Mapping Customer Reviews into AIRQUAL to Evaluate Service Quality and Customer Satisfaction: Empirical Evidence from EgyptAir

In today's competitive environment, organizations are constantly striving to improve quality in order to retain customers and promote loyalty. This study investigates the perceived service quality of EgyptAir, mapping the AIRQUAL dimensions to TripAdvisor ratings for the period from 2016 to 2025. Additionally, the research examines the relationship between overall customer satisfaction and the airline’s financial performance. To test the hypotheses, the research relied on large-scale processing of review data, mapping eight service attributes extracted from customer reviews to the five AIRQUAL dimensions. Descriptive analytics, including annual trends and distributional statistics, were employed, as well as statistical analyses such as Pearson’s correlations and Multiple Linear Regressions.Descriptive analysis revealed distinct temporal patterns in service perceptions aligned with the pandemic and recovery phases. Correlation and regression analyses indicate that AIRQUAL composite scores are significantly and positively related to overall satisfaction. Multiple regression analysis indicated that different dimensions of AIRQUAL account for a substantial portion of the variance in customer satisfaction, with customer service and value for money emerging as the strongest predictors. The airline experienced fluctuating financial performance, alternating between years of profit and loss. The paper recommends that airlines integrate review-driven AIRQUAL approaches into revenue-management decision-making processes. Enhancing personnel, which reflects good customer service and empathy, represented by value for money, realizes the greatest gains in satisfaction, which in turn supports higher yields and better financial performance. Practical implications include prioritizing efficient personnel capacity building and linking AIRQUAL dashboards to pricing and capacity-allocation systems for more effective yield optimization.