A Comparative Analysis of Pickup Forecasting Methods for Customer Arrivals in Airport Carparks

Accurate forecasts of customer demand lie at the core of any successful revenue management system. Most research has focused upon studying such methods for the airline and hotel industry. In this paper, we present a comparative analysis of various forecasting methods which we apply to the rapidly evolving airport carparking (ACP) industry. We use real ACP booking data from four distinct carparks of a major airport in UK to forecast customer arrivals for one to eight weeks out in the future. Conclusions are reached with regards to which forecasting methods perform best in this operating environment, and whether there is any benefit in employing complex methods over simpler ones.

[1]  Robert H. Shumway,et al.  Time series analysis and its applications : with R examples , 2017 .

[2]  Joao Sa,et al.  Reservations forecasting in airline yield management , 1987 .

[3]  Irma J. Terpenning,et al.  STL : A Seasonal-Trend Decomposition Procedure Based on Loess , 1990 .

[4]  Sheryl E. Kimes,et al.  Forecasting for Hotel Revenue Management: Testing Aggregation Against Disaggregation , 2001 .

[5]  Larry Weatherford,et al.  Better unconstraining of airline demand data in revenue management systems for improved forecast accuracy and greater revenues , 2002 .

[6]  Sheryl E. Kimes,et al.  A comparison of forecasting methods for hotel revenue management , 2003 .

[7]  Anthony Owen Lee,et al.  Airline reservations forecasting--probabilistic and statistical models of the booking process , 1990 .

[8]  Rob J Hyndman,et al.  A state space framework for automatic forecasting using exponential smoothing methods , 2002 .

[9]  Rob J Hyndman,et al.  Automatic Time Series Forecasting: The forecast Package for R , 2008 .

[10]  Rob J Hyndman,et al.  Forecasting with Exponential Smoothing: The State Space Approach , 2008 .

[11]  Athanasius Zakhary,et al.  A Comparative Study of the Pickup Method and its Variations Using a Simulated Hotel Reservation Data , 2008 .

[12]  Andreas Papayiannis,et al.  Continuous-time Revenue Management in Carparks - Part Two: Refining the PDE , 2013, ICORES.

[13]  Andreas Papayiannis,et al.  Continuous-time Revenue Management in Carparks , 2012, ICORES.

[14]  Daniela A. Rojas Revenue management techniques applied to the parking industry , 2006 .

[15]  Steven C. Wheelwright,et al.  Forecasting methods and applications. , 1979 .

[16]  Richard Robert Wickham Evaluation of forecasting techniques for short-term demand of air transportation , 1995 .