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Exploring Users’ Self-Disclosure Intention on Social Networking Applying Novel Soft Computing Theories

Author

Listed:
  • Yang-Chieh Chin

    (Department of Commerce Technology and Management, Chihlee University of Technology, New Taipei City 22050, Taiwan)

  • Wen-Zhong Su

    (Department of Business Administration, Chihlee University of Technology, New Taipei City 22050, Taiwan)

  • Shih-Chih Chen

    (National Kaohsiung University of Science & Technology, Kaohsiung 82444, Taiwan)

  • Jianing Hou

    (Business School, University of Hubei, Wuhan 430062, China)

  • Yu-Chuan Huang

    (Department of Accounting Information, Southern Taiwan University of Science and Technology, Tainan City 71005, Taiwan)

Abstract

In recent years, users have increasingly focused on the privacy of social networking sites (SNS); users have reduced their self-disclosure intention. To attract users, SNS rely on active platforms that collect accurate user information, even though that information is supposed to be private. SNS marketers must understand the key elements for sustainable operation. This study aims to understand the influence of motivation (extrinsic and intrinsic) and self-disclosure on SNS through soft computing theories. First, based on a survey of 1108 users of SNS, this study used a dominance-based rough set approach to determine decision rules for self-disclosure intention on SNS. In addition, based on 11 social networking industry experts’ perspectives, this study validated the influence between the motivation attributes by using Decision-Making Trial and Evaluation Laboratory (DEMATEL). In this paper, the decision rules of users’ self-disclosure preference are presented, and the influences between motivation attributes are graphically depicted as a flow network graph. These findings can assist in addressing real-world decision problems, and can aid SNS marketers in anticipating, evaluating, and acting in accord with the self-disclosure motivations of SNS users. In this paper, practical and research implications are offered.

Suggested Citation

  • Yang-Chieh Chin & Wen-Zhong Su & Shih-Chih Chen & Jianing Hou & Yu-Chuan Huang, 2018. "Exploring Users’ Self-Disclosure Intention on Social Networking Applying Novel Soft Computing Theories," Sustainability, MDPI, vol. 10(11), pages 1-16, October.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:11:p:3928-:d:179035
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    References listed on IDEAS

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    Cited by:

    1. Hung-Yue Suen & Kuo-En Hung & Fan-Hsun Tseng, 2020. "Employer Ratings through Crowdsourcing on Social Media: An Examination of U.S. Fortune 500 Companies," Sustainability, MDPI, vol. 12(16), pages 1-15, August.

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