A fuzzy AHP-TOPSIS framework for ranking the solutions of Knowledge Management adoption in Supply Chain to overcome its barriers |
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Affiliation: | 1. School of IOT Engineering, Jiangnan University, Wuxi 214122, China;2. Department of Electronics and Information Engineering, Chonbuk National University, Jeonju, Jeonbuk 561756, Republic of Korea;1. Fraunhofer INT, Appelsgarten 2, D-53879 Euskirchen, Germany;2. Ghent University, Faculty of Economics and Business Administration, Tweekerkenstraat 2, B-9000 Gent, Belgium;1. College of Biomedical Engineering and Instrument Science, Zhejiang University, 310008 Zhou Yiqing Building 510, Zheda road 38#, Hangzhou, Zhejiang, China;2. Department of Information and Communication Engineering, University of Murcia, Spain;1. Innovative Information Industry Research Center, School of Computer Science and Technology, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China;2. Information and Communications Research Laboratories, ITRI, Hsinchu, Taiwan, ROC;3. CyLab, Carnegie Mellon University, Pittsburgh, USA;4. Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan, ROC |
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Abstract: | The aim of this study is to identify and prioritize the solutions of Knowledge Management (KM) adoption in Supply Chain (SC) to overcome its barriers. It helps organizations to concentrate on high rank solutions and develop strategies to implement them on priority. This paper proposes a framework based on fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to identify and rank the solutions of KM adoption in SC and overcome its barriers. The AHP is used to determine weights of the barriers as criteria, and fuzzy TOPSIS method is used to obtain final ranking of the solutions of KM adoption in SC. The empirical case study analysis of an Indian hydraulic valve manufacturing organization is conducted to illustrate the use of the proposed framework for ranking the solutions of KM adoption in SC to overcome its barriers. This proposed framework provides a more accurate, effective and systematic decision support tool for stepwise implementation of the solutions of KM adoption in SC to increase its success rate. |
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Keywords: | Knowledge Management Supply Chain AHP TOPSIS |
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