Examining factors affecting students’ intention of using collaborative platform (Metaverse) with an extended acceptance technology model (TAM)

Purpose – This paper aims to examine the user’s willingness of golfers toward the use of GPS navigation based on the technology readiness and acceptance models. Design/methodology/approach – This study developed the research structure based on the theory of the technology acceptance and readiness model to address the relationship between technology readiness, perceived usefulness, perceived ease of use, user’s attitude and behavioral intention. A purposive sampling questionnaire was used in this study to investigate golf participants in Central Taiwan. In all, 245 copies of the questionnaire were issued. About 240 copies were returned and after removing the invalid copies, there were 230 valid questionnaires for a valid response rate of 95.8 per cent. Findings – The research results indicated that technology readiness has a significant influence on perceived usefulness, technology readiness has a significant influence on perceived ease of use, perceived ease of use has a significant influence on perceived usefulness, perceived usefulness has no significant influence on user’s attitude, perceived ease of use has a significant influence on user’s attitude, user’s attitude has no significant influence on behavioral intention and perceived usefulness has a significant influence on behavioral intention. Originality/value – The technology acceptance model has been widely used to examine user's acceptance and willingness toward computer technology or an information product. This study, hence, is based on this model to investigate the user's willingness of golfers toward golf GPS and shall serve as a reference for future golf sports promotion and device R&D.

Based on previous theoretical streams, the present study integrates technology readiness (TR) into the technology acceptance model (TAM) in the context of consumer adoption of e‐service systems, and theorizes that the impact of TR on use intention is completely mediated by both perceptions of usefulness and ease of use. TAM was originally developed to predict people's technology‐adopting behavior at work environments, but this research stemmed from a questioning of its applicability in marketing (i.e., non‐work) settings. The differences between the two settings are exhibited by consumers' self‐determining selection behavior and their high involvement in the e‐service creation and delivery process. This paper first reviews the TAM and the construct of technology readiness, and then proposes and empirically tests an integrated Technology Readiness and Acceptance Model (TRAM) to augment TAM by taking technology readiness construct into the realm of consumers' adoption of innovations. The results indicate that TRAM substantially broadens the applicability and the explanatory power of either of the prior models and may be a better way to gauge technology adoption in situations where adoption is not mandated by organizational objectives. Further, theoretical and practical implications and future research directions are discussed. © 2007 Wiley Periodicals, Inc.

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.

Technology Acceptance and Hand Anthropometry (TAHA) Model: Insights from Somatosensory Technology

Many technology acceptance models used in education were originally designed for general technologies and later adopted by education researchers. This study extends Davis' technology acceptance model to specifically evaluate educational technologies in higher education, focusing on virtual classrooms. Prior research informed the construction of the model, which contains perceived usefulness, perceived ease of use, behavioural intent, access and convenience, system attributes and self‐efficacy. Education‐specific constructs include cognitive engagement, feedback, instructor practice and class interaction and communication. Additionally, a new construct called comfort and well‐being is introduced. A total of 427 valid responses on a 5‐point Likert scale were received from university students. Exploratory factor analysis, confirmatory factor analysis and structural equation modelling were used to analyse the data. The model accounted for 78% of variance of behavioural intent, with comfort and well‐being demonstrating the strongest influence. Cognitive engagement, access and convenience influenced perceived usefulness, and system attributes and self‐efficacy influenced perceived ease of use. Feedback, instructor practice and class interaction and communication were not significant as educational constructs for this cohort. Based on this analysis, a final extended educational technology acceptance model (EETAM) is proposed for further use and testing. Practitioner notes What is already known about this topic Most technology acceptance models used in education were made for general technologies, or do not include factors specific to learning and pedagogy. Most students prefer face‐to‐face learning experiences and active class engagement. Qualitative research shows that instructional attributes and student comfort and well‐being are known to be important for students. What this paper adds A novel extended educational technology acceptance model, informed by prior empirical research, is presented. Confirmation of the importance of including student comfort and well‐being in technology acceptance models used in education. The model revealed the heterogeneous nature of the student learning experience. Implications for practice and research Technology acceptance models used in educational settings should include factors specific for education and learning, and student comfort and well‐being. We encourage use of the presented model in educational settings to further test the model.

The growing use of Instagram and its influencers in marketing demonstrates their substantial influence on customer behavior intentions. Despite this, further research into the effects of Instagram mega-influencers on purchase intention is needed among Generation Z (born between 1997 and 2012) consumers. The main aim of the study was to assess the influence of attractiveness, expertise, perceived ease of use, and perceived usefulness on intention to purchase due to Instagram mega-influencers among Generation Z in South Africa. This study combined purposive and snowball non-probability sampling methods using a quantitative approach. An online questionnaire was used to assess the effect of Instagram mega-influencers on young consumers’ purchase intention, which resulted in 497 Generation Z respondents. Positive associations were found between attractiveness, expertise, perceived ease of use, and perceived usefulness on intention to purchase. Perceived ease of use was also found to mediate the positive effects of attractiveness and expertise on intention to purchase. This analysis provides businesses with practical information about the use of Instagram mega-influencers in digital marketing to connect with Generation Z consumers and improve profitability. The research contributes to the theoretical development of constructs in the technology acceptance and source credibility models and generation cohort theory.

PurposeThe purpose of this study is to examine individuals' decisions to use health and fitness apps by applying the extended technology readiness and acceptance model (TRAM), which combines technology readiness (TR), the technology acceptance model (TAM) and perceived enjoyment (PEN). Moreover, this study explores the differences between users and non-users regarding their intentions to use health and fitness apps.Design/methodology/approachData collection (n = 206) was conducted using convenience sampling from four large universities in South Korea. The data were analysed by partial least squares structural equation modelling (PLS-SEM) using SmartPLS 3.0.FindingsThe results revealed that positive TR positively affects perceived ease of use (PEOU), perceived usefulness (PU) and PEN, while negative TR had a negative impact only on PEN. Furthermore, the significant relationships between PEOU, PU and PEN were identified. In addition, multigroup analyses indicated that the relationships between positive TR and PEN, between PEN and PEOU, between PEOU and PU, and between PU and behavioural intention were positively stronger for app users.Originality/valueThis study initially applied the TRAM to understand individuals' behavioural intentions to use health and fitness apps. Moreover, this study identified the distinct roles of positive and negative TR affecting individuals' cognition regarding using health and fitness apps. The differences in the psychological processes between app users and non-users offer insights and implications for practitioners.

ABSTRACTThe purpose of this study is to explore factors that affect the acceptance of brand-sponsored applications (brand apps) on the basis of the technology readiness and acceptance model (TRAM). This study explains mobile application users’ preferences in today’s rapidly changing customer communication environment. The study analyzes the data collected with reference to four dimensions of the TRAM. Two of these dimensions – optimism and innovativeness – are used to measure positive technology readiness, and another two – discomfort and insecurity – are used to measure negative technology readiness. The analysis produces a better understanding of the technology readiness index and the technology acceptance model. Multi-group confirmatory factor analysis with covariance structure analysis was conducted using EQS6b and data obtained from a survey of airline customers (n = 1,000). Support for the research model was statistically significant, indicating that positive technology readiness and the negative technology readiness played important roles in the formation in respondents of perceived ease of use and perceived usefulness as well as in generating satisfaction with brand apps and the intention to continuing using a brand app. The study found that negative technology readiness did not significantly affect the perceived ease of use. Applying the Kano model, the study explains the formation of consumer attitudes towards brand apps. Theoretical and practical implications and limitations are discussed.

The main aim of the study is to investigate the relationship between the variables included in the Technology Acceptance Model (TAM), and the core variables and the extended variables of the TAM. The research method is a quantitative research that tests hypotheses derived from variables extracted from the Technology Acceptance Model (TAM), which include the variables of perceived ease of use, perceived usefulness, attitude towards use, actual use, e-learning self- efficiency, and a set of variables. complexity To test the relationship between each variable, this study uses statistical tests using structural equation modeling (SEM) application tools SmartPLS. The results of the research hypothesis are (H1) the positive effect of e-learning self-efficacy (learning self-efficacy online) on the perception of comfort (perceived ease of use). (H2) positive effect of e-learning self-efficacy on perceived usefulness (perceived usefulness), (H3) positive effect of complexity on perceived ease of use. (H4) complexity has a positive effect on perceived usefulness. (H5) perception of ease of use (perceived ease of use) the use of e-learning affects the attitude to use (attitude to use). (H6) view of usefulness (perceived usefulness) positive effect of e-learning on usage attitude (attitude towards usage). (H7) perceived ease (perceived ease of use) negative effect on actual use e-learning (actual use). (H8) perceived usefulness of e-learning (perceived usefulness) positively affects actual use (actual use). (H9) usage attitude (attitude towards usage) positive effect on actual usage (actual usage). The practical implication of the research include conducting an extension study of external TAM variables, conducting a study with different objects and subjects and conducting a pretest of the samples to be studied in the prior to the research.

Few studies have investigated the extension of the technology acceptance model (TAM) of mobile‐assisted language learning (MALL) by incorporating psychological influence factors. We aimed to determine the factors affecting the continued adoption of MALL by college‐age students of English as a foreign language (EFL). We extended the TAM by adding psychological constructs from action control theory and the concept of intrinsic motivation. Data from a large‐scale survey of 557 Taiwanese college EFL students recruited through online convenience sampling were analysed through structural equation modelling. The results revealed that the significant predictors of behavioural intention were its antecedents. Three crucial psychological factors, namely nonpreoccupation, nonhesitation, and nonvolatility, significantly predicted behavioural intention. Perceived ubiquity value, tasks, and mobile self‐efficacy were strong predictors of intrinsic motivation. Intrinsic motivation significantly predicted behavioural intention through perceived usefulness and perceived ease of use. Finally, perceived ease of use had a moderate effect on behavioural intention through perceived usefulness. The satisfactory explanatory power of the extended model was indicated by the explained variance (R2) of 80% for behavioural intention. This extended TAM may contribute to the long‐term development of MALL. Practitioner notesWhat is already known about this topic Mobile technology has been widely adopted to enhance language learning. However, few studies have investigated individuals' adoption of mobile‐assisted language learning (MALL). Factors affecting users' behavioural intention to accept an information system have been researched extensively. The technology acceptance model (TAM) has been extensively used to investigate users' acceptance of different technology in various contexts. What this paper adds This study extended the TAM by incorporating psychological factors to predict the behavioural intention of learners to continue using mobile technology in language learning. The three action‐oriented psychological antecedents (nonpreoccupation, nonhesitation, and nonvolatility) used in the model significantly predicted EFL college learners' behavioural intention to continue using mobile devices for language learning. One major factor (intrinsic motivation) significantly affected continued behavioural intention to engage in MALL through perceived ease of use and perceived usefulness. Implications for practice and/or policy Teachers should incorporate various warm‐ups, collaborative activities, and positive feedback from others to MALL tasks to reduce feelings of negativity for state‐oriented learners and increase willingness to accept MALL for action‐oriented learners. Teachers and developers of MALL systems can promote its acceptance by prioritising usable interfaces and enjoyable, challenging tasks in the design of MALL systems to increase learners' intrinsic motivation and perceptions of usefulness and ease of use. Technical guidance, clear and brief operation orientation sessions, and immediate support should be offered to assist learners in engaging in MALL tasks.

This study analyses the implementation of the Technology Acceptance Model (TAM) in the Curriculum Review course among students of Universitas Islam Sumatera Utara. This study aims to identify the factors that influence students’ acceptance and understanding of technology in the learning process. A quantitative approach was employed, utilising a structured survey distributed to 125 selected participants using the purposive sampling technique. The research instrument is a questionnaire developed based on TAM constructs, including (1) perceived usefulness, (2) perceived ease of use, and (3) attitude toward using. Data analysis employs Structural Equation Modelling (SEM) techniques to examine the relationships between variables. The research hypothesis examines the impact of perceived usefulness and perceived ease of use on attitudes and intentions to utilise technology in learning. The results show that: (1) perceived usefulness of technology among students positively affects attitudes toward using technology (β=0.65, p<0.05), (2) perceived ease of use of technology among students significantly positively affects attitudes toward using technology among students (β=0.58, p<0.05), (3) attitudes towards using technology among students significantly positively affect intentions to use technology among students (β=0.72, p<0.05). The TAM model is proven to explain 68% of the variance in technology acceptance among students. This suggests that the understanding and acceptance of technology among students in the Curriculum Review course are influenced by the perceived usefulness and ease of use, which are in turn mediated by attitudes toward using technology.

With the advancement of information and technology, virtual and remote laboratories have become supplementary or extra tools for hands-on biology laboratories. In this study, we modified the technology acceptance model to incorporate three additional external variables derived from flow theory in predicting students' acceptance and use of virtual and remote laboratories. This research included 145 college students. These students used virtual and remote laboratories for at least three months. The learning subjects in this research are deoxyribonucleic acid extraction, polymerase chain reaction, gel electrophoresis, deoxyribonucleic acid microarray, and flow cytometry. Using SPSS 25.0, a multiple regression analysis was performed to test the structural model hypothesis. This study validated the association between the basic variables used in the technology acceptance model: perceived ease of use, perceived usefulness, attitudes toward using, behavioral intention, and actual use. There were no surprising discoveries for the technology acceptance model's primary variables. Concentration and perceived enjoyment in the flow theory variables have an extensive relationship with the technology acceptance model variables, perceived usefulness, and perceived ease of use. Meanwhile, one flow theory variable, time distortion, exhibits no significant relationship with perceived usefulness or ease of use. Abstrak: Laboratorium virtual dan jarak jauh menjadi tren yang dimanfaatkan sebagai alat bantu praktikum biologi. Kami memodifikasi model penerimaan teknologi dalam penelitian ini dengan memasukkan tiga variabel eksternal tambahan yang berasal dari teori flow dalam memprediksi bagaimana mahasiswa menerima dan menggunakan laboratorium virtual dan jarak jauh. Penelitian melibatkan 145 mahasiswa. Para mahasiswa ini telah menggunakan laboratorium virtual dan jarak jauh setidaknya tiga bulan. Materi pembelajaran penelitian ini adalah ekstraksi asam deoksiribonukleat (DNA), polymerase chain reaction (PCR), gel electrophoresis, deoxyribonucleic acid microarray, dan flow cytometry. Hubungan antara variabel dasar yang digunakan dalam technology acceptance model yaitu kemudahan penggunaan yang dirasakan (perceived ease of use), kebergunaan yang dirasakan (perceived usefulness), sikap (attitudes toward using), niat perilaku (behavioral intention), dan penggunaan sebenarnya (actual use) divalidasi dalam penelitian ini. Data yang terkumpul dianalisis regresi berganda dengan bantuan SPSS 25. Tidak ada penemuan mengejutkan untuk variabel utama technology acceptance model. Variabel konsentrasi (concentration) dan kesenangan yang dirasakan (perceived enjoyment) pada teori flow memiliki hubungan yang signifikan dengan variabel technology acceptance model, kebergunaan yang dirasakan dan kemudahan penggunaan yang dirasakan. Sedangkan satu variabel teori flow, distorsi waktu (time distortion) tidak menunjukkan hubungan yang signifikan dengan kebergunaan yang dirasakan atau kemudahan penggunaan yang dirasakan.

PurposeThe study aims to validate a mobile learning readiness scale through the technology readiness and acceptance model (TRAM), thereby assessing students' readiness to adopt m-learning in teaching and learning, including its acceptance.Design/methodology/approachA structured questionnaire was administered to open and distance learning (ODL) students in Odisha, India, to assess their readiness and acceptance of m-learning. 665 valid responses were collected, and collected data was analysed using statistical packages for social sciences (SPSS) and SmartPLS.FindingsThe findings of the study reveal that optimism contributes positively to perceived ease of use (PEOU) and perceived usefulness (PU) of m-learning (β = 7.921, p < 0.001; β = 2.123, p < 0.05), whereas innovativeness positively contributes to PEOU of m-learning (β = 2.227, p < 0.05), but not PU of m-learning. ODL student's optimism improves his/her PEOU and PU of m-learning, but innovativeness improves only his/her PEOU. Further, the impact of innovativeness is higher than that of optimism in the TRAM and innovativeness is the strong predictor to adopt m-learning. It also shows that the PU of m-learning positively influences behavioural intention to use m-learning (β = 4.757, p < 0.001). Integrating technology readiness (TR) with technology acceptance model (TAM) to predict students' acceptance of m-learning is very useful.Practical implicationsThe paper will help decision-makers to adopt and use m-learning in higher educational institutions.Originality/valueThis paper is the first to explore the readiness and acceptance of m-learning in higher education in India.

Behavioral Intention Factors for Prescription Deliveries by Small Unmanned Aircraft in Rural Communities

Teknologi dalam melakukan pembayaran secara non-tunai sudah banyak diterapkan dengan menganalisis penerimaan pengguna terhadap GoPay sebagai sistem pembayaran elektronik dengan menggunakan Technology Acceptance Model (TAM). GoPay adalah salah satu layanan pembayaran elektronik yang populer di Indonesia. Namun, meskipun popularitasnya, masih ada faktor-faktor yang memengaruhi penerimaan pengguna terhadap sistem ini. Dalam penelitian ini, penulis mengadopsi Technology Acceptance Model (TAM) sebagai kerangka teoritis. TAM adalah model yang telah terbukti digunakan dalam banyak penelitian untuk memahami penerimaan pengguna terhadap teknologi. Model ini terdiri 5 konstruk, yaitu Persepsi Kegunaan (Perceived Usefulness), Persepsi Kemudahan Penggunaan (Perceived Ease of Use) Sikap Penggunaan (Attitude Toward of Using), Minat Perilaku (Behavioral intention),Pengguna Sesungguhnya (Actual Use). Dengan menggunakan Google Form untuk media penyebaran kuesioner nya. Peneliti mengambil sampel sebanyak 90 orang mahasisiwa yang menggunakan Gopay sebagai sistem pembayaran elektronik. Dengan menggunakan perhitungan TAM, kita dapat bahwa setiap variable TAM berpengaruh postif terhadap Pengguna Sesungguhnya (Actual Use). Technology in making non-cash payments has been widely applied by analyzing user acceptance of GoPay as an electronic payment system using the Technology Acceptance Model (TAM). GoPay is one of the most popular electronic payment services in Indonesia. However, despite its popularity, there are still factors that influence user acceptance of this system. In this study, the authors adopt the Technology Acceptance Model (TAM) as a theoretical framework. TAM is a proven model used in many studies to understand user acceptance of technology. This model consists of 5 constructs, namely Perceived Usefulness, Perceived Ease of Use, Attitude Toward of Using, Behavioral intention, Actual Use. By using Google Form as a medium for distributing questionnaires. Researchers took a sample of 90 students who used Gopay as an electronic payment system. By using TAM calculations, we can find that each TAM variable has a positive effect on Actual Use.