E-Collaboration-Based Knowledge Refinement as a Key Success Factor for Knowledge Repository Systems
T. Rachel Chung (University of Pittsburgh, USA) and Kwangsu Cho (University of Missouri, Columbia, USA)
Copyright: © 2008
Electronic knowledge repository systems are fundamental tools for supporting knowledge management (KM) initiatives (Alavi, 2000; King, Marks, & McCoy, 2002). The KPMG Consulting Knowledge Management Research Report 2000 (KPMG, 2000) shows 61% of 423 firms surveyed in the United States and Europe have either implemented or expected to implement repository systems. A follow-up KPMG survey (KPMG, 2003) shows that more than 70% of the firms have either implemented knowledge repositories in the last 2 years or planned to implement them in the next 2 years. Compared to other IT systems for KM, repositories are one of the most widely implemented and used KM tools (KPMG, 2000).
Key Terms in this Chapter
Knowledge Source: An individual who provides content to a knowledge repository.
Knowledge User: An individual who accesses documents stored in a knowledge repository and applies the knowledge to his or her tasks.
Expertise Gap: The discrepancy between the knowledge source and user in their levels of expertise.
Decentralized Knowledge Refinement: A knowledge refinement approach that involves both experts and nonexperts in quality judgment and improvement processes.
Direct Refinement: A knowledge refinement process in which multiple participants refine and edit a codified document directly.
Indirect Refinement: A knowledge refinement process where reviewers refine the document indirectly by providing qualitative or quantitative feedback to the author.
Expert-Centralized Knowledge Refinement: A knowledge refinement approach that involves experts only in quality judgment and improvement processes.
Knowledge Refinement: The process of evaluating, analyzing and optimizing knowledge to be stored in a repository.