Modeling the Metrics of Individual, Organizational and Technological Knowledge Sharing Barriers: An Analytical Network Process Approach

In today's knowledge-based business, knowledge is the only source of competitive advantage for engineering industries. Knowledge sharing plays an important role in the success of knowledge management (KM). Knowledge sharing barriers (KSBs) become obstacles for KM to achieve the goals of the industries. In this paper, three categories of KSBs have been identified such as individual, organizational and technological. The main purpose of this research is to measure the effectiveness of individual, organizational and technological KSBs by the application of an analytical network process (ANP) framework which helps to the managers for taking decision to enhance the successful knowledge sharing in the engineering industries. An ANP framework has been developed with the help of identified determinants, dimensions and enablers to evaluate alternatives such as individual, organizational and technological KSBs. Results indicate that the organizational KSBs have the maximum effect on knowledge sharing followed by technological and individual KSBs.

[1]  Manoj Kumar Tiwari,et al.  Modeling the metrics of lean, agile and leagile supply chain: An ANP-based approach , 2006, Eur. J. Oper. Res..

[2]  I. Nonaka,et al.  The Concept of “Ba”: Building a Foundation for Knowledge Creation , 1998 .

[3]  Kim-Leng Poh,et al.  Transportation fuels and policy for Singapore: an AHP planning approach , 1999 .

[4]  Ravi Shankar,et al.  Survey of knowledge management practices in Indian manufacturing industries , 2006, J. Knowl. Manag..

[5]  T. L. Saaty A Scaling Method for Priorities in Hierarchical Structures , 1977 .

[6]  R. Kant,et al.  Knowledge management barriers: An interpretive structural modeling approach , 2007, 2007 IEEE International Conference on Industrial Engineering and Engineering Management.

[7]  L. Argote,et al.  KNOWLEDGE TRANSFER: A BASIS FOR COMPETITIVE ADVANTAGE IN FIRMS , 2000 .

[8]  M. D. Singh,et al.  Selected knowledge management implementation issues: a sectorial analysis , 2009 .

[9]  María Teresa Lamata,et al.  Consistency in the Analytic Hierarchy Process: a New Approach , 2006, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[10]  Ravi Kant,et al.  IT-enablement of Knowledge Management: the modelling of enablers , 2008, Int. J. Internet Enterp. Manag..

[11]  Thomas L. Saaty,et al.  The Analytic Hierarchy and Analytic Network Processes for the Measurement of Intangible Criteria and for Decision-Making , 2016 .

[12]  Kwang Seok Yoon,et al.  Measuring the Influence of Expertise and Epistemic Engagement to the Practice of Knowledge Management , 2012, Int. J. Knowl. Manag..

[13]  Llandis Barratt-Pugh,et al.  Managing Knowledge: The Critical Role of Culture and Ownership as a Mediator of Systems , 2013, Int. J. Knowl. Manag..

[14]  L. Thurstone A law of comparative judgment. , 1994 .

[15]  Chanan Glezer,et al.  The Role of Knowledge Sharing in Raising the Task Innovativeness of Systems Analysts , 2012, Int. J. Knowl. Manag..

[16]  R. Ruggles The State of the Notion: Knowledge Management in Practice , 1998 .

[17]  Andreas Riege,et al.  Three-dozen knowledge-sharing barriers managers must consider , 2005, J. Knowl. Manag..

[18]  Joseph Sarkis,et al.  Analyzing organizational project alternatives for agile manufacturing processes: An analytical network approach , 1999 .

[19]  Carla O'Dell,et al.  Overcoming cultural barriers to sharing knowledge , 2001, J. Knowl. Manag..

[20]  Thomas L. Saaty,et al.  Time dependent decision-making; dynamic priorities in the AHP/ANP: Generalizing from points to functions and from real to complex variables , 2007, Math. Comput. Model..