Stochastic Evaluation of Capacity and Demand Management of the Supply Chain of Airline Industry: The Case of Airlines of the AEA for Flights of Europe-Africa



Stochastic Evaluation of Capacity and Demand Management of the Supply Chain of Airline Industry: The Case of Airlines of the AEA for Flights of Europe-Africa

Authors

Yohannes Yebabe Tesfay, Molde Univeristy College, Getnet Yetagesu Metaferia, Unity University

Description

This tried to investigate the autocorrelation structure of the load factor of the AEA for flights of Europe - North Africa and Europe- Sub Saharan Africa. Finally, we to use dynamic time effect panel data model to forecast the load factor.

Abstract

In a supply chain of the airline industry the term load factor is defined as the percentage of seats filled by revenue passengers and is used to measure efficiency and performance. This metric evaluates the airlines capacity and demand management. The magnitude of the load factor of the given airline directly reflects the competency of that airline. Therefore, it is thought-provoking to examine factors that are potentially affecting the load factor of the airline. This paper applies stochastic models to investigate the autocorrelation structure of the load factor of the Association European Airlines for flights of Europe - North Africa and Europe- Sub Saharan Africa. The estimation result prevails that the airlines have better demand management than in the flights of Europe- Sub Saharan Africa but not in the flight of Europe - North Africa. The capacity management of the airlines is poor for both regional flights. The autocorrelation structures for the load factor for both regional flights have both periodic and serial correlations. Consequently, the use of ordinal panel data models is inappropriate for realistic model of load factor. Therefore, in order to control for the periodic correlation structure we introduce dynamic time effect in the model. Furthermore, in order to eliminate serial correlation we apply the Prais–Winsten methodology to fit the model. Finally, we build realistic and robust forecasting model of the load factor of the Europe- North Africa and Europe-Sub Saharan Africa flights
Keywords: AEA, Airlines Supply chain, Load factor, Spectral density estimation, dynamic
time effect panel data model.

Publisher

Association for European Transport