Investigation of factors affecting make-or-buy decisions with fuzy DEMATEL and fuzy TOPSIS methods and an application in automotive spare part industry

The reason why decision makers can not make easy decisions in make-or-buy decisions is that there are lots of main and sub-criteria that decision makers need to evaluate. At the same time these criteria require a multidisciplinary systematic that requires the interpretation of different departments. In this study, a literature research has been made for finding the factors/reasons and for the techniques/methodologies behind make-or-buy decisions. When the literature is examined, it is seen that multi-criteria decision making methods are used in the solution of these problems. After these researches, an exemplary application was made in automotive spare part industry. The weights of main and sub-criteria were determined by the Fuzzy DEMATEL method and the best alternative solution was found by the Fuzzy TOPSIS method in the application in this study. Since the interaction between the criteria is not possible to be expressed in quantitative terms, in order to determine the weight of the criteria, the DEMATEL method was expanded by fuzzy set theory and the Fuzzy DEMATEL method was used. In order to find the best solution among the alternatives of the make-or-buy decision, the TOPSIS method was expanded by fuzzy set theory to eliminate the uncertain situations caused by human judgements in the decision making process and Fuzzy TOPSIS method was used. As a result of study, the sub-criterion weights revealed by the different importance of weights which are stated by different disciplines were used to determine the alternatives of the make-or-buy decision, and a ranking was made from the best alternative to the worst alternative among the alternatives. This study has been prepared as a guide for decision makers in the "Make-or-Buy Decisions" of companies which is one of the most critical decision making issues. Keywords: Make-or-Buy Decisions, Multi-Criteria Decision Making, Supply Chain Management, Fuzzy DEMATEL, Fuzzy TOPSIS, Automotive Spare Part Industry