Antecedents and outcomes of internet usage within organisations in Yemen: An extension of the Unified Theory of Acceptance and Use of Technology (UTAUT) model

From theory to practice: An integrated TTF-UTAUT study on electric vehicle adoption behavior

In Industry 4.0, the adoption of new technology has played a major role in the transportation sector, especially in the electric vehicles (EVs) domain. Nevertheless, consumer attitudes towards EVs have been difficult to gauge but researchers have tried to solve this puzzle. The prior literature indicates that individual attitudes and technology factors are vital to understanding users' adoption of EVs. Thus, the main aim is to meticulously investigate the unexplored realm of EV adoption within nations traditionally reliant on oil, exemplified by Saudia Arabia. By integrating the "task technology fit" (TTF) model and the "unified theory of acceptance and usage of technology" (UTAUT), this research develops and empirically validates the framework. A cross-section survey approach is adopted to collect 273 valid questionnaires from customers through convincing sampling. The empirical findings confirm that the integration of TTF and UTAUT positively promotes users' adoption of EVs. Surprisingly, the direct effect of TTF on behavioral intentions is insignificant, but UTAUT constructs play a significant role in establishing a significant relationship. Moreover, the UTAUT social influence factor has no impact on the EVs adoption. This groundbreaking research offers a comprehensive and holistic methodology for unravelling the complexities of EV adoption, achieved through the harmonious integration of two well-regarded theoretical frameworks. The nascent of this research lies in the skilful blending of technological and behavioral factors in the transportation sector.

Technology Adoption and Human Resource Management Practices: The Use of Artificial Intelligence for Recruitment in Bangladesh

Artificial intelligence (AI) is now considered indispensable in undertaking operational activities, especially in the area of human resource analytics. However, in practice, the rate of the adoption of such modern algorithms in organisations is still in its early stages. Consequently, the primary objective of this study is to identify the main antecedents of the adoption of AI-based technologies in recruitment, using the lens of the unified theory of acceptance and use of technology (UTAUT) model, alongside perceived credibility and moderating variables, in the context of an emerging nation in South Asia, namely Bangladesh. Data were collected from 283 human resource professionals employed in different manufacturing and service firms in Bangladesh through the administration of a questionnaire, which was analysed by applying PLS-SEM. The outcomes of the study show that all the direct hypothesised relationships were found to be significant, apart from the extended variable of perceived credibility. However, no moderating effect of gender or firm size was found in any of the hypothesised propositions. Finally, policy implications and recommendations for future researchers are proposed.

Older people's intention to use medical apps during the COVID-19 pandemic in China: an application of the Unified Theory of Acceptance and Use of Technology (UTAUT) model and the Technology of Acceptance Model (TAM)

Previous studies on older adults' intention to adopt medical apps during irregular circumstances like the COVID-19 outbreak are still in its infancy. In order to fill this knowledge gap, we developed a theoretical framework based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model and the Technology of Acceptance Model (TAM) to explain Chinese older people's willingness to use medical apps during the COVID-19 pandemic. We collected 1,318 online questionnaires during the first wave of the pandemic in China in early 2020. We employed structural equation modelling to analyse the data, and the results show that (a) attitudes towards using apps influence older people's intention to use apps significantly; (b) only two factors, perceived usefulness and facilitating conditions, which were proposed in the UTAUT model, significantly predicted the older adults' intention to use apps, but not others; and (c) perceived usefulness, perceived ease of use, subjective norm and facilitating conditions all significantly impact attitudes towards using apps. Further mediation analysis found that attitudes towards using apps significantly mediated the paths suggested in the original UTAUT model. Due to the online survey method we used, older people who do not use the internet were excluded from our sampling process. However, our timely research contributes to the existing literature by showcasing older people's usage of eHealth technology in public health emergencies. It also builds on the broader discussions on technology use by combining the TAM and the UTAUT model, highlighting the vital role of people's attitude towards using technology in shaping their intention to use it.

The role of institutional factors and cognitive absorption on students' satisfaction and performance in online learning during COVID 19

With the rise of the Covid-19 pandemic, there has been a severe negative impact on all aspects of life, whether it be a job, business, health, education, etc. As a result, institutions, schools, colleges and universities are being shut down globally to control the spread of Covid-19. Due to this reason, the mode of education has a dramatic shift from on-campus to online learning with virtual teaching using digital technologies. This sudden shift has elevated the stress level among the students because they were not mentally prepared for it, and hence their academic performance has been adversely affected. So, there needs to figure out the underlying process to make online learning more productive. Thus, to obtain this objective, the present study has integrated the modified Technology Acceptance Model (TAM), Task Technology Fit Model (TTF), DeLone and McLean Model of Information Systems Success (DMISM) and Unified Theory of Acceptance and Use of Technology (UTAUT) model. A sample of 404 students was obtained, where 202 students were from the top ten public sector universities, and 202 were from the top ten private sector universities of Punjab. Structural Equation Modelling (SEM) was used to analyze the hypothesized framework using AMOS. The results reveal that institutional factors positively impact students' performance mediated by user satisfaction and task technology fit. Similarly, institutional factors affect performance through mediation by user satisfaction and actual usage in sequence. Cognitive absorption was used as a moderator between institutional factors and user satisfaction. In the end, theoretical and practical inferences have also been discussed.

Adoption of AI-Enabled Tools in Social Development Organizations in India: An Extension of UTAUT Model

Social development organizations increasingly employ artificial intelligence (AI)-enabled tools to help team members collaborate effectively and efficiently. These tools are used in various team management tasks and activities. Based on the unified theory of acceptance and use of technology (UTAUT), this study explores various factors influencing employees' use of AI-enabled tools. The study extends the model in two ways: a) by evaluating the impact of these tools on the employees' collaboration and b) by exploring the moderating role of AI aversion. Data were collected through an online survey of employees working with AI-enabled tools. The analysis of the research model was conducted using partial least squares (PLS), with a two-step model - measurement and structural models of assessment. The results revealed that the antecedent variables, such as effort expectancy, performance expectancy, social influence, and facilitating conditions, are positively associated with using AI-enabled tools, which have a positive relationship with collaboration. It also concluded a significant effect of AI aversion in the relationship between performance expectancy and use of technology. These findings imply that organizations should focus on building an environment to adopt AI-enabled tools while also addressing employees' concerns about AI.

Human Resource Professionals' Intention to Use and Actual Use of Human Resource Information Systems

Human resource information systems (HRISs) are widely used and have a strategic impact on organizations. The fundamental objective of this paper is to reveal the predominant antecedents affecting their adoption and implementation by replicating the unified theory of acceptance and use of technology (UTAUT) model from a South Asian emergent country perspective. The study collected data from human resource professionals employed in manufacturing and service companies located in Bangladesh, which were analyzed by employing partial least squares-based structural equation modeling software. It was revealed that performance expectancy, social pressure, and facilitation conditions significantly influence the intention to use and the actual use of HRIS, but that user’s effort expectancy had no significant impact. The study contributes by enriching the previous findings and validating the results based on relevant literature. Furthermore, managerial implications, the limitations of the study and suggested future study directions are presented.

Factors Influencing the Acceptance of Mobile Collaborative Learning for the Continuous Professional Development of Teachers

The COVID-19 epidemic has not only triggered a worldwide health catastrophe, it has also affected learning processes all over the world. While COVID-19 was in its initial wave of transmission, educational systems around the world witnessed bitter experiences in the form of the closure of institutes or a shift to distance (or online) learning techniques. The delivery of quality education was affected the most where the educational system was already weak due to the unavailability of effective teachers’ professional development programs and the lack of the integration of technology. This study extends the conventional continuous professional development (CPD) model of in-service teachers adopted in the province of Sindh, Pakistan. The extensions are based on the integration of mobile technology and support for collaborative learning and ongoing assistance, which are missed in the current traditional model. To assess the acceptance and use of the app, an Mobile collaborative learning (MCL) based CPD acceptance framework is designed by combining chosen components from a generally recognized Unified theory of acceptance and use of technology (UTAUT2) and other well-recognized acceptance models for the acceptance and use of the technology. In the context of CPD, a total of 14 constructs have been selected which include performance expectancy; effort expectancy; facilitating conditions; hedonic motivation; mobility; knowledge acquisition; content and information quality; on-the-job support; reward; behavioral intention; engagement; interactivity with peer & experts; self-management and collaborative learning. Based on these constructs; a total of 13 hypotheses were developed with 55 measurement items. A total of 494 teachers participated in a two-week training session using the designed app. Based on the activity, a questionnaire was designed and distributed among the participants using WhatsApp groups during the academic year of 2021–2022. Out of 494 participants; 472 participants correctly filled in the questionnaires, which were selected for analysis. The data was analyzed using IBM SPSS version 21; and, for Structural Equation Modeling (SEM) analysis, IBM AMOS version 21 was used. According to the results, all thirteen hypotheses were found statistically significant showing the positive impact on the acceptance and use of the CPD app. The results of this study promote teachers’ and experts’ engagement and participation in CPD activities which not only improve the knowledge and skills of the learners but also impact their long-term professional development and success. This research may help the teachers’ training and related institutions to make better choices and develop a mobile collaborative learning system for school-based teacher support and training programs. As a basis, this study may also be used in other provinces of Pakistan and beyond to make it a CPD standard.

International students’ university decision quality: The effect of online environment quality, information-task fit, perceived usefulness and social influence

In the world of online marketing, higher education (HE) sectors still question the appropriateness of their online marketing strategies for disseminating suitable information to influence academic matriculation decisions. Different information sources have the potential to positively enhance students’ decision quality through different levels of utilization. This research investigated the influence of online environment quality on international students’ decision quality, and whether information quality (IQ) of the online environment predicts information-task fit (ITF), perceived usefulness and decision quality. The data used for this study was gathered from first- and second-year international students ( N = 308) at different universities across six countries. A structural equation modelling approach revealed the significant influence of online environment quality on the decision quality of international students’ university choice through the mediating perceptions of two levels of utilization, ITF and perceived usefulness. Furthermore, the moderating roles of website type and source type showed the significantly different influences of IQ on students’ decision quality. Implications for HE researchers and marketers in improving the online environment quality and marketing are provided.

Telemedicine acceptance during the COVID-19 pandemic: User satisfaction and strategic healthcare marketing considerations

A lot remains unexplored regarding the antecedents and outcomes of telemedicine acceptance from health service marketing perspective. This study addresses this gap by integrating the Health Belief Model and the Unified Theory of Acceptance and Use of Technology model in the context of generation Y and Z's response to the COVID-19 pandemic. Data collected from 293 respondents were analyzed using structural equation modeling. The results confirm theoretical rigor of integrating two models examining the antecedents and user satisfaction as an outcome of telemedicine acceptance. The findings also suggest marketing strategies for implementing telemedicine during pandemic. Future research directions are highlighted.

Modeling the Factors that Influence Ghanaian Entrepreneurs to Adopt e-Commerce

This study investigated the factors that influence Ghanaian entrepreneurs to adopt e-commerce. Cross-sectional data was gathered from 520 entrepreneurs in the most populous and industrious regions in Ghana. The unified theory of acceptance and use of technology (UTAUT) was employed to effectively understand the unexplored phenomenon of e-commerce adoption among Ghanaian entrepreneurs. Partial Least Square-Structural Equation Modeling (PLS-SEM) was used to test the hypothesized relationships. The findings indicate that performance expectancy, effort expectancy, and social influence (SI) positively and significantly influenced the behavioral intention (BI) to adopt e-commerce. Facilitating conditions (FC) and BI had a significant positive relationship with the adoption of e-commerce.

Understanding the determinants of online pharmacy adoption: a two-staged SEM-neural network analysis approach

Purpose

This study aims to understand the determinants of online pharmacy or epharmacy adoption among young consumers in Bangladesh using an extended unified theory of acceptance and use of technology (UTAUT) model.

Design/methodology/approach

A structured Google Docs questionnaire was sent out to 420 respondents using messenger service; 285 useable responses were finally extracted. Data were empirically validated using the two-staged structural equation model (SEM)-neural network analysis approach.

Findings

The robustness of the classical UTAUT model remains intact in the context of online pharmacy adoption. Among the integrated variables, while perceived trust and health literacy were found significant, perceived risk and personal innovativeness were found insignificant in determining consumers’ intention to adopt online pharmacy. The neural network analysis provided further verification of these findings derived from the SEM.

Practical implications

The findings of this study would facilitate in devising better strategies for entering or expanding online pharmacy business in developing countries such as Bangladesh.

Originality/value

The originality of the current study relates to the two-fold contributions of this study. First, while this study extended the classical UTAUT model by incorporating perceived risk, perceived trust, personal innovativeness and health literacy, the inclusion of the following two variables is fresh within the extant online pharmacy literature. Second, by using a two-staged SEM-neural network analysis approach, this study advances the past studies on e-commerce adoption in pharmaceutical settings and provides a general understanding of the customers of developing countries.

The Impact of Task Technology Fit on Employee Job Performance

In today’s dynamic global business economy, the use of information technology has become an essential and pervasive technique for organizational success. In this essence, the present study extends the unified theory of acceptance and use of technology with task technology fit to see how underpinned factors impact on employee intention to adopt information technology and enhance employee job performance. In order to test the proposed research model, the respondent’s observations are required. Therefore, an administrative survey was conducted towards Saudi public organizations. A survey questionnaire was distributed among middle-level managers working in HR departments of Saudi Public organizations. In response to administrative survey 398 questionnaires were returned with a response rate of 79.6%. Among 398 questionnaires 38 were discarded due to inappropriate answers and 358 questionnaires were finally used for structural equation modelling. The inclusion criterion was that HR managers must have knowledge about online services offering by respective organizations to employees. For data analysis, structural equation modelling approach was used. Results indicate that the extended the unified theory of acceptance and use of technology model has substantial power and explained 77.0% variance in employee intention to adopt the technology. The effect size analysis showed that within extended model effort expectancy was the most important factor. The predictive relevance of the model was also adequate. Finally, importance of performance matrix analysis suggested that managers and policymakers should focus on effort expectancy, task characteristics, technology characteristics and supervisor support to boost employee intention to adopt technology and employee job performance. Keywords: employee job performance, innovation valance, intention to adopt technology, moderating analysis, structural equation modelling, supervisory support.