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Titel: Designing a Crowd-Based Relocation System—The Case of Car-Sharing
VerfasserIn: Brendel, Alfred Benedikt
Lichtenberg, Sascha
Morana, Stefan
Prinz, Christoph
Hillmann, Boris M.
Sprache: Englisch
Titel: Sustainability
Bandnummer: 14
Heft: 12
Verlag/Plattform: MDPI
Erscheinungsjahr: 2022
Freie Schlagwörter: sharing economy
car-sharing
supply and demand management
vehicle relocation
crowdsourcing
green is/it
design science
DDC-Sachgruppe: 330 Wirtschaft
Dokumenttyp: Journalartikel / Zeitschriftenartikel
Abstract: Car-sharing services promise environmentally sustainable and cost-efficient alternatives to private car ownership, contributing to more environmentally sustainable mobility. However, the challenge of balancing vehicle supply and demand needs to be addressed for further improvement of the service. Currently, employees must relocate vehicles from low-demand to high-demand areas, which generates extra personnel costs, driven kilometers, and emissions. This study takes a Design Science Research (DSR) approach to develop a new way of balancing the supply and demand of vehicles in car-sharing, namely crowd-based relocation. We base our approach on crowdsourcing, a concept by which customers are requested to perform vehicle relocations. This paper reports on our comprehensive DSR project on designing and instantiating a crowd-based relocation information system (CRIS). We assessed the resulting artifact in a car-sharing simulation and conducted a real world car-sharing service system field test. The evaluation reveals that CRIS has the potential for improving vehicle availability, increasing environmental sustainability, and reducing operational costs. Further, the prescriptive knowledge derived in our DSR project can be used as a starting point to improve individual parts of the CRIS and to extend its application beyond car-sharing into other sharing services, such as power bank- or e-scooter-sharing.
DOI der Erstveröffentlichung: 10.3390/su14127090
Link zu diesem Datensatz: urn:nbn:de:bsz:291--ds-365763
hdl:20.500.11880/33228
http://dx.doi.org/10.22028/D291-36576
ISSN: 2071-1050
Datum des Eintrags: 24-Jun-2022
Fakultät: HW - Fakultät für Empirische Humanwissenschaften und Wirtschaftswissenschaft
Fachrichtung: HW - Wirtschaftswissenschaft
Professur: HW - Prof. Dr. Stefan Morana
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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