A Web based Decision Support System for Used Car Pricing

Abstract

Used-car trade has a significant portion in overall automobile market and determining the values of the cars is an important problem. This study proposes a new methodology for determining the market value of the used-cars by observing the classifieds in an e-commerce site. This type of data acquisition plays an important role to build pricing models and to conduct further analysis in our approach. In data acquisition stage, a set of new listings are chosen randomly each day from an ecommerce site (a web site like Craigslist), then these listings are observed until a predetermined period (e.g. thirty days) or delisting time, whichever comes first. The crucial part of our approach is the assumption of a sale event when the listing is no longer available i.e. delisted from the e-commerce site. The proposed methodology may potentially be used for pricing any used item based on the web listings. A web site was developed to help clients/users for determining the market values of their cars as a decision support tool that can assess the likelihood of selling a particular car at a certain price. We also presented the applicability of predictive models to determine the likelihood of selling a car within thirty day period based on the price set by the owner.