Globally, Atlantic salmon aquaculture is faced with a critical challenge: How best to deliver long-term sustainable growth, whilst optimising the opportunity for the expansion of the industry presented by an increasing global seafood demand? This thesis presents a novel framework of complementary decision support approaches to enable decision-makers to better understand the factors influencing aquaculture development, and examine alternative production (growout) technologies that more effectively address the challenges associated with intensification and expansion. The framework was developed through a combination of fieldwork (international data-gathering), key stakeholder discussions, and the application of targeted qualitative and quantitative analytical approaches; using the Tasmanian industry as a Case Study. The initial research focused on shorter-term (tactical) decision support. A situational analysis defined the business environment, and appraised viable expansion options (offshore, closed-containment and extractive bio-remediation). An economic analysis of selected options then provided a comparison of financial performance and risk. The outputs of this initial component next informed strategic decision-making approaches; employing scenario analysis to explore plausible strategies for the adoption of land-based recirculating aquaculture systems; and qualitative modelling to understand the causal dynamics driving and regulating the industry, and their impact on technology selection. Whilst it was clear that business economic viability is paramount, the results suggested that societal acceptance (the Social License to operate) is playing an increasingly important role in influencing business decisions. There is no single 'right' technological solution; social acceptance, in particular considerations regarding human wellbeing, trust, and animal welfare concers, will shape the business environment and therefore technology selection. The research emphasised the importance of employing a balance of tactical and strategic decision-making techniques, and of engaging with a broad range of industry stakeholders. It also highlighted the complexity and dynamic nature of the industry and that key variances (economic, regional, strategic, technological, and temporal) must be included in decision-making.