Collaborative Research: Cognitive, social, and institutional dynamics of decision-making in complex hazard-prone environments

Ohio State University, The, Columbus OH

Investigators

Abstract

Recent years have demonstrated the substantial threat that wildfires pose to communities across the U.S. This project evaluates how local-level wildfire protection planning processes shape social interaction and consequently the implementation of risk mitigation measures at both local and regional scales. These local planning processes confront a range of challenges that relate to the need to coordinate risk mitigation efforts at multiple spatial and administrative scales (e.g., spanning public and private lands) and to promote cooperation among diverse stakeholder groups with distinct goals for managing wildfire-prone landscapes (e.g., fire suppression, timber production, protection for threatened species). This project improves understanding of how risk governance networks affect policy learning in collaborative planning processes and the scope of decisions they produce, how social processes (such as learning, cooperation, and competition) affect the implementation of those decisions, and how interdependent decision-making processes affect the efficiency of risk mitigation at regional scales. Understanding the interplay among cognitive, social, and policy processes is critical for reducing the vulnerability of communities to wildfire. Through partnerships with the Colorado Forest Restoration Institute and other key groups, the project engages policy makers, outreach professionals, and other stakeholders in initiatives that contribute to the design of communication strategies and capacity building programs to reduce wildfire risk. The project also directly addresses one of the top thirty-three NSF 2026 Idea Machine winning entries: "Large Landscape Resilience by Design". This project addresses theoretical and empirical gaps in scientific understanding of how the structure of decentralized risk governance networks affects policy learning and decision making, as well as the capacity of collaborative groups to implement decisions. Key research questions include: How do risk governance networks affect policy learning in collaborative planning processes? How do risk governance networks affect the scale and boundary-spanning potential of risk mitigation plans? How do social processes affect implementation conformance, and particularly the implementation status of large scale and boundary-spanning risk mitigation plans? How do risk governance networks affect the efficiency of risk mitigation at regional scales? In a departure from the abstract and generalized measures of policy learning used in much research on policy learning, the proposed research breaks new ground by evaluating learning through quantitative indicators of systems thinking in cognitive maps of collaborative decision-making processes. In so doing, the research makes significant methodological contributions through application of the tools and perspectives of network science to evaluate cognitive maps. Likewise, rigorous assessment of implementation enables evaluation of how the performance of decentralized governance systems varies according to patterns of interdependence among decision-making processes. This research is critical for developing a more complete model of how cognitive, social, and institutional dynamics shape risk governance systems, and ultimately the resilience of communities and regions. The project is jointly supported by the Decision, Risk and Management Sciences Program of the Social and Economic Sciences Division and the NSF 2026 Fund Program in the Office of Integrated Activities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.