Skip navigation
  • Home
  • Browse
    • Communities
      & Collections
    • Browse Items by:
    • Publication Date
    • Author
    • Title
    • Subject
    • Department
  • Sign on to:
    • My MacSphere
    • Receive email
      updates
    • Edit Profile


McMaster University Home Page
  1. MacSphere
  2. Open Access Dissertations and Theses Community
  3. Open Access Dissertations and Theses
Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/15461
Title: Understanding knowledge sharing in Web 2.0 online communities: A socio-technical study
Authors: Mojdeh, Sana
Advisor: Head, Milena
Department: Business Administration
Keywords: knowledge management;knowledge sharing;online communities;Web 2.0;social bookmarking;commenting;social capital theory
Publication Date: Nov-2014
Abstract: Knowledge sharing–the dissemination of knowledge from an individual/group to another–has been an interesting topic for knowledge management scholars. Previous studies on knowledge sharing in online communities have primarily focused on communities of practice (organizational/business communities) and the social factors of knowledge sharing behaviour. However, non-business-oriented online communities have not been rigorously examined in the academic literature as venues for facilitating knowledge sharing. In addition, the burst of new age Internet tools (artifacts) such as social bookmarking has changed the face of online social networking. Within the context of Web 2.0, this socio-technical research investigation introduces both social and technical factors affecting attitude towards knowledge sharing in communities of relationship and communities of interest, and proposes a relational model of knowledge sharing attitude in Web 2.0 online communities. Social Capital Theory provides the main theoretical backbone for the proposed model. Theory of Reasoned Action (TRA) and social constructionsim have also been used. Following the description of the proposed hypotheses and research methodology using a survey about three Web 2.0 websites (Facebook, LinkedIn, and Cnet), data analysis through Partial Least Squared (PLS) method is applied to examine the effect of social and technical antecedent of knowledge sharing attitude. The R2 value of 0.78 indicates the strong explanatory power of the research model.
Rights: An error occurred on the license name.
URI: http://hdl.handle.net/11375/15461
Appears in Collections:Open Access Dissertations and Theses

Files in This Item:
File Description SizeFormat 
SanaMojdeh-Thesis07 10 2014-V19.docx
Open Access
Main article2.95 MBMicrosoft Word XMLView/Open
Show full item record Statistics


Items in MacSphere are protected by copyright, with all rights reserved, unless otherwise indicated.

Sherman Centre for Digital Scholarship     McMaster University Libraries
©2022 McMaster University, 1280 Main Street West, Hamilton, Ontario L8S 4L8 | 905-525-9140 | Contact Us | Terms of Use & Privacy Policy | Feedback

Report Accessibility Issue