A Socially Aware Huff Model for Destination Choice in Nature-based Tourism

Abstract. Identifying determinants of tourist destination choice is an important task in the study nature-based tourism. Traditionally, behavior relies on survey data and travel logs, which are labor-intensive time-consuming. Thanks to location-based social networks, more detailed available at a finer grained spatio-temporal scale. This allows for better insights into patterns interactions between attractions, e.g., parks. Meanwhile, such sources also bring along novel influence component that has not yet been widely studied terms decisions. For example, influencers post about certain places, tend choices tourists. Therefore, this paper, we propose socially aware Huff model account factor choice. Moreover, with fine-grained media data, attractions (i.e., neighboring effects) can be quantified thus integrated models as another factor. In our experiment, calibrate by using trip sequences extracted from geotagged Flickr photos within two national parks United States. Our results demonstrate simulates preferences. addition, explore significance each summarize spatial-temporal pattern attraction. The calibration method applied other fields promotional marketing.