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

Abstract 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.