Investigation of supplier selection problem with four dimensional kemira-m method

Nowadays, in order to maintain their wellbeing in the industry, firms are required to enhance their efficiency of production. Vendor selection is also a sub requirement for firms in different industries to be developed further to provide better efficiency. As a result firms are in persuade of the best procedure for the vendor selection process with evaluating all possible risks. In order to avoid vendor based problems globally many firms are in persuade of the best procedure for the vendor selection process which evaluates multiple vendor candidates based on multiple performance criterion to find the best fit from all vendors in certain positions. Therefore subject to the matter vendor selection process is a multiple-criteria decision making (MCDM) process. Consequently in the literature many different studies can be found on MCDM based vendor selection processes. In this study amongst all MCDM methods a new model is proposed for vendor selection with using 4 different criteria groups all of which to be used by Modified Kemeny Median Indicator Ranks Accordance (KEMIRA-M) method with using three different ranking based criteria weighting methods to evaluate vendors. In the process of research MATLAB has been used to describe the method to all firms who are willing to implement the proposed model in their structure. Related to KEMIRA-M after the literature review it is interpreted that KEMIRA-M has only been used to analyze data which is collected in maximum of two groups of criteria groups. It is also observed that there is not any studies examining vendor selection problem to provide a model with using KEMIRA-M. It is considered that with providing a new approach to vendor selection process, enhancing KEMIRA-M to be operated up to 4 different groups of data and including a systematic weighting procedure, this study claims to be original. KEYWORDS: KEMIRA-M, Multiple-criteria decision making (MCDM), Ranking based criteria weighting, Vendor Selection, MATLAB.