Search

Research into the sustainable development of scenic regions has drawn more interest from researchers even though it has been suggested that the field needs to consider the spatial–temporal behavioral characteristics of tourists. However, few investigations within the extant literature focus on intra-attraction based tourist behavior; indeed, current research only examines GPS visualization problems without exploring deeper applications for the development of scenic regions. In this paper, we propose a new method to select potential development regions based on the characteristic of tourist flow structures and the relationships between scenic regions supported by GPS and social network models. We choose Gulangyu (a world famous heritage site in Xiamen, China) as our study case. The GPS trajectories of 312 tourists have been recorded and the social network centrality index of 54 regions in Gulangyu have been calculated. Based on tourists' spatial–temporal behavior characteristics and the relationships between scenic regions, we select two types of 'potential development regions'; these, are those 'potential development regions' near core scenic spots and those with clustering characteristics. The main contribution of our proposed method lies in linking GPS techniques with social network models to support deeper forms of quantitative spatial analysis in tourism research. [ABSTRACT FROM AUTHOR]