Emerging cities and travel motivation: A latent profile analysis approach

Emerging city destinations frequently face numerous managerial challenges, resulting in common pitfalls and rookie mistakes. The evolution, new dynamics, and shift in tourism demand, together with many cities’ efforts to diversify offerings and exploit their multi-attractiveness, necessitate a re-evaluation of present viewpoints on what motivates city break tourists. Thus, the purpose of this paper is to focus on scale development for emerging cities travel motivation; and to determine latent subpopulations (profiles) within a population of city break visitors based on their motivation to visit a city. The study used principal component analysis to test the dimensions of the emerging cities travel motivation factors scale. Confirmatory factor analysis was used to test the measurement model. Subtypes (profiles) of city break travel motivation factors were obtained using latent profile analysis (LPA). The following dimensions for the emerging cities travel motivation scale were identified: Image, Vibrance, and Novelty, Core Destination Values, Social Experience, Ego Boosting and Shopping, Psycho-physical Relaxation. Based on LPA analysis four profiles of emerging city visitors were defined: Indifferent, Conventional, Psycho-physical relaxing, ego-boosting, and Shopping city break tourists. From a theoretical standpoint, this study broadens the existing corpus of research on emerging cities travel motivation, allowing for the discovery of distinct latent groups of visitors as well as significant differences between them.