Discrete choice modelling in airline network management

The task of airline network management is to develop new flight schedule variants and evaluate them in terms of expected passenger demand and revenue. Given the industry's trend towards global cooperation, this is especially important when evaluating the potential synergies with alliance partners. From the econometric point of view, this task represents a discrete choice modelling problem in which one has to account for a large number of dependent alternatives. In this paper we discuss the applicability of recently proposed approaches and introduce a new multinomial probit specification designed for the airline network management task. The superior performance of the new model is demonstrated in a real-world application using airline bookings data. Copyright © 2005 John Wiley & Sons, Ltd.

[1]  D. S. Bunch,et al.  Estimability in the Multinomial Probit Model , 1989 .

[2]  Paul A. Ruud,et al.  Simulation of multivariate normal rectangle probabilities and their derivatives theoretical and computational results , 1996 .

[3]  D. McFadden,et al.  The method of simulated scores for the estimation of LDV models , 1998 .

[4]  J. Horowitz Statistical comparison of non-nested probabilistic discrete choice models , 1983 .

[5]  C. Bhat Covariance heterogeneity in nested logit models: Econometric structure and application to intercity travel , 1997 .

[6]  D. Bolduc GENERALIZED AUTOREGRESSIVE ERRORS IN THE MULTINOMIAL PROBIT MODEL , 1992 .

[7]  Seiji Iwakura,et al.  Multinomial probit with structured covariance for route choice behavior , 1997 .

[8]  J. Horowitz RECONSIDERING THE MULTINOMIAL PROBIT MODEL , 1991 .

[9]  J. de D. Ortúzar,et al.  Fundamentals of discrete multimodal choice modelling , 1982 .

[10]  V. Hajivassiliou,et al.  Smooth unbiased multivariate probability simulators for maximum likelihood estimation of limited dependent variable models , 1993 .

[11]  K. Train Discrete Choice Methods with Simulation , 2003 .

[12]  D. Wise,et al.  A CONDITIONAL PROBIT MODEL FOR QUALITATIVE CHOICE: DISCRETE DECISIONS RECOGNIZING INTERDEPENDENCE AND HETEROGENEOUS PREFERENCES' , 1978 .

[13]  Daniel McFadden,et al.  Modelling the Choice of Residential Location , 1977 .

[14]  D. McFadden,et al.  MIXED MNL MODELS FOR DISCRETE RESPONSE , 2000 .

[15]  H. Williams On the Formation of Travel Demand Models and Economic Evaluation Measures of User Benefit , 1977 .

[16]  T. Bollerslev,et al.  Intraday periodicity and volatility persistence in financial markets , 1997 .

[17]  D. McFadden A Method of Simulated Moments for Estimation of Discrete Response Models Without Numerical Integration , 1989 .