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.

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.

Reçu le :
Accepté le :
DOI : 10.1051/ro/2018001
Classification : 90B50, 90B90, 90C90
Mots-clés : Revenue management, dynamic pricing, forecasting, optimization
Bandalouski, Andrei M. 1 ; Kovalyov, Mikhail Y. 1 ; Pesch, Erwin 1 ; Tarim, S. Armagan 1

1
@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://archive.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://archive.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://archive.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://archive.numdam.org/articles/10.1051/ro/2018001/

[1] G. Abrate and G. Viglia, Strategic and tactical price decisions in hotel revenue management. Tour. Manag. 55 (2016) 123–132. | DOI

[2] G. Abrate, G. Fraquelli and G. Viglia, Dynamic pricing strategies: evidence from European hotels. Int. J. Hosp. Manag. 31 (2012) 160–168. | DOI

[3] M. Anjos, R. Cheng and C. Currie, Optimal pricing policies for perishable products. Eur. J. Oper. Res. 166 (2005) 246–254. | DOI | Zbl

[4] J. Armstrong and F. Collopy, Error measures for generalizing about forecasting methods: Empirical comparisons. Int. J. Forecast. 8 (1992) 69–80. | DOI

[5] H. Aziz, M. Saleh, M. Rasmy and H. Elshishiny, Dynamic room pricing model for hotel revenue management systems. Egypt. Inf. J. 12 (2011) 177–183.

[6] R. Badinelli, An optimal, dynamic policy for hotel yield management. Eur. J. Oper. Res. 121 (2000) 476–503. | DOI | Zbl

[7] T. Baker and D. Collier, The benefits of optimizing prices to manage demand in hotel revenue management systems. Prod. Oper. Manag. 12 (2003) 502–518. | DOI

[8] P. Belobaba, Air Travel Demand and Airline Seat Inventory Management. Ph.D. thesis, MIT (1987).

[9] M. Ben-Akiva, Improving airline passenger forecasts using reservation data, in Fall ORSA/TIMS Conference, St. Louis (1987).

[10] D. Bertsimas and S. De Boer, Simulation-based booking limits for airline revenue management. Oper. Res. 53 (2005) 90–106. | DOI | Zbl

[11] D. Bertsimas and R. Shioda, Restaurant revenue management. Oper. Res. 51 (2003) 472–486. | DOI

[12] D. Besanko and W. Winston, Optimal price skimming by a monopolist facing rational consumers. Manag. Sci. 36 (1990) 555–567. | DOI | MR | Zbl

[13] G. Bitran and R. Caldentey, An overview of pricing models for revenue management. Manuf. Serv. Oper. Manag. 5 (2003) 203–229. | DOI

[14] G. Bitran and S. Monschein, An application of yield management to the hotel industry considering multiple day stays. Oper. Res. 43 (1995) 427–443. | DOI | Zbl

[15] G. Bitran and S. Mondschein, Periodic pricing of seasonal product in retailing. Manag. Sci. 43 (1997) 427–443. | Zbl

[16] E. Boyd and I. Bilegan, Revenue management and e-commerce. Manag. Sci. 49 (2003) 1363–1386. | DOI

[17] S. Brumelle and J. Mcgill, Airline seat allocation with multiple nested fare classes. Oper. Res. 41 (1993) 127–137. | DOI | Zbl

[18] E. Brynjolfsson and M. Smith, Frictionless commerce? A comparison of internet and conventional retailers. Manag. Sci. 46 (1999) 563–585. | DOI

[19] C. Burger, M. Dohnal, M. Kathrada and R. Law, 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] P. Cao, J. Li and H. Yan, Optimal dynamic pricing of inventories with stochastic demand and discounted criterion. Eur. J. Oper. Res. 217 (2012) 580–588. | DOI | MR | Zbl

[21] S. Carvell and D. Quan, Exotic reservations – low price guarantee. Int. J. Hosp. Manag. 27 (2008) 162–169. | DOI

[22] E. Casado and J.-C. Ferrer, 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] R. Chatwin, 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] Y. Chen and V.F. Farias, Simple policies for dynamic pricing with imperfect forecasts. Oper. Res. 61 (2013) 612–624. | DOI | MR | Zbl

[25] C. Chen and S. Kachani, Forecasting and optimisation for hotel revenue management. J. Revenue Pricing Manag. 6 (2007) 163. | DOI

[26] V. Chen, D. Gunther and E. Johnson, A Markov Decision Problem Based Approach to the Airline YM Problem. Tech. rep., Georgia Institute of Technology, The Logistics Institute (1998).

[27] J. Chen, J. Wang and P. Bell, Lease expiration management for a single lease term in the apartment industry. Eur. J. Oper. Res. 238 (2014) 233–244. | DOI | MR | Zbl

[28] Y. Chen, R. Levi and C. Shi, Revenue management of reusable resources with advanced reservations. Prod. Oper. Manag. 26 (2017) 836–859. | DOI

[29] W. Chiang, J. Chen and X. Xu, Overview of research on revenue management: current issues and future research. Int. J. Revenue Manag. 1 (2007) 97–128. | DOI

[30] W. Cooper and T.H. De Mello, A Class of Hybrid Methods for Revenue Management. Tech. rep., Northwestern University, Department of Industrial Engineering and Manag. Sci. (2003).

[31] R. Cross, Revenue Management. Broadway Books (1997).

[32] R. Curry, Optimal airline seat allocation with fare classes nested by origin and destinations. Transp. Sci. 24 (1990) 193–204. | DOI

[33] S. Dasu and C. Tong, Dynamic pricing when consumers are strategic: analysis of posted and contingent pricing schemes. Eur. J. Oper. Res. 204 (2010) 662–671. | DOI | Zbl

[34] S. De Boer, R. Freling and N. Piersma, Mathematical programming for network revenue management revisited. Eur. J. Oper. Res. 137 (2002) 72–92. | DOI | Zbl

[35] T. Demirciftci, C. Cobanoglu, S. Beldona and P. Cummings, Room rate parity analysis across different hotel distribution channels in the U.S. J. Hosp. Mark. Manag. 19 (2010) 295–308.

[36] K. Donaghy, U. Mcmahon and D. Mcdowell, Yield management: an overview. Int. J. Hosp. Manag. 44 (1995) 139–150. | DOI

[37] W. Elmaghraby and P. Keskinocak, Dynamic pricing in the presence of inventory considerations: research overview, current practices, and future directions. Manag. Sci. 49 (2003) 1287–1305. | DOI | Zbl

[38] M. Emeksiz, D. Gursoy and O. Icoz, A yield management model for five-star hotels: computerized and non-computerized implementation. Int. J. Hosp. Manag. 25 (2006) 536–551. | DOI

[39] Y. Feng and G. Gallego, Optimal starting times for end-of-season sales and optimal stopping times for promotional fares. Manag. Sci. 41 (1995) 1371–1391. | DOI | Zbl

[40] Y. Feng and G. Gallego, Perishable asset revenue management with Markovian time dependent demand intensities. Manag. Sci. 46 (2000) 941–956. | DOI | Zbl

[41] Y. Feng and B. Xiao, A continuous-time yield management model with multiple prices and reversible price changes. Manag. Sci. 48 (2000) 644–657. | DOI | Zbl

[42] Y. Feng and B. Xiao, Optimal policies of yield management with multiple predetermined prices. Manag. Sci. 48 (2000) 332–343.

[43] Y. Feng and B. Xiao, 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] Y. Feng and B. Xiao, Integration of pricing and capacity allocation for perishable products. Eur. J. Oper. Res. 168 (2006) 17–34. | DOI | MR | Zbl

[45] R. Fildes and K. Ord, Forecasting competitions – their role in improving forecasting practice and research, in A Companion to Economic Forecasting. Blackwell Publishing (2002) 322–353.

[46] C. Gaimon, Simultaneous and dynamic price, production, inventory and capacity decisions. Eur. J. Oper. Res. 35 (1988) 426–441. | DOI | MR

[47] G. Gallego and G. Van Ryzin, Optimal dynamic pricing of inventories with stochastic demand over finite horizons. Manag. Sci. 40 (1994) 999–1020. | DOI | Zbl

[48] F. Glover, R. Glover, J. Lorenzo and C. Mcmillan, The passenger mix problem in the scheduled airlines. Interfaces 12 (1982) 73–79. | DOI

[49] P. Goldman, R. Freling, K. Pak and N. Piersma, Models and techniques for hotel revenue management using a rolling horizon. J. Revenue Pricing Manag. 1 (2002) 207–219. | DOI

[50] X. Guo,L. Ling, C. Yang, Z. Li and L. Liang, 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] R.E. Haddad, A. Roper and P. Jones, 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] G. Hadjinicola and C. Panayi, The overbooking problem in hotels with multiple tour-operators. Int. J. Oper. Prod. Manag. 17 (1997) 874–885. | DOI

[53] R. Hanks, R. Cross and R. Noland, Discounting in the hotel industry, A new approach. Cornell Hotel Restaur. Adm. Q. 43 (2002) 94–103. | DOI

[54] S. Ivanov, Management of overbookings in the hotel industry – basic concepts and practical challenges. Tour. Today 6 (2006) 19–32.

[55] S. Ivanov, Dynamic overbooking limits for guaranteed and nonguaranteed hotel reservations. Tour. Today 7 (2007) 100–108.

[56] S. Ivanov, Hotel Revenue Management – From Theory to Practice. Zangador, Varna (2014).

[57] S. Ivanov and V. Zhechev, Hotel revenue management – a critical literature review. Tourism 60 (2012) 175–197.

[58] S. Jauncey, I. Mitchell and P. Slamet, The meaning and management of yield in hotels. Int. J. Contemp. Hosp. Manag. 4 (1995) 23–26. | DOI

[59] P. Jonesand D. Hamilton, Yield management: putting people in the big picture. Cornell Hotel Restaur. Adm. Q. 33 (1992) 89–96. | DOI

[60] D. Kahneman, J. Knetsch and R. Thaler, Fairness and the assumptions of economics. J. Bus. 76 (1986) 728–741.

[61] D. Kahneman, J. Knetsch and R. Thaler, Fairness as a constraint on profit seeking: entitlements in the market. Am. Econo. Rev. 76 (1986) 728–741.

[62] S. Kimes, Perceived fairness of yield management. Cornell Hotel Restaur. Adm. 35 (1994) 22–24. | DOI

[63] S. Kimes, Revenue management: a retrospective. Cornell Hotel Restaur. Adm. Q. 44 (2004) 131–138. | DOI

[64] S. Kimes and R. Chase, The strategic levers of yield management. J. Serv. Res. 1 (1998) 156–166. | DOI

[65] S. Kimes and J. Wirtz, 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] A. Kleywegt and J. Papastavrou, The dynamic and stochastic knapsack problem. Oper. Res. 46 (1998) 17–35. | DOI | MR | Zbl

[67] M. Koenig and J. Meissner, List pricing versus dynamic pricing: impact on the revenue risk. Eur. J. Oper. Res. 204 (2010) 505–512. | DOI | MR | Zbl

[68] T. Koide and H. Ishii, The hotel yield management with two types of room prices, overbooking and cancellations. Int. J. Prod. Econ. 93 (2005) 417–428. | DOI

[69] D. Koushik, J. Higbie and C. Eister, Retail price optimization at intercontinental hotels group. Interfaces 42 (2012) 45–47. | DOI

[70] C. Kwon, T. Freisz, R. Mookherjee and B.F.T. Yao, Non-cooperative competition among revenue maximizing service providers with demand learning. Eur. J. Oper. Res. 197 (2009) 981–996. | DOI | MR | Zbl

[71] S. Ladany, Optimal market segmentation of hotel rooms – the non-linear case. Omega 24 (1996) 29–36 | DOI

[72] S. Ladany and A. Arbel, Optimal cruise-liner passenger cabin pricing policy. Eur. J. Oper. Res. 55 (1991) 136–147. | DOI | Zbl

[73] K.-K. Lai and W.-L. Ng, A stochastic approach to hotel revenue optimization. Comput. Oper. Res. 32 (2005) 1059–1072. | DOI | MR | Zbl

[74] A. Lau and H. Lau, The newsboy problem with price dependent demand distribution. IIE Trans. 20 (1988) 168–175. | DOI

[75] O. Lee, Airline Reservations Forecasting: Probabilistic and Statistical Models of the Booking Process. Ph.D. thesis. Massachusetts Institute of Technology (1990). | MR

[76] T. Lee and M. Hersh, A model for dynamic airline seat inventory control with multiple seat bookings. Transp. Sci. 27 (1993) 252–265. | DOI

[77] R. Levi and C. Shi, Dynamic allocation problems in loss network systems with advanced reservation. Preprint (2015). | arXiv

[78] C. Lim and F. Chan, An econometric analysis of hotel-motel room nights in New Zealand with stochastic seasonality. Int. J. Revenue Manag. 5 (2011) 63–83. | DOI

[79] C. Lim, C. Chang and M. Mcaleer, Forecasting hotel guest nights in New Zealand. Int. J. Hosp. Manag. 28 (2009) 228–235. | DOI

[80] K. Lin, Dynamic pricing with real-time demand learning. Eur. J. Oper. Res. 174 (2006) 522–538 | DOI | Zbl

[81] K. Lin and S. Sidbari, Dynamic price competition with discrete customer choices. Eur. J. Oper. Res. 197 (2009) 969–980. | DOI | MR | Zbl

[82] K. Littlewood, Forecasting and control of passenger bookings, in AGIFORS Symposium Proc. 12, Nathanya (1972).

[83] S. Liu, K. Lai, J. Dong and S. Wang, A stochastic approach to hotel revenue management considering multiple-day stays. Int. J. Inf. Technol. Decision Mak. 5 (2006) 545–556. | DOI

[84] S. Liu, K. Lai and S. Wang, Booking models for hotel revenue management considering multiple-day stays. Int. J. Revenue Manag. 2 (2008) 78–91. | DOI

[85] B. Maddah, L. Moussawi-Haidar, M. El-Taha and H. Rida, Dynamic cruise ship revenue management. Eur. J. Oper. Res. 207 (2010) 445–455. | DOI | MR | Zbl

[86] S. Makridakis, A. Andersen, R. Carbone, R. Fildes, M. Hibon, R. Lewandowski, et al. The accuracy of extrapolation (time series) methods: results of a forecasting competition. J. Forecast. 1 (1982) 111–153. | DOI

[87] J. Mcgill and G. Van Ryzin, Revenue management: research overview and prospects. Transp. Sci. 33 (1999) 233–256. | DOI | Zbl

[88] J. Meissner and A. Strauss, Improved bid prices for choice-based network revenue management. Eur. J. Oper. Res. 217 (2012) 417–427. | DOI | MR | Zbl

[89] J. Meissner and A. Strauss, Network revenue management with inventory-sensitive bid prices and customer choice. Eur. J. Oper. Res. 216 (2012) 459–468. | DOI | MR | Zbl

[90] S. Netessine and R. Shumsky, Introduction to the theory and practice of yield management. INFORMS Trans. Edu. 3 (2002) 34–44. | DOI

[91] I. Ng, A demand-based model for the advance and spot pricing of services. J. Prod. Brand Manag. 18 (2009b) 517–528. | DOI

[92] Y. Nguyen, 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] C. Özkan, F. Karaesmen and S. Özekici, Structural properties of Markov modulated revenue management problems. Eur. J. Oper. Res. 225 (2013) 324–331. | DOI | MR | Zbl

[94] S. Padhi and V. Aggarwal, Competitive revenue management for fixing quota and price of hotel commodities under uncertainty. Int. J. Hosp. Manag. 30 (2011) 725–734. | DOI

[95] K. Pak and N. Piersma, Airline Revenue Management: an Overview of OR Techniques 1982–2001. Tech. rep., Erasmus University Rotterdam (2002). | MR

[96] A. Palmer, U. Mcmahon-Beattie, Variable pricing through revenue management: a critical evaluation of affective outcomes. Manag. Res. News 31 (2008) 189–199. | DOI

[97] P. Pekgun, R.P. Menich, S. Acharya, P.G. Finch, F. Deschamps, K. Mallery, et al. Carlson Rezidor hotel group maximizes revenue through improved demand management and price optimization. Interfaces 43 (2013) 21–36. | DOI

[98] N. Phumchusri and P. Mongkolkul, 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] S. Pölt, Forecasting is difficult – especially if it refers to the future, in Reservations and Yield Management Study Group Annual Meeting Proceedings, Melbourne, AGIFORS (1998).

[100] M. Pullman and S. Rogers, Capacity management for hospitality and tourism: a review of current approaches. Int. J. Hosp. Manag. 29 (2010) 177–187. | DOI

[101] M. Rajopadhye, M. Ghalia, P. Wang, T. Baker and C. Eister, Forecasting uncertain hotel room demand. Inf. Sci. 132 (2001) 1–11. | DOI

[102] O. Rubel, Stochastic competitive entries and dynamic pricing. Eur. J. Oper. Res. 231 (2013) 381–392. | DOI | MR | Zbl

[103] K. Sato and K. Sawaki, A continuous-time dynamic pricing model knowing the competitor’s pricing strategy. Eur. J. Oper. Res. 229 (2013) 223–229. | DOI | MR | Zbl

[104] S. Schnaars, Situational factors affecting forecast accuracy. J. Mark. Res. 21 (1984) 290–297. | DOI

[105] X. Shi, H. Shen, T. Wu and T. Cheng, 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] S. Sibdari and D. Pyke, Dynamic pricing with uncertain production cost: an alternating-move approach. Eur. J. Oper. Res. 236 (2014) 218–228. | DOI | MR | Zbl

[107] D.D. Sierag, G.M. Koole, R. Van Der Mei, J.I. Van Der Rest and B. Zwart, Revenue management under customer choice behaviour with cancellations and overbooking. Eur. J. Oper. Res. 246 (2015) 170–185. | DOI | MR | Zbl

[108] C. Steinhardt and J. Gönsch, Integrated revenue management approaches for capacity control with planned upgrades. Eur. J. Oper. Res. 223 (2012) 380–391. | DOI | Zbl

[109] J. Subramanian, J. Stidham and C. Lautenbacher, Airline yield management with overbooking, cancellations and no-shows. Transp. Sci. 33 (1999) 147–167. | DOI | Zbl

[110] K. Talluri and G. Van Ryzin, An analysis of bid-price controls for network revenue management. Manag. Sci. 44 (1998) 1577–1593. | DOI | Zbl

[111] K. Talluri and G. Van Ryzin, A randomized linear programming method for computing network bid prices. Transp. Sci. 33 (1999) 207–216. | DOI | Zbl

[112] K. Tranter, T. Stuart-Hill and J. Parker, Introduction to Revenue Management for the Hospitality Industry. Prentice Hall (2008).

[113] G. Van Ryzin and G. Gallego, A multi-product dynamic pricing problem and its applications to network yield management. Oper. Res. 45 (1997) 24–41. | DOI | Zbl

[114] G. Van Ryzin and K.T. Talluri, Revenue management, in Handbook of Transportation Science. Kluwer Academic Publishers (2003) 599–659. | DOI

[115] G. Viglia, A. Mauri and M. Carricano, 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] B. Vinod, Unlocking the value of revenue management in the hotel industry. J. Revenue Pricing Manag. 3 (2004) 178–190. | DOI

[117] L. Weatherford, 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] L. Weatherford, Optimization of perishable-asset revenue management problems that allow prices as decision variables. Int. J. Serv. Technol. Manag. 2 (2001) 71–101. | DOI

[119] L. Weatherford and S. Bodily, A taxonomy and research overview of perishable-asset revenue management: yield management overbooking, and pricing. Oper. Res. 40 (1992) 831–843. | DOI

[120] L. Weatherford and S. Kimes, A comparison of forecasting methods for hotel revenue management. Int. J. Forecast. 19 (2003) 401–415. | DOI

[121] L. Weatherford, S. Kimes and D. Scott, Forecasting for hotel revenue management: testing aggregation against disaggregation. Cornell Hotel Restaur. Adm. Q. 42 (2001) 53–64. | DOI

[122] Y. Wei, Airline O-D Control Using Network Displacement Concepts. Master’s thesis, MIT (1997).

[123] H. Williams, Model Building in Mathematical Programming. John Wiley and Sons (1999). | Zbl

[124] E. Williamson, Airline Network Seatinventory Control: Methodologies and Revenue Impacts. Ph.D. thesis, MIT (1992).

[125] J. Wirtz, S. Kimes, J. Theng and P. Patterson, Revenue management: resolving potential customer conflicts. J. Revenue Pricing 3 (2003) 216–226. | DOI

[126] R. Wollmer, Hub-spoke Seat Management Model. Tech. rep., Douglas Aircraft Company, McDonnell Douglas Corporation, Long Beach, CA (1986).

[127] R. Wollmer, 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] P. You, Dynamic pricing in airline seat management for flights with multiple flight legs. Trans. Sci. 33 (1999) 192–206. | DOI | Zbl

[129] S. Yüksel, An integrated forecasting approach to hotel demand. Math. Comput. Model. 46 (2007) 1063–1070. | DOI

[130] A. Zakhary, N.E. Gayar and A. Atiya, 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] A. Zakhary, A. Atiya, H. El-Shishiny and N.E. Gayar, Forecasting hotel arrivals and occupancy using Monte Carlo simulation. J. Revenue Pricing Manag. 10 (2011) 344–366. | DOI

[132] M. Zhang and P. Bell, Fencing in the context of revenue management. Int. J. Rev. Manag. 4 (2010) 42–68.

[133] D. Zhang and Z. Lu, Assessing the value of dynamic pricing in network revenue management. INFORMS J. Comput. 25 (2013) 102–115. | DOI | MR

[134] D. Zhang and L. Weatherford, 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] W. Zhuang and M. Li, Dynamic pricing with two revenue streams. Oper. Res. Lett. 40 (2012) 46–51. | DOI | MR | Zbl

Cité par Sources :