Understanding Airline Passengers during Covid-19 Outbreak to Improve Service Quality: Topic Modeling Approach to Complaints with Latent Dirichlet Allocation Algorithm.
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| Titel: | Understanding Airline Passengers during Covid-19 Outbreak to Improve Service Quality: Topic Modeling Approach to Complaints with Latent Dirichlet Allocation Algorithm. |
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| Autoren: | Çallı L; Department of Information Systems Engineering, Sakarya University, Sakarya, Turkey., Çallı F; Department of Information Systems Engineering, Sakarya University, Sakarya, Turkey. |
| Quelle: | Transportation research record [Transp Res Rec] 2023 Apr; Vol. 2677 (4), pp. 656-673. Date of Electronic Publication: 2022 Aug 12. |
| Publikationsart: | Journal Article |
| Sprache: | English |
| Info zur Zeitschrift: | Publisher: Transportation Research Board, Commission on Sociotechnical Systems, National Research Council, National Academy of Sciences Country of Publication: United States NLM ID: 101481512 Publication Model: Print-Electronic Cited Medium: Print ISSN: 0361-1981 (Print) Linking ISSN: 03611981 NLM ISO Abbreviation: Transp Res Rec Subsets: PubMed not MEDLINE |
| Imprint Name(s): | Original Publication: Washington : Transportation Research Board, Commission on Sociotechnical Systems, National Research Council, National Academy of Sciences |
| Abstract: | The COVID-19 pandemic has deeply affected the airline industry, as it has many sectors, and has created tremendous financial pressure on companies. Flight bans, new regulations, and restrictions increase consumer complaints and are emerging as a big problem for airline companies. Understanding the main reasons triggering complaints and eliminating service failures in the airline industry will be a vital strategic priority for businesses, while reviewing the dimensions of service quality during the COVID-19 pandemic provides an excellent opportunity for academic literature. In this study, 10,594 complaints against two major airlines that offer full-service and low-cost options were analyzed with the Latent Dirichlet Allocation algorithm to categorize them by essential topics. Results provide valuable information for both. Furthermore, this study fills the gap in the existing literature by proposing a decision support system to identify significant service failures through passenger complaints in the airline industry utilizing e-complaints during an unusual situation such as the COVID-19 pandemic. (© National Academy of Sciences: Transportation Research Board 2022.) |
| Competing Interests: | The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. |
| References: | Front Psychol. 2021 Jul 08;12:687155. (PMID: 34305745) |
| Contributed Indexing: | Keywords: airline industry; customer complaints; decision support system; full-service carrier; latent dirichlet allocation algorithm; low-cost carrier; text mining |
| Entry Date(s): | Date Created: 20230508 Latest Revision: 20230509 |
| Update Code: | 20250114 |
| PubMed Central ID: | PMC10152225 |
| DOI: | 10.1177/03611981221112096 |
| PMID: | 37153180 |
| Datenbank: | MEDLINE |
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