IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i11p3928-d179035.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/11/3928/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/11/3928/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jose Ramon Saura & Ana Reyes-Menendez & Cesar Alvarez-Alonso, 2018. "Do Online Comments Affect Environmental Management? Identifying Factors Related to Environmental Management and Sustainability of Hotels," Sustainability, MDPI, vol. 10(9), pages 1-20, August.
    2. Kao-Yi Shen & Gwo-Hshiung Tzeng, 2018. "Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications," Sustainability, MDPI, vol. 10(5), pages 1-7, May.
    3. Jie Zhao & Jianfei Wang & Suping Fang & Peiquan Jin, 2018. "Towards Sustainable Development of Online Communities in the Big Data Era: A Study of the Causes and Possible Consequence of Voting on User Reviews," Sustainability, MDPI, vol. 10(9), pages 1-18, September.
    4. Truong, Yann & McColl, Rod, 2011. "Intrinsic motivations, self-esteem, and luxury goods consumption," Journal of Retailing and Consumer Services, Elsevier, vol. 18(6), pages 555-561.
    5. Geng, Ruibin & Bose, Indranil & Chen, Xi, 2015. "Prediction of financial distress: An empirical study of listed Chinese companies using data mining," European Journal of Operational Research, Elsevier, vol. 241(1), pages 236-247.
    6. Kao-Yi Shen & Min-Ren Yan & Gwo-Hshiung Tzeng, 2017. "Exploring R&D Influences on Financial Performance for Business Sustainability Considering Dual Profitability Objectives," Sustainability, MDPI, vol. 9(11), pages 1-21, October.
    7. Blaszczynski, Jerzy & Greco, Salvatore & Slowinski, Roman, 2007. "Multi-criteria classification - A new scheme for application of dominance-based decision rules," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1030-1044, September.
    8. Umit Can & Bilal Alatas, 2017. "Big Social Network Data and Sustainable Economic Development," Sustainability, MDPI, vol. 9(11), pages 1-19, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).
    2. Vasile-Daniel Păvăloaia & Elena-Mădălina Teodor & Doina Fotache & Magdalena Danileţ, 2019. "Opinion Mining on Social Media Data: Sentiment Analysis of User Preferences," Sustainability, MDPI, vol. 11(16), pages 1-21, August.
    3. Fernandez, Eduardo & Navarro, Jorge & Bernal, Sergio, 2010. "Handling multicriteria preferences in cluster analysis," European Journal of Operational Research, Elsevier, vol. 202(3), pages 819-827, May.
    4. Yulian Zhang & Shigeyuki Hamori, 2020. "Forecasting Crude Oil Market Crashes Using Machine Learning Technologies," Energies, MDPI, vol. 13(10), pages 1-14, May.
    5. Pawel Lezanski & Maria Pilacinska, 2018. "The dominance-based rough set approach to cylindrical plunge grinding process diagnosis," Journal of Intelligent Manufacturing, Springer, vol. 29(5), pages 989-1004, June.
    6. Omer Gokcekus & Yui Suzuki, 2014. "Is there a Corruption-effect on Conspicuous Consumption?," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 8(3), pages 215-235, August.
    7. Azam, Nouman & Zhang, Yan & Yao, JingTao, 2017. "Evaluation functions and decision conditions of three-way decisions with game-theoretic rough sets," European Journal of Operational Research, Elsevier, vol. 261(2), pages 704-714.
    8. Yanfang Zhang & Mushang Lee, 2019. "A Hybrid Model for Addressing the Relationship between Financial Performance and Sustainable Development," Sustainability, MDPI, vol. 11(10), pages 1-15, May.
    9. Jiang, Cuiqing & Zhou, Yiru & Chen, Bo, 2023. "Mining semantic features in patent text for financial distress prediction," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    10. Yoo, Jungmin & Park, Minjung, 2016. "The effects of e-mass customization on consumer perceived value, satisfaction, and loyalty toward luxury brands," Journal of Business Research, Elsevier, vol. 69(12), pages 5775-5784.
    11. Hu, Qiwei & Chakhar, Salem & Siraj, Sajid & Labib, Ashraf, 2017. "Spare parts classification in industrial manufacturing using the dominance-based rough set approach," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1136-1163.
    12. Kum Fai Yuen & Do Thi Khanh Huyen & Xueqin Wang & Guanqiu Qi, 2020. "Factors Influencing the Adoption of Shared Autonomous Vehicles," IJERPH, MDPI, vol. 17(13), pages 1-17, July.
    13. Oppio, Alessandra & Dell’Ovo, Marta & Torrieri, Francesca & Miebs, Grzegorz & Kadziński, Miłosz, 2020. "Understanding the drivers of Urban Development Agreements with the rough set approach and robust decision rules," Land Use Policy, Elsevier, vol. 96(C).
    14. Reyes-Menendez, Ana & Clemente-Mediavilla, Jorge & Villagra, Nuria, 2023. "Understanding STI and SDG with artificial intelligence: A review and research agenda for entrepreneurial action," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    15. Alev Kocak Alan & Inci Dursun & Ebru Tumer Kabadayi & Kenan Aydin & Fikret Anlagan, 2016. "What Influences the Repurchase Intention for Luxury Brands?-The Relative Impacts of Luxury Value Dimensions," International Business Research, Canadian Center of Science and Education, vol. 9(5), pages 11-24, May.
    16. Zhao Wang & Cuiqing Jiang & Huimin Zhao, 2022. "Know Where to Invest: Platform Risk Evaluation in Online Lending," Information Systems Research, INFORMS, vol. 33(3), pages 765-783, September.
    17. Abbas Mardani & Mehrbakhsh Nilashi & Jurgita Antucheviciene & Madjid Tavana & Romualdas Bausys & Othman Ibrahim, 2017. "Recent Fuzzy Generalisations of Rough Sets Theory: A Systematic Review and Methodological Critique of the Literature," Complexity, Hindawi, vol. 2017, pages 1-33, October.
    18. Jiang, Cuiqing & Lyu, Ximei & Yuan, Yufei & Wang, Zhao & Ding, Yong, 2022. "Mining semantic features in current reports for financial distress prediction: Empirical evidence from unlisted public firms in China," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1086-1099.
    19. Marta Postuła & Wojciech Chmielewski & Piotr Puczyński & Rafał Cieślik, 2021. "The Impact of Information and Communication Technologies (ICT) on Energy Poverty and Unemployment in Selected European Union Countries," Energies, MDPI, vol. 14(19), pages 1-18, September.
    20. Guanping Zhou, 2019. "Financial distress prevention in China: Does gender of board of directors matter?," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(6), pages 1-8.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:10:y:2018:i:11:p:3928-:d:179035. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.