Relationships between service quality and customer satisfaction in airlines: Evidence from SEM and ANN based on AIRQUAL model

Given the fierce competition in the airline industry, prioritising service quality is essential for airlines seeking sustainable success. This study aims to examine the influence of perceived service quality on customer satisfaction among Turkish air travellers, based on the AIRQUAL model. Data were collected via a self-administered questionnaire from 242 respondents, using volunteer sampling at Samsun Çarşamba Airport in Turkey. A multi-analytical approach, combining partial least squares structural equation modelling (PLS-SEM) and artificial neural network (ANN) modelling, was employed in the data analysis. The findings reveal that all five dimensions of AIRQUAL significantly and positively affect customer satisfaction. The ANN results further corroborate these findings, identifying image and airline tangibles as the strongest predictors of customer satisfaction based on relative importance.

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Publication Details

Journal
European Journal of Tourism Research
Published
2025-09-28
DOI
https://doi.org/10.54055/ejtr.v41i.4066
Primary Topic
Organizational and Employee Performance
Type
article
Field-Weighted Citation Impact
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article

Relationships between service quality and customer satisfaction in airlines: Evidence from SEM and ANN based on AIRQUAL model

Mahmut Bakır, M. Peters Kurt, Şahap Akan, İbrahim Naser Yousef Afaneh
European Journal of Tourism Research
Organizational and Employee Performance
article

Relationships between service quality and customer satisfaction in airlines: Evidence from SEM and ANN based on AIRQUAL model

Mahmut Bakır, M. Peters Kurt, Şahap Akan, İbrahim Naser Yousef Afaneh
article en

Abstract

Given the fierce competition in the airline industry, prioritising service quality is essential for airlines seeking sustainable success. This study aims to examine the influence of perceived service quality on customer satisfaction among Turkish air travellers, based on the AIRQUAL model. Data were collected via a self-administered questionnaire from 242 respondents, using volunteer sampling at Samsun Çarşamba Airport in Turkey. A multi-analytical approach, combining partial least squares structural equation modelling (PLS-SEM) and artificial neural network (ANN) modelling, was employed in the data analysis. The findings reveal that all five dimensions of AIRQUAL significantly and positively affect customer satisfaction. The ANN results further corroborate these findings, identifying image and airline tangibles as the strongest predictors of customer satisfaction based on relative importance.

European Journal of Tourism ResearchVol. 41
Dicle University (TR), Civil Aviation University of China (CN), Samsun University (TR)
Openalex Percentile: Top 86%
Organizational and Employee Performance
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