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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 89
PROCEEDINGS OF THE SIXTH INTERNATIONAL CONFERENCE ON ENGINEERING COMPUTATIONAL TECHNOLOGY
Edited by: M. Papadrakakis and B.H.V. Topping
Paper 34

Knowledge Value Adding Model for Quantitative Performance Evaluation of the Community of Practice in a Consulting Firm

W.D. Yu1, H.H. Yao1, S.J. Liu2 and P.L. Chang2

1Institute of Construction Management, Chung Hua University, Hsinchu, Taiwan
2Department of Business and Research, CECI Engineering Consultants, Inc., Taiwan

Full Bibliographic Reference for this paper
W.D. Yu, H.H. Yao, S.J. Liu, P.L. Chang, "Knowledge Value Adding Model for Quantitative Performance Evaluation of the Community of Practice in a Consulting Firm", in M. Papadrakakis, B.H.V. Topping, (Editors), "Proceedings of the Sixth International Conference on Engineering Computational Technology", Civil-Comp Press, Stirlingshire, UK, Paper 34, 2008. doi:10.4203/ccp.89.34
Keywords: performance evaluation, knowledge management, community of practice, architect-engineering consultant.

Summary
In the past decade knowledge management (KM) received more and more attention, while the assessment of its returns is lagging behind. In other words, organizations spent a lot of effort and resources in establishing their knowledge management infrastructure, both for hardware and software, while less effort was invested to measure the results of their KM endeavours. Very little literature is found on measuring the performance of a knowledge management system (KMS) due to a key problem: lack of quantification methods for benefits resulting from a KMS. Without such quantitative models, the top management of the organization could not determine the benefits generated from a KMS, so that a decision is hard to make on how much founding should be invested and what strategies can be adopted to improve the performance of a KMS.

Previous work of the research team has quantified the benefits of a specific type for a community of practice (CoP), namely the SOS (which stands for "emergent problem solving system"), of an exanple Architect/Engineering (A/E) consulting firm. However, no method has been developed to date to quantify the performance of a generic CoP. This paper describes preliminary results from a pilot study on the knowledge value adding model (KVAM) for quantitative performance evaluation of the CoP in the case of an A/E consulting firm. The KVAM is developed based on knowledge value adding theories proposed by previous researchers. It consists of two major components: (1) the value assessment of raw knowledge and the evaluation of value added by the knowledge sharing activities; (2) the knowledge management value adding procedure. The values for raw knowledge are categorized into five levels: no value, data, information, knowledge, and wisdom. Similarly, the value adding activities are classified into five types: no-value-adding, obtaining, using, learning, and contributing. Fuzzy sets representing value functions are defined for both the raw knowledge and value-adding activities based on the assessments by domain experts of the CoPs. Five CoPs of the KMS of the example A/E firm were selected for the case study. The KM activities of the selected CoPs were monitored for a whole year (from Jan. 2006 to Dec. 2006) to collect performance data. Performance indices are established for evaluation. It is found from the case study that the KVAM provides a promising method for quantitative performance measurement of the CoP. As a result, it assists the KM manages in decision making of funding and improvement strategy planning.

The proposed KVAM described in this paper provides a first-of-its-kind quantitative measurement of the performance for a CoP. While integrated with data mining and KDD techniques, a systematic strategy planning model for improving the KMS of construction firms is proposed and developed. With such a model, not only the performance of the CoP can be improved but also the competitiveness of firm can be strengthened. It is concluded that the research has developed a systematic decision-making model based on the business intelligence of the firm, which supports the top management in various decision making processes including evaluation of the KM performance for the CoP and individuals, and the performance improvement strategy planning for the KMS.

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