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Beyond surveys: leveraging automated text analysis of travellers' online reviews to enhance service quality and willingness to recommend
Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering. Marketing, University of Cape Town, Cape Town, South Africa.ORCID iD: 0000-0002-3486-8292
Corporate Communication, University of Malta, Msida, Malta.ORCID iD: 0000-0002-2146-5996
Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering.ORCID iD: 0000-0003-1137-1686
KTH Royal Institute of Technology, Stockholm, Sweden.ORCID iD: 0000-0002-2343-9361
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2024 (English)In: Journal of Strategic Marketing, ISSN 0965-254X, E-ISSN 1466-4488, Vol. 32, no 4, p. 516-535Article in journal (Refereed) Published
Abstract [en]

Airports are essential to the global economy, providing significant revenue and driving regional growth. In order to remain competitive and achieve sustainable development, airports must continuously monitor and improve service quality. To this end, understanding traveller perceptions of their experiences is important. While traditional survey-based methods are beneficial, managers are increasingly looking for alternative ways of collecting feedback, such as online reviews. Automated text analysis provides a cost- and time-effective technique with which to analyse large datasets of unsolicited online reviews, providing managers with strategic insights to enhance service quality. This study explores the potential of supplementing traditional airport service quality monitoring methods with automated text analyses to better understand traveller feedback and improve service quality. The results provide new methods to measure airport service quality, offering a fresh perspective on customers’ satisfaction with service quality experiences, and highlighting key strategic implications that can help organisations gain a competitive advantage.

Place, publisher, year, edition, pages
Taylor & Francis, 2024. Vol. 32, no 4, p. 516-535
Keywords [en]
Service quality, willingness to recommend, customer satisfaction, UGC, automated text analysis, LIWC
National Category
Business Administration
Research subject
Industrial Marketing
Identifiers
URN: urn:nbn:se:ltu:diva-101826DOI: 10.1080/0965254X.2023.2256738ISI: 001075642400001Scopus ID: 2-s2.0-85173953547OAI: oai:DiVA.org:ltu-101826DiVA, id: diva2:1807975
Note

Validerad;2024;Nivå 1;2024-06-27 (hanlid)

Available from: 2023-10-30 Created: 2023-10-30 Last updated: 2024-06-27Bibliographically approved

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Robertson, JeandriDuncan, Sherese

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