Details
| Original language | English |
|---|---|
| Title of host publication | Electric Vehicles in Shared Fleets |
| Subtitle of host publication | Mobility Management, Business Models, and Decision Support Systems |
| Editors | Kenan Degirmenci, Thomas M. Cerbe, Wolfgang E. Pfau |
| Publisher | World Scientific Publishing Co. Pte Ltd |
| Pages | 173-192 |
| Number of pages | 20 |
| ISBN (electronic) | 9781800611429 |
| ISBN (print) | 9781800611412 |
| Publication status | Published - 1 Jan 2022 |
Abstract
Electric carsharing is a mobility alternative addressing the world’s growing need for sustainability and allowing to reduce pollution, traffic congestion, and shortage of parking in cities. Since electric vehicles cut down carbon emissions through the use of renewable energy and reduce noise exposure compared to conventionally powered vehicles, they further enhance ecological sustainability within an even sustainable concept. For carsharing services, electric vehicles are a suitable fit for carsharing because typical carsharing trips are comparatively short, resulting in uncritical range restrictions for the trips itself. Yet, only station-based approaches can appropriately accommodate charging infrastructures and suitably account for range limitations and charging cycles. The positioning and sizing of carsharing stations are critical success factors for reaching many potential users. This represents a multi-dimensional challenge that requires decision makers to address the conflicting goals of fulfilling demands and maximizing profit. To provide decision support in anticipating optimal locations and to further achieve profitability, an optimization model is developed in this chapter. The integration of the model into a decision support system (DSS) enables easy operability by assisting the user to import, edit, export, and visualize data. Solutions are illustrated, discussed, and evaluated using the city of Portland (OR) as a computational study. Results demonstrate the applicability of the DSS indicating that profitable operation of electric carsharing is possible.
ASJC Scopus subject areas
- Economics, Econometrics and Finance(all)
- Business, Management and Accounting(all)
- General Business,Management and Accounting
Sustainable Development Goals
Cite this
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Electric Vehicles in Shared Fleets: Mobility Management, Business Models, and Decision Support Systems. ed. / Kenan Degirmenci; Thomas M. Cerbe; Wolfgang E. Pfau. World Scientific Publishing Co. Pte Ltd, 2022. p. 173-192.
Research output: Chapter in book/report/conference proceeding › Contribution to book/anthology › Research › peer review
}
TY - CHAP
T1 - Station-Based Electric Carsharing
T2 - A Decision Support System for Network Generation
AU - Sonneberg, Marc Oliver
AU - Breitner, Michael H.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - Electric carsharing is a mobility alternative addressing the world’s growing need for sustainability and allowing to reduce pollution, traffic congestion, and shortage of parking in cities. Since electric vehicles cut down carbon emissions through the use of renewable energy and reduce noise exposure compared to conventionally powered vehicles, they further enhance ecological sustainability within an even sustainable concept. For carsharing services, electric vehicles are a suitable fit for carsharing because typical carsharing trips are comparatively short, resulting in uncritical range restrictions for the trips itself. Yet, only station-based approaches can appropriately accommodate charging infrastructures and suitably account for range limitations and charging cycles. The positioning and sizing of carsharing stations are critical success factors for reaching many potential users. This represents a multi-dimensional challenge that requires decision makers to address the conflicting goals of fulfilling demands and maximizing profit. To provide decision support in anticipating optimal locations and to further achieve profitability, an optimization model is developed in this chapter. The integration of the model into a decision support system (DSS) enables easy operability by assisting the user to import, edit, export, and visualize data. Solutions are illustrated, discussed, and evaluated using the city of Portland (OR) as a computational study. Results demonstrate the applicability of the DSS indicating that profitable operation of electric carsharing is possible.
AB - Electric carsharing is a mobility alternative addressing the world’s growing need for sustainability and allowing to reduce pollution, traffic congestion, and shortage of parking in cities. Since electric vehicles cut down carbon emissions through the use of renewable energy and reduce noise exposure compared to conventionally powered vehicles, they further enhance ecological sustainability within an even sustainable concept. For carsharing services, electric vehicles are a suitable fit for carsharing because typical carsharing trips are comparatively short, resulting in uncritical range restrictions for the trips itself. Yet, only station-based approaches can appropriately accommodate charging infrastructures and suitably account for range limitations and charging cycles. The positioning and sizing of carsharing stations are critical success factors for reaching many potential users. This represents a multi-dimensional challenge that requires decision makers to address the conflicting goals of fulfilling demands and maximizing profit. To provide decision support in anticipating optimal locations and to further achieve profitability, an optimization model is developed in this chapter. The integration of the model into a decision support system (DSS) enables easy operability by assisting the user to import, edit, export, and visualize data. Solutions are illustrated, discussed, and evaluated using the city of Portland (OR) as a computational study. Results demonstrate the applicability of the DSS indicating that profitable operation of electric carsharing is possible.
UR - http://www.scopus.com/inward/record.url?scp=85143459483&partnerID=8YFLogxK
U2 - 10.1142/9781800611429_0008
DO - 10.1142/9781800611429_0008
M3 - Contribution to book/anthology
AN - SCOPUS:85143459483
SN - 9781800611412
SP - 173
EP - 192
BT - Electric Vehicles in Shared Fleets
A2 - Degirmenci, Kenan
A2 - Cerbe, Thomas M.
A2 - Pfau, Wolfgang E.
PB - World Scientific Publishing Co. Pte Ltd
ER -