Original Technology Acceptance Model Research Articles

A longitudinal model of continued acceptance of conversational artificial intelligence

PurposeThe existing technology acceptance models have not yet investigated functional and motivational factors impacting trust in and use of conversational artificial intelligence (AI) by integrating the feedback and sequential updating mechanisms. This study challenged the existing models and constructed an integrated longitudinal model. Using a territory-wide two-wave survey of a representative sample, this new model examined the effects of hedonic motivation, social motivation, perceived ease of use, and perceived usefulness on continued trust, intended use, and actual use of conversational AI.Design/methodology/approachAn autoregressive cross-lagged model was adopted to test the structural associations of the seven repeatedly measured constructs.FindingsThe results revealed that trust in conversational AI positively affected continued actual use, hedonic motivation increased continued intended use, and social motivation and perceived ease of use enhanced continued trust in conversational AI. While the original technology acceptance model was unable to explain the continued acceptance of conversational AI, the findings showed positive feedback effects of actual use on continued intended use. Except for trust, the sequential updating effects of all the measured factors were significant.Originality/valueThis study intended to contribute to the technology acceptance and human–AI interaction paradigms by developing a longitudinal model of continued acceptance of conversational AI. This new model adds to the literature by considering the feedback and sequential updating mechanisms in understanding continued conversational AI acceptance.

The Effect of Revisiting Technology Acceptance Model on the Behavioral Targeting Declaration

The technology acceptance model (TAM) encompasses seven factors that contribute to its effectiveness: subjective norms, output quality, voluntariness, job relevance, image, result demonstrability, and experience. Nevertheless, the evolution of the technology acceptance model into TAM2 resulted in a significant boost in its explanatory power, surpassing the original TAM by 20%. Various industries, including electronic commerce, have embraced this model. Exploring the role of the TAM2 model in social commerce is a crucial topic discussed in this article.

Exploring Journalists’ Intentions Towards Digital Mobile Technologies

In recent years, the use of digital mobile technologies for journalistic practice has gained much popularity among Ghanaian journalists. In this study, we explored three original Technology Acceptance Model (TAM) variables (perceived ease of use, perceived usefulness, and social influence) and two additional variables, (the cost of smartphones, and the cost of mobile data) to predict the relationship between the five variables, and journalists’ intention to use Digital Mobile Technologies (DMTs). A structured questionnaire was used to solicit data from 281 Ghanaian frontline journalists through an online survey. The respondents were selected by purposive sampling. Structural Equation Modelling analysis of the data showed that, as the cost of smartphones, and the cost of mobile data increases, journalists’ intention to use technology decreases in Ghana. Thus, mobile data and the cost of smartphones had a negative relationship with journalists’ intention to use DMTs. The testing of perceived ease of use, perceived usefulness, and social influence, however, reported a positive relationship with the use intention. The findings from this study have implications for policy change on the reduction of the prices of both mobile data and smartphones to enhance the use of DMTs among journalists in Ghana. Also, the findings from this study could be considered a template for the proper regulation of the use of DMTs for enhanced practice of journalism in Ghana and other developing countries.

What factors influence the intention to use electric motorcycles in motorcycle-dominated countries? An empirical study in Vietnam

Transitioning to electric motorcycles (EMs) can reduce dependence on carbon-based fuels, mitigate air pollution, and lower greenhouse gas emissions in countries where motorcycles dominate the transportation landscape. However, the factors influencing fleet electrification in these countries remain largely unknown. Given that this challenge pertains to the prior adoption of new technology, technology acceptance theories can provide valuable insights into the adoption of EMs. Additionally, misinformation about EM risks and self-assessment of knowledge could interact as determinants of adoption. This study integrates the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and perceived risk to elucidate the impact of psychosocial factors on consumers' intentions to use EMs. Furthermore, it examines the direct and moderating effect of subjective knowledge about EM technology on the formation of this behavioral intention. Structural Equation Modeling (SEM) analysis was applied to investigate data collected from 762 respondents through personal interviews using a questionnaire. The results confirm that all original TAM and TPB constructs significantly influence behavioral intention, aligning with theoretical expectations. As hypothesized, perceived risk was found to exert a negative influence on the intention to adopt EMs. Additionally, subjective knowledge was observed to moderate the relationship between perceived usefulness and subjective norms concerning the intention to use EMs. These findings offer a roadmap for developing strategies aimed at encouraging adoption intentions toward EMs, particularly in countries like Vietnam.

Assessing the Factors Influencing the Adoption of Digital Signatures Among Government Employees in Tanzania

This study aimed at assessing the factors influencing the adoption of digital signatures among government employees in Tanzania. The study was guided by the technology acceptance model (TAM) with an additional of facilitating condition, a construct that was borrowed from the Unified Theory of Acceptance and Use of Technology (UTAUT). The quantitative research design was used by employing a purposive sampling technique to effectively identify cases that would use limited research resources. The study involved sample of 256 respondents drawn from selected government organizations. Findings indicated that the results are consistent with the original TAM framework and the additional factor – facilitating conditions fit well into the model. The results were discussed and recommendations as well as future research directions were suggested.

Exploring the factors affecting behavioral intention to adopt wearable devices

The study explores factors like healthcare, fashionability, ease of use. affecting adoption of wearable devices, with the intent to contribute to the current global health research. ObjectiveThe objective of this study is to identify the effect of different factors on behavioral intention to adopt wearable device. With regard to the intention to utilize smart wearables, we explicitly proposed a theoretical model based on the task-technology fit (TTF) model, the technology acceptance model (TAM), and external factors. MethodsPrimary data was collected from 139 respondents and structural equation modeling was performed for getting insights regarding intention to adopt wearable devices. SmartPLS software was used to analyse the data. ResultsThe hypothesized model explains 76.9 % variance of BI. 73.5 % of PEOU and 79.3 % of PU. Task and technology characteristics explain 88.9% of TTF construct. Connectivity and health care have a significant impact on TTF. TTF model has effect on TAM model leading to Behavioral Intention to adopt smartwatch. In addition, fashionability had a significant effect on BI. However as per study results, perceived privacy did not impact BI. ConclusionsIn conclusion we document that our findings are in consistency with the original TAM and TTF model. Therefore, this provides an opportunity to extend previous findings of users’ adoption. From this study the reliability and validity of integrated models is also verified. Furthermore, the aspects of wearable devices such as fashionability, ease of use, connectivity and healthcare turned out to be significant in the intention to adopt wearable devices.

Factors Affecting English Language Teachers' Behavioral Intentions to Teach Online under the Pandemic Normalization of COVID-19 in China.

The unexpected outbreak of COVID-19 pandemic forced most teachers across the globe to switch their teaching from traditional face-to-face to online without having received adequate preparation and knowledge related to online teaching. To better comprehend teachers' willingness to conduct emergency remote teaching during the worldwide crisis, the current study was designed to examine teachers' intentions and, in particular, the factors affecting their behavioral intentions to teach online, by contextualizing the research in the English language teaching settings in China. The research model was developed based on an extended technology acceptance model (TAM) by adding subjective norm, self-efficacy, technological complexity, and facilitating conditions into the original TAM. The data were obtained from a total of 287 respondents including 228 (79.4%) female teachers and 59 (20.6%) male teachers via online questionnaires. The questionnaire was developed by adapting previously validated instruments and then refined by two educational technology experts in order to better suit the current study. The empirical findings, using structural equation modeling (SEM), showed that the extended TAM was valid in predicting English language teachers' intentions to teach online during the pandemic normalization. At the same time, the findings suggested that teachers' intentions were influenced significantly by attitude, facilitating conditions, and self-efficacy; language teachers' attitude toward online teaching was significantly affected by both its perceived usefulness and perceived ease of use; perceived usefulness had a significant association with perceived ease of use and subjective norms; and perceived ease of use was significantly impacted by self-efficacy and facilitating conditions. Perceived usefulness was not suggested as a significant determinant of English language teachers' intentions to adopt online teaching. Despite some limitations, the study has several implications from the perspective of theory and practice. The more factors with a higher influence should be determined from different perspectives in future research.

FINTECH ANALYSIS OF QRIS PAYMENT TRANSACTIONS USING TAM METHOD IN MICRO, SMALL, AND MEDIUM ENTERPRISES (MSMEs) IN BANGLI, BALI

The presence of Financial Technology (Fintech), Quick Response Code Indonesian Standard (QRIS), provides changes to payment transactions that used to be conventional but have now turned digital. With this research, it is intended to find out what influences users use of Fintech services, especially QRIS in Bangli, by applying the original Technology Acceptance Model (TAM) method, which is modified using one external variable. This study uses quantitative methods and uses Partial Least squares (PLS) with the help of Smart-PLS 3.0 software. The results of the Inner Model Q2 Evaluation Test have a value of 84.1%. This shows that the acceptance of QRIS service user interest (Behavior Intention) can be explained by the variables Perceived Risk on Perceived Usefulness, Perceived Ease of Use, and Attitude Toward Using, and there are six hypotheses that are accepted.

Determinants of Economical High School Students’ Attitudes toward Mobile Devices Use

Due to recent considerable technology breakthroughs in the education sector, new tools have been developed to improve learning. Motivating students to use new devices for learning rather than just for amusement, however, is a difficulty. The COVID-19 pandemic prompted the adoption of technological devices for course delivery, thereby highlighting the significance of mobile learning (m-learning) and allowing educators, students, and other stakeholders in the education sector to recognize its potential, advantages, drawbacks, and challenges. As m-learning has been an essential aspect of education for some time now, there is growing interest in assessing its long-term viability and usefulness across various educational domains, including economics. New technologies like computers, the internet, and related tools can help by bringing life to the classroom, gauging student progress, simulating economic activities and phenomena, and teaching vital skills needed for the economic world, like entrepreneurship. This study aims to explore the potential of incorporating new technologies in economic education, we study the tendency of the economical high school students towards using mobile devices for learning activities. A total of 407 participants were involved in research, the data from these respondents being collected with the help of a questionnaire survey. The original technology acceptance model (TAM) has been extended and the role of various external factors such as the subjective norm, learning autonomy, facilitating conditions or self-efficacy has been addressed. A list of hypotheses was proposed to validate the underlying model and provide guidance on how external factors affect attitudes towards using mobile devices. The empirical results indicated that perceived ease of use and perceived usefulness are significant predictors to explain the attitudes towards mobile devices use and m-learning and the analyzed external factors have a positive influence on them. In terms of methods used, we characterize the perception of students by structural equations modelling (SEM). This study identifies and analyzes the factors that influence students’ attitude and readiness towards mobile technology use in education, providing valuable insights into improving the adoption of new technologies and to evaluate the sustainability of m-learning in economic education.

A Review of the Technology Acceptance Model in Electronic Health Records

Over the years, many theories and models have been proposed to explain and interpret behaviours related to the acceptance and usage of technology. The technology acceptance model (TAM), which has been tested in different technological applications, is the most well-known of these models. This article reviews previously published research on the application of TAM to electronic health records. According to the findings of this review, the original TAM was updated and extended to fit the dynamic healthcare service environment by absorbing and integrating variables from various theoretical frameworks as well as by adding variables in specific contextual settings. This demonstrates how the TAM model has been adapted and expanded to meet the specific demands of the healthcare industry, emphasising its usefulness in various settings.

Students’ Acceptance of Learning Management Systems at the Peak of Covid-19 Pandemic by Employing a Modified Technology Acceptance Model

Objectives: This study aimed to investigate the motivating variables that affect students’ attitudes toward using Learning Management Systems (LMS) during the Covid-19 pandemic and beyond by extending the Technology Acceptance Model (TAM) to include perceived enjoyment and perceived trustworthiness. Methods: Data were collected from 599 tertiary students from across five public universities in Ghana using online questionnaires to measure Perceived Usefulness (PU), Perceived Ease of Use (PEU), Attitude Towards Use (ATU), and Behavioural Intention (BI). The collected data were analyzed using PLS-SMART. Findings: The study’s findings suggest that perceived usefulness and perceived ease of use affect students’ attitudes toward LMS use (That is, PEU — > ATU [O = 0.227, t = 4.747, p = 0.000] and PU — > ATU [O = 0.430, t = 8.993, p = 0.000]), which affects students’ behavioural intention to use IT (That is, ATU — > BI [O = 0.314, t = 6.828, p = 0.000]). In addition, the most vital relationship was “perceived ease of use” as a predictor of “perceived usefulness” (That is, PEU — > PU [O = 0.440, t = 10.025, p = 0.000]). Furthermore, contrary to expectations, perceived enjoyment and perceived trustworthiness, also considered critical predictors, did not affect students’ attitudes toward LMS use (That is, PE — > ATU [O = 0.085, t = 1.776, p = 0.076] and PT — > ATU [O = 0.033, t = 0.744, p = 0.457]). Novelty: These findings provide valuable insights which can enhance education quality and students’ acceptance of LMS during mandated environments such as the COVID-19 pandemic. The framework of the study is an extension of the original TAM model, including new constructs, perceived enjoyment, and perceived trustworthiness. Keywords: Covid19; TAM; User acceptance; Tertiary institutions; LMS; Perceived enjoyment; Perceived trustworthiness

Modelling the adoption of electronic vehicle diagnostic technology for vehicle repairs: A structural equation modelling approach

The introduction of emission legislation around the world has led to an increasing number of innovations including the use of on-board diagnostic techniques for pin-pointing faults on vehicles. Generally, the adoption of Electronic Vehicle Diagnostic Technology (EVDT) for the repair of vehicles is low in Ghana. The objective of the study was to develop an Electronic Vehicle Diagnostic Technology Acceptance Model (EVDTAM) to assess the mechanics' intention to use and the actual use of EVDT for the repair of vehicles. The model developed was derived from the original Technology Acceptance Model (TAM) by considering the technological factors (perceived ease of use and perceived usefulness), and Decomposed Theory of Planned Behaviour (DTPB). In this research, a convenient sampling technique was used to select a population of 384 auto mechanic master craftsmen from the Volta and Greater Accra Regions in Ghana where automobile repair workshops especially local and corporate garages were dominant.The results indicated that the majority of the structural relationships supported the hypotheses with positive significant links. The technology facilitating condition emerged as the strongest predictor of intention to use EVDT. The adoption of EVDT was strongly predicted by the resource facilitating conditions. The empirical findings of the study are a step forward towards filling the research gap given the fact that testing and validation of the EVDTAM model has not been performed by any other study. The proposed model was found acceptable per the requirements of measurement and structural model testing. Practical and theoretical implications were also discussed.

Determinants of e-Learning Services: Indonesian Open University

The Internet has been massively utilized for educational purposes during the last ten years with many platforms, including e-Learning Services (e-LS). This survey study aimed to report factors affecting the intention to use e-LS in the Indonesian Open University (OU) context. The original technology acceptance model (TAM) was extended, involving seven variables: facilitating conditions, perceived enjoyment, subjective norms, perceived ease of use, usefulness, attitudes, and intention to use. The survey questionnaire was piloted prior to the main data collection. Through random sampling, 2787 out of 341,956 Indonesian OU students responded to the questionnaire. The main data were analyzed through partial least square structural equation modeling (PLS-SEM) procedures. For predicting intention to use e-LS, the strongest affecting factor is attitudes. Subjective norms play a bigger than perceived usefulness in predicting intention to use. In predicting attitudes, perceived ease of use is the strongest predictor, followed by perceived usefulness. Subjective norms, facilitating conditions, and perceived enjoyment are significant predictors of perceived usefulness and perceived ease of use. Recommendations were elaborated for all stakeholders: researchers, tutors, policymakers, and OU students.

An Application of Partial Least Squares Structural Equation Modeling (PLS-SEM) to Examining Farmers’ Behavioral Attitude and Intention towards Conservation Agriculture in Bangladesh

Despite being widely advocated as a climate-smart farming system, the adoption of conservation agriculture (CA) among Bangladeshi farmers has remained surprisingly low. Evidence indicates that farmers’ behavior regarding the adoption and continuation of CA is affected by their socioeconomic and psychological factors. This study combined the Technology Acceptance Model (TAM) and Diffusion of Innovation (DOI) theories to examine the socio-psychological determinants of Bangladeshi farmers’ behavior regarding the adoption of CA. The proposed model included both reflective and formative measurements. Based on data collected from 201 CA farmers, this research used a variance-based structural equation modeling (PLS-SEM) approach to test the model. The analysis showed that the components of this integrated model explained more variance (Intention: 48.9%; Attitude: 59.2%) than the original TAM framework (Intention: 45.8%; Attitude: 54.5%). Farmers’ attitudes toward the continuation of CA were most influenced by the Relative Advantage (RA) of CA (β = 0.337). The low level of Complexity (β = 0.225) and Compatibility (β = 0.273) of CA had a significant positive effect on attitude. In a campaign to encourage farmers to act more sustainably, interventions should emphasize CA’s long-term benefits, such as its effects on soil, yield, and the environment.

Enhancing students’ English language learning via M-learning: Integrating technology acceptance model and S-O-R model

With the impact of COVID-19, many university students may not be able to learn English in the physical classroom in a traditional way. Students' English learning effectiveness and outcome were threatened when English learning was forced to turn online. Thus, a variety of technological media and platforms to improve their learning outcomes are in need. Mobile learning (M-learning) that involves interacting with other devices through mobile devices and wireless networks can also be a solution to improve students' online English learning effectiveness. In order to explore the learning behaviors and attitudes of university students when learning English with M-learning, this study integrated technology acceptance model and Stimulus Organism Response model including the concepts of perceived convenience, curiosity and self-efficacy in addition to the original technology acceptance model to verify university students’ usage cognition and attitude toward English M-learning. This study disseminated surveys to 10 targeted universities/colleges and collected 1432 valid surveys. This study implemented Smart-PLS 4.0 to examine structural model and verify the hypotheses. Results indicated that perceived convenience have positive impact on perceived ease of use, perceived usefulness and attitude toward using; there is a significant and positive relationship among perceived ease of use, perceived usefulness, attitude toward using and intention to using; curiosity and self-efficacy have positive impact on intention to using. Based on the findings, this study further provides abundant theoretical insights and practical significance on language learning.

Modelling the adoption of agro-advisory mobile applications: a theoretical extension and analysis using result demonstrability, trust, self-efficacy and mobile usage proficiency

PurposeThis paper aims to explore the determinants of intention towards the use of agro-advisory mobile applications by extending the technology acceptance model (TAM) with addition of the following constructs: result demonstrability (RD), trust, self-efficacy (SE) and mobile usage proficiency (MUP).Design/methodology/approachThe study employed a survey on farmers (n = 446), which was analysed through structural equation modelling using Analysis of Moment Structures (AMOS).FindingsThe results show that RD and farmer's trust on agro-advisory mobile apps (AAMA) positively impact their perceptions of usefulness. Also, farmer's SE and MUP positively affect their perceptions of ease of using AAMA. Further, interestingly, farmer's attitude towards the AAMA fully mediates the relationship between perceived usefulness and perceived ease of use on intention to use them.Research limitations/implicationsUnderstanding the antecedents of agro-advisory mobile application offers a unique contribution to policymakers, private firms, and non-government organizations by proving key insights on the acceptance of agriculture based mobile technologies in context of developing nations.Originality/valueTo the best of author's knowledge, this is one of the first research enquiries on the adoption of agro-advisory mobile applications. The new theoretical framework adds to the original TAM and offers novel insights that are helpful in augmenting the current understanding on AAMA and their acceptance by the beneficiaries.

Modeling basic school teachers acceptance of instructional technology in advancing mathematical pedagogy in Ghana

In this study a modified technology acceptance model (TAM) was used to examine factors that determine information and communication technology (ICT) adoption in junior high school (JHS) mathematics classrooms in Ghana. The study purely employed a quantitative research method. A cross sectional survey was conducted using 180 basic school mathematics instructors in the Kumasi Metro using a questionnaire. Multiple stepwise regression was used as the statistical technique to analyze the data. The study found that usage training, perceived ease of use (PEU), perceived usefulness (PU), and attitude towards use (ATU), had a direct and positive impact on the JHS mathematics instructors’ intentions to utilize ICT for academic purposes. It was likewise concluded that the perceived ICT usefulness was found to be the most influential factor for the instructors’ intention to utilize ICT. The significant effect of usage training was statistically supported against the original TAM constructs utilized in this study. Also, the result from the study further reveals that mathematics facilitators intension to use ICT is not merely based on PEU, PU, and ATU, but fostered through educational culture to train their teaching staff in order to increase their competence and ability to use the instructional technology for academic purposes.

Predicting the secondary school students’ intention to use e-learning technologies

Technology acceptance studies are interesting because they are practical and theoretically helpful in explaining the adoption and intention to use a particular technology. There is a large amount of research on e-learning and other technologies in the literature, but there is limited evidence to explain why secondary school students’ intention to use e-learning. This study explains secondary school students’ intentions to use e-learning with an extended Technology Acceptance Model (TAM). TAM is a useful theory to explain how people adopt new technologies in different fields. Data were collected from 2739 secondary school students in Turkey (Mage = 11.95). Confirmatory factor analysis (CFA) and structural equation modelling (SEM) were used to test the conceptual model. The results are consistent with the original TAM model. The most critical variable affecting secondary school students’ intention to use e-learning technologies is enjoyment. The results show that there may be differences in the intention to use e-learning technologies for secondary school students in different cultures and contexts.

The extended technology acceptance model for Web 2.0 technologies in teaching

Web 2.0-based learning enables collaborative learning and knowledge sharing and makes an important contribution to student learning. This study extended the original Technology Acceptance Model (TAM) by considering the effects of tool literacy, metacognitive self-regulation, subjective norm, facilitating conditions, and institutional support to understand pre-service teachers' intentions to use Web 2.0 technology in their courses. The sample data of 318 responses were from pre-service teachers. Structural equation modeling results showed a good fit for the extended model, indicating that metacognitive self-regulation and subjective norm had a significant influence on perceived ease of use and perceived usefulness, while institutional support and enabling conditions were not significantly associated with them. In addition, perceived ease of use and perceived usefulness influenced attitude, which in turn had a significant effect on intention. Furthermore, perceived ease of use, perceived usefulness, and attitude acted as significant mediators of behavioral intention. The indirect effect of perceived ease of use on perceived usefulness and attitude, and the indirect effect of perceived usefulness on attitude were also significant. Overall, the current study helps researchers and practitioners better understand future teachers' intentions to use Web 2.0 technologies in their courses.

The intentions of agricultural professionals towards diffusing wireless sensor networks: Application of technology acceptance model in Southwest Iran

BackgroundWireless Sensor Networks (WSNs) are environmentally friendly technology supporting more timely and cost-effective farm management and production. Noting that the adoption rate of WSNs is particularly low in emerging and developing countries, agricultural professionals can play a key role in facilitating WSN adoption through dedicated training and extension activities. ObjectiveThis study examines the determinants of the agricultural professionals' intention towards WSN diffusion using an extended version of the Technology Acceptance Model (TAM). MethodologyData was collected from 109 professionals in Khuzestan province, Southwest Iran. The data was analysed using a Structural Equation Modelling (SEM) approach in SPSS Amos. ResultsThe key constructs of an original TAM significantly affected the intention expressed by the professions and explained 40 % of its variance. By adding additional constructs of knowledge, confidence, social influence and facilitating conditions, the extended TAM significantly improved the explanatory power of the original model to 54 %. By adding control variables, the inclusive TAM explained 60 % of the variation in the professionals' intention. ConclusionThe findings of this study provide a clearer understanding of the decisive factors affecting the promotion of WSNs and can provide a valuable frame for policy and decision-makers to develop WSN policy and practical plans.