Exogenous factors in collective policy learning: the case of municipal flood risk governance in the Netherlands

Abstract

Conceptualizing and analyzing collective policy learning processes is a major ongoing theoretical and empirical challenge. A key gap concerns the role of exogenous factors, which remains under-theorized in the policy learning literature. In this paper, we aim to advance the understanding of the role that exogenous factors play in collective learning processes. We propose a typology of exogenous factors (i.e. material, socioeconomic, institutional, discursive), and subsequently apply this in a comparative study of flood risk policymaking in two municipalities in the Netherlands. We find that exogenous factors are indeed essential for understanding collective learning in these cases, as the combined influence with endogenous factors can steer similar learning processes towards different learning products. We conclude our contribution by identifying two opportunities for further developing the collective learning framework, namely regarding the distinction of varying learning products, and the dynamics of exogenous factors over time.

Tackling key challenges around learning in environmental governance

“…For example, Koebele's article illustrates how to measure individual learning and then aggregate indicators of individual learning to measure collective-level learning. De Voogt and Patterson (2019) use a most-similar case design to zoom into theoretically relevant variables that can help explain different learning products associated with mitigating flood risks facing two similar municipal governments. Newig et al (2019) employ a large cross-case dataset and common coding framework using data from published research, which provides a novel approach to theory testing.…”

“…In doing so, this special issue provides a nice complement to the recent JEPP special issue on learning that focuses specifically on the context of urban climate governance (Wolfram et al, 2019). For example, two of the papers in this special issue look at urban flood risk in European cities (De Voogt & Patterson, 2019;Mukhtarov, Dieperink, Driessen & Riley, 2019). Other researchers examine learning in planning processes in forestry management (Ricco & Schultz, 2019), new collaborative mechanisms around water management (Koebele, 2019), and learning in disaster recovery processes (Crow & Albright, 2019).…”

“…The papers in this special issue further illustrate how to apply a range of theoretical and methodological approaches to study questions about learning in environmental governance. Several follow a synthetic and integrative theoretical approach to the learning scholarship (De Voogt & Patterson, 2019;Newig et al, 2019;Rietig, 2019), while others apply a collective learning framework that we developed to guide analyses of the social, structural, and technical factors that can influence learning processes and products (Heikkila & Gerlak, 2013). Methodologically, some of the more common approaches used to study learning in this special issue include document analysis, interviews, and surveys (Crow & Albright, 2019;De Voogt & Patterson, 2019;Koebele, 2019;Ricco & Schultz, 2019;Rietig, 2019).…”

“…Several follow a synthetic and integrative theoretical approach to the learning scholarship (De Voogt & Patterson, 2019;Newig et al, 2019;Rietig, 2019), while others apply a collective learning framework that we developed to guide analyses of the social, structural, and technical factors that can influence learning processes and products (Heikkila & Gerlak, 2013). Methodologically, some of the more common approaches used to study learning in this special issue include document analysis, interviews, and surveys (Crow & Albright, 2019;De Voogt & Patterson, 2019;Koebele, 2019;Ricco & Schultz, 2019;Rietig, 2019). We also see the use of process tracing and ethnographic approaches (Mukhtarov et al, 2019), participant observation (Ricco & Schultz, 2019;Rietig, 2019), and a meta-analysis of existing literature (Newig et al, 2019).…”

“…For instance, Crow and Albright (2019) illustrate the degree of damage of floods as a factor associated with learning. Exogenous events may come up quickly as in the case of a large-scale flood, but as De Voogt and Patterson (2019) find, slow moving factors such as demographic trends can also have a substantial impact on learning within policymaking processes when they build up and reach a threshold point. As such, they argue for the importance of paying close attention to the temporal dimensions of exogenous factors, and not simply looking at crises that occur at a given point in time, while Crow and Albright (2019) underscore the importance of the magnitude of exogenous events.…”