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

Eunjeong Ko, Yeongmin Kwon, Woongbee Son, Junghwa Kim and Hyungjoo Kim
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Eunjeong Ko: The Cho Chun Shik Graduate School of Green Transportation, Korea Advanced Institute of Science and Technology, Daejeon 34051, Korea
Yeongmin Kwon: Policy Research Team, Incheon International Airport Corporation, Incheon 22382, Korea
Woongbee Son: Gyeonggi Autonomous Driving Center, Advanced Institute of Convergence Technology, Seongnam 13449, Korea
Junghwa Kim: Department of Urban and Transportation Engineering, Kyonggi University, Suwon 16227, Korea
Hyungjoo Kim: Gyeonggi Autonomous Driving Center, Advanced Institute of Convergence Technology, Seongnam 13449, Korea

Sustainability, 2021, vol. 14, issue 1, 1-14

Abstract: Mobility as a service (MaaS) integrates various transportation modalities and connects these modalities to enable users to travel from departure points to destination points. The objectives of this study were to analyze the factors influencing the intention to use MaaS and determine a direction for the implementation of this service. Hence, this study utilized an ordered probit model and marginal effect analysis. Specifically, a survey was conducted based on citizens living in Gyeonggi-do, South Korea, to prepare logical MaaS operation measures customized in this province. Subsequently, variables related to MaaS were classified, and statistical analysis was performed based on these variables. The need for integrated transportation service, intention to use shared mobility, gender, household income, and region are found to have significant effects. Moreover, demographic groups with high levels of intention to use MaaS were identified. Finally, the intention to use MaaS was found to be mainly affected by whether public transportation was the primary means of transportation or whether the subjects spent a comparatively long time commuting. It is expected that these findings will serve as the basis for MaaS implementation in the future and will also be used as fundamental data for transportation service planning.

Keywords: MaaS; intention to use; influencing factor; ordered probit model; 5-point Likert scale (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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