A SEM-ANN-NCA ANALYSIS OF GEN Z’S PERCEPTION-DRIVEN ADOPTION OF AUGMENTED E-COMMERCE

This study uses perceived usefulness and trust as mediating variables to investigate how Augmented Reality (AR) affects purchase intention in the setting of Indonesian e-commerce. An online survey is employed to employ the quantitative technique, and it is given to Indonesian e-commerce users who have previously used augmented reality features. Purposive sampling approaches were employed to pick respondents who met the following requirements: they had to be at least eighteen years old, had utilized augmented reality in e-commerce, and actively engaged with platforms that offer these capabilities. Using SmartPLS software, the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach was used to analyze the data. This study combines the Stimulus-Organism-Response (S-O-R) and Technology Acceptance Model (TAM) frameworks to describe how AR influences consumer behavior through affective and cognitive pathways. The results showed that AR significantly positively affected perceived usefulness and trust, which then positively impacted purchase intent. However, the effect of perceived usefulness on intention to visit is not supported. The mediating effect of perceived usefulness is also not supported, while trust is proven to mediate the influence of AR on purchase intention. These findings emphasize the importance of improving the AR experience to build consumer trust and demonstrate use value, thereby driving purchasing behavior. This research provides an empirical contribution to the digital marketing literature and practical implications for e-commerce players in optimizing AR technology.

Purpose: This study explores the impact of augmented reality (AR) technology on purchase intention in Indonesia. By integrating the AR experience framework with an extended Technology Acceptance Model (TAM), the research examines how five dimensions of the AR experience—sensory experience (SE), emotional experience (EE), thinking experience (TE), action experience (AE), and related experience (RE)—affect perceived ease of use (PEOU) and perceived usefulness (PU), which subsequently influence purchase intention (PI), with attitudinal ambivalence (AA) as a mediating factor.Method: A quantitative, cross-sectional survey was conducted with 300 Indonesian respondents, aged 18 to 60, who were recent users of the AR Sephora Virtual Artist. Data were collected through an online questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).Result: Findings reveal that the dimensions of the AR experience positively impact PEOU and PU, which subsequently negatively influence AA. PU also directly fosters positive PI, while PEOU does not. Importantly, AA negatively affects PI, underscoring its critical role in consumer decision-making.Practical Implications for Economic Growth and Development: This research offers valuable insights for retailers to optimize AR implementation, thereby enhancing consumer engagement and driving purchase intention. Improving AR usability and effectiveness can reduce consumer uncertainty, strengthen market adoption, and advance digital commerce in the beauty industry.Originality/Value: This study uniquely integrates AA into existing AR adoption models and combines the AR experience framework with an extended TAM, providing novel theoretical contributions to AR in retail and insights into consumer behavior.

This study examines the factors influencing seniors’ adoption of augmented reality (AR) cognitive training games through an extended Technology Acceptance Model (TAM). It incorporates exogenous constructs such as computer anxiety (CAX) and innovation traits (IT) to address barriers to digital inclusion and AR cognitive training games adoption for cognitive training. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the relationships between Perceived Ease of Use (PEOU), Perceived Usefulness (PU), and Behavioral Intention to use (BI) were analyzed. Data were collected from participants aged 65–80 who completed 30-minute AR sessions (Apple Shooter and AR Dunk) at community centers. BI emerged as the strongest predictor of actual usage behavior (AUB), with PU and attitude toward usage behavior (ATUB) also playing significant roles. Perceived enjoyment (PE) and IT positively influenced ATUB, while CAX negatively affected PEOU and BI. Age and gender moderated these relationships, underscoring the need for user-specific AR cognitive training games designs. The findings highlight BI’s critical role in AR cognitive training games adoption and emphasize the importance of intuitive, anxiety-reducing AR tools with simplified interfaces and tailored tutorials to support cognitive health and digital inclusion.

Introduction: Virtual Reality (VR) and Augmented Reality (AR) are increasingly integrated into medical education, offering immersive and interactive environments for safe clinical training. Several theoretical frameworks—Technology Acceptance Model (TAM), Self-Determination Theory (SDT), Task-Technology Fit (TTF), and Flow Theory—can explain technology adoption and learning effectiveness. However, no comprehensive empirical comparison has been conducted within the context of VR/AR-based medical education. Methods: A cross-sectional survey was conducted with 329 undergraduate medical and health sciences students who had prior experience using VR/AR for learning activities. Validated instruments representing each theoretical framework were employed. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate reliability, validity, and structural relationships, followed by a comparative assessment using R², Q², f², and path coefficients. Results: Flow Theory demonstrated the strongest explanatory power (R² up to 0.72), with immersion and engagement as critical predictors of learning outcomes. SDT also showed high predictive strength (R² up to 0.63), emphasizing the role of intrinsic motivation. TTF was effective in predicting task-related learning effectiveness (R² = 0.67), whereas TAM provided only moderate explanatory power (R² ≈ 0.41–0.46). Conclusions: Flow Theory and SDT offer the most comprehensive explanations of student engagement and learning outcomes in VR/AR medical education. TTF remains valuable for task-specific alignment, while TAM primarily captures initial usability perceptions. Overall, immersive and motivational factors are key drivers of effective VR/AR learning, providing guidance for both theoretical development and instructional design in medical training

This study examines the factors influencing the behavioral intention and usage behavior of e-bikes in Metro Manila and the National Capital Region (NCR) using constructs from the Diffusion of Innovation (DOI) theory, the Technology Acceptance Model (TAM), and external variables such as government policies, infrastructure, social influence, and public awareness. A cross-sectional survey of 340 respondents was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to explore the relationships among these constructs. The results indicate that perceived usefulness (PU), perceived ease of use (PEOU), social influence, and public awareness significantly affect behavioral intention, which strongly predicts e-bike usage behavior. Infrastructure also positively impacts ease of use, while trialability enhances perceived usefulness. However, the relationships between government policies and perceived usefulness, as well as between trialability and ease of use, were insignificant, reflecting contextual limitations in the Philippine setting. The findings highlight the importance of behavioral intention as a primary driver of e-bike adoption. To address barriers, practical recommendations include expanding bike lanes, implementing e-bike sharing systems, strengthening government incentives, and launching public awareness campaigns that highlight the benefits of e-bikes, such as cost savings and environmental sustainability. This study also contributes to theory by integrating DOI and TAM frameworks, offering a comprehensive understanding of e-bike adoption in developing urban settings. These insights provide actionable strategies for policymakers, manufacturers, and stakeholders to promote sustainable transportation in the Philippines and similar contexts.

Aim/Purpose: This study investigates the key factors influencing preschool teachers’ sustained use of Artificial Intelligence-Generated Content (AIGC) technology in educational settings. While prior research has extensively examined initial adoption, little attention has been given to understanding the continuous intention of preschool teachers with AIGC. To bridge this gap, this study integrates the Technology Acceptance Model (TAM), Expectation-Confirmation Model (ECM), and Flow Theory to develop a comprehensive framework that captures cognitive, affective, and experiential factors shaping continued AIGC adoption. Background: AIGC has demonstrated immense educational potential, providing personalized learning experiences, real-time feedback, and intelligent student progress tracking. However, most existing research focuses primarily on system usability and feasibility, neglecting the motivational and psychological aspects that determine continuous intention to use AIGC. Specifically, satisfaction, expectation confirmation, and flow experience have been largely overlooked as key determinants of sustained technology use. Given that preschool educators face unique pedagogical challenges, such as adapting AIGC content to young learners and maintaining engagement, understanding the drivers of long-term AIGC use is essential for optimizing its integration into preschool education. Methodology: This study employs a mixed-method approach to ensure a rigorous and comprehensive analysis. A total of 433 preschool teachers participated in the survey, and Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to test the hypothesized relationships. To complement structural modeling, Artificial Neural Network (ANN) modeling was applied to uncover non-linear relationships that traditional statistical methods might overlook. By integrating PLS-SEM and ANN, this study provides a more robust, predictive, and holistic understanding of the factors driving sustained AIGC adoption. Contribution: This study makes significant theoretical and practical contributions. Theoretically, it extends TAM and ECM by incorporating Flow Theory. Unlike prior studies focusing primarily on perceived usefulness and ease of use, this research identifies confirmation and satisfaction as the strongest predictors of continued intention to use AIGC. Practically, the findings provide valuable insights for policymakers, school administrators, and ed-tech developers, offering recommendations for designing more engaging, sustainable, and user-friendly AIGC solutions tailored for preschool education. Findings: The results indicate that satisfaction (β = 0.280, p < 0.001) is the strongest predictor of continued AIGC use, followed by attitude (β = 0.262, p < 0.001) and flow experience (β = 0.223, p < 0.001). Expectation confirmation significantly enhances perceived usefulness (β = 0.505, p < 0.001) and satisfaction (β = 0.349, p < 0.001), reinforcing the importance of aligning AIGC tools with teachers’ expectations. ANN analysis further highlights confirmation (95.28%) and satisfaction (82.41%) as the most influential factors, whereas perceived ease of use (22.35%) has a relatively minor impact. These findings suggest that positive user experience, engagement, and expectation fulfillment are key drivers of long-term AIGC adoption. Moreover, ANN analysis revealed complex nonlinear relationships, demonstrating that traditional statistical methods might underestimate the true impact of psychological and experiential factors on technology retention. Recommendations for Practitioners: For practitioners, this study provides several actionable recommendations. First, AIGC tools should be designed to enhance engagement and intrinsic motivation, integrating gamification elements, interactive features, and adaptive learning support to sustain user interest. Second, ongoing professional development programs should be implemented to train teachers on the pedagogical applications of AIGC, addressing any concerns related to usability or long-term feasibility. Third, AIGC platforms should incorporate customization features, allowing educators to tailor content based on their specific classroom needs and teaching styles. By addressing these factors, AIGC adoption in preschool education can be more sustainable and impactful. Recommendation for Researchers: For researchers, this study opens multiple avenues for future exploration. First, future research should adopt a longitudinal approach to examine how preschool teachers’ attitudes and behaviors toward AIGC evolve over time. Second, more research is needed to explore the role of teacher personality traits and digital literacy levels in shaping AIGC adoption patterns. Third, cross-cultural studies could provide deeper insights into how different educational systems and socio-cultural contexts influence preschool teachers’ responses to AIGC technologies. Furthermore, AI-driven predictive analytics should be explored to model behavioral trends and optimize AIGC implementations across diverse learning environments. Impact on Society: This study has significant implications for educational equity, teacher workload, and early childhood learning experiences. By empowering preschool teachers with AIGC, this research promotes more inclusive and accessible preschool education, reducing disparities in educational resources and opportunities. Additionally, AI-driven teaching solutions can alleviate teacher workload, enabling educators to focus on creative and interactive pedagogical strategies rather than administrative tasks. As AIGC continues to evolve, its potential to transform preschool education into a more engaging, adaptive, and learner-centered experience becomes increasingly evident. Future Research: While this study provides valuable insights into preschool teachers’ sustained use of AIGC, several areas require further exploration. First, objective usage data should be incorporated into future research rather than relying solely on self-reported surveys to enhance validity. Second, longitudinal studies should examine how teachers’ continuous intention to use AIGC evolves over time in response to technological advancements and policy shifts. Third, as this study focuses on preschool educators, future research should explore whether the identified factors apply to primary and secondary education teachers. Additionally, ethical concerns, AI trust, and data privacy issues should be further investigated, as they may significantly impact the long-term adoption of AIGC in educational settings.

The infrequent occurrence of resuscitating critically ill pediatric patients poses educational challenges for pediatric anesthesiology residents developing competence. Traditional medical simulations, despite their utility, incur significant costs due to the need for monitors, mannequins, and personnel. Augmented reality (AR) medical simulation shows promise as an alternative clinical teaching tool. The Technology Acceptance Model (TAM) assesses usefulness, ease of use, and attitudes toward new technologies, offering insights into their adoption. Following successful application with other healthcare innovations, the TAM can also assess innovations in pediatric anesthesiology resident education, including AR medical simulation. The primary aim identified factors that influenced acceptance of AR for medical simulation in pediatric anesthesiology using a TAM. The secondary aims assessed the model's reliability, usability, and ergonomics. This prospective, multi-site study was carried out across nine academic children's hospitals around the United States and Hong Kong. We recruited anesthesiology residents with a minimum of two weeks of pediatric anesthesia experience, excluding those with severe motion sickness, seizures, or who wore corrective glasses. Using Magic Leap 1 headsets, participants underwent a simulated AR pediatric resuscitation scenario. Data were collected via electronic surveys, evaluating TAM factors, usability (System Usability Scale), and ergonomics (ISO 9241-400 standard). A total of 101 participants completed the study. The AR TAM model indicated that perceived ease of use and computer self-efficacy predicted perceived usefulness. Behavioral intention to use the AR system was influenced by perceived usefulness and perceived ease of use. System usability scores showed 83% agreement on ease of use. Ergonomic assessments indicated minimal physical discomfort. AR simulations are highly acceptable and usable for pediatric resuscitation training, with perceived ease of use and computer self-efficacy influencing AR adoption. These findings align with previous TAM studies, supporting AR's potential to supplement traditional simulations and enhance accessibility.

This study aims to determine the impact of implementing Augmented Reality (AR) features on mobile shopping applications on purchasing decisions of Generation Z consumers, especially first-time buyers. The research method uses a quantitative approach, the study involved 385 Generation Z respondents (aged 18-25 years) who were using AR features for shopping for the first time. The results of multiple linear regression analysis show that AR Visual Quality (X1), AR Interactivity (X2) and AR Ease of Use (X3) have a significant positive effect on Purchasing Decisions (p <0.000). The study revealed that 78.5% of AR features influence Generation Z in deciding to purchase on mobile shopping applications. In this case, it can be concluded that the presence of AR features can reduce Gen Z's hesitation in deciding to purchase for first-time buyers. Key factors influencing purchasing decisions include AR visualization quality, ease of use, and feature interactivity.

This study aims to investigate the interrelationships among digital literacy, AI adoption, institutional image, social innovation, and sustainability accounting education in Chinese higher education institutions. Study’s framework was developed by integrating Technology Acceptance Model (TAM), Diffusion of Innovations (DOI) theory, and the Institutional Theory to guide analysing research factors. Two-stage analytical approach was employed - Partial Least Squares Structural Equation Modelling (PLS-SEM) followed by Artificial Neural Network (ANN) approach. Research data were collected through distributing 500 questionnaires, of which 375 valid responses, comprising 75% response. Findings revealed that digital literacy promotes critical connection with sustainability challenges, AI adoption improves personalized learning opportunities and access to real-time environmental data. Universities with a sustainability-oriented image are more likely to entrench sustainability principles into their curricula. Social innovation, promoting collaboration and participatory learning, is perceived as a key player in facilitating sustainability education. Moreover, sustainability leadership is a significant competency that aids in facilitating the responsible integration of technology with sustainability principles. This study provides both theoretical and practical insights for Higher Education Institutions seeking to enhance sustainability education, in addition it contributes to further technological and institutional environment knowledge to shape sustainability education.

The development of Augmented Reality (AR) technology in the e-commerce sector offers new opportunities to enhance online shopping experiences through immersive and interactive features. This study aims to analyze the influence of AR characteristics—interactivity, vividness, novelty, and informativeness—on consumer perceptions (perceived enjoyment, perceived usefulness, and hedonic value), and how these perceptions affect attitudes, satisfaction, and purchase intention on the Shopee platform. A quantitative approach was employed, with data collected from 100 active Shopee users who have experienced using AR features. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that most AR characteristics significantly affect consumer perception. Furthermore, perceived enjoyment, usefulness, and hedonic value were found to influence user attitudes and satisfaction, ultimately increasing purchase intention. This study contributes theoretically to the understanding of AR integration in consumer behavior within e-commerce, and provides practical implications for businesses in designing immersive technology-based marketing strategies.

PurposeThis paper proposes a model that extends the technology acceptance model (TAM) by identifying factors that influence consumers' acceptance of augmented reality (AR) self-service technologies (AR-based SSTs) in the retail sector, resulting in the Augmented Reality in Retail Model (ARiR Model).Design/methodology/approachThis study is based on an online questionnaire responded to by 284 makeup-using women from Nicaragua and the USA. It is based on an AR mobile app used to shop in retail stores. Partial least squares-structural equation modelling was used to validate the ARiR model and test the hypotheses.FindingsAesthetics and navigation are significant predictors of perceived usefulness and perceived ease of use (PEOU), and self-efficacy also explains perceived ease of use. Technology readiness and the need for personal interaction were not found to be influencing factors. A cross-cultural comparison indicated that both countries have similar overall attitudes towards AR-based SSTs.Research limitations/implicationsThis paper provides insights into the perceived value of, and motives for customer acceptance of, AR-based SSTs, which can serve as guidelines for their future implementation. Furthermore, it validates and confirms the application of the proposed ARiR model for technology acceptance in both developed and developing countries.Practical implicationsThe paper provides new insights for retailers on the implementation of AR at the point of sale.Originality/valueThe model extends the original TAM to AR and introduces five new constructs: need for personal interaction, aesthetics, navigation, self-efficacy and technology readiness. It was tested in both a developing and a developed country.

This research investigates the strategic influence of artificial intelligence (AI) adoption on the competitiveness of Micro, Small, and Medium Enterprises (MSMEs) in Indonesia, emphasizing the mediating role of innovation diffusion. By synthesizing the Technology Acceptance Model (TAM), the Diffusion of Innovations (DOI) theory, and the Resource-Based View (RBV), the study analyzes how perceived usefulness and ease of use contribute to the attainment of sustained competitive advantage. Employing a quantitative methodology, the analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) on data collected from 160 MSMEs. The measurement model demonstrated strong reliability and validity. The findings reveal that technology adoption exerts a significant effect on both innovation and competitiveness, with innovation serving as a partial mediator. The R² and Q² values reflect moderate explanatory and predictive capacity. This study provides both theoretical contributions and practical recommendations for fostering digital transformation in the MSME sector through AI-driven innovation.

PurposeMobile e-commerce has brought convenience to consumers. But for goods such as shoes, mobile e-commerce has failed to provide the same experience as consumers would have in physical stores, and that also causes problems for online merchants, such as high return rates. As a result, the augmented reality (AR) virtual shoe-try-on function appeared. The way that AR virtual shoe-try-on study different from other AR virtual try-on studies is that AR virtual shoe-try-on study only satisfies consumers' visual experience and consumers cannot judge whether the shoes are comfort or not. Whether consumers would accept AR virtual try-on function to help them make purchase decision due to the visual experience provided by AR virtual try-on function is worth discussion. Measuring users' perceptions and preferences can help companies design AR shoe-trying functions and provide services more cost-effectively.Design/methodology/approachTo promote the continuous use and better development of such mobile e-commerce based on the technology acceptance model (TAM), this study explored the influencing factors for users' intentions to continue using the AR virtual shoe-try-on function, including the perceived usefulness, perceived ease of use, system quality, perceived playfulness and attitude.FindingsThe results of this study showed that TAM is a powerful theoretical tool of the new technology in mobile e-commerce and that the system quality and perceived playfulness also have a positive impact on the original variables of TAM. System quality and perceived playfulness are important predictors of users' continuance intentions to use the AR virtual shoe-try-on function.Originality/valueThe main contribution of this study to model iteration and theoretical update is to verify the applicability of the TAM in the AR shoe-try-on function and to expand TAM model with system quality and perceived playfulness. The authors' results will help shoe enterprises win users' recognition through AR shoe-try-on function and improve users' continuance intention of use.

The ARTEfac project aims to develop a web solution for teachers and trainers to design flexible teaching scenario including Augmented Reality (AR). This solution, developed by researchers and engineers from Aix-Marseille University and a private company, is composed of a Backoffice for scenarios' designers and a mobile user application. This paper is focused on the possible factors influencing the teachers' behavioural intention to use AR models in their own classes. Based on the TAM (Technology Acceptance Model), the survey tool is a questionnaire assessing the Behaviour Intention of use, the Perceived Usefulness, the Perceived Ease of Use, the Perceived Enjoyment, the Attitudes towards the use and the Aesthetic aspect. Thirty-six pre-service teachers investigated earth seasons through an AR scenario during a science training session at university. The scenario included an interactive AR model representing the earth revolution around the sun using 3D objects. The users had the possibility to interact with the model like stopping the revolution and rotation, changing the earth inclination, etc. One of the pedagogical objectives was to make them aware that the seasons are explained by the earth inclination (and not by the earth distance from the sun which is a very common misconception). A multiple regression analysis, including the different factors tested by the questionnaire, shows that there is a significant link between the Perceived enjoyment and the Behaviour Intention to use AR models in their classes. In contrast to earlier findings in different field of technologies, no significant influence of other TAM factors such as Perceived Usefulness, Perceived Ease of Use, Attitudes towards the use, Aesthetic aspects of the AR model was found. External factors such as gender, or their speciality (science, literature, etc.) do not influence significantly their intention to use. All these results will be discussed according to their limitations and the previous studies done in the same field.


 
 
 
 E-commerce comes from presenting product catalogs through two-dimensional static images that create limitations for users. Augmented reality features on smartphones have changed online consumer shopping activities. This allows consumers to try various cosmetic product variants virtually anywhere and anytime. Augmented reality is a new technology that provides convenience and experience for customers online to buy cosmetics online and try products without having to remove makeup. This study aims to examine the effect of independent variables on a dependent variable, with mediating variables. The population of this study is users of the virtual product trial feature who have purchased cosmetic products online aged 17–50 years in Indonesia, with a sample of 200 respondents. This research used path analysis, with the results showing that perceived ease of use affects trust, customer experience affects customer satisfaction, perceived usefulness, and customer satisfaction affects repurchase intention. However, trust does not affect repurchase intention. Based on these results, it is recommended that companies that provide product trial features adopt augmented mobile reality to pay attention to the convenience and benefits and improve the quality of the shopping experience.