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An integrated fuzzy-stochastic model for revenue management

Author

Listed:
  • Valerio Lacagnina

    (Università di Palermo, Italy)

  • Davide Provenzano

    (Università di Palermo, Italy)

Abstract

Revenue management aims at improving the performance of an organization by selling the right product/service to the right customer at the right time. This task is very dependent on uncontrollable external factors. In the hospitality industry, rooms of the hotel represent perishable assets and fixed capacities at the same time. Therefore, in the case of a stochastic process for customers calling in reservations prior to a particular booking date, a common problem for hotels is to devise a policy for maximizing the total expected profit conditional on the set of bookings. We propose a fuzzy model for the hotel revenue management under an uncertain and vague environment. Fuzziness of objective and constraint functions have been incorporated into a stochastic booking model considering multiple-day stays to show the effect of uncertainty on the optimal demand. By changing the relaxation parameters of the objective function, we have found a set of optimal solutions with, in most of the cases, a value of the objective function equal to the optimal solution of the stochastic model, providing several alternative optimal room allocations.

Suggested Citation

  • Valerio Lacagnina & Davide Provenzano, 2016. "An integrated fuzzy-stochastic model for revenue management," Tourism Economics, , vol. 22(4), pages 779-792, August.
    • Handle: RePEc:sae:toueco:v:22:y:2016:i:4:p:779-792
    DOI: 10.1177/1354816616654250
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    References listed on IDEAS

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    1. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    2. Jeffrey I. McGill & Garrett J. van Ryzin, 1999. "Revenue Management: Research Overview and Prospects," Transportation Science, INFORMS, vol. 33(2), pages 233-256, May.
    3. Lawrence R. Weatherford & Samuel E. Bodily & Phillip E. Pfeifer, 1993. "Modeling the Customer Arrival Process and Comparing Decision Rules in Perishable Asset Revenue Management Situations," Transportation Science, INFORMS, vol. 27(3), pages 239-251, August.
    4. Kevin Pak & Nanda Piersma, 2002. "overview of OR techniques for airline revenue management," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 56(4), pages 479-495, November.
    5. Gabriel R. Bitran & Susana V. Mondschein, 1995. "An Application of Yield Management to the Hotel Industry Considering Multiple Day Stays," Operations Research, INFORMS, vol. 43(3), pages 427-443, June.
    6. Pak, K. & Piersma, N., 2002. "airline revenue management," ERIM Report Series Research in Management ERS-2002-12-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    7. Peter P. Belobaba, 1989. "OR Practice—Application of a Probabilistic Decision Model to Airline Seat Inventory Control," Operations Research, INFORMS, vol. 37(2), pages 183-197, April.
    8. Bodily, S. E. & Weatherford, L. R., 1995. "Perishable-asset revenue management: Generic and multiple-price yield management with diversion," Omega, Elsevier, vol. 23(2), pages 173-185, April.
    9. Badinelli, Ralph D., 2000. "An optimal, dynamic policy for hotel yield management," European Journal of Operational Research, Elsevier, vol. 121(3), pages 476-503, March.
    10. Weatherford, Larry R. & Kimes, Sheryl E., 2003. "A comparison of forecasting methods for hotel revenue management," International Journal of Forecasting, Elsevier, vol. 19(3), pages 401-415.
    11. Hadavandi, Esmaeil & Ghanbari, Arash & Shahanaghi, Kamran & Abbasian-Naghneh, Salman, 2011. "Tourist arrival forecasting by evolutionary fuzzy systems," Tourism Management, Elsevier, vol. 32(5), pages 1196-1203.
    12. Richard E. Chatwin, 1998. "Multiperiod Airline Overbooking with a Single Fare Class," Operations Research, INFORMS, vol. 46(6), pages 805-819, December.
    13. George B. Dantzig, 1955. "Linear Programming under Uncertainty," Management Science, INFORMS, vol. 1(3-4), pages 197-206, 04-07.
    14. 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.
    15. S. Liu & K.K. Lai & S.Y. Wang, 2008. "Booking models for hotel revenue management considering multiple-day stays," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 2(1), pages 78-91.
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    Cited by:

    1. Fatemeh Binesh & Amanda Belarmino & Carola Raab, 2021. "A meta-analysis of hotel revenue management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(5), pages 546-558, October.

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