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CO2 reduction through shared mobility: A review of psychological factors for the switch from a private car to shared transport

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Reducing CO2 emission and disrupting car travel habits through personalized feedback

This paper presents the results of an experimental field study, in which the effects were studied of personalized travel feedback on car owners’ car habits, awareness of the environmental impact of their travel choices, and the intention to switch modes. For a period of six weeks, 349 car owners living in Amsterdam used a smart mobility app that automatically registered all their travel movements. Participants in the experiment group received information about travel distance, time, and CO2 emission. Results show that the feedback did not influence self-reported car habits, intention, and awareness, suggesting that personalized feedback may not be a one-size-fits-all solution to change travel habits.

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Reducing CO2 emission and disrupting car travel habits through personalized feedback

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This study is the first to systematically and quantitatively explore the factors that determine the length of charging sessions at public charging stations for electric vehicles in urban areas, with particular emphasis placed on the combined parking- and charging-related determinants of connection times. We use a unique and large data set – containing information concerning 3.7 million charging sessions of 84,000 (i.e., 70% of) Dutch EV-users – in which both private users and taxi and car sharing vehicles are included; thus representing a large variation in charging duration behavior. Using multinomial logistic regression techniques, we identify key factors explaining heterogeneity in charging duration behavior across charging stations. We show how these explanatory variables can be used to predict EV-charging behavior in urban areas and we derive preliminary implications for policy-makers and planners who aim to optimize types and size of charging infrastructure.

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The Sharing Economy in the Netherlands: Grounding Public Values in Shared Mobility and Gig Work Platforms

Introduction: The Netherlands has been known as one of the pioneers in the sharing economy. At the beginning of the 2010s, many local initiatives such as Peerby (borrow tools and other things from your neighbours), SnappCar (p2p car-sharing), and Thuisafgehaald (cook for your neighbours) launched that enabled consumers to share underused resources or provide services to each other. This was accompanied by a wide interest from the Dutch media, zooming in on the perceived social and environmental benefits of these platforms. Commercial platforms such as Uber, UberPop and Airbnb followed soon after. After their entrance to the market, the societal debate about the impact of these platforms also started to include the negative consequences. Early on, universities and national research and policy institutes took part in these discussions by providing definitions, frameworks, and analyses. In the last few years, the attention has shifted from the sharing economy to the much broader defined platform economy.

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The Sharing Economy in the Netherlands: Grounding Public Values in Shared Mobility and Gig Work Platforms

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EV Charging Data Management, five issues to solve

The transition towards electric mobility is expected to take off the coming years, as more EV car models access the market and charging infrastructure is being expanded. The expansion of charging infrastructure will have to accelerate to keep pace with the fast-growing need for charging. The coming years will be marked by uncertainty regarding technological developments (batteries, range), charging technologies (e.g. fast charging, inductive), growth of car sharing and autonomous driving and impact on user preferences and charging behaviour Data management is key to the EV market and public parties involved: to be able to adapt quickly to changes and to reduce risks and costs. This paper describes the five most important preconditions for effective data management that allows stakeholders to monitor the performance of their charging infrastructure and to take informed decisions on rollout strategies based on data science research results.

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EV Charging Data Management, five issues to solve

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Behavioural perspective on car owners’ uptake of shared e-mobility

In the Interreg Smart Shared Green Mobility Hubs project, electric shared mobility is offered through eHUBs in the city. eHUBs are physical places inneighbourhoods where shared mobility is offered, with the intention of changing citizens’ travel behaviour by creating attractive alternatives to private car use.In this research, we aimed to gain insight into psychological factors that influence car owners’ intentions to try out shared electric vehicles from an eHUB in order to ascertain:1. The psychological factors that determine whether car owners are willing to try out shared electric modalities in the eHUBs and whether these factors are identical for cities with different mobility contexts.2. How these insights into psychological determinants can be applied to entice car owners to try out shared electric modalities in the eHUBs.Research was conducted in two cities: Amsterdam (the Netherlands) and Leuven (Belgium). An onlinesurvey was distributed to car owners in both cities inSeptember 2020 and, additionally, interviews wereheld with 12 car owners in each city.In general, car owners from Amsterdam and Leuven seem positive about the prospect of having eHUBs in their cities. However, they show less interest inusing the eHUBs themselves, as they are satisfied with their private car, which suits their mobility needs. Car owners mentioned the following reasons for notbeing interested in trying out the eHUBs: they simply do not see a need to do so, the costs involved with usage, the need to plan ahead, the expected hasslewith registration and ‘figuring out how it works’, having other travel needs, safety concerns, having to travel a distance to get to the vehicle, and a preferencefor ownership. Car owners who indicated that they felt neutral, or that they were likely to try out an eHUB, mentioned the following reasons for doing so:curiosity, attractive pricing, convenience, not owning a vehicle like those offered in an eHUB, environmental concerns, availability nearby, and necessity when theirown vehicle is unavailable.In both cities, the most important predictor determining car owners’ intention to try out an eHUB is the perceived usefulness of trying out an eHUB.In Amsterdam, experience with shared mobility and familiarity with the concept were the second and third factors determining car owners’ interest in tryingout shared mobility. In Leuven, pro-environmental attitude was the second factor determining car owners’ openness to trying out the eHUBs, and agewas the third factor, with older car owners being less likely to try one out.Having established that perceived usefulness was the most important determinant for car owners to try out shared electric vehicles from an eHUB, weconducted additional research, which showed that, in both cities, three factors contribute to perceived usefulness, in order of relevance: (1) injunctive norms(e.g., perceiving that society views trying out eHUBs as correct behaviour); (2) trust in shared electric mobility as a solution to problems in the city (e.g., expecting private car owners’ uptake of eHUBs to contributeto cleaner air, reduce traffic jams in city, and combat climate change); and (3) trust in the quality and safety of the vehicles, including the protection of users’privacy. In Amsterdam specifically, two additional factors contributed to perceived usefulness of eHUBs: drivers’ confidence in their capacity to try out anunfamiliar vehicle from the eHUB and experience of travelling in various modes of transport.Drawing on the relevant literature, the results of our research, and our behavioural expertise, we make the following recommendations to increase car users’ uptake of shared e-mobility:1. Address car owners’ attentional bias, which filters out messages on alternative transport modes.2. Emphasise benefits of (trying out) shared mobility from different perspectives so that multiple goals can be addressed.3. Change the environment and the infrastructure, as infrastructure determines choice of transport.4. For Leuven specifically: target younger car owners and car owners with high pro-environmental attitudes.5. For Amsterdam specifically: provide information on eHUBs and opportunities for trying out eHUBs.

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Behavioural perspective on car owners’ uptake of shared e-mobility

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Modes of fast charging

Fast charging is usually seen as a means to facilitate long distance driving for electric vehicles and roll-out therefore often happens with corridors in mind. Due to limited charging speeds, EV drivers usually tend to charge at home or work when the car is parked for a longer period to avoid unnecessarily time loss. However with increasing charging speeds and different modes (taxi, car sharing) also switching to electric vehicles, a different approach to fast charging is needed. This research investigates the different intentions of EV drivers at fast charging stations in inner-cities and along highways to see how usage at such stations differs to inform policy makers and charging point operators to accommodate an efficient roll-out strategy.

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Simulation of free-floating vehicle charging behaviour at public charging points

As society has to adapt to changing energy sources and consumption, it is driving away from fossil energy. One particular area of interest is electrical driving and the increasing demand for (public) charging facilities. For municipalities, it is essential to adapt to this changing demand and provide more public charging facilities.In order to accommodate on roll-out strategies in metropolitan areas a data driven simulation model, SEVA1, has been developed The SEVA base model used in this paper is an Agent-Based model that incorporate past sessions to predict future charging behaviour. Most EV users are habitual users and tend to use a small subset of the available charge facilities, by that obtaining a pattern is within the range possibilities. Yet, for non-habitual users, for example, car sharing users, obtaining a pattern is much harder as the cars use a significantly higher amount of charge points.The focus of this research is to explore different model implementations to assess the potential of predicting free-floating cars from the non-habitual user population. Most important result is that we now can simulate effects of deployement of car sharing users in the system, and with that the effect on convenience for habitual users. Results show that the interaction between habitual and non habitual EV users affect the unsuccessful connection attempts based increased based on the size of the car-sharing fleet up to approximately 10 percent. From these results implications for policy makers could be drawn.

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Simulation of free-floating vehicle charging behaviour at public charging points

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Charging free floating shared cars in metropolitan areas

This paper analyses the effect of two new developments: electrification and ‘free floating’ car sharing and their impact on public space. Contrary to station based shared cars, free floating cars do not have dedicated parking or charging stations. They therefore park at public parking spots and utilize public charging stations. A proper network of public charging stations is therefore required in order to keep the free floating fleet up and running. As more municipalities are considering the introduction of an electric free floating car sharing system, the outline of such a public charging network becomes a critical piece of information. The objective of this paper is to create insights that can optimize charging infrastructure for free floating shared cars, by presenting three analyses. First, a business area analysis shows an insight into which business areas are of interest to such a system. Secondly, the parking and charging behaviour of the vehicles is further examined. The third option looks deeper into the locations and their success factors. Finally, the results of the analysis of the city of Amsterdam are used to model the city of The Hague and the impact that a free floating electric car sharing system might have on the city and which areas are the white spots that need to be filled in.

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CO2 reduction through shared mobility: A review of psychological factors for the switch from a private car to shared transport

Reducing CO2 emission and disrupting car travel habits through personalized feedback

Fully charged

The Sharing Economy in the Netherlands: Grounding Public Values in Shared Mobility and Gig Work Platforms

EV Charging Data Management, five issues to solve

Behavioural perspective on car owners’ uptake of shared e-mobility

Modes of fast charging

Simulation of free-floating vehicle charging behaviour at public charging points

Charging free floating shared cars in metropolitan areas

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CO2 reduction through shared mobility: A review of psychological factors for the switch from a private car to shared transport

Reducing CO2 emission and disrupting car travel habits through personalized feedback

Fully charged

The Sharing Economy in the Netherlands: Grounding Public Values in Shared Mobility and Gig Work Platforms

EV Charging Data Management, five issues to solve

Behavioural perspective on car owners’ uptake of shared e-mobility

Modes of fast charging

Simulation of free-floating vehicle charging behaviour at public charging points

Charging free floating shared cars in metropolitan areas

Projecten 1

SolarMiles