Forecasting The Passenger Traffic Movement In Lufthansa Airlines: A Supply Chain Perspective | Aniruddh Kr Singh & Debadyuti Das

The present paper attempts to find out the forecasted passenger traffic movement of Lufthansa Airlines on quarterly basis at a global level by employing four forecasting methods namely moving average, exponential smoothing, Holt’s model and Winter’s model with the help of published data pertaining to passenger traffic movement of Lufthansa Airlines. The study has also found out the forecasting errors of all the four methods through Absolute error (AE), Mean squared error (MSE), Mean absolute deviation (MAD) and Mean absolute percentage error (MAPE). The study also carried out the comparative analyses of the above forecasting methods in the light of the vailable data. The findings reveal that the forecasting errors are the least in case of Winter’s model. Further the forecasted values suggested by Winter’s model more closely resemble the observed data of passenger traffic movement of Lufthansa Airlines. This provides a valuable insight to the top management as regards formulation of suitable strategies for addressing the varying demand of passenger traffic movement. Few strategies in respect of both demand side and supply side options have been suggested with a view to improving the overall supply chain profit of Lufthansa Airlines.