Do democratic elections affect policy outcomes, and how do these effects evolve over time? Existing evidence is mixed, focusing on federal elections in two-party systems using RDDs. We study municipal elections in Germany’s multiparty system, examining how electoral support for the pro-environmental Green Party affects photovoltaic power capacity investment. Exploiting quasi-random variation generated by staggered elections, we implement a triple difference-in-differences design using panel data (1990-2022). We find strongly time-dependent electoral effects. Additional electoral support generates sizable short-run increases in capacities (+3.4 MW/municipality), including anticipation effects. These effects reverse in the long-run (-4.2 MW/municipality), primarily driven by less residential capacity.

Sustainability research often seeks to transfer insights across cases, but the heterogeneity of contexts and outcomes presents significant challenges. What works in one case may fail in another, requiring an approach that combines classification with explanation. Classifying cases into several types, each with a particular explanation, however, involves a trade-off between too broad and too fine-grained classes. Existing studies often address this trade-off in ways that are difficult to reproduce, highlighting the need for more systematic and replicable methods. To address this gap, this study develops quantitative metrics and standard procedures that are replicable across contexts. They enable identifying archetypes from binary data sets using formal concept analysis (FCA). The novel procedures are demonstrated by replicating two previously published archetype analyses on land use and climate change adaptation. We propose three core steps (formal concept analysis, concept filter, theoretical analysis) alongside two optional steps (grouping, optimal concept selection). Key metrics, including consistency, coverage, richness, size, and lift, guide these steps. We show that the procedures enhance reproducibility and speed up analysis compared with previous approaches, and help determine the appropriate number of archetypes to provide more parsimonious research findings. This study thus contributes to methodological rigor in case-based sustainability research by balancing generality and particularity of archetype analysis.

Cities have taken center stage in the fight against climate change. Research identified key conditions shaping how cities tackle climate change but hasn't yet addressed how such conditions interact in order to reduce emissions. The present paper contributes to filling this gap through a crisp-set Qualitative Comparative Analysis of 34 CDP-reporting cities, identifying combinations of institutional and socioeconomic factors that are systematically associated with emission reductions. Results show emission reductions both in presence and in absence of favorable socioeconomic conditions. Under favorable socioeconomic conditions, institutions seem central to the task of steering the capacities of the local business community and reaping scale benefits. Under unfavorable socioeconomic conditions, institutions seemingly play a key role in gathering resources, reaching out to broader networks on the international stage. Implications for policy and research are explored.

Archetypes are increasingly used as a methodological approach to understand recurrent patterns in variables and processes that shape the sustainability of social-ecological systems. The rapid growth and diversification of archetype analyses has generated variations, inconsistencies, and confusion about the meanings, potential, and limitations of archetypes. Based on a systematic review, a survey, and a workshop series, we provide a consolidated perspective on the core features and diverse meanings of archetype analysis in sustainability research, the motivations behind it, and its policy relevance. We identify three core features of archetype analysis: recurrent patterns, multiple models, and intermediate abstraction. Two gradients help to apprehend the variety of meanings of archetype analysis that sustainability researchers have developed: (1) understanding archetypes as building blocks or as case typologies and (2) using archetypes for pattern recognition, diagnosis, or scenario development. We demonstrate how archetype analysis has been used to synthesize results from case studies, bridge the gap between global narratives and local realities, foster methodological interplay, and transfer knowledge about sustainability strategies across cases. We also critically examine the potential and limitations of archetype analysis in supporting evidence-based policy making through context-sensitive generalizations with case-level empirical validity. Finally, we identify future priorities, with a view to leveraging the full potential of archetype analysis for supporting sustainable development.

A growing number of studies apply the social-ecological systems (SES) framework with its standardized set of variables to examine place-based environmental governance. Yet, due to the wide diversity of social-ecological systems, a general theory about how variables interact-and systems can be governed-lacks empirical support. Despite many case studies, knowledge cumulation is hindered by data heterogeneity, and by the difficulties with synthesizing a large number of cases into middle-range theories, possibly understood as re-occurring patterns of the larger theoretical puzzle of environmental governance. Thus, this paper aims to cumulate knowledge by identifying repeating configurations of variables across 71 models from SES framework case studies using archetype analysis. We propose a building-blocks approach to identify eight archetypes, each characterized by a triad (presence of three variables), an explanation of this triad, and a qualitative characterization with cases which exemplify them. The triads relate to, for example: shared operational agency; small households in remote, inaccessible places; property and accountability; or formal investment conditions. We show how a relatively small set of triads can be combined in various ways to represent a larger diversity of SES, and illustrate this by re-visiting several cases. We argue that identifying these recurring archetypes advances the field because it allows scholars to focus their theorizing and empirical research around a known set of triads. More broadly, the paper contributes to advancing empirically supported claims about SES and environmental governance, new uses of the SES framework, and techniques for knowledge cumulation using archetype analysis.

The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) relies on future scenarios in its assessments of global social-ecological systems. Scenarios explicitly or implicitly embed normative positions (e.g., values for nature, nature’s contributions to people, good quality of life). Such scenario values shape how scenario narratives evolve, e.g. through driving forces, framings, or ways how decisions are legitimized within a given scenario. Initial research in futures studies has examined how scenario values depend on whose voices are included in scenario co-design. However, less attention has been paid so far to explicitly assessing the extent to which scenario values are associated with different types of scenario co-designers. Our paper expands this knowledge with a set of novel analyses building on the comprehensive review of scenarios in the IPBES values assessment. To this end, we conducted a formal archetype analysis of 257 scenarios assessed in the IPBES values assessment to identify re-appearing archetypal configurations of values and their link to the actors involved as scenario co-designers. The results show that scenarios valuing nature for itself and its benefits to societal well-being were co-designed by experts and academics less frequently than expected under the assumption of stochastic independence; on the contrary, such scenarios were co-designed more frequently than expected by governmental and community actors. The paper illustrates how archetype analysis can contribute to the validation and further development of scientific knowledge feeding into science-policy assessments. The findings are important to acknowledge how scenarios express and possibly re-enforce peoples’ normative positions, and what role values might play when scenarios get translated into real-world decisions and actions.

Although social learning (SL) conceptualization and implementation are flourishing in sustainability sciences, and its non-rigid conceptual fluidity is regarded as an advantage, research must advance the understanding of SL phenomenon patterns based on empirical data, thus contributing to the identification of its forms and triggering mechanisms, particularly those that can address urgent Anthropocene socio-ecological problems. This study aims to discover fundamental patterns along which SL in natural resources management differs by identifying SL archetypes and establishing correlations between the SL process and overall geopolitical conditions. Using a systematic literature review comprising 137 case studies in the five continents, content analysis, and correlations were performed. Results show two main archetypes of social learning (endogenous and exogenous). Their occurrence was linked, to where social learning occurs and how venues/preconditions for social learning are placed. In the Global South, endogenous SL should be better potentialized as a catalyzer of deliberative processes for sustainable natural resources management.

Abstract There is a need to synthesize the vast amount of empirical case study research on social‐ecological systems (SES) to advance theory. Innovative methods are needed to identify patterns of system interactions and outcomes at different levels of abstraction. Many identifiable patterns may only be relevant to small sets of cases, a sector or regional context, and some more broadly. Theory needs to match these levels while still retaining enough details to inform context‐specific governance. Archetype analysis offers concepts and methods for synthesizing and explaining patterns of interactions across cases. At the most basic level, there is a need to identify two and three independent variable groupings (i.e. dyads and triads) as a starting point for archetype identification (i.e. as theoretical building blocks). The causal explanations of dyads and triads are easier to understand than larger models, and once identified, can be used as building blocks to construct or explain larger theoretical models. We analyse the recurrence of independent variable interactions across 71 quantitative SES models generated from qualitative case study research applying Ostrom's SES framework and examine their relationships to specific outcomes (positive or negative, social or ecological). We use hierarchical clustering, principal component analysis and network analysis tools to identify the frequency and recurrence of dyads and triads across models of different sizes and outcome groups. We also measure the novelty of model composition as models get larger. We support our quantitative model findings with illustrative visual and narrative examples in four case study boxes covering deforestation in Indonesia, pollution in the Rhine River, fisheries management in Chile and renewable wind energy management in Belgium. Findings indicate which pairs of two (dyads) and three (triads) variables are most frequently linked to either positive or negative, social or ecological outcomes. We show which pairs account for most of the variation of interactions across all the models (i.e. the optimal suite). Both the most frequent and optimal suite sets are good starting points for assessing how dyads and triads can fulfil the role of explanatory archetype candidates. We further discuss challenges and opportunities for future SES modelling and synthesis research using archetype analysis. Read the free Plain Language Summary for this article on the Journal blog.

Cities increasingly address climate change, e.g. by pledging city-level emission reduction targets. This is puzzling for the provision of a global public good: what are city governments’ reasons for doing so, and do pledges actually translate into emission reductions? Empirical studies have found a set of common factors which relate to these questions, but also mixed evidence. What is still pending is a theoretical framework to explain those findings and gaps. This paper thus develops a theoretical public choice model. It features economies of scale and distinguishes urban reduction targets from actual emission reductions. The model is able to explain the presence of targets and public good provision, yet only under specified conditions. It is also able to support some stylized facts from the empirical literature, e.g. on the effect of city size, and resolves some mixed evidence as special cases. Larger cities chose more ambitious targets if marginal net benefits of mitigation rise with city size—if they set targets at all. Whether target setting is more likely for larger cities depends on the city type. Two types are obtained. The first type reduces more emissions than a free-riding city. Those cities are more likely to set a target when they are larger. However, they miss the self-chosen target. Cities of the second type reach their target, but mitigate less than a free-riding city. A third type does not exist. With its special cases, the model can thus guide further empirical and theoretical work.

Unilateral climate policies can lead to carbon leakage between countries. Deposit markets, where participants trade the right to keep fossil fuels unexploited in-situ, are a promising policy proposal to prevent leakage. For a single fossil fuel, deposit markets can only restore efficiency if there is no market power on the deposit market. With multiple fuels, however, multiple (interdependent) deposit markets could give rise to additional market power. We thus study deposit markets with market power and multiple fuels, and focus on comparing second-best policies. In contrast to a setting with a single fuel, more complex carbon leakage channels between both, countries and fuels, arise. Such effects can even hinder deposit markets covering all fuels from being implemented. At the same time, we identify conditions where deposit markets induce countries without emission reduction incentives to supply a cleaner fuel mix. Regarding the political economy, deposit markets covering all fuels can improve each country's welfare compared to those covering only one fuel. Deposit markets which cover only a single fuel or multiple fuels rank differently in terms of consumer and producer rents. These welfare rankings can have highly relevant implications for policy-making. Even with market power, deposit markets covering multiple fuels can Pareto-dominate a situation with unilateral, domestic policies.

Cities have become increasingly vocal in addressing climate change, crafting climate mitigation strategies, and committing to ambitious emission reductions. Previous studies found no evidence that ambitious targets, analyzed as a single factor, translate into actual emission reductions in cities. Yet, is this still the case if ambitious targets are analyzed in combination with other institutional and socioeconomic factors? We carry out a fuzzy-set Qualitative Comparative Analysis of all cities reporting their emissions to the Carbon Disclosure Project (CDP) where data are available for at least four years between 2000 and 2020. The analysis tests whether ambitious emission reduction targets, in conjunction with size, affluence, and favourable domestic enabling conditions are systematically associated with substantial emission reductions. Results show different configurations leading to emission reductions. In some configurations, ambitious targets are redundant or counterproductive. In other configurations, ambitious targets are necessary to achieve emission reductions. These results call for greater attention to cities' heterogeneity when studying urban climate governance. Three configurations seem systematically associated with downward emission trends: being large and affluent; being small and without ambitious emission reduction targets; and being large, with ambitious emission reduction targets but without favourable domestic enabling conditions.Ambitious emission targets and favourable conditions at the national level seem redundant for emission reductions in cities that are both large and affluent. These cities seem to achieve emission reductions regardless of the presence of ambitious targets.Small cities need to cooperate with other actors to reduce emissions and therefore need to be pragmatic and strategic in setting their targets.Large cities may need to set ambitious targets to exploit the benefits of their size for emission reduction. This seems to be necessary when they are lacking favourable conditions at the national level.

Values have been recognized as critical leverage points for sustainability transformations. However, there is limited evidence unpacking which types of values are associated with specific types of sustainable and unsustainable futures, as described by future scenarios and other types of futures-related works. This paper builds on a review of 460 future scenarios, visions, and other types of futures-related works in the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services Values Assessment, synthesizing evidence from academia, private sector, governmental and non-governmental strategies, science-policy reports, and arts-based evidence, to identify the types of values of nature that underlie different archetypes of the future. The results demonstrate that futures related to dystopian scenario archetypes such as Regional Competition, Inequality, and Breakdown are mostly underpinned by deeply individualistic and materialistic values. In contrast, futures with more sustainable and just outcomes, such as Global Sustainable Development and Regional Sustainability, tend to be underpinned by a more balanced combination of plural values of nature, with a dominant focus on nature's contribution to societal (as opposed to individual) aspects of well-being. Furthermore, the paper identifies research gaps and illustrates the key importance of acknowledging not only people's specific values directly related to nature, such as instrumental, intrinsic, and relational human-nature values and relationships, but also broad values and worldviews that affect the interactions between nature and society, with resulting impacts on Nature's Contributions to People and opportunities for a good quality of life.

Zusammenfassung In Deutschland ist – wie in vielen Mitgliedstaaten der EU – Anpassung an den Klimawandel als eigenes Politikfeld mit einer nationalen Strategie, einem Maßnahmenplan sowie zuständigen Institutionen etabliert. Während zu Beginn die Informationsgewinnung und praxisorientierte Modellprojekte im Vordergrund standen, liegt der Fokus zunehmend auf einer breiten gesellschaftlichen Umsetzung von Klimaanpassungsmaßnahmen, um den bekannten Klimafolgen zu begegnen. Im Mittelpunkt des Kapitels stehen Klimaanpassungsstrategien auf den unterschiedlichen politischen Ebenen – von der EU bis zur Kommune – sowie Hemmnisse und Ansätze erfolgreicher Umsetzung von Klimaanpassung.

If local governments reduce greenhouse gas emissions, they will not see effects unless a very large number of other actors do the same. However, reducing greenhouse gas emissions can have multiple local “co-benefits” (improved air quality, energy savings, even energy security), creating incentives for local governments to reduce emissions—if just for the local side-effects of doing so. Available empirical research yet shows a large gap between co-benefits as a rationale and an explanatory factor for climate mitigation by local governments: co-benefits are seemingly very large, but do not seem to drive local mitigation efforts. Relying on policy documents, available research, and other written sources, the present paper consists of a multiple case study addressing the link between co-benefits and climate mitigation in Moscow, Paris, and Montreal. Air quality plays a very different role in each case, ranging from a key driver of mitigation to a liability for local climate action. This heterogeneity of mechanisms in place emerges as a likely explanation for the lack of a clear empirical link between co-benefits and local mitigation in the literature. We finally discuss implications for urban climate action policy and research.

Fossile Kapitalanlagen entlang der gesamten Wertschöpfungskette – von Reserven bis zu Infrastruktur und Unternehmenswerten – werden durch die Transformation des Energiesystems in den nächsten Jahrzehnten massiv an Wert verlieren, also zu „Stranded Assets“ werden. Die Erfassung dieser Verluste hilft, Einzelinteressen in der Klimapolitik besser zu verstehen.

Research on urban climate action has identified a broad range of potential factors explaining why and how local governments decide to tackle climate change. However, empirical evidence linking such factors in order to explain actual urban climate action has so far been mixed. To address this roadblock, our paper relies on a novel approach, postulating that different configurations of factors may lead to the same outcome (“equifinality”), through a qualitative comparative analysis (QCA). It is based on an available data set of local climate mitigation plans in 885 European cities. We find that urban climate action is systematically associated with four qualitatively different configurations of factors, each with its own consistent narrative (“networker cities”, “green cities”, “lighthouse cities”, “fundraising cities”). Crucially, some factors play a positive role in some configurations, a negative in others, and no role in further configurations (e.g., whether a city is located in a country with supportive national climate policies). This confirms that there is no single explanation for urban climate action. Achieving greater robustness in empirical research about urban climate action may thus require a shift, both conceptual and methodological, to the interactions between factors, allowing for different explanations in different contexts.

Does climate change adaptation require that investments are designed to be more robust? What about when climate change is more uncertain? What if the climate changes faster? This decision problem is difficult if the design of the investments is irreversible for their lifetime, for instance, in the construction industry. We study an irreversible design decision when the investment starts, combined with an irreversible option to abandon. The design determines the investment's robustness to sustain detrimental conditions. We find that for short-lived investments, optimal robustness decreases if the climate changes faster, and increases if uncertainty is higher. For long-lived investments, these effects reverse. This has implications for decision makers who plan infrastructure adaptation, for instance, that adverse climate change does not require more robust investments under the identified circumstances.

Research on urban climate action has identified a broad range of potential factors explaining why and how local governments decide to tackle climate change. However, empirical evidence linking such factors in order to explain actual urban climate action has so far been mixed. To address this roadblock, our paper relies on a novel approach, postulating that different configurations of factors may lead to the same outcome (“equifinality”), through a qualitative comparative analysis (QCA). It is based on an available data set of local climate mitigation plans in 885 European cities. We find that urban climate action is systematically associated with four qualitatively different configurations of factors, each with its own consistent narrative (“networker cities”, “green cities”, “lighthouse cities”, “fundraising cities”). Crucially, some factors play a positive role in some configurations, a negative in others, and no role in further configurations (e.g., whether a city is located in a country with supportive national climate policies). This confirms that there is no single explanation for urban climate action. Achieving greater robustness in empirical research about urban climate action may thus require a shift, both conceptual and methodological, to the interactions between factors, allowing for different explanations in different contexts.

Recent years have seen a proliferation of studies that use archetype analysis to better understand and to foster transitions toward sustainability. This growing literature reveals a common methodological ground, as well as a variety of perspectives and practices. In this paper, we provide an historical overview of the roots of archetype analysis from ancient philosophy to recent sustainability science. We thereby derive core features of the archetype approach, which we frame by eight propositions. We then introduce the Special Feature, "Archetype Analysis in Sustainability Research," which offers a consolidated understanding of the approach, a portfolio of methods, and quality criteria, as well as cutting-edge applications. By reflecting on the Special Feature's empirical and methodological contributions, we hope that the showcased advances, exemplary applications, and conceptual clarifications will help to design future research that contributes to collaborative learning on archetypical patterns leading toward sustainability. The paper concludes with an outlook highlighting central directions for the next wave of archetype analyses.