Disaggregate behavioural airport choice models
thesisposted on 2020-01-03, 15:31 authored by Messaoud Benchemam
The identification of the distribution of air passengers among airports is an important task of the airport planner. It would be useful to understand how trip makers choose among competing airports. The ultimate purpose of this study is to research into , passengers' choice of airport so that the airport system can be planned on a more reliable basis. The choice of airport of passengers originating from central England in 1975 is explained by constructing multinomial disaggregate behavioural models of logit form. The data used for model calibration, were collected during two Civil Aviation Authority surveys. This work makes contribution to: -The definition of the major determinants of airport choice, -The responsiveness of passengers, choice to changes in these determinants, - The policy implications for the regional airports - The transferability of the model in time and space. The method of analysis has been selected after outlining the potential advantages and shortcomings of logit and probit models and after a test on the validity of the Independence from Irrelevant Alternatives (I.I.A.) property has been carried out. The results show that the multinomial logit model used for the airport choice is good in terms of its explanatory ability and successful in predicting the choices actually made. Travel time to the airport, frequency of flights and air fare are found to be decisive factors for a passenger to select a given airport but are not of equal importance. By influencing-these factors, it appears that there exists room for the transport planner to shift traffic from one airport to another to have an economically and/or environmentally efficient airport system. In their original form, the models have been tested and found not to be transferable to the London area in 1978. However, after a Bayesian updating procedure was applied, the business and inclusive tours models were transferable. The leisure model was not statistically transferable but had a good predictive ability while the domestic model was not transferable. Finally, subsequent directions ·for further research are outlined.
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering