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Markov Models of Advertising and Pricing Decisions

Author

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  • S. Christian Albright

    (Indiana University, Bloomington, Indiana)

  • Wayne Winston

    (Indiana University, Bloomington, Indiana)

Abstract

This paper uses Markov decision analysis to study the properties of optimal advertising and pricing decisions in a dynamic, stochastic environment. We are primarily concerned with exhibiting and interpreting properties of the Markovian transition probabilities and one-period reward functions that imply that the optimal advertising levels and optimal prices always increase or always decrease as a function of the firm's market position. This is done in both non-competitive and competitive situations. In the former, total discounted reward for a single firm is the objective, whereas in the latter we use the concept of stochastic games to construct what is known as a discounted equilibrium point for two competing firms.

Suggested Citation

  • S. Christian Albright & Wayne Winston, 1979. "Markov Models of Advertising and Pricing Decisions," Operations Research, INFORMS, vol. 27(4), pages 668-681, August.
    • Handle: RePEc:inm:oropre:v:27:y:1979:i:4:p:668-681
    DOI: 10.1287/opre.27.4.668
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    Cited by:

    1. Shengqi Ye & Goker Aydin & Shanshan Hu, 2015. "Sponsored Search Marketing: Dynamic Pricing and Advertising for an Online Retailer," Management Science, INFORMS, vol. 61(6), pages 1255-1274, June.
    2. Tava Lennon Olsen & Rodney P. Parker, 2014. "On Markov Equilibria in Dynamic Inventory Competition," Operations Research, INFORMS, vol. 62(2), pages 332-344, April.

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