
Factors Affecting Public Employees’ Acceptance of Video Conferencing Tools: An Extended TAM Perspective
By: Baki Bulduk and Erhan Ünal
References
- Agrebi, S., & Jallais, J. (2015). Explain the intention to use smartphones for mobile shopping. Journal of Retailing and Consumer Services, 22, 16–23. 10.1016/j.jretconser.2014.09.003
- Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Prentice-Hall.
- Alajmi, M. A., & Said Ali, M. (2021). Video-conference platforms: understanding the antecedents and consequences of participating in or attending virtual conferences in developing countries. International Journal of Human–Computer Interaction, 38(13), 1195–1211. 10.1080/10447318.2021.1988237
- Al-Madadha, A., Al Khasawneh, M. H., Al Haddid, O., & Al-Adwan, A. S. (2022). Adoption of telecommuting in the banking industry: a technology acceptance model approach. Interdisciplinary Journal of Information, Knowledge, and Management, 17, 443–470. 10.28945/5023
- Al-Samarraie, H. (2019). A scoping review of videoconferencing systems in higher education: learning paradigms, opportunities, and challenges. The International Review of Research in Open and Distributed Learning, 20(3). 10.19173/irrodl.v20i4.4037
- Alturki, U., & Aldraiweesh, A. (2022). Adoption of Google Meet by postgraduate students: the role of task technology fit and the TAM model. Sustainability, 14(23), Article
15765 . 10.3390/su142315765 - Aydın, İ. (2014). Hizmet içi eğitim el kitabı [In-service training handbook]. Pegem Akademi.
- Baber, H. (2021). Modelling the acceptance of e-learning during the pandemic of COVID-19 – A study of South Korea. The International Journal of Management Education, 19(2), Article
100503 . 10.1016/j.ijme.2021.100503 - Bandura, A. (1997). Self-efficacy: The exercise of control. Freeman.
- Baturay, M. (2010). Satisfaction and technology acceptance levels of medical instructors taking pediatric electrocardiography course through videoconferencing. Mersin University Journal of the Faculty of Education, 6(1), 145–160.
- Bozkurt, A., Karakaya, K., Turk, M., Karakaya, Ö., & Castellanos-Reyes, D. (2022). The impact of COVID-19 on education: A meta-narrative review. TechTrends, 66(5), 883–896. 10.1007/s11528-022-00759-0
- Bozkurt, A., & Sharma, R. C. (2020). Emergency remote teaching in a time of global crisis due to CoronaVirus pandemic. Asian Journal of Distance Education, 15(1), i–vi. 10.5281/zenodo.3778083
- Camilleri, M. A., & Camilleri, A. C. (2022). The acceptance of learning management systems and video conferencing technologies: Lessons learned from COVID-19. Technology, Knowledge and Learning, 27(4), 1311–1333. 10.1007/s10758-021-09561-y
- Carvalho, S. (2000). Modernizing and globalizing the learning environment: Video-conferencing in education. In Proceedings of the University of West Indies Small States Conference 2000 (pp. 299–309).
Commonwealth of Learning . - Carville, S., & Mitchell, D. R. (2000). “It’s a bit like Star Trek”: The effectiveness of video conferencing. Innovations in Education and Training International, 37(1), 42–49. 10.1080/135580000362070
- Cavus, N., & Sekyere-Asiedu, D. (2021). A comparison of online video conference platforms: Their contributions to education during COVID-19 pandemic. World Journal on Educational Technology: Current Issues, 13(4), 1162–1173. 10.18844/wjet.v13i4.6329
- Chatzoglou, P. D., Sarigiannidis, L., Vraimaki, E., & Diamantidis, A. (2009). Investigating Greek employees’ intention to use web-based training. Computers & Education, 53(3), 877–889. 10.1016/j.compedu.2009.05.007
- Chen, J. L. (2011). The effects of education compatibility and technological expectancy on e-learning acceptance. Computers & Education, 57(2), 1501–1511. 10.1016/j.compedu.2011.02.009
- Cheon, J., Lee, S., Crooks, S. M., & Song, J. (2012). An investigation of mobile learning readiness in higher education based on the theory of planned behavior. Computers & Education, 59(3), 1054–1064. 10.1016/j.compedu.2012.04.015
- Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189–211. 10.2307/249688
- Correia, A. P., Liu, C., & Xu, F. (2020). Evaluating videoconferencing systems for the quality of the educational experience. Distance Education, 41(4), 429–452. 10.1080/01587919.2020.1821607
- Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results [Doctoral dissertation, Massachusetts Institute of Technology].
https://dspace.mit.edu/bitstream/handle/1721.1/15192/14927137-MIT.pdf - Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. 10.2307/249008
- Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003. 10.1287/mnsc.35.8.982
- Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111–1132. 10.1111/j.1559-1816.1992.tb00945.x
- Deng, Z. (2013). Understanding public users’ adoption of mobile health service. International Journal of Mobile Communications, 11(4), 351–373. 10.1504/IJMC.2013.055748
- Denstadli, J. M., Julsrud, T. E., & Hjorthol, R. J. (2012). Videoconferencing as a mode of communication: A comparative study of the use of videoconferencing and face-to-face meetings. Journal of Business and Technical Communication, 26(1), 65–91. 10.1177/1050651911421125
- Ducey, A. J., & Coovert, M. D. (2016). Predicting tablet computer use: An extended Technology Acceptance Model for physicians. Health Policy and Technology, 5(3), 268–284. 10.1016/j.hlpt.2016.03.010
- El-Gayar, O., Moran, M., & Hawkes, M. (2011). Students’ acceptance of tablet PCs and implications for educational institutions. Journal of Educational Technology & Society, 14(2), 58–70.
- Escobar-Rodriguez, T., & Monge-Lozano, P. (2012). The acceptance of Moodle technology by business administration students. Computers & Education, 58(4), 1085–1093. 10.1016/j.compedu.2011.11.012
- Finlay, K. A., Trafimow, D., & Villarreal, A. (2002). Predicting exercise and health behavioral intentions: Attitudes, subjective norms and other behavioral determinants. Journal of Applied Social Psychology, 32(2), 342–356. 10.1111/j.1559-1816.2002.tb00219.x
- Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 39–50. 10.1177/002224378101800104
- Gabbiadini, A., Paganin, G., & Simbula, S. (2023). Teaching after the pandemic: The role of technostress and organizational support on intentions to adopt remote teaching technologies. Acta Psychologica, 236, Article
103936 . 10.1016/j.actpsy.2023.103936 - Giday, D. G., & Perumal, E. (2024). Students’ perception of attending online learning sessions post-pandemic. Social Sciences & Humanities Open, 9, Article
100755 . 10.1016/j.ssaho.2023.100755 - Grant, M. M., & Cheon, J. (2007). The value of using synchronous conferencing for instruction and students. Journal of Interactive Online Learning, 6(3), 211–226.
- Hacker, J., Vom Brocke, J., Handali, J., Otto, M., & Schneider, J. (2020). Virtually in this together–how web-conferencing systems enabled a new virtual togetherness during the COVID-19 crisis. European Journal of Information Systems, 29(5), 563–584. 10.1080/0960085X.2020.1814680
- Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. 10.2753/MTP1069-6679190202
- Hashim, J. (2008), Factors influencing the acceptance of web-based training in Malaysia: applying the technology acceptance model. International Journal of Training and Development, 12, 253–264. 10.1111/j.1468-2419.2008.00307.x
- Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115–135. 10.1007/s11747-014-0403-8
- Hong, X., Zhang, M., & Liu, Q. (2021). Preschool teachers’ technology acceptance during the COVID-19: An adapted technology acceptance model. Frontiers in Psychology, 12, Article
691492 . 10.3389/fpsyg.2021.691492 - Huang, F., Teo, T., & Scherer, R. (2020). Investigating the antecedents of university students’ perceived ease of using the Internet for learning. Interactive Learning Environments, 30(6), 1060–1076. 10.1080/10494820.2019.1710540
- Huang, T. (2023). Factors affecting students’ online courses learning behaviors. Education and Information Technologies, 28(12), 16485–16507. 10.1007/s10639-023-11882-7
- Hurst, E. J. (2020). Web conferencing and collaboration tools and trends. Journal of Hospital Librarianship, 20(3), 266–279. 10.1080/15323269.2020.1780079
- Hussain, S. B., Sumiea, E. H. H., Ahmad, M. H., Kumar, S., & Moshood, T. D. (2023). Factors affecting the public higher education institution (PHEI) acceptance of online meetings applications during COVID-19 pandemic: An empirical study. Journal of Applied Research in Higher Education, 15(4), 1146–1166. 10.1108/JARHE-03-2022-0082
- Ji, Z., Yang, Z., Liu, J., & Yu, C. (2019). Investigating users’ continued usage intentions of online learning applications. Information, 10(6), Article
198 . 10.3390/info10060198 - Karaali, D., Gumussoy, C. A., & Calisir, F. (2011). Factors affecting the intention to use a web-based learning system among blue-collar workers in the automotive industry. Computers in Human Behavior, 27(1), 343–354. 10.1016/j.chb.2010.08.012
- Koç, N. E. (2022). An example of a digital disease: causes of the “zoom” fatigue and its effects on employees. Turkish Online Journal of Design Art and Communication, 12(2), 383–400. 10.7456/11202100/012
- Lee, Y. -H., Hsieh, Y.-C., & Chen, Y.-H. (2013). An investigation of employees’ use of e-learning systems: applying the technology acceptance model. Behaviour & Information Technology, 32(2), 173–189. 10.1080/0144929X.2011.577190
- Lee, Y.-H., Hsieh, Y.-C., & Ma, C.-Y. (2011). A model of organizational employees’ e-learning systems acceptance. Knowledge-Based Systems, 24(3), 355–366. 10.1016/j.knosys.2010.09.005
- Luarn, P., & Lin, H.-H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21(6), 873–891. 10.1016/j.chb.2004.03.003
- Marangunić, N., & Granić, A. (2015). Technology acceptance model: a literature review from 1986 to 2013. Universal Access in the Information Society, 14, 81–95. 10.1007/s10209-014-0348-1
- Miao, R., Wu, Q., Wang, Z., Zhang, X., Song, Y., Zhang, H., Sun, Q., & Jiang, Z. (2017). Factors that influence users’ adoption intention of mobile health: a structural equation modeling approach. International Journal of Production Research, 55(19), 5801–5815. 10.1080/00207543.2017.1336681
- Nalaka, G. P. S., Ranagala, D. L., Gunarathne, G. R. N., Dhammasiri, M., & Prabashini, I. G. N. (2023). Academics’ intention to use zoom meetings for teaching. Anatolian Journal of Education, 8(2), 99–112. 10.29333/aje.2023.827a
- Nguyen, N. B. (2021). An overview of distance education during the pandemic: Student-teacher communication over videoconferencing platforms [Bachelor’s thesis, Corvinus University of Budapest: Hungary].
https://szd.lib.uni-corvinus.hu/14791/ - Nguyen, X.-A., Pho, D.-H., Luong, D. H., & Cao, X.-T.-A. (2021). Vietnamese students’ acceptance of using video conferencing tools in distance learning in Covid-19 pandemic. Turkish Online Journal of Distance Education, 22(3), 139–162. 10.17718/tojde.961828
- Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill.
- Okabe-Miyamoto, K., Durnell, E., Howell, R. T., & Zizi, M. (2022). Video conferencing during emergency distance learning impacted student emotions during COVID-19. Computers in human behavior reports, 7,
100199 . 10.1016/j.chbr.2022.100199 - Onur, Z. K. (2021). The use of zoom in teaching Turkish as a foreign language during the COVID-19 epidemic teacher opinions. Journal of Sustainable Education Studies, 2(3), 15–27.
- Panteli, N., & Dawson, P. (2001). Video conferencing meetings: Changing patterns of business communication. New Technology, Work and Employment, 16(2), 88–99. 10.1111/1468-005X.00079
- Park, N., Rhoads, M., Hou, J., & Lee, K. M. (2014). Understanding the acceptance of teleconferencing systems among employees: An extension of the technology acceptance model. Computers in Human Behavior, 39, 118–127. 10.1016/j.chb.2014.05.048
- Park, Y., Son, H., & Kim, C. (2012). Investigating the determinants of construction professionals’ acceptance of web-based training: An extension of the technology acceptance model. Automation in Construction, 22, 377–386. 10.1016/j.autcon.2011.09.016
- Riedl, R. (2022). On the stress potential of videoconferencing: definition and root causes of Zoom fatigue. Electronic Markets, 32(1), 153–177. 10.1007/s12525-021-00501-3
- Saheb, T. (2020). An empirical investigation of the adoption of mobile health applications: integrating big data and social media services. Health and Technology, 10(5), 1063–1077. 10.1007/s12553-020-00422-9
- Schepers, J., & Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44(1), 90–103. 10.1016/j.im.2006.10.007
- Smyth, R. (2005). Broadband videoconferencing as a tool for learner-centred distance learning in higher education. British Journal of Educational Technology, 36(5), 805–820. 10.1111/j.1467-8535.2005.00499.x
- Sonmez, A., & Ozdamar, N. (2024). Examining the factors related to learners’ intention and usage continuity of online learning. Open Praxis, 16(2), 195–207. 10.55982/openpraxis.16.2.570
- Soria-Barreto, K., Ruiz-Campo, S., Al-Adwan, A. S., & Zuniga-Jara, S. (2021). University students intention to continue using online learning tools and technologies: An international comparison. Sustainability, 13(24), Article
13813 . 10.3390/su132413813 - Steelman, Z. R., & Soror, A. A. (2017). Why do you keep doing that? The biasing effects of mental states on IT continued usage intentions. Computers in Human Behavior, 73, 209–223. 10.1016/j.chb.2017.03.027
- Taş, M., & Kiraz, A. (2023). A Model for the acceptance and use of online meeting tools. Systems, 11(12), Article
558 . 10.3390/systems11120558 - Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176. 10.1287/isre.6.2.144
- Teo, T. (2009). Modelling technology acceptance in education: A study of pre-service teachers. Computers & Education, 52(2), 302–312. 10.1016/j.compedu.2008.08.006
- Teo, T., Faruk Ursavaş, Ö., & Bahçekapili, E. (2011). Efficiency of the technology acceptance model to explain pre-service teachers’ intention to use technology: A Turkish study. Campus-Wide Information Systems, 28(2), 93–101. 10.1108/10650741111117798
- Teo, T., Huang, F., & Hoi, C. K. W. (2018). Explicating the influences that explain intention to use technology among English teachers in China. Interactive Learning Environments, 26(4), 460–475. 10.1080/10494820.2017.1341940
- Teo, T., & Noyes, J. (2011). An assessment of the influence of perceived enjoyment and attitude on the intention to use technology among pre-service teachers: A structural equation modeling approach. Computers & Education, 57(2), 1645–1653. 10.1016/j.compedu.2011.03.002
- Teo, T., Ursavaş, Ö. F., & Bahçekapılı, E. (2012). An assessment of pre-service teachers’ technology acceptance in Turkey: A structural equation modeling approach. Asia-Pacific Education Researcher, 21(1), 191–202.
- Terzis, V., & Economides, A. A. (2011). The acceptance and use of computer based assessment. Computers & Education, 56(4), 1032–1044. 10.1016/j.compedu.2010.11.017
- Terzis, V., Moridis, C. N., & Economides, A. A. (2013). Continuance acceptance of computer based assessment through the integration of user’s expectations and perceptions. Computers & Education, 62, 50–61. 10.1016/j.compedu.2012.10.018
- Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 125–143. 10.2307/249443
- Tırpan, E. C., & Bakırtaş, H. (2024). Technology Acceptance Model 3 in Understanding Employee’s Cloud Computing Technology. Global Business Review, 25(1), 117–136. 10.1177/0972150920957173
- Torres, C. C. (2021). Adaptation and validation of technostress creators and technostress inhibitors inventories in a Spanish-speaking Latin American country. Technology in Society, 66, Article
101660 . 10.1016/j.techsoc.2021.101660 - Ursavaş, Ö. F. (2014). Modeling and examining teachers’ ICT acceptance (Publication No. 356715) [Doctoral dissertation, Gazi University, Türkiye].
- Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342–365. 10.1287/isre.11.4.342.11872
- Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. 10.1111/j.1540-5915.2008.00192.x
- Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. 10.1287/mnsc.46.2.186.11926
- Verkijika, S. F. (2019). Digital textbooks are useful but not everyone wants them: The role of technostress. Computers & Education, 140,
103591 . 10.1016/j.compedu.2019.05.017 - Wang, X., & Yu, X. (2024). Art Students’ Technostress, Perceived Usefulness, Satisfaction, and Continuance Intention to Use Mobile Educational Applications. Sage Open, 14(2). 10.1177/21582440241260206
- Wu, R., & Yu, Z. (2023). The influence of social isolation, technostress, and personality on the acceptance of online meeting platforms during the COVID-19 pandemic. International Journal of Human-Computer Interaction, 39(17), 3388–3405. 10.1080/10447318.2022.2097779
- Yazici, H. J. (2025). Learner acceptance of video conferencing technologies and e-professionalism. Education and Information Technologies, 30, 1821–1847. 10.1007/s10639-024-12880-z
- Zobeidi, T., Homayoon, S. B., Yazdanpanah, M., Komendantova, N., & Warner, L. A. (2023). Employing the TAM in predicting the use of online learning during and beyond the COVID-19 pandemic. Frontiers in Psychology, 14, Article
1104653 . 10.3389/fpsyg.2023.1104653
DOI: https://doi.org/10.55982/openpraxis.17.3.799 | Journal eISSN: 2304-070X
Language: English
Page range: 467 - 484
Submitted on: Dec 3, 2024
Accepted on: Mar 5, 2025
Published on: Aug 11, 2025
Published by: International Council for Open and Distance Education (ICDE)
In partnership with: Paradigm Publishing Services
Keywords:
© 2025 Baki Bulduk, Erhan Ünal, published by International Council for Open and Distance Education (ICDE)
This work is licensed under the Creative Commons Attribution 4.0 License.