A polyhedral graph theory approach to revenue management in the airline industry

A Dynamic Pricing Model for a Maritime Transportation Service Provider

“…Random part of the utility which can not be observed by the researcher is identified as a mean-zero random component j ξ . Thus, the overall utility is formulated as (1).…”

“…Revenue management is a business principle that balances supply and demand to control price and/or inventory availability in order to maximize revenue and profit growth 1 . Although its impact depends on the size of the company and the complexity of its operations, an estimate of 2±10% in revenue increase has been directly attributed with revenue management 2 .…”

“…In a recent study, a Markov decision process formulation of a dynamic pricing problem for multiple substitutable flights between the same origin and destination has been developed taking into account customer choice among the flights 3 . The bulk of the published literature on revenue management in the transport industry deals with the airline industry 1,3,9,10,11 . However, the application of the principles of revenue management in railway industry has also been investigated in the literature.…”

“…Both revenue management and dynamic pricing models need to characterize the demand. Studies commonly propose Gamma, Normal shapes and Poisson function for demand distributions 1,14,9,3 . On the other hand, some of the studies make some assumptions for modeling demand under different price levels based on previous data 14,17,13,9 , some use price elasticity functions derived from previous data 12,11 .…”

Competitive revenue management for fixing quota and price of hotel commodities under uncertainty

“…The service industry has been a popular area of RM research for many researchers over the last two decades, and, in particular, researchers have applied RM in capacity-constrained service industries. For Example, Orkin (1988), Kimes (1989a), Brotherton and Mooney (1992), Weatherford and Kimes (2001), and Harewood (2006) have used the concepts of revenue management in the hospitality sector, Kimes (1989b) in healthcare, Goulding and Leask (1997) and Heo and Lee (2009) in theme parks, Hoseason and Johns (1998) in cruise lines, Noone and Mattila (2009), Guadix et al (2010) in hotel industry, Kasilingam (1997), Kuyumcu and Garcia-Diaz (2000), Gorin and Belobaba (2004), Luo and Peng (2007), Lindenmeier and Tscheulin (2008) in airline industry, Bharill and Rangaraj (2008) in railways, and Tsai and Hung (2009) in Internet retailing. Although extensive literature is available on applications of RM practices in various service industries, the literature is scanty, however, in the field of RM under uncertainty for fixing of quota and price of hotel commodities, where it is difficult to handle RM under stochastic market conditions i.e., uncertain customer demand, customer preferences, and commodity price.…”