Using the fuzzy multi-criteria decision making approach for measuring the possibility of successful knowledge management
This study develops a forecasting framework based on the fuzzy multi-criteria decision making (FMCDM) approach to help organizations build awareness of the critical influential factors on the success of knowledge management (KM) implementation, measure the success possibility of knowledge management projects, as well as identify the necessary actions prior to embarking on conducting knowledge management. Subjectivity, uncertainty and vagueness within the prediction process are dealt with using linguistic variables parameterized by triangular fuzzy numbers. By multiplying the importance weights of influential factors and the possible rating of success (failure), predicted success (failure) values are determined to enable organizations to decide whether to initiate knowledge management, inhibit adoption or undertake remedial improvements to increase the possibility of successful knowledge management project. The proposed approach is demonstrated using a real case involving a Taiwanese semiconductor engineering corporation.
multi-criteria decision making knowledge management prediction linguistic variables triangular fuzzy numbers fuzzy sets theory