Making better decisions : Utilizing qualitative signed digraphs modeling to enhance aquaculture production technology selection

• Published in: Marine Policy
• Main Authors: King, Andrew S., Elliott, Nicholas G., Macleod, Catriona K., James, Mark A., Dambacher, Jeffrey M.
• Other Authors: University of St Andrews.School of Biology, University of St Andrews.Marine Alliance for Science & Technology Scotland
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2019
• Subjects: QH301 Biology; NDAS; QH301; Imta; Atlantic salmon
• Online Access: https://hdl.handle.net/10023/18197; https://doi.org/10.1016/j.marpol.2018.01.032

Funding for the research was embedded with the Australian Seafood Cooperative Research Centre’s (CRC) future aquaculture production programme (Project 2011-735). 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. Peer reviewed