How to cite this paper
Al-Maroof, R., Ayoubi, K., Alhumaid, K., Aburayya, A., Alshurideh, M., Alfaisal, R & Salloum, S. (2021). The acceptance of social media video for knowledge acquisition, sharing and application: A com-parative study among YouTube users and TikTok Users’ for medical purposes.International Journal of Data and Network Science, 5(3), 197-214.
Refrences
Aburayya, A., Alshurideh, M., Al Marzouqi, A., Al Diabat, O., Alfarsi, A., Suson, R., Bash, M., & Salloum, S. A. (2020). An Empirical Examination of the Effect of TQM Practices on Hospital Service Quality: An Assessment Study in UAE Hospitals. Systematic Reviews in Pharmacy, 11(9), 347-362. https://doi.org/10.31838/srp.2020.9.51).
Al Kurdi, B., Alshurideh, M., Nuseir, M., Aburayya, A., & Salloum, S.A. (n.d.). The Effects of Subjective Norm on the Intention to Use Social Media Networks: An Exploratory Study Using PLS-SEM and Machine Learning Approach.
Agarwal, R., & Karahanna, E. (2000). Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665–694.
Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204–215.
Ahmed, A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2021). Digital Transformation and Organizational Operational Decision Making: A Systematic Review. Advances in Intelligent Systems and Computing (Vol. 1261 AISC). https://doi.org/10.1007/978-3-030-58669-0_63
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, 1–20.
Al-Emran, M., & 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-hawari, M. A., & Mouakket, S. (2010). The influence of technology acceptance model (tam) factors on students’e-satisfaction and e-retention within the context of uae e-learning. Education, Business and Society: Contemporary Middle Eastern Issues, 3(4), 299–314.
Al-Maroof R.A., Arpaci I., Al-Emran M., Salloum S.A., S. K. (2021). Examining the Acceptance of WhatsApp Stickers Through Machine Learning Algorithms. In: Al-Emran M., Shaalan K., Hassanien A. (Eds) Recent Advances in Intelligent Systems and Smart Applications. Studies in Systems, Decision and Control, Vol 295. Springer, Cham.
Al-Maroof, R.S., Alfaisal, A. M., & Salloum, S. A. (2020). Google glass adoption in the educational environment: A case study in the Gulf area. Education and Information Technologies. https://doi.org/10.1007/s10639-020-10367-1
Al-Maroof, R.S., Salloum, S. A., Hassanien, A. E., & Shaalan, K. (2020). Fear from COVID-19 and technology adoption: the impact of Google Meet during Coronavirus pandemic. Interactive Learning Environments. https://doi.org/10.1080/10494820.2020.1830121
Al-Maroof, Rana Saeed, Alhumaid, K., Alhamad, A. Q., Aburayya, A., & Salloum, S. (2021). User acceptance of smart watch for medical purposes: an empirical study. Future Internet, 13(5), 127.
Al-Maroof, Rana Saeed, Alshurideh, M. T., Salloum, S. A., AlHamad, A. Q. M., & Gaber, T. (2021). Acceptance of Google Meet during the spread of Coronavirus by Arab university students. In Informatics (Vol. 8, p. 24). Multidisciplinary Digital Publishing Institute.
Al-Skaf, S., Youssef, E., Habes, M., Alhumaid, K., & Salloum, S. A. (2021). The Acceptance of Social Media Sites: An Empirical Study Using PLS-SEM and ML Approaches. In Advanced Machine Learning Technologies and Applications: Proceedings of AMLTA 2021 (pp. 548–558). Springer International Publishing.
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.
Al Suwaidi, F., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2021). The Impact of Innovation Management in SMEs Performance: A Systematic Review. Advances in Intelligent Systems and Computing (Vol. 1261 AISC). https://doi.org/10.1007/978-3-030-58669-0_64
Alghizzawi, M., Ghani, M. A., Som, A. P. M., Ahmad, M. F., Amin, A., Bakar, N. A., … Habes, M. (2018). The Impact of Smartphone Adoption on Marketing Therapeutic Tourist Sites in Jordan. International Journal of Engineering & Technology, 7(4.34), 91–96.
Alghizzawi, M., Habes, M., Salloum, S. A., Ghani, M. A., Mhamdi, C., & Shaalan, K. (2019). The effect of social media usage on students’e-learning acceptance in higher education: A case study from the United Arab Emirates. International Journal of Information Technology and Language Studies, 3(3).
Alhashmi, S.F.S., Salloum, S. A., & Abdallah, S. (2020). Critical Success Factors for Implementing Artificial Intelligence (AI) Projects in Dubai Government United Arab Emirates (UAE) Health Sector: Applying the Extended Technology Acceptance Model (TAM). Advances in Intelligent Systems and Computing (Vol. 1058). https://doi.org/10.1007/978-3-030-31129-2_36
Alhashmi, Shaikha F S, Salloum, S. A., & Mhamdi, C. (2019). Implementing Artificial Intelligence in the United Arab Emirates Healthcare Sector: An Extended Technology Acceptance Model. International Journal of Information Technology and Language Studies, 3(3).
Almansoori A., AlShamsi M., Salloum S.A., S. K. (2021). Critical Review of Knowledge Management in Healthcare. In: Al-Emran M., Shaalan K., Hassanien A. (Eds) Recent Advances in Intelligent Systems and Smart Applications. Studies in Systems, Decision and Control, Vol 295. Springer, Cham.
Almazrouei, F. A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2021). Social Media Impact on Business: A Systematic Review. Advances in Intelligent Systems and Computing (Vol. 1261 AISC). https://doi.org/10.1007/978-3-030-58669-0_62
AlQudah, A. A., Salloum, S. A., & Shaalan, K. (2021). The Role of Technology Acceptance in Healthcare to Mitigate COVID-19 Outbreak. Emerging Technologies During the Era of COVID-19 Pandemic, 348, 223.
Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020). Examining the Main Mobile Learning System Drivers’ Effects: A Mix Empirical Examination of Both the Expectation-Confirmation Model (ECM) and the Technology Acceptance Model (TAM). Advances in Intelligent Systems and Computing (Vol. 1058). https://doi.org/10.1007/978-3-030-31129-2_37
Alshurideh, M. T., Kurdi, B. Al, AlHamad, A. Q., Salloum, S. A., Alkurdi, S., Dehghan, A., … Masa’deh, R. (2021). 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, p. 32). Multidisciplinary Digital Publishing Institute.
Alshurideh, M. (2018). Pharmaceutical Promotion Tools Effect on Physician’s Adoption of Medicine Prescribing: Evidence from Jordan. Modern Applied Science, 12(11), 210-222.
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.
Altalhi, M. M. (2021). Towards Understanding the Students’ Acceptance of MOOCs: A Unified Theory of Acceptance and Use of Technology (UTAUT). International Journal of Emerging Technologies in Learning (IJET), 16(2), 237–253.
Alyammahi, A., Alshurideh, M., Kurdi, B. A., & Salloum, S. A. (2021). The Impacts of Communication Ethics on Workplace Decision Making and Productivity. Advances in Intelligent Systems and Computing (Vol. 1261 AISC). https://doi.org/10.1007/978-3-030-58669-0_44
Ang, C. S., Zaphiris, P., & Mahmood, S. (2007). A model of cognitive loads in massively multiplayer online role playing games. Interacting with Computers, 19(2), 167–179.
Barclay, D., Higgins, C., & Thompson, R. (1995). The Partial Least Squares (pls) Approach to Casual Modeling: Personal Computer Adoption Ans Use as an Illustration.
Bavarsad, B., & Mennatyan, M. A. (2013). A Study of the effects of technology acceptance factors on users’ satisfaction of E-government services. World Applied Programming, 3(5), 190–199.
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.
Bilgihan, A., Okumus, F., Nusair, K., & Bujisic, M. (2014). Online experiences: flow theory, measuring online customer experience in e-commerce and managerial implications for the lodging industry. Information Technology & Tourism, 14(1), 49–71.
Bölen, M. C., Calisir, H., & Özen, Ü. (2021). Flow theory in the information systems life cycle: The state of the art and future research agenda. International Journal of Consumer Studies.
Boyinbode, O. K., Agbonifo, O. C., & Ogundare, A. (2017). Supporting mobile learning with WhatsApp based on media richness. Circulation in Computer Science, 2(3), 37–46.
Chatzoglou, P., Chatzoudes, D., Ioakeimidou, D., & Tokoutsi, A. (2020). Generation Z: Factors affecting the use of Social Networking Sites (SNSs). In 2020 15th International Workshop on Semantic and Social Media Adaptation and Personalization (SMA (pp. 1–6). IEEE.
Cheng, Y.-H., & Huang, T.-Y. (2013). High speed rail passengers’ mobile ticketing adoption. Transportation Research Part C: Emerging Technologies, 30, 143–160.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295–336.
Cho, J., Cheon, Y., Jun, J. W., & Lee, S. (2021). Digital advertising policy acceptance by out-of-home advertising firms: a combination of TAM and TOE framework. International Journal of Advertising, 1–19.
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.
Ciftci, O., Berezina, K., & Kang, M. (2021). Effect of Personal Innovativeness on Technology Adoption in Hospitality and Tourism: Meta-analysis. In Information and Communication Technologies in Tourism 2021 (pp. 162–174). Springer.
Csikszentmihalyi, M. (1988). The flow experience and its significance for human psychology.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319–340.
Dawud, Y., & Nikolic, S. (2020). Impact of Gamification on Social Network Platforms.
De Wulf, K., Schillewaert, N., Muylle, S., & Rangarajan, D. (2006). The role of pleasure in web site success. Information & Management, 43(4), 434–446.
Deci, E. (1985). L Intrinsic motivation and self-determination in human behavior/EL Deci, RM Ryan.
Dehghani, M., Niaki, M. K., Ramezani, I., & Sali, R. (2016). Evaluating the influence of YouTube advertising for attraction of young customers. Computers in Human Behavior, 59, 165–172.
DeWitt, D., Alias, N., Siraj, S., Yaakub, M. Y., Ayob, J., & Ishak, R. (2013). The potential of Youtube for teaching and learning in the performing arts. Procedia-Social and Behavioral Sciences, 103, 1118–1126.
Dijkstra, T. K., & Henseler, J. (2015). Consistent and asymptotically normal PLS estimators for linear structural equations. Computational Statistics & Data Analysis, 81, 10–23.
DU, C. T., NGO, T. T., TRAN, T. Van, & NGUYEN, N. B. T. (2021). Consumption Value, Consumer Innovativeness and New Product Adoption: Empirical Evidence from Vietnam. The Journal of Asian Finance, Economics and Business, 8(3), 1275–1286.
Duffy, P. (2008). Engaging the YouTube Google-eyed generation: Strategies for using Web 2.0 in teaching and learning. Electronic Journal of E-Learning, 6(2), 119–130.
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models With Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312
Fredrickson, B. L., Tugade, M. M., Waugh, C. E., & Larkin, G. R. (2003). What good are positive emotions in crisis? A prospective study of resilience and emotions following the terrorist attacks on the United States on September 11th, 2001. Journal of Personality and Social Psychology, 84(2), 365.
Gefen, D., & Straub, D. W. (2000). The relative importance of perceived ease of use in IS adoption: A study of e-commerce adoption. Journal of the Association for Information Systems, 1(1), 8.
George, A., & Kumar, G. S. G. (2013). Antecedents of customer satisfaction in internet banking: Technology acceptance model (TAM) redefined. Global Business Review, 14(4), 627–638.
Goodhue, D. L., Lewis, W., & Thompson, R. (2012). Does PLS have adavantages for small sample size or non-normal data? MIS Quaterly.
Gupta, K. P. (2021). Understanding learners’ completion intention of massive open online courses (MOOCs): role of personality traits and personal innovativeness. International Journal of Educational Management.
Habes, M., Salloum, S. A., Alghizzawi, M., & Mhamdi, C. (2019). The Relation Between Social Media and Students’ Academic Performance in Jordan: YouTube Perspective. In International Conference on Advanced Intelligent Systems and Informatics (pp. 382–392). Springer.
Hair, J., Hult, G. T. M., Ringle, C., Sarstedt, M., Hair, J. F. F., Hult, G. T. M., … Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications.
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.
Hameed, I., Zaman, U., Waris, I., & Shafique, O. (2021). A Serial-Mediation Model to Link Entrepreneurship Education and Green Entrepreneurial Behavior: Application of Resource-Based View and Flow Theory. International Journal of Environmental Research and Public Health, 18(2), 550.
Han, M., & Zhang, X. (2020). Prospects for the advancement of the TikTok in the age of 5G communication. In 2020 13th CMI Conference on Cybersecurity and Privacy (CMI)-Digital Transformation-Potentials and Challenges (51275) (pp. 1–5). IEEE.
Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., … Calantone, R. J. (2014). Common beliefs and reality about PLS: Comments on Rönkkö and Evermann (2013). Organizational Research Methods, 17(2), 182–209.
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.
Hoffman, D. L., & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing, 60(3), 50–68.
Hoffman, D. L., & Novak, T. P. (2009). Flow online: lessons learned and future prospects. Journal of Interactive Marketing, 23(1), 23–34.
Hu, L., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3(4), 424.
Huang, Y.-M., Huang, Y.-M., Huang, S.-H., & Lin, Y.-T. (2012). A ubiquitous English vocabulary learning system: Evidence of active/passive attitudes vs. usefulness/ease-of-use. Computers & Education, 58(1), 273–282.
Hung, C.-L., Chou, J. C.-L., & Ding, C.-M. (2012). Enhancing mobile satisfaction through integration of usability and flow. Engineering Management Research, 1(1), 44.
Jaffar, A. A. (2012). YouTube: An emerging tool in anatomy education. Anatomical Sciences Education, 5(3), 158–164.
Jung, I., & Lee, Y. (2015). YouTube acceptance by university educators and students: a cross-cultural perspective. Innovations in Education and Teaching International, 52(3), 243–253.
Jung, Y., Perez-Mira, B., & Wiley-Patton, S. (2009). Consumer adoption of mobile TV: Examining psychological flow and media content. Computers in Human Behavior, 25(1), 123–129.
Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.
Krauskopf, K., Zahn, C., & Hesse, F. W. (2012). Leveraging the affordances of Youtube: The role of pedagogical knowledge and mental models of technology functions for lesson planning with technology. Computers & Education, 58(4), 1194–1206.
Krejcie, R. V, & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610.
Larsen, T. J., Sørebø, A. M., & Sørebø, Ø. (2009). The role of task-technology fit as users’ motivation to continue information system use. Computers in Human Behavior, 25(3), 778–784.
Lee, D. Y., & Lehto, M. R. (2013). User acceptance of YouTube for procedural learning: An extension of the Technology Acceptance Model. Computers and Education, 61(1), 193–208. https://doi.org/10.1016/j.compedu.2012.10.001
Lee, M.-C., & Tsai, T.-R. (2010). What drives people to continue to play online games? An extension of technology model and theory of planned behavior. Intl. Journal of Human–Computer Interaction, 26(6), 601–620.
Lewis, W., Agarwal, R., & Sambamurthy, V. (2003). Sources of influence on beliefs about information technology use: An empirical study of knowledge workers. MIS Quarterly, 657–678.
Liao, C., Palvia, P., & Chen, J.-L. (2009). Information technology adoption behavior life cycle: Toward a Technology Continuance Theory (TCT). International Journal of Information Management, 29(4), 309–320.
Liaw, S.-S. (2008). Investigating students’ perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system. Computers & Education, 51(2), 864–873.
Limayem, M., Hirt, S. G., & Chin, W. W. (2001). Intention does not always matter: the contingent role of habit on IT usage behavior. ECIS 2001 Proceedings, 56.
Lohmöller, J. B. (1989). Latent variable path modeling with partial least squares. Heidelberg, Germany: Physica-Verlag.
Lu, J., Yao, J. E., & Yu, C.-S. (2005). Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. The Journal of Strategic Information Systems, 14(3), 245–268.
Mehrez, A. A. A., Alshurideh, M., Kurdi, B. A., & Salloum, S. A. (2021). Internal Factors Affect Knowledge Management and Firm Performance: A Systematic Review. Advances in Intelligent Systems and Computing (Vol. 1261 AISC). https://doi.org/10.1007/978-3-030-58669-0_57
Mhamdi, C., Al-Emran, M., & Salloum, S. A. (2018). Text mining and analytics: A case study from news channels posts on Facebook. Studies in Computational Intelligence (Vol. 740). https://doi.org/10.1007/978-3-319-67056-0_19
Mir, I. A., & Ur REHMAN, K. (2013). Factors affecting consumer attitudes and intentions toward user-generated product content on YouTube. Management & Marketing, 8(4).
Mun, Y. Y., Jackson, J. D., Park, J. S., & Probst, J. C. (2006). Understanding information technology acceptance by individual professionals: Toward an integrative view. Information & Management, 43(3), 350–363.
Niederhauser, D. S., & Perkmen, S. (2010). Beyond self-efficacy: Measuring pre-service teachers’ instructional technology outcome expectations. Computers in Human Behavior, 26(3), 436–442.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory. McGraw-Hill, New York. https://doi.org/10.1037/018882
Nunnally, Jum C, & Bernstein, I. H. (1978). Psychometric theory.
Oliver, R. L. (1981). Measurement and evaluation of satisfaction processes in retail settings. Journal of Retailing.
Omar, B., & Dequan, W. (2020). Watch, share or create: The influence of personality traits and user motivation on TikTok mobile video usage.
Ong, C.-S., & Lai, J.-Y. (2006). Gender differences in perceptions and relationships among dominants of e-learning acceptance. Computers in Human Behavior, 22(5), 816–829.
Oum, S., & Han, D. (2011). An empirical study of the determinants of the intention to participate in user-created contents (UCC) services. Expert Systems with Applications, 38(12), 15110–15121.
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.
Pituch, K. A., & Lee, Y. (2006). The influence of system characteristics on e-learning use. Computers & Education, 47(2), 222–244.
Rai, R. S., & Selnes, F. (2019). Conceptualizing task-technology fit and the effect on adoption–A case study of a digital textbook service. Information & Management, 56(8), 103161.
Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. Bönningstedt: SmartPLS.
Rogers, E. (1995). Diffusion of Innovations (Fourth Paperback ed.). New York: The Free Press Simon & Schuster Inc.
Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54–67.
Ryu, M.-H., Kim, S., & Lee, E. (2009). Understanding the factors affecting online elderly user’s participation in video UCC services. Computers in Human Behavior, 25(3), 619–632.
Salloum, S. A. (n.d.). Predicting the Intention to Use Social Media Sites: A Hybrid SEM-Machine Learning Approach. Advanced Machine Learning Technologies and Applications: Proceedings of AMLTA 2021, 324.
Salloum, S. A., Al-Emran, M., Abdallah, S., & Shaalan, K. (2017). Analyzing the Arab Gulf Newspapers Using Text Mining Techniques. In International Conference on Advanced Intelligent Systems and Informatics (pp. 396–405). Springer. https://doi.org/10.1007/978-3-319-64861-3_37
Salloum, S. A., Al-Emran, M., Habes, M., Alghizzawi, M., Ghani, M. A., & Shaalan, K. (2021). What Impacts the Acceptance of E-learning Through Social Media? An Empirical Study. Recent Advances in Technology Acceptance Models and Theories, 419–431.
Salloum, S. A., Al-Emran, M., & Shaalan, K. (2016). A Survey of Lexical Functional Grammar in the Arabic Context. Int. J. Com. Net. Tech, 4(3).
Salloum, S. A., Alhamad, A. Q. M., Al-Emran, M., Monem, A. A., & Shaalan, K. (2019). Exploring Students’ Acceptance of E-Learning Through the Development of a Comprehensive Technology Acceptance Model. IEEE Access, 7, 128445–128462.
Salloum, S. A., Maqableh, W., Mhamdi, C., Al Kurdi, B., & Shaalan, K. (2018). Studying the Social Media Adoption by university students in the United Arab Emirates. International Journal of Information Technology and Language Studies, 2(3).
Salloum, S. A., Mhamdi, C., Al Kurdi, B., & Shaalan, K. (2018). Factors affecting the Adoption and Meaningful Use of Social Media: A Structural Equation Modeling Approach. International Journal of Information Technology and Language Studies, 2(3).
Sánchez, R. A., & Hueros, A. D. (2010). Motivational factors that influence the acceptance of Moodle using TAM. Computers in Human Behavior, 26(6), 1632–1640.
Serenko, A. (2008). A model of user adoption of interface agents for email notification. Interacting with Computers, 20(4–5), 461–472.
Seyed Esfahani, M., & Reynolds, N. (2021). Impact of consumer innovativeness on really new product adoption. Marketing Intelligence & Planning.
Shah, S. F., Alshurideh, M., Kurdi, B. A., & Salloum, S. A. (2021). The Impact of the Behavioral Factors on Investment Decision-Making: A Systemic Review on Financial Institutions. Advances in Intelligent Systems and Computing (Vol. 1261 AISC). https://doi.org/10.1007/978-3-030-58669-0_9
Shang, R.-A., Chen, Y.-C., & Shen, L. (2005). Extrinsic versus intrinsic motivations for consumers to shop on-line. Information & Management, 42(3), 401–413.
Shee, D. Y., & Wang, Y.-S. (2008). Multi-criteria evaluation of the web-based e-learning system: A methodology based on learner satisfaction and its applications. Computers & Education, 50(3), 894–905.
Siersdorfer, S., Chelaru, S., Nejdl, W., & San Pedro, J. (2010). How useful are your comments? Analyzing and predicting YouTube comments and comment ratings. In Proceedings of the 19th international conference on World wide web (pp. 891–900).
Szymanski, D. M., & Hise, R. T. (2000). E-satisfaction: an initial examination. Journal of Retailing, 76(3), 309–322.
Tan, C.-H., Yang, X., & Teo, H.-H. (2007). When Counterfactual Thinking Meets the Technology Acceptance Model. In IFIP International Working Conference on Organizational Dynamics of Technology-Based Innovation (pp. 507–511). Springer.
Teo, T. (2011). Technology acceptance research in education. In Technology acceptance in education (pp. 1–5). Springer.
Trial, D. (n.d.). Model Fit.
Tung, F.-C., & Chang, S.-C. (2008). Nursing students’ behavioral intention to use online courses: A questionnaire survey. International Journal of Nursing Studies, 45(9), 1299–1309.
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., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425–478.
Wang, S., & Fu, R. (2020). Research on the Influencing Factors of the Communication Effect of Tik Tok Short Videos About Intangible Cultural Heritage. In International Conference on Applied Human Factors and Ergonomics (pp. 275–282). Springer.
Wang, Y.-S., Wang, H.-Y., & Shee, D. Y. (2007). Measuring e-learning systems success in an organizational context: Scale development and validation. Computers in Human Behavior, 23(4), 1792–1808.
Wang, Y. (2020). Humor and camera view on mobile short-form video apps influence user experience and technology-adoption intent, an example of TikTok (DouYin). Computers in Human Behavior, 110, 106373.
Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85–102.
Wu, J.-H., Tennyson, R. D., & Hsia, T.-L. (2010). A study of student satisfaction in a blended e-learning system environment. Computers & Education, 55(1), 155–164.
Xu, H., & Gupta, S. (2009). The effects of privacy concerns and personal innovativeness on potential and experienced customers’ adoption of location-based services. Electronic Markets, 19(2–3), 137–149.
Yang, Y., & Zilberg, I. E. (2020). Understanding Young Adults’ TikTok Usage.
Zhu, Y., Dong, J., Qi, X., & Deng, J. (2021). Intention to use Governmental Micro-Video in the Pandemic of Covid-19: An Empirical Study of Governmental Tik Tok in China. In 2021 6th International Conference on Inventive Computation Technologies (ICICT) (pp. 976–979). IEEE.
Al Kurdi, B., Alshurideh, M., Nuseir, M., Aburayya, A., & Salloum, S.A. (n.d.). The Effects of Subjective Norm on the Intention to Use Social Media Networks: An Exploratory Study Using PLS-SEM and Machine Learning Approach.
Agarwal, R., & Karahanna, E. (2000). Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665–694.
Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204–215.
Ahmed, A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2021). Digital Transformation and Organizational Operational Decision Making: A Systematic Review. Advances in Intelligent Systems and Computing (Vol. 1261 AISC). https://doi.org/10.1007/978-3-030-58669-0_63
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, 1–20.
Al-Emran, M., & 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-hawari, M. A., & Mouakket, S. (2010). The influence of technology acceptance model (tam) factors on students’e-satisfaction and e-retention within the context of uae e-learning. Education, Business and Society: Contemporary Middle Eastern Issues, 3(4), 299–314.
Al-Maroof R.A., Arpaci I., Al-Emran M., Salloum S.A., S. K. (2021). Examining the Acceptance of WhatsApp Stickers Through Machine Learning Algorithms. In: Al-Emran M., Shaalan K., Hassanien A. (Eds) Recent Advances in Intelligent Systems and Smart Applications. Studies in Systems, Decision and Control, Vol 295. Springer, Cham.
Al-Maroof, R.S., Alfaisal, A. M., & Salloum, S. A. (2020). Google glass adoption in the educational environment: A case study in the Gulf area. Education and Information Technologies. https://doi.org/10.1007/s10639-020-10367-1
Al-Maroof, R.S., Salloum, S. A., Hassanien, A. E., & Shaalan, K. (2020). Fear from COVID-19 and technology adoption: the impact of Google Meet during Coronavirus pandemic. Interactive Learning Environments. https://doi.org/10.1080/10494820.2020.1830121
Al-Maroof, Rana Saeed, Alhumaid, K., Alhamad, A. Q., Aburayya, A., & Salloum, S. (2021). User acceptance of smart watch for medical purposes: an empirical study. Future Internet, 13(5), 127.
Al-Maroof, Rana Saeed, Alshurideh, M. T., Salloum, S. A., AlHamad, A. Q. M., & Gaber, T. (2021). Acceptance of Google Meet during the spread of Coronavirus by Arab university students. In Informatics (Vol. 8, p. 24). Multidisciplinary Digital Publishing Institute.
Al-Skaf, S., Youssef, E., Habes, M., Alhumaid, K., & Salloum, S. A. (2021). The Acceptance of Social Media Sites: An Empirical Study Using PLS-SEM and ML Approaches. In Advanced Machine Learning Technologies and Applications: Proceedings of AMLTA 2021 (pp. 548–558). Springer International Publishing.
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.
Al Suwaidi, F., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2021). The Impact of Innovation Management in SMEs Performance: A Systematic Review. Advances in Intelligent Systems and Computing (Vol. 1261 AISC). https://doi.org/10.1007/978-3-030-58669-0_64
Alghizzawi, M., Ghani, M. A., Som, A. P. M., Ahmad, M. F., Amin, A., Bakar, N. A., … Habes, M. (2018). The Impact of Smartphone Adoption on Marketing Therapeutic Tourist Sites in Jordan. International Journal of Engineering & Technology, 7(4.34), 91–96.
Alghizzawi, M., Habes, M., Salloum, S. A., Ghani, M. A., Mhamdi, C., & Shaalan, K. (2019). The effect of social media usage on students’e-learning acceptance in higher education: A case study from the United Arab Emirates. International Journal of Information Technology and Language Studies, 3(3).
Alhashmi, S.F.S., Salloum, S. A., & Abdallah, S. (2020). Critical Success Factors for Implementing Artificial Intelligence (AI) Projects in Dubai Government United Arab Emirates (UAE) Health Sector: Applying the Extended Technology Acceptance Model (TAM). Advances in Intelligent Systems and Computing (Vol. 1058). https://doi.org/10.1007/978-3-030-31129-2_36
Alhashmi, Shaikha F S, Salloum, S. A., & Mhamdi, C. (2019). Implementing Artificial Intelligence in the United Arab Emirates Healthcare Sector: An Extended Technology Acceptance Model. International Journal of Information Technology and Language Studies, 3(3).
Almansoori A., AlShamsi M., Salloum S.A., S. K. (2021). Critical Review of Knowledge Management in Healthcare. In: Al-Emran M., Shaalan K., Hassanien A. (Eds) Recent Advances in Intelligent Systems and Smart Applications. Studies in Systems, Decision and Control, Vol 295. Springer, Cham.
Almazrouei, F. A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2021). Social Media Impact on Business: A Systematic Review. Advances in Intelligent Systems and Computing (Vol. 1261 AISC). https://doi.org/10.1007/978-3-030-58669-0_62
AlQudah, A. A., Salloum, S. A., & Shaalan, K. (2021). The Role of Technology Acceptance in Healthcare to Mitigate COVID-19 Outbreak. Emerging Technologies During the Era of COVID-19 Pandemic, 348, 223.
Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020). Examining the Main Mobile Learning System Drivers’ Effects: A Mix Empirical Examination of Both the Expectation-Confirmation Model (ECM) and the Technology Acceptance Model (TAM). Advances in Intelligent Systems and Computing (Vol. 1058). https://doi.org/10.1007/978-3-030-31129-2_37
Alshurideh, M. T., Kurdi, B. Al, AlHamad, A. Q., Salloum, S. A., Alkurdi, S., Dehghan, A., … Masa’deh, R. (2021). 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, p. 32). Multidisciplinary Digital Publishing Institute.
Alshurideh, M. (2018). Pharmaceutical Promotion Tools Effect on Physician’s Adoption of Medicine Prescribing: Evidence from Jordan. Modern Applied Science, 12(11), 210-222.
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.
Altalhi, M. M. (2021). Towards Understanding the Students’ Acceptance of MOOCs: A Unified Theory of Acceptance and Use of Technology (UTAUT). International Journal of Emerging Technologies in Learning (IJET), 16(2), 237–253.
Alyammahi, A., Alshurideh, M., Kurdi, B. A., & Salloum, S. A. (2021). The Impacts of Communication Ethics on Workplace Decision Making and Productivity. Advances in Intelligent Systems and Computing (Vol. 1261 AISC). https://doi.org/10.1007/978-3-030-58669-0_44
Ang, C. S., Zaphiris, P., & Mahmood, S. (2007). A model of cognitive loads in massively multiplayer online role playing games. Interacting with Computers, 19(2), 167–179.
Barclay, D., Higgins, C., & Thompson, R. (1995). The Partial Least Squares (pls) Approach to Casual Modeling: Personal Computer Adoption Ans Use as an Illustration.
Bavarsad, B., & Mennatyan, M. A. (2013). A Study of the effects of technology acceptance factors on users’ satisfaction of E-government services. World Applied Programming, 3(5), 190–199.
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.
Bilgihan, A., Okumus, F., Nusair, K., & Bujisic, M. (2014). Online experiences: flow theory, measuring online customer experience in e-commerce and managerial implications for the lodging industry. Information Technology & Tourism, 14(1), 49–71.
Bölen, M. C., Calisir, H., & Özen, Ü. (2021). Flow theory in the information systems life cycle: The state of the art and future research agenda. International Journal of Consumer Studies.
Boyinbode, O. K., Agbonifo, O. C., & Ogundare, A. (2017). Supporting mobile learning with WhatsApp based on media richness. Circulation in Computer Science, 2(3), 37–46.
Chatzoglou, P., Chatzoudes, D., Ioakeimidou, D., & Tokoutsi, A. (2020). Generation Z: Factors affecting the use of Social Networking Sites (SNSs). In 2020 15th International Workshop on Semantic and Social Media Adaptation and Personalization (SMA (pp. 1–6). IEEE.
Cheng, Y.-H., & Huang, T.-Y. (2013). High speed rail passengers’ mobile ticketing adoption. Transportation Research Part C: Emerging Technologies, 30, 143–160.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295–336.
Cho, J., Cheon, Y., Jun, J. W., & Lee, S. (2021). Digital advertising policy acceptance by out-of-home advertising firms: a combination of TAM and TOE framework. International Journal of Advertising, 1–19.
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.
Ciftci, O., Berezina, K., & Kang, M. (2021). Effect of Personal Innovativeness on Technology Adoption in Hospitality and Tourism: Meta-analysis. In Information and Communication Technologies in Tourism 2021 (pp. 162–174). Springer.
Csikszentmihalyi, M. (1988). The flow experience and its significance for human psychology.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319–340.
Dawud, Y., & Nikolic, S. (2020). Impact of Gamification on Social Network Platforms.
De Wulf, K., Schillewaert, N., Muylle, S., & Rangarajan, D. (2006). The role of pleasure in web site success. Information & Management, 43(4), 434–446.
Deci, E. (1985). L Intrinsic motivation and self-determination in human behavior/EL Deci, RM Ryan.
Dehghani, M., Niaki, M. K., Ramezani, I., & Sali, R. (2016). Evaluating the influence of YouTube advertising for attraction of young customers. Computers in Human Behavior, 59, 165–172.
DeWitt, D., Alias, N., Siraj, S., Yaakub, M. Y., Ayob, J., & Ishak, R. (2013). The potential of Youtube for teaching and learning in the performing arts. Procedia-Social and Behavioral Sciences, 103, 1118–1126.
Dijkstra, T. K., & Henseler, J. (2015). Consistent and asymptotically normal PLS estimators for linear structural equations. Computational Statistics & Data Analysis, 81, 10–23.
DU, C. T., NGO, T. T., TRAN, T. Van, & NGUYEN, N. B. T. (2021). Consumption Value, Consumer Innovativeness and New Product Adoption: Empirical Evidence from Vietnam. The Journal of Asian Finance, Economics and Business, 8(3), 1275–1286.
Duffy, P. (2008). Engaging the YouTube Google-eyed generation: Strategies for using Web 2.0 in teaching and learning. Electronic Journal of E-Learning, 6(2), 119–130.
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models With Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312
Fredrickson, B. L., Tugade, M. M., Waugh, C. E., & Larkin, G. R. (2003). What good are positive emotions in crisis? A prospective study of resilience and emotions following the terrorist attacks on the United States on September 11th, 2001. Journal of Personality and Social Psychology, 84(2), 365.
Gefen, D., & Straub, D. W. (2000). The relative importance of perceived ease of use in IS adoption: A study of e-commerce adoption. Journal of the Association for Information Systems, 1(1), 8.
George, A., & Kumar, G. S. G. (2013). Antecedents of customer satisfaction in internet banking: Technology acceptance model (TAM) redefined. Global Business Review, 14(4), 627–638.
Goodhue, D. L., Lewis, W., & Thompson, R. (2012). Does PLS have adavantages for small sample size or non-normal data? MIS Quaterly.
Gupta, K. P. (2021). Understanding learners’ completion intention of massive open online courses (MOOCs): role of personality traits and personal innovativeness. International Journal of Educational Management.
Habes, M., Salloum, S. A., Alghizzawi, M., & Mhamdi, C. (2019). The Relation Between Social Media and Students’ Academic Performance in Jordan: YouTube Perspective. In International Conference on Advanced Intelligent Systems and Informatics (pp. 382–392). Springer.
Hair, J., Hult, G. T. M., Ringle, C., Sarstedt, M., Hair, J. F. F., Hult, G. T. M., … Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications.
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.
Hameed, I., Zaman, U., Waris, I., & Shafique, O. (2021). A Serial-Mediation Model to Link Entrepreneurship Education and Green Entrepreneurial Behavior: Application of Resource-Based View and Flow Theory. International Journal of Environmental Research and Public Health, 18(2), 550.
Han, M., & Zhang, X. (2020). Prospects for the advancement of the TikTok in the age of 5G communication. In 2020 13th CMI Conference on Cybersecurity and Privacy (CMI)-Digital Transformation-Potentials and Challenges (51275) (pp. 1–5). IEEE.
Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., … Calantone, R. J. (2014). Common beliefs and reality about PLS: Comments on Rönkkö and Evermann (2013). Organizational Research Methods, 17(2), 182–209.
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.
Hoffman, D. L., & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing, 60(3), 50–68.
Hoffman, D. L., & Novak, T. P. (2009). Flow online: lessons learned and future prospects. Journal of Interactive Marketing, 23(1), 23–34.
Hu, L., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3(4), 424.
Huang, Y.-M., Huang, Y.-M., Huang, S.-H., & Lin, Y.-T. (2012). A ubiquitous English vocabulary learning system: Evidence of active/passive attitudes vs. usefulness/ease-of-use. Computers & Education, 58(1), 273–282.
Hung, C.-L., Chou, J. C.-L., & Ding, C.-M. (2012). Enhancing mobile satisfaction through integration of usability and flow. Engineering Management Research, 1(1), 44.
Jaffar, A. A. (2012). YouTube: An emerging tool in anatomy education. Anatomical Sciences Education, 5(3), 158–164.
Jung, I., & Lee, Y. (2015). YouTube acceptance by university educators and students: a cross-cultural perspective. Innovations in Education and Teaching International, 52(3), 243–253.
Jung, Y., Perez-Mira, B., & Wiley-Patton, S. (2009). Consumer adoption of mobile TV: Examining psychological flow and media content. Computers in Human Behavior, 25(1), 123–129.
Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.
Krauskopf, K., Zahn, C., & Hesse, F. W. (2012). Leveraging the affordances of Youtube: The role of pedagogical knowledge and mental models of technology functions for lesson planning with technology. Computers & Education, 58(4), 1194–1206.
Krejcie, R. V, & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610.
Larsen, T. J., Sørebø, A. M., & Sørebø, Ø. (2009). The role of task-technology fit as users’ motivation to continue information system use. Computers in Human Behavior, 25(3), 778–784.
Lee, D. Y., & Lehto, M. R. (2013). User acceptance of YouTube for procedural learning: An extension of the Technology Acceptance Model. Computers and Education, 61(1), 193–208. https://doi.org/10.1016/j.compedu.2012.10.001
Lee, M.-C., & Tsai, T.-R. (2010). What drives people to continue to play online games? An extension of technology model and theory of planned behavior. Intl. Journal of Human–Computer Interaction, 26(6), 601–620.
Lewis, W., Agarwal, R., & Sambamurthy, V. (2003). Sources of influence on beliefs about information technology use: An empirical study of knowledge workers. MIS Quarterly, 657–678.
Liao, C., Palvia, P., & Chen, J.-L. (2009). Information technology adoption behavior life cycle: Toward a Technology Continuance Theory (TCT). International Journal of Information Management, 29(4), 309–320.
Liaw, S.-S. (2008). Investigating students’ perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system. Computers & Education, 51(2), 864–873.
Limayem, M., Hirt, S. G., & Chin, W. W. (2001). Intention does not always matter: the contingent role of habit on IT usage behavior. ECIS 2001 Proceedings, 56.
Lohmöller, J. B. (1989). Latent variable path modeling with partial least squares. Heidelberg, Germany: Physica-Verlag.
Lu, J., Yao, J. E., & Yu, C.-S. (2005). Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. The Journal of Strategic Information Systems, 14(3), 245–268.
Mehrez, A. A. A., Alshurideh, M., Kurdi, B. A., & Salloum, S. A. (2021). Internal Factors Affect Knowledge Management and Firm Performance: A Systematic Review. Advances in Intelligent Systems and Computing (Vol. 1261 AISC). https://doi.org/10.1007/978-3-030-58669-0_57
Mhamdi, C., Al-Emran, M., & Salloum, S. A. (2018). Text mining and analytics: A case study from news channels posts on Facebook. Studies in Computational Intelligence (Vol. 740). https://doi.org/10.1007/978-3-319-67056-0_19
Mir, I. A., & Ur REHMAN, K. (2013). Factors affecting consumer attitudes and intentions toward user-generated product content on YouTube. Management & Marketing, 8(4).
Mun, Y. Y., Jackson, J. D., Park, J. S., & Probst, J. C. (2006). Understanding information technology acceptance by individual professionals: Toward an integrative view. Information & Management, 43(3), 350–363.
Niederhauser, D. S., & Perkmen, S. (2010). Beyond self-efficacy: Measuring pre-service teachers’ instructional technology outcome expectations. Computers in Human Behavior, 26(3), 436–442.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory. McGraw-Hill, New York. https://doi.org/10.1037/018882
Nunnally, Jum C, & Bernstein, I. H. (1978). Psychometric theory.
Oliver, R. L. (1981). Measurement and evaluation of satisfaction processes in retail settings. Journal of Retailing.
Omar, B., & Dequan, W. (2020). Watch, share or create: The influence of personality traits and user motivation on TikTok mobile video usage.
Ong, C.-S., & Lai, J.-Y. (2006). Gender differences in perceptions and relationships among dominants of e-learning acceptance. Computers in Human Behavior, 22(5), 816–829.
Oum, S., & Han, D. (2011). An empirical study of the determinants of the intention to participate in user-created contents (UCC) services. Expert Systems with Applications, 38(12), 15110–15121.
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.
Pituch, K. A., & Lee, Y. (2006). The influence of system characteristics on e-learning use. Computers & Education, 47(2), 222–244.
Rai, R. S., & Selnes, F. (2019). Conceptualizing task-technology fit and the effect on adoption–A case study of a digital textbook service. Information & Management, 56(8), 103161.
Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. Bönningstedt: SmartPLS.
Rogers, E. (1995). Diffusion of Innovations (Fourth Paperback ed.). New York: The Free Press Simon & Schuster Inc.
Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54–67.
Ryu, M.-H., Kim, S., & Lee, E. (2009). Understanding the factors affecting online elderly user’s participation in video UCC services. Computers in Human Behavior, 25(3), 619–632.
Salloum, S. A. (n.d.). Predicting the Intention to Use Social Media Sites: A Hybrid SEM-Machine Learning Approach. Advanced Machine Learning Technologies and Applications: Proceedings of AMLTA 2021, 324.
Salloum, S. A., Al-Emran, M., Abdallah, S., & Shaalan, K. (2017). Analyzing the Arab Gulf Newspapers Using Text Mining Techniques. In International Conference on Advanced Intelligent Systems and Informatics (pp. 396–405). Springer. https://doi.org/10.1007/978-3-319-64861-3_37
Salloum, S. A., Al-Emran, M., Habes, M., Alghizzawi, M., Ghani, M. A., & Shaalan, K. (2021). What Impacts the Acceptance of E-learning Through Social Media? An Empirical Study. Recent Advances in Technology Acceptance Models and Theories, 419–431.
Salloum, S. A., Al-Emran, M., & Shaalan, K. (2016). A Survey of Lexical Functional Grammar in the Arabic Context. Int. J. Com. Net. Tech, 4(3).
Salloum, S. A., Alhamad, A. Q. M., Al-Emran, M., Monem, A. A., & Shaalan, K. (2019). Exploring Students’ Acceptance of E-Learning Through the Development of a Comprehensive Technology Acceptance Model. IEEE Access, 7, 128445–128462.
Salloum, S. A., Maqableh, W., Mhamdi, C., Al Kurdi, B., & Shaalan, K. (2018). Studying the Social Media Adoption by university students in the United Arab Emirates. International Journal of Information Technology and Language Studies, 2(3).
Salloum, S. A., Mhamdi, C., Al Kurdi, B., & Shaalan, K. (2018). Factors affecting the Adoption and Meaningful Use of Social Media: A Structural Equation Modeling Approach. International Journal of Information Technology and Language Studies, 2(3).
Sánchez, R. A., & Hueros, A. D. (2010). Motivational factors that influence the acceptance of Moodle using TAM. Computers in Human Behavior, 26(6), 1632–1640.
Serenko, A. (2008). A model of user adoption of interface agents for email notification. Interacting with Computers, 20(4–5), 461–472.
Seyed Esfahani, M., & Reynolds, N. (2021). Impact of consumer innovativeness on really new product adoption. Marketing Intelligence & Planning.
Shah, S. F., Alshurideh, M., Kurdi, B. A., & Salloum, S. A. (2021). The Impact of the Behavioral Factors on Investment Decision-Making: A Systemic Review on Financial Institutions. Advances in Intelligent Systems and Computing (Vol. 1261 AISC). https://doi.org/10.1007/978-3-030-58669-0_9
Shang, R.-A., Chen, Y.-C., & Shen, L. (2005). Extrinsic versus intrinsic motivations for consumers to shop on-line. Information & Management, 42(3), 401–413.
Shee, D. Y., & Wang, Y.-S. (2008). Multi-criteria evaluation of the web-based e-learning system: A methodology based on learner satisfaction and its applications. Computers & Education, 50(3), 894–905.
Siersdorfer, S., Chelaru, S., Nejdl, W., & San Pedro, J. (2010). How useful are your comments? Analyzing and predicting YouTube comments and comment ratings. In Proceedings of the 19th international conference on World wide web (pp. 891–900).
Szymanski, D. M., & Hise, R. T. (2000). E-satisfaction: an initial examination. Journal of Retailing, 76(3), 309–322.
Tan, C.-H., Yang, X., & Teo, H.-H. (2007). When Counterfactual Thinking Meets the Technology Acceptance Model. In IFIP International Working Conference on Organizational Dynamics of Technology-Based Innovation (pp. 507–511). Springer.
Teo, T. (2011). Technology acceptance research in education. In Technology acceptance in education (pp. 1–5). Springer.
Trial, D. (n.d.). Model Fit.
Tung, F.-C., & Chang, S.-C. (2008). Nursing students’ behavioral intention to use online courses: A questionnaire survey. International Journal of Nursing Studies, 45(9), 1299–1309.
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., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425–478.
Wang, S., & Fu, R. (2020). Research on the Influencing Factors of the Communication Effect of Tik Tok Short Videos About Intangible Cultural Heritage. In International Conference on Applied Human Factors and Ergonomics (pp. 275–282). Springer.
Wang, Y.-S., Wang, H.-Y., & Shee, D. Y. (2007). Measuring e-learning systems success in an organizational context: Scale development and validation. Computers in Human Behavior, 23(4), 1792–1808.
Wang, Y. (2020). Humor and camera view on mobile short-form video apps influence user experience and technology-adoption intent, an example of TikTok (DouYin). Computers in Human Behavior, 110, 106373.
Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85–102.
Wu, J.-H., Tennyson, R. D., & Hsia, T.-L. (2010). A study of student satisfaction in a blended e-learning system environment. Computers & Education, 55(1), 155–164.
Xu, H., & Gupta, S. (2009). The effects of privacy concerns and personal innovativeness on potential and experienced customers’ adoption of location-based services. Electronic Markets, 19(2–3), 137–149.
Yang, Y., & Zilberg, I. E. (2020). Understanding Young Adults’ TikTok Usage.
Zhu, Y., Dong, J., Qi, X., & Deng, J. (2021). Intention to use Governmental Micro-Video in the Pandemic of Covid-19: An Empirical Study of Governmental Tik Tok in China. In 2021 6th International Conference on Inventive Computation Technologies (ICICT) (pp. 976–979). IEEE.