APPLYING EXPLANATORY FACTOR ANALYSIS TO TURKEY’S SECOND-HAND CAR MARKET

Increasing hand overs in second hand car market makes it necessary to investigate the market dynamics. Moreover, increased computer technology enables collecting huge datasets. The purpose of this study is to decrease the number of features by applying explanatory factor analysis to a large dataset gathered with web scraping technique from Turkey’s second-hand car market. In the study, the data set of 1,5277 vehicles obtained from the second-hand market were combined with the web scraping technique. For each car, the following variables are available: motor power, maximum speed and whether there is an mp3 player, cassette player or cd player as well as the information whether the car has original, painted or changed parts. The 11 features transformed to 4 new features after applying factor analysis and these factors explains the variation at 62,423% degree. Cronbach Alpha reliability values are computed, and the lowest coefficient is calculated as 0,571. As a result, it is understood that, the similar features are combined in the same factor