[PEREZGONZALEZ Jose D (2011). Prediction of Skytrax airport rankings, short formula (2011) (2e)4. Journal of Knowledge Advancement & Integration (ISSN 1177-4576), 2012, pages 204-208.] [Printer friendly] [YouTube channel] [Screenr channel]
Prediction of airport rankings for 2011
Perezgonzalez continued a previous study by Perezgonzalez and Gilbey (20102), attempting to predict Skytrax's 2011 Official World Airport Star rankings from average ratings that passengers had given to those airports, independently, on Skytrax's website. The regression formula was based on a single variable, the average 'Customer review scoring', which is a cumulative average of past ratings, including those given during 2011.
The short regression formula for predicting Skytrax's 2011 ranking was:
|Predicted Skytrax Ranking = 0.711 + (0.410 * Customer review scoring)|
|(F = 27.264, p = 0.00; R = 0.715; R2 = 0.512; Adj.R = 0.702; Adj.R2 = 0.493)|
Table 1 shows the actual ranking given by Skytrax, the predicted 'ranking' obtained from above formula, the customer average rating used as predictor and the same customer average rating adjusted to a scale ranging between 1 and 5 in order to facilitate comparisons with the other scores. Overall, 72% of the airports could be ranked in approximately the same hierarchy than the one provided by Skytrax. Furthermore, it may be possible to also rank correctly 70% of the remaining airports not ranked by Skytrax (adj.R).
|Table 1. Predicted and actual scores|
|Kuala Lumpur International||6.60||3.64||3.42||4.00|
|(The 'Customer (adj)' column shows customer scores on a 1-5 scale, thus facilitating comparisons with the other variables)|
The regression formula obtained in this study is relatively similar to that obtained in 2010. In order to ascertain how fit these formulas may be to predict future Skytrax airport rankings, a simulation was carried out in order to predict the 2011 ranking using the 2010 formula. A good correlation between the results of the simulation and the 2011 prediction could then be taken as evidence in support of such fit. A low correlation could be taken as evidence against such fit.
Table 2 collates the predictions made for 2010 (using the 2010 formula, see Perezgonzalez, 2010 1), for 2011 (using the 2011 formula), and the results of the simulation predicting 2011 ranking using the 2010 formula. The correlation between the 2010 ranking and the simulation ranking was 98% (r=0.98), while there was a perfect positive correlation between the 2011 ranking and the simulation ranking (r=1.00).
|Table 2. Predicted scores for 2010, 2011 using 2010 formula, and 2011|
|Airport||2010 prediction||Simulation||2011 prediction|
|Kuala Lumpur International||3.52||3.44||3.42|
|(The simulation column shows the predicted ranking for 2011 when using the 2010 formula)|
Jose D PEREZGONZALEZ (2012). Massey University, Turitea Campus, Private Bag 11-222, Palmerston North 4442, New Zealand. (JDPerezgonzalez).
Nicholas ASHLEY (2012). School of Aviation, Massey University, New Zealand (NickAshley).
Want to know more?
- Journal of Airport Management - Perezgonzalez et al's (2010) article
- This article describes an alternative regression formula which predicts Skytrax's airport ranking using three 2010-based variables as predictors. The article is, PEREZGONZALEZ Jose D & Andrew GILBEY (2010). Predicting Skytrax’s airport rankings from customer reviews. Journal of Airport Management (ISSN 1750-1938), 2011, volume 5, number 4, pages 335-339.
- Skytrax's website
- Skytrax offers the latest rankings for airports and airlines, as well as independent reviews of those by passengers.
- Wiki of Science - Skytrax's 2010 airport rankings
- Perezgonzalez et al's (2010) article expanded with actual data and predicted scores per airport.