Explore the vast range of titles available.

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.

Against the backdrop of rural deprivation during the rapid urbanization of China since the end of the previous century, rural renewal has been regarded as a vital strategy for facilitating rural sustainability. Rural renewal in contemporary China involves activities that replan, consolidate, and redevelop the extant and idle rural construction land and then convert such land for alternative uses, including new rural settlement construction and rural industry development. However, given the regionally decentralized authoritarian (RDA) regime of China, i.e., a combination of political centralization and economic regional decentralization, the governance of rural renewal and its performance show great diversity. The objective of this study was to explore and elucidate the underlying patterns of sustainable rural renewal. Thus, from the social-ecological systems (SES) perspective, an archetype analysis was conducted based on primary data from 27 cases from the eastern, central, and western parts of China. In total, eight archetypical patterns were extracted, and the following three overarching implications were observed: (1) a governance system aligning with the attributes of rural land resources, the characteristics of actors, and the properties of interactions is essential for sustainable rural renewal; (2) decentralized or self-organized governance emerges to facilitate sustainable rural renewal; and (3) a long-term perspective of designing and enforcing rural renewal and distinctive land resource endowment contribute to rural sustainability. These findings may benefit China and other regions pursuing rural sustainability.

A key challenge in addressing the global degradation of natural resources and the environment is to effectively transfer successful strategies across heterogeneous contexts. Archetype analysis is a particularly salient approach in this regard that helps researchers to understand and compare patterns of (un)sustainability in heterogeneous cases. Archetype analysis avoids traps of overgeneralization and ideography by identifying reappearing but nonuniversal patterns that hold for well-defined subsets of cases. It can be applied by researchers working in inter- or transdisciplinary settings to study sustainability issues from a broad range of theoretical and methodological standpoints. However, there is still an urgent need for quality standards to guide the design of theoretically rigorous and practically useful archetype analyses. To this end, we propose four quality criteria and corresponding research strategies to address them: (1) specify the domain of validity for each archetype, (2) ensure that archetypes can be combined to characterize single cases, (3) explicitly navigate levels of abstraction, and (4) obtain a fit between attribute configurations, theories, and empirical domains of validity. These criteria are based on a stocktaking of current methodological challenges in archetypes research, including: to demonstrate the validity of the analysis, delineate boundaries of archetypes, and select appropriate attributes to define them. We thus contribute to a better common understanding of the approach and to the improvement of the research design of future archetype analyses.

The development and implementation of measures aimed at climate change adaptation face many obstacles. This Perspective takes stock of current research on barriers to adaptation, and argues that more comparative research is now required to increase our in-depth understanding of barriers and to develop strategies to overcome them. The concept of barriers is increasingly used to describe the obstacles that hinder the planning and implementation of climate change adaptation. The growing literature on barriers to adaptation reveals not only commonly reported barriers, but also conflicting evidence, and few explanations of why barriers exist and change. There is thus a need for research that focuses on the interdependencies between barriers and considers the dynamic ways in which barriers develop and persist. Such research, which would be actor-centred and comparative, would help to explain barriers to adaptation and provide insights into how to overcome them.

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.

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.

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.

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 ion. 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. Read the free Plain Language Summary for this article on the Journal blog.

This paper identifies the literature that deals with adaptation to climate change in the transport sector. It presents a systematic review of the adaptations suggested in the literature. Although it is frequently claimed that this socially and economically important sector is particularly vulnerable to climate change, there is comparatively little research into its adaptation. The 63 sources we found are analysed following an action framework of adaptation. This distinguishes different adaptational functions and means of adaptation. By an open coding procedure, a total of 245 adaptations are found and classified. The paper shows a broad diversity of interdependent actors to be relevant—ranging from transportation providers to public and private actors and households. Crucial actors are hybrid in terms of being public or private. A substantial share of the identified adaptations follows a top-down adaptation policy pattern where a public or hybrid operator initiates action that affects private actors. Most of the exceptions from this pattern are technical or engineering measures. Identified adaptations mostly require institutional means, followed by technical means, and knowledge. Generally, knowledge on adapting transport to climate change is still in a stage of infancy. The existing literature either focuses on overly general adaptations, or on detailed technical measures. Further research is needed on the actual implementation of adaptation, and on more precise institutional instruments that fill the gap between too vague and too site-specific adaptations.