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Technology revenue management system for customer groups in hotels

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  • Guadix, José
  • Cortés, Pablo
  • Onieva, Luis
  • Muñuzuri, Jesús

Abstract

This paper discusses revenue management; a technique that focuses on decision making that will maximize profit from the sale of perishable inventory units. New technologies management plays an important role in the development of revenue management techniques. Each new advancement in technology management leads to more sophisticated revenue business capabilities. Today decision support revenue management systems and technologies management are crucial factors for the success of businesses in service industries. This paper addresses the specific case of customer groups in hotels. This paper introduces a new decision support system that sets the revenue maximization criteria for a hotel. The aforementioned system includes a set of demand forecasting methods for customers and addresses a general case considering individual guests and customer groups. The system also incorporates deterministic and stochastic mathematical programming models that help to make the best decisions. The actual revenue depends upon which reservation system the hotel uses. A simulation engine makes a comparison between different heuristics of room inventory control: the results include performance indexes such as occupancy rate, efficiency rate, and yield; it compares results and chooses one of them. The system proves its suitability for actual cases by testing against actual data and thus becoming an innovative and efficient tool in the management of hotels' reservation systems.

Suggested Citation

  • Guadix, José & Cortés, Pablo & Onieva, Luis & Muñuzuri, Jesús, 2010. "Technology revenue management system for customer groups in hotels," Journal of Business Research, Elsevier, vol. 63(5), pages 519-527, May.
    • Handle: RePEc:eee:jbrese:v:63:y:2010:i:5:p:519-527
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    References listed on IDEAS

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    Cited by:

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    2. Aydin, N. & Birbil, S.I., 2018. "Decomposition methods for dynamic room allocation in hotel revenue management," European Journal of Operational Research, Elsevier, vol. 271(1), pages 179-192.
    3. Aldric Vives & Marta Jacob & Marga Payeras, 2018. "Revenue management and price optimization techniques in the hotel sector," Tourism Economics, , vol. 24(6), pages 720-752, September.
    4. Selmi, Noureddine & Chaney, Damien, 2018. "A measure of revenue management orientation and its mediating role in the relationship between market orientation and performance," Journal of Business Research, Elsevier, vol. 89(C), pages 99-109.
    5. Ziad Alrawadieh & Zaid Alrawadieh & Gurel Cetin, 2021. "Digital transformation and revenue management: Evidence from the hotel industry," Tourism Economics, , vol. 27(2), pages 328-345, March.
    6. TILEAGA Cosmin & OPRISAN Oana, 2018. "The Importance Of Selling Techniques In The Tourism Industry," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 70(2), pages 142-152, August.
    7. Yunmei Bai & Chun-Hung Tang, 2021. "Determining the optimal group rate in the hotel industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(4), pages 446-456, August.
    8. Malasevska, Iveta & Haugom, Erik, 2018. "Optimal prices for alpine ski passes," Tourism Management, Elsevier, vol. 64(C), pages 291-302.
    9. Aldric Vives & Marta Jacob, 2021. "Dynamic pricing in different Spanish resort hotels," Tourism Economics, , vol. 27(2), pages 398-411, March.
    10. Lazov, Igor, 2017. "Profit management of car rental companies," European Journal of Operational Research, Elsevier, vol. 258(1), pages 307-314.
    11. Sahut, Jean-Michel & Hikkerova, Lubica & Pupion, Pierre-Charles, 2016. "Perceived unfairness of prices resulting from yield management practices in hotels," Journal of Business Research, Elsevier, vol. 69(11), pages 4901-4906.
    12. Stanislav H. Ivanov, 2015. "Optimal Overbooking Limits for a Hotel with Three Room Types and with Upgrade and dOwngrade Constraints," Tourism Economics, , vol. 21(1), pages 223-240, February.

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