Industrial Engineering and Management Systems

  • 제12권3호
  • /
  • Pages.207-223
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  • 2013
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  • 1598-7248(pISSN)
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  • 2234-6473(eISSN)
대한산업공학회 (Korean Institute of Industrial Engineers)
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Mathematical Model for Revenue Management with Overbooking and Costly Price Adjustment for Hotel Industries

  • Masruroh, Nur Aini (Department of Mechanical and Industrial Engineering, Faculty of Engineering, Gadjah Mada University) ;
  • Mulyani, Yun Prihantina (Department of Mechanical and Industrial Engineering, Faculty of Engineering, Gadjah Mada University)
  • 투고 : 2013.01.31
  • 심사 : 2013.09.10
  • 발행 : 2013.09.30
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초록

Revenue management (RM) has been widely used to model products characterized as perishable. Classical RM model assumed that price is the sole factor in the model. Thus price adjustment becomes a crucial and costly factor in business. In this paper, an optimal pricing model is developed based on minimization of soft customer cost, one kind of price adjustment cost and is solved by Lagrange multiplier method. It is formed by expected discounted revenue/bid price integrating quantity-based RM and pricing-based RM. Quantity-based RM consists of two capacity models, namely, booking limit and overbooking. Booking limit, built by assuming uncertain customer arrival, decides the optimal capacity allocation for two market segments. Overbooking determines the level of accepted order exceeding capacity to anticipate probability of cancellation. Furthermore, pricing-based RM models occupancy/demand rate influenced by internal and competitor price changes. In this paper, a mathematical model based on game theoretic approach is developed for two conditions of deterministic and stochastic demand. Based on the equilibrium point, the best strategy for both hotels can be determined.

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참고문헌

  1. Bertsimas, D. and De Boer, S. (2005), Simulation-based booking limits for airline revenue management, Operations Research, 53(1), 90-106. https://doi.org/10.1287/opre.1040.0164
  2. Bitran, G. B. and Gilbert, S. M. (1996), Managing hotel reservation with uncertain arrivals, Operations Research, 44(1), 35-49. https://doi.org/10.1287/opre.44.1.35
  3. Chen, X., Zhou, S. X., and Chen, Y. (2010), Integration of inventory and pricing decisions with costly price adjustments, Operations Research, 59(5), 1144-1158.
  4. Dolgui, A. and Porth, J. (2010), Pricing strategy and models, Annual Reviews in Control, 34(1), 101-110. https://doi.org/10.1016/j.arcontrol.2010.02.005
  5. Dai, Y., Chao, X., Fang, S. C., and Nuttle, H. L. W. (2004), Pricing in revenue management for multiple firms competing for customers, International Journal Production Economics, 98(1), 1-16.
  6. Gothesson, L. and Riman, S. (2004), Revenue manage ment within Swedish hotels, M.S. thesis, School of Economics and Commercial Law, Goteborg University, Goteborg, Sweden.
  7. Netessine, S. and Shumsky, R. A. (2004), Revenue management games: horizontal and vertical competition, Management Science, 51(5), 813-831.
  8. Netessine, S., Shumky, R. A., and Sadagopan, N. (2002), Introduction to the theory and practice of yield management, INFORMS Transactions on Education, 3(1), 34-44. https://doi.org/10.1287/ited.3.1.34
  9. Rapoport, A. (1971), Three- and four-person games, Comparative Group Studies, 2(2), 191-226. https://doi.org/10.1177/104649647100200205
  10. Talluri, K. T. and Van Ryzin, G. J. (2004), The Theory and Practice of Revenue Management, Kluwer Academic Publishers, Boston, MA.
  11. Turocy, T. L. and Von Stengel, B. (2001), Game theory, CDAM Research Report LSE-CDAM-2001-09, Mathematics Department, London School of Economics, London, UK.
  12. Wolman, A. L. (2000), The frequency and costs of individual price adjustment, Federal Reserve Bank of Richmond Economic Quarterly, 86(4), 1-22.