Basic concepts and brief description of revenue management models and decision tools in the hotel business are presented. An overview of the relevant literature on dynamic pricing, forecasting methods and optimization models is provided. The main ideas of the authors’ customized revenue management method for the hotel business are presented.
Accepté le :
DOI : 10.1051/ro/2018001
Mots clés : Revenue management, dynamic pricing, forecasting, optimization
@article{RO_2018__52_1_119_0,
author = {Bandalouski, Andrei M. and Kovalyov, Mikhail Y. and Pesch, Erwin and Tarim, S. Armagan},
title = {An overview of revenue management and dynamic pricing models in hotel business},
journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
pages = {119--141},
publisher = {EDP-Sciences},
volume = {52},
number = {1},
year = {2018},
doi = {10.1051/ro/2018001},
zbl = {1397.90203},
language = {en},
url = {http://www.numdam.org/articles/10.1051/ro/2018001/}
}
TY - JOUR AU - Bandalouski, Andrei M. AU - Kovalyov, Mikhail Y. AU - Pesch, Erwin AU - Tarim, S. Armagan TI - An overview of revenue management and dynamic pricing models in hotel business JO - RAIRO - Operations Research - Recherche Opérationnelle PY - 2018 SP - 119 EP - 141 VL - 52 IS - 1 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/ro/2018001/ DO - 10.1051/ro/2018001 LA - en ID - RO_2018__52_1_119_0 ER -
%0 Journal Article %A Bandalouski, Andrei M. %A Kovalyov, Mikhail Y. %A Pesch, Erwin %A Tarim, S. Armagan %T An overview of revenue management and dynamic pricing models in hotel business %J RAIRO - Operations Research - Recherche Opérationnelle %D 2018 %P 119-141 %V 52 %N 1 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/ro/2018001/ %R 10.1051/ro/2018001 %G en %F RO_2018__52_1_119_0
Bandalouski, Andrei M.; Kovalyov, Mikhail Y.; Pesch, Erwin; Tarim, S. Armagan. An overview of revenue management and dynamic pricing models in hotel business. RAIRO - Operations Research - Recherche Opérationnelle, Tome 52 (2018) no. 1, pp. 119-141. doi : 10.1051/ro/2018001. http://www.numdam.org/articles/10.1051/ro/2018001/
[1] and , Strategic and tactical price decisions in hotel revenue management. Tour. Manag. 55 (2016) 123–132. | DOI
[2] , and , Dynamic pricing strategies: evidence from European hotels. Int. J. Hosp. Manag. 31 (2012) 160–168. | DOI
[3] , and , Optimal pricing policies for perishable products. Eur. J. Oper. Res. 166 (2005) 246–254. | DOI | Zbl
[4] and , Error measures for generalizing about forecasting methods: Empirical comparisons. Int. J. Forecast. 8 (1992) 69–80. | DOI
[5] , , and , Dynamic room pricing model for hotel revenue management systems. Egypt. Inf. J. 12 (2011) 177–183.
[6] , An optimal, dynamic policy for hotel yield management. Eur. J. Oper. Res. 121 (2000) 476–503. | DOI | Zbl
[7] and , The benefits of optimizing prices to manage demand in hotel revenue management systems. Prod. Oper. Manag. 12 (2003) 502–518. | DOI
[8] , Air Travel Demand and Airline Seat Inventory Management. Ph.D. thesis, MIT (1987).
[9] , Improving airline passenger forecasts using reservation data, in Fall ORSA/TIMS Conference, St. Louis (1987).
[10] and , Simulation-based booking limits for airline revenue management. Oper. Res. 53 (2005) 90–106. | DOI | Zbl
[11] and , Restaurant revenue management. Oper. Res. 51 (2003) 472–486. | DOI
[12] and , Optimal price skimming by a monopolist facing rational consumers. Manag. Sci. 36 (1990) 555–567. | DOI | MR | Zbl
[13] and , An overview of pricing models for revenue management. Manuf. Serv. Oper. Manag. 5 (2003) 203–229. | DOI
[14] and , An application of yield management to the hotel industry considering multiple day stays. Oper. Res. 43 (1995) 427–443. | DOI | Zbl
[15] and , Periodic pricing of seasonal product in retailing. Manag. Sci. 43 (1997) 427–443. | Zbl
[16] and , Revenue management and e-commerce. Manag. Sci. 49 (2003) 1363–1386. | DOI
[17] and , Airline seat allocation with multiple nested fare classes. Oper. Res. 41 (1993) 127–137. | DOI | Zbl
[18] and , Frictionless commerce? A comparison of internet and conventional retailers. Manag. Sci. 46 (1999) 563–585. | DOI
[19] , , and , A practitioners guide to time-series methods for tourism demand forecasting – a case study of Durban, South Africa. Tour. Manag. 22 (2001) 403–409. | DOI
[20] , and , Optimal dynamic pricing of inventories with stochastic demand and discounted criterion. Eur. J. Oper. Res. 217 (2012) 580–588. | DOI | MR | Zbl
[21] and , Exotic reservations – low price guarantee. Int. J. Hosp. Manag. 27 (2008) 162–169. | DOI
[22] and , Consumer price sensitivity in the retail industry: latitude of acceptance with heterogeneous demand. Eur. J. Oper. Res. 228 (2013) 418–426. | DOI | MR | Zbl
[23] , Optimal dynamic pricing of perishable products with stochastic demand and a finite set of prices. Eur. J. Oper. Res. 125 (2000) 149–174. | DOI | Zbl
[24] and , Simple policies for dynamic pricing with imperfect forecasts. Oper. Res. 61 (2013) 612–624. | DOI | MR | Zbl
[25] and , Forecasting and optimisation for hotel revenue management. J. Revenue Pricing Manag. 6 (2007) 163. | DOI
[26] , and , A Markov Decision Problem Based Approach to the Airline YM Problem. Tech. rep., Georgia Institute of Technology, The Logistics Institute (1998).
[27] , and , Lease expiration management for a single lease term in the apartment industry. Eur. J. Oper. Res. 238 (2014) 233–244. | DOI | MR | Zbl
[28] , and , Revenue management of reusable resources with advanced reservations. Prod. Oper. Manag. 26 (2017) 836–859. | DOI
[29] , and , Overview of research on revenue management: current issues and future research. Int. J. Revenue Manag. 1 (2007) 97–128. | DOI
[30] and , A Class of Hybrid Methods for Revenue Management. Tech. rep., Northwestern University, Department of Industrial Engineering and Manag. Sci. (2003).
[31] , Revenue Management. Broadway Books (1997).
[32] , Optimal airline seat allocation with fare classes nested by origin and destinations. Transp. Sci. 24 (1990) 193–204. | DOI
[33] and , Dynamic pricing when consumers are strategic: analysis of posted and contingent pricing schemes. Eur. J. Oper. Res. 204 (2010) 662–671. | DOI | Zbl
[34] , and , Mathematical programming for network revenue management revisited. Eur. J. Oper. Res. 137 (2002) 72–92. | DOI | Zbl
[35] , , and , Room rate parity analysis across different hotel distribution channels in the U.S. J. Hosp. Mark. Manag. 19 (2010) 295–308.
[36] , and , Yield management: an overview. Int. J. Hosp. Manag. 44 (1995) 139–150. | DOI
[37] and , Dynamic pricing in the presence of inventory considerations: research overview, current practices, and future directions. Manag. Sci. 49 (2003) 1287–1305. | DOI | Zbl
[38] , and , A yield management model for five-star hotels: computerized and non-computerized implementation. Int. J. Hosp. Manag. 25 (2006) 536–551. | DOI
[39] and , Optimal starting times for end-of-season sales and optimal stopping times for promotional fares. Manag. Sci. 41 (1995) 1371–1391. | DOI | Zbl
[40] and , Perishable asset revenue management with Markovian time dependent demand intensities. Manag. Sci. 46 (2000) 941–956. | DOI | Zbl
[41] and , A continuous-time yield management model with multiple prices and reversible price changes. Manag. Sci. 48 (2000) 644–657. | DOI | Zbl
[42] and , Optimal policies of yield management with multiple predetermined prices. Manag. Sci. 48 (2000) 332–343.
[43] and , A continuous-time seat control model for single-leg flights with no-shows and optimal overbooking upper bound. Eur. J. Oper. Res. 174 (2006) 1298–1316. | DOI | Zbl
[44] and , Integration of pricing and capacity allocation for perishable products. Eur. J. Oper. Res. 168 (2006) 17–34. | DOI | MR | Zbl
[45] and , Forecasting competitions – their role in improving forecasting practice and research, in A Companion to Economic Forecasting. Blackwell Publishing (2002) 322–353.
[46] , Simultaneous and dynamic price, production, inventory and capacity decisions. Eur. J. Oper. Res. 35 (1988) 426–441. | DOI | MR
[47] and , Optimal dynamic pricing of inventories with stochastic demand over finite horizons. Manag. Sci. 40 (1994) 999–1020. | DOI | Zbl
[48] , , and , The passenger mix problem in the scheduled airlines. Interfaces 12 (1982) 73–79. | DOI
[49] , , and , Models and techniques for hotel revenue management using a rolling horizon. J. Revenue Pricing Manag. 1 (2002) 207–219. | DOI
[50] ,, , and , Optimal pricing strategy based on market segmentation for service products using online reservation systems: an application to hotel rooms. Int. J. Hosp. Manag. 35 (2013) 274–281. | DOI
[51] , and , The impact of revenue management decisions on customers attitudes and behaviours: a case study of a leading UK budget hotel chain, in EuroCHRIE 2008 Congress, Dubai, 11–14 October 2008, Emirates Hotel School (2008).
[52] and , The overbooking problem in hotels with multiple tour-operators. Int. J. Oper. Prod. Manag. 17 (1997) 874–885. | DOI
[53] , and , Discounting in the hotel industry, A new approach. Cornell Hotel Restaur. Adm. Q. 43 (2002) 94–103. | DOI
[54] , Management of overbookings in the hotel industry – basic concepts and practical challenges. Tour. Today 6 (2006) 19–32.
[55] , Dynamic overbooking limits for guaranteed and nonguaranteed hotel reservations. Tour. Today 7 (2007) 100–108.
[56] , Hotel Revenue Management – From Theory to Practice. Zangador, Varna (2014).
[57] and , Hotel revenue management – a critical literature review. Tourism 60 (2012) 175–197.
[58] , and , The meaning and management of yield in hotels. Int. J. Contemp. Hosp. Manag. 4 (1995) 23–26. | DOI
[59] and , Yield management: putting people in the big picture. Cornell Hotel Restaur. Adm. Q. 33 (1992) 89–96. | DOI
[60] , and , Fairness and the assumptions of economics. J. Bus. 76 (1986) 728–741.
[61] , and , Fairness as a constraint on profit seeking: entitlements in the market. Am. Econo. Rev. 76 (1986) 728–741.
[62] , Perceived fairness of yield management. Cornell Hotel Restaur. Adm. 35 (1994) 22–24. | DOI
[63] , Revenue management: a retrospective. Cornell Hotel Restaur. Adm. Q. 44 (2004) 131–138. | DOI
[64] and , The strategic levers of yield management. J. Serv. Res. 1 (1998) 156–166. | DOI
[65] and , Has revenue management become acceptable? Findings from an international study on the perceived fairness of rate fences. J. Serv. Res. 6 (2003) 125–135. | DOI
[66] and , The dynamic and stochastic knapsack problem. Oper. Res. 46 (1998) 17–35. | DOI | MR | Zbl
[67] and , List pricing versus dynamic pricing: impact on the revenue risk. Eur. J. Oper. Res. 204 (2010) 505–512. | DOI | MR | Zbl
[68] and , The hotel yield management with two types of room prices, overbooking and cancellations. Int. J. Prod. Econ. 93 (2005) 417–428. | DOI
[69] , and , Retail price optimization at intercontinental hotels group. Interfaces 42 (2012) 45–47. | DOI
[70] , , and , Non-cooperative competition among revenue maximizing service providers with demand learning. Eur. J. Oper. Res. 197 (2009) 981–996. | DOI | MR | Zbl
[71] , Optimal market segmentation of hotel rooms – the non-linear case. Omega 24 (1996) 29–36 | DOI
[72] and , Optimal cruise-liner passenger cabin pricing policy. Eur. J. Oper. Res. 55 (1991) 136–147. | DOI | Zbl
[73] and , A stochastic approach to hotel revenue optimization. Comput. Oper. Res. 32 (2005) 1059–1072. | DOI | MR | Zbl
[74] and , The newsboy problem with price dependent demand distribution. IIE Trans. 20 (1988) 168–175. | DOI
[75] , Airline Reservations Forecasting: Probabilistic and Statistical Models of the Booking Process. Ph.D. thesis. Massachusetts Institute of Technology (1990). | MR
[76] and , A model for dynamic airline seat inventory control with multiple seat bookings. Transp. Sci. 27 (1993) 252–265. | DOI
[77] and , Dynamic allocation problems in loss network systems with advanced reservation. Preprint (2015). | arXiv
[78] and , An econometric analysis of hotel-motel room nights in New Zealand with stochastic seasonality. Int. J. Revenue Manag. 5 (2011) 63–83. | DOI
[79] , and , Forecasting hotel guest nights in New Zealand. Int. J. Hosp. Manag. 28 (2009) 228–235. | DOI
[80] , Dynamic pricing with real-time demand learning. Eur. J. Oper. Res. 174 (2006) 522–538 | DOI | Zbl
[81] and , Dynamic price competition with discrete customer choices. Eur. J. Oper. Res. 197 (2009) 969–980. | DOI | MR | Zbl
[82] , Forecasting and control of passenger bookings, in AGIFORS Symposium Proc. 12, Nathanya (1972).
[83] , , and , A stochastic approach to hotel revenue management considering multiple-day stays. Int. J. Inf. Technol. Decision Mak. 5 (2006) 545–556. | DOI
[84] , and , Booking models for hotel revenue management considering multiple-day stays. Int. J. Revenue Manag. 2 (2008) 78–91. | DOI
[85] , , and , Dynamic cruise ship revenue management. Eur. J. Oper. Res. 207 (2010) 445–455. | DOI | MR | Zbl
[86] , , , , , , et al. The accuracy of extrapolation (time series) methods: results of a forecasting competition. J. Forecast. 1 (1982) 111–153. | DOI
[87] and , Revenue management: research overview and prospects. Transp. Sci. 33 (1999) 233–256. | DOI | Zbl
[88] and , Improved bid prices for choice-based network revenue management. Eur. J. Oper. Res. 217 (2012) 417–427. | DOI | MR | Zbl
[89] and , Network revenue management with inventory-sensitive bid prices and customer choice. Eur. J. Oper. Res. 216 (2012) 459–468. | DOI | MR | Zbl
[90] and , Introduction to the theory and practice of yield management. INFORMS Trans. Edu. 3 (2002) 34–44. | DOI
[91] , A demand-based model for the advance and spot pricing of services. J. Prod. Brand Manag. 18 (2009b) 517–528. | DOI
[92] , Hotel revenue management: a necessary evil, but not sufficient for delivering profitably. Available at http://hotelmarketing.com/index.php/content/article/hotel_revenue_management_a_necessary_evil_but_not_sufficient_for_delivering (2013).
[93] , and , Structural properties of Markov modulated revenue management problems. Eur. J. Oper. Res. 225 (2013) 324–331. | DOI | MR | Zbl
[94] and , Competitive revenue management for fixing quota and price of hotel commodities under uncertainty. Int. J. Hosp. Manag. 30 (2011) 725–734. | DOI
[95] and , Airline Revenue Management: an Overview of OR Techniques 1982–2001. Tech. rep., Erasmus University Rotterdam (2002). | MR
[96] , , Variable pricing through revenue management: a critical evaluation of affective outcomes. Manag. Res. News 31 (2008) 189–199. | DOI
[97] , , , , , , et al. Carlson Rezidor hotel group maximizes revenue through improved demand management and price optimization. Interfaces 43 (2013) 21–36. | DOI
[98] and , Demand forecasting via observed reservation information, in Proceedings of the Asia Pacific Industrial Engineering and Management Systems Conference, Asia Pacific Industrial Engineering and Management Society, Phuket, Thailand (2012) 1978–1985.
[99] , Forecasting is difficult – especially if it refers to the future, in Reservations and Yield Management Study Group Annual Meeting Proceedings, Melbourne, AGIFORS (1998).
[100] and , Capacity management for hospitality and tourism: a review of current approaches. Int. J. Hosp. Manag. 29 (2010) 177–187. | DOI
[101] , , , and , Forecasting uncertain hotel room demand. Inf. Sci. 132 (2001) 1–11. | DOI
[102] , Stochastic competitive entries and dynamic pricing. Eur. J. Oper. Res. 231 (2013) 381–392. | DOI | MR | Zbl
[103] and , A continuous-time dynamic pricing model knowing the competitor’s pricing strategy. Eur. J. Oper. Res. 229 (2013) 223–229. | DOI | MR | Zbl
[104] , Situational factors affecting forecast accuracy. J. Mark. Res. 21 (1984) 290–297. | DOI
[105] , , and , Production planning and pricing policy in a make-to-stock system with uncertain demand subject to machine breakdowns. Eur. J. Oper. Res. 238 (2014) 122–129. | DOI | MR | Zbl
[106] and , Dynamic pricing with uncertain production cost: an alternating-move approach. Eur. J. Oper. Res. 236 (2014) 218–228. | DOI | MR | Zbl
[107] , , , and , Revenue management under customer choice behaviour with cancellations and overbooking. Eur. J. Oper. Res. 246 (2015) 170–185. | DOI | MR | Zbl
[108] and , Integrated revenue management approaches for capacity control with planned upgrades. Eur. J. Oper. Res. 223 (2012) 380–391. | DOI | Zbl
[109] , and , Airline yield management with overbooking, cancellations and no-shows. Transp. Sci. 33 (1999) 147–167. | DOI | Zbl
[110] and , An analysis of bid-price controls for network revenue management. Manag. Sci. 44 (1998) 1577–1593. | DOI | Zbl
[111] and , A randomized linear programming method for computing network bid prices. Transp. Sci. 33 (1999) 207–216. | DOI | Zbl
[112] , and , Introduction to Revenue Management for the Hospitality Industry. Prentice Hall (2008).
[113] and , A multi-product dynamic pricing problem and its applications to network yield management. Oper. Res. 45 (1997) 24–41. | DOI | Zbl
[114] and , Revenue management, in Handbook of Transportation Science. Kluwer Academic Publishers (2003) 599–659. | DOI
[115] , and , The exploration of hotel reference prices under dynamic pricing scenarios and different forms of competition. Int. J. Hosp. Manag. 52 (2016) 46–55. | DOI
[116] , Unlocking the value of revenue management in the hotel industry. J. Revenue Pricing Manag. 3 (2004) 178–190. | DOI
[117] , A tutorial on optimization in the context of perishable-asset revenue management problems for the airline industry, in Operations Research in the Airline Industry. Kluwer Academic Publishers (1998) 68–100. | DOI
[118] , Optimization of perishable-asset revenue management problems that allow prices as decision variables. Int. J. Serv. Technol. Manag. 2 (2001) 71–101. | DOI
[119] and , A taxonomy and research overview of perishable-asset revenue management: yield management overbooking, and pricing. Oper. Res. 40 (1992) 831–843. | DOI
[120] and , A comparison of forecasting methods for hotel revenue management. Int. J. Forecast. 19 (2003) 401–415. | DOI
[121] , and , Forecasting for hotel revenue management: testing aggregation against disaggregation. Cornell Hotel Restaur. Adm. Q. 42 (2001) 53–64. | DOI
[122] , Airline O-D Control Using Network Displacement Concepts. Master’s thesis, MIT (1997).
[123] , Model Building in Mathematical Programming. John Wiley and Sons (1999). | Zbl
[124] , Airline Network Seatinventory Control: Methodologies and Revenue Impacts. Ph.D. thesis, MIT (1992).
[125] , , and , Revenue management: resolving potential customer conflicts. J. Revenue Pricing 3 (2003) 216–226. | DOI
[126] , Hub-spoke Seat Management Model. Tech. rep., Douglas Aircraft Company, McDonnell Douglas Corporation, Long Beach, CA (1986).
[127] , An airline seat management model for a single leg route when lower fare classes book first. Oper. Res. 40 (1992) 26–37. | DOI | Zbl
[128] , Dynamic pricing in airline seat management for flights with multiple flight legs. Trans. Sci. 33 (1999) 192–206. | DOI | Zbl
[129] , An integrated forecasting approach to hotel demand. Math. Comput. Model. 46 (2007) 1063–1070. | DOI
[130] , and , A comparative study of the pickup method and its variations using a simulated hotel reservation data. ICGST Int. J. Artif. Intel. Mach. Learn. 8 (2008) 15–21.
[131] , , and , Forecasting hotel arrivals and occupancy using Monte Carlo simulation. J. Revenue Pricing Manag. 10 (2011) 344–366. | DOI
[132] and , Fencing in the context of revenue management. Int. J. Rev. Manag. 4 (2010) 42–68.
[133] and , Assessing the value of dynamic pricing in network revenue management. INFORMS J. Comput. 25 (2013) 102–115. | DOI | MR
[134] and , Dynamic pricing for network revenue management: a new approach and application in the hotel industry. INFORMS J. Comput. 29 (2017) 18–35. | DOI | MR | Zbl
[135] and , Dynamic pricing with two revenue streams. Oper. Res. Lett. 40 (2012) 46–51. | DOI | MR | Zbl
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