Proposing a hybrid fuzzy model to consider knowledge management challenges in supply chain: Case study

Abstract

The steel industry is considered the second most vital industry in Iran after oil and petrochemical industry. Correspondingly, KM implementation is encountered with challenges and obstacles leading to cost enhancement and resources annihilation. This study aims at reducing the uncertainty made by expert judgments in the procedure of KM implementation using linguistic degrees. In this paper, a fuzzy theory is used to decrease the linguistic inaccuracy and the vagueness of human judgment. Firstly, challenges of KM were identified in the literature. Then, challenges corresponding to steel industry SC were finalised, short-listed and merged by expert judgment through Delphi fuzzy method. Also, new solutions were proposed by experts to cope with KM challenges. Afterwards, the fuzzy analytical hierarchy process (FAHP) is exploited to rank and weight determination of challenges and solutions. Using the fuzzy inference system (FIS) for improving KM implementation and managing the challenges is the next stage.