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https://hdl.handle.net/11499/56035
Title: | A Novel Combined Fuzzy MCDM Approach Based on IMF-SWARA and F-CODAS for Consulting Firm Selection | Authors: | Kundakçı, Nilsen Arman, Kevser |
Keywords: | Fuzzy Multi Criteria Decision Making IMF-SWARA F-CODAS Consulting Firm Selection Group Decision-Making Topsis Criteria |
Publisher: | Ege Univ, Fac Economics & Admin Sciences | Abstract: | In today's challenging industry conditions, where being good is not enough to be successful, companies trying to be the best need consultancy in different fields. Consulting firms provide consultancy services to businesses, and they need to determine the most appropriate one for them. Fuzzy MCDM (Multi Criteria Decision Making) methods are appropriate to solve consulting firm selection problem. In this study, consulting firm selection problem of a textile company operating in Istanbul, Turkey is introduced by using a novel combined fuzzy MCDM method based on IMF-SWARA (Improved Fuzzy Stepwise Weight Assessment Ratio Analysis) and F-CODAS (Fuzzy COmbinative Distance-based Assessment) methods. The importance weights of the criteria are calculated with IMF-SWARA method. Findings indicate that the top three important criteria are experience, references, and reliability, respectively. Then, F-CODAS method is used to rank the consulting firms and the best one is presented to the Human Resources (HR) department of the textile company. This study contributes to the existing literature in various aspects. It suggests a novel combined fuzzy MCDM method to solve consulting firm selection and a new Fuzzy CODAS based on Triangular Fuzzy Numbers (TFNs) is proposed. Moreover, HR managers can use the findings of this study to evaluate consulting firms. | URI: | http://dx.doi.org/10.21121/eab.1214630 https://hdl.handle.net/11499/56035 |
ISSN: | 1303-099X |
Appears in Collections: | İktisadi ve İdari Bilimler Fakültesi Koleksiyonu TR Dizin İndeksli Yayınlar Koleksiyonu / TR Dizin Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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document - 2024-04-03T102912.580.pdf | 1.21 MB | Adobe PDF | View/Open |
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