Search Results (60)

The primary objective of this study is to examine factors that influence Mobile Learning adoption and effectiveness in the case of higher education, underpinned by the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model. The study was conducted at some of the top Saudi universities. A survey method was used in this study, and the questionnaire includes 12 factors, which include enjoyment, hedonic motivation, and performance expectancy, among others, whose relationships with behavioral intention towards using m-learning and in turn, its actual use, were investigated. Additionally, two mediating factors, namely technostress and exhaustion, were included to examine the effects of students’ engagement with m-learning. The questionnaire was distributed to 500 undergraduate students, and 264 replied. Based on the findings, the traditional UTAUT2 factors had significant effects on students’ intention and use behaviors, which were mediated by technostress and exhaustion. The findings indicated that the effective management of mediators is important to improve student engagement in m-learning and that m-learning strategies can be developed through the information provided. This study validated the UTAUT2 model in the case of m-learning, with a 70% success rate in predicting IT adoption, which exceeded other models. Through the study findings, educators and policymakers can find ways to optimize m-learning platforms. Furthermore, it is recommended that focus is placed on the long-term effects of technostress and exhaustion on the students’ adoption of and engagement with m-learning. Full article

Background: Chronic obstructive pulmonary disease (COPD) increasingly strains European health systems amid population ageing. Digital health interventions (DHIs) can reduce hospitalizations and support self-management, yet older patients hesitate to adopt them. Tailored interventions require understanding patient profiles. This study aimed to identify clusters by intention to use DHIs. Methods: Between July 2024 and February 2025, 232 COPD patients (mean age 65; 61% female) across seven European countries completed surveys covering sociodemographic and Unified Theory of Technology Acceptance (UTAUT) constructs. Intention to use DHIs was categorized as positive, neutral, or negative. Weighted UTAUT scores were clustered using Gower distance and Partitioning Around Medoids. Associations were visualized with multiple correspondence analysis and heat maps; differences were tested with the chi-square test. Results: Intention to adopt DHIs varied across countries, with the highest in the Netherlands. Two clusters emerged. Cluster 1, the ‘balanced hesitant’ group (n = 104), showed mixed intentions (38% positive, 40% neutral, 21% negative). Barriers included low performance expectancy and limited digital skills (both p < 0.05). Cluster 2, the ‘enthusiastic’ group (n = 128), demonstrated strong adoption intentions, with 84% positive intention. Enablers included low effort expectancy and complex disease (p < 0.01). Across both clusters, performance expectancy predicted intention. Conclusions: Digital health adoption among COPD patients is shaped by psychosocial and digital skill profiles. Hesitant users benefit from expectation-based information about DHIs, digital literacy training and peer support. Enthusiasts require ease of integration. Performance expectancy is a consistent driver of adoption, whereas country-specific factors should guide strategies. Full article

This study analyses the integration of Generative Artificial Intelligence (GenAI) in agro-environmental higher education in Ecuador, focusing on its contribution to sustainable digital transformation aligned with Sustainable Development Goals (SDGs) 4 and 9. The research was conducted at the Faculty of Agricultural and Environmental Engineering (FICAYA) of Universidad Técnica del Norte (UTN) using a quantitative, cross-sectional, and analytical design. A validated digital survey grounded in established technology-acceptance frameworks—the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) was administered to 94% of the student population, showing satisfactory internal consistency (Cronbach’s α = 0.87). Data was analysed using descriptive statistics and multivariate techniques, including Principal Component Analysis (PCA) and k-means clustering. The results obtained in Microsoft Forms^® indicate that ChatGPT-5 is the most widely used GenAI tool (54.2%), followed by Gemini (11.9%). Students reported perceived improvements in academic performance (62.5%), conceptual understanding (74.6%), and task efficiency (69.1%). PCA explained 67% of the total variance, identifying three latent dimensions: effectiveness and satisfaction, institutional access and support, and ethical concerns versus operational benefits. Furthermore, k-means clustering (k = 2) segmented users into two distinct profiles Integrators, characterised by frequent use and positive perceptions, and Cautious Users, exhibiting lower usage and greater ethical or technical concerns. Overall, the findings highlight GenAI as a catalyst for sustainable education and underline the need for institutional and ethical frameworks to support its responsible integration in Latin American universities. Full article

This paper reports a study conducting an in-depth analysis of the impacts of ethical training on the adoption of AI tools among computer science students in higher vocational colleges. These students will serve as the pivotal human factor for advancing the field of AI. Aiming to explore practical models for integrating AI ethics into computer science education, the research seeks to promote more responsible and effective AI application and therefore become a positive influence in the field. Employing a mixed-methods approach, the study included 105 students aged 20–24 from a vocational college in Guangdong Province, a developed region in China. Based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model, a five-point Likert scale was used to evaluate the participants’ perceptions of AI tool usage based on ethical principles. The Structural Equation Modeling (SEM) results indicate that while participants are motivated to adopt AI technologies in certain aspects, performance expectancy negatively impacts their intention and actual usage. After systematically studying and understanding AI ethics, participants attribute a high proportion of responsibility (84.89%) to objective factors and prioritized safety (27.11%) among eight ethical principles. Statistical analysis shows that habit (β = 0.478, p < 0.001) and hedonic motivation (β = 0.239, p = 0.004) significantly influence behavioral intention. Additionally, social influence (β = 0.234, p = 0.008) affects use behavior. Findings regarding factors that influence AI usage can inform a strategic framework for the integration of ethical instruction in AI applications. These findings have significant implications for curriculum design, policy formulation, and the establishment of ethical guidelines for AI deployment in higher educational contexts. Full article

Cultural heritage tourism is a vital part of Malaysia’s tourism sector, attracting visitors to iconic UNESCO sites like George Town and Melaka. However, these heritage sites face growing challenges from overcrowding and environmental degradation, which accelerate the deterioration of historic architecture and cultural artifacts. Preservation efforts often require site closures, which negatively impact tourist experiences and satisfaction. Thus, augmented reality (AR) offers a solution by supporting heritage management and preservation, allowing visitors to engage with virtual representations via mobile AR apps, thereby enhancing visitor engagement and travel experience. Despite global adoption, mobile AR apps often suffer from low user retention, with many users abandoning them shortly after downloading them. Understanding what drives continued usage is crucial for successful AR implementation. This study integrates the expectation confirmation model (ECM) and the unified theory of acceptance and use of technology 2 (UTAUT2) to examine the determinants affecting user’s experiential satisfaction and continued usage intention of mobile AR apps. An online survey of 450 domestic tourists in George Town and Melaka was conducted. Data analysis using structural equation modeling with SmartPLS 4.0 revealed that the integrated model offers a stronger predictive power and significantly outperforms ECM and UTAUT2 individually. The findings contribute valuable insights for researchers, app developers, tourism stakeholders, and policymakers. Full article

The rise of financial technology (FinTech) has generated substantial research on its adoption by customers and the associated implications for traditional banks. This systematic review addresses two questions: (1) What factors enable or hinder consumer adoption of FinTech? (2) How does consumer adoption of FinTech affect the performance of traditional banks? Following the PRISMA guidelines, we screened and analyzed 109 peer-reviewed articles published between 2016 and 2024 in Scopus and Web of Science. The findings show that adoption is driven by economic incentives, digital infrastructure, personalized services, and institutional support, while barriers include limited literacy, perceived risk, and regulatory uncertainty. At the bank level, adoption enhances operational efficiency, customer loyalty, and revenue growth but also generates compliance costs, cybersecurity risks, and competition. Consumer adoption studies primarily employ the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), often extended with trust and privacy constructs. In contrast, bank performance research relies on empirical analyses with limited theoretical grounding. This review bridges behavioral and institutional perspectives by linking consumer-level drivers of adoption with organizational outcomes, offering an integrated conceptual framework. The limitations include a restriction of the retrieved literature to English publications in two databases. Future work should apply longitudinal, multi-theory models to deepen the understanding of how consumer behavior shapes bank performance. Full article

We explored the adoption of virtual try-on (VTO) technology in Taiwan’s fashion retail sector, which has gained prominence as consumer behavior online has changed since the COVID-19 pandemic. Using an extended unified theory of acceptance and use of technology 2 (UTAUT2) model, we examined the behavioral intentions and actual usage of VTO. The original framework of the UTAUT2 model was modified by excluding experience and incorporating personality traits as moderating variables. Based on 257 valid survey responses analyzed using SmartPLS 4.1, influencing factors were identified, revealing that gender was a significant moderator in VTO adoption. Full article

(1) Background: Mobile populations living in disadvantaged circumstances often face disrupted continuity of care due to incomplete or inaccessible health records. This feasibility study explored the perceived usefulness of Electronic Personal Health Records (EPHRs) in enhancing access to and continuity of care for mobile populations across Denmark, Ghana, Kenya, and The Netherlands. (2) Methods: A qualitative study using ninety semi-structured interviews, with multi-level stakeholders ranging from policymakers to mobile individuals, recruited through purposive and convenience sampling. Interview guides and analysis were informed by the Technology Acceptance Model (TAM), and analysis by the Unified Theory of Acceptance and Use of Technology (UTAUT). (3) Results: Stakeholders highlighted the value of improved medical data sharing and ownership and considered EPHRs promising for enhancing care continuity and efficiency. Key concerns included limited digital and health literacy, and data security and privacy, underscoring the need for education and safeguards against inappropriate data sharing. Due to differences in digital readiness and privacy guidelines, a one-size-fits-all EPHR is unlikely to succeed. (4) Conclusions: EPHRs are considered valuable tools to enhance care continuity and increase patient ownership, but they face technical, structural, and social challenges, including data security and varying levels of digital (health) literacy. Successful implementation requires context-sensitive, co-created solutions supported by strong policy frameworks. Full article

Background: Rapid urbanization has intensified the challenges of freight transport, particularly in last-mile (LM) delivery, leading to rising costs and environmental externalities. Autonomous vehicles (AVs) have emerged as a promising innovation to address these issues. While much of the existing literature emphasizes business and operational perspectives, this study focuses on the acceptance of AVs from the standpoint of e-consumers—individuals who make purchases via digital platforms—in an emerging market context. Methods: Grounded in an extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), which is specifically suited to consumer-focused technology adoption research, this study incorporates five constructs tailored to AV adoption. Structural Equation Modeling (SEM) was applied to survey data collected from 304 e-consumers in Northeast Brazil. Results: The findings reveal that performance expectancy, hedonic motivation, and environmental awareness exert significant positive effects on acceptance and intention to use AVs for LM delivery. Social influence shows a weaker, yet still positive, impact. Importantly, price sensitivity exhibits a minimal effect, suggesting that while consumers are generally cost-conscious, perceived value may outweigh price concerns in early adoption stages. Conclusions: These results offer valuable insights for policymakers and logistics providers aiming to implement consumer-oriented, cost-effective AV solutions in LM delivery, particularly in emerging economies. The findings emphasize the need for strategies that highlight the practical, emotional, and environmental benefits of AVs to foster market acceptance. Full article

The rapid development of generative artificial intelligence (AI) systems such as ChatGPT (GPT-4) could transform teaching and learning. Yet, integrating these tools requires insight into what drives students to adopt them. Research on ChatGPT acceptance has so far focused on university settings, leaving school contexts underexplored. This study addresses the gap by surveying 506 upper secondary students in Baden-Württemberg, Germany, using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Performance expectancy, habit and hedonic motivation emerged as strong predictors of behavioral intention to use ChatGPT for school purposes. Adding personality traits and personal values such as conscientiousness or preference for challenge raised the model’s explanatory power only marginally. The findings suggest that students’ readiness to employ ChatGPT reflects the anticipated learning benefits and enjoyment rather than the avoidance of effort. The original UTAUT2 is therefore sufficient to explain students’ acceptance of ChatGPT in school contexts. The results could inform educators and policy makers aiming to foster the reflective and effective use of generative AI in instruction. Full article

With the rapid development of digital technology, the use of digital learning resources has become increasingly widespread and is now an integral part of higher education. However, there is a lack of research on engineering students’ behavioral intention to use digital resources and their digital literacy. This study, which is based on two waves of longitudinal survey data from 422 Chinese engineering students, employs the unified theory of acceptance and use of technology 2 (UTAUT2) model to systematically analyze the factors influencing engineering students’ behavioral intention to use digital learning resources and explore the longitudinal relationship between this intention and digital literacy. The results show that engineering students’ behavioral intention to use digital learning resources positively predicts their digital literacy. Effort expectancy, social influence, facilitating conditions, hedonic motivation, and habit are positively related to engineering students’ behavioral intention, whereas performance expectancy and price value do not have significant effects. The findings extend the application of the UTAUT2 model in the context of digital education and reveal a longitudinal link between the use of digital learning resources and digital literacy. This provides theoretical support and practical guidance for optimizing digital learning environments, enhancing digital literacy in engineering students, and improving the design of teaching resources in higher education, contributing to the development of engineering education in China in the digital age. Full article

The article analyzes food rescue application reviews from around the world. The analysis was conducted using text mining methods, including LDA, which we used to extract the main topics in user-generated discussions of the applications. It identified eight main themes in user feedback on food rescue applications: (1) Application setup, features and general user experience, (2) User satisfaction and feedback, (3) Product management and organization, (4) Convenience, ease of use and time management, (5) Recipe discovery, product utilization and meal ideas, (6) Application updates and technical support, (7) Sustainability and environmental impact, and (8) Social interaction and sharing. All of them are indirectly related to factors derived from the unified theory of acceptance and use of technology (UTAUT). Our study aligns with a research trend concerning how digital technologies can support sustainable food consumption. Full article

Recent studies have increasingly focused on using virtual reality (VR) exercise video games (exergames) to boost motivation for physical activity among the elderly. However, there is little discussion about the factors influencing the performance and effort expectancy of immersive exergames in older adults. The study was based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model. UTAUT model was tested and extended by investigating two predicted factors—Physical Safety (PPS) and Physical Postures (PP)—of immersive exergames among older adults. PP, PPS, Performance Expectancy (PE), and Effort Expectancy (EE) relationships were analyzed. In this study, 40 healthy older adults were divided into 2 groups to play an immersive exergame for at least 5 min, either sitting or standing. Then, a list of measurement items based on the extended UTAUT model was completed by one-on-one interviews. The t-test results showed that PP was significantly correlated with PPS (t = −6.598, p < 0.001) and PE (t = 6.465, p < 0.001). The path analysis showed that PPS as a negative correlation was verified as a factor of PE (β = −0.438, p < 0.01). Both PP and PPS had no significant effect on EE. Overall, valuable insights and theoretical guidelines for older adults accepting immersive exergames are supported in this study. Full article

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. Full article

Digital transformation is a crucial option for nightscape tour to balance high-quality experiences and sustainable development in the new era. Tourists’ satisfaction and continuance intention are essential to the development of digital nightscape tour, but related research is insufficient. For this reason, by using the Chinese digital nightscape tour as a case study, this research integrates the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and the design dimensions (ambience, spatial layout, innovation, and cultural contact) to investigate the factors influencing tourists’ satisfaction and continuance intention. The research employed a convenience sampling method, selecting typical Chinese tourists who had experienced the digital nightscape tour as survey participants. A total of 650 responses were obtained. The results of Partial Least Square-Structural Equation Modeling (PLS-SEM) found that, firstly, UTAUT2, satisfaction, and ambience all directly predict continuance intention positively, with satisfaction having the strongest impact. Secondly, among the four variables of UTAUT2, social influence has the strongest impact on continuance intention. Thirdly, the design dimensions of the digital nightscape tour are very important, which indirectly affect continuance intention through satisfaction, with ambience having the greatest influence on continuance intention. The research conclusions help support the high-quality development of the digital nightscape tour. Full article