Survey Data Analysis on Intention to Use Shared Mobility Services

Abstract

Shared mobility is a service that allows users to share various transportation modes and use them with reservations when necessary. It started with private automotive car-sharing and ride-sharing services. Currently, it operates on a wider range, including personal mobility devices such as electric bicycles and scooters. The purpose of this study is to derive a direction for providing future shared mobility services through analysis of factors affecting the usage intention of both current and prospective users. The survey targets 753 citizens living in Gyeonggi Province, Korea. The survey period is from February 12, 2020, to February 26, 2020. In this study, a logistic regression analysis is conducted to investigate the factors affecting the use intention of shared mobility. The analysis results show that gender, car ownership, and education, among variables reflecting socio-demographic characteristics, have significant effects on intention to use shared mobility. Moreover, we find that experience factors, including mainly used transportation modes, ownership of shared mobility device, past experience in similar services, satisfaction of existing shared mobility services, and distance from the home to the nearest bus stop, are also statistically influential. The analysis results are expected to lay the foundation for the introduction of shared mobility services and can be used as data for planning smart mobility services in the future.

Factors Influencing Intention to Use Mobility as a Service: Case Study of Gyeonggi Province, Korea

“…Table 2 lists the characteristics of the samples obtained based on the survey. The results of analyzing the respondent characteristics show that the respondents sufficiently reflected the travel characteristics of commuters in South Korea [11]. Male and female respondents accounted for 58.0% and 42.0% of the 781 participants in the survey, respectively.…”

“…The survey was conducted from 12 February 2020 to 26 February 2020. This province is characterized by dense traffic zones with satellite cities connected to Seoul, the capital of South Korea [11]. It also has more than 10 million people, so many people commute to Seoul from nearby cities.…”

“…u 1 and β can be used to calculate the choice probability related to the intention to use MaaS. Equations ( 7)- (11) shows the choice probabilities according to alternatives ranging from 1 (not intending to use MaaS at all) to 5 (strongly intending to use MaaS) in order. Here, Φ is a function with a cumulative standard normal distribution:…”

“…In particular, Gyeonggi-do has numerous satellite cities connected with Seoul, the Korean capital, in which more than 13 million people reside. As this province also shows a high level of population mobility to the capital and nearby cities, it has symbolic significance as a heavy commuting area [11]. Accordingly, South Korea has research significance as various factors affecting MaaS implementation can be analyzed because Korea has an established transportation infrastructure.…”

Identifying and Quantifying Factors Determining Dynamic Vanpooling Use

“…Further, to understand the effect of individual's demographics, authors in [24] stated that gender, car ownership and education can significantly affect the preference to use shared mobility services. Specifically, considering their perceived value of time, authors in [25] stated that attributes referred to attitudes influence the travel behavior of individuals.…”