Exploring spatiotemporal heterogeneity in online travel searches: a local spatial model approach

ABSTRACT Online travel searches are important forms of travel virtual spaces. Previous studies have neglected to analyze the spatial features of the travel searches themselves, and the spatial heterogeneity of their influencing factors. In this study, a travel search index based on the Baidu index was established for analyzing travel searches. Meanwhile, a local spatial model was created for the linear features in order to discuss the spatiotemporal heterogeneity of the influencing factors. The results of this study indicated that travel searches have obvious spatial inequality, and economically developed regions had displayed advantages in the travel search network. The fitting results of the local model were found to be superior to global model. The number of attractions and the GDP of the origin were found to have promoting effects on the travel searches, whereas distances had shown inhibiting effects. These effects presented significant spatiotemporal heterogeneity. It was also found that within the travel search virtual space, the distance effects still existed, but the intensity was weaker than in the real space. The local spatial model for the linear features provided a new spatial analysis method for understanding the travel search network, as well as other types of networks (flow patterns).