Shared Transport Services Research Articles

Understanding prospective and actual users of campus-based electric moped sharing from a behavioral reasoning perspective – Insights from Taiwan

Shared transportation services using electric two-wheelers have been appearing in cities worldwide. They have the potential to reduce the burden of private, fossil-fueled vehicles on urban areas. Residents' acceptance and adoption behavior needs to be understood by policymakers, planners, and operators in order to promote such services. Campus-like settings, such as universities, can serve as nuclei for these new services. Taiwan has one of the highest moped densities in the world. Young people are the largest user segment of electric moped sharing, which is under researched. The purpose of this research is to investigate the subjective barriers and facilitators that drive the formation of (continued) usage intentions. Empirical and qualitative data from 443 users and non-users of an electric moped sharing in Kaohsiung are collected. This facilitates an investigation using structural equation modelling and multi-group analysis. We find different groups of respondents have different reasons for and against adoption intentions based on their mode use habits, demographic features, and word associations. Some modes habits are associated with higher usage intentions, while others are not. The results and insights may prove useful for policymakers or operators seeking to increase uptake of electric moped sharing services.

To share or not to share, by whom is the question. Acceptability and acceptance of shared transport services by vulnerable groups

ABSTRACT It is believed that shared transport services (STSs) can reduce transport poverty and social exclusion. This paper proposes a definition of “social acceptability” and “social acceptance” and examines whether vulnerable groups accept STSs. The notions “acceptability” and “acceptance” were distinguished and four necessary conditions, especially for vulnerable groups, or the 4As were identified: “availability”, “accessibility”, “affordability”, and “attractability”. In the context of STSs, “social acceptability” is defined as the degree to which an individual intends to use a STS before experiencing it in everyday travel based on the expected availability, accessibility, affordability, and attractability of the service, while “social acceptance” also incorporates the use of a STS after experiencing it in everyday travel based on a minimum level of perceived availability, accessibility, affordability, and attractability. This paper further reviews the scientific literature in transport research regarding the “acceptability” or “acceptance” of STSs by vulnerable groups. While several studies include socio-economic and demographic variables (e.g. age, gender) to explain the “acceptability” of STSs, only a few studies specifically focus on vulnerable groups. More research on the “social acceptance” of STSs, especially shared scooters, ride-sharing, and apps and Mobility as a Service (MaaS), by vulnerable groups is needed.

Assessing the Propensity to Car Sharing Services in University Cities: Some Insights for Developing the Co-Creation Process

Cities are often characterised by the presence of universities and by a greater number of students, often commuters, with an average age of less than 30 years. The study focused on the city of Enna (Italy), where the university students represent a significant percentage of residents and also a good rate of local travel demand. The survey campaign was conducted over a period of more than one year. A bivariate statistical method was applied highlighting significant variables regarding several features of a car sharing system. Additionally, non-parametric statistics and a before and after analysis were performed to evaluate the influence of implementation of the shared transport service. The results can also offer insights into the improvement of transport supply in urban context and the possible implementation of the co-creation actions between the companies managing the service with the end-users.

Open Innovation—Opportunities or Nightmares for the Shared Transport Services Sector?

Shared transport services, including short-term vehicle rentals (bike-, car-, moped-, scooter-sharing) and travel sharing systems (ride-sharing, ride-hailing), have become more and more popular forms of mobility in recent years. Their increasing availability has made them an alternative to individual transport in cities. Along with the development of the systems, a growing number of operators offering sharing services started to appear. Many of them ended their activities after the pilot period or closed the company shortly after launching the system. There are many reasons for this, from management to technical issues, but the aspects of open innovation, open data and transparency were often overlooked. This begs the question whether it is the openness of systems that is the recipe for the market success or failure of shared mobility services. The aim of this work was to evaluate the approaches to data openness and innovation in companies representing the shared mobility market. A research proposal was submitted to diagnose the approach to open innovations in the market of shared mobility services. An expert survey was carried out among representatives of shared mobility services operating in major Polish cities. The expert survey was conducted using the CAWI technique. Research results show that open innovation is a problematic aspect for operators. On the one hand, they are interested in it, but this interest does not translate into real practices. Among the entire shared transport sector, the micro-mobility service providers are the most committed to open innovation. Research indicates that in order to increase the dynamics of the development of open innovation in the shared transport industry, there is a need for education in the field of open innovation, especially in the era of the development of digitization of urban transport systems and the pursuit of sustainable transport.

Factors influencing intention to use on-demand shared ride-hailing services in Vietnam: risk, cost or sustainability?

Transport sustainability has become a major challenge worldwide. On-demand shared ride-hailing (OSR) is an alternative transport mode to private motorized mobility which allows passengers to share a vehicle and driver to their respective destination. OSR is more flexible than buses and cheaper than taxis. Additionally, ride-hailing services such as OSR play an important role in servicing communities with poor access to public transport (e.g., buses or trains) and people with increased vulnerabilities (e.g., women with children or people with disabilities). The present study investigates the impact of psychological factors on passengers' intention to use OSR services. To achieve this, the Theory of Planned Behaviour (TPB) was used and extended with perceived risk, price sensitivity, and perceived green value. Data were collected from 520 ride-hailing passengers in Vietnam. The results confirm the relevance of the original TPB constructs, i.e., attitudes, perceived behavioural control, and social norms. Concerning the three additional constructs, only perceived risk negatively and directly influences usage intention, while the two other constructs (i.e., price sensitivity and perceived green value) influence the intention to use OSR via attitudes. The results also reveal that the impact of perceived green value on usage intention is higher among females than males. Additionally, among middle- and high-income people, there is a significant negative association between perceived risk and intention, while this association is not significant among low-income participants. The findings from the present paper provide evidence of the importance of psychosocial factors such as perceptions of risk, price sensitivity, and sustainability when considering intention to use on-demand shared transport services.

Covid-19 Impact on Shared Transport Services: Perspectives from Eight African Countries

Covid-19 Impact on Shared Transport Services: Perspectives from Eight African Countries

Community sharing: sustainable mobility in a post-carbon, depopulating society

ABSTRACT This paper examines new initiatives in shared mobility of Kashiwa City, a satellite town outside Tokyo, from the users’ perspective. In Japan, the transport sector accounts for almost 20% of carbon emissions. At the same time, a population decrease has led to a decline in use of public transport, reducing the level of the quality of life of residents who live in rural and remote areas. This makes residents depend on private cars, ending up contributing to carbon emissions. Three key issues for sustainable mobility to tackle carbon emissions and residents’ wellbeing issues are discussed. Kashiwa City has experimented with new shared transport services with fixed-route microbuses and more flexible community taxis. The paper explores user perception and experience of such community mobility services and considers the three issues from the viewpoint of the practice of mobility. Background interviews were conducted with the city’s officials and transport service operators, and an ethnographic study was carried out and in-situ conversations were made to explore the utility and meaning of mobility. To increase use of public transport to further reduce CO2 emissions from transport, it is important to pay more attention to the practice of mobility from the user’s perspective. (200 words)

What drives the utility of shared transport services for urban travellers? A stated preference survey in German cities

The supply of shared mobility solutions has been increasing during the last years, so has the popularity of Mobility-as-a-Service. Both promise an easy access to and usage of shared vehicles or shared rides. Nevertheless, usage of these services remains low in German cities. Hence, the question arises: what determines the utility of travellers regarding shared modes and how is this different to conventional modes? To answer this, we conduct a stated preference experiment amongst 1,445 respondents (8,670 observations). The sample is drawn from residents of the 83 largest cities in Germany. We consider four shared (e-scooter-, bike-, carsharing, and ridepooling) and three conventional modes (walking, private car, and public transport). We estimate a mixed logit model and calculate the respective value of travel time (VoT) as well as the value of access, egress, and parking search time. The importance of the individual attributes is analysed drawing on a part-worth analysis. Further, we calculate average treatment effects to show simulated mode-choice probability changes. We find that costs are more important than travel time for carsharing and ridepooling whilst they are equally important for the remaining modes. For shared services, access is more important than egress. Moreover, among the shared services, e-scootersharing shows the highest VoT (23.73 EUR/h), followed by bikesharing (18.53 EUR/h). Finally, cost changes to private cars and public transport show the highest simulated shifting potential with carsharing profiting most from cost increases in these two modes.

Optimal fleet size for a shared demand-responsive transport system with human-driven vs automated vehicles: A total cost minimization approach

Vehicle automation is expected to reduce the cost of shared demand-responsive transport (DRT) services. In this context, questions regarding the conditions under which fixed-route public transport can be replaced with shared on-demand services have emerged. The expected increase in competitiveness between fixed-route and on-demand services requires the development of frameworks that enable the analysis of transportation costs of alternative modes. In this research, we develop a total cost minimization model for demand-responsive door-to-door shared transportation services, including operator and user costs. Optimization variables are vehicle size and fleet size for operation with human-driven and automated vehicles. A hybrid approach is used in which the relevant variables are analytically and numerically modeled, using data from a large-scale agent-based simulation applied to the city of Munich. We compare the case in which all trip requests must be served with the case in which request rejections are allowed, based on waiting and travel times. Different demand levels and alternative scenarios for vehicle automation are analyzed. The results indicate that the performance of door-to-door on-demand shared systems depends on the operational scheme selected. For the DRT setup and vehicle assignment strategy studied, we find that if the system is forced to have no trip rejections, economies of scale are not present, and the high user costs hinder the system’s competitiveness even under the assumption of automated vehicles. In contrast, in a system that allows for trip rejections, economies of scale are present, and vehicle automation can especially reduce operator costs, increasing the system’s competitiveness against other transportation modes. Therefore, in our setting, the efficiency of the demand-responsive service depends on the ability to reject customers, which is against the spirit of a truly public transportation service. On scenario analysis, we show that a theoretical improvement in the performance of the real-time vehicle assignment strategy can significantly reduce total cost, with economies of scale under no-rejection operation. Future research needs to address whether the actual application of more complex vehicle assignment strategies can indeed make DRT systems more cost competitive while serving all trip requests.

Estimation of value-of-time and a comparison of an ex ante and an ex post willingness to pay for shared transport services in Thessaloniki

Although the value-of-time and willingness-to-pay are critical measures in a broad range of public transport policy and planning applications, they cannot be measured directly. The purpose of the present research is the estimation of these measures in Thessaloniki, where a pilot mobility scheme inspired by the concept of sharing economy is implemented. The pilot focuses on reducing the commuting trips to the city centre, aggregating as much as possible the origins-destinations and the timetables, by using a taxi sharing service. A questionnaire including a stated-preference experiment has been developed and delivered to a random sample of 90 people. Discrete choice models are developed within a methodological framework and VOT has been estimated through the estimated coefficients. For the estimation of WTP, the Price Sensitivity Model is used based on two samples consisted of the pilot service's users at the beginning and at the end of the pilot period. The model results in a range of acceptable prices from 2.00 to 3.50€ for the both samples supporting the long-term sustainability of the taxi-sharing service.

Designing sustainable services with the ECO-Service design method: Bridging user experience with environmental performance

Eco-design is focused on incorporating environmental criteria early in the design process to reduce the environmental impacts of new products. However, while services now represent the largest share of the world’s economy, the incorporation of environmental sustainability in the design of new services is very limited. This research proposes the ECO-Service Design (ECO-SD) method that integrates eco-design and service design to conceptualize new environmentally sustainable services. The ECO-SD method bridges environmental criteria from eco-design with the human-centred approach of service design, to foster the environmental sustainability of new services, while offering a desirable user experience. To this end, this method encompasses four stages: service exploration, to understand the service context and how users interact with it; service visualization, to visually identify the barriers to environmental performance and user experience during service provision; service ideation, to conceptualize a new service that overcomes the identified barriers; and service assessment, to understand the changes in environmental sustainability and user experience of the newly designed service. The application of the ECO-SD method to two individual shared transport services shows how it enables integrated identification of opportunities to overcome environmental and user experience barriers in the existing services.

Taxi vs. demand responsive shared transport systems: An agent-based simulation approach

Public transport in urban and suburban areas is not always able to meet population's need of accessibility to jobs, education, health and other opportunities in terms of routes and frequencies; therefore, those who do not own a private vehicle, or who cannot afford individual public transport (e.g. taxis), are often in a condition of social exclusion. Taking advantages of new ICT tools and facilities, Demand Responsive Shared Transport (DRST) services can provide “on demand” transport gathering ride bookings of different users and routing a fleet of vehicles to satisfy passengers' needs while minimizing the cost for the operator.In this paper, different DRST service configurations are compared to taxi services to investigate their economic attractiveness and sustainability. This is done by using an agent-based simulation model applied to the case of Ragusa (Italy), a city with poor public transport supply, where an innovative DRST service has already been experimented. A set of 50 different scenarios has been simulated, by varying the numbers of vehicles and seat capacity, and considering different demand rates and route choice strategies of the vehicles. Results are analyzed according to different key performance indicators, mainly showing that the DRST system is more advantageous than taxis when dealing with higher demand rates. On the other hand, the efficiency of the DRST system is rather limited compared to taxis in the case of low transport demand and fleets with a small number of vehicles. Between high and low demand there is a balance between the taxi and the DRST systems, where one should deepen the analysis to identify optimal operational parameters. These results pave the way for further analyses to help the planning and design of intermediate transport services like DRST, which are able to bridge the gap between collective and individual transport in urban and suburban areas.

Potential of Shared Taxi Services in Rural Areas – A Case Study

Due to modern communication and information technology, shared taxi services are on the rise. While most research and practical projects focus on services operating in densely populated areas, the advantages of individual, flexible and shared transportation services in sparsely populated urban areas have not been well explored yet. Using a constraint programming formulation, this work investigates request management policies to evaluate the economic potential of shared taxi services. Computational experiments simulate such services under various effective degrees of dynamism and demonstrate the impact of pre-bookings on their efficiency and service quality in rural areas.

Estimating latent demand of shared mobility through censored Gaussian Processes

Transport demand is highly dependent on supply, especially for shared transport services where availability is often limited. As observed demand cannot be higher than available supply, historical transport data typically represents a biased, or censored, version of the true underlying demand pattern. Without explicitly accounting for this inherent distinction, predictive models of demand would necessarily represent a biased version of true demand, thus less effectively predicting the needs of service users. To counter this problem, we propose a general method for censorship-aware demand modeling, for which we derive a censored likelihood function capable of handling time-varying supply. We apply this method to the task of shared mobility demand prediction by incorporating the censored likelihood within a Gaussian Process model, which can flexibly approximate arbitrary functional forms. Experiments on artificial and real-world datasets show how taking into account the limiting effect of supply on demand is essential in the process of obtaining an unbiased predictive model of user demand behavior.

Assignment constraints in shared transportation services

Competitive markets, increased fuel costs, and underutilized vehicle fleets are characteristics that currently define the logistics sector. Given an increasing pressure to act in a manner that is economically and ecologically efficient, mechanisms that help to benefit from idle capacities are on the rise. In the Sharing Economy, collaborative usage is typically organized through platforms that facilitate the exchange of goods or services. Our study examines a collaborative pickup and delivery problem where carriers can exchange customer requests. The aim is to quantify the potential of horizontal collaborations under a centralized framework. An Adaptive Large Neighborhood Search is developed to solve yet unsolved test instances. A computational study confirms the results of past studies which have reported cost savings between 20 and 30%. In addition, the numerical results indicate an even greater potential for settings with a high degree of regional customer overlap. Unfortunately, these high collaborative gains typically come at the cost of an uneven customer distribution, which is known to be one of the main barriers that prevent companies from entering into horizontal collaborations. To generate acceptable solutions for all participants, several constraints are included in the model. The introduction of these constraints to single-vehicle instances, decreases the potential collaborative gain considerably. Surprisingly, this does not happen in more realistic settings of carriers operating multiple vehicles. Overall, the computational study shows that centralized collaborative frameworks have the potential to generate considerable cost savings, while at the same time limiting customer or profit share losses and enabling carriers to keep some of their most valued customers.

University propensity assessment to car sharing services using mixed survey data: the Italian case study of Enna city

The sustainable development of urban areas, characterized by the expansion of university centers, can benefit from car sharing services, expanding the potential of public transport, especially when the population is almost represented by off-side students and commuters. This work focuses on the investigation of a set of attributes able to interpret and measure the propensity of students to join car sharing. The paper provides a discussion about the potential implementation of a car sharing service, particularly referring to the case of Enna (Italy), where university students constitute a significant percentage of residents. Students have been involved via a wide consultation survey and the analysis was conducted by using mixed Internet/paper survey data. The propensity was modelled in applying the Likert Scale and a chi-squared test was calculated to check the difference between expected and observed frequencies for several combinations of the analyzed attributes. Results are useful to understand their heterogeneous preferences and to define the way for a well-thought-out design of a new shared transport service.

User Perception on Urban Light Rail Transit

Public transport is a shared passenger transport service available for public use. Increased population is accompanied by the increased demand for private vehicles. The exponential growth in the number of private vehicles will result in negative impacts such as air pollution, excessive noise, and traffic congestion. Additionally, customers’ perceptions on different aspects include safety, operation or time, comfortableness and cleanness of public transportation that are also essential in affecting their mode of choice when travelling. The public transport that is discussed in this paper is light rail transit. This paper intends to investigate the main purpose of using light rail transit and elucidate the public perspective of the light rail transit via factor analysis and correlation analysis. A questionnaire with five-point Likert scale was designed, and data were randomly selected from 200 light rail transit users in Kuala Lumpur, Malaysia. The results revealed that the majority of the customers use light rail transit to school or university. Moreover, most of the users satisfy with the safety, operation, cost, comfortableness and cleanness of the light rail transit. This can be concluded that light rail transit provides mobility and choice for everyone in the context of efficiency, health and safety, affordability, accessibility, and environmental friendliness. © 2019 by authors, all rights reserved.

Analysing the Relationship between the Preference on Shared Transport Service and the features of Rental Apartments

Analysing the Relationship between the Preference on Shared Transport Service and the features of Rental Apartments

Multi-agent simulation for planning and designing new shared mobility services

Limiting private cars' use while promoting sustainable modes of transport is one of the main challenges of urban transport planning. In this context, characterized by scarce resources and increasing demand for mobility, Demand Responsive Shared Transport (DRST) services can bridge the gap between shared low-quality public transport and unsustainable individual private transport. Taking advantage of Information and Communication Technologies (ICT), they can supply transport solutions ranging from flexible transit to ride sharing services, providing real-time “on demand” mobility through fleets of vehicles shared by different passengers. The optimal design of a DRST service requires a trade-off among efficiency (from the operators' point of view), service quality (from the users' point of view) and sustainability (from the community's point of view). In this paper, an agent-based model (ABM) fed with GIS data is used to explore different system configurations of a specific type of DRST service, i.e. flexible transit, and to estimate the transport demand and supply variables that make the service feasible and convenient. The model reproduces a mixed fixed/flexible route transit service with different fleet size and vehicle capacity in the city of Ragusa (Italy) with the aim to: (i) make a first test of the ABM model with GIS-based demand and road network models; (ii) explore different vehicle dispatching strategies; (iii) find appropriate indicators to monitor the service quality and efficiency. Simulation results show the impact of fleet composition and route choice strategy on the system performance. In particular, they show an optimal range of operating vehicles that minimizes a total unit cost indicator, accounting both for passenger travel time and vehicle operation cost. By reproducing the microinteraction between demand and supply agents (i.e. passengers and vehicles), it is possible to monitor the macroscopic behaviour of the system, and derive useful suggestions for the correct planning, management and optimization of DRST services.

The Value of Sharing Inland Transportation Services in a Dry Port System

A dry port system consists of a dry port and a number of shippers, where shippers enjoy the public logistics and auxiliary services provided by the dry port. This paper studies the shared transportation services in this system. The interaction between a dry port and shippers is modeled as a bi-level program. The optimal properties of the model are analyzed analytically and an enumeration algorithm is proposed to solve the model. Furthermore, a bi-level model is developed for the direct transportation system. Carbon dioxide (CO2) emissions in transportation are calculated under two scenarios: with and without sharing transportation. Numerical studies are conducted to investigate the sensitivity of the economic and environmental value of sharing with respect to various system parameters. The studies show that sharing transportation service could bring significant profit improvement to the dry port and cost savings to shippers in most circumstances. It is found that carbon emissions are not always mitigated when the distance between shippers is too long, or the dry port is located too close to shippers. When the total distance traveled in the direct transportation system is longer than that in the shared one, the analysis reveals that carrying lighter cargoes could generate more significant CO2 emissions savings.