Abstract
Mobility as a Service (MaaS), which integrates public and shared transportation into a single service, is drawing attention as a travel demand management strategy aimed at reducing automobile dependency and encouraging public transit. In particular, there have been few studies that recognize traffic congestion during peak hours and identify related factors for practical application. The purpose of this study is to explore what factors affect Seoul commuters’ mode choice including MaaS. A web-based survey that 161 commuters participated in was conducted to collect information about personal, household, and travel attributes, together with their mode preference for MaaS. A latent class model was developed to classify unobserved latent groups based on trip frequency by means and to identify factors influencing mode-specific utilities (in particular, MaaS service) for each class. The result shows that latent classes are divided into two groups (public transit-oriented commuters and balanced mode commuters). Most variables have significant impacts on choice for MaaS. The coefficient of MaaS choice of Class 1 and Class 2 were different. These findings suggest there is a difference between the classes according to trip frequency by means as an influencing factor in MaaS choice.
Highlights
The 4th industrial revolution, first presented at the world economic forum annual meeting 2016 [1], emphasizes the significance of artificial intelligence, big data analysis and platform technologies based on information and communications technology (ICT)
Choice probability of Class 1 and Class 2 are 82.6% and 62.5%, respectively. Those who belong to Class 1 are more likely to choose Mobility as a Service (MaaS) compared to those in Class 2
Three out of four covariates were statistically significant at the 99% significance level; respondents belonging to Class 2 are more likely to use personal vehicles including cars and bicycles and less likely to use taxis than those belonging to
Summary
The 4th industrial revolution, first presented at the world economic forum annual meeting 2016 [1], emphasizes the significance of artificial intelligence, big data analysis and platform technologies based on information and communications technology (ICT). It aims to produce and efficiently utilize services in response to consumer preferences. Such changes are gradually affecting the shared economy. Shared economy was only utilized in the living community unit, but its scope is expanding with the development of ICT, leading to services such as Uber and Airbnb. Advances in the Internet of Things (IoT) and platform technology have made it possible for users to take advantage of information about transportation, emerging as a new transport service—MaaS
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