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AN OVERVIEW OF THE HOTEL REVENUE MANAGEMENT MODELS

Abstract

The paper gives a brief scope of Hotel Revenue Management theory and discusses its basic def-initions. It also suggests a new classification of Revenue Management processes and surveys dynamic pricing, forecasting and optimization models employed in Hotel Revenue Management. Last section proposes promising directions of future research.

About the Author

A. M. Bandalouski
Объединенный институт проблем информатики НАН Беларуси
Belarus


References

1. Nguyen, Y. Hotel revenue management: a necessary evil, but not sufficient for delivering profitably / Y. Nguyen // hotelmarketing.com [Electronic resource]. – 2013. – Mode of access : http://goo.gl/pb2UfN. – Date of access : 22.04.2014.

2. Kimes, S.E. Revenue management: a retrospective / S.E. Kimes // Cornell hotel and restaurant administration quarterly. – 2004. – Vol. 44. – P. 131–138.

3. El Haddad, R. The impact of revenue management decisions on customers attitudes and behaviours: a case study of a leading UK budget hotel chain / R. El Haddad, A. Roper, P. Jones // EuroCHRIE 2008 Congress. – Dubai : Emirates hotel school, 2008.

4. Kimes, S.E. Has revenue management become acceptable? Findings from an international study on the perceived fairness of rate fences / S.E. Kimes, J. Wirtz // Journal of service research. – 2003. – Vol. 6, № 2. – P. 125–135.

5. Jauncey, S. The meaning and management of yield in hotels / S. Jauncey, I. Mitchell, P. Slamet // International journal of contemporary hospital management. – 1995. – Vol. 4. – P. 23–26.

6. Donaghy, K. Yield management: an overview / K. Donaghy, U. McMahon, D. McDowell // International journal of hospitality management. – 1995. – Vol. 14, № 2. – P. 139–150.

7. Jones, P. Yield management: putting people in the big picture / P. Jones, D. Hamilton // The Cornell hotel and restaurant administration quarterly. – 1992. – Vol. 33, № 3. – P. 89–96.

8. Bitran, G. An overview of pricing models for revenue management / G. Bitran, R. Caldentey // Manufacturing and service operations management. – 2003. – Vol. 5, № 20. – P. 203–229.

9. Chiang, W. An overview of research on revenue management: current issues and future research / W. Chiang, J.C.H. Chen, X. Xu // International journal of revenue management. – 2007. – Vol. 1, № 1. – P. 97–128.

10. Elmaghraby, W. Dynamic pricing in the presence of inventory considerations: research overview, current practices, and future directions / W. Elmaghraby, P. Keskinocak // Management science. – 2003. – Vol. 49, № 10. – P. 1287–1305.

11. Weatherford, L.R. A taxonomy and research overview of perishable-asset revenue management: yield management, overbooking, and pricing / L.R. Weatherford, S.E. Bodily // Operations research. – 1992. – Vol. 40, № 5. – P. 831–843.

12. McGill, J.I. Revenue management: research overview and prospects / J.I. McGill, G.J. van Ryzin // Transportation science. – 1999. – Vol. 33. – P. 233–256.

13. Ivanov, S. Hotel revenue management – a critical literature review / S. Ivanov, V. Zhechev // Tourism. – 2012. – Vol. 60, № 2. – P. 175–197.

14. A practitioners guide to time-series methods for tourism demand forecasting – a case study of Durban, South Africa / C.J.S. Burger [et.al.] // Tourism management. – 2001. – Vol. 22, № 4. – P. 403–409.

15. Chen, C. Forecasting and optimisation for hotel revenue management / C. Chen, S. Kachani // Journal of revenue and pricing management. – 2007. – Vol. 6, № 3. – P. 163–174.

16. Phumchusri, N. Hotel room demand forecasting via observed reservation information / N. Phumchusri, P. Mongkolkul // Proceedings of the Asia Pacific industrial engineering and management systems conference; Asia Pacific industrial engineering and management society. – Phuket, 2012. – P. 1978–1985.

17. Bitran, G. An application of yield management to the hotel industry considering multiple day stays / G. Bitran, S. Mondschein // Operations research. – 1995. – Vol. 43, № 3. – P. 427–443.

18. Models and techniques for hotel revenue management using a rolling horizon / P. Goldman [et al.] // Journal of revenue and pricing management. – 2002. – Vol. 1, № 3. – P. 207–226.

19. Kahneman, D. Fairness and the assumptions of economics / D. Kahneman, J.L. Knetsch, R.H. Thaler // Journal of business. – 1986. – Vol. 59. – P. 285–300.

20. Kahneman, D. Fairness as a constraint on profit seeking: entitlements in the market / D. Kahneman, J.L. Knetsch, R.H. Thaler // The american economic review. – 1986. – Vol. 76, № 4. – P. 728–741.

21. Kimes, S.E. Perceived fairness of yield management / S.E. Kimes // The Cornell hotel and restaurant administration. – 1994. – Vol. 35, № 1. – P. 22–24.

22. Revenue management: resolving potential customer conflicts / J. Wirtz [et al.] // Journal of revenue and pricing. – 2003. – Vol. 2, № 3. – P. 216–226.

23. Palmer, A. Variable pricing through revenue management: a critical evaluation of affective outcomes / A. Palmer, U. McMahon-Beattie // Management research news. – 2008. – Vol. 31, № 3. – P. 189–199.

24. Besanko, D. Optimal price skimming by a monopolist facing rational consumers / D. Besanko, W.L. Winston // Management science. – 1990. – Vol. 36, № 5. – P. 555–567.

25. Anderson, C.K. Wait or Buy? The strategic consumer: pricing and profit implications / C.K. Anderson, J.G. Wilson // The journal of the operational research society. – 2003. – Vol. 54. – P. 299–306.

26. Interval scheduling: a survey / A.W.J. Kolen [et al.] // Naval research logistics. – 2007. – Vol. 54, № 5. – P. 530–543.

27. Kovalyov, M.Y. Fixed interval scheduling: models, applications, computational complexity and algorithms / M.Y. Kovalyov, C.T. Ng, T.C.E. Cheng // European journal of operational research. – 2007. – Vol. 178. – P. 331–342.

28. A graph-theoretic approach to interval scheduling on dedicated unrelated parallel ma-chines / C.T. Ng [et al.] // Journal of the operational research society [Electronic resource]. – Mode of access : http://goo.gl/kOW6fH. – Date of access : 22.04.2014.

29. Pullman, M. Capacity management for hospitality and tourism : a review of current approaches / M. Pullman, S. Rogers // International journal of hospitality management. – 2010. – Vol. 29, № 1. – P. 177–187.

30. Hadjinicola, G.C. The overbooking problem in hotels with multiple tour-operators / G.C. Hadjinicola, C. Panayi // International journal of operations and production management. – 1997. – Vol. 17, № 9. – P. 874–885.

31. Ivanov, S. Dynamic overbooking limits for guaranteed and nonguaranteed hotel reservations / S. Ivanov // Tourism today. – 2007. – Vol. 7. – P. 100–108.

32. Ivanov, S. Management of overbookings in the hotel industry – basic concepts and practical challenges / S. Ivanov // Tourism today. – 2006. – Vol. 6. – P. 19–32.

33. Koide, T. The hotel yield management with two types of room prices, overbooking and cancellations / T. Koide, H. Ishii // International journal of production economics. – 2005. – Vol. 93, № 94. – P. 417–428.

34. Netessine, S. Introduction to the theory and practice of yield management / S. Netessine, R. Shumsky // INFORMS transactions on education. – 2002. – Vol. 3, № 1. – P. 34–44.

35. Kimes, S.E. The strategic levers of yield management / S.E. Kimes, R.B. Chase // Journal of service research. – 1998. – Vol. 1, № 2. – P. 156–166.

36. Vinod, B. Unlocking the value of revenue management in the hotel industry / B. Vinod // Journal of revenue and pricing management. – 2004. – Vol. 3, № 2. – P. 178–190.

37. Hanks, R.D. Discounting in the hotel industry. A new approach / R.D. Hanks, R.G. Cross, R.P. Noland // Cornell hotel and restaurant administration quarterly. – 2002. – Vol. 43, № 4. – P. 94–103.

38. Ng, I.C.L. A demand-based model for the advance and spot pricing of services / I.C.L. Ng // Journal of product and brand management. – 2009. – Vol. 18, № 7. – P. 517–528.

39. Zhang, M. Fencing in the context of revenue management / M. Zhang, P.C. Bell // International journal of revenue management. – 2010. – Vol. 4, №1. – P. 42–68.

40. Carvell, S.A. Exotic reservations – low price guarantee / S.A. Carvell, D.A. Quan // International journal of hospitality management. – 2008. – Vol. 27, № 2. – P. 162–169.

41. Room rate parity analysis across different hotel distribution channels in the U.S. / T. Demirciftci [et al.] // Journal of Hospitality Marketing & Management. – 2010. – Vol. 19, № 4. – P. 295–308.

42. Bitran, G. Periodic pricing of seasonal product in retailing / G. Bitran, S. Mondschein // Management science. – 1997. – Vol. 43. – P. 427–443.

43. Feng, Y. Optimal starting times for end-of-season sales and optimal stopping times for promotional fares / Y. Feng, G. Gallego // Management science. – 1995. – Vol. 41. – P. 1371–1391.

44. Gallego, G. Optimal dynamic pricing of inventories with stochastic demand over finite horizons / G. Gallego, G. van Ryzin // Management science. – 1994. – Vol. 40. – P. 999–1020.

45. Brynjolfsson, E. Frictionless Commerce? A Comparison of internet and conventional retailers / E. Brynjolfsson, M. Smith // Management science. – 1999. – Vol. 46, № 4. – P. 563–585.

46. Boyd, E.A. Revenue management and e-commerce / E.A. Boyd, I.C. Bilegan // Management science. – 2003. – Vol. 49, № 10. – P. 1363–1386.

47. van Ryzin, G. A multi-product dynamic pricing problem and its applications to network yield management / G. van Ryzin, G. Gallego // Operations research. – 1997. – Vol. 45. – P. 24–41.

48. Ladany, S. Optimal cruise-liner passenger cabin pricing policy / S. Ladany, A. Arbel // European journal of operational research. – 1991. – Vol. 55, № 2. – P. 136–147.

49. You, P.S. Dynamic pricing in airline seat management for flights with multiple flight legs / P.S. You // Transportation science. – 1999. – Vol. 33, № 2. – P. 192–206.

50. Gaimon, C. Simultaneous and dynamic price, production, inventory and capacity decisions / C. Gaimon // European journal of operational research. – 1988. – Vol. 35. – P. 426–441.

51. Lau, A.H.L. The newsboy problem with price dependent demand distribution / A.H.L. Lau, H.S. Lau // IIE transactions. – 1988. – Vol. 20, № 2. – P. 168–175.

52. Weatherford, L.R. Optimization of perishable-asset revenue management problems that allow prices as decision variables / L.R. Weatherford // International journal of services technology and management. – 2001. – Vol. 2, № 1/2. – P. 71–101.

53. Chatwin, R.E. Optimal dynamic pricing of perishable products with stochastic demand and a finite set of prices / R.E. Chatwin // European journal of operational research. – 2000. – Vol. 125. – P. 149–174.

54. Feng, Y. Perishable asset revenue management with Markovian time dependent demand intensities / Y. Feng, G. Gallego // Management science. – 2000. – Vol. 46. – P. 941–956.

55. Feng, Y. A continuous-time yield management model with multiple prices and reversible price changes / Y. Feng, B. Xiao // Management science. – 2000. – Vol. 48. – P. 644–657.

56. Feng, Y. Optimal policies of yield management with multiple predetermined prices / Y. Feng, B. Xiao // Management science. – 2000. – Vol. 48. – P. 332–343.

57. Tranter, K.A. Introduction to revenue management for the hospitality industry / K.A. Tranter, T. Stuart-Hill, J. Parker. – Harlow : Pearson Prentice hall, 2008. – 352 p.

58. Emeksiz, M. A yield management model for five-star hotels: computerized and non-computerized implementation / M. Emeksiz, D. Gursoy, O. Icoz // International journal of hospitality management. – 2006. – Vol. 25, № 4. – P. 536–551.

59. Cross, R.G. Revenue management / R.G. Cross. – N.Y. : Broadway books, 1997. – 288 p.

60. Pölt, S. Forecasting is difficult – especially if it refers to the future / S. Pölt // Reservations and yield management study group annual meeting proceedings. – Melbourne, 1998. – 32 p.

61. Weatherford, L.R. Forecasting for hotel revenue management: testing aggregation against disaggregation / L.R. Weatherford, S.E. Kimes, D.A. Scott // Cornell hotel and restaurant administration quarterly. – 2001. – Vol. 42. – P. 53–64.

62. Lee, A.O. Airline reservations forecasting: probabilistic and statistical models of the booking process: PhD thesis / O.A. Lee. – Cambridge, 1990. – 266 p.

63. The accuracy of extrapolation (time series) methods: results of a forecasting competition / S. Makridakis [et al.] // Journal of forecasting. – 1982. – Vol. 1. – P. 111–153.

64. Weatherford, L.R. A comparison of forecasting methods for hotel revenue management / L.R. Weatherford, S.E. Kimes // International journal of forecasting. – 2003. – Vol. 19. – P. 401–415.

65. Fildes, R. Forecasting competitions – their role in improving forecasting practice and research / R. Fildes, K. Ord // A companion to economic forecasting / M.P. Clements, D.F. Hendry. – Oxford, 2002. – Ch. 15. – P. 322–353.

66. Ben-Akiva, M. Improving airline passenger forecasts using reservation data / M. Ben-Akiva // Fall ORSA/TIMS conference. – St. Louis, 1987.

67. Forecasting uncertain hotel room demand / M. Rajopadhye [et al.] // Information sciences. – 2001. – Vol. 132, № 1–4. – P. 1–11.

68. Yüksel, S. An integrated forecasting approach to hotel demand / S. Yüksel // Mathematical and computer modellincg. – 2007. – Vol. 46, № 7, 8. – P. 1063–1070.

69. Lim, C. An econometric analysis of hotel-motel room nights in New Zealand with stochastic seasonality / C. Lim, F. Chan // International journal of revenue management. – 2011. – Vol. 5, № 1. – P. 63–83.

70. Lim, C. Forecasting hotel guest nights in New Zealand / C. Lim, C. Chang, M. McAleer // International journal of hospitality management. – 2009. – Vol. 28, № 2. – P. 228–235.

71. Armstrong, J.S. Error measures for generalizing about forecasting methods: empirical comparisons / J.S. Armstrong, F. Collopy // International journal of forecasting. – 1992. – Vol. 8. – P. 69–80.

72. Zakhary, A. A comparative study of the pickup method and its variations using a simulated hotel reservation data / A. Zakhary, N. El. Gayar, A.F. Atiya // ICGST international journal on artificial intelligence and machine learning. – 2008. – Vol. 8. – P. 15–21.

73. Schnaars, S.P. Situational factors affecting forecast accuracy / S.P. Schnaars // Journal of marketing research. – 1984. – Vol. 21. – P. 290–297.

74. Weatherford, L.R. A tutorial on optimization in the context of perishable-asset revenue management problems for the airline industry / L.R. Weatherford // Operations research in the airline industry / ed. G. Yu. – Boston, 1998. – P. 68–100.

75. Pak, K. Airline revenue management: an overview of OR techniques 1982–2001 / K. Pak, N. Piersma // Erasmus University Rotterdam [Electronic resource]. – 2002. – Mode of access : http://repub.eur.nl/pub/584. – Date of access : 22.04.2014.

76. Littlewood, K. Forecasting and control of passenger bookings / K. Littlewood // AGIFORS symposium proc. 12, Nathanya, 1972; Alliance group of the international federation of operational research scientists. – Nathanya, 1972.

77. Belobaba, P.P. Air travel demand and airline seat inventory management: PhD thesis / P.P. Belobaba. – Cambridge, 1987. – 236 p.

78. Curry, R.E. Optimal airline seat allocation with fare classes nested by origin and destinations / R.E. Curry // Transportation science. – 1990. – Vol. 24. – P. 193–204.

79. Wollmer, R.D. An airline seat management model for a single leg route when lower fare classes book first / R.D. Wollmer // Operations research. – 1992. – Vol. 40. – P. 26–37.

80. Brumelle, S.L. Airline seat allocation with multiple nested fare classes / S.L. Brumelle, J.I. McGill // Operations research. – 1993. – Vol. 41. – P. 127–137.

81. Lee, T.C. A model for dynamic airline seat inventory control with multiple seat bookings / T.C. Lee, M. Hersh // Transportation science. – 1993. – Vol. 27. – P. 252–265.

82. Kleywegt, A.J. The dynamic and stochastic knapsack problem / A.J. Kleywegt, J.D. Papastavrou // Operations research. – 1998. – Vol. 46. – P. 17–35.

83. Subramanian, J. Airline yield management with overbooking, cancellations, and no-shows / J. Subramanian, Jr. S. Stidham, C.J. Lautenbacher // Transportation science. – 1999. – Vol. 33. – P. 147–167.

84. Williams, H.P. Model building in mathematical programming / H.P. Williams. – Chichister, N.Y. : Willey, 1999. – 353 p.

85. Писарук, Н.Н. Модели и методы смешанно-целочисленного программирования / Н.Н. Писарук. – Минск : БГУ, 2010. – С. 205–208.

86. The passenger mix problem in the scheduled airlines / F. Glover [et al.] // Interfaces. – 1982. – Vol. 12. – P. 73–79.

87. Talluri, K.T. A randomized linear programming method for computing network bid prices / K.T. Talluri, G.J. van Ryzin // Transportation science. – 1999. – Vol. 33. – P. 207–216.

88. Williamson, E.L. Airline network seat inventory control: methodologies and revenue impacts: PhD thesis / E.L. Williamson. – Cambridge, 1992. – 270 p.

89. Wei, Y.J. Airline O-D control using network displacement concepts: MS thesis / Y.J. Wei. – Cambridge, 1997. – 139 p.

90. Talluri, K.T. An analysis of bid-price controls for network revenue management / K.T. Talluri, G.J. van Ryzin // Management science. – 1998. – Vol. 44, № 11. – P. 1577–1593.

91. Chen, V.C.P. A Markov decision problem based approach to the airline YM problem / V.C.P. Chen, D. Gunther, E.L. Johnson // Georgia institute of technology, The Logistics Institute [Electronic resource]. – Mode of access : http://goo.gl/H77hjL. – Date of access : 22.04.2014.

92. van Ryzin, G. Revenue management / G. van Ryzin, K.T. Talluri // Handbook of transportation science / ed. R.W. Hall. – Boston, 2003. – Ch. 16. – P. 599–659.

93. Cooper, W.L. A class of hybrid methods for revenue management / W.L. Cooper, T. Homem-de-Mello // Northwestern university, Department of industrial engineering and management sciences [Electronic resource]. – Mode of access : http://goo.gl/pJzeF9. – Date of access : 22.04.2014.

94. Lai, K.-K. A stochastic approach to hotel revenue optimization / K.-K. Lai, W.-L. Ng // computers and operations research. – 2005. – Vol. 32, № 5. – P. 1059–1072.

95. A stochastic approach to hotel revenue management considering multiple-day stays / S. Liu [et al.] // International journal of information technology and decision making. – 2006. – Vol. 5, № 3. – P. 545–556.

96. Liu, S. Booking models for hotel revenue management considering multiple-day stays / S. Liu, K.K. Lai, S.-Y. Wang // International journal of revenue management. – 2008. – Vol. 2, № 1. – P. 78–91.

97. Baker, T.K. The benefits of optimizing prices to manage demand in hotel revenue management systems / T.K. Baker, D.A. Collier // Production and operations management. – 2003. – Vol. 12. – P. 502–518.

98. Forecasting hotel arrivals and occupancy using Monte Carlo simulation / A. Zakhary [et al.] // Journal of revenue and pricing management. – 2011. – Vol. 10, № 4. – P. 344–366.

99. Bertsimas, D. Restaurant revenue management / D. Bertsimas, R. Shioda // Operations research. – 2003. – Vol. 51. – P. 472–486.

100. Badinelli, R.D. An optimal, dynamic policy for hotel yield management / R.D. Badinelli // European journal of operations research. – 2000. – Vol. 121. – P. 476–503.

101. Padhi, S.S. Competitive revenue management for fixing quota and price of hotel commodities under uncertainty / S.S. Padhi, V. Aggarwal // International journal of hospitality management. – 2011. – Vol. 30, № 3. – P. 725–734.

102. Dynamic pricing and the direct-to-customer model in the automotive industry / S. Biller [et al.] // Electronic commerce research. – 2005. – Vol. 5, № 2. – P. 309–334.


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Bandalouski A.M. AN OVERVIEW OF THE HOTEL REVENUE MANAGEMENT MODELS. Informatics. 2014;(2):66-83. (In Russ.)

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