フリマ利用者の購買意欲に影響を与える出品データの特徴分析

抄録

To extract features of the listing data for purchasing motivation of potential buyers, we focused not only on textual information but also on product images. The target of this study was shoes and we performed a predictive analysis using XGBoost with 1,000 items of past listing data. The dependent variable was whether the item was sold or not, and the explanatory variables were 17 features extracted from the basic information of the item, the characteristics of the item description, and the characteristics of the item image. The results were showed that it was important for preparing item images to have a large number of item images, to use a single background color and to photograph shoes at a 45-degree angle. The results of a questionnaire survey with 240 people revealed that the listing information reflecting the extracted characteristics enhance the purchasing motivation of infrequent users of flea market apps.