Archetype analysis in sustainability research: methodological portfolio and analytical frontiers

Abstract

In sustainability research, archetype analysis reveals patterns of factors and processes that repeatedly shape socialecological systems. These patterns help improve our understanding of global concerns, including vulnerability, land management, food security, and governance. During the last decade, the portfolio of methods used to investigate archetypes has been growing rapidly. However, these methods differ widely in their epistemological and normative underpinnings, data requirements, and suitability to address particular research purposes. Therefore, guidance is needed for systematically choosing methods in archetype analysis. We synthesize strengths and weaknesses of key methods used to identify archetypes. Demonstrating that there is no "one-size-fits-all" approach, we discuss advantages and shortcomings of a range of methods for archetype analysis in sustainability research along gradients that capture the treatment of causality, normativity, spatial variations, and temporal dynamics. Based on this discussion, we highlight seven analytical frontiers that bear particular potential for tackling methodological limitations. As a milestone in archetype analysis, our synthesis supports researchers in reflecting on methodological implications, including opportunities and limitations related to causality, normativity, space, and time considerations in view of specific purposes and research questions. This enables innovative research designs in future archetype analysis, thereby contributing to the advancement of sustainability research and decision-making.

Design and quality criteria for archetype analysis

“…Archetype analysis, as understood in sustainability research, is a comparative approach that seeks to identify recurrent patterns among cases in which general regularities that apply to all cases cannot be expected (Eisenack et al 2006). The number of applications of archetype analysis has risen in recent years (Oberlack et al 2019), giving rise to a growing portfolio of methods (Sietz et al, 2019). However, researchers currently face a lack of standard research designs and quality criteria.…”

“…Archetype analysis is situated between these two extremes. It is an approach that is able to accommodate both inductive and deductive research designs, a range of qualitative and quantitative methods (e.g., cluster analysis, grounded theory, meta-analysis of case studies, process tracing and simulation; see Sietz et al 2019), and different epistemologies.…”

Mapping social-ecological systems archetypes

“…Our study also contributes to a growing literature characterizing systems archetypes in SES [14,15,40]. The concept of archetype, first introduced by Forrester [47], refers to canonical structures or causal building blocks to many dynamical systems and their managerial problems.…”

“…Based on this pattern we can speculate where an additional dam is likely to have a similar effect, or more importantly, where an additional reservoir is not likely to have an impact on food production. These patterns are relevant for SES theory development because it help us understand what works and where [40], or to circumvent the problem of context dependence that Ostrom describes. However, these results cannot be interpreted as causal effects.…”

“…However, the studies do not provide guidance on how to make choices regarding optimal number of clusters or algorithmic selection (with exception of [36,38,39]), limiting their replicability when applied to different places or data. These choices remain idiosyncratic in the SES literature [5,40], they depend on tacit knowledge of the researchers, and hence there has been no way of assessing best practices. Here we apply clustering techniques to SES data while explicitly addressing these limitations.…”