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Using “Yams” for Enterprise Knowledge Sharing among Knowledge Workers from the Perspective of a Task Categorisation-Knowledge Sharing Systems Fit

  • Tong-Ming Lim
  • Angela Siew-Hoong Lee
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 444)

Abstract

Emerging digital technologies play a key role in the development of enterprises. Their uses demand a transition on the part of knowledge workers, however. Web 2.0 is an emerging communication technology that supports collaborative knowledge sharing in corporate learning paradigms, changing tailor-made, expensive and high learning curve digital systems to simple but well-accepted ones [1, 2]. These platforms revolutionise how participants share, communicate and create knowledge in a corporate setting [3]. The use of Web 2.0 to support Knowledge Sharing (KS) has been extensively investigated [4, 5]. Studies that use a task-technology fit model on systems such as decision support [6] and eLearning [7] demonstrate that a good fit between tasks and digital technologies is able to improve performance of knowledge workers. This research reports the outcomes on the fit between task categorization and knowledge sharing systems. The task categories and Web 2.0 functions used in knowledge sharing practices were consistent. The outcomes highlighted that intuitive design, ease of use and a low learning curve were able to elicit both tacit and explicit organizational knowledge. Text analysis demonstrated that new knowledge was created, exchanged and shared. The study concluded that knowledge sharing activity and the fit between Web 2.0 functions and task categories were consistent and significant.

Keywords

Knowledge sharing task categorization knowledge sharing systems text mining Web 2.0 

References

  1. 1.
    Smith, G.: Social Networking and the Transfer of Knowledge. The Electronic Journal of Knowledge Management 7(1), 165–178 (2009)Google Scholar
  2. 2.
    Yamamoto, S., Kanbe, M.: Knowledge Creation by Enterprise SNS. The International Journal of Knowledge, Culture And Change Management 8(1), 1–14 (2008)CrossRefGoogle Scholar
  3. 3.
    Yang, S.J.H., Chen, I.Y.L.: A social network-based system for supporting interactive collaboration in knowledge sharing over peer-to-peer network. International Journal of Human-Computer Studies 66, 36–50 (2008)CrossRefGoogle Scholar
  4. 4.
    Kaiser, S., Müller-Seitz, G., Lopes, M.P., Cunha, M.P.: Weblog-Technology as a Trigger to Elicit Passion for Knowledge. Organization 14(3), 391–412 (2007)CrossRefGoogle Scholar
  5. 5.
    Kim, H.N.: The phenomenon of blogs and theoretical model of blog use in educational contexts. Computers & Education 51, 1342–1352 (2008)CrossRefGoogle Scholar
  6. 6.
    Gu, L., Wang, J.: A Study of Exploring the “Big Five" and Task Technology Fit in Web-based Decision Support Systems. Issues in Information Systems, X(2), 210–217 (2009)Google Scholar
  7. 7.
    Klopping, I.M., McKinney, E.: Extending the Technology Acceptance Model and The Task-Technology Fit Model To Consumer E-Commerce. Information Technology, Learning, and Performance Journal 22(1), 35–48 (2004)Google Scholar
  8. 8.
    Du, H.S., Wagner, C.: Learning with Weblogs: An Empirical Investigation. In: Proceedings of the 38th Annual Hawaii International Conference on System Sciences (2005)Google Scholar
  9. 9.
    Alejandro, C.S., Urena, J.D.F., Sanchez, R.C., Gutierrez, J.A.C.: Knowledge Construction Through ICT’s: Social Networks. In: World Conference on Educational Multimedia, Hypermedia & Telecommunication, vol. 1-9, pp. 2330–2337 (2008)Google Scholar
  10. 10.
    Coakes, E.: Storing and sharing knowledge, supporting the management of knowledge made explicit in transnational organizations. The Learning Organization 13(6), 579–593 (2006)CrossRefGoogle Scholar
  11. 11.
    Bausch, P., Haughey, M., Hourihan, M.: We Blog: Publishing Online with Weblogs. Wiley Publishing, Indianapolis (2002)Google Scholar
  12. 12.
    Zhong, N., Li, Y., Wu, S.-T.: Effective Pattern Discovery for Text Mining. IEEE Transactions on Knowledge and Data Engineering 24(1), 30–44 (2012)CrossRefGoogle Scholar
  13. 13.
    Mailvaganam, H.: Evolution of Analysis – Microsoft’s NetScan and Project Aura (2005), http://www.dwreview.com/Data_mining/Microsoft_netscan.html (retrieved June 3, 2011)
  14. 14.
    Marylene, G.: A Model of Knowledge-Sharing Motivation. Human Resource Management 48(4), 571–589 (2009)CrossRefGoogle Scholar
  15. 15.
    Palmisano, J.: A Motivational Model of Knowledge Sharing. Handbook on Decision Support Systems 1, 355–370 (2008)CrossRefGoogle Scholar
  16. 16.
    Zigurs, I., Buckland, B.K.: A Theory of Task/Technology Fit and Group Support Systems Effectiveness. MIS Quarterly 22(3), 313–329 (1998)CrossRefGoogle Scholar
  17. 17.
    Hsu, C.L., Lin, J.C.C.: Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & Management 45, 65–74 (2008)CrossRefGoogle Scholar
  18. 18.
    Fun, I.P., Wagner, R.K., Weblogging, C.: A study of social computing and its impact on organizations. Decision Support Systems 45, 242–250 (2008)CrossRefGoogle Scholar
  19. 19.
    Kaiser, S., Kansy, S., Mueller-Seitz, G., Ringlstetter, M.: Weblogs for organizational knowledge sharing and creation: A comparative case study. Knowledge Management Research & Practice, 120–130 (2008)Google Scholar
  20. 20.
    Ras, E., Avram, G., Waterson, P., Weibelzahi, S.: Using Weblogs for Knowledge Sharing and Learning in Information Spaces. Journal of Universal Computer Science 11(3), 394–409 (2005)Google Scholar
  21. 21.
    Yu, T.-K., Lu, L.-C., Liu, T.-F.: Exploring factors that influence knowledge sharing behavior via weblogs. Computers in Human Behavior 26, 32–41 (2010)CrossRefGoogle Scholar
  22. 22.
    Maruping, L.M., Agarwal, R.: Managing Team Interpersonal Processes Through Technology: A Task-Technology Fit Perspective. Journal of Applied Psychology 89(6), 975–990 (2004)CrossRefGoogle Scholar
  23. 23.
    Goodhue, D.L.: Development and Measurement Validity of a Task-Technology Fit Instrument for User Evaluations of Information System. Decision Sciences 29(1), 105–138 (1998)CrossRefGoogle Scholar
  24. 24.
    Nauman, S., Suku, S.: Adoption of Twitter in higher education – a pilot study. In: Proceedings Ascilite 2011, Hobart, TAS, pp. 1115–1120 (2011)Google Scholar
  25. 25.
    Davis, F.: Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly 13(3), 319–339 (1989)CrossRefGoogle Scholar
  26. 26.
    Chelmis, C., Prasanna, V.K.: An empirical analysis of microblogging behavior in the enterprise. Social Networking Analysis Mining 3(3), 611–633 (2013)CrossRefGoogle Scholar
  27. 27.
    Riemer, K., Richter, A.: Tweet Inside: Microblogging in a Corporate Context. In: 23rd Bled eConference eTrust, Implications for the Individual, Enterprises and Society, pp. 1–17 (2010)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2014

Authors and Affiliations

  • Tong-Ming Lim
    • 1
  • Angela Siew-Hoong Lee
    • 1
  1. 1.Sunway UniversityBandar SunwayMalaysia

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