Abstract:

Tourist satisfaction is very important in terms of destination loyalty as revisit and recommendation intentions. The development of airline transportation has led to an increase in the average time spent by tourists during the destination process by shortening the transportation time. The purpose of this study is to determine the spatial distribution of passenger satisfaction levels at airports in the Americas. For this purpose, data for determining tourist satisfaction has been obtained from two different platforms. In order to determine the general satisfaction level at the airports, the data of 904 airports where 30 or more users made comments were taken into consideration in the google map database. Satisfaction distribution and clustering regarding airports were evaluated with the data obtained from Google. Mapping analysis was conducted using the spatial analysis method to determine the satisfaction levels of the tourists. MapInfo 16 program was used for mapping analysis. Satisfaction levels from American airports vary between 2.5 and 4.7. In addition, whether the airport satisfaction is spatial autocorrelation has been tested using the GeoDa program. Analyzes have revealed that airport satisfaction creates spatial autocorrelation in America. It is observed that satisfaction is high in airports in the east and west of North America and low in the middle parts. Satisfaction for Central America has been found to be high in the west of the continent and low in the east. Satisfaction levels for South America are high in the northeast, northwest, and also southwest coasts, while it is low in other parts. This situation shows that airports located in certain regions of the continent have similar characteristics. Skytrax data were used to determine the variables affecting satisfaction at airports. Because there is no statistical difference between the general satisfaction values obtained from Skytrax and google platforms. In the study, the data of 58 airports, which are 30 or more evaluated in the Skytrax database, were used. Accordingly, the variables affecting general satisfaction were explained by airport cleanliness, seating capacity, and waiting times. In addition, it was determined that the independent variable that affects satisfaction the most is the waiting time in the queue. This situation shows that measures should be taken to reduce the waiting time in the queue to increase satisfaction at airports. As a result, it is important to determine tourist satisfaction, to evaluate the quality of current practices, and to identify improvement aspects. High overall satisfaction at airports will increase the likelihood of tourists to reuse these airports and recommend them to other passengers, and will positively affect destination loyalty.

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