The Role of Non-social Benefits Related to Convenience: Towards an Enhanced Model of User’s Self-disclosure in Social Networks

  • Tristan Thordsen
  • Matthias Murawski
  • Markus BickEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9844)


Despite the overwhelming and unabated popularity of social networks in the past years, the motivation behind an individual’s registration to such platforms is still largely uncharted. Based on an in-depth review of leading Information Systems literature, this paper investigates which factors potentially influence individual´s self-disclosure in social networks. The literature review reveals information privacy violation as the primary risk of online platform use. Regarding benefits, two categories are identified: social benefits, like reciprocity, relationship building and maintenance, or self-presentation as well as non-social benefits related to convenience, like personalization, entertainment, and safety and security. The later ones are mostly neglected in existing models. The main contribution of this paper consists of filling this gap by developing an enhanced research model of the user’s self-disclosure in social networks.


Convenience Privacy concerns Self-disclosure Social and non-social benefits Social networks Structured literature review 


  1. 1.
    Statista: Facebook: number of monthly active users worldwide 2008–2015.
  2. 2.
    Statista: Number of worldwide {Internet} users from 2000 to 2015 (in millions).
  3. 3.
    Krasnova, H., Spiekermann, S., Koroleva, K., Hildebrand, T.: Online social networks: why we disclose. J. Inf. Technol. 25, 109–125 (2010)CrossRefGoogle Scholar
  4. 4.
    Twitter Inc.: About Twitter.
  5. 5.
  6. 6.
    Richter, D., Riemer, K., vom Brocke, J., Große Böckmann, S.: Internet social networking - distinguishing the phenomenon from its manifestations. In: Proceedings of 17th European Conference on Information Systems, Verona (2009)Google Scholar
  7. 7.
    Gerlach, J., Widjaja, T., Buxmann, P.: Handle with care: how online social network providers’ privacy policies impact users’ information sharing behavior. J. Strateg. Inf. Syst. 24, 33–43 (2015)CrossRefGoogle Scholar
  8. 8.
    Acquisti, A., Brandimarte, L., Loewenstein, G.: Privacy and human behavior in the age of information. Science 347, 509–514 (2015)CrossRefGoogle Scholar
  9. 9.
    Goes, P.B.: Big data and IS research. Science 38, 3–8 (2014)Google Scholar
  10. 10.
    Tow, W.N.H., Venable, J.R., Dell, P.: Understanding information disclosure behaviour in Australian Facebook users. J. Inf. Technol. 25, 1019–1028 (2010)CrossRefGoogle Scholar
  11. 11.
    Jiang, Z.J., Heng, C.S., Choi, B.C.F.: Privacy concerns and privacy-protective behavior in synchronous online social interactions. Inf. Syst. Res. 24, 579–595 (2013)CrossRefGoogle Scholar
  12. 12.
    Thibaut, J., Kelley, H.: The Social Psychology of Groups. Wiley, New York (1959)Google Scholar
  13. 13.
    Ryschka, S.: Location-Based Services from a User’ s Perspective Benefits and Risks (2015).
  14. 14.
    Martensen, M., Börgmann, K., Bick, M.: The impact of social networking sites on the employer-employee relationship. In: Proceedings of 24th Bled eConference. eFuture: Creating Solutions for the Individual. Organisations and Society, Bled, 12–15 June 2011 (2011)Google Scholar
  15. 15.
    Rowe, F.: What a literature review is not - diversity, boundaries and recommendations. Eur. J. Inf. Syst. 3, 240–250 (2014)Google Scholar
  16. 16.
    Boote, D.N., Beile, P.: Scholars before researchers: on the centrality of the dissertation literature review in research preparation. Educ. Res. 6, 3–15 (2005)CrossRefGoogle Scholar
  17. 17.
    Aral, S., Dellarocas, C., Godes, D.: Social media and business transformation: a framework for research. Inf. Syst. Res. 24, 3–13 (2013)CrossRefGoogle Scholar
  18. 18.
  19. 19.
    Harzing, A.-W.: Journal Quality List.
  20. 20.
    VHB: VHB Jourqual 3 Rating.
  21. 21.
    Webster, J., Watson, R.T.: Analyzing the past to prepare for the future: writing a literature review. MIS Q. 26, xiii–xxiii (2002)Google Scholar
  22. 22.
    AIS: Senior Scholars’ Basket of Journals.
  23. 23.
    Sørensen, C., Landau, J.S.: Academic agility in digital innovation research. J. Strateg. Inf. Syst. 24, 158–170 (2015)CrossRefGoogle Scholar
  24. 24.
    Downe-Wamboldt, B.: Content analysis- method, applications, and issues. Health Care Women Int. 13, 313–321 (1992)CrossRefGoogle Scholar
  25. 25.
    Hsieh, H., Shannon, S.E.: Three approaches to qualitative content analysis. Qual. Health Res. 15, 1277–1288 (2005)CrossRefGoogle Scholar
  26. 26.
    Lowry, P.B., Cao, J., Everard, A.: Privacy concerns versus desire for interpersonal awareness in driving the use of self-disclosure technologies: the case of instant messaging in two cultures. J. Manag. Inf. Syst. 27, 163–200 (2011)CrossRefGoogle Scholar
  27. 27.
    Krasnova, H., Veltri, F.N., Günther, P.O.: Self-disclosure and privacy calculus on social networking sites: the role of culture. Bus. Inf. Syst. Eng. 4, 127–135 (2012)CrossRefGoogle Scholar
  28. 28.
    Posey, C., Lowry, P.B., Roberts, T.L., Ellis, T.S.: Proposing the online community self-disclosure model: the case of working professionals in France and the UK who use online communities. Eur. J. Inf. Syst. 19, 181–195 (2010)CrossRefGoogle Scholar
  29. 29.
    Chen, A., Lu, Y., Chau, P.Y.K., Gupta, S.: Classifying, measuring, and predicting users’ overall active behavior on social networking sites. J. Manag. Inf. Syst. 31, 213–253 (2014)CrossRefGoogle Scholar
  30. 30.
    Richter, D., Riemer, P.D.K., vom Brocke, P.D.J.: Internet social networking research state of the art and implications for Enterprise 2.0. Bus. Inf. Syst. Eng. 53, 1–89 (2011)Google Scholar
  31. 31.
    Izquierdo-Yusta, A., Schultz, R.J.: Understanding the effect of internet convenience on intention to purchase via the internet. J. Mark. Dev. Compet. 5, 32 (2011)Google Scholar
  32. 32.
    Rao, H.K.: On risk, convenience, and internet shopping. Commun. ACM. 43, 98–105 (2000)Google Scholar
  33. 33.
    Kacen, L., Rabinovich, M.: Qualitative coding methodology. Psychoanal. Psychol. 30, 210–231 (2013)CrossRefGoogle Scholar
  34. 34.
    Chen, H., Storey, V.C., Chiang, R.H.L.: Business intelligence and analytics: from big data to big impact. MIS Q. 36, 1165–1188 (2012)Google Scholar
  35. 35.
    Dhar, P.V., Jarke, P.D.M., Laartz, D.J.: Big data. Bus. Inf. Syst. Eng. 6, 257–259 (2014)CrossRefGoogle Scholar
  36. 36.
    Zhao, X.I.A., Xue, L.: Competitive target advertising and consumer data sharing. J. Manag. Inf. Syst. 29, 189–221 (2013)CrossRefGoogle Scholar
  37. 37.
    Lee, D., Youngsok Bang, J.-H.A.: Managing consumer privacy concerns in personalization: a strategic analysis of privacy protection. MIS Q. 35, 423–444 (2011)Google Scholar
  38. 38.
    Heimbach, I., Kostyra, D.S., Hinz, O.: Marketing automation. Bus. Inf. Syst. Eng. 57, 129–133 (2015)CrossRefGoogle Scholar
  39. 39.
    Pavlou, P.A.: State of the information privacy literature: where are we now and where should we go? MIS Q. 35, 977–988 (2011)Google Scholar
  40. 40.
    Bruns, A., Neuberger, C., Stieglitz, S., Dang-Xuan, L.: Social media analytics: an interdisciplinary approach and its implications for information systems. Bus. Inf. Syst. Eng. 56, 89–96 (2014)Google Scholar
  41. 41.
    Hui, K.-L., Tan, B.C.Y., Goh, C.-Y.: Online information disclosure: motivators and measurements. ACM Trans. Internet Technol. 6, 415–441 (2006)CrossRefGoogle Scholar
  42. 42.
    Rosen, P., Sherman, P.: Hedonic information systems: acceptance of social networking websites, Paper 162. In: Americas Conference on Information Systems, Acapulco, Mexico (2006)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2016

Authors and Affiliations

  • Tristan Thordsen
    • 1
  • Matthias Murawski
    • 1
  • Markus Bick
    • 1
    Email author
  1. 1.ESCP Europe Business School BerlinBerlinGermany

Personalised recommendations