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

Author Identifier

Sanjit K. Roy: https://orcid.org/0000-0003-4932-2222

Document Type

Journal Article

Publication Title

Journal of Strategic Marketing

Publisher

Taylor & Francis

School

School of Business and Law

RAS ID

77136

Comments

Roy, S. K., Tsao, H. Y., Lin, C. C., Singh, G., & Lo, H. Y. (2024). Do you love traveling to the beach or mountain? Predicting personality traits and choice behaviour. Journal of Strategic Marketing. Advance online publication. https://doi.org/10.1080/0965254X.2024.2428629

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.

DOI

10.1080/0965254X.2024.2428629

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