An Online Reference Pricing System Using Business Analytics: The Case of a Rent-a-Car Company

Abstract

The Internet enables businesses to acquire a great deal of reference information, including the price in the open markets, for estimating appropriate prices of the assets to sell off. However, companies may be unsure whether this information is useful for their pricing strategies. In particular, what is the value of reference price information to a company in the market and how can the company make use of this information? Using a multiple regression model for price estimation applied to used cars for a rent-a-car company, we propose a framework to collect the reference price information, in order to estimate appropriate prices in the future. In this process, we identify factors that affect the estimated prices. The result is a new information system that collects online reference price information and provides very accurate information in estimating future prices of used cars and rental prices resulting from the estimation.