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This study aims to identify the most significant factors that influence acceptance of e-learning in India. As e-learning has gained popularity in the wake of the COVID-19 pandemic and continues to be one of the most sustainable methods of education, it is pertinent to examine learners' perception towards its acceptance. There is limited literature available on this subject in India, especially factoring in impact of the pandemic.

This study empirically analyses data of 331 adult e-learners in India, who have enrolled for one of the following e-learning formats: higher education, private coaching, test preparation, re-skilling and online certifications, corporate training and hobby and language-related learning. Their perception is examined on the basis of a model developed using the Unified Theory of Acceptance and Use of Technology model. Data are analysed through structural equation modelling using SPSS and AMOS statistical tools.

The result of the study shows that Infrastructure Dependability, Effectiveness of Design and Content of Courses and Student's Competency with Computers are the top three factors impacting e-learning acceptance in India.

This study makes several theoretical contributions. Additionally, research findings and recommendations will facilitate education providers, corporates in the education industry and policymakers to focus on the significant areas for enhancing the acceptance of e-learning.

This study identifies and confirms important factors that influence e-learning acceptance and suggests opportunities for further in-depth research and analysis.

This research aims to examine the factors that may hinder or enable the adoption of e-learning systems by university students.

A conceptual framework was developed through extending the unified theory of acceptance and use of technology (performance expectancy, effort expectancy, hedonic motivation, habit, social influence, price value and facilitating conditions) by incorporating two additional factors, namely, trust and self-efficacy. Data were collected from students at two universities in England using a cross-sectional questionnaire survey between January and March 2015.

The results showed that behavioral intention (BI) was significantly influenced by performance expectancy, social influence, habit, hedonic motivation, self-efficacy, effort expectancy and trust, in their order of influencing the strength and explained 70.6 per cent of the variance in behavioral intention. Contrary to expectations, facilitating conditions and price value did not have an influence on behavioral intention.

The aforementioned factors are considered critical in explaining technology adoption but, to the best of the authors’ knowledge, there has been no study in which all these factors were modeled together. Therefore, this study will contribute to the literature related to social networking adoption by integrating all these variables and the first to be tested in the UK universities.

The purpose of this study was to investigate the factors that might influence the intention and use behaviour of e-learning systems by students in state universities in Sri Lanka.

The theoretical model for this study was primarily drawn from unified theory of acceptance and Use of Technology 2 (UTAUT2). Exogenous variables included performance expectancy, effort expectancy, social influence, work life quality, hedonic motivation, internet experience and facilitating condition, and their influence on behavioural intention and use behaviour were studied. Instrument was developed using validated items from past literature. Data for this quantitative study were collected from undergraduate and postgraduate students from 15 Sri Lankan state universities by self-administering and Web-form during second quarter of 2018. Structural equation modelling was used to see the insights from the valid data using IBM’s SPSS 25 and AMOS 22.

Results of the confirmatory factor analysis and subsequent evaluation of the structural model confirmed the proposed hypotheses, and it was found that constructs of UTAUT2 have a significant impact on and play an important role in behavioural intention to use and use behaviour of e-learning system by state university students in Sri Lanka.

The adoption of an e-learning system in Sri Lankan state universities is fairly low. Hence, investigation of what determinants might be contributing for adoption is important to enhance the learning experience of students and help them improve their knowledge. This paper contributes by delineating the factors that influence the acceptance and use of e-learning systems by students of state universities in Sri Lanka.

Conceptual model in this paper combines existing scientific knowledge grounded in theories of planned behavior, diffusion of innovation and a unified theory of acceptance and use of technology, while aiming to identify relevant determinants of continuous use of e-learning by employees who used e-learning in the past year at their workplace.

The authors developed and empirically tested the positive impact of professional, personal, IT and environmental factors on the continued use of e-learning among 672 employees across different sectors using the structural equation modeling technique.

Research results suggest that the most powerful determinant of continuous use of e-learning are personal factors. Environmental influences and technological aspects also exhibit a positive and significant impact on the continuous use of e-learning. Research hypothesis related to the positive influence of professional factors on the continuous use of e-learning has not been empirically confirmed. Also, results demonstrated that continued use of e-learning contributes to better individual business performance.

The practical contribution is threefold: to companies, education institutions and human resource managers. For companies, identification of key determinants will lead to a better understanding of employees needs regarding continuous job improvements. The findings can be used by educational institutions to design e-learning programs according to results and real value to employees. On the other hand, human resource managers can benefit from this study in terms of getting concrete factors that motivate employees for continuous job improvement.

The research sheds light on the proposed integrated model that tests the post-adoption of the continuous use of e-learning within an organizational context.

This article aims to study the determinants of e-learning acceptability by university students based on their experiences with distance learning during the coronavirus disease 2019 (COVID-19) pandemic.

A questionnaire was used to collect data from 448 students enrolled in a Moroccan business school's fourth and fifth years. The technology acceptance model (TAM) was the primary framework used for this analysis, into which variables from the expectation confirmation model were injected, namely facilitating conditions, social influence, expectation confirmation and satisfaction. The proposed conceptual model was tested and evaluated using the partial least squares structural equation modeling (PLS-SEM) technique. Then the authors have offered an in-depth analysis by employing the importance-performance map analysis (IPMA) approach.

The investigation suggested that the proposed measurement scale effectively assesses the factors impacting students' decision to continue using e-learning in the future. This study’s results show that e-learning acceptance depends significantly on the students' satisfaction, perceived ease of use (PEU) and perceived usefulness (PU). In contrast, the facilitating conditions are not a valid measurement scale to determine students' attitudes toward e-learning.

This is one of the first studies in the Moroccan context to evaluate e-learning acceptability by management students after COVID-19 using a unique research model.

This systematic review aims to assess the studies collected by identifying factors influencing the acceptance of e-learning systems before and during the current propagation of the COVID-19 pandemic.

This study undertook a literature review on the in-depth revision of studies published before 2021. The reviewed research papers meet the inclusion and exclusion criteria. A total of 97 out of 214 articles met the inclusion criteria and were subsequently used in this review.

The findings revealed that the survey questionnaire is the most common data collection instrument used regardless of the research objectives. 2019 was a remarkable year because of the emergence of the COVID-19 pandemic.

This systematic review relied on specific databases (ScienceDirect, Emerald, IEEE and Google Scholar) to search for the articles included in this paper. However, these databases may not comprehensively represent all papers published on e-learning using the technology acceptance model (TAM).

This paper suggests a guide for managers and scholars in educational institutions and acts as a roadmap for practitioners and academics in the educational field and policymakers. This research spotlights the significant factors influencing the acceptance and adoption of e-learning.

This research assessed articles that examined the TAM in e-learning and classified them according to their methodology, country of dissemination, context and distribution within the year of publication. This paper contributes to the body of knowledge in a way that will benefit stakeholders in an educational setting.

This study aims to examine the factors affecting behavioural intention to use E-learning during the COVID-19 pandemic. The study applies the unified theory of acceptance and use of technology 2 (UTAUT2) to identify the factors that predict intention to use E-learning. Also, the study examines the effect of personal innovativeness in information technology and perceived financial cost on intention to use E-learning.

The study adopted a cross-sectional quantitative study design involving 617 university students. The data was collected through an online survey due to the COVID-19 restrictions. The proposed hypotheses were analysed using partial least squares structural equation modelling.

The study found that personal innovativeness in information technology, perceived financial cost, performance expectancy, hedonic motivation and social influence have a significant effect on the intention to use E-learning. Contrary to expectation, habits, effort expectancy and facilitating conditions did not predict intention to use E-learning.

The study was conducted on university students and did not include other school-going students and working professionals. Also, the study sample was not drawn from many universities. The study used a quantitative approach. The use of a mixed-methods approach could provide deeper insights into the factors affecting the intention to use E-learning in developing countries.

The practical implications inform policymakers and educational institutions on how E-learning adoption can be enhanced. In this context, social influence, performance expectancy, hedonic motivation, personal innovativeness and perceived financial cost are identified as predictors of intention to use E-learning. This study has implications for the development of E-learning systems and the promotion of the use of E-learning in the context of developing countries.

The study is amongst the few studies from a developing economy to use the UTAUT2 model to examine students’ intention to use E-learning. The study proposes the inclusion of personal innovativeness in information technology and perceived financial cost as factors predicting intention to use E-learning. Again, the study adopts importance-performance matrix analysis to provide decisional areas where management may improve for successful E-learning acceptance and use.

This 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.

The 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.

The 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.

The 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.

The purpose of this study is to investigate the factors that affect students’ behavioral intentions to use virtual classrooms at Princess Sumaya University for Technology (PSUT) in Jordan.

A quantitative research approach was adopted, an online survey method was used and the data were collected among students at PSUT in Jordan. A total of 511 responses were usable for analysis. A structural equation modeling partial least squares technique was used to examine the hypothesized model.

The findings reveal that the proposed factors have direct and indirect relationships with behavioral intentions to use virtual classrooms. They show that students’ satisfaction has a direct influence on behavioral intention, while other variables such as instructor characteristics, virtual classroom quality, perceived self-efficacy, perceived organizational support, perceived ease of use and perceived usefulness have an indirect effect on behavioral intentions to use virtual classrooms.

The study was conducted at PSUT in Jordan, which could limit the generalizability of the findings. Furthermore, the present study measured students’ behavioral intentions to use virtual classrooms and future research should consider the actual use of virtual classrooms.

The findings of this study offer significant and useful information to policymakers, instructors, developers and students regarding the use of virtual classrooms in universities. Based on students’ needs and readiness, the findings identify which factors to consider when developing an e-learning system to enhance learning and teaching performance.

This study extends existing knowledge by developing a conceptual model to identify the key factors of virtual classroom adoption in higher education institutions in Arab countries. This study contributes to the literature in the context of e-learning by validating an extended technology acceptance model from an Arab countries perspective and considering the differences in culture, learning style and physical environment compared to developed countries.

In this paper, the authors review the extant literature on e-learning effectiveness in higher education (HE) to investigate how teachers are affected by the actions that the management of higher education institutions (HEIs) need to take to address the success factors that are critical for e-learning effectiveness. E-learning, in the context of this study, encompasses the delivery of and access to a coordinated collection of learning materials and instructions over an electronic medium using a web server to provide the materials and a web browser to access them.

To address the study's aims the authors employ a narrative literature review methodology. Since the area under review is comprehensive and it entails the examination of several topics, the authors have selected this methodology to ensure thorough coverage, and a narrative literature review approach can provide the required degree of thoroughness as it covers a wide range of topics within the thematic area under review. The authors focus on contemporary scientific studies published between January 2017 and May 2022 on how teachers involved in e-learning are affected by management actions taken to achieve success factors for e-learning effectiveness within the HE sector, after identifying and grouping the success factors identified in prior literature into dimensions that reinforce effectiveness.

The authors of the present study have identified and outlined the most prevalent success factor dimensions by performing a narrative review of the extant literature on the topics of e-learning effectiveness and success factors, and by grouping the various success factors identified into the overarching dimensions presented. These dimensions must also be examined in terms of their relevant importance to the most significant e-learning stakeholder groups. Prior studies have made attempts to obtain relevant stakeholder views on success factors for e-learning, with the student perspective naturally being the most widely covered point of view in terms of e-learning success factors prioritization. More studies are needed that tackle the teachers' perspective as well, since this would enable researchers to determine how teachers view e-learning effectiveness success factors.

The authors also discover that the main success factors in literature are not discussed nearly enough from teachers' perspectives. The authors, therefore, highlight the importance of addressing teachers' perspectives, mainly because this will reinforce teacher acceptance of the e-learning system adopted by an HEI, and the authors also outline future research avenues through which the perception of teachers could be obtained. The authors have identified the technique of knowledge management as a potential method to involve teachers in the decision-making process concerning the management of e-learning more, by taking their views into account and documenting them. The authors have discerned that teachers' acceptance of e-learning would be reinforced by supportive management actions since as a result, teachers see improvements in their technological literacy and pedagogical skills, and this would bring about increased motivation, satisfaction and acceptance of e-learning systems.