Perspectives on artificial intelligence use in pharmacy education in Northern Ireland: A qualitative study based on the unified theory of acceptance and use of technology.

Agricultural extension plays a vital role in supporting agricultural development; however, the use of digital extension media remains limited and has not yet become embedded in extension practices. This study aims to evaluate the dynamics of perceptions among farmers and Field Agricultural Extension Workers (FAEW) toward smartphone-based digital extension media using the ADDIE model. An evaluative research approach was applied by integrating the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Innovation Diffusion Theory to analyze technology adoption. The study involved 100 respondents, consisting of 36 farmers and 64 FAEWs, from five Agricultural Extension Centers (BPP) under the Kostratani program in East Java. Data were collected using a structured questionnaire with a Likert scale of 1–5. Multivariate regression analysis revealed that five key factors explained 85.2% of the variance in digital media adoption (R² = 0.852; p < 0.01). Among these factors, Perceived Usefulness (β = 0.42) and Performance Expectancy (β = 0.38) were identified as the strongest determinants influencing adoption. Comparative analysis indicated perception gaps between farmers and extension workers, particularly in digital literacy. The Android-based multimedia applications developed through the ADDIE stages were shown effective in improving communication, information delivery, and collaboration in extension activities. This study offers a novel integration of the ADDIE model with dual perception analysis based on TAM and UTAUT in the Indonesian agricultural extension context. Recommendations include strengthening digital literacy training and improving infrastructure to support sustainable adoption of digital extension media.

Rapid adoption of digital surveying technologies in construction has highlighted the need for engineering education to equip students with technological competency as well as higher-order problem-solving skills. This experiment explores undergraduate students’ acceptance of emerging surveying technologies and their perceived learning results within a constructivist framework of experiential learning. Thirty-six students in a required construction surveying class interacted with traditional and advanced technologies such as total stations, terrestrial laser scanning, drones, and mobile LiDAR through structured, semi-structured, and unstructured lab activities. Data were gathered based on two post-course surveys: a technology acceptance survey grounded in Unified Theory of Acceptance and Use of Technology (UTAUT) and a self-perceived cognitive learning outcome survey through Bloom’s Taxonomy. Qualitative analysis along with quantitative analysis indicated a gap between technology acceptance and perceived learning gains. Laser scanner had the greatest acceptance scores followed by other advanced tools. Total station (widespread in hands-on lab activities) was perceived to have been most influential in terms of enhancing learning. Lower-order skills were strengthened in structured labs, while higher-order thinking emerged more unevenly in open-ended labs. These findings underscore that the mode of student engagement with technology matters more for learning than the sophistication of the tools themselves. By embedding UTAUT and Bloom’s Taxonomy in an authentic learning environment, this experiment provides engineering educators a mechanism to assess technology-enhanced learning and identifies strategies to facilitate higher-order skills aligned with industry needs.

The study intends to propose a new conceptual research model that integrates the Unified Theory of Acceptance and Use of Technology Theory (UTAUT) and green factors to address the growing challenge of greenwashing practices and environmental degradation. Causal quantitative research will be conducted using a cross-sectional survey to collect the research data. The proposed model is applicable in various industries such as tourism and hospitality, banking, education, and healthcare. The validated structured questionnaire will be completed by the respondents and will be tested using Smart PLS-SEM to examine the effects of UTAUT constructs and green factors on consumer behavioural intentions. The expected findings suggested that the green factors would strengthen the explanatory power of UTAUT by linking consumer technology adoption with pro-environmental behaviour. Theoretically, the present study extends the UTAUT framework by including additional green constructs, providing a more comprehensive model that bridges consumer technology acceptance with environmental sustainability. Practically, it will guide tourism operators, bankers, educators, and healthcare providers to embed empathy, transparency, and trust in digital platforms to reduce consumers’ skepticism towards greenwashing claims.

This study examines the determinants of Islamic financial inclusion in Indonesia, focusing on internet access effects through integrated Unified Theory of Acceptance and Use of Technology (UTAUT) and Diffusion of Innovations (DOI) frameworks. Probit regression analysis was conducted on 6,606 respondents from the 2018-2019 Financial Inclusion Insights survey. The model includes internet access, demographic characteristics, and socio-economic factors, with comprehensive robustness checks including multicollinearity assessment, goodness-of-fit measures, and sensitivity analyses. Internet access is the strongest predictor of Islamic financial inclusion, with a marginal effect of 2.71 percentage points (p<0.001), representing a 160% relative increase. Marital status shows a 2.24 percentage point effect (p<0.001), while primary education contributes 0.88 percentage points (p<0.10). Unexpectedly, being male decreases adoption by 0.73 percentage points (p<0.05). Urban residence, age, higher education, and employment status show no significant effects. This research is the first to integrate UTAUT-DOI frameworks for Islamic financial services, extends UTAUT to Sharia-compliant behavior, and demonstrates that digital infrastructure can override traditional geographic barriers. The findings reveal context-dependent gender moderation and establish internet access as the highest-leverage policy intervention for expanding Islamic financial inclusion in developing countries.

Food loss is a pressing global issue, with significant economic, environmental, and social ramifications. Small and Medium Enterprises (SMEs), which constitute a substantial share of food production, often face higher levels of food loss during processing due to limited resources and production capacity. Digital technologies present a promising solution for managing food loss and enhancing sustainable food security. However, SMEs frequently encounter barriers, such as resource constraints, limited budgets, and inadequate technical expertise, when adopting such technologies. This study investigates the factors influencing the adoption of digital technologies for food loss management among SMEs in the food manufacturing industry by employing an integrated framework that combines the Unified Theory of Acceptance and Use of Technology (UTAUT) with the Technology-Organization-Environment (TOE) perspective. Data were collected through a census approach, using questionnaires emailed to representatives of food manufacturing SMEs registered with the Department of Business Development in the Bangkok Metropolitan Region, Thailand, yielding 371 usable responses. Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) were utilized for data analysis. The findings revealed that performance expectancy, effort expectancy, and facilitating conditions, significantly impact the adoption of digital technologies, with facilitating conditions being the most influential factor. Conversely, social influence does not have a significant effect. The study highlights the importance of robust digital infrastructure, accessible technology specialists, and tailored training programs to enhance SMEs’ digital adoption. Furthermore, promoting awareness of the benefits of digital technologies and ensuring user-friendly solutions can improve confidence, motivation, and operational efficiency, ultimately reducing food loss in SMEs.

BackgroundClinical decision support systems (CDSS) for renal anemia among hemodialysis patients are gaining clinical attention. However, wide adoption remains challenging, and critical factors concerning physician acceptance remain elusive. This qualitative study conducted in-depth interviews with nephrologists to determine the relevant factors influencing physician acceptance.MethodsSeventeen nephrologists in the hemodialysis center at Far Eastern Memorial Hospital participated in semi-structured, in-depth interviews to explore their views and concerns regarding CDSS. The qualitative study was performed under the well-established framework of the unified theory of acceptance and use of technology (UTAUT).ResultsThe majority of participating physicians (14 of the 17) believed that a CDSS could streamline their workflow and save time. All participants agreed that robust clinical evidence of CDSS efficacy was critical to enhance CDSS acceptance. In addition, physicians noted that CDSS provides educational value, promotes patient safety and quality of care, and aligns with future technological trends. Despite these benefits, physicians raised concerns regarding dependence, distrust, and potential interference, which related to the physician professionalism. The UTAUT model should be extended with additional construct of autonomy in recognition of physician professionalism.ConclusionThis qualitative study revealed that nephrologists expressed positive views on the CDSS for anemia management. They acknowledged that the CDSS could enhance their work efficiency, improve patient safety, enhance care quality, and provide educational value. To optimize the acceptance of the CDSS under the UTAUT-Autonomy framework, the design and implementation of the CDSS should also address three additional key factors: over-dependence, distrust, and workflow interruption.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12913-025-13780-9.

English as a Foreign Language (EFL) teachers’ willingness to adopt artificial intelligence (AI) in teaching writing can significantly impact their teaching effectiveness. This narrative inquiry aimed to explore how a teacher preparation program shaped EFL teachers’ perspectives regarding AI integration, interpreted through the lens of the Unified Theory of Acceptance and Use of Technology (UTAUT). To this end, autobiographical narratives and semi-structured interviews were collected from 21 EFL teachers. Data were analyzed using Braun and Clarke’s 2006 six phases of thematic analysis. The analysis followed a deductive approach guided by the UTAUT constructs, encompassing performance expectancy, effort expectancy, social influence, and facilitating conditions, as well as the stages of process writing, including prewriting, planning, drafting, reflection, peer and tutor review, revision, and proofreading.The findings revealed that the teachers perceived the program as supporting their growing willingness to adopt AI in teaching. Following participation in the program, teachers demonstrated increased belief in AI’s potential to improve student writing and feedback. The various training opportunities offered within the program made AI integration less demanding for teachers and boosted their confidence in using available AI-driven writing resources. Moreover, teachers described how observing colleagues’ successful AI integration contributed to a sense of social support. The study shows that strategically designing EFL teacher preparation programs around UTAUT constructs can positively shape teacher’s perceived willingness to adopt AI for writing instruction. The findings have implications for teacher education programs to highlight the pedagogical benefits of AI, provide user- friendly training, foster supportive communities, and ensure access to adequate resources that enhance EFL teachers’ willingness to effectively adopt AI in process writing instruction in Iran and similar contexts.

This research addresses the strategic challenge facing Krom Bank as it transitions from a high-yield savings model to a comprehensive lifestyle banking ecosystem in Indonesia's competitive digital banking landscape. Using a quantitative research design, the study surveyed 281 respondents (100 KROM users and 181 non-KROM users) to identify consumer preferences and prioritize feature development to achieve sustainable competitive advantage. The research framework integrated UTAUT (Unified Theory of Acceptance and Use of Technology) constructs, along with a gap analysis, spider chart analysis, and strategic scoring across 12 dimensions. All measurement constructs demonstrated acceptable-to-good reliability, with the confirming sample adequacy. This research validates Krom Bank’s strategic transition from a high-yield niche to a comprehensive lifestyle ecosystem. The primary solution identifies Transport Payment Integration as the optimal "Daily Anchor" to convert passive savers into active transactors. Concurrently, gap analysis mandates a critical secondary solution: overhauling Customer Service and Security infrastructure to close fundamental trust deficits. Synthesized via the Strategy Diamond framework, the roadmap prioritizes stabilizing trust before anchoring daily habits, ultimately evolving Krom’s economic logic from high-cost deposit dependency to a sustainable, transaction-led model.

Artificial Intelligence (AI) is transforming public sector services by improving efficiency, accessibility, and decision-making. However, security and privacy remain key challenges to user adoption. Despite the global rise in AI-enabled public services, empirical research on public perceptions remains limited, particularly regarding the relationship between security, trust, and adoption intention. Additionally, research on the factors shaping security perception in AI-enabled public services remains scarce, leaving key antecedents unexplored. To bridge this gap, this study offers empirical insights into the determinants of security, trust, and adoption intention in AI-enabled public services. Informed by the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), a theoretical model is developed and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) on survey data from 506 respondents in Saudi Arabia. The findings show that information security awareness, cybersecurity law, and security culture significantly influence security. Furthermore, security, privacy, recommendation quality, and anthropomorphism positively affect trust. Among adoption factors, trust emerges as the second most influential after performance expectancy. The results contribute to AI adoption research by highlighting the role of security-related factors and trust in shaping citizen adoption of AI-enabled public services, offering practical implications for policymakers to enhance public confidence in AI-driven services.

ABSTRACT This study aimed to explore the factors influencing usage intention (UI) for “Internet + Nursing Service” among older adults based on the extended Unified Theory of Acceptance and Use of Technology (UTAUT) model. From March 2024 to February 2025, 542 older adults who met the inclusion and exclusion criteria in 6 communities in Lanzhou were selected as participants. SPSS 26.0 software was used for statistical analysis. AMOS 22.0 software was used to construct and revise the model, fit test, path analysis, and hypothesis verification. A total of 526 questionnaires were collected. Performance expectancy, effort expectancy, facilitating conditions and individual innovativeness had positive effects on the UI of older adults for “Internet + Nursing Service”, and perceived risk and resistance to change had negative effects on the UI of older adults for “Internet + Nursing Service”. Among these factors, facilitating conditions positively affected older adults’ performance expectancy and effort expectancy. Individual innovativeness positively affected older adults’ effort expectancy and negatively affected older adults’ perceived risk. Technology anxiety positively affected older adults’ resistance to change. The UI of older adults for “Internet + Nursing Service” is affected by performance expectancy, effort expectancy, facilitating conditions, individual innovativeness, perceived risk, resistance to change and technology anxiety. The results of the study expand the applicable areas and study objects of the UTAUT model to some extent. In addition, it can provide reference and suggestions for the promotion and innovation path of “Internet + Nursing Service” in Gansu Province.

The study examines factors influencing the behavioural intention and actual usage of Moodle among academics at the University of KwaZulu-Natal (UKZN), South Africa. The study is anchored on the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The research design utilised in this study is quantitative in nature, guided by the survey method where data are collected from 89 academic staff. Data collected are analysed using the Partial Least Squares Structural Equation Modelling (PLS-SEM) technique. The analysis reveals that performance expectancy and social influence are the most relevant determinants of behavioural intention, while facilitating conditions significantly determines actual use. Behavioural intention is also a significant predictor of actual use where higher intentions to use Moodle led to higher usage. Notably, effort expectancy does not impact behavioural intention to use Moodle. Neither gender, age, nor experience, when considered as moderating variables, shows a significant effect on the relationships between constructs. Consequently, the applicability remains consistent across different user groups. The results of this study indicate that interventions aimed at increasing Moodle usage at UKZN, and similar institutions should focus on increasing the perceived usefulness of Moodle, capitalising on positive peer influence, and providing strong support systems. The study also contributes to the validation of the UTAUT model in the South African higher education setting and offers leads that can inform the design and implementation of e-learning strategies for developing countries and the setting of Learning Management Systems (LMS) platforms to maximise educational results.

Purpose This study aims to investigate the interplay between blockchain-enabled technological stimuli and religious commitment in shaping Islamic donors’ behavior in charitable crowdfunding. It also aims to address the critical issue of trust within Islamic charitable platforms by integrating the stimulus-organism-response (SOR) framework and the unified theory of acceptance and use of technology (UTAUT). Design/methodology/approach A qualitative research approach was adopted, with data collected from 201 young Muslims in Indonesia who were actively involved in various crowdfunding projects. Data analysis and model measurement were conducted using partial least squares structural equation modeling (PLS-SEM). Findings The results of this research indicate that the convenience of transactions exerts a positive and substantial influence on the expectations of Muslim donors regarding platform performance and their perception of legitimacy. Religious conviction exerts a distinct influence on donors’ behavior; however, it lacks the necessary strength to effectively govern the relationship between intention and the act of contributing. In contrast to various studies undertaken across multiple sectors, the results of this investigation suggest that perceptions regarding the conduct of Islamic donors or their philanthropic activities positively influence charitable behavior or actual acts of charity. Practical implications This study provides a novel integration of SOR and UTAUT frameworks to explain Islamic donor behavior in the digital age, offering a comprehensive view of how technological and religious factors co-shape trust and participation in charitable crowdfunding. Originality/value This study presents a distinctive conceptual approach by incorporating transaction convenience and religious devotion, a combination rarely found in existing literature, thereby underscoring the significance of the research. The research additionally used the SOR Framework, accompanied by a meticulously crafted construct that stands apart from the UTAUT. This approach enhances the theoretical landscape and introduces novel concepts to the discourse.

Background Artificial Intelligence (AI) is transforming service-oriented industries, yet its adoption in developing countries remains underexplored, particularly from the employee perspective. Employees’ perceptions, intentions, and organizational support are pivotal for effective AI integration in hospitality. Objective This study investigates the determinants of AI adoption among employees in Egypt’s hotel sector, drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT). It examines the effects of performance expectancy, effort expectancy, social influence, and facilitating conditions on AI usage, the mediating role of behavioral intention, and the moderating role of gender. Methods A quantitative design was applied using a structured online survey administered to 346 frontline employees in five-star hotels in Greater Cairo. Partial Least Squares Structural Equation Modeling (PLS-SEM) tested direct and indirect effects. Results Findings reveal that effort expectancy, social influence, and facilitating conditions directly and positively influence AI usage, while performance expectancy affects adoption indirectly via behavioral intention. BI mediates the link between UTAUT constructs and AI use, with gender moderating the intention–usage relationship: male employees exhibit stronger adoption tendencies. Conclusions The study underscores the role of user-friendly systems, inclusive training, and gender-sensitive strategies, extending UTAUT by establishing BI as a central mediator and revealing demographic contingencies.

Abstract Generative AI Health Assistants (GAIHAs) are transforming patient engagement in modern healthcare by providing personalized support and medical information. Despite the rapid growth in the number of GAIHAs and the technologies that integrate them, patient adoption remains uncertain. This uncertainty highlights the need for a deeper exploration of the factors influencing their acceptance and adoption as well as the barriers that limit widespread use. Traditional models, like the Technology Acceptance Model (TAM), primarily emphasize adoption drivers such as usefulness and ease of use while overlooking barriers such as privacy concerns and resistance to change. Other models such as the Unified Theory of Acceptance and Use of Technology (UTAUT) include social influence but limit scope to workplace expectations, neglecting broader social dynamics that are relevant in consumer-driven contexts like healthcare. This study investigates the drivers of GAIHA adoption through a new framework, EVF-DOI-IB, which integrates the Extended Valence Framework (EVF), the Diffusion of Innovation (DOI) theory, and Innovation Barriers (IB). The proposed framework builds on the core constructs of trust, risk, benefit, and intention from EVF, and extends them with additional antecedents. The new framework also incorporates innovation drivers from the DOI perspective, namely relative advantage, trialability, and interpersonal communication. Finally, the new framework includes the innovation barriers resistance to change and privacy concerns. The results from a quantitative analysis of our survey data reveal that trust and perceived benefits strongly predict adoption intentions while resistance to change and privacy concerns heighten perceived risks. The findings also show that interpersonal communication and relative advantages play vital roles in reinforcing trust. Our research contributes to the body of knowledge in that it expands EVF’s application to the domain of healthcare AI technologies and provides actionable recommendations for developers and healthcare providers.

Purpose This study aims to explore factors influencing travelers’ intentions to adopt artificial intelligence (AI) chatbots, focusing on both individual effects and configurational patterns. Design/methodology/approach An integrated framework combining the unified theory of acceptance and use of technology (UTAUT), affordance theory and self-determination theory (SDT) was tested using partial least squares structural equation modeling (PLS-SEM), necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA). Findings PLS-SEM indicates that performance expectancy, effort expectancy, interactivity, credibility, anthropomorphism and autonomy significantly influence adoption intention. NCA identifies performance expectancy, effort expectancy and anthropomorphism as necessary conditions. fsQCA reveals multiple sufficient configurations leading to high or low intention. Originality/value To the best of the authors’ knowledge, this study is the first to integrate autonomy and competence from SDT with UTAUT and affordance theory in travel AI chatbot adoption, applying NCA and fsQCA to reveal necessary and configurational conditions, thereby offering richer theoretical and practical insights.

Background: The increasing use of telemedicine has transformed communication between patients, physicians, and other health professionals through virtual platforms, offering new possibilities for healthcare delivery and accessibility. Objective: This study aimed to identify the factors influencing the acceptance of telemedicine services among women in Peru by applying an extended and conceptually adapted unified theory of acceptance and use of technology (UTAUT) model. Methods: A quantitative correlational design was used, involving a survey of 503 Peruvian women. Data were analyzed using the partial least squares structural equation modeling technique with SmartPLS 4 software. The analysis included a measurement model to assess convergent and discriminant validity of the constructs, followed by a structural model to test the proposed hypotheses. Results: Findings revealed that performance expectancy, social influence, effort expectancy, and perceived safety are the most influential factors affecting women's intention to use telemedicine services. Conclusions: From a theoretical perspective, this study contributes to understanding telemedicine adoption among Peruvian women by validating the relevance and reliability of the extended UTAUT model in this context. Practically, the results provide valuable insights for designing public policies and training programs to promote the use of telemedicine in Peru.

The objective of this scoping review will be to chart the available evidence on user experience and adoption of automation and artificial intelligence (AI) technologies for evidence synthesis. Evidence syntheses are crucial for informing health care practice and policy; however, they are constrained by the ever-increasing volume of research and labor-intensive methods. With reviews often taking over a year to complete, automation and AI offer promising solutions by streamlining evidence synthesis workflows. However, while these technologies may offer significant time savings, their adoption depends on usability, trustworthiness, and workflow integration-elements which are currently poorly understood. This review will include primary research articles, all types of reviews, expert opinions, and gray literature that discuss user experience and/or adoption of automation and AI technologies for evidence synthesis across all disciplines. Following JBI scoping review methodology, the search strategy will identify published and unpublished evidence sources using a 3-step process. An initial exploratory search of PubMed was conducted to identify relevant keywords and terms. This will be followed by searches of PubMed, Web of Science Core Collection, Scopus, ProQuest Central, and ACM Digital Library databases, as well as online gray literature sources to identify eligible studies. A date limit of October 2015 will be applied to the searches, with no language limitations. Three reviewers will independently screen, select, and extract data from relevant evidence sources. Data extraction and analysis will be charted and mapped through the lenses of 4 distinct frameworks: Unified Theory of Acceptance and Use of Technology (UTAUT), RE-AIM, Human-AI Interaction (HAI), and user experience (UX) principles. OSF https://doi.org/10.17605/OSF.IO/AYQJC.

Abstract Background Digital payment systems have already become the key to transforming financial services in emerging markets, but their usage remains highly dependent on user trust, perceptions of usefulness and convenience, and the availability of favourable conditions. Objectives This research sought to investigate how consumer trust and adoption of digital payment platforms depend on variables, drawing on the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and a multidimensional trust theory. Methods/Approach A quantitative survey of 500 respondents across four emerging-market regions was conducted. The relationship among performance expectancy, effort expectancy, social influence, facilitating conditions, and the three trust dimensions was analysed using structural equation modelling (SEM). Results Performance expectancy, facilitating conditions, and trust-related constructs proved to be strong predictors of behavioural intention to use digital payments, and actual system utilisation was strongly predictable by behavioural intention. Trust was identified as mediating the users’ technological perceptions and their intentions to adopt. Qualitative implications revealed issues of security, data privacy, and infrastructural inconsistency that continued to influence user reluctance and perceptions of risk. Conclusions The results highlight the roles of trust-building mechanisms, effective user support systems, and regulatory assurance in promoting digital financial inclusion in emerging markets.

To explore the formation mechanism of college students' adoption intention of generative artificial intelligence (GAI)—i.e., the dynamic paths of direct/indirect effects of antecedent variables and interaction effects of moderating variables—this study integrates and extends the traditional Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). The integration is necessary because traditional TAM focuses on rational cognition, while UTAUT2 lacks the emotional dimension in educational scenarios and the integration of multi-level contexts. A theoretical framework incorporating the “individual-family- institution-region” four-dimensional moderating and collaborative perspective was constructed, and an empirical analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM). A multi-stage stratified sampling method was adopted, with a sample of 842 college students from five universities in eastern and western China. The scales for UTAUT2 core variables and extended TAM variables in the questionnaire were adapted from previous studies that had undergone reliability and validity verification. Reliability was tested using Cronbach's α and Composite Reliability, while validity was tested using Average Variance Extracted, the Fornell-Larcker criterion, and Heterotrait-Monotrait Ratio. Results showed that the measurement model had acceptable reliability and validity, with good explanatory power (R 2 = 0.743) and predictive validity of the structural model. Specifically, perceived comfort (β = 0.112, p < 0.005), perceived security (β = 0.109, p < 0.05), and emotional dependence (β = 0.497, p < 0.005) all exerted positive effects on perceived usefulness and perceived ease of use. Performance expectancy (β = 0.216, p < 0.005), social influence (β = −0.064, p < 0.05), facilitating conditions (β = 0.143, p < 0.005), and perceived ease of use (β = 0.469, p < 0.005) directly drove adoption intention, whereas the direct effect of perceived usefulness was not significant (β = −0.031, p = 0.523). This result challenges the core assumption of TAM—which emphasizes “priority of rational utility” and confirms the “de- instrumentalization” characteristic of generative AI adoption, meaning user decisions rely more on emotional experience and interactive fluency.Regarding moderating effects: gender negatively moderated the relationship between performance expectancy and adoption intention (β = −0.207, p < 0.05); family structure negatively moderated the relationship between habit and adoption intention (β = −0.228, p < 0.05); university type positively moderated the relationship between performance expectancy and adoption intention (β = 0.251, p < 0.05); and regional differences negatively moderated this relationship (β = −0.251, p < 0.05).In practice, it is suggested that educational authorities strengthen the construction of digital infrastructure in western universities, universities develop differentiated guidance strategies for students majoring in humanities/social sciences and science/engineering, and developers optimize emotional interaction design. This study provides theoretical support for context-adapted strategies for the educational application of generative AI.