Open AccessTo switch travel mode or not? Impact of Smartphone delivered high‐quality multimodal information
Author(s) -
Gan Hongcheng
Publication year - 2015
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2014.0150
Subject(s) - binary logit model , mode (computer interface) , discrete choice , mixed logit , public transport , logit , mode choice , quality (philosophy) , smart card , service (business) , service quality , ordered logit , logistic regression , transport engineering , business , computer science , marketing , econometrics , economics , engineering , statistics , computer security , mathematics , philosophy , epistemology , machine learning , operating system
Travellers' mode switch behaviour with the presence of high‐quality Smartphone delivered multimodal information (SMMI) seems to have rarely been addressed. This study investigated commuters’ en‐trip mode decision about switching from ‘auto’ to ‘park‐and‐ride’ (P + R) under high‐quality SMMI that provides travel time for both modes, delay for auto, cause of delay, P + R cost and comfort level of rail transit. It is based on a stated preference survey of Shanghai travellers. A binary logit model was developed to identify contributing factors that affect mode switching decisions. Results showed that SMMI can significantly influence mode choice and its impacts depend on traveller attributes, driver's previous experience, and level of service attributes. Statistically significant explanatory variables in the model are delay for auto, comfort level of rail transit, gender, education level, income, driving experience, driving frequency, main criterion of mode choice, owning an easy public transportation ride card, previous use of P + R, perceived value of existing real‐time traveller information and frequency of using real‐time traveller information. This study also developed a practical logit model that encompasses policy related explanatory variables to obtain policy implications for real application of SMMI services in Shanghai.