Dynamic Revenue Management in Airline Alliances

  • Authors:

  • Christopher P. Wright;Harry Groenevelt;Robert A. Shumsky

  • Affiliations:

  • College of Business Administration, Niagara University, Niagara, New York 14109;Simon Graduate School of Business, University of Rochester, Rochester, New York 14627;Tuck School of Business, Dartmouth College, Hanover, New Hampshire 03755

  • Venue:
  • Transportation Science
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

Major airlines are selling increasing numbers of interline itineraries in which flights operated by two or more airlines are combined and sold together. One reason for this increase is the rapid growth of airline alliances, which promote the purchase of interline itineraries and, therefore, virtually extend the reach of each alliance member's network. This practice, however, creates a difficult coordination problem: Each member of the alliance makes revenue management decisions to maximize its own revenue and the resulting behavior may produce suboptimal revenue for the alliance as a whole. Airline industry researchers and consultants have proposed a variety of static and dynamic mechanisms to control revenue management decisions across alliances (a dynamic mechanism adjusts its parameters as the number of available seats in the network changes and time passes). In this paper, we formulate a Markov game model of a two-partner alliance that can be used to analyze the effects of these mechanisms on each partner's behavior. We begin by showing that no Markovian transfer pricing mechanism can coordinate an arbitrary alliance. Next, we examine three dynamic schemes as well as three forms of the static scheme widely used in practice. We derive the equilibrium acceptance policies under each scheme and use analytical techniques as well as numerical analyses of sample alliances to generate fundamental insights about partner behavior under each scheme. The analysis and numerical examples also illustrate how certain transfer price schemes are likely to perform in networks with particular characteristics.