Dynamic Archetype Analysis in Sustainability Science
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Date
2024
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Abstract
"Archetype analysis has been used to study changes in a wide range of social-ecological systems. However, it is still an open question how to aptly address the dynamic aspects of archetypes, considering changes of archetypes over time and their underlying drivers. By capturing change and dynamics in archetypes, we would be better equipped to theorize about causality in sustainability transitions. Here, we conceptualize and classify different approaches to develop archetype analysis from a time-dynamic perspective. We drew on previous research that has incorporated temporal dynamics when studying archetypes, and also theorized on new potential approaches that could be developed. We conducted a proof-of-concept analyses using cluster analysis, causal loop diagrams and dynamic time warping to test their ability to analyze dynamic archetypes. Therefore, we used data from the Shared Socio-economic Pathways (SSPs) database and their three main drivers of social-ecological system change: population, urbanization, and gross domestic product. Our results showcase promising quantitative methods for generating dynamic archetypes, and empirical insights gained from the different approaches. In identifying mechanisms of change for SSPs in UK, we illustrate how triggers and mechanisms interact to produce varying degrees of likelihood of transition between different SSPs. Looking globally at clusters of countries following similar SSP pathways, we see that countries that differ in historical pathways share projected future patterns of change. Lastly, we propose how to expand the eight core principles of archetype analysis to also cover temporal dynamics. This is a milestone to better understand system changes over time and to develop resilience and adaptation mechanisms to an ever-changing world."
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Abstract of working paper
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sustainability