S-Space College of Engineering/Engineering Practice School (공과대학/대학원) Dept. of Architecture and Architectural Engineering (건축학과) Journal Papers (저널논문_건축학과)
CONSTRUCTION KNOWLEDGE EVALUATION USING EXPERT INDEX
- Park, Moonseo; Lee, Hyun-Soo; Kwon, Soonseok
- Issue Date
- VILNIUS GEDIMINAS TECH UNIV
- JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT; Vol.16, No.3, pp.401-411
- While the current global economy can be characterized by the intensification of business competitiveness, leaner organizations, the convergence of products and services, and by vast technological developments, the risks and uncertainties inherent in such a dynamic environment make the management of organizational knowledge even more crucial. Indeed, previous theoretical and empirical-based studies have proven that knowledge leads to organizational success. Knowledge Management (KM) has particularly gained credence, and continues to generate interest, in academic and business circles. KM is of especial interest to project-based industries such as construction, as the effective management of knowledge is critical to the survival and continued advancement of a company. In fact, in the construction industry, the implementation of a knowledge management system (KMS) is currently being considered, and an increasing number of companies have already proposed knowledge management initiatives. However, quality of information must take precedence over quantity, especially in the developmental phases of this KMS. Therefore, how to filter and accurately evaluate quantitative and qualitative data becomes a significant challenge. Yet, thus far, only a few studies examining the improvement of knowledge evaluation have been conducted and that researches only focus on the evaluation methods. This research addresses these issues by focusing on knowledge management and evaluation and by specifically addressing how to evaluate knowledge effectively. Based on the Active Knowledge Management, this study proposes a process model for effectual construction knowledge evaluation using Expert Index (EI). EI is the level of specialty workers achieve in a certain field after engaging in a knowledge activity. The proposed model will not only enable precise evaluation, but will also provide stimulating knowledge activities; thus, if practically applied, this model could enhance actual organizational success.
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