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Predicting consumer personality traits in the sharing economy: The case of Airbnb

Author

Listed:
  • Acar, Murat
  • Toker, Aysegul

Abstract

For today’s human-centred engagement models and disruptive innovations, personalisation is paramount. In this regard, the use of Big Data analytics to leverage unstructured and user-generated content and create psychographic or psychologically-personalised marketing could well be a game-changer. This article describes a method to identify the ‘Big Five personalities’ of Airbnb guests through the linguistic analysis of their reviews. The study, conducted with IBM Watson Personality Insights AI, obtained these psychometric insights from a sample of 512 guests who had written at least 1,500 words’ worth of reviews. The statistically significant results indicate that Airbnb guests score high in altruism, cooperation, sympathy, trust, cautiousness, dutifulness, activity-level, extraversion, artistic interests, intellect, liberalism and openness. Concurrent with this, they score low in excitement-seeking, gregariousness, anger and self-consciousness.

Suggested Citation

  • Acar, Murat & Toker, Aysegul, 2019. "Predicting consumer personality traits in the sharing economy: The case of Airbnb," Applied Marketing Analytics: The Peer-Reviewed Journal, Henry Stewart Publications, vol. 5(1), pages 83-96, May.
    • Handle: RePEc:aza:ama000:y:2019:v:5:i:1:p:83-96
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    Cited by:

    1. Mariani, Marcello M. & Machado, Isa & Nambisan, Satish, 2023. "Types of innovation and artificial intelligence: A systematic quantitative literature review and research agenda," Journal of Business Research, Elsevier, vol. 155(PB).

    More about this item

    Keywords

    sharing economy; Big Data; artificial intelligence; user-generated content; content analysis; linguistic analytics; personality analysis;
    All these keywords.

    JEL classification:

    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

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