Copyright © 2019 by the author(s). Published here under license by the Resilience Alliance. Eisenack, K., S. Villamayor-Tomas, G. Epstein, C. Kimmich, N. Magliocca, D. Manuel-Navarrete, C. Oberlack, M. Roggero, and D. Sietz. 2019. Design and quality criteria for archetype analysis. Ecology and Society 24(3):6. https://doi.org/10.5751/ES-10855-240306 Synthesis, part of a Special Feature on Archetype Analysis in Sustainability Research Design and quality criteria for archetype analysis Klaus Eisenack 1, Sergio Villamayor-Tomas 2, Graham Epstein 3, Christian Kimmich 4, Nicholas Magliocca 5, David Manuel-Navarrete 6, Christoph Oberlack 7,8, Matteo Roggero 1 and Diana Sietz 9,10 ABSTRACT. 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. Key Words: abstraction; archetype analysis; generalization; ideographic trap; interdisciplinary collaboration; panacea; pattern; research design; social-ecological systems; qualitative; quantitative; validity INTRODUCTION criteria. Such criteria would help to address common Natural resources and the environment continue to degrade all methodological challenges when designing and conducting over the globe, even though we have known about these problems archetype analyses. Archetype analysis is thus not an exception for decades. There is thus an urgent need for new ways to build to the general difficulties and problems affecting inter- and knowledge that both explains the drivers of sustainability transdisciplinary sustainability research. We therefore aim to problems and helps to find solutions in diverse social and contribute to the development of quality criteria to guide ecological contexts. Many scholars and experts emphasize the researchers applying diverse theories and methods when they need for inter- or transdisciplinary approaches and design future archetype analyses. methodological pluralism to address this challenge (e.g., Poteete The growing body of scholarship on archetypes demonstrates its et al. 2010, Ruppert-Winkel et al. 2015, Karpouzoglou et al. 2016, value to the theory and practice of sustainability and consolidates Defila and Di Giulio 2018). Those approaches, however, unifying assumptions of the approach (Oberlack et al. 2019). frequently suffer from inconsistent quality criteria (Defila and Di Archetype analysis generally rejects a single universal model that Giulio 2015, Belcher et al. 2016). Shared quality criteria are crucial explains or seeks to achieve sustainability across a complete to support rigorous research designs that lead to high quality universe of cases (Young et al. 2006). This addresses concerns that outcomes, better knowledge integration, and ultimately, sustainability research is frequently complicated by the diversity improved decision making (Bergmann et al. 2005, Stoll- of social, ecological, and institutional contexts (Warren 2002, Kleemann and Pohl 2007, Belcher et al. 2016, Magliocca et al. Schachhuber 2004, Ostrom 2005, Padmanabhan and Jungcurth 2018). 2012). Neglecting this diversity can lead to the imposition of One rapidly developing approach to study the sustainability of policies that are fundamentally at odds with the social-ecological social-ecological systems in inter- and transdisciplinary settings conditions in which they are implemented (Brown 2003, Acheson is archetype analysis (UNEP 2007, for a systematic review see 2006, Epstein et al. 2015). In contrast, archetype analysis identifies Oberlack et al. 2019). Archetype analysis, as understood in multiple recurrent patterns (archetypes) that function as building sustainability research, is a comparative approach that seeks to blocks to explain outcomes in multiple, more or less identify recurrent patterns among cases in which general heterogeneous cases (Eisenack 2012, Oberlack and Eisenack regularities that apply to all cases cannot be expected (Eisenack 2018). It characterizes and classifies environmental problems and et al. 2006). The number of applications of archetype analysis has opportunities, explains each class based on a theory, and thereby risen in recent years (Oberlack et al. 2019), giving rise to a growing enables planners and policymakers to learn from the experience portfolio of methods (Sietz et al., 2019). However, researchers of others working in different areas to address similar problems currently face a lack of standard research designs and quality (Eisenack et al. 2006, UNEP 2007, Kok et al. 2016). 1 Resource Economics Group, Humboldt-Universität zu Berlin, Berlin, Germany, 2Institute of Environmental Science and Technology (ICTA), Autonomous University of Barcelona, Barcelona, Spain, 3Environmental Change and Governance Group, School of Environment, Resources and Sustainability, University of Waterloo, Canada, 4Department of Environmental Studies, Masaryk University, Brno, Czechia, 5University of Alabama, Department of Geography, Tuscaloosa, Alabama, USA, 6School of Sustainability, Arizona State University, Tempe, Arizona, USA, 7 Institute of Geography, University of Bern, Bern, Switzerland, 8Centre for Development and Environment (CDE), University of Bern, Bern, Switzerland, 9Potsdam Institute for Climate Impact Research, Earth System Analysis Research Domain, Potsdam, Germany, 10Wageningen University, Soil Physics and Land Management Group, Wageningen, The Netherlands Ecology and Society 24(3): 6 https://www.ecologyandsociety.org/vol24/iss3/art6/ Quantitative analyses are sometimes criticized for overgeneralization explains its configuration of attributes, in which the attributes are and disregarding the role of context (Ragin 2000, Bennett and taken from the common vocabulary. The vocabulary might Elman 2006), while qualitative studies are sometimes criticized contain, e.g., presence of fossil-fuel industries, influence of certain for being overly specific, neglecting patterns that exist across cases kinds of lobbies, participation in international standardization (Basurto and Ostrom 2009). Archetype analysis is situated processes, etc. Depending on the research questions, components between these two extremes. It is an approach that is able to might be city quarters, economics sectors, or specific political accommodate both inductive and deductive research designs, a processes. range of qualitative and quantitative methods (e.g., cluster analysis, grounded theory, meta-analysis of case studies, process Fig. 1. Simplified illustration of an archetype analysis of cities tracing and simulation; see Sietz et al. 2019), and different (cases represented by boxes, components by bullet points). Each epistemologies. archetype is characterized by a specific configuration of We present a joint reflection on the insights from a survey with attributes (icons in the circles) from a common vocabulary, experts in archetype analysis and from a collaborative effort at supplied with a theory (circle) and a domain of validity two international research workshops (Oberlack et al. 2017, (containing all cities to which bulleted arrows from one circle Eisenack et al. 2018). We aim to identify a coherent set of quality lead). The approach identifies a suite of archetypes instead of a criteria that are consistent with reported challenges for and universal model. Like building blocks, archetypes can be definitions of archetype analysis. combined in different ways to explain the unique character of individual cases (multiple arrows pointing to single boxes). ARCHETYPE ANALYSIS IN SUSTAINABILITY RESEARCH Archetype analysis generally “investigates recurrent patterns of the phenomenon of interest at an intermediate level of abstraction to identify multiple models that explain the phenomenon under particular conditions” (Oberlack et al. 2019). Within this general understanding, we adopt a view of archetypes as building blocks (instead of case typologies, that are also considered as archetype analyses by Oberlack et al. 2019) and build on the following more detailed conceptualization. First, archetypes are nonuniversal, i.e., the analysis identifies multiple recurrent patterns across a set of heterogeneous empirical cases. The set of these patterns is called a suite of archetypes (cf. Eisenack et al. 2006, Oberlack and Eisenack 2018). Thus, an archetype does not need to hold in all cases. However, each archetype can hold in multiple cases. The archetype Archetypes are understood as mental representations of approach thus avoids getting stuck in the “ideographic trap” in relationships between attributes and processes that characterize which all cases are considered to be unique. Second, archetypes systems. The way that archetypes are developed and applied function as building blocks that can be combined with other depends on the purpose of the analysis and choice of methods. archetypes to explain phenomena in individual cases. Multiple The identification of archetypes can be inductive, e.g., identifying archetypes can thus characterize a single case. Third, a suite of similar social-ecological patterns in a large number of locations archetypes and the cases of interest are described by referring to (Sietz et al. 2017), or deductive, i.e., actively looking for a “common vocabulary of attributes.” Each description does not manifestations of a particular theory (Manuel-Navarrete et al. require the use of all attributes. Attributes can be characteristics, 2007). Furthermore, we argue that archetype analysis is compatible variables, qualities, factors, or other properties chosen at an with different epistemological positions (e.g., realist, constructivist, intermediate level of abstraction to achieve a balance between explanatory, or interpretive). Archetype analysis shares (but case-based validity and generalization. Fourth, the analysis recombines) some features with other approaches (e.g., qualitative classifies “components of cases” (e.g., phenomena or processes comparative analysis, QCA, Ragin 1989, Schneider and within cases) that are present in subsets of the universe of cases. Wagemann 2012; multiple case studies, Yin 2009; model-centered Thus, a single archetype does not necessarily characterize whole meta-analysis, Rudel 2008; and scenario archetypes, cf. King et al. cases, but certain aspects of them. Classes of components of cases 1994, Bennett 2005, Della Porta and Keating 2008; Sitas et al. are described through “configurations of attributes.” Each 2019). This adaptability is important to make archetype analysis archetype is further characterized by a theory that explains the suitable for inter- and transdisciplinary research. corresponding configuration of attributes. Thus, each archetype CHALLENGES FOR ARCHETYPE ANALYSIS in a suite is characterized by three elements: (1) a configuration One source for our argument is a survey with 28 experienced of attributes, together with (2) a theory, and (3) the set of cases researchers, who used archetype analysis, conducted in March 2017 in which it holds (called the domain of validity, which is a subset with a response rate of 61%, covering fields including agricultural of the universe of cases). sciences, climatology, economics, environmental sciences, Figure 1 illustrates these concepts. A suite of city archetypes might geography, institutional analysis, land-use science, modeling, and contain the patterns of global cities, cities in federal states, cities sociology (for more details see Oberlack et al. 2019). It yielded, that lead in climate protection, and so on. Each archetype’s theory inter alia, a repository of key papers and a collection of challenges. Ecology and Society 24(3): 6 https://www.ecologyandsociety.org/vol24/iss3/art6/ This collection was extended, synthesized, and discussed in a Boundaries of archetypes collaborative effort at two international research workshops with It is possible to conduct an archetype analysis that produces a 46 participants based in 12 countries from Asia, Europe, and very large suite of archetypes, each one characterized by a North and South America (Oberlack et al. 2017, Eisenack et al. complex configuration of many attributes encompassing social, 2018). After the first workshop, the authors developed the above ecological, and technological features (processes, structures), so definition of archetype analysis and discussed it in the second that each archetype only holds in a small number of cases. workshop. The discussion of participants’ experience with Alternatively, one can aim at a small suite, in which each archetype tackling the collected challenges led to a set of quality criteria. is characterized by a small and simple configuration of attributes. For this paper, the authors prioritized challenges and quality We might describe city archetypes by two attributes (e.g., being criteria in light of the key papers and a coherent line of argument. large/small and poor/wealthy, so that there are potentially four Some remaining issues are discussed below. We now turn to the city classes) or by many attributes in complex relations (e.g., prioritized challenges. referring to details of topography, infrastructure, economy, culture, political system, so that there are many classes). Validity of archetypes Depending on the research question, the best balance between Archetype analysis is fundamentally motivated by the pursuit of these extremes needs to be chosen. For instance, when should a explaining outcomes in heterogeneous cases that lack universal domain of validity be divided into two archetypes with more patterns. However, this presents a challenge: how can we establish narrow boundaries, or when should two domains be fused into the validity of the resulting archetype analysis? Scholars may one archetype with broader boundaries? The balance can be choose to ignore contradictory evidence by invoking limits to the expressed by the number of attributes per archetype, but also by external validity of a given archetype (i.e., its applicability beyond the number of archetypes in a suite because both perspectives the set of cases for which it has been developed). In other words, tend to be closely related. For example, Oberlack and Eisenack if one observation does not fit to an archetype, this does not falsify (2018) identified a suite of 21 archetypical barriers to climate the archetype, simply because archetypes are not required to be adaptation, each characterized by 2 to 4 attributes. Václavík et al. universal. It only falsifies the applicability of that archetype in (2013) used 32 land-use indicators to obtain 12 archetypes. United that case. In the face of this difficulty, few studies have actually Nations Environment Programmes (UNEP 2007) identified seven taken steps to validate the archetypes they identify, and yet archetypes of vulnerability, each of which contains multiple validation is crucial if archetype analysis is to provide vulnerability profiles (Kok et al. 2016). In the literature, there theoretically and empirically rigorous and practically useful seems to be no systematic criterion on how to select the knowledge. appropriate size, complexity, and number of archetypes. Internal validity refers to inferences within a particular study. If Challenges in delineating boundaries occur frequently in pattern cases in the study’s sample are relatively homogenous, a limited analysis like cluster analysis (Kaufman and Rousseeuw 1990). At set of attributes might explain their variation; so validity could one extreme we could classify all cases into one cluster, whereas be established using standard inferential statistics. However, this at the other, we could consider each case as a cluster on its own. approach has the potential to neglect factors that are important Although several standards have been proposed, there is still no within particular subpopulations of cases (e.g., Keys and agreement on how to determine the appropriate number of McConnell 2005, Sietz and Van Dijk 2015). Ultimately, internal clusters, or how to interpret their meanings. Similar challenges validity of an archetype analysis depends on the validity of the are known in QCA (Ragin 1989), a method which seeks to (combination of) methods used to study the cases and to classify determine logical conjunctions of attributes that are sufficient for the components. This is particularly obvious for meta-analyses an outcome. Qualitative comparative analysis produces multiple because they need to rely on the theories and configurations solutions, allowing the analyst to choose between more identified by the primary studies (e.g., Oberlack and Eisenack parsimonious but coarse conjunctions and more complex and 2017, Kimmich and Villamayor-Tomás 2018). precise ones. By contrast, external validity presents a particular challenge for For archetype analysis, the difficulty of defining boundaries stems archetype analysis. It refers to the domains of validity, or more more generally from a lack of clear or objective boundaries of generally to the universe of cases in which it is expected to hold social-ecological systems. Although ecological boundaries may (Sietz et al. 2011, 2017, Kok et al. 2016). For example, if we find be structured through species interactions (Cadenasso et al. 2003) a suite of archetypes of cities from a medium-sized sample, and physical gradients (Allen et al. 2001), they are socially external validity refers to our confidence in extending those to constructed by norms, rules, or habits (Smith and Varzi 2000). cities that are not in the sample. Standard inferential statistics Boundaries thus depend on theoretical conceptions and the approaches, for instance, aim at general results that apply to a research questions of the analyst. universe of cases that is broader than the sample, or at least to all those that fall within the ranges of independent variables in the For the analyst, there is a trade-off between more nuanced and sample (King et al. 1994). In contrast, many qualitative more coarse-grained statements. If archetypes are characterized approaches are cautious in trying to generalize beyond one or a by more attributes, their domain of validity will tend to shrink. small number of cases, placing significant limits on the It will be less likely that multiple archetypes hold in one case, and transferability of research findings. Archetype analysis falls the theories to explain the configurations will be less between these extremes. parsimonious. Simply said, the challenge is to find guidelines regarding the number of attributes per archetype required to achieve an appropriate balance between generalization and highlighting meaningful differences among cases. Ecology and Society 24(3): 6 https://www.ecologyandsociety.org/vol24/iss3/art6/ Fig. 2. Recommended design and quality criteria for archetype analysis. Numbers correspond to the following subsections with more details. The four columns propose possible strategies that may be chosen in a research design to approach the quality criteria (see explanations in the text). Appropriate attributes are measured, and the dimensions that are emphasized, which Archetype analysis aims to achieve a balance between abstract may include biophysical, socio-political, politico-economic, explanations and providing contextually explicit guidance to cultural, or psychological factors (e.g., Hofstede 1983, Cash et al. policymakers. However, the heterogeneity of social-ecological 2006, Anderies et al. 2013, Davidson 2013, Hatt 2013, Kimmich systems and diversity of institutional arrangements often requires 2013, Sietz 2014, Manuel-Navarrete 2015, Manuel-Navarrete and trade-offs between accuracy and meaning (Cox 2008). In light of Pelling 2015, Schmid et al. 2017). Further decisions relate to the this challenge, the outcome of an archetype analysis crucially resolution of institutional arrangements or options for decision depends on the common vocabulary of attributes. It is far from making considered (Oberlack 2017). The social-ecological- obvious how the attributes in the vocabulary should be systems framework, for instance, generally conceptualizes the determined. This involves choosing what to look at. Theories can universe of sustainability problems as common-pool resource be useful for vocabulary development but should not problems (Frey and Cox 2015) and has been even broadened in unnecessarily constrain empirical discovery. scope (McGinnnis and Ostrom 2014). Common-pool resource problems can be further subdivided, to consider cases with rules One key aspect of this challenge is to achieve a selection of for enforcement (Ostrom 1990, Cox et al. 2010) or, more attributes at an appropriate level of abstraction. Starting from the specifically, third-party enforcement (Agrawal and Goyal 2001). premise that every case is unique in some way, archetypes can only Recurrent archetypes in resource governance, such as dilemmas recur in multiple cases if the attributes are sufficiently abstract. or coordination problems, can be building blocks that are nested However, they should not be so abstract that important within recurrent network configurations of those situations differences cannot be expressed or captured. For instance, (Kimmich and Villamayor-Tomás 2018). institutional designs can be too generic to be applicable in any case because they are very abstract (panaceas, Ostrom et al. 2007). Finding the appropriate set of attributes represents thus a major On the other hand, the very idea of transferring insights and challenge for archetype analysis. It is however paramount to policies between cases implies some kind of generalization. As a avoiding both overgeneralization and the ideographic trap. There result, there is a clear need for guidance as to how one might is a clear need for strategies and guidance to determine the level systematically navigate between two extremes: meaningless of abstraction and the size of the common vocabulary of overabstraction or ideographic concreteness. The challenge is to attributes. achieve an appropriate balance between the analytical relevance (or significance) of attributes and their importance for QUALITY CRITERIA meaningful case-level descriptions. Based on the above, we suggest four quality criteria to further advance archetype analysis (see Fig. 2). In addition, we provide Archetype analysis also requires preanalytical decisions about suggestions for research strategies to achieve these quality criteria. which levels and scales of attributes and cases of interest will be Naturally, the criteria are additional to general standards for good relevant for the analysis (Kay 2008, Giampietro et al. 2009). Some scientific practice, and the specific standards of particular decisions refer to the geographic scales and places in which the methods used in the analysis. archetypes are expected to hold, e.g., from global to local (Sietz et al. 2011, Vidal Merino et al. 2018), at multiple scales (e.g., Sietz Figure 2 denotes the Recommended design and quality criteria 2014, Sietz et al. 2017), or combining individual and for archetype analysis. Numbers correspond to the following organizational levels (Villamayor-Tomás and García-López subsections with more details. The four columns propose possible 2017). Other decisions refer to the level of detail at which variables strategies that may be chosen in a research design to approach the quality criteria (see explanations in the text). Ecology and Society 24(3): 6 https://www.ecologyandsociety.org/vol24/iss3/art6/ An archetype analysis should specify the domain of validity for An archetype analysis should ensure that multiple archetypes can each archetype (1) be combined in different ways to characterize single cases (2) Establishing validity enhances the credibility of any archetype Archetype analysis analytically decomposes cases into analysis. This can build, in part, on the standards of the particular components that are classified by identifying recurrent methods chosen for an archetype analysis. It is helpful to configurations of attributes. Then, multiple archetypes can be distinguish between the validity of a single archetype and the combined, like building blocks, to produce a comprehensive validity of a suite of archetypes, as well as between internal and picture of a single case (Eisenack 2012). Building blocks allow us external validity. to economize upon the number of archetypes needed to characterize heterogeneous cases. The challenge is to determine To assess the internal validity of single archetypes, it is good the appropriate boundaries of the building blocks, which in turn practice to examine their explanatory capacity in accordance with will delimit the archetypes’ domains of validity. the chosen methods. In QCA, for example, consistency scores provide information about the proportion of cases in which a Think of the following hypothetical example. Assume an configuration is associated with a given outcome. A common archetype analysis of 100 cases and an even larger set of attributes. recommendation is to revise “contradictory” cases that diverge Suppose there is considerable case heterogeneity so that the cases from expected outcomes. This usually results in the addition of can be grouped into 30 classes, each with 3 or 4 cases that share attributes or configurations (Ragin 2008). Additionally, it is all attributes. If each class was considered as an archetype, this essential to explain why and how the attributes are interrelated as would be tractable, but with difficulty; it would clearly be an a configuration. Internal validity can be provided through case- advantage if we could capture the same heterogeneity with fewer based qualitative methods (e.g., Neudert et al. 2019), for instance archetypes. This is possible, in principle, if we do not require all by process tracing (Rihoux 2006, Elo and Kyngäs 2008, Collier cases within an archetype’s domain of validity to share all 2011). In cluster analyses, domains of validity can be established attributes. When classifying cases based on partial attribute based on numerical grid-cell data (Václavík et al. 2013, 2016, agreement, a smaller number of classes (albeit overlapping) is Levers et al. 2018). obtained. If we consider these partially shared configurations of attributes as archetypes, just 5 of them might be sufficient to cover To assess the internal validity of a whole suite, the validity of the all 100 cases. Those 5 archetypes can combine like building blocks classification of the components of cases needs to be in 31 different ways, so that almost every combination may demonstrated in conformity with methodological standards, e.g., represent one of the original case classes. This economizing aspect distance measures to assess whether a case belongs to a cluster of the building-blocks principle becomes increasingly important (Kaufman and Rousseeuw 1990), or the closure criterion in formal for larger sets of cases. Based on experience, it is probably good concept analysis (Ganter et al. 2005; Wang et al. 2019), or practice to aim for 4 to 30 archetypes in an analysis, with at least deductively, or by standards of qualitative methods. In 1 case in which more than 1 archetype holds. If there are very metastudies, the common vocabulary of attributes should be many archetypes, or if they never combine, they are probably too subject to intercoder reliability checks, and the obtained specific and there may be potential for greater generalization. If archetypes can be revalidated using primary studies (Oberlack there are fewer than four archetypes, data might be sufficiently and Eisenack 2018, Kimmich and Villamayor-Tomás 2018). In homogeneous to employ conventional analytical approaches. frequency-based meta-analyses, justified thresholds for the minimum number of cases in which an archetype should hold are In operational terms, there are different ways to identify the recommended to be proportional to the size of the case sample appropriate number of archetypes for a particular study (see also (e.g., two cases in Oberlack and Eisenack 2018; A. Gotgelf, M. Sietz et al. 2019). A quantitative approach is to identify recurrent Roggero, and K. Eisenack, unpublished manuscript). Typically, a configurations of attributes in the data by cluster analysis (e.g., higher threshold will identify fewer and less detailed archetypes Sietz et al. 2011, 2017, Kok et al. 2016) or self-organizing maps in any given population. (Václavík et al. 2013, Levers et al. 2018). The number of clusters, each representing a class of cases, can be chosen using stability- To determine the external validity of a single archetype, precise based procedures (Sietz et al. 2011, Janssen et al. 2012). Although information about its domain of validity is important (Magliocca crisp classification categorizes each case by exactly one archetype, et al. 2018), for example through an analysis of critical cases (Yin other techniques like fuzzy clustering reveal the degree of 2009), or field experiments (U. Kasymov, X. Wang, D. Zikos, et membership of a case in one or several clusters without sharp al., unpublished manuscript). If data allow, statistical models and boundaries (Ramachandra and Srinivas 2006, Cullum et al. 2017), correlation analyses can test the validity of archetypes against so that clusters can be understood as building blocks. different scope conditions (Brambor et al. 2006, Ragin 2008). Further suitable qualitative or quantitative methods to classify External validity of a whole suite can be assessed by studying new recurrent components within cases include grounded theory cases and checking whether they are already covered by the suite (Corbin and Strauss 2008, Moser et al. 2019), QCA (e.g., of archetypes. It can also be assessed by adding more attributes Srinivasan et al. 2012, Crona et al. 2015, Roggero 2015), formal to see if this does not require an extension of the suite. For concept analysis (e.g., Oberlack and Eisenack 2017; Wang et al. example, vulnerability archetypes among farming households 2019), sensitivity analysis (e.g., Messerli et al. 2015), interpretive identified through cluster analysis were validated by Sietz et al. analysis of model-centered meta-analysis (e.g., Oberlack 2017), (2012) by comparing them to separate vulnerability outcome data. participatory systems mapping (e.g., Kopainsky et al. 2017), or In some situations, researchers might be able to split the sample analytical narratives (Bates et al. 1998, Kimmich 2016). using one subsample to perform the analysis and the other to test Sometimes, multiple methods can be productively combined (e. the resulting suite of archetypes. Ecology and Society 24(3): 6 https://www.ecologyandsociety.org/vol24/iss3/art6/ g., S. Villamayor-Tomás, I. Iniesta-Arandia, and M. Roggero, multitiered coding systems is common in grounded theory unpublished manuscript). Archetypes then classify similar (Corbin and Strauss 2008). For example, the archetype analysis outcomes (e.g., Crona et al. 2015), similar processes (e.g., by Oberlack and Eisenack (2017) considered six attributes in the Oberlack et al. 2016), or similar configurations of causal effects most abstract tier, each refined by about five attributes in the next (e.g., Manuel-Navarrete et al. 2007, Messerli et al. 2015). Because tier, e.g., social connectivity, which is further refined by two multiple components can occur in single cases, multiple attributes in an even more concrete tier, limited vertical and archetypes can be combined. limited horizontal coordination. Oberlack and Eisenack (2014) used a three-tier system in a similar way. For navigating levels of Depending on the research question, different deductive abstraction, QCA or formal concept analysis could be applied to typologies for configurations of attributes can be used (e.g., attributes at different levels of abstraction, and the quality of the Fischer et al. 2017). If the analysis employs multiple typologies, solution formulas can be compared among them. Similarly, each provides separate archetypes that can combine in different cluster analysis or grounded theory could be used to navigate combinations to characterize single cases. For cities, one might variables at different levels of abstraction. Typically, an archetype consider the archetype of global cities (Sassen 1991), cities as analysis with more abstract attributes will produce a smaller suite. growth machines (Logan and Molotch 1987), and shrinking cities (e.g., Couch et al. 2005). There are cities in the domain of validity From our experience, we suggest organizing attributes in two to of two of those archetypes. It might be possible that some theories four levels of abstraction (tiers). At least two levels are needed to provide more than one archetype, e.g., cultural theory (Douglas test different abstraction levels, but too many levels might prove and Wildavsky 1983, Thompson et al. 1990, Ripberger et al. 2014; intractable and difficult to communicate and explain (see Achen S. Pedde, K. Kok, K. Hölscher, et al., unpublished manuscript). 2002). The number of attributes on each level needs to be tractable Grid/group theory may explain how certain cities approach risks and will depend on the research question. There might be three related to air pollution in different ways. These archetypes can to six attributes on the most abstract level. With only two then be combined with other typologies in one suite. attributes, conventional approaches might be more appropriate. If there are too many attributes on the most abstract level, the An archetype analysis should explicitly navigate through different analysis is more likely to run into an ideographic trap. On the levels of abstraction (3) most concrete level, however, it might not be a problem if the Choosing the appropriate attributes involves analytical decisions number of attributes is larger than the number of cases because about the level of abstraction on which cases and attributes are of the hierarchical organization. During the archetype analysis, selected. In an archetype analysis of cities, for instance, we might a fit between configurations of attributes, empirical evidence, and navigate between cases being households, quarters, administrative theories can be sought for at each level to find out which level boundaries, or metropolitan areas. We might navigate from more balances generalization and ideographic concreteness to provide abstract attributes like proneness to corruption in general, over the most useful number of insightful archetypes with respect to vested interests in certain sectors, down to the influence of specific the research question, available data, and the kind of institutional organizations. We might navigate from average annual arrangements or level of decision making that the analysis aims precipitation down to seasonal or monthly precipitation. to inform. It is important however to avoid mixing attributes with Although this tension is implicit in many scientific approaches, different levels of abstraction in one archetype. archetype analysis requires to purposefully deal with the entailed trade-offs to obtain nonuniversal but recurrent patterns. As far Each archetype in a suite should obtain a fit between its as possible, the resolution at which attributes are described should configuration of attributes, theory, and empirical evidence (4) be commensurate with the variation that is actually observable. An archetype analysis that is designed to satisfy the above criteria If the attributes of interest are few and coarsely described, data in a coherent way has the greatest prospects of generating new, may be more accessible, but with more risk of overgeneralization. theoretically rigorous, and practically useful knowledge. This Conversely, specifying (many) attributes at fine resolution may fourth quality criterion brings them all together. First, an produce more precise analyses capable of identifying specific archetype analysis requires that the three elements characterizing causal mechanisms in a few cases, but makes it difficult to compare each archetype (configuration of attributes, corresponding cases. theory, domain of validity) are made explicit. Second, care is needed to ensure that the three elements are coherent with each Because the appropriate level of abstraction typically will not be other. If, for example, recurrent configurations are determined clear at the outset, it can be helpful to purposefully shift between but the theories do not explain them, this indicates an absence of more concrete and more abstract levels to decide on an fit. This criterion can be viewed from two perspectives. The first appropriate level. This can be done using diagnostic approaches is how to check whether a concluded analysis has achieved it, and such as Ostrom’s social-ecological-systems framework (Ostrom the second is how to obtain it. 1990, 2009, Ostrom et al. 2007, Epstein et al. 2015). This framework aims to provide scholars with a common vocabulary A number of procedures can be applied to check for a requisite of attributes for describing, understanding, and predicting fit between the three elements. One can pick any pair out of those environmental and social outcomes in diverse social and three and check whether it is made explicit and whether it is ecological contexts. Attributes are organized hierarchically; coherent. If the three possible pairs are successfully checked for whereby more concrete tiers provide greater specificity and all archetypes, a fit is obtained. For example, in a primarily refinement to attributes on more abstract tiers. An attribute at a deductive study, Cox et al. (2010) used selected cases to study the more abstract tier can be considered to hold if at least one of the validity of Ostrom’s (1990) design principles for governing local refinements of this attribute holds. A similar approach to commons. If considered as an archetype analysis, the cases of Ecology and Society 24(3): 6 https://www.ecologyandsociety.org/vol24/iss3/art6/ community-based natural resource management comprise the way. This is even more challenging for transdisciplinary domains of validity. However, the configurations of attributes research designs. that explain each principle are not explicitly stated, so it is difficult 2. The above quality criteria do not address how archetype to assess their fit to the underlying theories. Eisenack (2012) analysis can become policy relevant. For action-oriented characterized archetypes of adaptation based on anecdotal analyses, application validity (Bossel 1994) is essential. A evidence and theory-driven arguments (e.g., principal agent specific promise of archetype analysis is the ability to relations). Because attributes and domains of validity are unclear, transfer best practices between cases with shared archetypes. a fit between those cannot be checked. Further examples use Although some attempts have been made in this respect cluster analysis to obtain a precisely determined fit between (UNEP 2007), proven strategies to achieve this (including configurations and domains of validity in studies of land-use assessments by field experts or decision makers) are still change (Václavík et al. 2013, 2016, Levers et al. 2018). However, pending. they have not formulated a robust theoretical explanation of the corresponding archetypes. By contrast, metastudies by Oberlack 3. Although validity is important for any method, establishing et al. (2016) and Oberlack and Eisenack (2017) started from case- causality with archetype analysis is a further issue (see also based validity in the primary studies. Recurrent configurations of Oberlack et al. 2019). This is not straightforward if scholars attributes are identified, domains of validity in the case sample with different epistemic positions on causality collaborate. are reproducibly characterized by the configurations, and Establishing causality also depends on the kind of data theoretical entry points to explain groups of similar available and on the specific methods applied under the configurations are given. The SESMAD project (Cox 2014) umbrella of an archetype analysis (see Sietz et al. 2019). studied large-scale social-ecological systems using a coherent 4. Cases are typically defined as units of analysis for archetypes vocabulary of attributes that allows expression of domains of analysis. However, in sustainability studies, cases are validity, configurations, and theories. It can then be checked frequently interdependent, linked, or telecoupled to other whether the theories explain the configurations, whether the cases through biophysical interdependence, externalities, configurations correctly map the domains, and whether the cases markets, or by being part of multi-layered or polycentric in the domains support the respective theory. governance systems. Vocabularies currently in use may need A fit can be obtained if analysis follows iterative steps that to be expanded in order to specify attributes of spatial specifically concentrate on configurations, theories, or domains relations and functional linkages. of validity, possibly with a mix of qualitative and quantitative Finally, archetype analysis is currently mostly static in character, methods. Although this can present an immense analytical neglecting patterns of change over time or, at best, considering challenge and has not been achieved by most archetype analyses dynamics in a simplified way (Reckien et al. 2011, Lüdeke et al. thus far, we believe that it is indispensable to advance the 2014, Levers et al. 2018). However, many problems of and approach. The sequence of iterative steps should be planned pathways to sustainable development emerge and evolve over time ahead and will depend on the aims of the research, for example (e.g., Eisenack 2016). Although existing theories of change might whether it is oriented toward inductively building or deductively help in a particular dynamic archetype analysis (e.g., panarchy, testing theories, whether it is more positive or more action Gunderson and Holling 2002; path dependence, David 1985, oriented, and so on. Nonetheless, we argue that the following steps Arthur 1989; systems archetypes, Wolstenholme 2003), it would need to appear somewhere in the sequence: constructing the additionally require a common vocabulary of change to represent common vocabulary; collecting data and studying cases; different time scales or to link static archetype analyses over time. classifying components of cases; identifying recurrent Quality criteria and guidelines for such analyses are still needed. configurations and characterizing their domains of validity; developing theories to explain configurations; finding the Despite these current limitations, existing research on archetypes appropriate level of abstraction; and developing a useful naming has already laid an important foundation for a better convention for each obtained archetype. understanding of environmental degradation and vulnerability, as well as options for a more sustainable future. The approach DISCUSSION contributes to an emerging recognition of the need to The proposed quality criteria address gaps acknowledged in contextualize global change processes while simultaneously previous archetype analyses and, at the same time, provide more generalizing local change within broader trends. precision to the specific character of the approach. On the other hand, we need to acknowledge that not every archetype CONCLUSIONS publication will be able to meet the highest standards given the This paper is part of wider efforts toward the definition of shared usual constraints to research. Moreover, the survey and the principles for research quality in inter- and transdisciplinary workshops identified further challenges that need to be addressed sustainability studies (e.g., Defila and Di Giulio 2015, Magliocca (see also Oberlack et al. 2019). These include the following: et al. 2018). Specifically, it contributes to a common understanding of archetype analysis, its scope and current 1. Although archetype analysis is designed to provide a challenges, and to the improvement of research designs. Drawing methodological grounding for interdisciplinary research, on experience from different research fields and epistemic challenges remain in integrating methods from different communities, it is to our knowledge the first attempt to formulate epistemic communities. We therefore need to develop best generally applicable quality criteria for archetype analysis. By practices on how to let qualitative and quantitative methods identifying strategies to achieve them, our aim is to help scholars resonate in a single archetype analysis in the most productive judge whether archetype analysis is appropriate for their research questions and provide guidance for planning their research. Ecology and Society 24(3): 6 https://www.ecologyandsociety.org/vol24/iss3/art6/ Based on a survey and two workshops with scholars experienced resilience, and sustainability. Ecology and Society 18(2):8. https:// in archetype analysis, we identified several challenges in which doi.org/10.5751/ES-05178-180208 the following were prioritized: (1) how to establish the validity of Arthur, W. B. 1989. Competing technologies increasing returns a suite of archetypes; (2) how to delineate the boundary of and lock-in by historical events. Economic Journal 99:116-131. archetypes; and (3) how to find the appropriate attributes. We https://doi.org/10.2307/2234208 argue that these challenges can be addressed through the adoption of four quality criteria: (1) each archetype in a suite of archetypes Basurto, X., and E. Ostrom. 2009. Beyond the tragedy of the should precisely specify and justify its domain of validity; (2) commons. Economia delle fonti di energia e dell’ambiente 52 archetypes should be constructed so that they can be consistently (1):35-60. [online] URL: https://papers.ssrn.com/sol3/papers. combined in different ways to characterize single cases; (3) the cfm?abstract_id=1304688 common vocabulary of attributes should be multitiered to Bates, R. H., A. Greif, M. Levi, J.-L. Rosenthal, and B. Weingast. explicitly navigate different levels of abstraction; and (4) a fit 1998. Analytic narratives. Princeton University Press, Princeton, should be obtained between attribute configurations, domains of New Jersey, USA. validity, and theories. We propose several strategies for achieving these quality criteria to guide the design of future archetype Belcher, B. M., K. E. Rasmussen, M. R. Kemshaw, and D. A. analyses. Zornes. 2016. Defining and assessing research quality in a transdisciplinary context. Research Evaluation 25(1):1-17. https:// Because archetype analysis is a recent innovation, future research doi.org/10.1093/reseval/rvv025 will undoubtedly provide input for further development and improvement of the quality criteria we have outlined. We hope Bennett, A. 2005. Case studies and policy relevant theory. Pages our recommendations serve as a starting point for such an 263-284 in A. L. George, and A. Bennett, editors. Case studies and endeavor. We believe that adoption of the proposed criteria will theory development. MIT Press, Cambridge, New Jersey, USA. further increase the potential of archetype analysis to contribute Bennett, A., and C. Elman. 2006. Qualitative research: recent toward the development of the integrated and yet nuanced developments in case study methods. Annual Review of Political perspectives that are urgently needed to address sustainability Science 9:455-476. https://doi.org/10.1146/annurev. problems in a heterogeneous world. polisci.8.082103.104918 Bergmann, M., B. Brohmann, E. Hoffmann, M. C. Loibl, R. Responses to this article can be read online at: Rehaag, E. Schramm, and J. P. Voß. 2005. Quality criteria of http://www.ecologyandsociety.org/issues/responses. transdisciplinary research: a guide for the formative evaluation of php/10855 research projects. Institute for Social-Ecological Research, Frankfurt, Germany. [online] URL: https://www.katalyse.de/wp- content/uploads/2013/08/2005_evalunet_guide.pdf" Acknowledgments: Bossel, H. 1994. Modeling and simulation. Vieweg and Teubner Verlag, Wiesbaden, Germany. This work has received financial support from the Swiss National Science Foundation (grant no. IZ32Z0_173396), the Institute of Brambor, T., W. R. Clark, and M. Golder. 2006. 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