Factors affecting the public higher education institution (PHEI) acceptance of online meetings applications during COVID-19 pandemic: an empirical study

PurposeIn order to ensure effectiveness of staff's performance using online meetings applications during coronavirus disease (COVID-19), having the behavioural intention is mandatory for staff to measure, test, and manage the staff's data. Understanding of Public Higher Education Institution (PHEI) staffs' intention and behaviour toward online meetings platforms is needed to develop and implement effective and efficient strategies. The objectives of this paper to identify the factors that affect staff to use online meetings applications, to develop a model that examining the factors that affect PHEI staff to online meetings applications and to validate the proposed model. This study used a cross-sectional quantitative correlational study with using UTAUT2 model by validating the model and mediating variables to enhance the model's explanatory power and to make the model more applicable to PHEI staff's behavioural intention.Design/methodology/approachThe data were collected in Malaysia from March to May 2021. The survey took place using Google form and was send to PHEI staff for answer. This research particularly chooses PHEI as the location to carry out the research due to two main factors. Statistical analysis and hypotheses were tested using structural equation modelling based on the optimisation technique of partial least squares. SmartPLS software, Version 3.0 (Hair et al., 2010) was used to conduct the analysis. A conceptualised estimation model was "drawn in” the partial least squares structural equation modeling (PLS-SEM) to analyse the consequences of the variables' relationships. In essence, the PLS-SEM simulation was carried out in a model by assessing and computing various parameters that included elements like validity, durability, and item loading. Henseler et al. (2009) suggested a two-step method that includes PLS model parameter computing. This is accomplished by first solving the estimation model in the structural model independently before calculating the direction coefficients. The results of data analysis using SmartPLS findings and interpretation of the data are addressed. The questionnaire was extensively examined to ensure that the data obtained were presented in a clear and intelligible manner, with the use of figures, and graphs.FindingsThis current study found that the usability of the material, the reliability of operating, the impact of the PHEI staff's views on its usage, and finally the familiarity with the online meetings platforms influenced PHEI staff's behavioural intention for adoption and long-term use of online meeting platforms using UTAUT2. The staff's behavioural intention for using online meeting platforms was significantly influenced by the effort expectancy, facilitating conditions and habit of online meeting platforms. There was a clear association between "Habit” and "Behavioural Intention” for the usage of information technology in learning in several studies (El-Masri and Tarhini, 2017;Uur and Turan, 2018;Mosunmola et al., 2018;Venkatesh et al., 2003). As a consequence of the utility of online meeting platforms in daily staff meetings and learning activities, this technology has been adopted.Originality/valueThis study used UTAUT2 and structural equations modelling in this study to assess respondents' perspectives on the use of online meetings platforms in PHEI, since users' perspective is a significant factor in the adoption and acceptance of online meeting applications. Staff's behavioural intention to use online meeting platforms was effectively enhanced by "Effort Expectancy,” "Facilitating Conditions” and "Habit” in this study. The study shows that identifying PHEI staff's perspectives will effectively increase the staff's aversion to utilising online meeting platforms for online meetings purposes.

Factors affecting the use of accounting and finance technology during the pandemic crisis

The recent COVID-19 pandemic, which led to lockdowns and new working norms, has influenced business and accounting transactions in significant ways. This phenomenon and its longer-term impacts are still under-researched and remain unexplored in emerging countries, particularly Malaysia. Therefore, the current study intended to determine the actions taken by Malaysian organizations, specifically in their accounting and finance functions, in response to the COVID-19 crisis. Online survey questionnaires were distributed to collect data. The questionnaires comprised several sections, including demographic information of the respondents and factors affecting users' intentions to use technology for accounting and finance functions in the face of the COVID-19 crisis. This research adopted the Unified Theory of Acceptance and Use of Technology (UTAUT) model as a theoretical basis from which to evaluate the research objectives. The findings showed that only performance expectancy is related to user intention, while other factors, such as effort, attitude, social influence, self-efficacy, and anxiety, display the opposite effect. This empirical study suggests that accounting and finance functions in Malaysia still lag behind in terms of the technology used by employees. In addition, organizations, particularly government departments, are not ready to adopt a fully integrated scientific accounting and finance system. © 2023 Conscientia Beam. All Rights Reserved.

Acceptance of Mobile Learning Technology by Teachers: Influencing Mobile Self-Efficacy and 21st-Century Skills-Based Training

This study aimed to investigate the factors influencing the acceptance of mobile learning technology for 21st-century skills-based training among teachers in Saudi Arabia and Pakistan. This study adopted the Unified Theory of Acceptance and Use of Technology (UTAUT) model, which included constructs such as performance expectancy, effort expectancy, facilitating conditions, social influence, mobile self-efficacy, student self-efficacy, behavioural intention, 21st-century skills-based training, and creative thinking skills. A survey was conducted with 619 teachers from Saudi Arabia and Pakistan who participated in a two-week mobile learning-based training session. The data were analysed using structural equation modeling (SEM). The results show that all hypotheses were supported, indicating a positive relationship between the constructs and the acceptance and use of mobile learning technology for 21st-century skills-based training. This study's findings suggest that by emphasising factors such as performance expectancy, effort expectancy, facilitating conditions, social influence, mobile self-efficacy, and student self-efficacy when designing mobile learning interventions, teachers will be more likely to accept and use mobile learning technology for 21st-century skills-based training and contributed to sustainability by providing increased access to quality education.

A new contextual and comprehensive application of the UTAUT2 model post‐COVID‐19 pandemic in higher education

This study examines tertiary students' behavioural intention to resume face‐to‐face mode of study, post‐COVID‐19. A modified UTAUT2 model of nine factors and a moderator is used to investigate the impact of these factors on developing country's tertiary students' behavioural intention. The influence of these students' behavioural intention on se behaviour is also examined. Using a quantitative research approach, data were gathered from 419 students at a regional university using convenience sampling technique. Data were analysed to test and validate the proposed model using covariance‐based structural equation modelling. The study's findings reveal significant positive relationships between social influence, hedonic motivation, facilitating conditions, commitment, behavioural intention and use behaviour. However, it did not find performance expectancy, effort expectancy, price value, trust and comfortability, reporting any significant positive influence on behavioural intentions. Additionally, the moderating analysis shows that COVID‐19 fear did not moderate or strengthen the association between behavioural intentions and use behaviour, given the insignificant interaction effect of COVID‐19 fear. This study provides novelty in the contextual application of the modified UTAUT2 model, post‐COVID‐19. The addition of three additional constructs (trust, commitment and comfortability) has further improved the predictive power of the model. Lastly, the new construct that emerged in recent literature, COVID‐19 fear, has been tested for the first time within the UTAUT2 model as a moderator between behavioural intentions and use behaviour. In terms of practical implications, this study first adds to the current literature on higher education, after the COVID‐19 situation, being useful to education scholars. Second, it also offers specific suggestions to educational institutions and policymakers who fund universities. Such suggestions include: involving students' families in orientation and open day events, featuring family and friend support in promotional activities, upgrading facilities, including more teaching and learning sessions with team‐based assessments, encouraging comfortable interactions and continuously practising COVID‐19 safety protocols. [ FROM AUTHOR] Copyright of Higher Education Quarterly is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Self-Protective Dining Behavior: An Investigation on Consumer's Use of Online Food Delivery Service

This study aims to investigate how consumer's use of online food delivery (OFD) services is driven by its self-protective nature. Drawing on protection motivation theory, the unified theory of use and acceptance of technology, and diffusion of innovation theory, an integrated model was tested with 1,000 empirical data points to explain consumers' OFD use during the pandemic. Results confirmed the self-protective nature of OFD use by uncovering a significant positive effect of fear of COVID-19 on consumers' OFD ordering frequency. Perceived vulnerability contributed more strongly to an individual's fear of COVID-19 than perceived severity in dining activities. These findings theoretically expand the current understanding of OFD services and provide practical implications for OFD platforms, restaurateurs, and governments.

The Acceptance and Use of Social Media in Public Libraries During the COVID-19 Pandemic Based on UTAUT Model in Khuzestan Province, Iran

Present study examines the acceptance and use of social media by public librarians during the COVID-19 pandemic based on the Unified Theory of Acceptance and Use of Technology model. Simple random method based on Morgan table was used, and 175 public librarians were selected to participate in this study. A questionnaire was used to collect data, and SPSS statistical software was used for data analysis. Findings revealed that the Unified Theory of Acceptance and Use of Technology model can be applied to the admission test for public libraries in the context of using social media during the pandemic.

IDENTIFYING HEALTHCARE WORKERS' INTENTION TOWARD TELEHEALTH IN INDONESIA DUE TO COVID-19 PANDEMIC

Background: Healthcare sectors adopted various steps during the Covid-19 pandemic to prevent virus transmission, including limiting patient numbers. Telehealth can be an alternative solution since healthcare institutions can provide services without direct contact. Aims: This research aims to analyze healthcare workers' intentions in Indonesia toward telehealth using the unified theory of acceptance and use of technology (UTAUT) framework with additional variables. Methods: A literature review was undertaken to develop a framework tested using Partial Least Square-Structural Equation Modeling (PLS-SEM). This study was conducted with Indonesian healthcare institutions in Bandung and Surakarta. Participants consisted of doctors and nurses. Results: Of 200 participants, this finding showed effort expectancy, social influence, facilitating conditions, self-efficacy, and technology anxiety influenced the intention to adopt telehealth (p-Value ≤ 0.05). However, performance expectancy and perceived security and data have no significant influence (p-Value > 0.05). This study discovered that performance expectancy is influenced by effort expectancy (β = 0.727), while effort expectancy is influenced by self-efficacy (β = 0.642). Conclusion: Indonesian healthcare institutions must be concerned with factors affecting telehealth implementation, especially with data security, which has proven insignificant. Further research is required to optimize the application. © 2022, Airlangga University. All rights reserved.

Factors Affecting Adoption of Telemedicine for Virtual Healthcare Services in Indonesia

Background: The utilization of virtual healthcare services, particularly telemedicine, has been accelerated by the COVID-19 pandemic. Although the pandemic is no longer the primary concern, telemedicine still holds potential for long-term adoption. However, implementing telemedicine in Indonesia as an online platform for remote healthcare delivery still faces issues, despite its potential. Further investigation is required to identify the factors that affect its adoption and develop strategies to surmount implementation challenges. Objective: This study aims to examine and enrich knowledge about the adoption of telemedicine in Indonesia. Methods: A cross-sectional survey was conducted through an online questionnaire to collect data. Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) was employed by integrating with several factors, such as eHealth Literacy, Privacy Concerns, and Trust. Gender and age were considered as moderating variables. Data samples were analyzed using Partial Least Square - Structural Equation Modeling (PLS-SEM). Results: The findings suggest that performance expectancy, effort expectancy, social influence, eHealth literacy, and trust have a significant impact on adults' behavioral intention to use telemedicine. However, facilitating condition, price value, and privacy concern do not show any significant effects on adults' Behavioral Intention to Use Telemedicine. Conclusion: This study highlights the importance of understanding adoption factors to develop effective strategies. Results show performance expectancy, effort expectancy, social influence, eHealth literacy, and trust are significant factors, while facilitating condition, price value, and privacy concern are not. The UTAUT2 model is a good predictive tool for healthcare adoption. To increase usage intention, several aspects must be considered in the implementation of telemedicine. © 2023 The Authors. Published by Universitas Airlangga.

Acceptance, drivers, and barriers to use eHealth interventions in patients with post-COVID-19 syndrome for management of post-COVID-19 symptoms: a cross-sectional study.

Background: Post-COVID-19 syndrome is a new and debilitating disease without adequate treatment options. eHealth could be a reasonable approach for symptom management. Objectives: This study aims to evaluate the acceptance for eHealth interventions for symptom management in individuals with post-COVID-19 syndrome, as well as drivers and barriers influencing acceptance. Design: Cross-sectional study. Methods: This study was conducted from January 19 until 24 May 2022. Recruitment took place with a web-based survey. Acceptance and predictors of eHealth interventions were measured by the extended UTAUT model. Included in the model were the core predictor performance expectancy, social influence, and effort expectancy. Previously diagnosed mental illness was estimated and mental health by using the well-established Generalized Anxiety Disorder Scale-7 and the Patient Health Questionnaire Depression Scale. The effect of sociodemographic and medical data was assessed. Multiple hierarchical regression analyses as well as group comparisons were performed. Results: 342 individuals with post-COVID-19 syndrome were examined. The acceptance of eHealth interventions for symptom management was moderate to high (M = 3.60, SD = 0.89). Acceptance was significantly higher in individuals with lower/other education, patients with moderate to severe symptoms during initial COVID-19 infection, still significantly impaired patients, and individuals with a mental illness. Identified predictors of acceptance were age (ß = .24, p < .001), current condition including moderate (ß = .49, p = .002) and still significantly impaired (ß = .67, p < .001), digital confidence (ß = .19, p < .001), effort expectancy (ß = .26, p < .001), performance expectancy (ß = .33, p < .001), and social influence (ß = .26, p < .001). Conclusion: Patients with post-COVID-19 syndrome reported a satisfying level of acceptance and drivers and barriers could be identified. These factors need to be considered for the implementation and future use of eHealth interventions.

Enhancing Value Co-Creation through the Lens of Dart Model, Innovation, and Digital Technology: An Integrative Supply Chain Resilient Model

The global supply chain process has been badly affected by the COVID-19 pandemic. Consequently, firms search for factors that influence supply chain resilience and improve firm operational performance. The current research develops an integrated resilient supply chain model that combines factors underpinned DART model, innovation, digital technology, and value co-creation to investigate supply chain resilience during the COVID-19 pandemic. The research framework was empirically tested with a data set of 329 responses from employees working in logistics firms. the study find that supply chain resilience is determined by value co-creation, the DART model, innovation, and digital technology. The factors underpinning the DART model, including dialogue, access, risk assessment, and transparency, have positively impacted value co-creation. The structural model shows that dialogue has a positive impact on developing value co-creation between manufacturing firms and stakeholders, Empirical investigation revealed that value co-creation in supply chain operations is estimated by dialogue, access, risk assessment, transparency, innovation, and digital technology and revealed substantial variance R-2 71.9% in measuring value co-creation. This research is significant as it develops a resilient supply chain model with the combination of the DART model, innovation, digital technology, and value co-creation and investigates supply chain resilience during the COVID-19 pandemic. Although current research contributes to theory, practice, and method, disclosing research limitations opens numerous avenues for future researchers. This study does not claim to include all factors that impact the value co-creation process in supply chain operations. For instance, other factors, such as IT infrastructure, commitment, and integrative quality, may positively influence value co-creation. Second, supply chain resilience is determined by value co-creation and network capability. Therefore, the research encourages academicians and policymakers to investigate the supply chain resilience phenomenon with other market-oriented facts. future researchers are suggested to investigate the current research model in longitudinal method.

Adoption of video consultations during the COVID-19 pandemic.

Background: Video consultations have the potential to play a significant role for the future of healthcare by solving some of the imminently arising healthcare challenges, as pointed by the European Commission in Europe and the National Academy of Medicine in the United States of America. This technology can improve quality, efficiency, and enhance access to healthcare. Objective: The aim of this study is to explore and understand individual video consultations acceptance drivers. Methods: An extended technology acceptance model was created based on the diffusion of innovation theory (DOI), unified theory of acceptance and use of technology (UTAUT), health belief model (HBM), and concerns for information privacy framework (CFIP). 346 valid responses were collected through an online questionnaire, and the partial least squares (PLS) modeling approach was used to test the model. Results: The model explained 77.6 % (R2) of the variance on intention to use, and 71.4 % (R2) of the variance in attitude. The predictors of intention to use are attitude (beta = 0.504, p-value<0.001), performance expectancy (beta = 0.196, p-value = 0.002), and COVID-19 (beta = 0.151, p-value<0.001). The predictors of attitude are performance expectancy (beta = 0.643, p-value>0.001), effort expectancy (beta = 0.138, p-value = 0.001), and COVID-19 (beta = 0.170, p-value<0.001). Conclusions: This research model highlights the importance of creating extended acceptance models to capture the specificities of each technology in healthcare. The model created helps to understand the most important drivers of video consultation acceptance, highlighting the importance of the COVID-19 pandemic and perceived health risks.

Exploring the Factors Affecting Learners' Adoption Intention of MOOC in Higher Education during the COVID-19 Pandemic

The COVID-19 epidemic has had a huge impact on all education systems throughout the world. The lockdown policy caused higher education to find alternative teaching solutions to serve students' needs. Consequently, MOOCs have become a fascinating solution for several universities. However, the evidence from existing research still needs to be better understood by significant factors to support learners during COVID-19. This study examined the factors influencing students' adoption intention of MOOCs in developing countries during the coronavirus outbreak. This research reports the online survey of 1,384 university students enrolled in Thai MOOC as the primary part of the curriculum. The extended UTAUT2 was proposed and analyzed using a structural equation model to improve the comprehension of students' adoption intention on Thai MOOC. The result found Performance Expectancy, Hedonistic Motivation, Habit, and Local Language Support significantly influence MOOCs adoption intentions. While Habit was found to be the most significant to students' adoption intention, only gender had a moderating effect on the relationship between Habit and Adoption intention. The overall proposed model explained 84% of the variance in MOOC adoption intention of university students in Thailand during the COVID-19 pandemic. © 2023 IEEE.

Testing the Impact of Social Isolation on Students' Acceptance of Learning Management Systems After the COVID-19 Crisis Using a Modified UTAUT Model

After more than two years of the beginning of Covid-19 crisis, this research work investigates the students' acceptance towards utilizing learning management systems (LMSs) as a useful supporting learning medium while most of higher education institutions over the world have adopted these systems to become an indispensable, promising teaching tool and considering the distance learning as compliance to the conditions of social isolation is case of any crisis. This article analyzes the most significant factors effecting the adoption and led to the acceptance of LMSs through the higher education across 423 undergraduate and postgraduate students from several universities in Jordan. By applying the structural equation modelling, the results reveal that all proposed determinants have an impact on the adoption of distance learning, with noted significant impact for social isolation. The infection anxiety and students' level have moderated these effects on the behavioral intentions and actual use of learning management systems and show significant impact on them.

Views and Needs of Students, Parents, and Teachers on Closed-Circuit Television, Proximity Trackers, and Access Cards to Facilitate COVID-19 Contact Tracing in Schools: Thematic Analysis of Focus Groups and Interviews.

BACKGROUND: Contact tracing is considered a key measure in preventing the spread of infectious diseases. Governments around the world adopted contact tracing to limit the spread of COVID-19 in schools. Contact tracing tools utilizing digital technology (eg, GPS chips, Bluetooth radios) can increase efficiency compared to manual methods. However, these technologies can introduce certain privacy challenges in relation to retention, tracking, and the using and sharing of personal data, and little is known about their applicability in schools. OBJECTIVE: This is the second of two studies exploring the potential of digital tools and systems to help schools deal with the practical challenges of preventing and coping with an outbreak of COVID-19. The aim was to explore the views, needs, and concerns among secondary school stakeholders (parents, teachers, pupils) regarding the implementation of three digital tools for contact tracing: access cards, proximity tracking, and closed-circuit television (CCTV). METHODS: Focus groups and interviews were conducted with secondary school students, parents, and teachers. The topic guide was informed by the Unified Theory of Technology and Acceptance. Data-driven and theory-driven approaches were combined to identify themes and subthemes. RESULTS: We recruited 22 participants. Findings showed that there is no single solution that is suitable for all schools, with each technology option having advantages and limitations. Existing school infrastructure (eg, CCTV and smart/access cards technology) and the geography of each school would determine which tools would be optimal for a particular school. Concerns regarding the cost of installing and maintaining equipment were prominent among all groups. Parents and teachers worried about how the application of these solutions will affect students' right to privacy. Parents also appeared not to have adequate knowledge of the surveillance technologies already available in schools (eg, CCTV). Students, who were mostly aware of the presence of surveillance technologies, were less concerned about any potential threats to their privacy, while they wanted reassurances that any solutions would be used for their intended purposes. CONCLUSIONS: Findings revealed that there is not one tool that would be suitable for every school and the context will determine which tool would be appropriate. This study highlights important ethical issues such as privacy concerns, balancing invasions of privacy against potential benefits, transparency of communication around surveillance technology and data use, and processes of consent. These issues need to be carefully considered when implementing contact tracing technologies in school settings. Communication, transparency, and consent within the school community could lead to acceptance and engagement with the new tools.

Factors that impacted mobile-payment adoption in China during the COVID-19 pandemic.

The Unified Theory of Acceptance and Use of Technology (UTAUT) is a potential paradigm for explaining technology adoption and can be applied to a wide range of scenarios. During the COVID-19 (C-19) outbreak in China, mobile-payment platforms (Mpayment) were used extensively in everyday life because they allowed people to avoid direct and indirect connections during transactions, adhere to social-distancing guidelines, and support social-economic stabilization. By exploring the technological and psychological variables that influenced user Mpayment-adoption intentions during the C-19 pandemic, this study broadens the literature on technology adoption in emergency circumstances and expands the UTAUT. A total of 593 complete samples were collected online, with SPSS used for data analysis. The empirical findings reveal that performance expectancy, trust, perceived security, and social influence all had a significant influence on Mpayment acceptance during the C-19 outbreak, with social distancing having the greatest impact, followed by fear of C-19. Interestingly, perceived-effort expectancy had a negative influence on payment acceptance. These findings suggest that future studies should apply the expanded model to different countries and areas to investigate the impact of the C-19 pandemic on Mpayment acceptance.

Predicting students' continuance use of learning management system at a technical university using machine learning algorithms

PurposeThis study aims to investigate factors that could predict the continued usage of e-learning systems, such as the learning management systems (LMS) at a Technical University in Ghana using machine learning algorithms.Design/methodology/approachThe proposed model for this study adopted a unified theory of acceptance and use of technology as a base model and incorporated the following constructs: availability of resources (AR), computer self-efficacy (CSE), perceived enjoyment (PE) and continuance intention to use (CIU). The study used an online questionnaire to collect data from 280 students of a Technical University in Ghana. The partial least square-structural equation model (PLS-SEM) method was used to determine the measurement model's reliability and validity. Machine learning algorithms were used to determine the relationships among the constructs in the proposed research model.FindingsThe findings from the study confirmed that AR, CSE, PE, performance expectancy, effort expectancy and social influence predicted students' continuance intention to use the LMS. In addition, CIU and facilitating conditions predicted the continuance use of the LMS.Originality/valueThe use of machine learning algorithms in e-learning systems literature has been rarely used. Thus, this study contributes to the literature on the continuance use of e-learning systems using machine learning algorithms. Furthermore, this study contributes to the literature on the continuance use of e-learning systems in developing countries, especially in a Ghanaian higher education context.

Using Utaut2 Model For Explaining Telemedicine Adoption, Evidence From Iran

Background and aims: With the epidemic of the COVID-19 virus and the increasing development of information and communication technology, an opportunity has emerged for medical and therapeutic service providers to develop telemedicine services. In the current research, the authors tried to explain people's turn to this technology by expanding the Unified Theory of Use and Acceptance of Technology 2 (UTAUT2) and adding the features of telemedicine services. Methods: The current research is applied from the point of view of the objective, and in terms of data collection, it is considered to be descriptive research, which is carried out by the correlation-causal method. The data collection tool is a standard questionnaire with a Likert scale, distributed by available sampling among the population with a history of using telemedicine services in Ahvaz city. Finally, 407 usable questionnaires were analyzed using SPSS and Smart PLS. Results: The results show that performance expectancy, effort expectancy, facilitating conditions, hedonic motivation, perceived product advantage, and perceived security have a significant and positive effect on the intention to use telemedicine. Moreover, the moderating role of innovativeness and gender was confirmed. Conclusion: UTAUT2 and some characteristics of telemedicine services can well explain the intention to use this technology in the context of COVID -19. In addition, considering the moderating role of personal innovation and gender in some relationships between the model and product features confirmed, it is necessary to pay attention to the individual characteristics of people using these technological services in the design of telemedicine services. © 2022 Iran University of Medical Sciences. All rights reserved.

Antecedents of E-learning in undergraduate entrepreneurship education

This study examines the factors that influence the intention and actual use of e-learning in entrepreneurship education by undergraduate students. The paper relies on a predictive study design and the partial least squares structural equation modelling to analyse data from a cluster sample of 599 students from the University of Cape Coast, Ghana. The results demonstrate that all the independent variables, assessed within a framework of an extended unified theory of acceptance and use of technology, determine students' intention to use e-learning in entrepreneurship education. Of particular importance are the preponderant effects of hedonic motivation, facilitating conditions and social influence on students' intention as well as the effect of intention and facilitating conditions on actual use of e-learning. A key implication of the findings is that students' continuous acceptance and use of e-learning in undergraduate entrepreneurship course delivery is contingent upon adequate presence of all the examined predictors of technology usage. © The Author(s) 2023.

Online-only learning during the COVID-19 pandemic. What determines accounting students' engagement?1

Objective: The paper aims to identify the factors that determine accounting students' engagement in online-only learning during the COVID-19 pandemic. Methodology/research approach: The unified theory of acceptance and use of technology (UTAUT) is used as a theoretical lens. Survey responses provided by accounting students participating in online-only courses at Polish universities between May and June 2020 are analyzed, and regression analysis is employed to verify the research hypotheses. Findings: According to our findings, student effort expectancy and performance signifi-cantly and positively influence their engagement in online-only learning. Age is also significant for student engagement, with younger students being more engaged in online-only learning than older ones. Originality/value: The study contributes to the literature on distance learning as it in-vestigates a relatively unexplored group of students in an unprecedented situation. The paper also proposes new measures to capture UTAUT factors. The findings are also relevant for practice. It seems that after the pandemic, online learning will continue to be used and ensuring student engagement will become more relevant than technological issues, already mastered by both sides of the educational process. © 2022 Stowarzyszenie Księgowych w Polsce.

Digitalization in higher education: does personal innovativeness matter in digital learning?

PurposeThe explosion of technology has revolutionized the teaching and learning process in higher education. Students are using the digital technology to aid their learning process. In this sense, digital divide exists among students in higher education as they come from different socioeconomic backgrounds. Thus, this study aims to examine the digital usage among the students from the low-income families (B40) in higher education institutions.Design/methodology/approachThe data was drawn by using an online survey from the undergraduates (low-income families B40) in Malaysia higher education institutions. In total, 391 responses were collected. The data was analysed using structural equation modelling method.FindingsThe results showed that performance expectancy and facilitating conditions have a significant relationship with digital usage. In addition, personal innovativeness has positive significant effect on performance expectancy and effort expectancy.Research limitations/implicationsThis study sheds light on the students from the lower income family behaviour while using digital technologies for their learning purpose.Originality/valueThe study further contributes to the new knowledge on students from the low-income family's behaviour in using digital technology for their learning process.