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Revenue management has been successfully applied to service-oriented industries for a long time. In the more recent past, besides these classical application areas, it has been introduced to other production and logistics processes as well. For the automobile industry so far, only a few revenue managementmodels have been developed but practically none for its used car sector. Being a sector with suitable prerequisites and a low pro?t margin, this is a promising application area for price-based revenue management. As used cars are "individual" and "durable" goods - unlike seat or room bookings -, a different approach is necessary with "dynamic pricing" as the main control strategy. A somewhat similar problem can only be found in the real estate sector. Thus, a conceptual framework of an appropriate revenue management model based on dynamic pricing must be developed. Using current and historical m- ket data, the price-responsefunctionhas to be estimated which then can serve as the basis for determining the optimal dynamic pricing strategy. For two central components of this framework, optimization and estimation, - novative approaches are proposed. Based on results from Control Theory, different possible models are suggested and extensively evaluated. Finally, a stochastic discrete-time model is identi?ed as themost appropriate.Withthis, it is possible todevelopiterativealgorithmsto det- mine the optimal pricing strategy even for problems without closed-form solution.
Sommario
From the contents:
Revenue management and the automobile industry; Modeling the price-based revenue management problem; Survival analysis: estimation of the price-response function; Validation of the survival analysis approach; Computational analysis: proof of concept
Info autore
Dr. André Jerenz promovierte extern bei Prof. Dr. Ulrich Tüshaus am Lehrstuhl Operations Research an der Universität der Bundeswehr, Hamburg. Er ist als Offizier im Bundesamt für Informationsmanagement und Informationstechnik der Bundeswehr in Koblenz tätig.
Riassunto
Today, the automobile industry is faced by increasing price competition while profit margins are shrinking. The used car sector is affected the most, amplified by excess supply in day registrations and the impact of the continuing rebate war in the new car sector.
André Jerenz develops a price-based revenue management framework to support retailers in establishing better and more profitable pricing strategies, including assigning an initial asking price and the adjustment of price over time. For the profit maximization problem of a used car retailer, the author derives different algorithms for determining optimal strategies by applying stochastic control theory. Within the scope of the demand forecasting component, he proposes the adoption of survival analysis for estimating individual price response functions, modeled by parametric and semi-parametric survival functions. Thus, the effects of variables such as the asking price are taken into account. The evaluation of data from a case study in the German used car market reveals a significant potential for an increase in profitability and confirms the proposed price-based revenue management concept.
