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Strategic and operational decisions in restaurant revenue management

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  • Guerriero, Francesca
  • Miglionico, Giovanna
  • Olivito, Filomena

Abstract

The paper addresses restaurant revenue management from both a strategic and an operational point of view. Strategic decisions in restaurants are mainly related to defining the most profitable combination of tables that will constitute the restaurant. We propose new formulations of the so-called “Tables Mix Problem” by taking into account several features of the real setting. We compare the proposed models in a computational study showing that restaurants, with the capacity of managing tables as renewable resources and of combining different-sized tables, can improve expected revenue performances. Operational decisions are mainly concerned with the more profitable assignment of tables to customers. Indeed, the “Parties Mix Problem” consists of deciding on accepting or denying a booking request from different groups of customers, with the aim of maximizing the total expected revenue. A dynamic formulation of the “Parties Mix Problem” is presented together with a linear programming approximation, whose solutions can be used to define capacity control policies based on booking limits and bid prices. Computational results compare the proposed policies and show that they lead to higher revenues than the traditional strategies used to support decision makers.

Suggested Citation

  • Guerriero, Francesca & Miglionico, Giovanna & Olivito, Filomena, 2014. "Strategic and operational decisions in restaurant revenue management," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1119-1132.
  • Handle: RePEc:eee:ejores:v:237:y:2014:i:3:p:1119-1132
    DOI: 10.1016/j.ejor.2014.02.048
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    References listed on IDEAS

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    1. Guillermo Gallego & Garrett van Ryzin, 1997. "A Multiproduct Dynamic Pricing Problem and Its Applications to Network Yield Management," Operations Research, INFORMS, vol. 45(1), pages 24-41, February.
    2. 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.
    3. Dimitris Bertsimas & Romy Shioda, 2003. "Restaurant Revenue Management," Operations Research, INFORMS, vol. 51(3), pages 472-486, June.
    4. Kalyan Talluri & Garrett van Ryzin, 1998. "An Analysis of Bid-Price Controls for Network Revenue Management," Management Science, INFORMS, vol. 44(11-Part-1), pages 1577-1593, November.
    5. de Boer, Sanne V. & Freling, Richard & Piersma, Nanda, 2002. "Mathematical programming for network revenue management revisited," European Journal of Operational Research, Elsevier, vol. 137(1), pages 72-92, February.
    6. S Benigno & F Guerriero & G Miglionico, 2012. "A revenue management approach to address a truck rental problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(10), pages 1421-1433, October.
    7. Wen-Chyuan Chiang & Jason C.H. Chen & Xiaojing Xu, 2007. "An overview of research on revenue management: current issues and future research," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 1(1), pages 97-128.
    8. Huseyin Topaloglu & Warren B. Powell, 2006. "Dynamic-Programming Approximations for Stochastic Time-Staged Integer Multicommodity-Flow Problems," INFORMS Journal on Computing, INFORMS, vol. 18(1), pages 31-42, February.
    9. Guerriero, Francesca & Miglionico, Giovanna & Olivito, Filomena, 2012. "Revenue management policies for the truck rental industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 202-214.
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    Cited by:

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    2. Milad HajMirzaei & Koorush Ziarati & Alireza Nikseresht, 2022. "A customer type discovery algorithm in hotel revenue management systems," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(2), pages 200-211, April.
    3. Mohit Tyagi & Nomesh B. Bolia, 2022. "Approaches for restaurant revenue management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(1), pages 17-35, February.

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