Do you love traveling to the beach or mountain? Predicting personality traits and choice behaviour

Several personality-predicting tools are being used by managers in their strategic decision-making process. The most common are the Big Five model and the Myers – Myers-Briggs Type Indicator model, respectively. This study deviates and tests a novel personality prediction model. Specifically, it utilizes the TF-IDF (Term Frequency-Inverse Document Frequency) algorithm as a feature extraction method to map personality traits based on consumers’ textual data from the Kaggle MBTI Personality Type dataset. This study uses realistic data gathered from traveller reviews and comments on hotel stays from TripAdvisor’s widely recognised platform to predict different personality traits and their travel destination preferences, i.e. beach or mountain. The contribution of this study lies in the identification of multiple dimensions of peoples’ personality traits and their relationship with their preferences for travel locations. This proposed trait classification mechanism can assist marketing managers in effectively carrying out customer segmentation, setting realistic goals, and optimizing marketing strategies.

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Publication Details

Journal
Journal of Strategic Marketing
Published
2024-11-12
DOI
https://doi.org/10.1080/0965254x.2024.2428629
Citations
1
Primary Topic
Consumer Behavior in Brand Consumption and Identification
Type
article
Field-Weighted Citation Impact
0.44
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article

Do you love traveling to the beach or mountain? Predicting personality traits and choice behaviour

Sanjit Kumar Roy, Gaganpreet Singh, Hsiu‐Yuan Tsao, Hui-Yi Lo et al.
1 citations
Journal of Strategic Marketing
Consumer Behavior in Brand Consumption and Identification
0.44
article

Do you love traveling to the beach or mountain? Predicting personality traits and choice behaviour

Sanjit Kumar Roy, Gaganpreet Singh, Hsiu‐Yuan Tsao, Hui-Yi Lo, Ching-Chang Lin
article en
1 citations

Abstract

Several personality-predicting tools are being used by managers in their strategic decision-making process. The most common are the Big Five model and the Myers – Myers-Briggs Type Indicator model, respectively. This study deviates and tests a novel personality prediction model. Specifically, it utilizes the TF-IDF (Term Frequency-Inverse Document Frequency) algorithm as a feature extraction method to map personality traits based on consumers’ textual data from the Kaggle MBTI Personality Type dataset. This study uses realistic data gathered from traveller reviews and comments on hotel stays from TripAdvisor’s widely recognised platform to predict different personality traits and their travel destination preferences, i.e. beach or mountain. The contribution of this study lies in the identification of multiple dimensions of peoples’ personality traits and their relationship with their preferences for travel locations. This proposed trait classification mechanism can assist marketing managers in effectively carrying out customer segmentation, setting realistic goals, and optimizing marketing strategies.

Journal of Strategic Marketing
Taipei City University of Science and Technology (TW), Edith Cowan University (AU), National Chung Hsing University (TW), O. P. Jindal Global University (IN)
Openalex Percentile: Top 26%
Consumer Behavior in Brand Consumption and Identification
0.44
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