Recognise me from outside to inside: Learning the influence chain of urban destination personalities

Abstract

This study aims to develop a personality scale specific to urban destinations and explore the antecedents and consequences of perceived urban destination personalities. Using a sample of 672 tourists, and an intelligent data analysis tool, machine learning, this study develops an urban destination personality scale with four components, i.e., temperament, competence, attitude and mood. Urban landscapes are found to be significant antecedents, with different influential importance in both components (modern space/ancient space/ecological/living/social landscapes) and elements. Besides, the impacts of urban destination personalities on overall destination image are identified, and the mediating effects of urban destination personalities on the relationship between urban landscapes and overall destination image are discovered. The findings contribute to revealing an influence chain of urban destination personalities and furtherly providing concrete practical insights into building or upgrading personalities of a particular urban destination so as to make it be more distinctive and attractive from outside to inside.