In the last years, tourism has experienced deep transformations, so searching new alternatives is an absolute necessity. Urban space has become a very interesting option, as its enormous range of possibilities may respond to many demand patterns changes. On the other hand, cities are going through a crisis period, because of the drift of industry and residents to new areas. In this context, tourism has become one of the main activities to promote. This paper is concerned with the study of urban tourism, focused on demand analysis, as a way to economic growth in cities and regions in general. A previous review of urban tourism features and strategies is presented, applied to the Barcelona case, one of the most paradigmatic examples of tourism growth during the last decade. Information has been provided by Turisme de Barcelona (the local tourism agency), from a survey adressed to hotel customers. After that, an analysis of the demand patterns in Barcelona is carried out using descriptive statistics, multivariate analysis techniques and qualitative response econometric modelling (logistic regression and others). The first part of the study analyses the repetition factor or the fidelity of visitors in Barcelona, with the aim to discriminate the two main tourist segments: return visits (consolidated tourism) and first visits (attracted tourism). Therefore, the probability of a return visit is estimated, on the basis of several variables including individual ones. Conclusions prove that the repeated visits in Barcelona are closely linked to the notion of captivity. So the presence of two very different demand segments is demonstrated. Both segments present specific advantages for a long term sustainable and well-balanced development, introducing some feed-back effects. Nevertheless, some times they are rivals within the tourist policy. Since the main goal of the paper is to contribute to correct tourism planning, the second part of the analysis introduces an approach to captive and new clientele behaviour, focusing on several aspects such as the purchase, activities, etc., with the aim to compare both segments demand patterns.
