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dc.contributor.authorNatvig, Marit Kjøsnes
dc.contributor.authorJiang, Shanshan
dc.contributor.authorHallsteinsen, Svein Olav
dc.date.accessioned2021-04-23T07:50:22Z
dc.date.available2021-04-23T07:50:22Z
dc.date.created2020-06-10T12:29:12Z
dc.date.issued2020
dc.identifier.isbn978-3-030-44038-1
dc.identifier.issn2194-5357
dc.identifier.urihttps://hdl.handle.net/11250/2739255
dc.description.abstractAn innovative smart charging infrastructure is a prerequisite for the wide scale adoption of electric mobility (eMobility) to avoid intolerable demand peaks in the electricity grid, and to ensure predictable availability of charging facilities and green energy supply. Realising such a system is a cross-sectorial undertaking and concerns of a wide range of involved stakeholders must be addressed. This paper presents a stakeholder motivation analysis for smart and green charging for eMobility. The drivers, barriers, goals and requirements have been modelled using ArchiMate motivation models with input and feedback from representatives of the stakeholder groups. The work contributes with insight on how to achieve the required changes towards eMobility for core stakeholder groups, more specifically the associated drivers, barriers, goals and overall requirements. The motivation models have been the basis for the design of solutions for smart and green charging.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.relation.ispartofWeb, Artificial Intelligence and Network Applications
dc.subjectBatteriladingen_US
dc.subjectBattery Chargingen_US
dc.subjectSmart energyen_US
dc.subjectSmart Energyen_US
dc.subjectSmarte Byeren_US
dc.subjectSmart Citiesen_US
dc.subjectHCI and Software Engineeringen_US
dc.subjectHCI and Software Engineeringen_US
dc.titleStakeholder Motivation Analysis for Smart and Green Charging for Electric Mobilityen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionacceptedVersionen_US
dc.rights.holderThis is a post-peer-review, pre-copyedit version of an article published in Advances in Intelligent Systems and Computing. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-44038-1_127en_US
dc.subject.nsiVDP::Informasjons- og kommunikasjonssystemer: 321en_US
dc.subject.nsiVDP::Information and communication systems: 321en_US
dc.source.pagenumber1394-1407en_US
dc.source.volume1150en_US
dc.source.journalAdvances in Intelligent Systems and Computingen_US
dc.identifier.doi10.1007/978-3-030-44038-1_127
dc.identifier.cristin1814776
dc.relation.projectEC/H2020/769016en_US
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.fulltextpreprint
cristin.qualitycode1


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