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Negative Impact of Social Network Services Based on Stressor-Stress-Outcome: The Role of Experience of Privacy Violations

Author

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  • Sanghyun Kim

    (School of Business Administration, Kyungpook National University, Daegu 41566, Korea)

  • Hyunsun Park

    (School of Business Administration, Kyungpook National University, Daegu 41566, Korea)

  • Moon Jong Choi

    (Department of Computer Science and Engineering, Sunmoon University, Asan 31460, Korea)

Abstract

Social network service (SNS) information has benefited many individuals. However, as such information has increased exponentially, the number of SNS users has increased dramatically and negative effects of SNSs on users have emerged. Many SNS users experience negative psychological conditions such as fatigue, burnout, and stress. Thus, in this study, we investigated the SNS and user characteristics that affect SNS fatigue, living disorder, and reduced SNS use intention. We developed a research model to examine the impact of two SNS characteristics (irrelevant information overload and open reachability) and two user characteristics (engagement and maintaining self-reputation) on SNS fatigue. We also examined the role of the experience of privacy violations in the relationship between living disorder and reduced SNS use intention. We collected data from 579 SNS users and created a partial least squares structural equation model to test the hypotheses. The results of the analysis showed that three factors, other than open reachability, positively affected SNS fatigue. Furthermore, we found that SNS fatigue significantly affected living disorder and reduced SNS use intention, and that experience of privacy violations significantly affected the relationship between living disorder and reduced SNS use intention. These results expand our understanding of SNS fatigue and users’ negative behaviors.

Suggested Citation

  • Sanghyun Kim & Hyunsun Park & Moon Jong Choi, 2019. "Negative Impact of Social Network Services Based on Stressor-Stress-Outcome: The Role of Experience of Privacy Violations," Future Internet, MDPI, vol. 11(6), pages 1-20, June.
  • Handle: RePEc:gam:jftint:v:11:y:2019:i:6:p:137-:d:241589
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    References listed on IDEAS

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    1. Sanghyun Kim & Gary Garrison, 2009. "Investigating mobile wireless technology adoption: An extension of the technology acceptance model," Information Systems Frontiers, Springer, vol. 11(3), pages 323-333, July.
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    5. José Ramón Saura & Pedro Palos-Sánchez & Luis Manuel Cerdá Suárez, 2017. "Understanding the Digital Marketing Environment with KPIs and Web Analytics," Future Internet, MDPI, vol. 9(4), pages 1-13, November.
    6. Thara Ravindran & Alton Chua Yeow Kuan & Dion Goh Hoe Lian, 2014. "Antecedents and effects of social network fatigue," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(11), pages 2306-2320, November.
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    Cited by:

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    3. Yazn Alshamaila & Ferial Mohammad Abu Awwad & Ra’ed Masa’deh & Mahmoud E. Farfoura, 2023. "Complexities, Challenges, and Opportunities of Mobile Learning: A Case Study at the University of Jordan," Sustainability, MDPI, vol. 15(12), pages 1-24, June.

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