In this paper various ensemble learning methods from machine learning and statistics are considered and applied to the customer choice modeling problem. The application of ensemble learning usually improves the prediction quality of flexible models like decision trees and thus leads to improved...

Hedonic pricing models attempt to model a relationship between object attributes and the object's price. Traditional hedonic pricing models are often parametric models that suffer from misspecification. In this paper we create these models by means of boosted CART models. The method is explained...

Firms increasingly view each contact with their customers as an opportunity that needs to be managed. The primary purpose of this article is to gain a better understanding of the customers’ post-complaint period. Specific focus is placed on the impact of effective complaint handling on actual...

In high-dimensional data, one often seeks a few interesting low-dimensional projections that reveal important features of the data. Projection pursuit is a procedure for searching high-dimensional data for interesting low-dimensional projections via the optimization of a criterion function...

In high-dimensional data, one often seeks a few interesting low-dimensional projections that reveal important features of the data. Projection pursuit is a procedure for searching high-dimensional data for interesting low-dimensional projections via the optimization of a criterion function...