"Moving through Uncertain Pathways": Health Professionals' perspectives on novel technologies for continuing care in high-risk pregnancy using the technology acceptance model.

Enhancing sustainable fashion through QR-enabled showrooming: A Philippine consumer behavior perspective.

Exploring Chinese college EFL learners' AI technology acceptance driven by computer self-efficacy.

Adaptive Learning System (ALS) is one of the useful learning tools that has emerged in the technological innovation of the educational sector. Many schools and universities have adopted it for academic use since the prompt of online learning. However, the relative evaluation of ALS has been undermined in the current generation - especially among developing countries. The purpose of this study was to analyze the variables affecting the actual academic use of online ALS among students. A total of 638 students from the Philippines answered an online survey of 50-item questions derived from the eleven constructs used in this study, which were analyzed simultaneously using Structural Equation Modeling. This study utilized two important theories, integrating both the Self-Determination Theory and the Unified Theory of Acceptance and Use of Technology Use in ALS acceptance. The findings showed that autonomy, competence, price value, and facilitating conditions were the significant factors in student's behavioral intention to use the ALS. Since developing countries are trying to adapt to the current trends among developed countries, it was suggested that developers may need to make their ALS accessible through other gadgets like smartphones and tablets. The findings of this study can contribute to the educational context of digital learning to meet the needs of the students by increasing their behavioral intentions to use ALS. Further, the results provided insights and suggestions to universities and ALS developers to collaborate on improving the ALS for the student's welfare in learning.

Empowered by AI: exploring the link between literacy, self-efficacy, and career expectations.

This study explores the key factors influencing hospitality and tourism researchers’ intentions to integrate GenAI like ChatGPT into their research practices through the Technology Acceptance Model (TAM). While prior studies highlight GenAI’s transformative potential in hospitality and tourism, there remain gaps in understanding its adoption challenges. In-depth qualitative interviews were conducted with twenty-two H&T researchers, purposefully selected from four universities in the UK. The analysis of the interview data was conducted within the procedural framework of a six-step thematic analysis. Researchers perceive GenAI as a dual-facet assistant. The thematic reflects four key factors: ‘Perceived Usefulness’, ‘Perceived Ease of Use’, ‘Trust vs. Mistrust’ and ‘Cultural and Ethical Concerns’. Although the interface is simple to navigate and the responses are quick, there are notable negative implications concerning ethics, cultural biases, and trustworthiness. The study found that the researchers’ actual use patterns vary from full adoption to entire avoidance. This study is transformative because it provides a foundational understanding of the TAM applied to one of the latest technologies, GenAI. It further opens a discussion on how GenAI can promote publishing within the hospitality and tourism research communities while also highlighting potential limitations, such as ethical considerations, over-reliance on AI, and the shifting role of human expertise in academic settings. The study also offers a guide that directs the research community, such as higher education and research institutions (HERs), to establish clear policies that support researchers in efficiently using technology and enhancing their research skills and knowledge.

The rapid integration of digital technologies in the sphere of higher education has had an essential influence on the process of teaching and learning and imposed new psychological and cognitive requirements on students of universities. Even with the increasing technical infrastructure on the ground, student academic performance is increasingly reliant on internal factors, including their dispositions towards technology use and their self-beliefs on their capability to study. The proposed research aims at exploring the extent to which academic self-efficacy and technology attitudes of undergraduate students have a bearing on academic achievement at the University of Lahore, Pakistan. It is founded on the Self-Efficacy Theory developed by Bandura and Technology Acceptance Model (TAM). Quantitative correlational study was used to collect data on 404 undergraduate students in six academic departments using validated self-report questionnaires. The evaluation of academic success based on cumulative grade point average (CGPA) was used to assess academic performance of students. The multiple regression analysis, independent-samples t-tests, descriptive statistics and Pearson correlation were performed in SPSS (Version 27). Findings showed academic self-efficacy and technology attitudes explained 52% variance in academic attainment. Self-efficacy was the strongest predictor, while females showed higher self-efficacy and more favorable technology attitudes.. The results support the paramount importance of the psychological preparation in the technology-enhanced learning space and emphasize the urgency of the institutional intervention increasing student confidence levels and engagement rates with digital technologies. The present research, policy and practice implications on higher education are discussed.

ABSTRACT The developments in technology-mediated channels serve personalization as a critical component to marketing communications strategies. However, the influence of proactive psychological traits through which personalization can translate into customer engagement in omnichannel retail touchpoints remains unclear. The present study offers and empirically tests the integrative conceptual framework of cognitive and proactive psychological traits grounded on technology readiness and acceptance model (TRAM) to assess the impact of personalization on customer engagement by including key mediating constructs. The study incorporated structural equation modelling (SEM) through a survey of 409 customers from India. The study evaluates both direct and indirect relationships that reveal a significant impact of personalization on customer engagement through the mediating constructs in the omnichannel retail. The study contributes and advances the literature by framing personalization as a pertinent communication stimulus that serves as the groundwork for future academic and managerial platforms.

This study examines the determinants of meta-banking adoption by extending the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) to include technostress, AR/VR experience, and perceived value. Data from 312 respondents with prior AR/VR exposure were analyzed using confirmatory factor analysis (CFA) and multi-group structural equation modeling (SEM), and multi-group SEM. The measurement model met the necessary reliability and validity standards (with Cronbach’s α at least 0.74, CR at least 0.83, and AVE at least 0.56), and confirmed discriminant validity through HTMT, which was below 0.85. The CFA indices showed a good fit, with values like χ²/df at 2.8, CFI at 0.96, RMSEA at 0.049, and SRMR at 0.041. Testing for measurement invariance demonstrated that both configural, metric, and scalar invariance were upheld among users of Islamic and conventional banking. The findings indicate that factors such as perceived ease of use, usefulness, facilitating conditions, and compatibility all positively affect perceived value. In contrast, technostress has a negative influence on it. Moreover, perceived value is a strong predictor of adoption intention, with trust in technology playing a crucial moderating role. Multi-group analysis further shows that Islamic banking users have a stronger connection between perceived usefulness, ease of use, and their intention to adopt compared to conventional banking users. These insights enhance technology adoption theory by weaving in psychological and cultural aspects into the TAM/UTAUT framework, while also providing practical guidance for creating user-friendly and trust-building AR/VR banking solutions.

The integration of emotional monitoring technologies in logistics represents a significant leap in enhancing operational efficiency and worker well-being. As the logistics evolves, understanding the acceptance and adoption of such technologies becomes crucial. This study employs the extended Technology Acceptance Model (TAM) as a framework to investigate the determinants influencing logistics workers’ acceptance of emotional monitoring technologies, with a focus on facial expression recognition (FER), electroencephalography (EEG) and a bundle of physiological measures including Electromyography (EMG), Electrocardiography (ECG), and Galvanic Skin Conductance (GSC). We aim to explore how perceived usefulness (PU) and perceived ease of use (PEOU), core constructs of TAM, along with external variables belonging to social, individual and system levels, contribute to this acceptance. The questionnaire was administered to 45 warehouse operators from a logistics company in Italy. Results show that TAM models are able to explain the acceptance of these technologies in the examined working environment.

The adoption of green technologies is a central component of sustainability transitions, yet it cannot be fully understood through individual cognitive evaluations alone. Increasing evidence suggests that citizens’ acceptance of environmentally oriented technologies is shaped by institutional and normative contexts that influence behavioural decision-making. In response to this challenge, this study develops a conceptual extension of the Technology Acceptance Model (TAM) to examine green technology acceptance from an integrative perspective grounded in environmental psychology and behavioural public policy. The analysis is based on a structured conceptual synthesis informed by bibliometric and semantic evidence from 789 Scopus-indexed articles published between 2021 and 2025, including early-indexed records from 2025 available at the time of data retrieval. Recurrent patterns within this corpus link technology acceptance research with institutional constructs such as trust, legitimacy, transparency, and community support. These insights are complemented by a structured expert elicitation exercise using the Analytic Hierarchy Process (AHP), applied in an exploratory manner to examine the relative salience of institutional dimensions within the proposed framework. Rather than offering empirical validation of behavioural relationships, the study advances a theoretically grounded conceptual model in which institutional trust and legitimacy operate as contextual conditions shaping the relationship between perceived usefulness, perceived ease of use, and behavioural intention in sustainability-related adoption contexts. Institutional transparency and community support further reinforce perceptions of fairness, credibility, and social endorsement. Overall, the resulting framework conceptualises green technology adoption as a socially and institutionally embedded process, providing a coherent analytical foundation for future empirical research and for the design of behavioural public policies aimed at supporting sustainability transitions.

China is experiencing rapid population aging and is actively promoting smart home–based eldercare. Smart homes offer a promising means of supporting older adults in aging in place. However, low adoption and limited sustained use constrain their potential benefits, thereby exacerbating social, economic, and healthcare burdens. This study examined factors influencing older adults’ continuance intention to use smart homes in Shandong Province, China, by integrating the Expectation–Confirmation Model of Information Systems and the Technology Acceptance Model and incorporating China-specific contextual antecedents, including government policy, intergenerational technical support, compatibility, and cost. Data were collected using an online questionnaire survey of older adults aged 60 years and older with prior smart home experience (n = 421) and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results showed that perceived usefulness, perceived ease of use, satisfaction, and cost directly affected continuance intention, whereas government policy, compatibility, and intergenerational technical support influenced continuance intention through perceived usefulness, perceived ease of use, and confirmation. Based on these results, this study proposes a conceptual framework for understanding older adults’ continuance intention toward smart homes. The findings provide implications for inclusive policy, user-centered design, and family-supported digital aging in rapidly aging societies.

Purpose The purpose of this study is to investigate the role of policy incentives (PIs) on the adoption intention (AI) of electric vehicles (EVs). It also examines the mediating and moderating roles of technology knowledge (TK) and environmental awareness (EA) to promote EVs in the context of sustainable transportation. Design/methodology/approach A cross-sectional quantitative study using structured questionnaires is administered, and data from 312 responses are analysed with the help of SPSS and AMOS. Exploratory factor analysis is used to confirm the factor structure, while SEM is used to test the direct, mediating and moderating hypotheses. Findings The results of the study reveal that PIs significantly influence the AI of EVs. These incentives also impact the TK of consumers positively. TK is found to mediate the relationship between PIs and AI of EVs, signifying that PIs’ impact on EV adoption is enhanced if the consumer knows about EV technology. Furthermore, EA is found to moderate both PIs and TK relations with AI of EVs, implying that higher environmental consciousness converts PIs and TK into better adoption prospects. Research limitations/implications Based on technology acceptance model and theory of planned behaviour, this study integrates PIs with environmental and technological variables to analyse a comprehensive adoption framework for EVs. It examines the interplay between PIs, TK and EA and extends the multilayer understanding into consumer behaviour in the EV domain. Practical implications The focus of EV firms and policymakers, in addition to financial and non-financial incentives, should be on enhancing consumer knowledge about the EV technology. Making the masses aware of the environmental issues through sustainability messaging can significantly strengthen EV adoption rates. EV makers can use TK and EA as segmenting variables to develop tailormade strategies for EV adoption. Social implications This study shows how the impact of PIs can be complemented through TK and EA to encourage pro-environmental behaviour, such as the adoption of EVs in society. The combination of economic, technological and psychological factors is therefore required to bridge the socio-environmental gap that still exists globally. Originality/value This study integrates TK and EA with PIs to analyse their impact on EV adoption rates. The insights into direct, mediating and moderating roles of these variables thus offer new insights for advancing sustainable mobility.

An integrated model to assess the psychosocial determinants of the intention to adopt organic farming practices.

This study aims to investigate the impact of Industry 4.0 technology adoption on organizational performance in the healthcare sector, with a specific focus on the mediating roles of perceived usefulness, perceived ease of use, emotional trust and actual use. Grounded in the technology acceptance model (TAM), the research further explores how these mediators influence the relationship between technology adoption and performance outcomes. A mixed-method research approach was adopted, integrating structural equation modeling (SEM) and necessary condition analysis (NCA). SEM was employed to assess the direct and indirect (mediated) effects between variables, while NCA identified the necessary conditions required to achieve improved organizational performance. Data were collected from key stakeholders in the healthcare industry through a structured questionnaire. The results highlight the pivotal mediating roles of perceived usefulness and emotional trust in enhancing the relationship between Industry 4.0 adoption and organizational performance. Emotional trust and actual usage emerged as critical factors, indicating that both cognitive and affective dimensions significantly influence successful technology integration. The study also reveals that certain conditions, particularly related to trust and usability, are necessary (though not sufficient on their own) for achieving optimal performance outcomes. The findings provide actionable insights for healthcare managers and policymakers on how to improve technology implementation strategies. Emphasis should be placed on fostering emotional trust and user engagement alongside ensuring technological effectiveness. By addressing these mediators, healthcare institutions can more effectively leverage Industry 4.0 technologies to enhance organizational performance. This study offers a novel contribution by combining TAM with a mixed-method SEM-NCA approach to examine Industry 4.0 adoption in the healthcare supply chain. Unlike prior research, it underscores the necessity of emotional trust and actual use as core drivers of performance, providing both theoretical enrichment and practical guidance for successful technology assimilation in complex organizational settings.

Purpose This study aims to integrate the Technology Acceptance Model (TAM) and Innovation Resistance Theory (IRT) to explore how innovation and consumer characteristics influence both the usage intention and resistance towards virtual assistants (VAs). In addition, it examines the moderating role of privacy concerns within these relationships. Design/methodology/approach The study uses a quantitative research approach. Data from a survey of 206 VA users provided input for the partial least squares modelling (PLS-SEM) to analyse the proposed model. Findings The findings reveal that performance risk increases resistance to VAs, whereas relative advantage decreases resistance and positively influences usage intentions. Self-efficacy was found to reduce resistance but did not significantly affect usage intentions. The study demonstrates that privacy concerns intensify the negative relationship between resistance and usage intentions, suggesting that higher privacy concerns strengthen resistance and reduce usage intentions. Originality/value The integration of the TAM and the IRT to study VAs provides a holistic view that encapsulates both adoption and resistance within the same model. The inclusion of a moderating factor highlights how privacy concerns can amplify or dampen both the resistance to and the acceptance of VAs, providing a deeper insight into the barriers and facilitators of technology adoption.

Abstract: This study examines how obstacles in Thailand’s electric vehicle market reshape consumer psychology and reduce readiness to buy by integrating the Technology Acceptance Model with the Theory of Planned Behavior into a single path where price burden, infrastructure gaps, technical uncertainty and policy opacity elevate perceived risk, recast usefulness and ease beliefs, weaken attitudes and perceived control, and thereby depress intention. A structured questionnaire in Thai, English, and Chinese produced four hundred valid responses from prospective buyers recruited through convenience sampling, the instrument underwent translation and back translation with a pilot of thirty cases, and robust reliability and validity checks supported subsequent regression tests. Results indicate that financial, technical, and charging constraints significantly increase consumer doubt, that doubt is a strong negative predictor of purchase intention, and that barriers retain a direct association with intention, revealing partial rather than complete mediation. The findings enrich adoption theory by situating doubt within a stimulus organism response sequence and offer practical guidance for finance, warranty communication, and dependable public and workplace charging that together improve perceived control and reduce anxiety. Keywords: Electric vehicles, Consumer doubt, Adoption barriers, Purchase intention, Technology Acceptance Model, Theory of Planned Behavior, Thailand

The objective of this study is to conduct a systematic literature review of repurchase intention in social commerce. Specifically, the study examines the current state of research, identifies the key determinants of repurchase intention, and synthesizes background theories and measurement approaches applied in this domain. This research employed the PRISMA procedure for a systematic literature review conducted across two databases: Web of Science and Scopus. A total of 177 papers were identified from databases, with no restrictions on publication year, facilitating the assessment of all pertinent research on the topic. After screening, eligibility for evaluation was based on the study’s objective; ultimately, 27 publications were identified for systematic review and analysis. The results underscore the top five primary determinants of repurchase intention in social commerce: trust, social influences, user experience, perceived value and social commerce attributes. Furthermore, the research identified 16 theoretical foundations for examining repurchase intention in social commerce, with the Stimulus–Organism–Response framework and the Technology Acceptance Model as the primary theories for this systematic review. Furthermore, the findings indicated that partial least squares structural equation modeling remains the predominant measurement technique, but alternative methods continue to be used.

Digital hoarding is a newly emerging phenomenon in academia, with researchers having explored it from multiple disciplinary perspectives in recent years. However, empirical research from the perspective of communication studies is limited. Notably, digital hoarding behaviours are closely linked to individuals’ media usage patterns. Accordingly, our research grounded in theories of Social Cognition and Overconfidence Bias, Technology Acceptance Model, investigates the relationship between new media literacy and digital hoarding behaviours among Chinese youth ( N = 399, M age = 27.5). We also introduce information overload and information anxiety as two mediating variables that may function as explanatory mechanisms. The findings indicate that higher levels of new media literacy are associated with more pronounced digital hoarding behaviour, while greater new media literacy is also linked to lower levels of information overload and information anxiety. Furthermore, higher levels of information overload and information anxiety correspond to more severe digital hoarding behaviours. In addition, a positive relationship exists between information overload and information anxiety. Information overload mediates the relationship between new media literacy and digital hoarding behaviour, reversing the relationship so that increased new media literacy leads to a reduction in perceived information overload, which subsequently results in less digital hoarding behaviour. Our study offers empirical evidence from a new media literacy perspective, contributing to the research on digital hoarding, providing insights into young people’s information management practices.

ObjectivesThis study examined early care and education (ECE) providers’ routine and pandemic-related use of digital technology for nutrition training and explored their attitudes and perceptions toward digital technology using the Technology Acceptance Model as a guiding framework to inform future training delivery.MethodsWe employed a convergent mixed-methods design consisting of a national survey and semi-structured qualitative interviews with licensed ECE providers. Inclusion criteria were licensed/registered ECE providers, English-speaking, age ≥18, and currently caring for children for pay. Exclusion criteria included unlicensed providers and inactive programs. Survey data was analyzed using chi-square tests to examine differences by variable type and logistic regressions to examine predictors of digital technology use. Qualitative analysis underwent thematic analysis using a blended deductive/inductive approach guided by the Braun and Clarke multi-step method. Integrated analyses were conducted and shown through a joint display to contextualize the findings.ResultsMost ECE providers (97.9%) had access to high-speed internet, and 95.1% used electronic devices for work-related purposes. Approximately 83.2% had received nutrition training since the COVID-19 pandemic began, with 53.2% accessing training via virtual platforms. ECE providers enrolled in the Child and Adult Care Food Program were more likely to receive nutrition training digitally than those not enrolled (OR = 24.0, p < .001). As ECE providers’ age increases, the odds of receiving training digitally decreased (OR = 0.52, p = .043). Providers reported that digital training improved accessibility and flexibility. However, the study also identified challenges such as reduced social connectedness, technical difficulties, and limited knowledge or awareness of digital nutrition training programming.ConclusionFindings suggest that digital technology enhances access to nutrition training for ECE providers, yet barriers remain. Future efforts should focus on expanding digital training programming, improving technological support, and balancing digital and in-person training to optimize hands-on learning and social connectedness.