Second-Hand Automobile Selection with Grey Relational Analysis in A High-Volume Dataset

Mehmet ÖZÇALICI, Mahmut YARDIMCIOĞLU, Yücel AYRIÇAY

Abstract


Automobiles make human life easier. For this reason, the demand for the automobiles are increasing day by day. Firms operating in the industry are launching automobiles which has characteristics in a rich diversity. Automobiles purchased as first-hand are sold in second-hand market after a certain period of use. Therefore, customers who want to buy automobiles from second-hand car market must choose from a wide range of alternatives. Moreover, the features that customers seek in second hand automobiles are different from each other. In this case, a technique is needed to match the customer needs with the second-hand vehicles offered for sale. In the literature, different decision making techniques for automobile selection problem have been emphasized, but it has been determined that the selection process is limited by a few alternatives. For this study, a high-volume data set containing data belong to 248450 automobiles was collected with web scraping technique. Grey Relational Analysis (GRA) is used to analyze the alternatives. Grey Relational Analysis is a member of the Grey System Theory family that deals with situations where insufficient information available. The purposed model applied through interviews with three customers. The customers determined 8, 6 and 7 criteria respectively considering their needs. Calculations are performed in MATLAB platform. The method presented in the study can be used as a practical decision support system for customers and those who deal with second hand vehicle sales.


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