Forecasting annual European travel market from early data provided by ECM members

In a study conducted by ECM’s academic advisors, Prof. Karl Wöber and Dr. Irem Arsal (MODUL University Vienna), shows that annual European tourist bednights can be accurately predicted by using monthly data. In addition, annual forecasts are more accurate for the near rather than the distant future.

The study included different methods of forecasting to find out the most accurate forecasting method for predicting annual and monthly tourism demand in Europe based on statistics provided by ECM members on TourMIS. The sample data included 41 European cities and their monthly tourist bednight numbers for the years 2005 until 2009, which included 1,512 observations. Moreover, the data was adjusted for the influence of seasonality which is an important factor for many cities in Europe.

Figure 1. Amsterdam forecasting results

Overall, results indicate that forecasting annual values provides more accurate predictions than forecasting monthly values. For forecasting annual estimates, the study shows that the more complete the annual aggregated data is (i.e. the smaller the time lag for estimating the annual value), the better the forecast values. For instance, when we take into consideration Amsterdam, the average percentage error is less than 2% if five or less months are missing, and only starts increasing gradually after that time period. These can be seen in Figure 1, with the red columns. Estimating individual moths is much more difficult as shown by the blue bars in Figure 1. The average error for predicting monthly data in Amsterdam is between 4 and 7% and depends on how many months someone wants to look into the future.

Figure 2. Total foreign and domestic market forecasting results

The results were even more encouraging when the researchers examined the total number of bednights (foreign and domestic), for a sample of 41 ECM members regularly entering their monthly data into TourMIS (www.tourmis.info). The average percentage errors (MAPE) of annual estimates were less than 2% when only four months of data are available. Moreover, when predicting individual months, tourism managers are faced with an average error between 3 and 4%.

The relatively high accuracy of forecasting annual data based on preliminary monthly results encourages the ECM Benchmarking team to further develop and integrate forecasts in the ECM Annual Benchmarking report.
The results of this study were also presented to ten leading city tourism organizations in Europe.

For more information on the ECM Benchmarking report, please read www.europeancitiesmarketing.com

Contact:
Dr. Irem Arsal, MODUL University Vienna, Department of Tourism and Hospitality Management, Am Kahlenberg 1, 1190 Vienna, Austria
irem.arsal@modul.ac.at | www.modul.ac.at