Making better decisions : Utilizing qualitative signed digraphs modeling to enhance aquaculture production technology selection
MetadataShow full item record
Altmetrics Handle Statistics
Altmetrics DOI Statistics
Understanding 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.
King , 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 . https://doi.org/10.1016/j.marpol.2018.01.032
© 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: https://doi.org/10.1016/j.marpol.2018.01.032
DescriptionFunding for the research was embedded with the Australian Seafood Cooperative Research Centre’s (CRC) future aquaculture production programme (Project 2011-735).
Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.