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Optimal pricing and advertising policies for a one-time entertainment event

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  • Jørgensen, Steffen
  • Zaccour, Georges

Abstract

We consider the problem of pricing and advertising a one-time entertainment event. Three pricing policies are characterized and contrasted, namely, dynamic price (DP), constant price (CP) and two-market price (TMP). In this last scenario, the selling season is composed of a regular price period and a last-minute price period, with the switching date between the two markets being determined endogenously.

Suggested Citation

  • Jørgensen, Steffen & Zaccour, Georges, 2019. "Optimal pricing and advertising policies for a one-time entertainment event," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 395-416.
    • Handle: RePEc:eee:dyncon:v:100:y:2019:i:c:p:395-416
    DOI: 10.1016/j.jedc.2019.01.007
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    1. Boucekkine, Raouf & Saglam, Cagri & Valléee, Thomas, 2004. "Technology Adoption Under Embodiment: A Two-Stage Optimal Control Approach," Macroeconomic Dynamics, Cambridge University Press, vol. 8(2), pages 250-271, April.
    2. Youyi Feng & Guillermo Gallego, 1995. "Optimal Starting Times for End-of-Season Sales and Optimal Stopping Times for Promotional Fares," Management Science, INFORMS, vol. 41(8), pages 1371-1391, August.
    3. Guillermo Gallego & Garrett van Ryzin, 1994. "Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons," Management Science, INFORMS, vol. 40(8), pages 999-1020, August.
    4. Léonard,Daniel & Long,Ngo van, 1992. "Optimal Control Theory and Static Optimization in Economics," Cambridge Books, Cambridge University Press, number 9780521331586, September.
    5. Huang, Jian & Leng, Mingming & Liang, Liping, 2012. "Recent developments in dynamic advertising research," European Journal of Operational Research, Elsevier, vol. 220(3), pages 591-609.
    6. Jørgensen, Steffen & Kort, Peter M. & Zaccour, Georges, 2009. "Optimal pricing and advertising policies for an entertainment event," Journal of Economic Dynamics and Control, Elsevier, vol. 33(3), pages 583-596, March.
    7. Gabriel Bitran & René Caldentey, 2003. "An Overview of Pricing Models for Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 5(3), pages 203-229, August.
    8. Helmes, Kurt L. & Schlosser, Rainer, 2013. "Dynamic advertising and pricing with constant demand elasticities," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2814-2832.
    9. Raphael Amit, 1986. "Petroleum Reservoir Exploitation: Switching from Primary to Secondary Recovery," Operations Research, INFORMS, vol. 34(4), pages 534-549, August.
    10. Raouf Boucekkine & Jacek Krawczyk & Thomas Vallée, 2011. "Environmental quality versus economic performance: A dynamic game approach," Post-Print hal-03193660, HAL.
    11. Jørgensen, Steffen & Zaccour, Georges, 2014. "A survey of game-theoretic models of cooperative advertising," European Journal of Operational Research, Elsevier, vol. 237(1), pages 1-14.
    12. Pascal COURTY, 2000. "An economic guide to ticket pricing in the entertainment industry," Discussion Papers (REL - Recherches Economiques de Louvain) 2000024, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    13. Tomiyama, Ken, 1985. "Two-stage optimal control problems and optimality conditions," Journal of Economic Dynamics and Control, Elsevier, vol. 9(3), pages 317-337, November.
    14. Stephen A. Smith & Dale D. Achabal, 1998. "Clearance Pricing and Inventory Policies for Retail Chains," Management Science, INFORMS, vol. 44(3), pages 285-300, March.
    15. Wedad Elmaghraby & P{i}nar Keskinocak, 2003. "Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions," Management Science, INFORMS, vol. 49(10), pages 1287-1309, October.
    16. Constantinos Maglaras & Joern Meissner, 2006. "Dynamic Pricing Strategies for Multiproduct Revenue Management Problems," Manufacturing & Service Operations Management, INFORMS, vol. 8(2), pages 136-148, July.
    17. Lawrence R. Weatherford & Samuel E. Bodily, 1992. "A Taxonomy and Research Overview of Perishable-Asset Revenue Management: Yield Management, Overbooking, and Pricing," Operations Research, INFORMS, vol. 40(5), pages 831-844, October.
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    More about this item

    Keywords

    Entertainment; Advertising; Pricing; Capacity planning; Optimal control problems;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D92 - Microeconomics - - Micro-Based Behavioral Economics - - - Intertemporal Firm Choice, Investment, Capacity, and Financing
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising

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