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Tourist mobility has attracted considerable attention from tourism academics and industry practitioners. This study explores the destination network, which is constructed based on tourists' digital footprint data collected from online travel diaries, by proposing a multi-scale analytical framework. In particular, to analyze the tourism destination network comprehensively, the proposed framework integrates traditional quantitative analysis (gravity center model, statistics of flow directions) and three scales of network analysis (macroscopic, mesoscopic and microscopic network metrics), to reveal the structural patterns of the underlying pattern characteristics; furthermore, by using the multiple regression quadratic assignment procedure (MRQAP), the framework also explores the formation mechanism of the destination network by measuring the correlation and causality between the destination network and the corresponding transportation network, combining other potential driving factors. Based on illustrative case study data, which contains 18, 939 travel diaries and 51, 603, 044 transportation records from Chengdu-Chongqing economic circle in China, the empirical results show that the destination network is dynamically changed during four-year period, and the transportation network has great potential in explaining the formation of destination network. The dynamic characteristics of destination network and the exploration of formation mechanism offer the opportunities for improving destination planning and management.
Xu et al. (Fri,) studied this question.