Using technology acceptance model to discuss factors in university employees’ behavior intention to apply social media

Jaitip Nasongkhla 1 * , Chich-Jen Shieh 1
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1 Disruptive Innovation Technology in Education Research Unit, Chulalongkorn University, Bangkok, THAILAND
* Corresponding Author
Online Journal of Communication and Media Technologies, Volume 13, Issue 2, Article No: e202317. https://doi.org/10.30935/ojcmt/13019
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ABSTRACT

In order to evaluate the problem of employees using social networking technology for business purposes, the technology acceptance model will be applied. The purpose of the study is to establish the levels of impact exerted by the elements that influence the intentions of individuals working in the university to utilize social media. Employees in the university’s connections between “organizational support,” “colleague support,” “self-efficacy,” “technology capacity,” “perceived usefulness,” “perceived ease of use,” and “behavior intention” are acknowledged as factors in this study. It was possible to get a total of 247 copies that were legitimate. For the purpose of inferential statistics, the partial least squares structural equation modeling method was applied. The data indicate that colleague support and technological capabilities do not have any impact on how easily something may be used or how valuable it is thought to be. On the other hand, organizational support and self-efficacy have a favorable influence on the perceived ease of use, but they have no effect on the perceived effectiveness of the tool. Additionally, while perceived usefulness does not have any influence on behavioral intention, perceived simplicity of use does have a favorable effect on behavioral intention.

CITATION

Nasongkhla, J., & Shieh, C.-J. (2023). Using technology acceptance model to discuss factors in university employees’ behavior intention to apply social media. Online Journal of Communication and Media Technologies, 13(2), e202317. https://doi.org/10.30935/ojcmt/13019

REFERENCES

  • Abbad, M. M. M. (2021). Using the UTAUT model to understand students’ usage of e-learning systems in developing countries. Education and Information Technologies, 26(6), 7205-7224. https://doi.org/10.1007/s10639-021-10573-5
  • Achterkamp, R., Hermens, H. J., & Vollenbroek-Hutten, M. M. R. (2015). The influence of success experience on self-efficacy when providing feedback through technology. Computers in Human Behavior, 52, 419-423. https://doi.org/10.1016/j.chb.2015.06.029
  • Al Asyari, M. K. H., & Rahman, M. (2020). Technology: Technological advances and changes in human lifestyles in a socio-cultural perspective. In Proceedings of the International Conference on Science and Engineering (pp. 721-730). https://doi.org/10.14421/icse.v3.592
  • Alam, M. Z., Hoque, M. R., Hu, W., & Barua, Z. (2020). Factors influencing the adoption of mHealth services in a developing country: A patient-centric study. International Journal of Information Management, 50, 128-143. https://doi.org/10.1016/j.ijinfomgt.2019.04.016
  • Aldabbas, H., Pinnington, A., & Lahrech, A. (2021). The influence of perceived organizational support on employee creativity: The mediating role of work engagement. Current Psychology. https://doi.org/10.1007/s12144-021-01992-1
  • Alharbi, S., & Drew, S. (2019). The role of self-efficacy in technology acceptance. K. Arai, R. Bhatia, & S. Kapoor (Eds.), Advances in intelligent systems and computing. Springer. https://doi.org/10.1007/978-3-030-02686-8_85
  • Al-Mamary, Y. H., & Shamsuddin, A. (2015). The impact of top management support, training, and perceived usefulness on technology acceptance. Mediterranean Journal of Social Sciences, 6(6), 11-17. https://doi.org/10.5901/mjss.2015.v6n6s4p11
  • Arafah, B., & Hasyim, M. (2022). Social media as a gateway to Information: Digital literacy on current issues in social media. Webology, 19(1), 2491-2503. https://doi.org/10.14704/web/v19i1/web19167
  • Awodoyin, A., Adetoro, N., & Osisanwo, T. (2017). Self-efficacy and new technology adoption and use among trainee mid-wives in Ijebu-Ode, Nigeria. Education and Information Technologies, 22(4), 1911-1925. https://doi.org/10.1007/s10639-016-9524-7
  • Brown, I. T. J. (2002). Individual and technological factors affecting perceived ease of use of web-based learning technologies in a developing country. The Electronic Journal of Information Systems in Developing Countries, 9(1), 1-15. https://doi.org/10.1002/j.1681-4835.2002.tb00055.x
  • Conway, E. (2015). Perceived organizational support. In Wiley encyclopedia of management (pp. 1-2). John Wiley & Sons, Ltd. https://doi.org/10.1002/9781118785317.weom110285
  • Dai, H. M., Teo, T., & Rappa, N. A. (2020). Understanding continuance intention among MOOC participants: The role of habit and MOOC performance. Computers in Human Behavior, 112, 106455. https://doi.org/10.1016/j.chb.2020.106455
  • Daryanto, D., Rina, F., Massus, S., & Siswantari, S. (2019). Effect of perceived ease of use of ICT on stakeholder service quality in vocational high school in West Java. Journal of Physics: Conference Series, 1402, 077079. https://doi.org/10.1088/1742-6596/1402/7/077079
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319-339. https://doi.org/10.2307/249008
  • DeConinck, J. B., Moss, H. K., & DeConinck, M. B. (2017). The relationship between servant leadership, perceived organizational support, performance, and turnover among business to business salespeople. Archives of Business Research, 5(10). https://doi.org/10.14738/abr.510.3730
  • Deng, X., Doll, W. J., & Truong, D. (2004). Computer self-efficacy in an ongoing use context. Behavior and Information Technology, 23(6), 395-412. https://doi.org/10.1080/01449290410001723454
  • Doulani, A. (2019). An assessment of effective factors in technology acceptance model: A meta- analysis study. Journal of Scientometric Research, 7(3), 153-166. https://doi.org/10.5530/JSCIRES.7.3.26
  • Dunatchik, A., Gerson, K., Glass, J., Jacobs, J. A., & Stritzel, H. (2021). Gender, parenting, and the rise of remote work during the pandemic: Implications for domestic inequality in the United States. Gender and Society, 35(2), 194-205. https://doi.org/10.1177/08912432211001301
  • Eisenberger, R., Rhoades Shanock, L., & Wen, X. (2020). Perceived organizational support: Why caring about employees counts. Annual Review of Organizational Psychology and Organizational Behavior, 7, 101-124. https://doi.org/10.1146/annurev-orgpsych-012119-044917
  • Erasmus, E., Rothmann, S., & van Eeden, C. (2015). A structural model of technology acceptance. SA Journal of Industrial Psychology, 41(1), 1-12. https://doi.org/10.4102/sajip.v41i1.1222
  • Esen, M., & Ozbag, G. K. (2014). An investigation of the effects of organizational readiness on technology acceptance in e-HRM applications. International Journal of Human Resource Studies, 4(1), 232. https://doi.org/10.5296/ijhrs.v4i1.5643
  • Fardinal, W. K. (2020). The effect of perceived ease of use on the quality of accounting information systems and its impact on the quality of accounting information. Saudi Journal of Business and Management Studies, 5(12), 571-577. https://doi.org/10.36348/sjbms.2020.v05i12.004
  • Feriady, M., Nurkhin, A., Mahmud, N., Setiani, R., & Astuti, D. P. (2020). Influence of organizational support and digital literacy on lecturer acceptance of e-learning in Indonesia: A modification of technology acceptance model. International Journal of Scientific and Technology Research, 9(1), 2229-2233.
  • Fibrianto, A. S., & Yuniar, A. D. (2019). Technological development and its impact on community social behavior. In Proceedings of the 1st International Conference on Social Knowledge Sciences and Education (pp. 210-213). https://doi.org/10.2991/icskse-18.2019.42
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables. Journal of Marketing Research, XVIII(February), 39-50. https://doi.org/10.1177/002224378101800104
  • Fu, J., & Cook, J. (2021). Everyday social media use of young Australian adults. Journal of Youth Studies, 24(9), 1234-1250. https://doi.org/10.1080/13676261.2020.1828843
  • Granić, A., & Marangunić, N. (2019). Technology acceptance model in educational context: A systematic literature review. British Journal of Educational Technology, 50(5), 2572-2593. https://doi.org/10.1111/bjet.12864
  • Gruszczynski, L. (2020). The COVID-19 pandemic and international trade: Temporary turbulence or paradigm shift? European Journal of Risk Regulation, 11(2), 337-342. https://doi.org/10.1017/err.2020.29
  • Habes, M., Alghizzawi, M., Ali, S., SalihAlnaser, A., & Salloum, S. A. (2020). The relation among marketing ads, via digital media and mitigate (COVID-19) pandemic in Jordan. International Journal of Advanced Science and Technology, 7(29), 12326-12348.
  • Hair, J. F., Hult, T., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM). SAGE. https://doi.org/10.1007/978-3-030-80519-7
  • Hair, Joseph F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Springer. https://doi.org/10.1007/978-3-030-80519-7
  • 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. https://doi.org/10.1007/s11747-014-0403-8
  • Jacobson, J., Gruzd, A., & Hernández-García, Á. (2020). Social media marketing: Who is watching the watchers? Journal of Retailing and Consumer Services, 53, 101774. https://doi.org/10.1016/j.jretconser.2019.03.001
  • Juergensen, J., Guimón, J., & Narula, R. (2020). European SMEs amidst the COVID-19 crisis: Assessing impact and policy responses. Journal of Industrial and Business Economics, 47(3), 499-510. https://doi.org/10.1007/s40812-020-00169-4
  • Jungert, T., Van den Broeck, A., Schreurs, B., & Osterman, U. (2018). How colleagues can support each other’s needs and motivation: An intervention on employee work motivation. Applied Psychology, 67(1), 3-29. https://doi.org/10.1111/apps.12110
  • Korcsmáros, E., & Csinger, B. (2022). Sustainable competitiveness in the case of SMEs—Opportunities provided by social media in an international comparison. Sustainability (Switzerland), 14(19), 12505. https://doi.org/10.3390/su141912505
  • Lazim, C. S. L. M., Ismail, N. D. B., & Tazilah, M. D. A. K. (2021). Application of technology acceptance model (TAM) towards online learning during COVID-19 pandemic: Accounting students perspective. International Journal of Business, Economics and Law, 24(1), 1.
  • Lee, D., Lee, S. M., Olson, D. L., & Chung, S. H. (2010). The effect of organizational support on ERP implementation. Industrial Management and Data Systems, 110(2), 269-283. https://doi.org/10.1108/02635571011020340
  • Lestari, D. A., & Tiarawati, M. (2020). The effect of hedonic motivation and consumer attitudes towards purchase decision on K-pop CD albums (study on KPOPSURABAYA community). The Spirit of Society Journal, 3(2), 1-7. https://doi.org/10.29138/scj.v3i2.1084
  • Miller, J., & Khera, O. (2010). Digital library adoption and the technology acceptance model: A cross-country analysis. The Electronic Journal of Information Systems in Developing Countries, 40(1), 1-19. https://doi.org/10.1002/j.1681-4835.2010.tb00288.x
  • Mohamad, M. A., Radzi, S. M., & Hanafiah, M. H. (2021). Understanding tourist mobile hotel booking behavior: Incorporating perceived enjoyment and perceived price value in the modified technology acceptance model. Tourism and Management Studies, 17(1), 19-30. https://doi.org/10.18089/TMS.2021.170102
  • Mohamad, N. I., Ismail, A., & Nor, A. M. (2020). Effect of managers support in technology based training on training transfer. International Journal on Emerging Technologies, 11(2), 985-990.
  • Na, S., Heo, S., Han, S., Shin, Y., & Roh, Y. (2022). Acceptance model of artificial intelligence (AI)-based technologies in construction firms: Applying the technology acceptance model (TAM) in combination with the technology-organization-environment (TOE) framework. Buildings, 12(2), 90. https://doi.org/10.3390/buildings12020090
  • Naujokaitiene, J., Tereseviciene, M., & Zydziunaite, V. (2015). Organizational support for employee engagement in technology-enhanced learning. SAGE Open, 5(4). https://doi.org/10.1177/2158244015607585
  • Nazir, O., & Islam, J. U. (2017). Enhancing organizational commitment and employee performance through employee engagement: An empirical check. South Asian Journal of Business Studies, 6(1), 98-114. https://doi.org/10.1108/SAJBS-04-2016-0036
  • Newman, S. A., Ford, R. C., & Marshall, G. W. (2020). Virtual team leader communication: Employee perception and organizational reality. International Journal of Business Communication, 57(4), 452-473. https://doi.org/10.1177/2329488419829895
  • Ninh Nguyen, H., & Dung Tran, M. (2021). The effect of perceived organizational support on employee engagement during the COVID-19 pandemic: An empirical study in Vietnam. Journal of Asian Finance, 8(6), 415-426. https://doi.org/10.13106/jafeb.2021.vol8.no6.0415
  • Nugroho, H. S. W., Notobroto, H. B., & Rosyanti, L. (2021). Acceptance model of a mandatory health information system in Indonesia. Healthcare Informatics Research, 27(2), 127-136. https://doi.org/10.4258/HIR.2021.27.2.127
  • Oh, S., & Syn, S. Y. (2015). Motivations for sharing information and social support in social media: A comparative analysis of Facebook, Twitter, Delicious, YouTube, and Flickr. Journal of the Association for Information Science and Technology, 66(10), 2045-2060. https://doi.org/10.1002/asi.23320
  • Panaccio, A., & Vandenberghe, C. (2009). Perceived organizational support, organizational commitment and psychological well-being: A longitudinal study. Journal of Vocational Behavior, 75(2), 224-236. https://doi.org/10.1016/j.jvb.2009.06.002
  • Qiu, J., Shen, B., Zhao, M., Wang, Z., Xie, B., & Xu, Y. (2020). A nationwide survey of psychological distress among Chinese people in the COVID-19 epidemic: Implications and policy recommendations. General Psychiatry, 33(2), 1-4. https://doi.org/10.1136/gpsych-2020-100213
  • Rad, D., Egerau, A., Roman, A., Dughi, T., Balas, E., Maier, R., Ignat, S., & Rad, G. (2022). A preliminary investigation of the technology acceptance model (TAM) in early childhood education and care. Broad Research in Artificial Intelligence and Neuroscience, 13(1), 518-533. https://doi.org/10.18662/brain/13.1/297
  • Radulovic, J., Deretic, N., Vujanovic, N., Matic, R., & Djurica, N. (2022). Challenges and perspectives for remote work. 41st International Conference on Organizational Science Development, 5(3), 841-853. https://doi.org/10.18690/um.fov.3.2022.61
  • Roney, L. N., Westrick, S. J., Acri, M. C., Aronson, B. S., & Rebeschi, L. M. (2017). Technology use and technological self-efficacy among undergraduate nursing faculty. Nursing Education Perspectives, 38(3), 113-118. https://doi.org/10.1097/01.NEP.0000000000000141
  • Sanjeev, R., & Natrajan, N. S. (2021). A systematic review on education 4.0 using social media platform. Independent Journal of Management & Production, 12(7), 1901-1918. https://doi.org/10.14807/ijmp.v12i7.1438
  • Sukendro, S., Habibi, A., Khaeruddin, K., Indrayana, B., Syahruddin, S., Makadada, F. A., & Hakim, H. (2020). Using an extended technology acceptance model to understand students’ use of e-learning during COVID-19: Indonesian sport science education context. Heliyon, 6(11), e05410. https://doi.org/10.1016/j.heliyon.2020.e05410
  • Syriopoulos, K. (2020). The impact of COVID-19 on entrepreneurship and SMES. Journal of International Academy for Case Studies, 26(2), 5822.
  • Tsolou, O., Babalis, T., & Tsoli, K. (2021). The impact of COVID-19 pandemic on education: Social exclusion and dropping out of school. Creative Education, 12(03), 529-544. https://doi.org/10.4236/ce.2021.123036
  • Usman, O., Septianti, A., Susita, D., & Marsofiyati. (2021). The effect of computer self-efficacy and subjective norm on the perceived usefulness, perceived ease of use and behavioral intention to use technology. Journal of Southeast Asian Research, 2020(2020), 753259. https://doi.org/10.5171/2020.753259
  • Venkateswaran, R., Ugalde, B., & T., R. (2019). Impact of social media application in business organizations. International Journal of Computer Applications, 178(30), 5-10. https://doi.org/10.5120/ijca2019919126
  • Wang, B., Liu, Y., Qian, J., & Parker, S. K. (2021). Achieving effective remote working during the COVID-19 pandemic: A work design perspective. Applied Psychology, 70(1), 16-59. https://doi.org/10.1111/apps.12290
  • Wang, G. X., & Rashid, A. M. (2022). Job satisfaction as the mediator between a learning organization and organizational commitment among lecturers. European Journal of Educational Research, 11(2), 847-858. https://doi.org/10.12973/eu-jer.11.2.847
  • Welch, R., Alade, T., & Nichol, L. (2020). Using the unified theory of acceptance and use of technology (UTAUT) model to determine factors affecting mobile learning adoption in the workplace: A study of the science museum group. IADIS International Journal on Computer Science and Information Systems, 15(1), 85-98. https://doi.org/10.33965/ijcsis_2020150107
  • Wolgast, A., & Fischer, N. (2017). You are not alone: Colleague support and goal-oriented cooperation as resources to reduce teachers’ stress. Social Psychology of Education, 20(1), 97-114. https://doi.org/10.1007/s11218-017-9366-1
  • Yang, L., Holtz, D., Jaffe, S., Suri, S., Sinha, S., Weston, J., Joyce, C., Shah, N., Sherman, K., Hecht, B., & Teevan, J. (2022). The effects of remote work on collaboration among information workers. Nature Human Behavior, 6(1), 43-54. https://doi.org/10.1038/s41562-021-01196-4
  • Zhou, P., Yang, X.-L, Wang, X.-G., Hu, B., Zhang, L., Zhang, W., Si, H.-R., Zhu, Y., Li, B., Huang, C.-L., Chen, H.-D., Chen, J., Luo, Y., Guo, H., Jiang, R.-D, Liu, M.-Q., Chen, Y., Shen, X.-R., Wang, X., …, & Shi, Z.-L. (2020). A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature, 579(7798), 270-273. https://doi.org/10.1038/s41586-020-2012-7