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This thesis develops methodological approaches to extend the service spectrum of price comparison websites for electronic consumer goods with respect to the determination of the optimal purchase time point. The central decision criterion of price comparison sites’ customers is the (expected) minimum price.
This paper therefore focuses on the prediction of minimum prices and therefrom derived events and answers three questions that set the stage for extending services of price comparison sites:
1. How long do is the expected waiting time to buy our desired product for a set budget or desired price?
2. When should a customer buy so that s/he pays the lowest price within a short, predefined decision horizon?
3. How can a price comparison site make price predictions for a large, heterogeneous set of products over different horizons, and what are the best methods for doing so?
The database used for the analysis results from the specific requirements of the study context. While the first two papers focus on a subset of electronic consumer goods - smartphones - to demonstrate the application of the developed methodology, the third paper addresses the challenges of price prediction for the heterogeneous product landscape on price comparison sites and therefore includes multiple product categories in the analysis.