The Mediating Effect of Facilitating Conditions on The Relationship Between Actual Usage of Online Social Networks (OSN) And User Satisfaction
DOI:
https://doi.org/10.61841/d6xk7a85Keywords:
Online social networks, ; facilitating conditions;, user satisfactionAbstract
--- The rapid rate of change in the organization's environment has continuously pushed the need for technologies and acceptance of these technologies at an accelerating rate. The new technologies are enabling organizations to be flatter, networked, and more flexible. Organizations in the 21st century inevitably make substantial investments in Information Technology (IT) in order to achieve competitive advantage, by spending enormous sums of money on computer hardware, software, communication networks, databases and specialized personnel. The main objective of this study is to determine factors influencing the user satisfaction of online social networks use among employees within Tourism Development and Investment Company (TDIC) in Abu Dhabi. This study collected data through quota nonprobability sampling, and 401 valid responses were received. Structural Equation Modelling- Variance based (SEM-VB) through partial least squares (PLS) method to analyse the research model using the software of SmartPLS 3.0. Although various limitations exist, the findings have been encouraging, as it has managed to shed some lights on new variables affecting the user satisfaction of online social networks. This study proposed an extended model of the Unified Theory of Acceptance & use of Technology (UTAUT) and found that two variables play an important role to determine the performance impact of online social networks namely actual usage and facilitating condition. The findings of this study can provide policymakers with important insights on how to more successfully incorporate online social networks to improve performance and the services of public sector, and how to encourage top managers to ensure that employees are more likely to utilize new technologies and thereby enabling better work outcome, wider reach of services, gives employees more control over their daily tasks and enhances their performance.
Downloads
References
[1] Abrego-Almazán, D., Sánchez-Tovar, Y., & Medina-Quintero, J. M. (2017). Influence of information systems on organizational results. Contaduría y Administración, 62(2), 321–338. https://doi.org/10.1016/j.cya.2017.03.001
[2] Almarashdeh, I. (2016). Sharing instructors experience of learning management system: A technology perspective of user satisfaction in distance learning course. Computers in Human Behavior, 63, 249–255. https://doi.org/http://dx.doi.org/10.1016/j.chb.2016.05.013
[3] Aparicio, M., Bacao, F., & Oliveira, T. (2017). Grit in the path to e-learning success. Computers in Human Behavior, 66(1), 388–399. https://doi.org/10.1016/j.chb.2016.10.009
[4] Arab Social Media Report. (2015). Benefits of Social Media usage, Arab Social Media Influencers Summit.
[5] Arteaga Sánchez, R., Cortijo, V., & Javed, U. (2014). Students’ perceptions of Facebook for academic purposes. Computers and Education, 70, 138–149. https://doi.org/10.1016/j.compedu.2013.08.012
[6] Awang, Z. (2014). Structural Equation Modeling Using AMOS. Shah Alam.Malaysia: University Teknologi MARA Publication Center.
[7] Baruch, Y., & Holtom, B. C. (2008). Survey response rate levels and trends in organizational research. Human Relations, 61(8), 1139–1160. https://doi.org/10.1177/0018726708094863
[8] Chang, C.-C. (2013). Library mobile applications in university libraries. Library Hi Tech, 31(3), 478–492. https://doi.org/10.1108/LHT-03-2013-0024
[9] Chen, C. (2008). Study on Application of E-commerce and Organizational Performance in Taiwanese Professional Sports Event Promotion Organizations. The Journal of Human Resource and Adult Learning, 4(1), 66–73.
[10] Cheung, W., Chang, M. K., & Lai, V. S. (2000). Prediction of Internet and World Wide Web usage at work: a test of an extended Triandis model. Decision Support Systems, 30(1), 83–100. https://doi.org/10.1016/S0167-9236(00)00125-1
[11] Chin, W. W. (1998a). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), 7–16.
[12] Chin, W. W. (1998b). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295-358). New Jersey: Lawrence Erlbaum Associates. Mahwah, NJ: Lawrence Erlbaum.
[13] Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd Editio). LawreAssociatesnce Erlbaum.
[14] Cooper, D. R., & Schindler, P. S. (2013). Business Research Methods (12th Editi). McGraw-Hill Education.
[15] Culibrk, D., Lalic, B., Stefanovic, D., Marjanovic, U., & Delic, M. (2016). Information & Management Assessing the success of e-government systems : An employee perspective. Information & Management, 53(1), 717–726. https://doi.org/10.1016/j.im.2016.02.007
[16] Delone, W. H., & Mclean, E. R. (1992). Information Systems Success: The Quest for the Dependent Variable. Information Systems Research, 3(1), 60–95.
[17] Delone, W. H., & Mclean, E. R. (2003). The DeLone and McLean Model of Information Systems Success : A Ten-Year Update. Journal of Management Information System, 19, 9–31.
[18] DeLone, W H, & Mclean, E. R. (2003). The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. Journal of Management Information Systems / Spring, 19(4), 9–30. https://doi.org/10.1073/pnas.0914199107
[19] DeLone, William H., & McLean, E. R. (2016). Information Systems Success Measurement. In Series in Information Technology Management. now Publishers Inc. PO.
[20] Fang, S.-F. (2014). Using UTAUT Model to Explore the User Behavior of E-Learning System in a Public Sector. Department of Communications Management.
[21] Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
[22] Global Information Technology Report. (2016). Importance of ICTs to government vision of the future and Impact of ICTs on organizational in UAE, World Economic Forum.
[23] Greengard, S. (2015). The Internet of Things (T. M. Press, Ed.).
[24] Gu, J.-C., Lee, S.-C., & Suh, Y.-H. (2009). Determinants of behavioral intention to mobile banking. Expert Systems with Applications, 36(9), 11605–11616. https://doi.org/10.1016/j.eswa.2009.03.024
[25] Guo, Y. (2015). Moderating Effects of Gender in the Acceptance of Mobile SNS Based on UTAUT Model. International Journal of Smart Home, 9(1), 203–216.
[26] Hadji, B., & Degoulet, P. (2016). Information system end-user satisfaction and continuance intention : A unified modeling approach. Journal of Biomedical Informatics, 61, 185–193. https://doi.org/10.1016/j.jbi.2016.03.021
[27] Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7th Editio). Prentice Hall.
[28] Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). London: Thousand Oaks: SAGE.
[29] Im, I., Hong, S., & Kang, M. S. (2011). An international comparison of technology adoption: adoption Testing the UTAUT model. Information & Management, 48(1), 1–8. https://doi.org/10.1016/j.im.2010.09.001
[30] Internet Live Stats. (2016). Internet Users in the World.
[31] Isaac, O., Abdullah, Z., Ramayah, T., & Mutahar, A. M. (2017). Internet usage , user satisfaction , task- technology fit , and performance impact among public sector employees in Yemen. The International Journal of Information and Learning Technology, 34(3), 210–241. https://doi.org/10.1108/IJILT-11-2016- 0051
[32] Isaac, O., Abdullah, Z., Ramayah, T., & Mutahar, A. M. (2017). Internet usage, user satisfaction, task- technology fit, and performance impact among public sector employees in Yemen. International Journal of Information and Learning Technology, 34(3), 210–241. https://doi.org/10.1108/IJILT-11-2016-0051
[33] Isaac, Osama, Abdullah, Z., Ramayah, T., & Mutahar, A. M. (2018). Factors determining user satisfaction of internet usage among public sector employees in Yemen. International Journal of Technological Learning,
Innovation and Development, 10(1), 37–68. https://doi.org/10.1504/IJTLID.2018.10012960
[34] Isaac, Osama, Abdullah, Z., Ramayah, T., Mutahar, A. M., & Alrajawy, I. (2017). Towards a Better Understanding of Internet Technology Usage by Yemeni Employees in the Public Sector: An Extension of the Task-Technology Fit (TTF) Model. Research Journal of Applied Sciences, 12(2), 205–223. https://doi.org/10.3923/rjasci.2017.205.223
[35] Isaac, Osama, Abdullah, Z., Ramayah, T., Mutahar, A. M., & Alrajawy, I. (2018). Integrating User Satisfaction and Performance Impact with Technology Acceptance Model (TAM) to Examine the Internet Usage Within Organizations in Yemen. Asian Journal of Information Technology, 17(1), 60–78. https://doi.org/10.3923/ajit.2018.60.78
[36] Isaac, Osama, Aldholay, A., Abdullah, Z., & Ramayah, T. (2019). Online learning usage within Yemeni higher education: The role of compatibility and task-technology fit as mediating variables in the IS success model.
Computers & Education, 136(1), 113–129. https://doi.org/https://doi.org/10.1016/j.compedu.2019.02.012
[37] Kim, C., Lee, I.-S., Wang, T., & Mirusmonov, M. (2015). Evaluating effects of mobile CRM on employees’ performance. Industrial Management & Data Systems, 115(4), 740–764. https://doi.org/10.1108/IMDS-08- 2014-0245
[38] Kim, H.-W., Chan, H. C., & Gupta, S. (2007). Value-based Adoption of Mobile Internet: An empirical investigation. Decision Support Systems, 43(1), 111–126. https://doi.org/10.1016/j.dss.2005.05.009
[39] Kline, R. B. (2010). Principles and practice of structural equation modeling (3rd ed.). New York: The Guilford Press.
[40] Kripanont, N. (2007). Examining a Technology Acceptance Model of Internet Usage by Academics within Thai Business Schools.
[41] Lian, J. (2015). Critical factors for cloud based e-invoice service adoption in Taiwan : An empirical study. International Journal of Information Management, 35(1), 98–109.
[42] Lin, C.-P., & Anol, B. (2008). Learning online social support: an investigation of network information technology based on UTAUT. Cyberpsychology & Behavior : The Impact of the Internet, Multimedia and Virtual Reality on Behavior and Society, 11(3), 268–272. https://doi.org/10.1089/cpb.2007.0057
[43] Lin, H. F. (2007). Predicting consumer intentions to shop online: An empirical test of competing theories.
Electronic Commerce Research and Applications, 6, 433–442. https://doi.org/10.1016/j.elerap.2007.02.002
[44] M. Kocaleva, I. S. Z. Z. (2014). Research on UTAUT Application in Higher Education Institution. International Conference on Information Technology and Development of Education, (June).
[45] Makokha, M. W., & Ochieng, D. O. (2014). Assessing the Success of ICT ’ s from a User Perspective : Case Study of Coffee Research Foundation in Kenya. Journal of Management and Strategy, 5(4), 46–54. https://doi.org/10.5430/jms.v5n4p46
[46] Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1–13. https://doi.org/10.1016/j.ijinfomgt.2013.06.002
[47] McNamee, R. (2011). 6 ways to save the internet.
[48] Moghawemi, S., Mohd Salleh, N. A., Zhao, W., & Mattila, M. (2012). The entrepreneur’s perception on information technology innovation adoption: An empirical analysis of the role of precipitating events on usage behavior. Innovation: Management, Policy and Practice, 14(2), 231–246. https://doi.org/10.5172/impp.2012.14.2.231
[49] Montesdioca, G. P. Z., & Maçada, A. C. G. (2015). Measuring user satisfaction with information security practices. Computers & Security, 48(1), 267–280. https://doi.org/10.1016/j.cose.2014.10.015
[50] Nistor, N., Lerche, T., Weinberger, A., Ceobanu, C., & Heymann, O. (2014). Towards the integration of culture into the Unified Theory of Acceptance and Use of Technology. British Journal of Educational Technology, 45(1), 36–55. https://doi.org/10.1111/j.1467-8535.2012.01383.x
[51] Norzaidi, M. D. (2008). Factors determining intranet usage: an empirical study of middle managers in Malaysian port industry. Multimedia University.
[52] Norzaidi, M. D., & Salwani, M. I. (2009). Evaluating technology resistance and technology satisfaction on students’ performance. Campus-Wide Information Systems, 26(4), 298–312. https://doi.org/10.1108/10650740910984637
[53] Pahnila, S., Siponen, M., & Zheng, X. (2011). Integrating Habit into UTAUT : The Chinese eBay Case. 3(2), 1–30.
[54] Petter, S., & McLean, E. R. (2009). A meta-analytic assessment of the DeLone and McLean IS success model: An examination of IS success at the individual level. Information and Management, 46(3), 159–166. https://doi.org/10.1016/j.im.2008.12.006
[55] Pew Research Center. (2013).
[56] Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36(4), 717–731.
[57] Radcliffe, D. (2016). Social Media in the Middle East: The Story of 2015. Northwestern University in Qatar.
[58] Raman, A., & Don, Y. (2013). Preservice Teachers’ Acceptance of Learning Management Software: An Application of the UTAUT2 Model. International Education Studies, 6(7), 157–164. https://doi.org/10.5539/ies.v6n7p157
[59] Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. Bonningstedt: SmartPLS.
[60] Singeh, F. W., Abrizah, A., & Karim, N. H. A. (2013). Malaysian authors’ acceptance to self-archive in institutional repositories: Towards a unified view. Electronic Library, 31(2), 188–207. https://doi.org/10.1108/02640471311312375
[61] Statista. (2017a). Active social network penetration.
[62] Statista. (2017b). Leading online social networks worldwide , ranked by number of active users (in millions).
[63] Statista. (2017c). Number of social media users worldwide from 2010 to 2020 (in billions).
[64] Tam, C., & Oliveira, T. (2016). Understanding the impact of m-banking on individual performance: DeLone & McLean and TTF perspective. Computers in Human Behavior, 61(1), 233–244. https://doi.org/10.1016/j.chb.2016.03.016
[65] Tull, D. S., & Hawkins, D. I. (1984). Marketing Research: Measurement and Method (3rd editio). Macmillan Library Reference.
[66] Venkatesh, V., Morris, M. G., Davis, G. B., Davis, F. D., & Walton, S. M. (2003). USER ACCEPTANCE OF INFORMATION TECHNOLOGY : TOWARD A UNIFIED VIEW 1. 27(3), 425–478.
[67] Venkatesh, V., & Zhang, X. (2010). Unified Theory of Acceptance and Use of Technology: U.S. Vs. China. Journal of Global Information Technology Management, 13(1), 5–27. https://doi.org/10.1080/1097198X.2010.10856507
[68] Wang, J., & Hou, F. (2003). Research on the Relationship between the Internet Usages and the Organizational Performance in the Taiwanese E-commerce Business Organizations. Informing Science, 1(1), 17–25.
[69] Wang, Y.-S., Li, H.-T., Li, C.-R., & Wang, C. (2014). A model for assessing blog-based learning systems success. Online Information Review, 38(7), 969. https://doi.org/10.1108/OIR-04-2014-0097
[70] Wang, Y.-S., & Liao, Y.-W. (2008). Assessing eGovernment systems success: A validation of the DeLone and McLean model of information systems success. Government Information Quarterly, 25(4), 717–733. https://doi.org/10.1016/j.giq.2007.06.002
[71] Wu, Y. L., Tao, Y. H., & Yang, P. C. (2007). Using UTAUT to explore the behavior of 3G mobile communication users. IEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management, 199–203. https://doi.org/10.1109/IEEM.2007.4419179
[72] Xinli, H. (2015). Effectiveness of information technology in reducing corruption in China. Electronic Library, 33(1), 52–64. https://doi.org/10.1108/EL-11-2012-0148
[73] Yu-Lung, W., Yu-Hui, T., & Pei-Chi, Y. (2008). The use of unified theory of acceptance and use of technology to confer the behavioral model of 3G mobile telecommunication users Yu-Lung Wu. Journal of Statistics & Management Systems, 11(5), 919–949. https://doi.org/10.1080/09720510.2008.10701351
[74] Yueh, H. P., Huang, J. Y., & Chang, C. (2015). Exploring factors affecting students’ continued Wiki use for individual and collaborative learning: An extended UTAUT perspective. Australasian Journal of Educational Technology, 31(1), 16–31.
[75] Zikmund, W. G., Babin, B. J., Carr, J. C., & Griffin, M. (2010). Business Research Methods (Eighth). Cengage Learning.
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.