Validity Testing of Technology Acceptance Model Based on Factor Analysis Approach

E-learning is believed by various parties to be effective and efficient learning media if implemented through good governance. Although some problems arise not only in terms of governance but also arise from the side of user behavior. This problem encourages experts to conduct researches that support the formation of models to measure user behavior towards the acceptance of technology, especially information technology. Models which recorded in various literature and references on results of information technology research are such as Theory of Reasoned Action (TRA), Theory of Planned Behavior (TPB), and Technology Acceptance Model (TAM). The most popular and widely used model in various studies is the TAM model that contains 3 factors which are perceived usefulness, perceived ease of use, behavioural intention to use, and 1 final factor which is actual system use. E-learning in Unpad is known as the LIVE (Learning in Virtual Environment) of Universitas Padjadjaran with the website address http://live.unpad.ac.id. This study uses the TAM model involving 3 external factors namely e-learning self efficacy, complexity and lack of time. The results showed that the factors of e-learning self efficacy, complexity and lack of time for educators are not an obstacle in the use of e-learning. This is supported by the testing result. (1) The e-learning self-efficacy factor has a significant effect on the factor of the e-learning actual system use through behavioural intention to use factor, meaning that the factor of self-efficacy influence the intention of e-learning actual system use, (2) complexity factors influences the e-learning actual system use factor through behavioural intention to use factor, which means the complexity factor influences the behavioural intention to use factor of the teaching staff to use e-learning and the last (3) the lack of time factor influences the actual system use of technology through behavioural intention to use factors, meaning that lack of time affect the behavioural intention to use of the teaching staff to use e-learning

PurposeThis research aims to combine and extend the literature on the self-monitoring approach used by faculty members in online teaching during the COVID-19 pandemic using the Technology Acceptance Model (TAM) model. The study also highlights the challenges faced by faculty members in online teaching.Design/methodology/approachBased on a mixed methodology approach, the primary data was obtained from the faculty members of the post-graduate business schools. This data enabled the measurement of self-monitoring adopted by the faculty members and the relationship of the factors by using the TAM model. Multivariate regression was adopted to study the relationships between the elements in the TAM model and faculty members’ self-monitoring. Secondly, a few exploratory questions were asked to the respondents about the challenges faced by them during online teaching.FindingsThe quantitative analysis conducted using multiple regression directed that the faculty’s contentment with any digital platform influenced their engagement, attention and participation while taking an online class as a part of the self-monitoring process. The perception of the technology platforms used for online teaching affected the faculty members’ self-monitoring dimensions: attention, participation and engagement. Based on the qualitative approach, the thematic analysis pointed out five major challenges for faculty members in conducting online classes: I.T. support, hesitation, interaction with peers and students, proficiency with an online platform and evaluation challenges.Research limitations/implicationsThis study was conducted during the complete lockdown of the COVID-19 pandemic; many faculty members were initially trained to get familiarized with the online teaching platforms and educate students. Hence, this study enriches the literature on online teaching during pandemic times.Practical implicationsTo ensure that the faculty impacts quality online education and the students obtain the knowledge and skills required, faculty need to alter their pedagogy based on the technology they use to focus on their students’ teaching, learning and needs.Originality/valueThis study measures self-monitoring and its dimensions for faculty members, which is unique in nature. This was the first time the faculty members were imposed with the responsibility of online teaching and ensuring that the learning-teaching process was fruitful. This study has both-theoretical and practical implications as the paper focuses on various insights which can make online teaching-learning more effective.

Ngaglik I Public Health Center in Sleman is one of the health centers that have already applied SIMPUS (an application of management information system for public health center). The implementation of clinical information systems could potentially improve the performance of health care facilities, save operational costs, and increase patient satisfaction. In fact, the clinical information systems applied by public health center vary. One of them is SIMPUS. However until present, there have not been any assessments of the acceptance of the clinical information system, especially SIMPUS, at Ngaglik I Public Health Center. To describe the use of SIMPUS at Ngaglik I Public Health Center and evaluate user understanding in accepting SIMPUS application based on the Technology Acceptance Model (TAM). This was a quantitative study which used a survey method and a cross-sectional design. The research sample consisted of 50 respondents who were selected using a simple random sampling method. The data analysis technique was the SEM-PLS analysis with the TAM model and SmartPLS software. Statistically, the relationship between the Job Relevance and Perceived Ease of Use variables was weak (p-value = 0.818). There was a weak relationship between Output Quality and Perceived Ease of Use (p-value = 0.208). There was a strong relationship between Result Demonstrability and Perceived Ease of Use (0.000). There was a strong relationship between Result Demonstrability and Intention to Use (p-value = 0.011). There was a weak relationship between Screen Design and Intention to Use (p-value = 0.870). There was a weak relationship between Perceived Ease of Use and intention to use. Users’ job relevance to SIMPUS did not have any effect on perceived ease of use. Output quality did not have any effect on perceived ease of use. The screen design of SIMPUS display had no effect on intention to use. Intention to use did not affect system use. Intention to use did not affect system use. Facilitating condition did not have any effect on system use. System use was influenced by perceived ease of use and intention to use. Perceived ease of use and intention to use were influenced by result demonstrability.

Electronic procurement has continued to gain ground in many organisations world over both in government and private institutions as a basis for competitive procurement and good practice. African countries have also started implementing electronic procurement and Zambia is no exception. Electronic procurement when well implemented has many organisational advantages to be gained by respective institutions that implement these reforms. In this paper, the aim was to identify the factors affecting successful implementation of electronic procurement in government institutions based on the Technology Acceptance Model (TAM). A baseline study was conducted for a targeted population of 100 respondents purposively selected, drawn from Information Technology, Procurement and Finance Departments. Data were collected through the questionnaires. Statistical correlation was used in data analysis in order to assess the level of adoption and usage of electronic procurement based on the TAM model. The study findings revealed that perceived ease of use and intention to use was positive. This implies that the personnel in most government institutions were ready to embrace electronic procurement implementation reforms largely due to ease of use and usefulness of the electronic system. However, the study revealed that not much was being done by top management in respective institutions regarding the implementation of electronic procurement.

User acceptance of information technology has been a significant area of research for more than two decades in the field of information technology. This study assessed the acceptance of information technology in the context of Health Information Management (HIM) by utilizing Technology Acceptance Model (TAM) which was modified and applied to assess user acceptance of health information technology as well as viability of TAM as a research construct in the context of HIM. This was a descriptive- analytical study in which a sample of 187 personnel from a population of 363 personnel, working in medical records departments of hospitals affiliated to Tehran University of Medical Sciences, was selected. Users' perception of applying information technology was studied by a researcher-developed questionnaire. Collected data were analyzed by SPSS software (version16) using descriptive statistics and regression analysis. The results suggest that TAM is a useful construct to assess user acceptance of information technology in the context of HIM. The findings also evidenced the perceived ease of use (PEOU) and perceived usefulness (PE) were positively associated with favorable users' attitudes towards HIM. PU was relatively more associated (r= 0.22, p = 0.05) than PEOU (r = 0.014, p = 0.05) with favorable user attitudes towards HIM. Users' perception of usefulness and ease of use are important determinants providing the incentive for users to accept information technologies when the application of a successful HIM system is attempted. The findings of the present study suggest that user acceptance is a key element and should subsequently be the major concern of health organizations and health policy makers.

Digital payment systems are pivotal in the digital economy, relying on the interplay between internet technology and e-vendors. While the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB) have been extensively used to explain technology adoption, the role of trust in financial technology adoption remains underexplored. This study addresses this gap by developing an extended Trust-TAM-TPB model, providing a comprehensive framework to analyze digital payment adoption in emerging markets. A quantitative approach was adopted, analyzing survey data from 509 respondents using Structural Equation Modeling (SEM). The extended model examines both technological factors (perceived usefulness, perceived ease of use) and trust-related factors (trust's influence on behavioral intention via subjective norms, attitude, and perceived behavioral control). Findings confirm that trust is a significant determinant of digital payment adoption, influencing both perceived usefulness and subjective norms. However, a negative relationship was found between perceived usefulness (PU) and attitude (ATT), suggesting that while users recognize the benefits of digital payments, their attitudes may still be shaped by traditional cash-based habits and security concerns. These insights challenge traditional TAM assumptions and emphasize the importance of trust in driving adoption. This study contributes to technology acceptance literature by integrating trust into the TAM-TPB framework and highlighting its dual role in shaping both perceived usefulness and behavioral intention. Practically, the findings suggest that policymakers and financial institutions should prioritize trust-building strategies, including fraud prevention measures, financial literacy programs, and transparent transaction policies, to accelerate digital payment adoption in developing economies. These insights are particularly relevant for Vietnam's Northern mountainous regions, where digital payment penetration remains low.

The rapid growth of virtual communities (VCs) on the Internet raises important research questions regarding the antecedents of satisfaction and loyalty in VCs. This study compared the technology acceptance model (TAM), Seddon Information Systems Success Model (Seddon model), and an integrated model (combining the TAM and Seddon model) to examine which model best helps to predict user satisfaction with VCs. Using a structural equation model, data collected from 198 community members were used to compare the three models in terms of overall model fit, explanatory power, and path significance. The findings show that two TAM components (perceived usefulness and ease of use) are determinants of user satisfaction with VCs. This study also found the influence of quality-perception dimensions (e.g., system and information quality) on user satisfaction to be significant. Additionally, this study found general support for user satisfaction as a determinant of loyalty in VCs. Finally, an integrated model, combining the TAM and Seddon model, provided better explanatory power than either the TAM or the Seddon model alone. Finally, this study discusses the implications of these findings and offers directions for future research.

This research aimed to contribute to the overall understanding of pre-service teachers’ acceptance of the Digital Storytelling (DS) tool. The primary associations of the Technology Acceptance Model (TAM) were tested in the academic years 2017/2018 and 2018/2019 for statistical significance when the effects of the pre-service training teachers' digital age and status were controlled. Data from 296 pre-service teachers, from second and third study year, majority women considered vulnerable group were collected. The factor analysis and invariance tests on basic TAM were performed. The results revealed that DS tool usage intention was a function of perceived usefulness and ease of use. This research established the TAM applicability with the control variables addition to model the DS tool acceptance by pre-service teachers, as didactic material for natural sciences and technology education. Configural, metric, and scalar invariance were confirmed across both cross-temporal and cross-sectorial groups. Perceived ease of use of DS has strongly influenced both usefulness (β=.571, t=11.958, p<.0001) and intention to use of DS (β=.763, t=19.914, p<.0001), under the influences of the control variables. The outcomes contributed to the general understanding of DS pre-service teachers’ adoption relevant for natural sciences and technology education and for recognition of vulnerable category behavior. Keywords: digital storytelling tool, natural sciences didactics, technology education didactics, pre-service teachers’ digital age, pre-service teachers’ status, TAM model.

A respectable amount of work dealing with Technology Acceptance Model (TAM) clearly indicates a popularity of TAM in the field of technology acceptance in general. Nevertheless, there is still a gap in existing knowledge regarding representative academic literature that underlie research on TAM in educational context. The main objective of this systematic literature review is to provide an overview of the current state of research efforts on TAM application in the field of learning and teaching for a variety of learning domains, learning technologies and types of users. Through systematic search by the use of EBSCO Discovery Service, the review has identified 71 relevant studies ranged between 2003 and 2018. The main findings indicate that TAM and its many different versions represent a credible model for facilitating assessment of diverse learning technologies. TAM's core variables, perceived ease of use and perceived usefulness, have been proven to be antecedent factors affecting acceptance of learning with technology. The paper identifies some gaps in current work and suggests areas for further investigation. The results of this systematic review provide a better understanding of TAM acceptance studies in educational context and create a firm foundation for advancing knowledge in the field. Practitioner Notes What is already known about this topic Technology acceptance research in teaching and learning context has become an attractive trend. A number of reviews and meta‐analysis focused on specific topics related to technology acceptance in education have been conducted. The Technology Acceptance Model (TAM) is the key model in understanding predictors of human behaviour towards potential acceptance or rejection of the technology. What this paper adds The state of current research on Technology Acceptance Model application in educational context lacks comprehensive reviews addressing variety of learning domains, learning technologies and types of users. The paper presents systematic review of relevant academic literature on Technology Acceptance Model (TAM) in the field of learning and teaching. The paper provides empirical evidence on the predictive validity of the models based on TAM presented in selected literature. The findings revealed that TAM, along with its many different versions called TAM++, is a leading scientific paradigm and credible model for facilitating assessment of diverse technological deployments in educational context. TAM's core variables, perceived ease of use and perceived usefulness, have been proven to be antecedent factors that have affected acceptance of learning with technology. Implications for practice and/or policy The systematic review adds to the body of knowledge and creates a firm foundation for advancing knowledge in the field. By following the most common research objectives and/or by filling current gaps in applied research methods, chosen sample groups and types of result analysis, an own study could be conducted. Future research may well focus on identifying additional external factors that could further explain acceptance and usage of various learning technologies.

This study investigates adoption/use behavior within the context of college students. A research framework based on the Technology Acceptance Model (TAM) is developed to identify factors that would influence the adoption and continue use of the credit card. Besides the "perceived usefulness" and "perceived ease of use", this paper introduces the "perceived risk", "promotion", "trust in electronic channel", "computer self-efficacy", "subject norm", "structural assurance" as new factors. Structural Equation Modeling (SEM) is employed to examine the entire pattern of inter-correlations among the factors, and to test related propositions empirically. A survey including a total of 343 college students is conducted and confirmatory factor analysis used to determine the measurement efficacies. The results reveal that perceived usefulness, perceived ease of use, promotion and perceived risk play direct and significant role in influencing the intention of adopt the credit card while computer self-efficacy and subject norm play indirect role. Perceived ease of use has a significant indirect effect on intention to adopt/use through perceived usefulness, while its direct effect is less significant.

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One common model utilized to understand clinical staff and patients' technology adoption is the technology acceptance model (TAM). This article reviews published research on TAM use in health information systems development and implementation with regard to application areas and model extensions after its initial introduction. An electronic literature search supplemented by citation searching was conducted on February 2017 of the Web of Science, PubMed, and Scopus databases, yielding a total of 492 references. Upon eliminating duplicates and applying inclusion and exclusion criteria, 134 articles were retained. These articles were appraised and divided into three categories according to research topic: studies using the original TAM, studies using an extended TAM, and acceptance model comparisons including the TAM. The review identified three main information and communication technology (ICT) application areas for the TAM in health services: telemedicine, electronic health records, and mobile applications. The original TAM was found to have been extended to fit dynamic health service environments by integration of components from theoretical frameworks such as the theory of planned behavior and unified theory of acceptance and use of technology, as well as by adding variables in specific contextual settings. These variables frequently reflected the concepts subjective norm and self-efficacy, but also compatibility, experience, training, anxiety, habit, and facilitators were considered. Telemedicine applications were between 1999 and 2017, the ICT application area most frequently studied using the TAM, implying that acceptance of this technology was a major challenge when exploiting ICT to develop health service organizations during this period. A majority of the reviewed articles reported extensions of the original TAM, suggesting that no optimal TAM version for use in health services has been established. Although the review results indicate a continuous progress, there are still areas that can be expanded and improved to increase the predictive performance of the TAM.

The study’s major goal was to figure out what factors impact university students’ behavior and intentions to use social media to boost their academic performance during the COVID-19 Pandemic. Given the context-dependent nature of online learning, the Technology Acceptance Model (TAM) was adopted and supplemented with components largely relevant to harnessing social media for collaborative learning and engagement. Collaborative learning, student participation, and a social media mindset are just a few of the new features. The enlarged model was validated using empirical data from an online survey questionnaire filled by a sample of 409 Saudi Arabia higher education students, which assesses students’ social media usage intentions and academic performance during the COVID-19 Pandemic. AMOS-SEM was used to analyze the model’s various assumptions (Analysis of Moment Structures- Structural Equation Modeling). The findings revealed that: (1) utilizing social media for collaborative learning and student engagement has a direct positive impact on perceived usefulness, ease of use, and enjoyment; (2) perceived usefulness, ease of use, and enjoyment has a direct positive impact on attitude to use social media; and (3) the link between TAM characteristics “usefulness, ease of use, and pleasure” and behavior intention to use social media is mediated by attitude to use social media. (4) Students’ attitudes and behavior intentions on social media have a direct positive influence on their academic performance during the COVID-19 Pandemic. Academics, higher education institutions, and educational technology application providers will benefit greatly from the conclusions of this study, both theoretically and practically.

Mobile health apps (MHAs) are increasingly used in modern health care provision. The technology acceptance model (TAM) is the most widely used framework for predicting health care technology acceptance. Since the advent of this model in 1989, technology has made generational advancements, and extensions of this model have been implemented. This systematic review aimed to re-examine TAM models to establish their validity for predicting the acceptance of modern MHAs, reviewing relevant core and extended constructs, and the relationships between them. In this systematic review, MEDLINE, Embase, Global Health, APA PsycINFO, CINAHL, and Scopus databases were searched on March 8, 2024, with no time constraints, for studies assessing the use of TAM-based frameworks for MHA acceptance. Studies eligible for data extraction were required to be peer-reviewed, English-language, primary research articles evaluating MHAs with health-related utility, using TAM as the primary technology acceptance evaluation framework, and reporting app use data. Data were extracted and grouped into 5 extended TAM construct themes. Quality assessment was conducted using the Joanna Briggs Institute (JBI) tools. For cross-sectional methodologies (9/14, 64%), the JBI checklist for analytical cross-sectional studies was used. For non-cross-sectional studies (5/14, 36%), the JBI checklist most relevant to the specific study design was used. For mixed methods studies (1/14, 7%), the JBI checklist for qualitative studies was applied, in addition to the JBI checklist most suited to the quantitative design. A subsequent narrative synthesis was conducted in line with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. A total of 2790 records were identified, and 14 were included. Furthermore, 10 studies validated the efficacy of TAM and its extensions for the assessment of MHAs. Relationships between core TAM constructs (perceived usefulness, perceived ease of use, and behavioral intention) were validated. Extended TAM constructs were grouped into 5 themes: health risk, application factors, social factors, digital literacy, and trust. Digital literacy, trust, and application factor extended construct themes had significant predictive capacity. Application factors had the strongest MHA acceptance predictive capabilities. Perceived usefulness and extended constructs related to social factors, design aesthetics, and personalization were more influential for those from deprived socioeconomic backgrounds. TAM is an effective framework for evaluating MHA acceptance. While original TAM constructs wield significant predictive capacity, the incorporation of social and clinical context-specific extended TAM constructs can enhance the model's predictive capabilities. This review's findings can be applied to optimize MHAs' user engagement and minimize health care inequalities. Our findings also underscore the necessity of adapting TAM and other acceptability frameworks as the technological and social landscape evolves. PROSPERO CRD42024532974; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024532974.

Driven by market competitiveness enhancement, service improvement, and working effectiveness promotion, more and more organizations have realized their potentials and paid a lot of attentions to them (Chau & Hu, 2002). As estimated, about 50% of new capital investment has been put in information technology (Westland & Clark, 2000). Despite its great potentials, users’ acceptance or adoption of these technologies does not live up to the initial expectations (Sun & Zhang, 2004). It is obvious that ITs are useless unless users accept and subsequently use them. Therefore, user technology acceptance becomes a hot topic and much effort has been made in order to obtain a deep understanding of how and why users accept certain technologies. Several models have been proposed in the last 2 decades and subsequent studies tested them (Table 1). New virtual technologies, especially collaborative technologies, enable some new forms of interaction. For example, members in virtual teams can work simultaneously on a document together as a distributed team, remotely access shared information from anywhere, or record team activities (Majchrzak et al., 2000). Virtual technologies, like other types of technology, have to be accepted and used by users first. However, virtual technologies, while sharing certain characteristics with other technologies, have special features. Therefore, this article is an attempt to identify the structure and factors influence user acceptance of virtual technologies based on existing user technology acceptance models. In general, the existing technology acceptance models can still be used for virtual technologies. Prior studies have confirmed that users accept virtual technologies in a similar way as other technologies (Moon & Kim, 2001; Yager, 1999; Chen et al., 2002). For example, Moon and Kim (2001) studied the acceptance of the World Wide Web (WWW). According to their study, the results about key factors in extant models are consistent with prior studies, which means that the factors influencing user acceptance of general technologies, although a little different, are also suitable for virtual technologies. Another example is Yager’s study (1999), in which many factors, such as usefulness, ease of use that are traditionally considered to be important for technology acceptance in general, are still valid for virtual technologies. Therefore, we can borrow factors from existing models. However, virtual technologies have their own characteristics. Therefore the factors contributing to user acceptance are likely to be different (Moon & Kim, 2001). So we need to propose new factors pertaining to the new type of technology. For example, playfulness is considered as an additional factor that is especially influential for virtual technologies (Moon & Kim, 2001). In summary, we can refer to existing models while considering the characteristics of virtual technologies. Actually, it is a highly valid approach (Chen et al., 2002).