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Card sorting is one method that can be used to solicit meaningful insight from end users on the design and assessment of technologies. The objective of this paper is to present methods for and results from a card sorting activity exploring the social impacts experienced by households that have adopted improved cookstoves in peri-urban and rural Uganda. Using a framework consisting of eleven social impacts (population change, family, gender, education, stratification, employment, health and well-being, human rights, networks and communication, conflict and crime, and cultural identity/heritage), households were asked to sort the cards into most, somewhat, and least impacted categories with conversations facilitated around each card placement. Results from this activity reaffirmed positive impacts for family, gender, health and well-being, and education that have been well documented in the literature while also identifying social impacts often overlooked in the sector such as changes in networks and communication, cultural identity and heritage, and human rights. Reflections on these results in terms of cookstove design as well as improvements that could be made in future card sorting activities are discussed. 

Increasing the adoption of household clean energy technologies is important to achieving sustainable development and to improving the environmental, economic, and social impacts of these technology interventions. While much work has been done to understand the many factors driving successful interventions, little research has been done to quantify and then model the adoption of these technologies. Current optimization models to maximize impact rely on the effective prediction of adoption, yet this piece remains the least understood component. The purpose of this paper is to outline the various ways in which being able to model the adoption of household clean energy technologies would be beneficial for designers, implementation organizations, and policymakers to aid in their design and decision-making processes. We provide a brief review of the literature and current challenges to adoption, examples of current methods and modeling tools that can be used to optimize sustainable impacts, and how these tools could be improved through adoption modeling. We discuss the benefits of being able to model adoption for various stakeholders in the clean energy sector along with proposing some methodologies that can be used to accomplish this goal.