Visual Data Mining: Analysis of Airline Service Quality Attributes |
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| Authors: | Vanja Bogicevic Wan Yang Anil Bilgihan |
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| Institution: | 1. Department of Human Sciences, The Ohio State University, Columbus, Ohio, USA;2. The Collins College of Hospitality Management, California State Polytechnic University, Pomona, California, USA;3. College of Business, Florida Atlantic University, Boca Raton, Florida, USA |
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| Abstract: | The objectives of the study are to identify the key airline quality attributes from online review posts and to examine the effect of identified airline quality attributes on eWOM communication. This study employed data-mining techniques and logistic regression on 901 passenger reviews to evaluate the service quality of passenger airlines. The major contribution was identifying the most salient topics of travelers complimenting and complaining reviews. Passengers’ comments support that service, staff, cabin seat comfort, and entertainment are among the most discussed themes in positive and negative reviews. Additionally, value, seat comfort, staff/service, and catering were found to be significant predictors of airline eWOM. |
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| Keywords: | Airline industry data mining eWOM satisfaction service quality |
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