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dc.contributor.authorKing, Andrew S.
dc.contributor.authorElliott, Nicholas G.
dc.contributor.authorMacleod, Catriona K.
dc.contributor.authorJames, Mark A.
dc.contributor.authorDambacher, Jeffrey M.
dc.identifier.citationKing , A S , Elliott , N G , Macleod , C K , James , M A & Dambacher , J M 2018 , ' Making better decisions : Utilizing qualitative signed digraphs modeling to enhance aquaculture production technology selection ' , Marine Policy , vol. 91 , pp. 22-33 .
dc.identifier.otherPURE: 252347604
dc.identifier.otherPURE UUID: 3fc93d38-6156-46e0-b632-286d0275c859
dc.identifier.otherRIS: urn:18082E7922ED95A797A44550E41BD678
dc.identifier.otherScopus: 85044652512
dc.identifier.otherORCID: /0000-0002-7182-1725/work/57330862
dc.identifier.otherWOS: 000429393500004
dc.descriptionFunding for the research was embedded with the Australian Seafood Cooperative Research Centre’s (CRC) future aquaculture production programme (Project 2011-735).en
dc.description.abstractUnderstanding causal relationships within complex business environments represents an essential component in a decision-maker's toolset when evaluating alternative aquaculture production technologies. This article assesses the utility of employing signed digraph qualitative modeling to support technology selection decision-making through evaluating the adoption of three alternative production expansion strategies (offshore production, IMTA, or land-based RAS) by the Atlantic salmon industry. Results underlined the benefits of strategically understanding the dynamics of demand growth, emphasized the requirement to address societal concerns early; and indicated that levels of ambiguity are lowest with expansion offshore and highest with land-based RAS growout. The research suggests that signed digraph modeling can provide an objective perspective on the levels of uncertainty and causal linkages within a business environment when exploring aquaculture adoption technology scenarios.
dc.relation.ispartofMarine Policyen
dc.rights© 2018 Elsevier Ltd. All rights reserved. This work has been made available online in accordance with the publisher’s policies. This is the author created accepted version manuscript following peer review and as such may differ slightly from the final published version. The final published version of this work is available at:
dc.subjectQH301 Biologyen
dc.titleMaking better decisions : Utilizing qualitative signed digraphs modeling to enhance aquaculture production technology selectionen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
dc.contributor.institutionUniversity of St Andrews. Marine Alliance for Science & Technology Scotlanden
dc.description.statusPeer revieweden

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