Prediction of Skytrax airport rankings, short formula (2e) - 2010

[PEREZGONZALEZ Jose D (2010). Prediction of Skytrax airport rankings, short formula (2e)4. Journal of Knowledge Advancement & Integration (ISSN 1177-4576), 2012, pages 200-203.] [Printer friendly] [YouTube channel] [Screenr channel]

# Prediction of airport rankings

Perezgonzalez & Gilbey (2010a2) obtained a regression formula for predicting Skytrax's 2010 airport rankings from customer reviews. The research behind the study attempted to predict Skytrax's 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 simpler formula to calculate but also less contemporary than that described in Perezgonzalez & Gilbey (2010b3).

The short regression formula for predicting Skytrax's 2010 ranking was:

Predicted Skytrax Ranking = 0.686 + (0.417 * Customer review scoring)
(F = 13.140, p < 0.01; R = 0.672; R2 = 0.451; Adj.R = 0.646; Adj.R2 = 0.417)

Table 1 shows the actual ranking given by Skytrax, the predicted 'ranking' obtained from above formula, as well as the customer average rating used as predictor. Overall, 67% of the research airports could be ranked in approximately the same hierarchy than the one provided by Skytrax. Furthermore, it may be possible to also rank correctly 65% of the remaining airports not ranked by Skytrax (adj.R).

Although an accuracy of 65%-67% is probably too low for dependable predictions (after all, the ranking of 33%-35% of airports will not be predicted well), these results suggest the possibility of using customer reviews as proxies for estimating the quality of those airports not "officially" ranked by Skytrax.

Table 1. Predicted and actual scores
Airport Customer Customer (adj) Predicted Skytrax
Seoul Incheon 9.20 4.68 4.52 5.00
Singapore Changi 8.30 4.32 4.15 5.00
Hong Kong 8.70 4.48 4.31 5.00
Zurich 8.10 4.24 4.06 4.00
Kuala Lumpur 6.80 3.72 3.52 4.00
Amsterdam 7.10 3.84 3.65 4.00
Beijing 7.70 4.08 3.90 4.00
Frankfurt 6.20 3.48 3.27 4.00
London Heathrow 7.70 4.08 3.90 3.00
Bangkok Suvarnabhumi 7.30 3.92 3.73 3.00
Johannesburg 7.20 3.88 3.69 3.00
Doha 7.50 4.00 3.81 3.00
Abu Dhabi 5.70 3.28 3.06 3.00
Sydney 5.60 3.24 3.02 3.00
Madrid Barajas 6.70 3.68 3.48 3.00
Bahrain 7.00 3.80 3.61 3.00
Dubai 5.00 3.00 2.77 3.00
Kuwait 4.50 2.80 2.56 3.00
(The 'Customer (adj)' column shows customer scores on a 1-5 scale, thus facilitating comparisons with the other variables)

## Author

Jose D PEREZGONZALEZ (2011). Massey University, Turitea Campus, Private Bag 11-222, Palmerston North 4442, New Zealand. ().

## Peer-reviewers

Nicholas ASHLEY (2011). School of Aviation, Massey University, New Zealand ().
Matt BIRCHALL (2011). School of Aviation, Massey University, New Zealand ().

# Want to know more?

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 2011 airport rankings
This Wiki of Science page offers information about a similar study done in 2011.

 Other interesting sites
page revision: 49, last edited: 21 Jul 2012 01:14