support. These findings imply that faster EV uptake in Palembang can be supported by improving usability and charging convenience, communicating clear benefits, and expanding incentives, charging facilities, and consistent public information to reduce uncertainty and encourage wider adoption locally.

Purpose In the rapidly evolving landscape of online travel agencies (OTAs), the integration of AI-powered chatbots represents a transformative innovation that has fundamentally changed how travelers interact with services. These intelligent virtual assistants provide real-time support, personalized recommendations and instant solutions, effectively addressing the diverse needs of users. This study aims to investigate the factors that influence both the adoption and continued use of chatbots by OTA customers. To achieve this, authors propose an integrated conceptual framework that combines the Technology Acceptance Model (TAM), the Expectation–Confirmation Model (ECM) and the Information Systems Success (ISS) model, providing a comprehensive understanding of user acceptance, satisfaction and system effectiveness in the context of chatbots. Design/methodology/approach This study uses a multi-method approach (qualitative and quantitative) to examine the interaction between individuals and chatbots in OTAs. In-depth, semi-structured interviews were used to gather data, which was then analyzed using a grounded theory methodology. Subsequently, quantitative hypotheses are formulated based on the findings of the qualitative inquiry. The study sample comprised 445 customers who were familiar with and had prior experience using travel AI chatbots. The research model was tested using Partial Least Squares structural equation modeling and artificial neural networks (ANNs). Findings The study’s findings reveal that all examined factors significantly influence user satisfaction, which in turn drives the continued usage of chatbots; however, the moderating effects of self-representation and intimacy were found to be insignificant. Originality/value This study makes a methodological contribution by using a rigorous mixed-method approach that combines qualitative interviews, a quantitative survey and advanced ANN analysis. This comprehensive design enables a nuanced understanding of the factors influencing customer satisfaction and the continued use of AI-powered chatbots in OTAs. Theoretically, the study advances knowledge by integrating the TAM, ECM and ISS model into a unified framework. The findings contribute to these models by demonstrating how their constructs interact and adapt specifically within the domain of chatbot-enabled services in emerging tourism markets, such as India, thereby offering both conceptual synthesis and domain-specific insights.

Oral disease remains a global public health concern, disproportionately affecting socioeconomically disadvantaged populations. Adults with disabilities or health conditions face additional barriers to dental care, including physical accessibility, communication challenges, and heightened anxiety. These factors contribute to care avoidance and poorer oral health outcomes. While virtual reality (VR) has shown promise in reducing procedural anxiety in pediatric and private dental settings, its application in adult public dentistry, particularly for people with disabilities, remains underexplored. This study aims to evaluate the feasibility, usability, and acceptability of Smileyscope, a Therapeutic Goods Administration-approved head-mounted VR headset, in reducing dental anxiety and enhancing care experiences for adults with disabilities in public dental clinics. A mixed methods convergent design will be implemented across community dental sites in Victoria, Australia. In total, 50 adult patients and up to 10 dental staff members will be recruited. Primary feasibility indicators include recruitment rate (≥60% consent), completion rate (≥80% System Usability Scale [SUS] completion), and usability threshold (mean SUS ≥68). The primary analysis will be descriptive, with 95% CIs reported. Quantitative data will be collected using the visual analog scale for willingness, the SUS, and the technology acceptance model questionnaire. Qualitative data from semistructured interviews will be thematically analyzed. The study is co-designed with a disability advocate and integrates lived experience throughout all phases, including recruitment, evaluation, and dissemination. The project was funded in 2025, and ethics approval was granted by Peninsula Health Human Research Ethics Committee (project ID 117565). Data collection is scheduled for October 2025 to March 2026 at the participating community dental sites. Primary feasibility estimates and qualitative themes are expected to be submitted for publication in mid‑2026. This protocol outlines a feasibility study that will inform scalable models for VR integration into public dental services. The findings will contribute to improved oral health equity and patient-centered care, advancing the evidence base for inclusive digital health innovation in dentistry. PRR1-10.2196/85916.

This study aims to identify the factors affecting the intention to adapt mobile learning and the relationship between identified factors and mobile learning (m-learning) among school students in the Eastern Province, Sri Lanka. With the consideration of constructs such as performance expectancy, effort expectancy, perceived playfulness, social influence, and perceived usefulness, the survey was done among 150 Advanced Level school students in the Eastern Province, Sri Lanka. The model of the study was evaluated using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Smart PLS was used for measurement model testing and structural model testing. The results showed factors such as performance expectancy, effort expectancy, and social influence have positive and significant influence on the perceived level of intention to use m-learning. Unexpectedly, the results also showed that factors such as perceived usefulness and perceived playfulness do not have a positive and significant influence on the perceived level of intention to use m-learning. The findings of the study provide information to educational institutions such as schools on factors that they should concentrate on when improving the use of m-learning. The study did not examine the m-learning intention among the school students from other grades, other schools as well as other districts. Therefore, it is suggested to consider school students with various geographical locations for future research.

This study examines how Grammarly AI helps students improve their writing and avoid plagiarism in digital learning. As more academic work is done online, students need quick and clear feedback to guide their revisions. This research focuses on students’ perceptions of Grammarly and how they respond to its feedback. A survey was conducted with 30 university students using Likert scale and open-ended questions. The results show that most students find Grammarly helpful for correcting grammar, improving clarity, and motivating them to revise their writing. Students also reported that the paraphrasing and similarity checking features help them maintain originality and understand academic integrity better. These findings are supported by the Technology Acceptance Model (TAM), which explains that students respond positively when a tool is useful and easy to use, and by feedback theory, which highlights how learners process corrective input. Overall, this study concludes that Grammarly functions not only as an error-correction tool but also as a learning support system that strengthens writing skills and promotes responsible writing practices in digital environments.

The proposed study explores the determinants of e-learning use in Pakistan during COVID-19 and examines the mediating effects of Perceived Usefulness (PU) and Perceived Ease of Use (PEOU). Also based on the prolonged Technology Acceptance Model (TAM), the study adds external variables of other significant theories, such as Cost, System Quality, and Complexity. A total of 461 students were sampled from major Pakistani universities using a structured questionnaire. Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to analyse the data using SmartPLS software. The results demonstrate that PU and PEOU are essential mediators between several external variables and Behavioural Intention (BI). In particular, PEOU completely mediates the relationship between Application Complexity and PU and partially mediates the effects of Facilitating Conditions and COVID-19 on PU. Furthermore, PU mediates the relationships between Social Influence, PEOU, and BI. Moreover, PU mediates between Social Influence, PEOU, and BI. This research validates the essential mediating processes of the TAM model and provides valuable information for stakeholders interested in improving e-learning adoption during the crisis.

This study proposes a theoretically grounded conceptual framework to enhance student engagement in virtual engineering laboratories. The framework is validated through expert review rather than empirical testing. To address the challenges of online and blended learning environments, the model integrates two established theories: the extended Technology Acceptance Model (TAM2) and Self-Determination Theory (SDT). TAM2 captures extrinsic motivational factors, including perceived usefulness and ease of use, while SDT focuses on intrinsic psychological needs, particularly autonomy and competence. This paper presents an initial theoretical model that has been validated by experts and is intended to precede future empirical testing with students. Expert validation was conducted using a mixed-methods approach involving eight specialists in engineering education and educational technology. Quantitative evaluation employed the content validity ratio (CVR) and item-level content validity index (I-CVI), while qualitative feedback was analyzed using inductive thematic coding. The results showed strong agreement among experts on key components such as system usability, learner engagement, and feedback processes. However, some conceptual overlap was identified between the gamification and enjoyment constructs, suggesting the need for further clarification. The validated framework provides a foundation for future empirical studies to examine the proposed relationships among its constructs. By linking pedagogical design with digital system features, the framework contributes to a deeper understanding of student motivation and engagement in virtual engineering learning environments.

The rapid increase of ride-hailing services has revolutionized urban mobility in India, but its adoption in medium-sized cities with distinct socioeconomic contexts remains unexplored. This study uses the technology acceptance model and the theory of planned behavior to investigate the factors that influence ride-hailing uptake in Vijayawada, a rapidly urbanizing medium-sized city in India. Data from 450 users were analyzed using structural equation modeling. The findings support the fundamental role of perceived usefulness in influencing attitude and behavioral intention. While social influence encourages adoption, one important finding is the negative impact of perceived behavioral control, which reflects hurdles such as cost, app complexity, and inadequate peripheral coverage. The impact of these elements is mitigated by gender and income, with women and higher-income users having lower adoption intentions. The findings highlight the need for localized initiatives—such as simplified app interfaces, increased safety features, and greater service equity—to be initiated by service providers and policymakers targeting growing urban markets.

This study examines drivers’ acceptance of the cooperation vehicle–infrastructure system (CVIS) by comparing an extended technology acceptance model (TAM) and an extended unified theory of acceptance and use of technology (UTAUT). CVIS-specific interaction factors, including information service quality, display service quality, perceived distraction, and trust, are incorporated into both models. Survey data from 392 drivers are analyzed using structural equation modeling. Results indicate that both models demonstrate satisfactory fit and explanatory power, with the extended UTAUT outperforming the extended TAM. Performance expectancy, effort expectancy, social influence, information service quality, and trust positively influence intention to use CVIS, whereas perceived distraction has a negative effect. Trust is the strongest predictor. The study further identifies significant moderating effects of age, gender, and prior experience on these relationships, providing crucial insights for the design and implementation of CVIS technologies.

The widespread adoption of solar energy storage systems is transforming the global energy landscape, enabling more efficient use of renewable resources and enhancing energy resilience. The integration of residential batteries significantly enhances energy efficiency and sustainability by facilitating the storage of surplus renewable energy, providing reliable backup during power outages, and optimising energy consumption. This study explores the factors influencing end-user adoption of batteries, utilising the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) as a guiding framework to analyse adoption behaviours and determinants. This study employs a qualitative approach using semi-structured interviews with stakeholders divided into three categories: regulatory authorities, industry experts, and end-users. This study highlights key factors influencing battery adoption, such as energy independence, grid reliability, and environmental impact, while addressing challenges like regulatory inconsistencies and installer training. Study extends UTAUT2 to residential battery adoption, emphasising performance expectancy, facilitating conditions, and price value in decision-making and makes a methodological contribution by validating deeper qualitative insights into renewable technology adoption. The practical implications emphasise the need for designing targeted policies, such as subsidies and net metering, alongside developing user-centric systems that enhance affordability, usability, and consumer awareness to facilitate residential battery adoption.

The literature review offers a focused synthesis of prior studies on the use of digital platforms in e government and their implications for public access transparency and administrative efficiency. Existing research is critically assessed to support the adoption of a multi level theoretical perspective that integrates technology acceptance models institutional theory diffusion of innovation and socio technical systems theory. This perspective frames digital adoption as a complex process shaped by institutional and social dynamics rather than a purely technical change. The review identifies key drivers of effective e government implementation including inclusive communication strategies technological capacity and political support. At the same time it highlights persistent constraints such as digital divides outdated institutional practices fragmented legal jurisdictions low levels of public trust and weak system design. The analysis demonstrates that digitalization often produces uneven outcomes. Access tends to improve mainly for groups that are already digitally connected while transparency initiatives may result in limited accountability. Efficiency gains are frequently confined to isolated administrative units without broader organizational transformation. Overall the review concludes that achieving integrated improvements in access transparency and efficiency is a challenging socio technical and political process influenced by contextual variation and uneven institutional maturity. It also identifies research gaps related to long term impacts artificial intelligence governance context specific implementation pathways and new measures of public value.

This study examines the adoption challenges of FIFA Connect within Moroccan women's football clubs with an aim of defining the factors that determine the use of technology as mandatory in structurally-dependent organizations. With Morocco on the verge of co-hosting the 2030 FIFA world cup, it is even more important to understand the barriers in digital transformation. The study fills an obvious gap in the literature related to sports management by questioning technology acceptance among structurally-dependent women-based entities in which structure is dominated by male parent clubs. Mixed-methods design was used which combined quantitative survey data of 21 administrative staff members in all National Women’s Football League (LNFF) clubs with the qualitative thematic analysis of open-ended responses which were processed using the Tropes software. The study conceptualized the DeLone and McLean Information Systems Success Model through validated constructs of system quality, the quality of information, service quality, user satisfaction, and net benefits. The adoption determinants were analyzed using descriptive statistics, whereas qualitative coding was used to determine emergent patterns of challenges. The non-parametric methods were used due to the small sample size and non-normality. The quantitative analysis showed that Information Quality was the most decisive success factor (mean=4,0/5), and System Quality was the least rated (2,9/5) which is a critical performance issue. The most important predictor of User Satisfaction was Service Quality (β = 0,816, R2 =0,666). Qualitative analysis identified three primary challenges: structural dependency on men's clubs, inadequate training provision, and technical support limitations. There was also an interesting Paradox of System Quality in which administrators ensured high rates of utilization despite technical performance. The convergence of the methodology shows that the technology adoption experiences in the women sports organizations are inherently based on governance structures. The results indicate that successful digital change in women football requires context-sensitive implementation strategies that can handle structural dependencies and ensure that information quality is guaranteed. When implementing mandatory technologies, sports federations are recommended to develop gender-sensitive solutions and introduce special support systems of dependent women sections.

Purpose This study aims to synthesize meta-analytic research in the banking sector by mapping thematic clusters and identifying theoretical and methodological patterns. It highlights how meta-analyses contribute to understanding heterogeneity across banking contexts. Design/methodology/approach A systematic literature review was conducted across seven academic databases using targeted search terms. Four thematic clusters were identified: technology adoption, consumer trust and satisfaction, behavioral aspects and digital financial innovation. Findings The analysis revealed theoretical convergence in some domains (e.g., technology acceptance model in technology adoption) and fragmentation in others (e.g., behavioral aspects). Some clusters (e.g., technology adoption) show more methodological maturity, while others (e.g., behavioral) require further development. Moderator analysis and sample size variation indicate the need for more balanced and standardized designs. Contextual moderators such as culture, regulation and infrastructure significantly impact effect sizes. Research limitations/implications There may be publication bias due to the exclusion of gray literature and non-significant results. Clustering may oversimplify overlapping constructs between domains. Future research should integrate longitudinal, qualitative and interdisciplinary designs. Practical implications Banks should prioritize trust, transparency and user-centric innovation to enhance consumer engagement. Policymakers must design context-sensitive regulation to support both inclusion and innovation. Financial education and CSR strategies are crucial for strengthening long-term brand trust. Originality/value To the best of the authors’ knowledge, this is the first structured meta-review focused on banking marketing meta-analyses. It offers a comparative evaluation of theoretical frameworks, methodologies and moderator applications. The study contributes a novel cluster-based framework to map research maturity and heterogeneity.

ABSTRACT The field of education has witnessed a rapid expansion in the utilization of Artificial Intelligence (AI) technologies, fundamentally transforming classroom instruction. Thus, it is critical for pre-service teachers to implement AI-powered technology in their future teaching. This study was conducted in six higher education institutions (HEIs) in China and is grounded in resource-based theory, the technology acceptance model (TAM), and relevant literature. SmartPLS 4.0 was utilized to develop a partial least squares structural equation model (PLS-SEM) to examine the relationships among AI capability (AIC), creativity, self-efficacy, Technological Pedagogical Content Knowledge (TPACK), and pre-service teachers’ behavioural intentions towards AI-assisted teaching. The findings indicated that HEIs’ AIC is a significant predictor of pre-service teachers’ behavioural intentions towards designing AI-assisted teaching. It also predicts their creativity, self-efficacy, and TPACK. Furthermore, creativity, self-efficacy, and TPACK were found to mediate the relationships between HEIs’ AIC and pre-service teachers’ behavioural intentions. These findings suggest that HEIs should support the development of pre-service teachers by enhancing AIC, including resources (data and technology) and awareness (reform and innovation), providing insights into AI integration in higher education within the Asia-Pacific context.

Purposes The study investigated the intention of account executives from Small and Medium Enterprises (SMEs) to employ artificial intelligence at their workplace. This study will examine the Unified Theory of Acceptance and Use of Technology (UTAUT), as well as technological and personal characteristics, and the role of SME account executives in adopting artificial intelligence. This study addresses the knowledge gaps in SME account executives’ understanding of artificial intelligence. Methodology employed an online questionnaire distributed in collaboration with SMEs in Malaysia to gather responses from 273 account executives who work in SMEs. The data were analyzed using PLS-SEM and Artificial Neural Networks (ANN) to investigate SME account executives’ intentions to employ artificial intelligence. The demographic information of the individuals was analyzed using SPSS software. Results The study’s findings revealed positive and significant relationships between performance expectancy, effort expectancy, social influence, facilitating conditions, system quality, employee awareness, and personal innovativeness toward artificial intelligence. Insignificant relationships were found between time-saving features and technological self-efficacy, and a negative, significant relationship existed with internet technology (IT) features toward artificial intelligence. Limitation The cross-sectional approach focuses on SMEs in Malaysia, where the study’s applicability to other industries and countries is limited due to changes in the cultural, economic, and regulatory environment. Because participants may give socially acceptable answers rather than honest ones, using self-reported data raises the possibility of bias. Because inquiry assumes a certain level of knowledge with AI technology, respondents’ varying levels of digital competency may influence the findings. Practical implication The findings of this study can help SMEs adopt artificial intelligence for their operations, particularly in accounting departments. Collaboration among organizations can help improve employee motivation to increase intention to use artificial intelligence. Originality/value This study uses the Unified Theory of Acceptance and Use of Technology (UTAUT), technical qualities, and individual traits.

The implementation of Management Information Systems (MIS) in education in Indonesia has not been fully optimized, despite being supported by various educational digitalization policies. One key factor in the success of MIS implementation is user acceptance, particularly from teachers, education personnel, and school leaders. This study aims to systematically examine the factors influencing user acceptance of MIS in education in Indonesia using a Systematic Literature Review (SLR) approach. The SLR method was conducted by reviewing 25 national scientific articles obtained from the Garuda Portal with publication years ranging from 2015 to 2024. The Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) were used as the primary analytical frameworks. The results indicate that perceived usefulness, perceived ease of use, performance expectancy, and facilitating conditions are the dominant factors influencing the acceptance of MIS in education. The implications of this research are expected to form the basis for developing user-oriented policies and strategies for implementing MIS in education.

Individuals with eating disorders (EDs) often face significant barriers to accessing care, including prolonged waitlists and systemic delays. Digital interventions, such as mobile apps, offer a scalable way to enhance pre-treatment engagement during this high-risk period. This pilot study evaluated the feasibility and acceptability of MI-Coach: ED, a program-led mobile app designed to support motivation among female-identifying individuals awaiting ED treatment. Twenty-three female-identifying individuals on waitlists at ED clinics across British Columbia, Canada, participated in a 4-week single-arm pilot trial of MI-Coach: ED. The app delivered motivational interviewing-informed content through seven sequential modules containing reflective exercises, psychoeducational articles, and psychologist-led videos. Feasibility was assessed via service-provider uptake, participant enrollment, engagement, and retention metrics. Acceptability was measured using the user version of the Mobile App Rating Scale and adapted Technology Acceptance Model ratings. Exploratory analyses descriptively examined pre-to-post changes in motivation and related symptoms. Feasibility was constrained at the service-provider level, with 6% of contacted sites agreeing to distribute study materials. At the participant level, 67.6% initiated app use and 44% completed at least four modules, and 78% completed pre- and post-assessments, indicating partial engagement across the sample. Participants rated the app positively across domains of quality, ease of use, and perceived usefulness. Small-to-medium reductions in global ED severity and depressive symptoms, as well as increases in motivational confidence, were observed with confidence intervals that did not cross zero. Change scores were moderately correlated across select motivational and symptom measures. Findings suggest that MI-Coach: ED was acceptable among users who engaged, while feasibility was substantially influenced by system-level recruitment constraints and variable participant engagement. Observed engagement patterns were lower than those reported for general mental health apps but consistent with prior digital ED intervention literature, underscoring the importance of disorder-specific feasibility benchmarks. Results will inform ongoing refinements and implementation strategies for a future randomized trial.

Adoption of IoT-Based Smart Campuses Based on an Extended Technology Acceptance Model: The Mediating Role of Behavior Intention