Quality Design for the COVID-19 Pandemic: Use of a Web Scraping Technique on Text Comments and Quality Ratings from Multiple Online Sources

ABSTRACT

This study explores the main determinants of airline satisfaction by integrating data from two online survey sources collected via the use of a web scraping technique on text comments and quality ratings to determine service recovery procedures for the aviation industry during the COVID-19 pandemic. The text analysis technique provides information on how passengers rate service attributes (high or low) by generating clusters of the most frequent comments (WordCloud). The results suggest that satisfied passengers highlight empathy and responsive service, while negative reviews suggest frequent instances of poor operational performance, such as refund processes, rescheduling, and system breakdowns. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.