Do We Scapegoat The Pandemic? Investigating The Changes in Satisfaction Drivers of Air Passengers With DWLS-SEM

Abstract

This paper aims to investigate whether there is an alteration in the drivers of air passenger satisfaction before and after COVID-19. We conducted the multigroup structural equation modelling with the diagonally weighted least squares estimation method as the variables are categorical. Lastly, we performed ANOVA to spot if there is a change in the drivers of passenger satisfaction between before and after the pandemic. The results suggest all service attributes have a significant impact on satisfaction in the pre-COVID-19 era. Even if it seems that in-flight entertainment and in-flight WiFi are not as influential as before in the post-pandemic, ANOVA results revealed the difference between the pre-pandemic and the new-normal period was not statistically significant. Accordingly, airlines should not ignore the need to improve service attributes, called premium services, and holistically improve service design. In addition, after value for money, the most important attribute for passengers is ground handling. Hence, speeding up the boarding process would return carriers in the form of more satisfied customers. To the best of our knowledge, this is the first paper employing Multigroup DWLS SEM to focus on changes in determinants of air passenger satisfaction in a holistic approach, focusing on pandemic periods.

Keywords

• Airlines
• Customer satisfaction
• COVID-19
• Diagonally weighted least squares
• Structural equation modeling

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