Do you love traveling to the beach or mountain? Predicting personality traits and choice behaviour
Author Identifier (ORCID)
Sanjit K. Roy: https://orcid.org/0000-0003-4932-2222
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.
Document Type
Journal Article
Date of Publication
1-1-2024
Publication Title
Journal of Strategic Marketing
Publisher
Taylor & Francis
School
School of Business and Law
RAS ID
77136
Copyright
subscription content
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