Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/7295
Title: A fuzzy logic model for benchmarking the knowledge management performance of construction firms
Authors: Kale, Serdar
Karaman, Erkan A.
Keywords: Knowledge management
Fuzzy logic model
Performance evaluation
Benchmarking
Construction firm
Publisher: NRC Research Press
Source: Kale, S. and Karaman, E. A. (2011). A fuzzy logic model for benchmarking the knowledge management performance of construction firms. Canadian Journal of Civil Engineering, 38(4), 464-475. doi:10.1139/L11-019
Abstract: Knowledge management is rapidly becoming a key organizational capability for creating competitive advantage in the construction industry. The emergence of knowledge management in this capacity poses enormous challenges to executives of construction firms. This paper proposes a model for benchmarking the knowledge management performance of construction firms that can guide and assist construction business executives in meeting these challenges. The proposed model incorporates benchmarking and knowledge management concepts with fuzzy set theory to adequately handle imprecision, vagueness, and uncertainty that prevail in this process. It uses the fuzzy-weighted average (FWA) algorithm to evaluate the knowledge management performance of construction firms. It is an internal reporting model that can provide powerful diagnostic information to executives of construction firms by evaluating their firm's knowledge management performance, identifying their firm's strengths and weaknesses with regard to each knowledge management practice, and setting priorities for managerial actions related to knowledge management practices that need improvement. A real-world case study is presented to illustrate the implementation and utility of the proposed model.
URI: http://doi.org/10.1139/L11-019
https://hdl.handle.net/11147/7295
ISSN: 0315-1468
Appears in Collections:Architecture / Mimarlık
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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