Preparing instructors to transition to online distance learning: a pandemic panacea?

Siti Nurul Atiqah; Mohd Hafiz Hanafiah; Hazmal Ismail; Balasubramaniam Kandappan

doi:10.24310/ijtei.101.2024.16820

Authors

Siti Nurul Atiqah Universiti Teknologi MARA, Malaysia
Mohd Hafiz Hanafiah Universiti Teknologi MARA, Malaysia https://orcid.org/0000-0002-3378-7300
Hazmal Ismail Universiti Teknologi MARA, Malaysia
Balasubramaniam Kandappan Taylor´ s University, Malaysia https://orcid.org/0000-0001-7634-4676

DOI:

https://doi.org/10.24310/ijtei.101.2024.16820

Keywords:

online teaching, online distance learning, COVID-19, instructor readiness

Abstract

This research explores the interconnectedness between readiness, the adoption of online teaching, attitude, and behavioral intention concerning Online Distance Learning (ODL) within the realm of hospitality and tourism instruction. The study framework intergrates the Unified Theory of Acceptance and Use of Technology (UTAUT) model and Technology Readiness (TR) dimension. The data, collected through purposive sampling and online surveys from 248 instructors, was analyzed using Partial-least Square-Structural Equation Modeling (PLS-SEM) to assess the study's model and hypotheses. The outcomes reveal that factors such as effort expectancy (EE), performance expectancy (PE), and social influence (SI) directly impact instructors' attitudes towards ODL. Additionally, the study establishes that technical, pedagogical, and lifestyle readiness are robust indicators for enhancing instructors' behavioral intention towards ODL. Intriguingly, the sole distinction between the theoretical and practical class arises in the interaction between instructors' technical and lifestyle readiness regarding behavioral intention. The pragmatic implications of this study underscore the significance of instructors' attitude and technology readiness in driving the adoption of ODL within the hospitality and tourism instruction domain. Furthermore, the study's findings offer valuable insights to policymakers, aiding them in developing effective methodologies for practical class teaching within the ODL framework and aligned with the dynamic environment of online learning.

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Author Biographies

Siti Nurul Atiqah, Universiti Teknologi MARA,

Faculty of Hotel and Tourism Management, Universiti Teknologi MARA, Malaysia

Mohd Hafiz Hanafiah, Universiti Teknologi MARA,

Faculty of Hotel and Tourism Management, Universiti Teknologi MARA, Malaysia

Hazmal Ismail , Universiti Teknologi MARA,

Faculty of Hotel and Tourism Management, Universiti Teknologi MARA, Malaysia

Balasubramaniam Kandappan, Taylor´ s University,

Faculty of Social Sciences & Leisure Management, Taylor´ s University, Malaysia

References

Abou-Khalil, V., Helou, S., Khalifé, E., Chen, M. A., Majumdar, R., & Ogata, H. (2021). Emergency online learning in low-resource settings: Effective student engagement strategies. Education Sciences, 11(1), e24. https://doi.org/10.3390/educsci11010024

Aditya, D. S. (2021). Embarking Digital Learning Due to COVID-19: Are Teachers Ready? Journal of Technology and Science Education, 11(1), 104-116. https://doi.org/10.3926/jotse.1109

Afthanorhan, A., Nazim, A., & Ahmad, S. (2014). A parametric approach to partial least square structural equation modeling of multigroup analysis (PLS-MGA). International Journal of Economic, Commerce, and Management, 2(10), 15-24.

Akinnuwesi, B. A., Uzoka, F. M. E., Fashoto, S. G., Mbunge, E., Odumabo, A., Amusa, O. O., Okpeku, M., & Owolabi, O. (2022). A modified UTAUT model for the acceptance and use of digital technology for tackling Covid-19. Sustainable Operations and Computers, 3, 118–135. https://doi.org/10.1016/j.susoc.2021.12.001

Al-Fraihat, D., Joy, M., Masa’deh, R., & Sinclair, J. (2020). Evaluating e-learning systems success: An empirical study. Computers in Human Behavior, 102, 67–86. https://doi.org/10.1016/j.chb.2019.08.004

Alea, L. A., Fabrea, M. F., Roldan, R. D. A., & Farooqi, A. Z. (2020). Teachers’ covid-19 awareness, distance learning education experiences and perceptions towards institutional readiness and challenges. International Journal of Learning, Teaching and Educational Research, 19(6), 127-144. https://doi.org/10.26803/ijlter.19.6.8

Alfy, S., Gómez, J. M., & Ivanov, D. (2016). Exploring instructors’ technology readiness, attitudes and behavioral intentions towards e-learning technologies in Egypt and United Arab Emirates. Education and Information Technologies, 22(5), 2605–2627. https://doi.org/10.1007/s10639-016-9562-1

Asghar, M. Z., Barberà, E., & Younas, I. (2021). Mobile Learning Technology Readiness and Acceptance among Pre-Service Teachers in Pakistan during the COVID-19 Pandemic. Knowledge Management & E-Learning, 13(1), 83-101. https://doi.org/10.34105/j.kmel.2021.13.005

Ayodele, S., Endozo, A., & Ogbari, M. E. (2018, October). A study on factors hindering online learning acceptance in developing countries. In ICETC (Ed.), Proceedings of the 10th International Conference on Education Technology and Computers (pp. 254–258). Association for Computing Machinery. https://dl.acm.org/doi/abs/10.1145/3290511.3290533

Boettcher, J. V., & Conrad, R.-M. (2021). The online teaching survival guide: Simple and practical pedagogical tips. John Wiley & Sons.

Brinkley-Etzkorn, K.E. (2018). Learning to teach online: Measuring the influence of faculty development training on teaching effectiveness through a tpack lens. The Internet and Higher Education, 38, 28-35. https://doi.org/10.1016/j.iheduc.2018.04.004

Chao, C. M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the utaut model. Frontiers in Psychology, 10, 1-14. https://doi.org/10.3389/fpsyg.2019.01652

Chin, W.W. (1998). The partial least squares approach to structural equation modelling. Advances in Hospitality and Leisure, 8(2), 295-336.

Coakes, S. J., Steed, L., & Ong, C. (2009). Analysis without anguish: SPSS version 16.0 for windows. John Wiley and Sons Ltd.

Coman, C., Țîru, L. G., Meseșan-Schmitz, L., Stanciu, C., & Bularca, M. C. (2020). Online teaching and learning in higher education during the coronavirus pandemic: Students’ perspective. Sustainability, 12(24), e10367. https://doi.org/10.3390/su122410367

Cutri, R. M., Mena, J., & Whiting, E. F. (2020). Faculty readiness for online crisis teaching: Transitioning to online teaching during the covid-19 pandemic. European Journal of Teacher Education, 43(4), 523-541. https://doi.org/10.1080/02619768.2020.1815702

Davis, N. L., Gough, M., & Taylor, L. L. (2019). Online teaching: advantages, obstacles and tools for getting it right. Journal of Teaching in Travel & Tourism, 19(3), 256-263. https://doi.org/10.1080/15313220.2019.1612313

Dragan, I.M., & Isaic-Maniu, A. (2013). Snowball sampling completion. Journal of Studies in Social Science, 5(2), 160-177.

Dumford, A. D., & Miller, A. L. (2018). Online learning in higher education: exploring advantages and disadvantages for engagement. Journal of Computing in Higher Education, 30(3), 452-465. https://doi.org/10.1007/s12528-018-9179-z

Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 21(3), 719-734. https://doi.org/10.1007/s10796-017-9774-y

Dwivedi, Y.K., Rana, N.P., Janssen, M., Lal, B., Williams, M.D., &Clement, M. (2017). An empirical validation of a unified model of electronic government adoption (UMEGA). Government Information Quarterly, 34(2), 211-230. https://doi.org/10.1016/j.giq.2017.03.001

Ersin, P., Atay, D., & Mede, E. (2020). Boosting preservice teachers’ competence and online teaching readiness through e-practicum during the COVID-19 outbreak. International Journal of TESOL Studies, 2(2), 112-124.

Eseadi, C. (2023). Online Learning Attitude and Readiness of Students in Nigeria during the Covid-19 pandemic: A Case of Undergraduate Accounting Students. Innoeduca. International Journal of Technology and Educational Innovation, 9(1), 27-38. https://doi.org/10.24310/innoeduca.2023.v9i1.15503

Estriegana, R., Medina-Merodio, J. A., & Barchino, R. (2019). Student acceptance of virtual laboratory and practical work: An extension of the technology acceptance model. Computers & Education, 135, 1-14. https://doi.org/10.1016/j.compedu.2019.02.010

Firat, M., & Bozkurt, A. (2020). Variables affecting online learning readiness in an open and distance learning university. Educational Media International, 57(2), 112-127. https://doi.org/10.1080/09523987.2020.1786772

Gamage, K. A., Wijesuriya, D. I., Ekanayake, S. Y., Rennie, A. E., Lambert, C. G., & Gunawardhana, N. (2020). Online delivery of teaching and laboratory practices: Continuity of university programmes during COVID-19 pandemic. Education Sciences, 10(10), e291. https://doi.org/10.3390/educsci10100291

Gay, G. H. (2016). An assessment of online instructor e-learning readiness before, during, and after course delivery. Journal of Computing in Higher Education, 28(2), 199-220. https://doi.org/ 10.1007/s12528-016-9115-z

Geldsetzer, P. (2020). Use of rapid online surveys to assess people's perceptions during infectious disease outbreaks: a cross-sectional survey on COVID-19. Journal of Medical Internet Research, 22(4), e18790. https://doi.org/10.2196/18790

Geng, S., Law, K. M., & Niu, B. (2019). Investigating self-directed learning and technology readiness in blending learning environment. International Journal of Educational Technology in Higher Education, 16, e17. https://doi.org/10.1186/s41239-019-0147-0

Goh, E., & King, B. (2020). Four decades (1980–2020) of hospitality and tourism higher education in Australia: Developments and future prospects. Journal of Hospitality and Tourism Education, 32(4), 266-272. https://doi.org/10.1080/10963758.2019.1685892

Gopal, R., Singh, V., & Aggarwal, A. (2021). Impact of online classes on the satisfaction and performance of students during the pandemic period of COVID 19. Education and Information Technologies, 26(6), 6923-6947. https://doi.org/10.1007/s10639-021-10523-1

Guðmundsdóttir, G., & Hathaway, D. (2020). “We always make it work”: Teachers’ agency in the time of crisis. Journal of Technology and Teacher Education, 28(2), 239-250.

Hair, J.F., Risher, J.J., Sarstedt, M., & Ringle, C.M. (2020). When to use and how to report the results of pls-sem. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203

Hair. F. Jr, J., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM). European Business Review, 26(2), 106–121. https://doi.org/10.1108/ebr-10-2013-0128

Hanafiah, M. (2020). Formative vs reflective measurement model: Guidelines for structural equation modelling research. International Journal of Analysis and Applications, 18(5), 876-889. https://doi.org/10.28924/2291-8639-18-2020-876

Henseler, J. (2012, July 21-23). PLS-MGA: A non-parametric approach to partial least squares-based multi-group analysis. In W. A. Gaul, A. Geyer-Schulz, L. Schmidt-Thieme, & J. Kunze (Eds.), Challenges at the Interface of Data Analysis, Computer Science, and Optimization (pp. 495-501). Springer Berlin Heidelberg.

Henseler, J., Ringle, C.M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of Academy of Marketing Science, 43, 115-135. https://doi.org/10.1007/s11747-014-0403-8

Hung, M. L. (2016). Teacher readiness for online learning: Scale development and teacher perceptions. Computers & Education, 94 , 120-133. https://doi.org/10.1016/j.compedu.2015.11.012

Iyer, D. G., & Chapman, T. A. (2021). Overcoming technological inequity in synchronous online learning. Communications of the Association for Information Systems, 48(1), 205-212. https://doi.org/ 10.17705/1CAIS.04826

Jung, I., & Lee, J. (2020). A cross‐cultural approach to the adoption of open educational resources in higher education. British Journal of Educational Technology, 51(1), 263-280. https://doi.org/10.1111/bjet.12820

Junus, K., Santoso, H. B., Putra, P. O. H., Gandhi, A., & Siswantining, T. (2021). Lecturer readiness for online classes during the pandemic: A survey research. Education Sciences, 11(3), e139. https://doi.org/10.3390/educsci11030139

Kaplan, K. J. (1972). On the ambivalence-indifference problem in attitude theory and measurement: A suggested modification of the semantic differential technique. Psychological Bulletin, 77(5), 361-372. https://doi.org/10.1037/h0032590

Karen, E., & Etzkorn, B. (2020). The effects of training on instructor beliefs about and attitudes toward online teaching. American Journal of Distance Education, 34(1), 19-35. https://doi.org/10.1080/08923647.2020.1692553

Kaushik, M. K., & Agrawal, D. (2021). Influence of technology readiness in adoption of e-learning. International Journal of Educational Management, 35(2), 483-495. https://doi.org/10.1108/IJEM-04-2020-0216

Kemp, N., & Grieve, R. (2014). Face-to-face or face-to-screen? Undergraduates’ opinions and test performance in classroom vs. online learning. Frontiers in Psychology, 5, 1-11. https://doi.org/10.3389/fpsyg.2014.01278

Keong, Y. C., Albadry, O., & Raad, W. (2014). Behavioral intention of efl teachers to apply e-learning. Journal of Applied Sciences, 14(20), 2561-2569. https://doi.org/10.3923/jas.2014.2561.2569

Khalil, R., Mansour, A. E., Fadda, W. A., Almisnid, K., Aldamegh, M., Al-Nafeesah, A., Alkhalifah, A., & Al-Wutayd, O. (2020). The sudden transition to synchronized online learning during the COVID-19 pandemic in Saudi Arabia: A qualitative study exploring medical students’ perspectives. BMC Medical Education, 20, e285. https://doi.org/10.1186/s12909-020-02208-z

Khechine, H., Raymond, B., & Augier, M. (2020). The adoption of a social learning system: Intrinsic value in the utaut model. British Journal of Educational Technology, 51(6), 2306–2325. https://doi.org/10.1111/bjet.12905

Kim, D., Lee, Y., Leite, W. L., & Huggins-Manley, A. C. (2020). Exploring student and teacher usage patterns associated with student attrition in an open educational resource-supported online learning platform. Computers & Education, 156, 103961. https://doi.org/10.1016/j.compedu.2020.103961

Koet, T. W., & Abdul Aziz, A. (2021). Teachers’ and students’ perceptions towards distance learning during the covid-19 pandemic: A systematic review. International Journal of Academic Research in Progressive Education and Development, 10(3), 531-562. https://doi.org/10.6007/ijarped/v10-i3/11005

König, J., Jäger-Biela, D. J., & Glutsch, N. (2020). Adapting to online teaching during covid-19 school closure: Teacher education and teacher competence effects among early career teachers in Germany. European Journal of Teacher Education, 43(4), 608-622. https://doi.org/10.1080/02619768.2020.1809650

Lassoued, Z., Alhendawi, M., & Bashitialshaaer, R. (2020). An exploratory study of the obstacles for achieving quality in distance learning during the COVID-19 pandemic. Education Sciences, 10(9), e232. https://doi.org/10.3390/educsci10090232

Loomis, K.D. (2000). Learning styles and asynchronous learning: Comparing the lassi model to class performance. Online Learning, 4(1), 23-32. https://doi.org/ 10.24059/olj.v4i1.1908

MacKinnon, D. P. (2011). Integrating mediators and moderators in research design. Research on Social Work Practice, 21(6), 675-681. https://doi.org/ 10.1177/1049731511414148

Maheshwari, G. (2021). Factors affecting students’ intentions to undertake online learning: an empirical study in Vietnam. Education and Information Technologies, 26(6), 6629–6649. https://doi.org/10.1007/s10639-021-10465-8

Mailizar, M., Almanthari, A., & Maulina, S. (2021). Examining teachers’ behavioral intention to use e-learning in teaching of mathematics: An extended tam model. Contemporary Educational Technology, 13(2), e298. https://doi.org/10.30935/cedtech/9709

Mathew, V. N., & Chung, E. (2020). University students’ perspectives on open and distance learning (odl) implementation amidst covid-19. Asian Journal of University Education, 16(4), 152-160. https://doi.org/10.24191/ajue.v16i4.11964

Mazman Akar, S. G. (2019). Does it matter being innovative: Teachers’ technology acceptance. Education and Information Technologies, 24(6), 3415-3432. https://doi.org/10.1007/s10639-019-09933-z

McGee, P., Windes, D., & Torres, M. (2017). Experienced online instructors: beliefs and preferred supports regarding online teaching. Journal of Computing in Higher Education, 29(2), 331-352. https://doi.org/10.1007/s12528-017-9140-6

Md Yunus, M., Ang, W. S., & Hashim, H. (2021). Factors affecting teaching English as a Second Language (TESL) postgraduate students’ behavioural intention for online learning during the COVID-19 pandemic. Sustainability, 13(6), 3524. https://doi.org/10.3390/su13063524

Mei, B., Brown, G. T., & Teo, T. (2018). Toward an understanding of preservice English as a Foreign language teachers’ acceptance of computer-assisted language learning 2.0 in the people’s Republic of China. Journal of Educational Computing Research, 56(1), 74–104. https://doi.org/10.1177/0735633117700144

Mokhtar, S., Katan, H., & Rehman, H., (2018). Instructors’ behavioural intention to use learning management system: An integrated tam perspective. Technology, Education and Management Journal, 7(3), 513-525. https://doi.org/10.18421/TEM73-07

Mosunmola, A., Mayowa, A., Okuboyejo, S., & Adeniji, C. (2018, January). Adoption and use of mobile learning in higher education: The utaut model. In IC4E '18 (Ed.), Proceedings of the 9th International Conference on E-Education, E-Business, E-Management and E-Learning (pp. 20-25). Association for Computing Machinery. https://doi.org/10.1145/3183586.3183595

Munoz, K. E., Wang, M.-J., & Tham, A. (2021). Enhancing online learning environments using social presence: evidence from hospitality online courses during covid-19. Journal of Teaching in Travel & Tourism, 21(4), 339-357. https://doi.org/10.1080/15313220.2021.1908871

Nikolopoulou, K., Gialamas, V., & Lavidas, K. (2021). Habit, hedonic motivation, performance expectancy and technological pedagogical knowledge affect teachers’ intention to use mobile internet. Computers and Education Open, 2, 100041. https://doi.org/10.1016/j.caeo.2021.100041

Nikou, S. A., & Economides, A. A. (2018). Factors that influence behavioral intention to use mobile-based assessment: A stem teachers’ perspective. British Journal of Educational Technology, 50(2), 587–600. https://doi.org/10.1111/bjet.12609

Oguguo, B., Ezechukwu, R., Nannim, F., & Offor, K. (2023). Analysis of teachers in the use of digital resources in online teaching and assessment in COVID times. Innoeduca. International Journal of Technology and Educational Innovation, 9(1), 81-96. https://doi.org/10.24310/innoeduca.2022.v8i1.11144

Omotayo, F.O. & Adekunle, O.A. (2021). Adoption and use of electronic voting system as an option towards credible elections in Nigeria. International Journal of Development Issues, 20(1), 38 - 61. https://doi.org/10.1108/IJDI-03-2020-0035

Owen, S. M., White, G., Palekahelu, D. T., Sumakul, D. T., & Sediyono, E. (2020). Integrating online learning in schools: Issues and ways forward for developing countries. Journal of Information Technology Education: Research, 19, 571-614. https://doi.org/10.28945/4625

Peattie, K. (2001). Golden goose or wild goose? The hunt for the green consumer. Business Strategy and the Environment, 10(4), 187–199. https://doi.org/10.1002/bse.292

Phan, T. T. N., & Dang, L. T. T. (2017). Teacher readiness for online teaching: A critical review. International Journal on Open and Distance E-Learning, 3(1), 1-16.

Pillay, H., Irving, K., & Tones, M. (2007). Validation of the diagnostic tool for assessing tertiary students’ readiness for online learning. Higher Education Research and Development, 26(2), 217-234. https://doi.org/10.1080/07294360701310821

Prause, M. (2019). Challenges of industry 4.0 technology adoption for smes: the case of Japan. Sustainability, 11(20), e5807. https://doi.org/10.3390/su11205807

Rafique, G. M., Mahmood, K., Warraich, N. F., & Rehman, S. U. (2021). Readiness for online learning during covid-19 pandemic: A survey of Pakistanis students. The Journal of Academic Librarianship, 47(3), 1-10. https://doi.org/10.1016/j.acalib.2021.102346

Ramos-Morcillo, A. J., Leal-Costa, C., Moral-García, J. E., & Ruzafa-Martínez, M. (2020). Experiences of nursing students during the abrupt change from face-to-face to e-learning education during the first month of confinement due to COVID-19 in Spain. International Journal of Environmental Research and Public Health, 17(15), 5519. https://doi.org/10.3390/ijerph17155519

Rana, N. P., Dwivedi, Y. K., Lal, B., Williams, M. D., & Clement, M. (2017). Citizens’ adoption of an electronic government system: Towards a unified view. Information Systems Frontiers, 19(3), 549–568. https://doi.org/10.1007/s10796-015-9613-y

Sabet, S. A., Moradi, F., & Soufi, S. (2022). Predicting students’ satisfaction with virtual education based on health-oriented lifestyle behaviors. Innoeduca: International Journal of Technology and Educational Innovation, 8(2), 43-57. https://doi.org/10.24310/innoeduca.2022.v8i2.13079

Sangeeta & Tandon, U. (2021). Factors influencing adoption of online teaching by school teachers: A study during COVID‐19 pandemic. Journal of Public Affairs, 21(4), e2503. Htpps://doi.org/10.1002/pa.2503

Schlenz, M. A., Schmidt, A., Wöstmann, B., Krämer, N., & Schulz-Weidner, N. (2020). Students’ and lecturers’ perspective on the implementation of online learning in dental education due to SARS-CoV-2 (COVID-19): A cross-sectional study. BMC Medical Education, 20, e354. https://doi.org/10.1186/s12909-020-02266-3

Selvaraj, A., Radhin, V., Nithin, K. A., Benson, N., & Mathew, A. J. (2021). Effect of pandemic based online education on teaching and learning system. International Journal of Educational Development, 85, e102444. https://doi.org/10.1016/j.ijedudev.2021.102444

Semerci, A., & Aydın, M. K. (2018). Examining high school teachers’ attitudes towards ICT use in education. International Journal of Progressive Education, 14(2), 93–105. https://doi.org/10.29329/ijpe.2018.139.7

Sewandono, R. E., Thoyib, A., Hadiwidjojo, D., & Rofiq, A. (2023). Performance expectancy of E-learning on higher institutions of education under uncertain conditions: Indonesia context. Education and Information Technologies, 28(4), 4041-4068. https://doi.org/10.1007/s10639-022-11074-9

Sidpra, J., Gaier, C., Reddy, N., Kumar, N., Mirsky, D., & Mankad, K. (2020). Sustaining education in the age of covid-19: A survey of synchronous web-based platforms. Quantitative Imaging in Medicine and Surgery, 10(7), 1422–1427. https://doi.org/10.21037/qims-20-714

Simamora, R. M. (2020). The Challenges of online learning during the COVID-19 pandemic: An essay analysis of performing arts education students. Studies in Learning and Teaching, 1(2), 86-103. https://doi.org/10.46627/silet.v1i2.38

Stangor, C., Tarry, H., & Jhangiani, R. (2014). Principles of Social Psychology – 1st International Edition. Pressbooks by BCcampus.

Tang, Y. M., Chen, P. C., Law, K. M., Wu, C. H., Lau, Y.-y., Guan, J., & Ho, G. T. (2021). Comparative analysis of student’s live online learning readiness during the coronavirus (Covid-19) pandemic in the higher education sector. Computers & Education, 168, e104211. https://doi.org/10.1016/j.compedu.2021.104211

Tiwari, P., Séraphin, H., & Chowdhary, N. R. (2020). Impacts of Covid-19 on tourism education: Analysis and perspectives. Journal of Teaching in Travel & Tourism, 21(4), 313-338. https://doi.org/10.1080/15313220.2020.1850392

Triandis, H. C. (1971). Attitude and attitude change (foundations of social psychology). John Wileys & Sons Inc.

Tsourela, M., & Roumeliotis, M. (2015). The moderating role of technology readiness, gender, and sex in consumer acceptance and actual use of Technology-based services. The Journal of High Technology Management, 26(2), 124-136. https://doi.org/10.1016/j.hitech.2015.09.003

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. Management Information Systems Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

Wang, Y., Gu, J., Wang, S., & Wang, J. (2019). Understanding consumers’ willingness to use ride-sharing services: The roles of perceived value and perceived risk. Transportation Research Part C: Emerging Technologies, 105, 504-519. https://doi.org/10.1016/j.trc.2019.05.044

Weerakkody, V., Irani, Z., Kapoor, K., Sivarajah, U., & Dwivedi, Y. K. (2017). Open data and its usability: An empirical view from the citizen’s perspective. Information Systems Frontiers, 19(2), 285–300. https://doi.org/10.1007/s10796-016-9679-1

Wei, H.-C., & Chou, C. (2020). Online learning performance and satisfaction: Do perceptions and readiness matter? Distance Education, 41(1), 48-69. https://doi.org/10.1080/01587919.2020.1724768

Wilson, B. J., Deckert, A., Shah, R., Kyei, N., Copeland Dahn, L., Doe-Rogers, R., Hinneh, A. B., Johnson, L. W., Natt, G. D., Verdier, J. A., Vosper, A., Louis, V. R., Dambach, P., & Thomas-Connor, I. (2021). Covid-19-related knowledge, attitudes and practices: a mixed-mode cross-sectional survey in Liberia. BMJ Open, 11(7), 1-14. https://doi.org/10.1136/bmjopen-2021-049494

Wong, G. K. (2016). The behavioral intentions of Hong Kong primary teachers in adopting educational technology. Educational Technology Research and Development, 64(2), 313–338. https://doi.org/10.1007/s11423-016-9426-9

Zikmund, W.G., Carr, B.J., Griffin, M., & Babin, B.J. (2013). Business Research Method. Dryden Press.