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dc.contributor.authorSikder, SK
dc.contributor.authorNagarajan, M
dc.contributor.authorMustafee, N
dc.date.accessioned2023-09-25T07:42:50Z
dc.date.issued2023-09-22
dc.date.updated2023-09-24T07:38:04Z
dc.description.abstractAn increasing number of studies have reported on the need to augment public electric vehicle (EV) charging points (E-CPs) in areas with growing demand for parking. However, the focus on E-CP infrastructure equity has largely been ignored. For increased uptake of EVs, we argue that future E-CP infrastructure augmentation (EIA) will necessitate the identification of the optimal locations based on a need-focused strategic approach. Our work utilises open datasets and presents a generic multicriteria-based modelling framework for EIA framework. The E-CP Infrastructure Framework a two-stage framework. The first stage assesses the existing infrastructure gap and spatial disparity of E-CP allocation at the city scale. Next, guided by the information from stage one, stage two identifies the optimal E-CP candidate locations for future EIA expansion. The locations are determined using a parametric scoring approach that includes ease of access, available bays for parked vehicles, and potential congestion risk. We take the example of Dresden city to demonstrate the applicability of the EIA framework. Our findings show the wide prevalence of spatial disparities in E-CPs across nine of the ten wards in the city. Our proposed city-scale approach for identifying candidate locations could help policymakers decide on the augmentation strategies of E-CP infrastructure in a spatially equitable and cost-effective manner.en_GB
dc.format.extent122829-122829
dc.identifier.citationVol. 196, article 122829en_GB
dc.identifier.doihttps://doi.org/10.1016/j.techfore.2023.122829
dc.identifier.urihttp://hdl.handle.net/10871/134077
dc.identifierORCID: 0000-0002-2204-8924 (Mustafee, Navonil)
dc.identifierScopusID: 57666502800 | 8355557400 (Mustafee, Navonil)
dc.identifierResearcherID: B-8313-2008 (Mustafee, Navonil)
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.relation.urlhttps://doi.org/10.5281/zenodo.8335314en_GB
dc.rights© 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)en_GB
dc.subject15-Minute cityen_GB
dc.subjectElectric vehicleen_GB
dc.subjectCharging infrastructureen_GB
dc.subjectSpatial analysisen_GB
dc.subjectMulti-criteria decision makingen_GB
dc.titleAugmenting EV charging infrastructure towards transformative sustainable cities: An equity-based approachen_GB
dc.typeArticleen_GB
dc.date.available2023-09-25T07:42:50Z
dc.identifier.issn0040-1625
exeter.article-number122829
dc.descriptionThis is the final version. Available on open access from Elsevier via the DOI in this recorden_GB
dc.descriptionData availability: We maintain all dataset, code and interactive visualizaiton for this paper in an open repository. This can be accessed at: https://doi.org/10.5281/zenodo.8335314en_GB
dc.identifier.journalTechnological Forecasting and Social Changeen_GB
dc.relation.ispartofTechnological Forecasting and Social Change, 196
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en_GB
dcterms.dateAccepted2023-09-03
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2023-09-22
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2023-09-25T07:38:34Z
refterms.versionFCDVoR
refterms.dateFOA2023-09-25T07:43:51Z
refterms.panelCen_GB


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© 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Except where otherwise noted, this item's licence is described as © 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)