Original scientific paper
https://doi.org/10.7307/ptt.v38i2.867
The Impact of Spatio-Temporal Constraints on Tourists’ Travel Mode Choice Behaviour – Case of Sijiao Island, China
Yazao YANG
orcid.org/0000-0003-2890-8232
; Chongqing Key Laboratory of Intelligent Integrated and Multidimensional Transportation System, Chongqing Jiaotong University, Chongqing, China
Hui WEN
; School of Traffic and Transportation, Chongqing Jiaotong University, Chongqing, China
Tangzheng WENG
; School of Traffic and Transportation, Chongqing Jiaotong University, Chongqing, China
Abstract
With the continuous rise in tourism consumption demand, the spatio-temporal aggregation effects are strengthening, leading to an imbalance in travel structure within tourist destinations. To address these issues, this study focuses on SiJiao Island in Zhoushan, China. It empirically studies tourists’ mode choice behaviour from the perspectives of personal social attributes, temporal attributes and spatial attributes. This study gathers tourist characteristics through surveys and multidimensional data mining. It employs a multinomial logistic regression method to identify influencing factors and constructs a gradient boosting decision tree model to explore the relationship between spatio-temporal factors and tourists’ mode choice behaviour. The results show that the cumulative importance of temporal and spatial attributes is much greater than that of personal social attributes. Among the many spatiotemporal influencing factors, travel distance, transfer time, departure time and the number of bus stops have a significant impact on tourists’ mode choice behaviour, accounting for 26.25%, 16.57%, 14.65% and 11.87% of the total importance, respectively. Additionally, there are complex non-linear relationships between these influencing factors and tourists’ mode choice behaviour. The interaction effects of spatiotemporal combinations on tourists’ mode choice behaviour exhibit correlations. The sensitivity of mode choice to different spatiotemporal factors varies.
Keywords
spatio-temporal factors; machine learning; travel mode choice; active travel
Hrčak ID:
344889
URI
Publication date:
24.2.2026.
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