Passenger Satisfaction in European Airports

Yavuz, Nevin; Olgaç, Serkan; Aktaş, Semra Günay; Kantar, Yeliz Mert

doi:10.1007/978-981-10-7068-6_14

Cited by 6 publications

(10 citation statements)

References 34 publications

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“…First, the results from MRA reveal that; a. queuing times, b. terminal cleanliness, c. terminal seating, d. terminal signs, e. food and beverages, and f. airport staff have positive effects on passenger satisfaction (a. β = 0.206, p < 0.001; b. β = 0.068, p = 0.001; c. β = 0.158, p < 0.001; d. β = 0.137, p < 0.001; e. β = 0.073, p < 0.01; f. β = 0.350, p < 0.001). These findings are also in line with that of previous research [31,34,45,52,56]. Surprisingly, airport shopping and airport Wi-Fi connectivity have no significant effect on passenger satisfaction (β = 0.031, p > 0.173, β = 0.026, p > 0.148).…”

Section: Complementary Analysis For Post-covid-19 Periodsupporting

confidence: 92%

“…Airport operators should strive to keep queueing times to a minimum, as longer queueing times have a negative impact on ASQ. Yavuz [45] stated in this regard that queueing times are critical for achieving overall passenger satisfaction. Moreover, queuing time is found to be one of the most influential factors on satisfaction [46,47].…”

Section: Research Hypothesesmentioning

confidence: 99%

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How to Achieve Passenger Satisfaction in the Airport? Findings from Regression Analysis and Necessary Condition Analysis Approaches through Online Airport Reviews

et al. 2022

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Delivering high-quality service to passengers can be critical for an airport’s survival, competitiveness, profitability, and long-term growth in a highly competitive environment. The present study aims to examine the relationship between airport service attributes and passenger satisfaction. To this end, we conducted multi-method research consisting of symmetric (multiple regression analysis—MRA) and asymmetric (necessary condition analysis—NCA) approaches. The research data consists of 1463 valid online reviews (n = 1463) of the top 50 busiest airports in Europe retrieved from Skytrax. The MRA was employed to examine the net effect of the eight airport service attributes on passenger satisfaction, while the NCA was used to explore the necessary conditions and level of necessity to achieve passenger satisfaction. Using MRA, the findings reveal that airport staff is the most influential predictor of passenger satisfaction, whereas airport shopping and airport Wi-Fi connectivity do not have a significant effect on passenger satisfaction. Moreover, the NCA results found that six of the eight conditions are necessary to achieve passenger satisfaction at the airport. To complement and comprehend the findings, this study also sheds light on the antecedents underlying airport passenger satisfaction in the post-COVID-19 era using NCA.

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Section: Complementary Analysis For Post-covid-19 Periodsupporting

confidence: 92%

Section: Research Hypothesesmentioning

confidence: 99%

How to Achieve Passenger Satisfaction in the Airport? Findings from Regression Analysis and Necessary Condition Analysis Approaches through Online Airport Reviews

et al. 2022

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“…In particular, queuing time has been the most important factor affecting overall satisfaction at airports. Yavuz et al (2020) revealed the general satisfaction of the 100 airports with the highest number of passengers in Europe using Skytrax data and explained the general satisfaction level with other satisfaction levels. In the research, airport ownership, seating capacity, cleaning, queuing time, and the number of passengers was determined as variables that explain general satisfaction.…”

Section: Literature Reviewmentioning

confidence: 96%

Tourist satisfaction with American continent airports

Aktaş

Yavuz

et al. 2021

Journal of Multidisciplinary Academic Tourism

Self Cite

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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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“…This method offers a structured approach to gathering specific insights into various aspects of the airport experience. (2) Scraping data from user-generated online content (UGC), i.e., social media platforms and review websites such as Google Maps [4][5][6], TripAdvisor [7,8], Twitter [9,10], Skytrax [11][12][13][14][15][16][17][18][19][20][21], and airports' social media channels [22]. Recently, Abouseada, Hassan [23] conducted quantitative analysis of data extracted from the Skytrax, TripAdvisor, Traveler, and Flight Report platforms.…”

Section: User-generated Online Contentmentioning

confidence: 99%

“…Recent advancements in the study of airport service quality have incorporated big data and user-generated online content (UGC), offering authentic and diverse perspectives. Researchers have turned to platforms such as Google Maps [4][5][6], TripAdvisor [7,8], Twitter [9,10], Skytrax [11][12][13][14][15][16][17][18][19][20][21], and airports' social media channels [22] for service quality analysis. A recent study by Abouseada, Hassan [23] employed a quantitative content analysis approach to examine data from various travel platforms, including Skytrax, Tri-pAdvisor, Traveler, and Flight Reports.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid MRA-BN-NN Approach for Analyzing Airport Service Based on User-Generated Contents

Pholsook,

Wipulanusat,

Ratanavaraha

2024

Sustainability

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As the world transitions from the COVID-19 pandemic to a new normal, the Airports Council International (ACI) has disclosed that the Asia-Pacific region is lagging other regions in terms of air traffic recovery. This research comprehensively examines passenger satisfaction at leading airports in Southeast Asia. A multimethod approach incorporating multiple regression analysis, Bayesian networks, and neural network analysis was utilized to scrutinize user-generated content from Skytrax. The study contemplates eight distinct attributes of airport customer ratings: queuing time, cleanliness, seating areas, signage, food services, retail options, Wi-Fi availability, and staff courtesy. The findings reveal that queuing time and staff courtesy are the most important factors influencing the overall airport service rating. These results provide empirical evidence supporting the enhancement of airport services in the region and contribute significantly to the theoretical understanding and managerial implications for airport management and authorities. This research thus offers a valuable resource for improving service quality and operational efficiency in the airport industry, which could lead to a recovery and increase in the number of air passengers in this region.

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Passenger Satisfaction in European Airports

Cited by 6 publications

References 34 publications

How to Achieve Passenger Satisfaction in the Airport? Findings from Regression Analysis and Necessary Condition Analysis Approaches through Online Airport Reviews

How to Achieve Passenger Satisfaction in the Airport? Findings from Regression Analysis and Necessary Condition Analysis Approaches through Online Airport Reviews

Tourist satisfaction with American continent airports

A Hybrid MRA-BN-NN Approach for Analyzing Airport Service Based on User-Generated Contents

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