Open Access
Issue |
E3S Web Conf.
Volume 426, 2023
The 5th International Conference of Biospheric Harmony Advanced Research (ICOBAR 2023)
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Article Number | 02004 | |
Number of page(s) | 6 | |
Section | Innovative Management and Sustainable Society | |
DOI | https://doi.org/10.1051/e3sconf/202342602004 | |
Published online | 15 September 2023 |
- S. Rahi, M. M. Othman Mansour, M. Alghizzawi, and F. M. Alnaser, “Integration of UTAUT model in Internet banking adoption context: The mediating role of performance expectancy and effort expectancy,” J. Res. Interact. Mark., vol. 13, no. 3, pp. 411–435, Aug. 2019, doi: 10.1108/JRIM- 02-2018-0032. [Google Scholar]
- K. Stecula and R. Wołniak, “Advantages and disadvantages of e-learning innovations during COVID-19 pandemic in higher education in Poland,” J. Open Innov. Technol. Mark. Complex., vol. 8, no. 3, p. 159, Sep. 2022, doi: 10.3390/joitmc8030159. [CrossRef] [Google Scholar]
- M. D. Lytras, A. C. Serban, M. J. T. Ruiz, S. Ntanos, and A. Sarirete, “Translating knowledge into innovation capability: An exploratory study investigating the perceptions on distance learning in higher education during the COVID-19 pandemic - the case of Mexico,” J. Innov. Knowl., vol. 7, no. 4, p. 100258, Oct. 2022, doi: 10.1016/j.jik.2022.100258. [CrossRef] [Google Scholar]
- W. O. Oyediran, A. M. Omoare, M. A. Owoyemi, A. O. Adejobi, and R. B. Fasasi, “Prospects and limitations of e-learning application in private tertiary institutions amidst COVID-19 lockdown in Nigeria,” Heliyon, vol. 6, no. 11, p. e05457, Nov. 2020, doi: 10.1016/j.heliyon.2020.e05457. [CrossRef] [PubMed] [Google Scholar]
- T. Aikina and L. Bolsunovskaya, “Moodle-based learning: Motivating and demotivating factors,” Int. J. Emerg. Technol. Learn. IJET, vol. 15, no. 2, pp. 239–248, Jan. 2020. [CrossRef] [Google Scholar]
- H. Mulyono, G. Suryoputro, and S. R. Jamil, “The application of WhatsApp to support online learning during the COVID-19 pandemic in Indonesia,” Heliyon, vol. 7, no. 8, p. e07853, Aug. 2021, doi: 10.1016/j.heliyon.2021.e07853. [CrossRef] [PubMed] [Google Scholar]
- P. A. Suri, M. E. Syahputra, A. S. H. Amany, and A. Djafar, “Systematic literature review: The use of virtual reality as a learning media,” Procedia Comput. Sci., vol. 216, pp. 245–251, Jan. 2023, doi: 10.1016/j.procs.2022.12.133. [CrossRef] [Google Scholar]
- V. A. Goodyear and K. M. Armour, “Young people’s health-related learning through social media: What do teachers need to know?,” Teach. Teach. Educ., vol. 102, p. 103340, Jun. 2021, doi: 10.1016/j.tate.2021.103340. [CrossRef] [Google Scholar]
- E. Chantavaridou, “What exactly is it that technical services does?: Promoting and advocating for technical services work to the academic community,” J. Acad. Librariansh., vol. 48, no. 4, p. 102536, Jul. 2022, doi: 10.1016/j.acalib.2022.102536. [CrossRef] [Google Scholar]
- I. L. Wu, P. J. Hsieh, and S. M. Wu, “Developing effective e-learning environments through e- learning use mediating technology affordance and constructivist learning aspects for performance impacts: Moderator of learner involvement,” Internet High. Educ., vol. 55, p. 100871, Oct. 2022, doi: 10.1016/j.iheduc.2022.100871. [CrossRef] [Google Scholar]
- C. M. Chen, “Personalized e-learning system with self-regulated learning assisted mechanisms for promoting learning performance,” Expert Syst. Appl., vol. 36, no. 5, pp. 8816–8829, Jul. 2009, doi: 10.1016/j.eswa.2008.11.026. [CrossRef] [Google Scholar]
- A. Chang, “UTAUT and UTAUT 2: A review and agenda for future research,” The Winners, vol. 13, no. 2, pp. 10–114, 2012. [CrossRef] [Google Scholar]
- Z. Hutabarat, I. N. Suryawan, R. Andrew, and F. P. Akwila, “Effect of performance expectancy and social influence on continuance intention in OVO,” J. Manaj., vol. 25, no. 1, pp. 125–140, 2021. [Google Scholar]
- S. Onaolapo and O. Oyewole, “Performance expectancy, effort expectancy, and facilitating conditions as factors influencing smart phones use for mobile learning by postgraduate students of the University of Ibadan, Nigeria,” Interdiscip. J. E- Ski. Lifelong Learn., vol. 14, pp. 095–115, 2018, doi: 10.28945/4085. [CrossRef] [Google Scholar]
- P. Utomo, F. Kurniasari, and P. Purnamaningsih, “The effects of performance expectancy, effort expectancy, facilitating condition, and habit on behavior intention in using mobile healthcare application,” Int. J. Community Serv. Engagem., vol. 2, no. 4, pp. 183–197, Nov. 2021, doi: 10.47747/ijcse.v2i4.529. [CrossRef] [Google Scholar]
- V. Venkatesh, J. Y. L. Thong, and X. Xu, “Consumer acceptance and use of information technology: Extending the Unified Theory of Acceptance and Use of Technology,” MIS Q., vol. 36, no. 1, pp. 157–178, 2012, doi: 10.2307/41410412. [CrossRef] [Google Scholar]
- Y. K. Dwivedi, N. P. Rana, A. Jeyaraj, M. Clement, and M. D. Williams, “Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a revised theoretical model,” Inf. Syst. Front., vol. 21, no. 3, pp. 719–734, Jun. 2019, doi: 10.1007/s10796-017- 9774-y. [CrossRef] [Google Scholar]
- C. W. Hsu and C. C. Peng, “What drives older adults’ use of mobile registration apps in Taiwan? An investigation using the extended UTAUT model,” Inform. Health Soc. Care, vol. 47, no. 3, pp. 258–273, Jul. 2022, doi: 10.1080/17538157.2021.1990299. [CrossRef] [PubMed] [Google Scholar]
- N. K. Jain, K. Bhaskar, and S. Jain, “What drives adoption intention of electric vehicles in India? An integrated UTAUT model with environmental concerns, perceived risk and government support,” Res. Transp. Bus. Manag., vol. 42, p. 100730, Mar. 2022, doi: 10.1016/j.rtbm.2021.100730. [Google Scholar]
- K. K. Twum, D. Ofori, G. Keney, and B. Korang-Yeboah, “Using the UTAUT, personal innovativeness and perceived financial cost to examine student’s intention to use e-learning,” J. Sci. Technol. Policy Manag., vol. 13, no. 3, pp. 713–737, Jan. 2021, doi: 10.1108/JSTPM-12-2020-0168. [Google Scholar]
- B. Chiparausha, O. B. Onyancha, and I. J. Ezema, “Factors influencing the use of social media by academic librarians in Zimbabwe: a UTAUT model analysis,” Glob. Knowl. Mem. Commun., vol. ahead-of-print, no. ahead-of-print, Jan. 2022, doi: 10.1108/GKMC-09-2021-0151. [Google Scholar]
- R. E. Sewandono, A. Thoyib, D. Hadiwidjojo, and A. Rofiq, “Performance expectancy of e-learning on higher institutions of education under uncertain conditions: Indonesia context,” Educ. Inf. Technol., Oct. 2022, doi: 10.1007/s10639-022-11074-9. [Google Scholar]
- T. H. Hassan, A. E. Salem, and S. A. Refaat, “The Impact of Eatmarna application usability on improving performance expectancy, facilitating the practice of rituals and improving spirituality feelings during Umrah amid the COVID-19 outbreak,” Religions, vol. 13, no. 3, Art. no. 3, Mar. 2022, doi: 10.3390/rel13030268. [CrossRef] [Google Scholar]
- A. M. Sayaf, M. M. Alamri, M. A. Alqahtani, and W. M. Alrahmi, “Factors influencing university students’ adoption of digital learning technology in teaching and learning,” Sustainability, vol. 14, no. 1, Art. no. 1, Jan. 2022, doi: 10.3390/su14010493. [CrossRef] [Google Scholar]
- H. V. Osei, K. O. Kwateng, and K. A. Boateng, “Integration of personality trait, motivation and UTAUT 2 to understand e-learning adoption in the era of COVID-19 pandemic,” Educ. Inf. Technol., vol. 27, no. 8, pp. 10705–10730, Sep. 2022, doi: 10.1007/s10639-022-11047-y. [CrossRef] [PubMed] [Google Scholar]
- C. Chet, S. Sok, and V. Sou, “The antecedents and consequences of study commitment to online learning at Higher Education Institutions (HEIs) in Cambodia,” Sustainability, vol. 14, no. 6, Art. no. 6, Jan. 2022, doi: 10.3390/su14063184. [CrossRef] [Google Scholar]
- I. Khan, N. Khan, F. Jazim, Y. H. Al-Mamary, M. Abdulrab, and A. M. Al-Ghurbani, “The effect of external factors in use of technology among Ha’il university academic faculty: evidence from Saudi Arabia,” J. Appl. Res. High. Educ., vol. 14, no. 4, pp. 1319–1339, Jan. 2021, doi: 10.1108/JARHE- 04-2021-0140. [Google Scholar]
- M. Jang, M. Aavakare, S. Nikou, and S. Kim, “The impact of literacy on intention to use digital technology for learning: A comparative study of Korea and Finland,” Telecommun. Policy, vol. 45, no. 7, p. 102154, Aug. 2021, doi: 10.1016/j.telpol.2021.102154. [CrossRef] [Google Scholar]
- M. A. Almaiah et al., “Determinants influencing the continuous intention to use digital technologies in higher education,” Electronics, vol. 11, no. 18, Art. no. 18, Jan. 2022, doi: 10.3390/electronics11182827. [Google Scholar]
- R. M. Wong and O. O. Adesope, “Meta-analysis of emotional designs in multimedia learning: A replication and extension study,” Educ. Psychol. Rev., vol. 33, no. 2, pp. 357–385, Jun. 2021, doi: 10.1007/s10648-020-09545-x. [CrossRef] [Google Scholar]
- V. Peñarroja, J. Sánchez, N. Gamero, V. Orengo, and A. M. Zornoza, “The influence of organisational facilitating conditions and technology acceptance factors on the effectiveness of virtual communities of practice,” Behav. Inf. Technol., vol. 38, no. 8, pp. 845–857, Aug. 2019, doi: 10.1080/0144929X.2018.1564070. [CrossRef] [Google Scholar]
- N. Taufik and M. H. Hanafiah, “Airport passengers’ adoption behaviour towards self- check-in Kiosk Services: The roles of perceived ease of use, perceived usefulness and need for human interaction,” Heliyon, vol. 5, no. 12, p. e02960, Dec. 2019, doi: 10.1016/j.heliyon.2019.e02960. [CrossRef] [PubMed] [Google Scholar]
- R. Saeed Al-Maroof, K. Alhumaid, and S. Salloum, “The continuous intention to use e-learning, from two different perspectives,” Educ. Sci., vol. 11, no. 1, p. 6, Dec. 2020, doi: 10.3390/educsci11010006. [CrossRef] [Google Scholar]
- S. Guoyan, A. Khaskheli, S. A. Raza, K. A. Khan, and F. Hakim, “Teachers’ self-efficacy, mental well-being and continuance commitment of using learning management system during COVID-19 pandemic: A comparative study of Pakistan and Malaysia,” Interact. Learn. Environ., pp. 1–23, Oct. 2021, doi: 10.1080/10494820.2021.1978503. [Google Scholar]
- J. F. Hair, M. Page, and N. Brunsveld, The essentials of business research methods fourth edition. New York, London: Routledge, Taylor & Francis Group, 2020. [Google Scholar]
- I. Y. Alyoussef, “Acceptance of a flipped classroom to improve university students’ learning: An empirical study on the TAM model and the Unified Theory Of Acceptance and Use of Technology (UTAUT),” Heliyon, vol. 8, no. 12, p. e12529, Dec. 2022, doi: 10.1016/j.heliyon.2022.e12529. [CrossRef] [PubMed] [Google Scholar]
- K. Nikolopoulou, V. Gialamas, and K. Lavidas, “Habit, hedonic motivation, performance expectancy and technological pedagogical knowledge affect teachers’ intention to use mobile internet,” Comput. Educ. Open, vol. 2, p. 100041, Dec. 2021, doi: 10.1016/j.caeo.2021.100041. [CrossRef] [Google Scholar]
- M. Sarfraz, K. F. Khawaja, and L. Ivascu, “Factors affecting business school students’ performance during the COVID-19 pandemic: A moderated and mediated model,” Int. J. Manag. Educ., vol. 20, no. 2, p. 100630, Jul. 2022, doi: 10.1016/j.ijme.2022.100630. [CrossRef] [Google Scholar]
- S. Sharma, G. Singh, L. Gaur, and A. Afaq, “Exploring customer adoption of autonomous shopping systems,” Telemat. Inform., vol. 73, p. 101861, Sep. 2022, doi: 10.1016/j.tele.2022.101861. [CrossRef] [Google Scholar]
- A. S. Al-Adwan, H. Yaseen, A. Alsoud, F. Abousweilem, and W. M. Al-Rahmi, “Novel extension of the UTAUT model to understand continued usage intention of learning management systems: The role of learning tradition,” Educ. Inf. Technol., vol. 27, no. 3, pp. 3567–3593, Apr. 2022, doi: 10.1007/s10639-021-10758-y. [CrossRef] [Google Scholar]
- A. Mishra, L. Baker-Eveleth, P. Gala, and J. Stachofsky, “Factors influencing actual usage of fitness tracking devices: Empirical evidence from the UTAUT model,” Health Mark. Q., vol. 0, no. 0, pp. 1–20, Oct. 2021, doi: 10.1080/07359683.2021.1994170. [Google Scholar]
- S. Alam, I. Mahmud, S. M. S. Hoque, R. Akter, and S. M. Sohel Rana, “Predicting students’ intention to continue business courses on online platforms during the COVID-19: An extended expectation confirmation theory,” Int. J. Manag. Educ., vol. 20, no. 3, p. 100706, Nov. 2022, doi: 10.1016/j.ijme.2022.100706. [CrossRef] [Google Scholar]
- Y. J. Seo and K. H. Um, “The role of service quality in fostering different types of perceived value for student blended learning satisfaction,” J. Comput. High. Educ., Aug. 2022, doi: 10.1007/s12528-022-09336-z. [Google Scholar]
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