Humboldt-Universität zu Berlin - High Dimensional Nonstationary Time Series

IRTG1792DP2018 065

Price Management in the Used-Car Market: An Evaluation of Survival Analysis

Alexander Born
Nikoleta Kovachka
Stefan Lessmann
Hsin-Vonn Seow

Second-hand car markets contribute to billions of Euro turnover each year but
hardly generate profit for used car dealers. The paper examines the potential of
sophisticated data-driven pricing systems to enhance supplier-side decision-
making and escape the zero-profit-trap. Profit maximization requires an accurate
understanding of demand. The paper identifies factors that characterize consumer
demand and proposes a framework to estimate demand functions using survival
analysis. Empirical analysis of a large data set of daily used car sales between
2008 to 2012 confirm the merit of the new factors. Observed results also show
the value of survival analysis to explain and predict demand. Random survival
forest emerges as the most suitable vehicle to develop price response functions
as input for a dynamic pricing system.

Automotive Industry, Price Optimization, Survival Analysis, Dynamic Pricing

JEL Classification: