Assessing the Negative Determinants on the Usage Intention of Social Media
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Asian Institute of Research, Journal Publication, Journal Academics, Education Journal, Asian Institute
Asian Institute of Research, Journal Publication, Journal Academics, Education Journal, Asian Institute

Economics and Business

Quarterly Reviews

ISSN 2775-9237 (Online)

asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
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open access

Published: 26 October 2020

Assessing the Negative Determinants on the Usage Intention of Social Media

Hsin-yeh Tsai, Yu-Ping Lee, Wen-Bin Tsai

Shu-Te University (Taiwan), Southern Taiwan University of Science and Technology (Taiwan)

asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, management journal

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doi

10.31014/aior.1992.03.04.286

Pages: 1357-1371

Keywords: Social Media, Negative Factors, Social Fatigue, Partial Least Squares

Abstract

Since the development of the Internet jumped quickly, the user can perform a variety of social media information and communicate via computers, mobile phones and other smart devices. Social media can be presented in many different forms, including text, images, music and videos. Under the high popularity of social media usage, users will share information on community self-media platforms, including personal ideas, feelings and experiences. However, social media is one of the sides of a virtual network that allows users to bring convenient, instant, etc. But they also bring negative factors can’t be predicted for users, such as: lack of privacy controls, social media into hidden problems. Due to these reasons, users can cause by long-term excessive use of social media, and make themselves feel fatigue social of psychology. The study investigates whether the negative factors will affect users of social media for social impact of fatigue, use Google questionnaires to collect samples of the web results. To sum up, the conclusion of the study showed that most of the negative factors of social media are social media users will feel social fatigue.

References

  1. Bevan, J. L., Ang, P. C., & Fearns, J. B. (2014). Being unfriended on Facebook: An application of expectancy violation theory. Computers in Human Behavior, 33, 171-178.

  2. Chang, Y. P., & Zhu, D. H. (2012). The role of perceived social capital and flow experience in building users’ continuance intention to social networking sites in China. Computers in Human Behavior, 28(3), 995-1001.

  3. Chen, S. C., Yen, D. C., & Hwang, M. I. (2012). Factors influencing the continuance intention to the usage of Web 2.0: An empirical study. Computers in Human Behavior, 28(3), 933-941.

  4. Chen, W., & Lee, K. H. (2013). Sharing, liking, commenting, and distressed? The pathway between Facebook interaction and psychological distress. Cyberpsychology, Behavior, and Social Networking, 16(10), 728-734.

  5. Chou, H. T. G., & Edge, N. (2012). They are happier and having better lives than I am”: the impact of using Facebook on perceptions of others' lives. Cyberpsychology, Behavior, and Social Networking, 15(2), 117-121.

  6. Fox, J., & Moreland, J. J. (2015). The dark side of social networking sites: An exploration of the relational and psychological stressors associated with Facebook use and affordances. Computers in Human Behavior, 45, 168-176.

  7. Fox, J., Jones, E. B., & Lookadoo, K. (2013). Romantic relationship dissolution on social networking sites: Social support, coping, and rituals on Facebook. Paper presented at the 63rd Annual Conference of the International Communication Association, London, UK.

  8. Hochberg, M. S., Berman, R. S., Kalet, A. L., Zabar, S. R., Gillespie, C., & Pachter, H. L. (2013). The stress of residency: recognizing the signs of depression and suicide in you and your fellow residents. The American Journal of Surgery, 205(2), 141-146.

  9. Hong, H. K., Han, S. Y., Lee, J. W., Kim, M. S., & Han, K. S. (2015). A Study on the Effects of SNS Fatigue and Ambivalent Attitude on the Intention on SNS Continual Use. International Journal of u-and e-Service, Science and Technology, 8(10), 129-138.

  10. Hsu, C. L., & Lu, H. P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information & management, 41(7), 853-868.

  11. Kim, A. J., & Ko, E. (2010). Impacts of luxury fashion brand’s social media marketing on customer relationship and purchase intention. Journal of Global Fashion Marketing, 1(3), 164-171.

  12. Koo, D. M. (2009). The moderating role of locus of control on the links between experiential motives and intention to play online games. Computers in Human Behavior, 25(2), 466-474.

  13. Krämer, N. C., & Winter, S. (2008). Impression management 2.0: The relationship of self-esteem, extraversion, self-efficacy, and self-presentation within social networking sites. Journal of Media Psychology, 20(3), 106-116.

  14. Kross, E., Verduyn, P., Demiralp, E., Park, J., & Lee, D. S. (2013). Facebook Use Predicts Declines in Subjective Well-Being in Young Adults. PLoS ONE, 8(8).

  15. Lee, A. R., Son, S. M., & Kim, K. K. (2016). Information and communication technology overload and social networking service fatigue: A stress perspective. Computers in Human Behavior, 55, 51-61.

  16. Lin, K. M. (2013, May). The negative critical incidents of social network service: An exploratory study. In Service Science and Innovation (ICSSI), 2013 Fifth International Conference on (pp. 96-99). IEEE.

  17. Lin, K. M. (2015). Predicting Asian undergraduates’ intention to continue using social network services from negative perspectives. Behaviour & Information Technology, 34(9), 882-892-11.

  18. Liu, Z., Min, Q., Zhai, Q., & Smyth, R. (2015). Self-disclosure in Chinese micro-blogging: A social exchange theory perspective. Information & Management.

  19. Marshall, T. C. (2012). Facebook surveillance of former romantic partners: associations with postbreakup recovery and personal growth. Cyberpsychology, Behavior, and Social Networking, 15(10), 521-526.

  20. Masur, P. K., Reinecke, L., Ziegele, M., & Quiring, O. (2014). The interplay of intrinsic need satisfaction and Facebook specific motives in explaining addictive behavior on Facebook. Computers in Human Behavior, 39, 376-386.

  21. Stieger, S., Burger, C., Bohn, M., & Voracek, M. (2013). Who commits virtual identity suicide? Differences in privacy concerns, internet addiction, and personality between Facebook users and quitters. Cyberpsychology, Behavior, and Social Networking, 16(9), 629-634.

  22. Tokunaga, R. S. (2014). Relational transgressions on social networking sites: Individual, interpersonal, and contextual explanations for dyadic strain and communication rules change. Computers in Human Behavior, 39, 287-295.

  23. Ukaegbu, C. I., & Rashid, S. S. (2014). KINETOSIS-ALL YOU NEED TO KNOW. Journal of Biotechnology Science Research, 1(3).

  24. Wu, C. H., & Chen, S. C. (2015). Understanding the relationships of critical factors to Facebook educational usage intention. Internet Research, 25(2), 262-278.

  25. Yamakami, T. (2012, December). Towards understanding SNS fatigue: exploration of social experience in the Virtual World. In Computing and Convergence Technology (ICCCT), 2012 7th International Conference on (pp. 203-207). IEEE

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