Preview

Информатика

Расширенный поиск

ОБЗОР МОДЕЛЕЙ УПРАВЛЕНИЯ ДОХОДНОСТЬЮ В ГОСТИНИЧНОМ БИЗНЕСЕ

Полный текст:

Аннотация

Приводится краткое описание теории управления доходностью в гостиничном бизнесе, рас-крываются основные понятия. Предлагается новая классификация процессов управления доход-ностью, дается обзор литературы по динамическому ценообразованию, методам прогнозирования и оптимизационным моделям, применяемым в управлении доходностью в гостиничном бизнесе. Указы-ваются перспективные направления будущих исследований.

Об авторе

А. М. Бондоловский
Объединенный институт проблем информатики НАН Беларуси
Беларусь


Список литературы

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.


Для цитирования:


Бондоловский А.М. ОБЗОР МОДЕЛЕЙ УПРАВЛЕНИЯ ДОХОДНОСТЬЮ В ГОСТИНИЧНОМ БИЗНЕСЕ. Информатика. 2014;(2):66-83.

For citation:


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

Просмотров: 312


Creative Commons License
Контент доступен под лицензией Creative Commons Attribution 4.0 License.


ISSN 1816-0301 (Print)
ISSN 2617-6963 (Online)