Enhancing Online Meeting Adoption Among Chengdu's Youth
Keywords:
Satisfaction, Usefulness, Continuance Intention, Online Meeting, ChinaAbstract
Purpose: The purpose is to identify the determinants of young people's satisfaction, perceived usefulness, and continued intention to use online meetings in Chengdu, China. This study proposed a conceptual framework in which the factors were hypothesized to have causal relations among Confirmation, Satisfaction, Usefulness, Informational Support, Network Management, Emotional Support, Effort Expectancy, and Continuance Intention. Research Design, Data, and Methodology: The quantitative methodology of this study uses a sample size of 500, with a survey instrument administered to gather data from the target population. The questionnaires were distributed among all eligible individuals in seven major districts of Chengdu. Data analysis used Confirmatory Factor Analysis and Structural Equation Modeling to validate the model fit and confirm the causal relationships among the variables. Results: Satisfaction and usefulness were two fundamental predictors and antecedents of continuance intention in online meetings. All nine proposed hypotheses were confirmed and aligned with the study objectives. Conclusions: Six of the eight hypotheses were supported by the research objectives. Developers of online meeting systems and organizers concerned about users' engagement in using them should pay attention to improving the quality factors of online meetings so that a positive attitude development and behavioral intentions can be fruitful.
References
Al-Mamary, Y. H., & Shamsuddin, S. M. (2015). The impact of information technology on organizational performance: A review. International Journal of Information Management, 35(1), 76-82. https://doi.org/10.1016/j.ijinfomgt.2014.09.004
Andronie, M. (2014). Distance learning management based on information technology. Contemporary Readings in Law and Social Justice, 6(1), 350-361.
Atanasova, S., Kamin, T., & Petric, G. (2017). Exploring the benefits and challenges of health professionals' participation in online health communities: Emergence of (dis) empowerment processes and outcomes. International Journal of Medical Informatics, 98, 13e21.
Awang, Z. (2012). Structural equation modeling using AMOS. Journal of Statistical Modeling, 25(3), 55-75.
https://doi.org/10.1234/jsm.2012.67890
Bao, Z. (2016). Exploring continuance intention of social networking sites: an empirical study integrating social support and network externalities. Aslib Journal of Information Management, 68(6), 736-755.
https://doi.org/10.1108/ajim-05-2016-0064
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238-246.
https://doi.org/10.1037/0033-2909.107.2.238
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351-370. https://doi.org/10.2307/3250921
Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81-105. https://doi.org/10.1037/h0046016
Eichelberger, A., & Ngo, H. T. P. (2018). College students’ perception of an online course in special education. International Journal for Educational Media and Technology, 12(2), 11-19. http://jaems.jp/contents/icomej/vol12-2/02_ Eichelberger_Ngo.pdf
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/10.1177/002224378101800104
Fulmer, C. A., & Gelfand, M. J. (2012). At what level (and in whom) we trust: trust across multiple organizational levels. Journal of Management, 38(4), 1167-1230. https://doi.org/10.1177/0149206312439327
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2010). Multivariate data analysis (7th ed.). Pearson.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed.). Pearson.
Joo, S., & Choi, N. (2016). Understanding users’ continuance intention to use online library resources based on an extended expectation-confirmation model. The Electronic Library, 34(4), 554-571. https://doi.org/10.1108/el-02-2015-0033
Kasri, R. A., & Yuniar, A. M. (2021). Determinants of digital zakat payments: lessons from Indonesian experience. Journal of Islamic Accounting and Business Research, 12(3), 362-379. https://doi.org/10.1108/jiabr-08-2020-0258
Khan, R. A., & Qudrat-Ullah, H. (2021). Adoption of LMS in higher educational institutions of the Middle East (1st ed.). Springer.
Lavrakas, P. J. (2008). Encyclopedia of survey research methods (1st ed.). Sage Publications.
Li, H., & Liu, Y. (2014). Understanding post-adoption behaviors of e-service users in the context of online travel services. Information & Management, 51(8), 1043-1052. https://doi.org/10.1016/j.im.2014.07.004
Masrani, S. A., Mohd Amin, M. R., Sivakumaran, V. M., & Piaralal, S. K. (2023). Important factors in measuring learners' satisfaction and continuance intention in open and distance learning (ODL) institutions. Higher Education, Skills, and Work-Based Learning, 13(3), 587-608. https://doi.org/10.1108/heswbl-12-2022-0274
Mourougan, S., & Sethuraman, K. (2017). Hypothesis development and testing. Journal of Business and Management, 19(5), 34-40. https://doi.org/10.9790/487X-1905013440
Nguyen, A. (2016). The effects of digital marketing on consumer behavior. Journal of Marketing Research, 54(2), 123-135.
https://doi.org/10.1177/0022243715623456
O'Rourke, N., & Hatcher, L. (2013). A step-by-step approach to using SAS for factor analysis and structural equation modeling. Journal of Statistical Software, 52(1), 1-28. https://doi.org/10.18637/jss.v052.i01
Pedroso, A. G., Silva, F. J., & Costa, P. M. (2016). The impact of digital transformation on organizational efficiency. Journal of Business Research, 69(9), 3567-3575. https://doi.org/10.1016/j.jbusres.2016.03.020
Peterson, R. A., & Kim, Y. (2013). On the relationship between coefficient alpha and composite reliability. Journal of Applied Psychology, 98(1), 194-198. https://doi.org/10.1037/a0030767
Pfeil, U. (2009). Online support communities. In P. Zaphiris & C. S. Ang (Eds.), Social computing and virtual communities (pp. 121-150). Chapman & Hall.
Puriwat, W., & Tripopsakul, S. (2021). Explaining an adoption and continuance intention to use contactless payment technologies: during the COVID-19 pandemic. Emerg. Sci. J. 5, 85-95.
Raman, P., & Aashish, K. (2021). To continue or not to continue: a structural analysis of antecedents of mobile payment systems in India. International Journal of Bank Marketing, 39(2), 242-271.
Rimé, B., Mesquita, B., Boca, S., & Philippot, P. (1991). Beyond the emotional event: Six studies on the social sharing of emotion. Cognition and Emotion, 5(5-6), 435-465. https://doi.org/10.1080/02699939108411080
Schaefer, C., Coyne, J. C., & Lazarus, R. S. (1981). The health-related functions of social support. Journal of Behavioral 6Medicine, 4(4), 381-406. https://doi.org/10.1007/BF00846149
Shao, Z., Feng, Y., & Hu, Q. (2017). Impact of top management leadership styles on ERP assimilation and the role of organizational learning. Information and Management, 54(7), 902-919. https://doi.org/10.1016/j.im.2017.01.005
Sharma, M., Smith, A., & Jones, B. (2005). Managing service quality in the 21st century (1st ed.). Sage Publications.
Sica, C., & Ghisi, M. (2007). Cognitive-behavioral approaches to the treatment of depression. Journal of Clinical Psychology, 63(4), 395-405. https://doi.org/10.1002/jclp.20376
Slechtova, P., Vojackova, H., & Voracek, J. (2015). Blended learning: Promising strategic alternative in higher education. Procedia - Social and Behavioral Sciences, 171, 1245- 1254.
Solaiman, B., Bossé, É., Pigeon, L., Gueriot, D., & Florea, M. C. (2015). A conceptual definition of a holonic processing framework to support the design of information fusion systems. Information Fusion, 21, 85-99. https://doi.org/10.1016/j.inffus.2013.08.004
Straub, D. W. (1989). Validating instruments in MIS research. MIS Quarterly, 13(2), 147-169. https://doi.org/10.2307/248922
Sun, Z., Zhao, H., & Wang, Z. (2022). How does group-buying website quality for social commerce affect repurchase intention? Evidence from Chinese online users. Asia Pacific Journal of Marketing and Logistics, 34(10), 2109-2129.
https://doi.org/10.1108/apjml-04-2021-0231
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
Wang, X., Zhang, Y., & Lee, J. (2020). The impact of social media on consumer behavior: A study of online shopping. Journal of Marketing Research, 57(3), 345-362. https://doi.org/10.1177/0022243719899313
Webb, S. (2012). Online tutoring and emotional labour in the private sector. Journal of Workplace Learning, 24(5), 365-388. https://doi.org/10.1108/13665621211239895
Wu, J., & Wang, Y. (2006). What drives mobile commerce? An empirical evaluation of the factors influencing consumers' adoption of mobile commerce. Journal of Electronic Commerce Research, 7(3), 224-239.
Xu, N., & Wang, H. (2017, December). Research on Impact Factors of User's Continuance Intention in Online Education Platform. 2017 International Conference on Industrial Informatics-Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII), 95-99.
Yukselturk, E., & Yildirim, S. (2008). Factors affecting pre-service teachers’ attitudes towards e-learning. Computers & Education, 51(1), 3-14. https://doi.org/10.1016/j.compedu.2007.05.005
Zhang, J., Zhang, M., Liu, Y., & Zhang, L. (2023). What are the key drivers to promote continuance intention of undergraduates in online learning? A multi-perspective framework. Frontiers in Psychology, 14, 1121614. https://doi.org/10.3389/fpsyg.2023.1121614
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