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Stochastic dynamic multi-product pricing with dynamic advertising and adoption effects

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  • Rainer Schlosser

    (Hasso Plattner Institute, University of Potsdam)

Abstract

In this article we analyze stochastic dynamic multi-product pricing models for the sale of durable goods. In addition, we consider a single advertising channel to promote all types of products. We also include product-specific unit costs, inventory holding costs as well as general adoption and saturation effects in the demand. For the case of isoelastic, exponential and linear demand, we derive solution formulas for the expected profit, the optimal prices of all types of products, and the optimal advertising rate. Efficient simulation techniques are used to evaluate optimally controlled sales processes over time. Moreover, for the case of exponential demand, we demonstrate how to include constant absolute risk aversion in the model.

Suggested Citation

  • Rainer Schlosser, 2016. "Stochastic dynamic multi-product pricing with dynamic advertising and adoption effects," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(2), pages 153-169, April.
    • Handle: RePEc:pal:jorapm:v:15:y:2016:i:2:d:10.1057_rpm.2015.28
    DOI: 10.1057/rpm.2015.28
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    Cited by:

    1. Schlosser, Rainer & Gönsch, Jochen, 2023. "Risk-averse dynamic pricing using mean-semivariance optimization," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1151-1163.
    2. Sen Lin & Bo Li & Antonio Arreola-Risa & Yiwei Huang, 2023. "Optimizing a single-product production-inventory system under constant absolute risk aversion," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(3), pages 510-537, October.
    3. R. Schlosser, 2021. "Scalable relaxation techniques to solve stochastic dynamic multi-product pricing problems with substitution effects," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(1), pages 54-65, February.
    4. Gönsch, Jochen, 2017. "A survey on risk-averse and robust revenue management," European Journal of Operational Research, Elsevier, vol. 263(2), pages 337-348.
    5. Jochen Gönsch & Michael Hassler & Rouven Schur, 2018. "Optimizing conditional value-at-risk in dynamic pricing," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(3), pages 711-750, July.

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