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Determinants of Recommendation in the Airline Industry: An Application of Online Review Analysis

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Decision Support Systems X: Cognitive Decision Support Systems and Technologies (ICDSST 2020)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 384))

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Abstract

This study explores key determinants of airline recommendations by integrating ratings and text comments scraped from online source. Numerical review scores are used to characterize features on how passengers decide to recommend others. Text analysis technique provides information of service attributes that differentiate positive and negative comments. Using generated frequent words visualization of Word Cloud, the results suggested that positive recommenders are satisfied with human dimensions such as personality and friendly services, while negative comments suggested frequent complaints on poor operational dimensions such as on-time performance and seat comfort.

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Authors and Affiliations

  1. NIDA Business School, National Institute of Development Administration (NIDA), 118 Seri Thai Road, Bangkok, 10240, Thailand

    Praowpan Tansitpong

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  1. Praowpan Tansitpong
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Correspondence to Praowpan Tansitpong .

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Editors and Affiliations

  1. University of Zaragoza, Zaragoza, Spain

    José María Moreno-Jiménez

  2. University of Namur, Namur, Belgium

    Isabelle Linden

  3. SimTech Simulation Technology, Graz, Austria

    Fatima Dargam

  4. Loughborough University, Loughborough, UK

    Uchitha Jayawickrama

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Tansitpong, P. (2020). Determinants of Recommendation in the Airline Industry: An Application of Online Review Analysis. In: Moreno-Jiménez, J., Linden, I., Dargam, F., Jayawickrama, U. (eds) Decision Support Systems X: Cognitive Decision Support Systems and Technologies. ICDSST 2020. Lecture Notes in Business Information Processing, vol 384. Springer, Cham. https://doi.org/10.1007/978-3-030-46224-6_10

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  • DOI: https://doi.org/10.1007/978-3-030-46224-6_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-46223-9

  • Online ISBN: 978-3-030-46224-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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