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    Digital Supplier Selection for a Garment Business Using Interval Type-2 Fuzzy TOPSIS
    (Ege Univ, 2020) Ozbek, Ahmet; Yıldız, Aytaç
    The aim of this study was to use the interval type-2 fuzzy TOPSIS method to select the best supplier among a number of suppliers digitized by Industry 4.0 for a company operating in the garment industry. The interval type-2 fuzzy TOPSIS method involves an interval of type-2 fuzzy sets and can model uncertainties very well to solve fuzzy multi-criteria decision making problems. Alternatives were listed based on closeness indexes, and the best digital supplier was selected based on sensitivity analysis. This is the first study to use the model in question to select the best digital supplier for a company. We, therefore, believe that it will contribute to the literature. It is recommended that the model in question be used in other industries as well.
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    SELECTION OF SOCKS EXPORT MARKETS FOR TURKEY USING MULTI-CRITERIA DECISION MAKING METHODS
    (Yildiz Technical Univ, 2020) Yıldız, Aytaç; Ozbek, Ahmet
    Export provides foreign exchange inflow and reduces unemployment and is, therefore, an important field of economic activity promoted by every country. Turkey is the sixth-largest exporter in the socks industry, which is a strategic export product. In this context, it wants to take first place by increasing its export volume. For this, it must choose the markets which will export well. However, there are many criteria that are effective in selecting the export market place and are independent of exporting countries. It is beneficial to use multi-criteria decision-making (MCDM) methods in the solution of such problems. The aim of this study is to select the most suitable export market to increase Turkey's socks export volume. Firstly, a survey of export market selection criteria is developed based on a literature review. The survey is completed by export specialists of socks exporting companies in Turkey to determine the most important criteria in the selection of socks export markets. Afterward, between 2014-2018 criterion data of the top 11 countries accounting for 70 percent of the world's total socks imports are derived from the Trade Map Database. 2020 values were obtained using regression analysis. TOPSIS (Technique for Order-Preference by Similarity to Ideal Solution), GRA (Grey Relational Analysis) and ANP (Analytical Network Process) methods are used to evaluate the alternative socks export markets. Sensitivity analysis is performed using TOPSIS, GRA and ANP data. The results are compared to select the best export market for the Turkish socks industry.