MAPPING AFFECTIVE IMAGE OF DESTINATIONS

Following Baloglu and Brinberg (1997), who advocate that the affective image space may be used as a tool to positioning tourism destinations, the main purpose of this paper is to introduce latent class factor analysis (LCFA) to map the affective space of environments, namely tourism destinations. Twelve European cities, marketed as short-break destinations for Portuguese travelers, were appraised by a sample of 140 respondents on 20 indicators of affective qualities, taken from Russell and Pratt (1980). The affective qualities attributed to the destinations were successfully reproduced by LCFA on two bipolar latent dimensions, positive or negative valence and high or low arousal. Each of the 20 indicators relates as expected with the poles of the latent dimensions. Considering the variable destination as a covariate, its categories (i.e. the destinations) are depicted in the affective map and tend to cluster in the four quadrants, allowing to easily identifying each destination‘s positioning