Volltext-Downloads (blau) und Frontdoor-Views (grau)
  • search hit 3 of 13
Back to Result List

Modelling Passenger Behaviour in Airline Network Design

  • Although the market share of a specific airline is very often a rough estimation, it is still of great importance for the airline top management. In order to make the right strategic decision, management should be aware of its current position and its competitors. This information is important to decide on the airline’s fleet assignment, revenue management and planning and scheduling. A variety of different models exists for market size and market share forecasting. Since no single model provides accuracy, airlines usually combine and compare the results of different approaches. Generally speaking, market share can be estimated using different starting parameters, such as flight frequency, fare, quality of service, number of airplane’s seats, time of departure, etc. The market share depends also on its competitors’ strategy and current economic situation. As it is almost impossible to take into consideration all these parameters in one model, different techniques very often provide different results, and it is the task of the airline network planners to calibrate and validate the model. In this Master Thesis I consider market share as a parameter whose value is between 0 and 1 and which is calculated as a ratio of passengers travelled by a specific airline to a total number of passengers travelled between a given pairs of cities. This Master Thesis presents two objectives. First, it gives an introduction to the history of the airline industry. It analyzes the main factors affecting the demand, gives and overview of the airline network management and presents the most popular models for market size and share forecasting. Second, it estimates the airlines’ market shares for a given set of city pairs for 2013 and 2014 and finds the formula which can be used for future network planning. The estimation is conducted using the Multinomial Logit (MNL) model.

Export metadata

Additional Services

Search Google Scholar

Statistics

frontdoor_oas
Metadaten
Author:Maria Akbulatova
Advisor:Rütger Conzelmann
Document Type:Master's Thesis
Language:English
Year of Completion:2016
Granting Institution:Hochschule Furtwangen
Date of final exam:2016/02/29
Release Date:2016/06/02
Degree Program:MBA - International Business Management
Licence (German):License LogoUrheberrechtlich geschützt