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

Praowpan Tansitpong ()
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Praowpan Tansitpong: NIDA Business School, National Institute of Development Administration (NIDA)

Chapter Chapter 19 in Decision Sciences for COVID-19, 2022, pp 329-341 from Springer

Abstract: 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.

Keywords: Web scraping; Text mining; Airline recommendation; Online review; WordCloud; COVID-19 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/978-3-030-87019-5_19

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