DocumentCode
1362104
Title
Determinants of Knowledge Management Assimilation: An Empirical Investigation
Author
Lee, Jae-Nam ; Choi, Byounggu
Author_Institution
Bus. Sch., Korea Univ., Seoul, South Korea
Volume
57
Issue
3
fYear
2010
Firstpage
430
Lastpage
449
Abstract
Knowledge management (KM) and its effective assimilation as an interrelated innovation are critical to the success of contemporary organizations, and have recently attracted increasing interest. The sources of influence on successful KM assimilation were explored via a study of Korean firms. A synthesis of previous studies that had utilized various theories to investigate KM variables yields six critical factors (i.e., knowledge worker, technical knowledge infrastructure, external knowledge linkage, knowledge strategy, internal knowledge climate, and knowledge management process), which facilitate KM assimilation. We then evaluated the effects of these critical factors on the level of KM assimilation, using responses from 187 Korean organizations that had already implemented enterprise-wide KM systems. Our findings show that four of the six variables were significantly related to KM assimilation. Interestingly, the KM process was found to be the most critical factor in the proliferation of KM activities across an organization, and knowledge strategy and external knowledge linkage were identified as insignificant ones for KM assimilation. The findings of this paper are expected not only to serve as early groundwork for researchers hoping to understand KM and its effective assimilation in organizations, but also to provide practitioners with guidelines as to how they can enhance their KM assimilation level, thus improving their organizational performance.
Keywords
innovation management; knowledge management; organisational aspects; regression analysis; Korean firms; contemporary organizations; enterprise-wide KM systems; external knowledge linkage; knowledge management assimilation; knowledge strategy; organizational performance; proliferation; Assembly systems; Business; Couplings; Guidelines; Innovation management; Knowledge management; Regression analysis; Resource management; Technological innovation; Technology management; KM assimilation; Knowledge-based view; knowledge management (KM); ordinal regression analysis; resource-based view;
fLanguage
English
Journal_Title
Engineering Management, IEEE Transactions on
Publisher
ieee
ISSN
0018-9391
Type
jour
DOI
10.1109/TEM.2009.2036839
Filename
5357438
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