How to cite this paper
Alhumaid, K., Alnazzawi, N., Akour, I., Khasoneh, O., Alfaisal, R & Salloum, S. (2022). An integrated model for the usage and acceptance of stickers in WhatsApp through SEM-ANN approach.International Journal of Data and Network Science, 6(4), 1261-1272.
Refrences
Aburayya, A., Al Marzouqi, A., Al Ayadeh, I., Albqaeen, A., & Mubarak, S. (2020). Evolving a Hybrid Appointment System for Patient Scheduling in Primary Healthcare Centres in Dubai: Perceptions of Patients and Healthcare Provider. International Journal on Emerging Technologies, 11(2), 251–260.
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). https://doi.org/10.31838/srp.2020.9.51
Aburub, F., & Alnawas, I. (2019). A new integrated model to explore factors that influence adoption of mobile learning in higher education: An empirical investigation. Education and Information Technologies, 1–14.
Ahmed, A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2021). Digital Transformation and Organizational Operational Decision Making: A Systematic Review. In Advances in Intelligent Systems and Computing: Vol. 1261 AISC. https://doi.org/10.1007/978-3-030-58669-0_63
Al-Emran, M., Abbasi, G. A., & Mezhuyev, V. (2021). Evaluating the Impact of Knowledge Management Factors on M-Learning Adoption: A Deep Learning-Based Hybrid SEM-ANN Approach. Recent Advances in Technology Acceptance Models and Theories, 159–172.
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., Mezhuyev, V., & Kamaludin, A. (2018). PLS-SEM in Information Systems Research: A Comprehensive Methodological Reference. 4th International Conference on Advanced Intelligent Systems and Informatics (AISI 2018), 644–653.
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-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 (IJET).
Al-Maroof, R. S., Akour, I., Aljanada, R., Alfaisal, A. M., Alfaisal, R. M., Aburayya, A., & Salloum, S. A. (2021). Acceptance determinants of 5G services. International Journal of Data and Network Science, 5(4), 613–628.
Al-Maroof, R. S., 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, R. S., 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. Informatics, 8(2), 24.
Al-Maroof, R. S., Salloum, S. A., AlHamadand, A. Q. M., & Shaalan, K. (2020a). A Unified Model for the Use and Acceptance of Stickers in Social Media Messaging. In Advances in Intelligent Systems and Computing (Vol. 1058). https://doi.org/10.1007/978-3-030-31129-2_34
Al-Maroof, R. S., Salloum, S. A., AlHamadand, A. Q., & Shaalan, K. (2020b). Understanding an Extension Technology Acceptance Model of Google Translation: A Multi-Cultural Study in United Arab Emirates. International Journal of Interactive Mobile Technologies (IJIM), 14(03), 157–178.
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., S. S. A. (2021). An Integrated Model of Continuous Intention to Use of Google Classroom. 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-Sarayrah, W., Al-Aiad, A., Habes, M., Elareshi, M., & Salloum, S. A. (2021). Improving the Deaf and Hard of Hearing Internet Accessibility: JSL, Text-into-Sign Language Translator for Arabic. Advanced Machine Learning Technologies and Applications: Proceedings of AMLTA 2021, 456.
Al Rashdi, F. (2015). Forms and functions of emojis in WhatsApp interaction among Omanis. Georgetown University.
Al Rashdi, F. (2018). Functions of emojis in WhatsApp interaction among Omanis. Discourse, Context & Media, 26, 117–126.
Al Zidjaly, N. (2010). Intertextuality and constructing Islamic identities online. In Handbook of research on discourse behavior and digital communication: Language structures and social interaction (pp. 191–204). IGI Global.
Albawardi, A. H. (2018). Digital literacy practices of Saudi Female university students. University of Reading.
Alhashmi, S. 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).
Alhumaid, K., Habes, M., & Salloum, S. A. (2021). Examining the factors influencing the mobile learning usage during COVID-19 Pandemic: An Integrated SEM-ANN Method. IEEE Access, 9, 102567–102578. https://doi.org/10.1109/ACCESS.2021.3097753
Almarzouqi, A., Aburayya, A., & Salloum, S. A. (2022). Determinants of intention to use medical smartwatch-based dual-stage SEM-ANN analysis. Informatics in Medicine Unlocked, 28, 100859. https://doi.org/https://doi.org/10.1016/j.imu.2022.100859
Alsharhan, A., Salloum, S., & Aburayya, A. (2022). Technology acceptance drivers for AR smart glasses in the middle east: A quantitative study. International Journal of Data and Network Science, 6(1), 193–208.
Alsharhan, A., Salloum, S., & Shaalan, K. (n.d.). The Impact of eLearning as a Knowledge Management Tool in Organizational Performance.
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.
Asadi, S., Abdullah, R., Safaei, M., & Nazir, S. (2019). An integrated SEM-Neural Network approach for predicting determinants of adoption of wearable healthcare devices. Mobile Information Systems, 2019.
Chairunnisa, S., & Benedictus, A. S. (2017). Analysis of Emoji and Emoticon Usage in Interpersonal Communication of Blackberry Messenger and WhatsApp Application User. International Journal of Social Sciences and Management, 4(2), 120–126.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319–340.
Dijkstra, T. K., & Henseler, J. (2015). Consistent and asymptotically normal PLS estimators for linear structural equations. Computational Statistics & Data Analysis, 81, 10–23.
Elareshi, M., Habes, M., Youssef, E., Salloum, S. A., Alfaisal, R., & Ziani, A. (2022). SEM-ANN-based approach to understanding students’ academic-performance adoption of YouTube for learning during Covid. Heliyon, e09236.
Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends:” Social capital and college students’ use of online social network sites. Journal of Computer‐Mediated Communication, 12(4), 1143–1168.
Elnagar, A., Afyouni, I., Shahin, I., Nassif, A. B., & Salloum, S. A. (2021). The empirical study of e-learning post-acceptance after the spread of COVID-19: A multi-analytical approach based hybrid SEM-ANN. ArXiv Preprint ArXiv:2112.01293.
Escobar-Rodriguez, T., & Monge-Lozano, P. (2012). The acceptance of Moodle technology by business administration students. Computers & Education, 58(4), 1085–1093.
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
Gan, C. (2017). Understanding WeChat users’ liking behavior: An empirical study in China. Computers in Human Behavior, 68, 30–39.
Goffman, E. (1959). Presentatxon of Self xn Everyday Lxfe. Doubleday and Co. Anchor Books, Garden City, New York.
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
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.
Herring, S. C. (2007). A faceted classification scheme for computer-mediated discourse. Language@ Internet, 4(1).
Herring, S., & Dainas, A. (2017). “Nice picture comment!” Graphicons in Facebook comment threads. Proceedings of the 50th Hawaii International Conference on System Sciences.
Huang, W., & Stokes, J. W. (2016). MtNet: a multi-task neural network for dynamic malware classification. International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, 399–418.
Khan, A. N., & Ali, A. (2018). Factors affecting retailer’s adopti on of mobile payment systems: A SEM-neural network modeling approach. Wireless Personal Communications, 103(3), 2529–2551.
Lee, J. Y., Hong, N., Kim, S., Oh, J., & Lee, J. (2016). Smiley face: why we use emoticon stickers in mobile messaging. Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct, 760–766.
Lee, S.-Y., Hansen, S. S., & Lee, J. K. (2016). What makes us click “like” on Facebook? Examining psychological, technological, and motivational factors on virtual endorsement. Computer Communications, 73, 332–341.
Lee, V.-H., Hew, J.-J., Leong, L.-Y., Tan, G. W.-H., & Ooi, K.-B. (2020). Wearable payment: A deep learning-based dual-stage SEM-ANN analysis. Expert Systems with Applications, 157, 113477.
Leong, L.-Y., Hew, T.-S., Ooi, K.-B., Lee, V.-H., & Hew, J.-J. (2019). A hybrid SEM-neural network analysis of social media addiction. Expert Systems with Applications, 133, 296–316.
Leong, L.-Y., Hew, T.-S., Tan, G. W.-H., & Ooi, K.-B. (2013). Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach. Expert Systems with Applications, 40(14), 5604–5620.
Lu, X., Ai, W., Liu, X., Li, Q., Wang, N., Huang, G., & Mei, Q. (2016). Learning from the ubiquitous language: an empirical analysis of emoji usage of smartphone users. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 770–780.
Luo, M. M., & Remus, W. (2014). Uses and gratifications and acceptance of Web-based information services: An integrated model. Computers in Human Behavior, 38, 281–295.
Muhammad, G. (2017). The intention of using emojis in Whatsapp messages among young adults. SKRIPSI Jurusan Sastra Inggris-Fakultas Sastra UM.
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Saeed Al-Maroof, R., Alhumaid, K., & Salloum, S. (2021). The Continuous Intention to Use E-Learning, from Two Different Perspectives. Education Sciences, 11(1), 6.
Salloum, S. A., & Al-Emran, M. (2018). Factors affecting the adoption of e-payment systems by university students: extending the TAM with trust. International Journal of Electronic Business, 14(4), 371–390.
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Aburub, F., & Alnawas, I. (2019). A new integrated model to explore factors that influence adoption of mobile learning in higher education: An empirical investigation. Education and Information Technologies, 1–14.
Ahmed, A., Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2021). Digital Transformation and Organizational Operational Decision Making: A Systematic Review. In Advances in Intelligent Systems and Computing: Vol. 1261 AISC. https://doi.org/10.1007/978-3-030-58669-0_63
Al-Emran, M., Abbasi, G. A., & Mezhuyev, V. (2021). Evaluating the Impact of Knowledge Management Factors on M-Learning Adoption: A Deep Learning-Based Hybrid SEM-ANN Approach. Recent Advances in Technology Acceptance Models and Theories, 159–172.
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., Mezhuyev, V., & Kamaludin, A. (2018). PLS-SEM in Information Systems Research: A Comprehensive Methodological Reference. 4th International Conference on Advanced Intelligent Systems and Informatics (AISI 2018), 644–653.
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-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 (IJET).
Al-Maroof, R. S., Akour, I., Aljanada, R., Alfaisal, A. M., Alfaisal, R. M., Aburayya, A., & Salloum, S. A. (2021). Acceptance determinants of 5G services. International Journal of Data and Network Science, 5(4), 613–628.
Al-Maroof, R. S., 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, R. S., 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. Informatics, 8(2), 24.
Al-Maroof, R. S., Salloum, S. A., AlHamadand, A. Q. M., & Shaalan, K. (2020a). A Unified Model for the Use and Acceptance of Stickers in Social Media Messaging. In Advances in Intelligent Systems and Computing (Vol. 1058). https://doi.org/10.1007/978-3-030-31129-2_34
Al-Maroof, R. S., Salloum, S. A., AlHamadand, A. Q., & Shaalan, K. (2020b). Understanding an Extension Technology Acceptance Model of Google Translation: A Multi-Cultural Study in United Arab Emirates. International Journal of Interactive Mobile Technologies (IJIM), 14(03), 157–178.
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., S. S. A. (2021). An Integrated Model of Continuous Intention to Use of Google Classroom. 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-Sarayrah, W., Al-Aiad, A., Habes, M., Elareshi, M., & Salloum, S. A. (2021). Improving the Deaf and Hard of Hearing Internet Accessibility: JSL, Text-into-Sign Language Translator for Arabic. Advanced Machine Learning Technologies and Applications: Proceedings of AMLTA 2021, 456.
Al Rashdi, F. (2015). Forms and functions of emojis in WhatsApp interaction among Omanis. Georgetown University.
Al Rashdi, F. (2018). Functions of emojis in WhatsApp interaction among Omanis. Discourse, Context & Media, 26, 117–126.
Al Zidjaly, N. (2010). Intertextuality and constructing Islamic identities online. In Handbook of research on discourse behavior and digital communication: Language structures and social interaction (pp. 191–204). IGI Global.
Albawardi, A. H. (2018). Digital literacy practices of Saudi Female university students. University of Reading.
Alhashmi, S. 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).
Alhumaid, K., Habes, M., & Salloum, S. A. (2021). Examining the factors influencing the mobile learning usage during COVID-19 Pandemic: An Integrated SEM-ANN Method. IEEE Access, 9, 102567–102578. https://doi.org/10.1109/ACCESS.2021.3097753
Almarzouqi, A., Aburayya, A., & Salloum, S. A. (2022). Determinants of intention to use medical smartwatch-based dual-stage SEM-ANN analysis. Informatics in Medicine Unlocked, 28, 100859. https://doi.org/https://doi.org/10.1016/j.imu.2022.100859
Alsharhan, A., Salloum, S., & Aburayya, A. (2022). Technology acceptance drivers for AR smart glasses in the middle east: A quantitative study. International Journal of Data and Network Science, 6(1), 193–208.
Alsharhan, A., Salloum, S., & Shaalan, K. (n.d.). The Impact of eLearning as a Knowledge Management Tool in Organizational Performance.
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.
Asadi, S., Abdullah, R., Safaei, M., & Nazir, S. (2019). An integrated SEM-Neural Network approach for predicting determinants of adoption of wearable healthcare devices. Mobile Information Systems, 2019.
Chairunnisa, S., & Benedictus, A. S. (2017). Analysis of Emoji and Emoticon Usage in Interpersonal Communication of Blackberry Messenger and WhatsApp Application User. International Journal of Social Sciences and Management, 4(2), 120–126.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319–340.
Dijkstra, T. K., & Henseler, J. (2015). Consistent and asymptotically normal PLS estimators for linear structural equations. Computational Statistics & Data Analysis, 81, 10–23.
Elareshi, M., Habes, M., Youssef, E., Salloum, S. A., Alfaisal, R., & Ziani, A. (2022). SEM-ANN-based approach to understanding students’ academic-performance adoption of YouTube for learning during Covid. Heliyon, e09236.
Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends:” Social capital and college students’ use of online social network sites. Journal of Computer‐Mediated Communication, 12(4), 1143–1168.
Elnagar, A., Afyouni, I., Shahin, I., Nassif, A. B., & Salloum, S. A. (2021). The empirical study of e-learning post-acceptance after the spread of COVID-19: A multi-analytical approach based hybrid SEM-ANN. ArXiv Preprint ArXiv:2112.01293.
Escobar-Rodriguez, T., & Monge-Lozano, P. (2012). The acceptance of Moodle technology by business administration students. Computers & Education, 58(4), 1085–1093.
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
Gan, C. (2017). Understanding WeChat users’ liking behavior: An empirical study in China. Computers in Human Behavior, 68, 30–39.
Goffman, E. (1959). Presentatxon of Self xn Everyday Lxfe. Doubleday and Co. Anchor Books, Garden City, New York.
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
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.
Herring, S. C. (2007). A faceted classification scheme for computer-mediated discourse. Language@ Internet, 4(1).
Herring, S., & Dainas, A. (2017). “Nice picture comment!” Graphicons in Facebook comment threads. Proceedings of the 50th Hawaii International Conference on System Sciences.
Huang, W., & Stokes, J. W. (2016). MtNet: a multi-task neural network for dynamic malware classification. International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, 399–418.
Khan, A. N., & Ali, A. (2018). Factors affecting retailer’s adopti on of mobile payment systems: A SEM-neural network modeling approach. Wireless Personal Communications, 103(3), 2529–2551.
Lee, J. Y., Hong, N., Kim, S., Oh, J., & Lee, J. (2016). Smiley face: why we use emoticon stickers in mobile messaging. Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct, 760–766.
Lee, S.-Y., Hansen, S. S., & Lee, J. K. (2016). What makes us click “like” on Facebook? Examining psychological, technological, and motivational factors on virtual endorsement. Computer Communications, 73, 332–341.
Lee, V.-H., Hew, J.-J., Leong, L.-Y., Tan, G. W.-H., & Ooi, K.-B. (2020). Wearable payment: A deep learning-based dual-stage SEM-ANN analysis. Expert Systems with Applications, 157, 113477.
Leong, L.-Y., Hew, T.-S., Ooi, K.-B., Lee, V.-H., & Hew, J.-J. (2019). A hybrid SEM-neural network analysis of social media addiction. Expert Systems with Applications, 133, 296–316.
Leong, L.-Y., Hew, T.-S., Tan, G. W.-H., & Ooi, K.-B. (2013). Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach. Expert Systems with Applications, 40(14), 5604–5620.
Lu, X., Ai, W., Liu, X., Li, Q., Wang, N., Huang, G., & Mei, Q. (2016). Learning from the ubiquitous language: an empirical analysis of emoji usage of smartphone users. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 770–780.
Luo, M. M., & Remus, W. (2014). Uses and gratifications and acceptance of Web-based information services: An integrated model. Computers in Human Behavior, 38, 281–295.
Muhammad, G. (2017). The intention of using emojis in Whatsapp messages among young adults. SKRIPSI Jurusan Sastra Inggris-Fakultas Sastra UM.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory. In McGraw-Hill, New York. https://doi.org/10.1037/018882
Ringle, C. M., & Sarstedt, M. (2016). Gain more insight from your PLS-SEM results. Industrial Management & Data Systems.
Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. Bönningstedt: SmartPLS.
Riordan, M. A. (2017). The communicative role of non-face emojis: Affect and disambiguation. Computers in Human Behavior, 76, 75–86.
Saeed Al-Maroof, R., Alhumaid, K., & Salloum, S. (2021). The Continuous Intention to Use E-Learning, from Two Different Perspectives. Education Sciences, 11(1), 6.
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