• Journal of Service Research and Studies
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• v.9 no.4
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• pp.19-40
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• 2019

Mobility as a Service is a service conception to achieve the intelligent transportation system. Its aims to improve the travel experience. In one platform, it connects various transportation modes to offer service and users only need to pay in one time for the whole travel. But the single MaaS platform easily faces the problems such as low user traffic, low retention rate and the access to markets of the this service is still unfound. From the perspective of bicycle-sharing, this research makes the MaaS concept into bicycle-sharing to build a better service model. The bicycle-sharing combine with the MaaS concept is innovative in business model, travel model and service architecture. In addition, this research also tests users' expectations for service model. The research shows that MaaS-based bicycle-sharing could offer flexible and convenient travel experience in the aspects of combined transportation, travel, transfer and payment, and it also makes it possible to make travel services according to need, and sustainable transport.

• Asia Marketing Journal
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• v.24 no.3
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• pp.121-130
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• 2022

To achieve the widespread use of Mobility as a Service (MaaS), a novel transportation platform, it is important to increase consumers' intention to use MaaS. Therefore, this study clarifies the determinants of consumers' intention to use MaaS based on the UTAUT2 model. The research model is tested using structural equation modeling based on data from a web-based questionnaire survey of Japanese consumers. The results show that performance expectancy, social influence, hedonic motivation, and price value have significant effects on the intention to use MaaS. Moreover, the relationship between the intention to use MaaS and independent variables is moderated by old age. Theoretical and practical implications are discussed based on the findings.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.117-132
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• 2023

Mobility as a Service(MaaS) is an integrated mobility service that enables flexible reservation and payments for various transportation services on one platform, including existing public transportation. To popularize MaaS, users need to be satisfied with the service, and the factors that lower satisfaction need to be improved. In this study, the structural equation model was used to identify the influence of factors on the overall satisfaction level. Improvement plans to increase user satisfaction were derived based on importance-satisfaction analysis and the decision tree model. The analysis revealed the level of connectivity in MaaS apps to be a significant factor that needs to be improved for a higher user satisfaction level of MaaS

• The Journal of the Korea Contents Association
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• v.19 no.10
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• pp.568-580
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• 2019

With mobility-as-a-service(MaaS) drawing attention to its influence and ripple effect around the world, the mobility service market is currently growing rapidly mainly focusing on mobility sharing. In order to preemptively dominate the mobility service market following the full-scale spread of MaaS, it is important to first identify the recognition and experience of users in personal mobility sharing services, which are currently in the early stages of diffusion, and through which to understand the characteristics of potential consumers of the extended mobility service market. Therefore, the study aims to classify the user types of mobility service and establish a future user experience-oriented mobility service strategy using a subjectivity study method, Q methodology.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.1-13
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• 2019

With commercial apps popular in EU, MaaS has been emerging around the globe as a new approach to worsening urban traffic problems. In contrast, it is still mainstay in Korea simply discussing the concept and necessities of MaaS, rather than seeking for real-world solutions for the commercialization. The purpose of this research is to analyze the demand-side i1mpacts of travel time and cost changes according to MaaS adoption, and to see its commercial feasibility in Korea. The 2010 KTDB traveler's nationwide OD data is used to estimate the level of fare discount for balancing the mode shift and fare revenue changes followed by MaaS implementation. The analysis results show that MaaS leads to the increase of public transport ridership as a result of the diminishing travel cost and time, and that the time saving works more positively for ridership increase. Also, the optimum level of fare discount is estimated 2.56% without damaging the revenue. This finding reveals that MaaS impact is superior to the other single-sided public transport inventive measures since it can affect both travel cost and time reduction at the same time.

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.330-336
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• 2023

Rapid urbanization is rapidly progressing around the world, and urban problems such as traffic congestion, environmental pollution, and noise pollution are emerging, due to this urban concentration phenomenon, logistics and transportation costs are increasing. Urban Air Mobility(UAM) is a three-dimensional futuristic urban transportation that is expected to become an important transportation axis of smart cities as a service(MaaS) linked to roads, railways, and personal transportation. However, as of July 2023, research on airspace systems, Bertieport design, navigation, and communication for UAM operation is actively being conducted, but little research has been conducted on the concept of pilot education and training and education and training programs. Therefore, this paper aims to present a suitable plan for the domestic pilot training system through SWOT analysis of vertical takeoff and landing(VTOL) pilot education and training programs in the United States and Europe.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.9
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• pp.806-813
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• 2012

In a cloud computing environment, various solutions were introduced to provide the service to users such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS) and Desktop as a Service (DaaS). Nowadays, Mobile as a Service (MaaS) to provide the mobility in a cloud environment. In other words, users must have access to data and applications even when they are moving. Thus, to support the mobility to a mobile Thin-Client is the key factor. Related works to support the mobility for mobile devices were Mobile IPv6 and Proxy Mobile IPv6 which showed performance drawbacks such as packet loss during hand-over which could be very critical when collaborating with cloud computing environment. The proposed model in this paper deploys middleware and replica servers to support the data transmission among cloud and PMIPv6 domain. It supports efficient mobility during high-speed movement as well as high-density of mobile nodes in local mobility anchor. In this paper, through performance evaluation, the proposed scheme shows the cost comparison between previous PMIPv6 and verifies its significant efficiency.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.73-86
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• 2018

The increase in the number of private automobiles has incurred various traffic problems. Globally, studies on MaaS(Mobility as a Service) has already been initiated to mobilize the use of public transportation in reducing private passenger cars in roads. This study aims to analyze the passenger's optimal route considering the transfer between different transportation modes through simulation, and analyze the effect of available route through the connected transportation modes. Sejong Special Self-Governing City was chosen as the study area due to its extensive transportation network. As a result of the analysis, the predominant obtainable route is derived either from using public transportation (i.e. bus and subway) only or by bicycle. However, it is also possible to use the car sharing and public bicycle to reach their final destination efficiently when paths that can be traversed were more scrutinized. When various transportation information and location-based services are introduced in smart phone applications, they can provide very useful information to passengers, and also promote social problems such as traffic congestion and environmental issues in the future.

• Industry Promotion Research
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• v.9 no.1
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• pp.47-55
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• 2024

In the transportation sector, reducing total vehicle mileage and passenger vehicle traffic are proposed as strategies to achieve carbon neutrality. To achieve this, MaaS services must be actively promoted with the goal of revitalizing public transportation. In order to promote MaaS, individual movement data is required, such as the individual's means of movement, route, and conversion of the individual's means of use. However, in Korea, there are legal limitations in collecting and utilizing data on individual movements. As the right to request transmission of personal information was newly established in the revised Personal Information Protection Act in 2023, a law was established to collect and utilize data on individual movements. However, enforcement ordinance, detailed rules, instructions, guidelines must be prepared, and the standardization of data format and transmission system for collecting my data needs to take precedence.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.118-133
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• 2020

Research interest in the Mobility-as-a-Service (MaaS) concept for enhancing users' mobility experience is increasing. In particular, dynamic pricing techniques based on reinforcement learning have emerged since adjusting prices based on the demand is expected to help mobility services, such as taxi and car-sharing services, to gain more profit. This paper provides a simulation framework that considers more practical factors, such as demand density per location, preferred prices, the distance between users and drivers, and distance to the destination that critically affect the probability of matching between the users and the mobility service providers (e.g., drivers). The aforementioned new practical features are reflected on a data structure referred to as the Matching Matrix. Using an efficient algorithm of computing the probability of matching between the users and drivers and given a set of precisely identified high-demand locations using HDBSCAN, this study developed a better reward function that can gear the reinforcement learning process towards finding more realistic dynamic pricing policies.