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dc.contributor.authorNørstebø, Vibeke Stærkebye
dc.contributor.authorKrøgli, Svein Olav
dc.contributor.authorDebella-Gilo, Misganu
dc.contributor.authorValdes, Gerardo Alfredo Perez
dc.contributor.authorUggen, Kristin Tolstad
dc.contributor.authorDramstad, Wenche
dc.date.accessioned2020-08-24T12:46:28Z
dc.date.available2020-08-24T12:46:28Z
dc.date.created2020-02-17T13:17:51Z
dc.date.issued2020
dc.identifier.citationEnvironmental Modelling and Assessment. 2020, .en_US
dc.identifier.issn1420-2026
dc.identifier.urihttps://hdl.handle.net/11250/2673675
dc.description.abstractA transition to a bioeconomy implies an increased focus on efficient and sustainable use of biological resources. A common, but often neglected feature of these resources is their location dependence. To optimize their use, for example in bioeconomic industrial clusters, this spatial aspect should be integrated in analyses. Optimal design and localization of a bioeconomic cluster with respect to the various biological and non-biological resources required for the cluster, the composition of industrial facilities in the cluster, as well as the demands of the outputs of the cluster, is crucial for profitability and sustainability. We suggest that optimal design and location of bioeconomic clusters can benefit from the use of a Multicriteria Decision Analysis (MCDA) in combination with Geographic Information Systems (GIS) and Operations Research modeling. The integration of MCDA and GIS determines a set of candidate locations based on various criteria, including resource availability, accessibility, and usability. A quantitative analysis of the flow of resources between and within the different industries is then conducted based on economic Input-Output analysis. Then, the cluster locations with the highest potential profit, and their composition of industrial facilities, are identified in an optimization model. A case study on forest-based bioeconomic clusters in the Østfold county of Norway is presented to exemplify this methodology, the expectation being that further implementation of the method at the national level could help decision makers in the planning of a smoother transition from a fossil-based economy to a bioeconomy.en_US
dc.language.isoengen_US
dc.publisherSpringer
dc.rightsCC BY 4.0*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectBioeconomyen_US
dc.subjectBioeconomyen_US
dc.subjectBiomassetilgangen_US
dc.subjectBiomass accessen_US
dc.subjectKlyngeren_US
dc.subjectClustersen_US
dc.subjectOptimeringen_US
dc.subjectOptimizationen_US
dc.subjectGIS-modelleren_US
dc.subjectGIS modelsen_US
dc.subjectInput-Output analyseen_US
dc.subjectInput-Output Analysisen_US
dc.titleIdentifying Suitable Bioeconomic Cluster Sites—Combining GIS-MCDA and Operational Research Methodsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2020 The authorsen_US
dc.source.pagenumber15en_US
dc.source.journalEnvironmental Modelling and Assessmenten_US
dc.identifier.doi10.1007/s10666-020-09694-x
dc.identifier.cristin1794780
dc.relation.projectNorges forskningsråd: 244608en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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