KNOWLEDGE FLOW NETWORKS AND COMMUNITIES OF PRACTICE FOR KNOWLEDGE MANAGEMENT

Rajiv Khosla, Mei-Tai Chu, K. G. Yamada, S. Doi, K. Kuneida and S. Oga
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Rajiv Khosla: Research Centre for Computers, Communication and Social Innovation, School of Management, La Trobe University, Melbourne, Vic 3086, Australia
Mei-Tai Chu: Research Centre for Computers, Communication and Social Innovation, School of Management, La Trobe University, Melbourne, Vic 3086, Australia
K. G. Yamada: C&C Innovation Res. Labs, NEC Corporation, 8916-47 Takayama-cho, Ikoma-Shi, Nara, 630-0101, Japan
S. Doi: C&C Innovation Res. Labs, NEC Corporation, 8916-47 Takayama-cho, Ikoma-Shi, Nara, 630-0101, Japan
K. Kuneida: C&C Innovation Res. Labs, NEC Corporation, 8916-47 Takayama-cho, Ikoma-Shi, Nara, 630-0101, Japan
S. Oga: C&C Innovation Res. Labs, NEC Corporation, 8916-47 Takayama-cho, Ikoma-Shi, Nara, 630-0101, Japan

Chapter 2 in Managing Knowledge for Global and Collaborative Innovations, 2009, pp 15-25 from World Scientific Publishing Co. Pte. Ltd.

Abstract: AbstractThis research discusses KFNs in the context of Communities of Practice (CoPs) and Knowledge Management (KM). KFNs unlike workflow can often transcend organizational boundaries and are distinct and different than workflow models. CoPs involve both personal and organizational aspects, and are an iteration of the transmission between explicit and tacit knowledge. This research develops, implements, and analyzes a CoPs Centered KFNs model in a multinational organization. The CoPs Centered KFNs model is underpinned in a CoPs model built around four organization performance evaluation dimensions and sixteen criteria. Many criteria and comprehensive segments should be taken into consideration while establishing CoPs model, this explains why this research employs fuzzy multi-criteria decision making. The cluster analysis techniques are used for evaluation of the CoPs Centered KFN model. The result of attribute analysis via KFNs model has been designed to determine the characteristic of each cluster and identify suggestions for effective linkage among knowledge workers.

Keywords: Management; Collaboration; Innovation; Knowledge Sharing (search for similar items in EconPapers)
Date: 2009
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