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

In: Decision Sciences for COVID-19

Author

Listed:
  • Praowpan Tansitpong

    (NIDA Business School, National Institute of Development Administration (NIDA))

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.

Suggested Citation

  • Praowpan Tansitpong, 2022. "Quality Design for the COVID-19 Pandemic: Use of a Web Scraping Technique on Text Comments and Quality Ratings from Multiple Online Sources," International Series in Operations Research & Management Science, in: Said Ali Hassan & Ali Wagdy Mohamed & Khalid Abdulaziz Alnowibet (ed.), Decision Sciences for COVID-19, chapter 0, pages 329-341, Springer.
    • Handle: RePEc:spr:isochp:978-3-030-87019-5_19
    DOI: 10.1007/978-3-030-87019-5_19
    as

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