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

Abstract

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.

A Model for the Acceptance and Use of Online Meeting Tools

“…Similarly, the study found a significant positive effect of the perceived usefulness and ease of use of these tools on employees' intention to use them. These results are consistent with studies [39,40] in the literature using online meeting tools.…”

“…The desire of students to use web-based video conferencing for learning is influenced by factors such as ease of use, usefulness, and complexity [60]. Individuals who perceive online meeting tools as advantageous and straightforward may possess a favorable attitude towards this technology and, consequently, are inclined to use it even after the pandemic ends [38][39][40]. As users master online meeting platforms and recognize their utility, they develop favorable attitudes towards these platforms and intend to use them extensively.…”

“…TAM postulates that an individual's perceived usefulness precedes their attitude toward it [28,30]. Studies on online meeting tools have demonstrated a significant correlation between these two constructs [39][40][41][42][43]. In a study regarding the approval of e-learning among students, a crucial factor impacting the use of online meeting tools by the instructor was the perceived usefulness [61].…”

“…Extending TAM to evaluate the acceptance level of online meeting tools has become a growing trend with the pandemic. Earlier research [38][39][40][41][42][43] has explored the acceptance of online meeting platforms among educators and learners by incorporating diverse external dimensions such as perceived risk, system quality, social influence, and perceived interactivity with TAM. The results of prior studies indicate that both students and teachers are open to accepting online meeting platforms.…”

“…Another study [38] examined the effects of social isolation, technostress, and personality factors on the intention to use these tools, enlisting students, instructors, and university staff as the target group. During the pandemic, a study [39] was conducted to investigate the factors influencing the adoption of online meeting tools in public higher education institutions. The target audience for this research was the staff of a university, and the UTAUT2 model variables were employed to analyze the data.…”