TY - JOUR
T1 - Depicting urban multi-scale tourist activity spaces using digital footprints for smart destinations
AU - Zhao, Pengfei
AU - Ma, Zhongfu
AU - Chen, Jinyan
AU - Law, Rob
AU - Zhang, Yi
AU - Liu, Yu
N1 - Publisher Copyright:
© 2022 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2022
Y1 - 2022
N2 - Given the complex characteristics of city structure, the analysis of tourists’ activities in urban space is challenging. Previous studies on urban tourists’ activities were mostly limited to official administrative units, such as attractions, blocks, and administrative districts, and rarely considered the multi-scale characteristics of urban tourism space. This study offered insights into urban tourism by depicting multi-scale tourism spaces from the perspective of tourists’ activities. Based on a spatial conceptual model, the urban destination was divided into multi-scale spaces, including tourist areas of interest (areas of intensive tourist activity), attraction-community complexes (comprising tourist attractions and supporting service facilities), and tourism districts (subregions with different tourism types). The Geographic Information System field and spatial interaction models were combined to identify multi-scale tourist activity spaces using digital footprints from geolocated social media data. The proposed framework was verified in Suzhou, a typical urban destination in China, which confirmed that the systematic and comprehensive methodology could be used as a tool for smart urban destination management and planning based on tourists’ demands.
AB - Given the complex characteristics of city structure, the analysis of tourists’ activities in urban space is challenging. Previous studies on urban tourists’ activities were mostly limited to official administrative units, such as attractions, blocks, and administrative districts, and rarely considered the multi-scale characteristics of urban tourism space. This study offered insights into urban tourism by depicting multi-scale tourism spaces from the perspective of tourists’ activities. Based on a spatial conceptual model, the urban destination was divided into multi-scale spaces, including tourist areas of interest (areas of intensive tourist activity), attraction-community complexes (comprising tourist attractions and supporting service facilities), and tourism districts (subregions with different tourism types). The Geographic Information System field and spatial interaction models were combined to identify multi-scale tourist activity spaces using digital footprints from geolocated social media data. The proposed framework was verified in Suzhou, a typical urban destination in China, which confirmed that the systematic and comprehensive methodology could be used as a tool for smart urban destination management and planning based on tourists’ demands.
KW - digital footprints
KW - geolocated social media data
KW - multi-scale
KW - smart destination
KW - Urban tourist activity space
UR - http://www.scopus.com/inward/record.url?scp=85135217933&partnerID=8YFLogxK
U2 - 10.1080/13683500.2022.2104696
DO - 10.1080/13683500.2022.2104696
M3 - Journal article
AN - SCOPUS:85135217933
JO - Current Issues in Tourism
JF - Current Issues in Tourism
SN - 1368-3500
ER -