How to cite this paper
Al-Hamad, M., Mbaidin, H., AlHamad, A., Alshurideh, M., Kurdi, B & Al-Hamad, N. (2021). Investigating students' behavioral intention to use mobile learning in higher education in UAE during Coronavirus-19 pandemic.International Journal of Data and Network Science, 5(3), 321-330.
Refrences
Ahorsu, D. K., Lin, C.-Y., Imani, V., Saffari, M., Griffiths, M. D., & Pakpour, A. H. (2020). The Fear of COVID-19 Scale: Development and Initial Validation. International Journal of Mental Health and Addiction, 1.
Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314–324.
Al-Emran, M., Arpaci, I., & Salloum, S. A. (2020). An empirical examination of continuous intention to use m-learning: An integrated model. Education and Information Technologies, 25(4), 2899-2918. https://doi.org/10.1007/s10639-019-10094-2
Al-Emran, Mostafa, & Salloum, S. A. (2017). Students’ Attitudes Towards the Use of Mobile Technologies in e-Evaluation. International Journal of Interactive Mobile Technologies (IJIM), 11(5), 195–202.
Al-Maroof, R. A. S., & Al-Emran, M. (2018). Students Acceptance of Google Classroom: An Exploratory Study using PLS-SEM Approach. International Journal of Emerging Technologies in Learning, 13(6).
Al Hamad, A. Q. (2016, February). Students' perception of implementing a Smart Learning System (SLS) based on Moodle at Fujairah College. In 2016 13th International Conference on Remote Engineering and Virtual Instrumentation (REV) (pp. 315-318). IEEE.
AlHamad, A. Q., Al Omari, F., & AlHamad, A. Q. (2014). Recommendation for Managing Patients’ Privacy in an Integrated Health Information Network. Journal of Information Technology & Economic Development, 5(1), 47-52
AlHamad, A. Q., & Al Qawasmi, K. I. (2014). Building an ethical framework for e-learning management system at a university level. Journal of Engineering and Economic Development, 1(1), 11.
Alhamad, H, Patel, N., & Donyai, P. (2018). Beliefs and intentions towards reusing medicines in the future: A large-scale, cross-sectional study of patients in the UK. International Journal of Pharmacy Practice, 26, 4–36.
Alhamad, H., Abu‐Farha, R. K., Albahar, F., & Jaber, D. (2020). Public Perceptions about Pharmacists’ Role in Prescribing, Providing Education and Delivering Medications during COVID‐19 Pandemic Era. International journal of clinical practice, e13890.
Alhamad, H., & Donyai, P. (2020). Intentions to “Reuse” Medication in the Future Modelled and Measured Using the Theory of Planned Behavior. Pharmacy, 8(4), 213.
Alhamad, H., & Donyai, P. (2021). The Validity of the Theory of Planned Behaviour for Understanding People’s Beliefs and Intentions toward Reusing Medicines. Pharmacy, 9(1), 58.
AlHamad, A. Q., Yaacob, N., & Al-Omari, F. (2012, September). Applying JESS rules to personalize Learning Management System (LMS) using online quizzes. In 2012 15th International Conference on Interactive Collaborative Learning (ICL) (pp. 1-4). IEEE.
Al Kurdi, B., Alshurideh, M., & Salloum, S. A. (2020). Investigating a theoretical framework for e-learning technology acceptance. International Journal of Electrical and Computer Engineering (IJECE), 10(6), 6484-6496.
Alshamsi, A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). The influence of service quality on customer retention: A systematic review in the higher education. In International Conference on Advanced Intelligent Systems and Informatics (pp. 404-416). Springer, Cham.
Alsharari, N. M., & Alshurideh, M. T. (2020). Student retention in higher education: the role of creativity, emotional intelligence and learner autonomy. International Journal of Educational Management, 35(1), 233-247.
Alshurideh, D. M. (2019). Do electronic loyalty programs still drive customer choice and repeat purchase behaviour?. International Journal of Electronic Customer Relationship Management, 12(1), 40-57.
Alshurideh, M., Al Kurdi, B., Salloum, S. A., Arpaci, I., & Al-Emran, M. (2020). Predicting the actual use of m-learning systems: a comparative approach using PLS-SEM and machine learning algorithms. Interactive Learning Environments, 1–15.
Alshurideh, M., Al Kurdi, B., Abumari, A., & Salloum, S. (2018). Pharmaceutical Promotion Tools Effect on Physician’s Adoption of Medicine Prescribing: Evidence from Jordan. Modern Applied Science, 12(11), 210-222.
Alshurideh, M. T., Al Kurdi, B., & Salloum, S. A. (2021). The moderation effect of gender on accepting electronic payment technology: a study on United Arab Emirates consumers. Review of International Business and Strategy.
Alshurideh, M. T., Kurdi, B. A., AlHamad, A. Q., Salloum, S. A., Alkurdi, S., Dehghan, A., ... & Masa’deh, R. E. (2021, June). Factors affecting the use of smart mobile examination platforms by universities’ postgraduate students during the COVID 19 pandemic: an empirical study. In Informatics (Vol. 8, No. 2, p. 32). Multidisciplinary Digital Publishing Institute.
Alshurideh, M., Masa'deh, R., & Alkurdi, B. (2012). The effect of customer satisfaction upon customer retention in the Jordanian mobile market: An empirical investigation. European Journal of Economics, Finance and Administrative Sciences, 47(12), 69-78.
Bailey, A. A., Pentina, I., Mishra, A. S., & Ben Mimoun, M. S. (2020). Exploring factors influencing US millennial consumers’ use of tap-and-go payment technology. The International Review of Retail, Distribution and Consumer Research, 30(2), 143–163.
Barclay, D., Higgins, C., & Thompson, R. (1995). The Partial Least Squares (pls) Approach to Casual Modeling: Personal Computer Adoption Ans Use as an Illustration.
Bettayeb, H., Alshurideh, M. T., & Al Kurdi, B. (2020). The effectiveness of Mobile Learning in UAE Universities: A systematic review of Motivation, Self-efficacy, Usability and Usefulness. International Journal of Control and Automation, 13(2), 1558-1579.
Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation-confirmation model. MIS Quarterly, 25(3), 351–370.
Bhattacherjee, A., & Hikmet, N. (2007). Physicians’ resistance toward healthcare information technology: a theoretical model and empirical test. European Journal of Information Systems, 16(6), 725–737.
Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS Quarterly, 29(3), 399–426.
Chuan, C. L., & Penyelidikan, J. (2006). Sample size estimation using Krejcie and Morgan and Cohen statistical power analysis: A comparison. Jurnal Penyelidikan IPBL, 7, 78–86.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Davis, Fred D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
Davis, Fred 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.
Distler, V., Lallemand, C., & Koenig, V. (2020). How Acceptable Is This? How User Experience Factors Can Broaden our Understanding of The Acceptance of Privacy Trade-offs. Computers in Human Behavior, 106, 106227.
Elshamy, A. M., Abdelghany, M. A., Alhamad, A. Q., Hamed, H. F., Kelash, H. M., & Hussein, A. I. (2017, September). Secure implementation for video streams based on fully and permutation encryption techniques. In 2017 International Conference on Computer and Applications (ICCA) (pp. 50-55). IEEE.
Gerhold, L. (2020). COVID-19: Risk perception and Coping strategies.
Goodhue, D. L., Lewis, W., & Thompson, R. (2012). Does PLS have adavantages for small sample size or non-normal data? MIS Quaterly, 36(3), 981-1001.
Gresham, J. (2020). Manufacturing Trends in Automated Inspection Equipment: Linking Technology with Business Change Management Using the Technology Acceptance Model. Northcentral University.
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.
Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442–458. https://doi.org/10.1108/IMDS-04-2016-0130
Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications.
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(1), 115–135.
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New challenges to international marketing (pp. 277–319). Emerald Group Publishing Limited.
Johnston, A. C., & Warkentin, M. (2010). Fear appeals and information security behaviors: an empirical study. MIS Quarterly, 34(3), 549–566.
Joo, Y. J., Kim, N., & Kim, N. H. (2016). Factors predicting online university students’ use of a mobile learning management system (m-LMS). Educational Technology Research and Development, 64(4), 611–630. https://doi.org/10.1007/s11423-016-9436-7
Kamal, S. A., Shafiq, M., & Kakria, P. (2020). Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM). Technology in Society, 60, 101212.
Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.
Krejcie, R. V, & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610.
Le, T. T., Pham, H. M., Chu, N. H., Nguyen, D. K., & Ngo, H. M. (2020). Factors Affecting Users’ Continuance Intention towards Mobile Banking In Vietnam. American Journal of Multidisciplinary Research & Development (AJMRD), 2(4), 42–51.
Liu, S.-H., Liao, H.-L., & Peng, C.-J. (2005). Applying the technology acceptance model and flow theory to online e-learning users’ acceptance behavior. E-Learning, 4(H6), H8.
Mac Callum, K., & Jeffrey, L. (2014). Comparing the role of ICT literacy and anxiety in the adoption of mobile learning. Computers in Human Behavior, 39, 8–19.
Makttoofa, N., Khalidb, H., & Abdullahc, I. (n.d.). The Effect of Individual Factors on the Adoption of Mobile Banking Within Banks in Iraq.
Meng, F., Guo, X., Zhang, X., Peng, Z., & Lai, K.-H. (2020). Examining the Role of Technology Anxiety and Health Anxiety on Elderly Users’ Continuance Intention for Mobile Health Services Use. Proceedings of the 53rd Hawaii International Conference on System Sciences.
Nascimento, B., Oliveira, T., & Tam, C. (2018). Wearable technology: What explains continuance intention in smartwatches? Journal of Retailing and Consumer Services, 43, 157–169.
Nchunge, D. M., Sakwa, M., & Mwangi, W. (2012). User’s perception on ICT adoption for education support in schools: a survey of secondary school teacher’s in Thika district Kenya. International Journal of Humanities and Social Science, 2(10), 17–29.
Nicomedes, C. J., & Avila, R. M. (2020). An Analysis on the Panic of Filipinos During COVID-19 Pandemic in the Philippines.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory. In McGraw-Hill, New York. https://doi.org/10.1037/018882
Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. Bönningstedt: SmartPLS.
Tam, C., Santos, D., & Oliveira, T. (2020). Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model. Information Systems Frontiers, 22(1), 243-257.
Tarhini, A., Hone, K., & Liu, X. (2015). A cross‐cultural examination of the impact of social, organisational and individual factors on educational technology acceptance between B ritish and L ebanese university students. British Journal of Educational Technology, 46(4), 739–755.
Teo, T. (2012). Examining the intention to use technology among pre-service teachers: An integration of the technology acceptance model and theory of planned behavior. Interactive Learning Environments, 20(1), 3–18.
Thatcher, J. B., & Perrewe, P. L. (2002). An empirical examination of individual traits as antecedents to computer anxiety and computer self-efficacy. MIS Quarterly, 26(4), 381–396.
Urbach, N., & Ahlemann, F. (2010). Structural equation modeling in information systems research using partial least squares. Journal of Information Technology Theory and Application, 11(2), 5–40. https://doi.org/10.1037/0021-9010.90.4.710
Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
Zhang, S. X., Wang, Y., Rauch, A., & Wei, F. (2020). Unprecedented disruption of lives and work: Health, distress and life satisfaction of working adults in China one month into the COVID-19 outbreak. Psychiatry Research, 112958.
Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314–324.
Al-Emran, M., Arpaci, I., & Salloum, S. A. (2020). An empirical examination of continuous intention to use m-learning: An integrated model. Education and Information Technologies, 25(4), 2899-2918. https://doi.org/10.1007/s10639-019-10094-2
Al-Emran, Mostafa, & Salloum, S. A. (2017). Students’ Attitudes Towards the Use of Mobile Technologies in e-Evaluation. International Journal of Interactive Mobile Technologies (IJIM), 11(5), 195–202.
Al-Maroof, R. A. S., & Al-Emran, M. (2018). Students Acceptance of Google Classroom: An Exploratory Study using PLS-SEM Approach. International Journal of Emerging Technologies in Learning, 13(6).
Al Hamad, A. Q. (2016, February). Students' perception of implementing a Smart Learning System (SLS) based on Moodle at Fujairah College. In 2016 13th International Conference on Remote Engineering and Virtual Instrumentation (REV) (pp. 315-318). IEEE.
AlHamad, A. Q., Al Omari, F., & AlHamad, A. Q. (2014). Recommendation for Managing Patients’ Privacy in an Integrated Health Information Network. Journal of Information Technology & Economic Development, 5(1), 47-52
AlHamad, A. Q., & Al Qawasmi, K. I. (2014). Building an ethical framework for e-learning management system at a university level. Journal of Engineering and Economic Development, 1(1), 11.
Alhamad, H, Patel, N., & Donyai, P. (2018). Beliefs and intentions towards reusing medicines in the future: A large-scale, cross-sectional study of patients in the UK. International Journal of Pharmacy Practice, 26, 4–36.
Alhamad, H., Abu‐Farha, R. K., Albahar, F., & Jaber, D. (2020). Public Perceptions about Pharmacists’ Role in Prescribing, Providing Education and Delivering Medications during COVID‐19 Pandemic Era. International journal of clinical practice, e13890.
Alhamad, H., & Donyai, P. (2020). Intentions to “Reuse” Medication in the Future Modelled and Measured Using the Theory of Planned Behavior. Pharmacy, 8(4), 213.
Alhamad, H., & Donyai, P. (2021). The Validity of the Theory of Planned Behaviour for Understanding People’s Beliefs and Intentions toward Reusing Medicines. Pharmacy, 9(1), 58.
AlHamad, A. Q., Yaacob, N., & Al-Omari, F. (2012, September). Applying JESS rules to personalize Learning Management System (LMS) using online quizzes. In 2012 15th International Conference on Interactive Collaborative Learning (ICL) (pp. 1-4). IEEE.
Al Kurdi, B., Alshurideh, M., & Salloum, S. A. (2020). Investigating a theoretical framework for e-learning technology acceptance. International Journal of Electrical and Computer Engineering (IJECE), 10(6), 6484-6496.
Alshamsi, A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020, October). The influence of service quality on customer retention: A systematic review in the higher education. In International Conference on Advanced Intelligent Systems and Informatics (pp. 404-416). Springer, Cham.
Alsharari, N. M., & Alshurideh, M. T. (2020). Student retention in higher education: the role of creativity, emotional intelligence and learner autonomy. International Journal of Educational Management, 35(1), 233-247.
Alshurideh, D. M. (2019). Do electronic loyalty programs still drive customer choice and repeat purchase behaviour?. International Journal of Electronic Customer Relationship Management, 12(1), 40-57.
Alshurideh, M., Al Kurdi, B., Salloum, S. A., Arpaci, I., & Al-Emran, M. (2020). Predicting the actual use of m-learning systems: a comparative approach using PLS-SEM and machine learning algorithms. Interactive Learning Environments, 1–15.
Alshurideh, M., Al Kurdi, B., Abumari, A., & Salloum, S. (2018). Pharmaceutical Promotion Tools Effect on Physician’s Adoption of Medicine Prescribing: Evidence from Jordan. Modern Applied Science, 12(11), 210-222.
Alshurideh, M. T., Al Kurdi, B., & Salloum, S. A. (2021). The moderation effect of gender on accepting electronic payment technology: a study on United Arab Emirates consumers. Review of International Business and Strategy.
Alshurideh, M. T., Kurdi, B. A., AlHamad, A. Q., Salloum, S. A., Alkurdi, S., Dehghan, A., ... & Masa’deh, R. E. (2021, June). Factors affecting the use of smart mobile examination platforms by universities’ postgraduate students during the COVID 19 pandemic: an empirical study. In Informatics (Vol. 8, No. 2, p. 32). Multidisciplinary Digital Publishing Institute.
Alshurideh, M., Masa'deh, R., & Alkurdi, B. (2012). The effect of customer satisfaction upon customer retention in the Jordanian mobile market: An empirical investigation. European Journal of Economics, Finance and Administrative Sciences, 47(12), 69-78.
Bailey, A. A., Pentina, I., Mishra, A. S., & Ben Mimoun, M. S. (2020). Exploring factors influencing US millennial consumers’ use of tap-and-go payment technology. The International Review of Retail, Distribution and Consumer Research, 30(2), 143–163.
Barclay, D., Higgins, C., & Thompson, R. (1995). The Partial Least Squares (pls) Approach to Casual Modeling: Personal Computer Adoption Ans Use as an Illustration.
Bettayeb, H., Alshurideh, M. T., & Al Kurdi, B. (2020). The effectiveness of Mobile Learning in UAE Universities: A systematic review of Motivation, Self-efficacy, Usability and Usefulness. International Journal of Control and Automation, 13(2), 1558-1579.
Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation-confirmation model. MIS Quarterly, 25(3), 351–370.
Bhattacherjee, A., & Hikmet, N. (2007). Physicians’ resistance toward healthcare information technology: a theoretical model and empirical test. European Journal of Information Systems, 16(6), 725–737.
Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS Quarterly, 29(3), 399–426.
Chuan, C. L., & Penyelidikan, J. (2006). Sample size estimation using Krejcie and Morgan and Cohen statistical power analysis: A comparison. Jurnal Penyelidikan IPBL, 7, 78–86.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Davis, Fred D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
Davis, Fred 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.
Distler, V., Lallemand, C., & Koenig, V. (2020). How Acceptable Is This? How User Experience Factors Can Broaden our Understanding of The Acceptance of Privacy Trade-offs. Computers in Human Behavior, 106, 106227.
Elshamy, A. M., Abdelghany, M. A., Alhamad, A. Q., Hamed, H. F., Kelash, H. M., & Hussein, A. I. (2017, September). Secure implementation for video streams based on fully and permutation encryption techniques. In 2017 International Conference on Computer and Applications (ICCA) (pp. 50-55). IEEE.
Gerhold, L. (2020). COVID-19: Risk perception and Coping strategies.
Goodhue, D. L., Lewis, W., & Thompson, R. (2012). Does PLS have adavantages for small sample size or non-normal data? MIS Quaterly, 36(3), 981-1001.
Gresham, J. (2020). Manufacturing Trends in Automated Inspection Equipment: Linking Technology with Business Change Management Using the Technology Acceptance Model. Northcentral University.
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.
Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442–458. https://doi.org/10.1108/IMDS-04-2016-0130
Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications.
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(1), 115–135.
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New challenges to international marketing (pp. 277–319). Emerald Group Publishing Limited.
Johnston, A. C., & Warkentin, M. (2010). Fear appeals and information security behaviors: an empirical study. MIS Quarterly, 34(3), 549–566.
Joo, Y. J., Kim, N., & Kim, N. H. (2016). Factors predicting online university students’ use of a mobile learning management system (m-LMS). Educational Technology Research and Development, 64(4), 611–630. https://doi.org/10.1007/s11423-016-9436-7
Kamal, S. A., Shafiq, M., & Kakria, P. (2020). Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM). Technology in Society, 60, 101212.
Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.
Krejcie, R. V, & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610.
Le, T. T., Pham, H. M., Chu, N. H., Nguyen, D. K., & Ngo, H. M. (2020). Factors Affecting Users’ Continuance Intention towards Mobile Banking In Vietnam. American Journal of Multidisciplinary Research & Development (AJMRD), 2(4), 42–51.
Liu, S.-H., Liao, H.-L., & Peng, C.-J. (2005). Applying the technology acceptance model and flow theory to online e-learning users’ acceptance behavior. E-Learning, 4(H6), H8.
Mac Callum, K., & Jeffrey, L. (2014). Comparing the role of ICT literacy and anxiety in the adoption of mobile learning. Computers in Human Behavior, 39, 8–19.
Makttoofa, N., Khalidb, H., & Abdullahc, I. (n.d.). The Effect of Individual Factors on the Adoption of Mobile Banking Within Banks in Iraq.
Meng, F., Guo, X., Zhang, X., Peng, Z., & Lai, K.-H. (2020). Examining the Role of Technology Anxiety and Health Anxiety on Elderly Users’ Continuance Intention for Mobile Health Services Use. Proceedings of the 53rd Hawaii International Conference on System Sciences.
Nascimento, B., Oliveira, T., & Tam, C. (2018). Wearable technology: What explains continuance intention in smartwatches? Journal of Retailing and Consumer Services, 43, 157–169.
Nchunge, D. M., Sakwa, M., & Mwangi, W. (2012). User’s perception on ICT adoption for education support in schools: a survey of secondary school teacher’s in Thika district Kenya. International Journal of Humanities and Social Science, 2(10), 17–29.
Nicomedes, C. J., & Avila, R. M. (2020). An Analysis on the Panic of Filipinos During COVID-19 Pandemic in the Philippines.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory. In McGraw-Hill, New York. https://doi.org/10.1037/018882
Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. Bönningstedt: SmartPLS.
Tam, C., Santos, D., & Oliveira, T. (2020). Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model. Information Systems Frontiers, 22(1), 243-257.
Tarhini, A., Hone, K., & Liu, X. (2015). A cross‐cultural examination of the impact of social, organisational and individual factors on educational technology acceptance between B ritish and L ebanese university students. British Journal of Educational Technology, 46(4), 739–755.
Teo, T. (2012). Examining the intention to use technology among pre-service teachers: An integration of the technology acceptance model and theory of planned behavior. Interactive Learning Environments, 20(1), 3–18.
Thatcher, J. B., & Perrewe, P. L. (2002). An empirical examination of individual traits as antecedents to computer anxiety and computer self-efficacy. MIS Quarterly, 26(4), 381–396.
Urbach, N., & Ahlemann, F. (2010). Structural equation modeling in information systems research using partial least squares. Journal of Information Technology Theory and Application, 11(2), 5–40. https://doi.org/10.1037/0021-9010.90.4.710
Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
Zhang, S. X., Wang, Y., Rauch, A., & Wei, F. (2020). Unprecedented disruption of lives and work: Health, distress and life satisfaction of working adults in China one month into the COVID-19 outbreak. Psychiatry Research, 112958.