Extracting Key Drivers of Air Passenger’s Experience and Satisfaction through Online Review Analysis
2020; Multidisciplinary Digital Publishing Institute; Volume: 12; Issue: 21 Linguagem: Inglês
10.3390/su12219188
ISSN2071-1050
AutoresAralbayeva Shadiyar, Hyun-Jeong Ban, Hak‐Seon Kim,
Tópico(s)Technology and Data Analysis
ResumoThis study compared the competitiveness of the Commonwealth Independent State Airlines (Azerbaijan Airlines, Air Astana, Aeroflot) with Korean airlines (Asiana Airlines, Korean Air) using customer online reviews through big data analytics. The purpose of this study was to get the understanding of airline issues, especially the relationship between airline traveler experience and satisfaction. This study also shows which group has a better service and is more developed and provides significant and social network-oriented suggestions for another group of airlines. Data were collected from Skytrax and the collected reviews were written from January 2011 to March 2019. The size of the dataset was 1693 reviews, and a total of 199,469 words were extracted. As part of the qualitative analysis method, semantic network analysis through text mining was performed, and linear regression analysis was conducted using SPSS as part of the quantitative analysis method. This study shows which group of airlines has a better service and provides significant and social network-oriented suggestions for another group of airlines. The common concerns, as well as special features for different airlines, can also be extracted from online review data.
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