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Electric Vehicle Sharing Services for Smarter Cities

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Cover of 'Electric Vehicle Sharing Services for Smarter Cities'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction: Car-Sharing Evolution and Green Move Project
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    Chapter 2 Service Idea: Creating Mobility Scenarios Through Service Design
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    Chapter 3 Traditional and Innovative Vehicle-Sharing Models
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    Chapter 4 Analysis of Mobile Phone Data for Deriving City Mobility Patterns
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    Chapter 5 Analysis of Peer-to-Peer Car Sharing Potentialities
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    Chapter 6 Testing a New Model for a Sustainable Mobility in the City of Milan: The Condominium Car Sharing
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    Chapter 7 Communication Design for Social Engagement. Micro TV and the Integration of Branding and Storytelling into Participatory Processes
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    Chapter 8 Architecture of the Green Move System
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    Chapter 9 Green Move Dynamic Applications
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    Chapter 10 Context-Driven Pervasive and Personalized Information Management
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    Chapter 11 A Smartphone-Based Energy-Oriented Driving Assistance System
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    Chapter 12 Automatic Fleet Balancing in One-Way VSSs via Closed-Loop Dynamic Pricing
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    Chapter 13 Information System: Georeferenced Database
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    Chapter 14 The Evaluation Model: Estimation of Economic, Social and Environmental Impacts of Car Sharing Services
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    Chapter 15 Model of the O/D Matrix: Grid Driven Estimate of the O/D Matrices for a Car Sharing Service
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    Chapter 16 System Sizing Model—Simulation Model of the Service
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    Chapter 17 Conclusions and Future Trends: From Ownership to Sharing
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Title
Electric Vehicle Sharing Services for Smarter Cities
Published by
Springer, Cham, January 2017
DOI 10.1007/978-3-319-61964-4
ISBNs
978-3-31-961963-7, 978-3-31-961964-4
Editors

Daniele Fabrizio Bignami, Alberto Colorni Vitale, Alessandro Lué, Roberto Nocerino, Matteo Rossi, Sergio Matteo Savaresi

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X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 26%
Student > Bachelor 3 13%
Student > Master 3 13%
Researcher 3 13%
Lecturer 2 9%
Other 3 13%
Unknown 3 13%
Readers by discipline Count As %
Computer Science 6 26%
Engineering 5 22%
Design 2 9%
Environmental Science 1 4%
Earth and Planetary Sciences 1 4%
Other 4 17%
Unknown 4 17%