We used the mental models research method to generate a conceptual map of how Midwest farmers use knowledge, experience, and individual perceptions of weed-related risk to make weed management decisions. We discovered that Midwest farmer knowledge of ecological weed management practices is robust, and that the difficult trade-offs farmers make regarding cultivation, cover crops, and soil health determine what weed management practices they use. Midwest farmers balance the risks of cultivation and implementation of cover crops with their valuable benefits to soil health and weed suppression. Developing a decision support tool that provides a baseline of scientific evidence and that offers flexibility based on farmers’ experiences and values will clarify these trade-offs and guide effective decision-making.
In an effort to reduce “carbon pollution” as well as prepare the U.S. for the impacts of climate change, President Obama’s 2013 Climate Action Plan calls for changes to be made to the nation’s energy system. In addition to focusing on alternative portfolios of different fuels and power-generation technologies, researchers and advisory panels have urged that changes to the nation’s energy system be based on a decision-making framework that incorporates stakeholders and accounts for real-world resource, supply, and demand constraints. To date, research and development on such a framework have proven elusive. The research reported here describes the development and test of a potential decision support framework that combines elements from structured decision-making (SDM) with portfolio analysis, methods that have been used independently to elicit preferences in complex decision contexts. This hybrid framework aimed to (1) provide necessary background information to users regarding the development of coupled climate-energy strategies; (2) account for users’ values and objectives; (3) allow for the construction of bespoke energy portfolios bounded by real-world supply and demand constraints; and (4) provide a more rigorous basis for addressing trade-offs. Results show that this framework was user-friendly, led to significant increases in users’ knowledge about energy systems and, importantly, led to more internally consistent decisions. For these reasons, this framework may serve as a suitable template for supporting decisions about energy transitions in the United States and abroad.
Decisions about energy in developing communities are challenging from a technical standpoint, and because of the unique characteristics that typify them, e.g. limited infrastructure and government budgets, complex social and political arrangements, and economic vulnerability. Against the backdrop of these challenges, the government of Canada’s Northwest Territories (NWT) is attempting to reform the region’s energy system. This paper provides insights from the decision sciences, stemming from our work on the NWT’s energy planning process, about how to structure decisions about energy development and delivery so as to effectively meet a range of stakeholders’ objectives in a transparent and inclusive manner.
This article presents research aimed at developing and testing an online, multistakeholder decision-aiding framework for informing multiattribute risk management choices associated with energy development and climate change. The framework was designed to provide necessary background information and facilitate internally consistent choices, or choices that are in line with users’ prioritized objectives. In order to test different components of the decision-aiding framework, a six-part, 2 × 2 × 2 factorial experiment was conducted, yielding eight treatment scenarios. The three factors included: (1) whether or not users could construct their own alternatives; (2) the level of detail regarding the composition of alternatives users would evaluate; and (3) the way in which a final choice between users’ own constructed (or highest-ranked) portfolio and an internally consistent portfolio was presented. Participants’ self-reports revealed the framework was easy to use and providing an opportunity to develop one’s own risk-management alternatives (Factor 1) led to the highest knowledge gains. Empirical measures showed the internal consistency of users’ decisions across all treatments to be lower than expected and confirmed that providing information about alternatives’ composition (Factor 2) resulted in the least internally consistent choices. At the same time, those users who did not develop their own alternatives and were not shown detailed information about the composition of alternatives believed their choices to be the most internally consistent. These results raise concerns about how the amount of information provided and the ability to construct alternatives may inversely affect users’ real and perceived internal consistency.