Participatory environmental governance has received much attention from scientists and decision makers because of its potential to improve decision making. Participatory environmental governance refers to the processes and structures that, alongside policy makers, involve actors from civil society, administration, and business in deciding and managing (Newig et al. 2018) environment-related issues such as water management, energy infrastructure, and nature conservation. Social learning is a major area of interest within the field of participatory environmental governance (Reed et al. 2010, Siebenhüner et al. 2016). Social learning is understood here as an analytical concept that can be used to investigate normative, substantive, and instrumental participatory mechanisms (Fiorino 1990), and thus, provides a valuable research object. It helps to explore “knowledge claims between the parties in a process, while also exploring different values and ways of seeing the world” (Burgess and Clark 2009:183). Social learning is a collective communication process (Muro and Jeffrey 2008) of acquiring knowledge, making sense and abstracting meaning, and disseminating knowledge (Heikkila and Gerlak 2013). The process takes place in a social setting and leads to relational, cognitive, and technical change (Muro and Jeffrey 2012). Such a social setting is participatory environmental governance, and thus, social learning is understood here as an outcome of participation processes. Further outcomes (the final result or effect) of participation processes can be environmental (e.g., improved habitat or water quality) or socioeconomic (e.g., changes of institutions; Conley and Moote 2003). It is assumed that social learning through participatory environmental governance could induce the necessary social change process toward sustainable development.
Despite increasing research on participation in environmental governance, there is still a lack of understanding about how and under what conditions participation leads to improved outcomes (Heikkila and Gerlak 2013, Newig et al. 2018). In their recent systematic metareview, Gerlak et al. (2018) concluded that the participatory contexts in which social learning takes place have been insufficiently studied. This conclusion corroborates previous research that found that, “despite high expectations, social learning processes in sustainability appraisals are poorly conceptualized and empirically understudied” (Garmendia and Stagl 2010:1712). Research has been conducted on participatory environmental governance, but the findings are still largely inconclusive (von Korff et al. 2012). There is not only a lack of empirical evidence analyzing whether participation promotes social learning, but also a scarcity of profound analytical concepts guiding such empirical analyses.
Here, I perform a narrative review to extend the findings of the systematic reviews of Siebenhüner et al. (2016) and Gerlak et al. (2018), analyzing the issue of social learning by applying meta-analyses. This qualitative review of 72 publications supports empirical findings from a range of different research efforts and aims to identify a comprehensive set of factors that explain social learning within the scope of participatory environmental governance. A clear definition and analysis of factors influencing social learning offers a reference point for future empirical research. The findings can be used in the evaluation of participation processes, which, in addition to precise and unbiased elaboration, requires a clear definition of the indicators measured. Furthermore, the results point to research gaps and provide a better understanding of the interdependence of the participatory setting (cause) and the social learning outcome (effect). Therefore, this study makes an original contribution to the scientific debate on how participatory governance can improve environmental outcomes and promote sustainable development.
I have structured the paper as follows. First, I explain the selection of studies reviewed. In the narrative review of literature, I define each factor identified and then discuss existing empirical findings assessing social learning within the scope of participatory environmental governance. I then discuss the findings in a wider sense and present the interdependencies identified between causes and effects. Finally, I end with conclusions about the current state of research and point to research gaps.
In the narrative literature review, I examine existing empirical findings and identify important factors that influence social learning within the context of participatory environmental governance. In contrast to systematic metareviews, which usually provide quantitative syntheses of existing research findings (Roberts et al. 2006), narrative reviews are rather unsystematic, comprehensive, and descriptive syntheses of already published scientific results (Green et al. 2006). They represent a valuable method of linking studies from different topics for the purpose of establishing interconnections and interpreting the results of single case studies in a broader sense (Baumeister and Leary 1997). This process is important for analyzing the interconnection of participation and social learning.
I defined some criteria for excluding or including literature before the literature search was undertaken. To develop a theory that includes possible factors influencing social learning, I reviewed findings from studies that used multiple research methods. Waylen et al. (2015) emphasize that there is a lack of research on “imperfect participation processes” and that the implications of various aspects of these processes, such as different expectations of politicians and participants, are therefore insufficiently understood. In addition, a diverse range of cultural and political systems must be considered in the case of participatory environmental governance. My review includes various research designs and studies from different countries or regions. Because of the large, and steadily increasing, number of findings in participation research (von Korff et al. 2012), I only focused on studies in the field of environmental governance. Environmental governance is understood to be the setting of rules, decision-making procedures, and activities that serve to define social practices and guide the interactions of actors in practices (Young 1997) that have serious environmental impacts or center around environmental issues (Coenen 2009). The concentrated focus of my study is not only necessary for minimizing the amount of literature but also for comparing specific factors, meaning that similar contextual conditions are necessary. Furthermore, I chose only empirical studies assessing social learning in participatory environmental governance because I compared theoretical assumptions with existing empirical evidence. However, most empirical studies assessing social learning are explorative or do not define precisely factors that influence social learning. This reason is why I chose literature from participation research such as reviews, theoretical research, or empirical papers with strong theoretical foundation to define each factor. To ensure the quality and currentness of data in the literature reviewed, I only considered literature published in scientific journals, as a book, or as book chapters between 1990 and 2018. Definitions of participation and social learning, which further guided the selection of literature, are provided in the following three paragraphs.
As with many frequently used terms, there is no common understanding or definition of the term participation. The terms public participation, political participation, citizen participation, collaboration, and citizen involvement or engagement are often applied synonymously (Schroeter et al. 2016), and are summarized here using the term participation. I provide a definition and understanding of the term participation, but without a wholesale depiction of the scientific debate. The normative understanding of participation derives from deliberative theory, which focuses on the considered weighing of options through applied logic and reason (Renn 2006). This understanding includes the actors involved in gaining influence over the output and outcome of the decision-making process (Rowe and Frewer 2000). In contrast to traditional, sovereign, decision-making approaches, participation aims at involving both experts and professional politicians as well as lay people and organizations that are not legally responsible for making socially relevant decisions (Renn 2005). Participation is discussed as having numerous consequences such as “promoting the development of individual capacities, building community, and legitimating the regime” (Verba et al. 1995:12). Here, I use the term “participation” in its broadest sense to consider as many aspects of participation as possible, deriving, as much as possible, a holistic list of factors that influence social learning. Therefore, participation is defined here as a process involving citizens, experts, state or governmental actors, and other stakeholders that influence decision making at any stage of environmental governance. This definition does not include simple voting procedures for electing officials or for referenda (Beierle and Cayford 2002).
Siebenhüner et al.’s (2016) review of social learning shows that understandings and definitions of social learning vary greatly. It demonstrates that social learning is used as an analytical concept to examine social processes or is applied as a governance instrument. In addition, various goals and aims are associated with social learning, such as capacity building, knowledge integration, adaptive management (Westberg and Polk 2016), and change of governance systems (Armitage et al. 2008) or whole societies (Siebenhüner et al. 2016). Reed et al.’s (2010) review of social learning further underlines that social learning is defined in multiple, overlapping ways, and that some concepts lack a proper distinction between casual factors explaining social learning and elements and process dynamics of social learning. As Muro (2008) argues, there is no right or wrong definition of social learning, but the diverse range of learning concepts is more complementary than competitive. Therefore, research referring to theoretical concepts similar or closely related to social learning, such as transformative learning (Wilner et al. 2012); cognitive, normative, and relational learning (Baird et al. 2014); collaborative learning (Leach et al. 2014, Elbakidze et al. 2015); policy learning (Huitema et al. 2010); mutual learning (Wiek 2007); multidirectional learning (Roldán 2017); knowledge integration (Berman 2017); and coproduction of knowledge (Pohl et al. 2010, Edelenbos et al. 2011), are considered useful sources for investigating factors that influence social learning within participation processes. Such research complements the review.
Here, I discuss social learning as an analytical concept to investigate environmental governance and, more generally, transformation processes. Following Reed et al.’s (2010) definition, social learning consists not only of the elements of acquiring new information and experiences, and inducing change in the individuals involved, but must take place through social interactions; change should go beyond the individual to affect wider social units. Change is understood as the assimilation or accommodation (Muro 2008) of individual cognition, values, and perceptions, which is not to be mistaken with establishing proenvironmental positions and behavior (Caspersen et al. 2017). Such a change process can have multiple dimensions such as relational (e.g., improved sense of community), cognitive (e.g., change of perspectives), and technical (e.g., communication skills), and is dynamic (Muro and Jeffrey 2012). The learning phases such as acquiring knowledge, making sense and abstracting meaning, and disseminating knowledge (Heikkila and Gerlak 2013) do not necessarily emerge as a linear development. This definition makes a clear distinction between social learning and participation: social learning occurs through participation, and thus, it is assumed that the conditions of participation processes explain social learning.
I obtained literature through multiple search methods, including electronic searching of search engines, snowballing, and identification of studies through ResearchGate (https://www.researchgate.net/) and mailing lists. Electronic searches using the terms “social learning”, “learning”, “participation”, “collaboration”, and “consultation” were performed in the Web of Science, Google Scholar, and Scopus databases. In addition, continuous literature searches were conducted through a Google Scholar alert using the terms in the title “participation or consultation or collaborative”, and two Scopus search alerts using the keywords “social learning” and “participation or consultation or collaborative”. Most suitable literature, however, was detected by conducting a backward snowball approach to identify published empirical findings by searching the references of articles, which continued as the study proceeded. Based on the described selection criteria, 48 publications assessing social learning were identified, and 24 theory-driven publications in participation research were considered for the conceptual part and provide the foundation of the narrative literature review (Appendix 1).
Here, I review empirical studies assessing social learning within the framework of environmental governance, examining possible factors that influence social learning. Based on the assumption that social learning occurs through participation processes, I define and discuss factors describing participation processes. Similar to the literature evaluating participatory environmental governance (Carr et al. 2012), I distinguished three generic categories that cluster the identified factors and structure the literature review. The “participation process characteristics” category comprises factors describing process characteristics such as participation format or diversity of participants. “Normative process factors” describe desirable and often theory-driven factors. “Intermediate process outcomes” include factors that evolve during the course of participation and denote short-term effects of participation such as trust and conflict resolution. In each section for each factor, I begin by defining and conceptualizing each term, and then review the empirical literature.
A participation format is the method and organization structure that characterizes a participation process and describes the intensity of communication or dialogue. For example, public meetings and advisory committees provide different opportunities to participate (Beierle and Cayford 2002) and can be distinguished by the extent to which the public can share in collective decision making, structure of dialogue, and the time period of participation (Fiorino 1990). Coenen et al. (1998) claim that different participation formats generate different outcomes of participation processes. However, there is still debate about which are the best participation strategies.
The review of social learning literature provides inconclusive findings about the desired intensity of collective dialogue and communication. Berman (2017) focuses on the integration of local knowledge within participation processes and argues that participation formats that are dialogic, take place over time, and are unmediated represent the best ways of finding alternative solutions and promoting consensus, understanding, and the dissemination of knowledge. Muro and Jeffrey (2012) found that face-to-face and dialogic processes seem to promote social learning to a greater extent than do less intensive participation processes, but that less intensive participation also resulted in cognitive change.
Leach et al.’s (2014) findings suggest that “extended engagement”, which means that participants engaged multiple times in a process, promotes social learning. This kind of repeated contact might reduce conflicts because time is taken to understand the perspectives of others (Webler et al. 1995). This idea is why scholars argue for a sufficient process duration and early involvement (Tippett et al. 2005). Similar findings suggest that the number of meetings and activities complementary to plenary discussions, such as field trips, enhance social learning (Petts 2006, Mostert et al. 2007). Beers et al. (2016) further indicate that different forms of interaction offer different potential for generating learning outcomes. In particular, participation resulted in learning when participants were able to question each other’s positions and estimate the validity of proposed actions. Furthermore, the venue where the interaction takes place might also influence learning processes. Webler et al. (1995) indicate that a familiar atmosphere such as a pub or restaurant relaxed participants, thereby promoting a sense of collegiality.
In contrast, Cundill’s (2010) findings suggest that identical participation formats might yield different learning outcomes. Her study indicates that factors such as participation format, process organization, and knowledge integration do not influence social learning directly but rather via normative process factors or intermediate process outcomes such as procedural fairness and trust.
Access to information relates to access to external scientific and technical resources (Beierle 2002, Carr et al. 2012) and to relevant knowledge that refers to the decision (Schroeter et al. 2016). Beierle (2002) demonstrated that insufficient access to information can prevent effective participation in decision making.
Van de Kerkhof and Wieczorek (2005) suggest that the information provided in the process should be of scientific quality but communicated in a way that is comprehensible and accessible, which also makes uncertainties and controversies explicit to increase participants’ competence to deliberate and make argued choices. Information ought to be communicated understandably for the participants, and access to further information must be guaranteed, for example, the collection, organization, and provision of information from the Internet (Mostert et al. 2007). Access to information should be ensured, providing sufficient opportunities and freedom to shape the learning process and a certain degree of ownership (van de Kerkhof and Wieczorek 2005).
Facilitation refers to the mediation and structuring of discussions as well as the balancing of contributions and the creation of opportunities for equal participation (Palm and Thoresson 2014, Ernst et al. 2017). To manage the dominance of a few participants and power imbalances, which might limit equal participation opportunities and create biased outcomes, skilled facilitation is seen as an important driver of successful participation by Leach and Pelkey (2001) and Reed (2008).
Skilled facilitation is seen as a key factor fostering social learning by Tippett et al. (2005), van de Kerkhof and Wieczorek (2005), and Petts (2006). Some studies indicate that facilitation of the participation processes is critical for sustaining the relationships that lead to increased trust and legitimacy (Edelenbos et al. 2011, Podestá et al. 2013). Pohl et al. (2010) consider a trustworthy relationship as essential for identifying and acknowledging both limitations and potentials of each knowledge type and perspective. However, Wiek (2007) notes that confounded agendas, different perceptions of appropriate data acquisition, reluctance to face exposure, and coexisting values can hamper the process and might make some knowledge types or perspectives perceived as more relevant or legitimate than others. Therefore, Wiek (2007:57) argues that appropriate facilitation should mediate, structure discussion, and balance contributions in a way to “cope with a great number of social aspects such as communication technology and virtuality, team size and structure (power, roles, possibility of participation), which could greatly influence the knowledge-generation performance of the collaborating agents.” Furthermore, it is suggested that facilitation must be independent (van de Kerkhof and Wieczorek 2005) because defending one’s own interests prevents neutral facilitation (Mostert et al. 2007). Facilitation aiming to enable participation, and thus, social learning, ought to overcome participation barriers. Therefore, facilitators should choose a venue that is in close proximity to the target group and provide financial and other support to stakeholders requiring assistance (Mostert et al. 2007).
The diversity of participants, meaning the representation of interests, values, and knowledge, influences the outcomes of participation processes. Although the participants should represent a sample of the population of affected public, a relative distribution of views and interests should be pursued (Rowe and Frewer 2000). Furthermore, Koontz and Johnson (2004) found that the number and balance of stakeholder types participating influence the content of discourse and the outcome.
Multiple actors must be included in the participation process because social learning aims to integrate different knowledge types (Brown et al. 2005). According to Knoepfel and Kissling-Näf (1998), the social learning process is influenced by the number and type of participants. However, van der Wal et al. (2014) argue that an increase in participants does not necessarily improve learning conditions, but rather that a balanced stakeholder selection is key. Mostert et al. (2007) showed that a lack of participant selection might lead to the absence of important stakeholders and thus reduce the legitimacy of the participation process and opportunities for social learning. The selection of participants should not only be guided by the identification of all relevant perspectives and interests, but should also consider issues of power and create a balance of power, which is viewed as a prerequisite for social learning (Mostert et al. 2007). van de Kerkhof and Wieczorek (2005) conclude that participants should be selected by an independent facilitator. They argue that a balance between homogeneity and heterogeneity needs to be achieved: heterogeneity to ensure alternative viewpoints and ideas, and homogeneity to provide a common ground for discussion and action. However, van de Kerkhof and Wieczorek (2005) acknowledge that this may be hindered by people’s lack of motivation to participate in the first place.
Some studies indicate that the participants’ characteristics influence participation processes. Participants’ characteristics are manifold and, next to gender and age, behavioral patterns such as civic attitude or the political engagement of participants (Parés et al. 2015) are summarized in this term. Furthermore, the creativity, willingness to cooperate, commitment (Leach and Pelkey 2001), and competence (skills, abilities, knowledge; Webler 1995, Beierle and Cayford 2002) of individuals are important participant characteristics shaping participation processes.
In contrast to van der Wal et al. (2014), Leach et al. (2014) consider the characteristics of the individual participating as important features that influence the learning outcome. Tippett et al. (2005) highlight that the different mental models and framings of the process by participants, based on the reasons for participating, expertise and knowledge, previous experiences, interests, and perception of the problem, need to be recognized to encourage change. It is essential that the participants involved are open to questioning their own underlying assumptions, values, habits, and actions. Squires and Renn (2011) found that social learning is influenced by participants’ individual degree of knowledge of the respective topic. In addition, Egunyu and Reed (2015) suggest that learning activities and outcomes differ for men and women because norms and traditions about the place of women and men in society hinder engagement in certain topics and participation in general. This situation leads to fewer learning opportunities and possibilities for getting to know unfamiliar topics. Furthermore, established social norms as well as different levels of education and literacy might limit opportunities for learning and influence.
A clear definition of what “context” entails is difficult because the characteristics defining context are almost endless (O’Toole and Meier 2015). Context consists of the features of the type of issue, pre-existing relationships, and the institutional setting (Beierle and Cayford 2002). Furthermore, pre-existing social and cultural contexts are important features influencing participation (Peterson et al. 2010) and describing the given situation.
A comparative case study conducted by Cundill (2010) found that variation in social learning might be explained by preexisting institutions. Hierarchical institutional structures and cultural frameworks may provide insufficient support for participation and, therefore, social learning (Tippett et al. 2005, Benson et al. 2016). Giebels et al.’s (2016) findings indicate that governance approaches to knowledge generation need to match the context. They found that factors such as knowledge capacity and conflict are important contextual factors influencing learning processes. Their approach builds on the findings of Jennings and Hall (2012), which indicate that the perceived availability, relevance, and credibility of (scientific) knowledge has an effect on the acting agency’s readiness to engage in dialogue. However, crises such as environmental disasters (floods, etc.) might also increase general awareness and overcome institutional barriers. They create pressure to act and they lead to increased citizen demand to become part of the decision and planning process (Mostert et al. 2007), which might trigger social learning (Siebenhüner et al. 2016).
The factor of fairness (also justice) can be understood in multiple ways within the context of participation processes and is often not clearly defined in the reviewed literature. However, the reviewed literature most frequently addresses aspects of procedural fairness when considering fairness or justice. Issues regarding distributive fairness are discussed within the terms “effectiveness”, “efficiency”, and “satisfaction”. Following Webler (1995:47), an ideal participation process should realize popular sovereignty and political equality so that participants “must presume each other to have equal chances to effect the formulation of the argument.” Procedural fairness indicates whether people’s ability to attend, initiate, and participate in discourse as well as contribute to decision making (Webler and Tuler 2000) comply with normative assumptions and expectations about fairness. Furthermore, Schroeter et al. (2016) stress that procedural fairness is a “subjective impression” of the process.
Webler et al. (1995) and Leach et al. (2014) found that a participatory process characterized by equal participation in which participants feel that they are heard and treated fairly enhances social learning. Controversies exist on whether to establish an open dialogue that can be attended by everyone, or to limit groups of participants (van de Kerkhof and Wieczorek 2005). Furthermore, Leach and Sabatier (2005) provide evidence that fair processes are not only highly associated with social learning but also with trust among stakeholders. Van de Kerkhof and Wieczorek (2005) see the facilitator as being responsible for ensuring a fair process. However, very few empirical studies analyze issues of procedural fairness.
In contrast with procedural fairness, which refers to the process, the factors effectiveness, efficiency, and satisfaction relate to the (perceived) output and outcome of participation. The effectiveness of participation processes measures the impact of a participation process (Schroeter et al. 2016). Efficiency judges the outcome of the process in relation to the resources used (Ernst et al. 2017) and is closely related to what Carr et al. (2012) refer to as cost-effectiveness. However, some studies emphasize that the participants’ perception of their own effect on the participation process should be measured instead of effectiveness. Respondents may subconsciously overestimate the effectiveness of the participation process they were involved in “to avoid the emotional discomfort” (Leach et al. 2002:665). Furthermore, satisfaction with the process does not equate to being totally content with the results (Parés et al. 2015, Schroeter et al. 2016). Satisfaction relates to one’s own participation and whether it was satisfying. This concept differs from the perception of procedural fairness, which refers to whether the participation opportunities were fair for everyone.
Koontz’s (2014) findings from a comparative case study in Germany and USA provide evidence that greater social learning is positively associated with participants’ greater process control and perceived individual efficacy. It is suggested that the capacity of individuals, or faith in one’s own ability to engage (meaningfully) in the process, can enhance learning outcomes (Webler et al. 1995, Kumler and Lemos 2008, Natarajan 2017). The appropriate facilitation and communication of information might help to overcome limited confidence in one’s own abilities to participate (Natarajan 2017). No literature was found that analyzes whether efficiency or effectiveness influence social learning.
Participation processes can increase the legitimacy of the final decision, according to Duram and Brown (1999). Legitimacy examines decision-making sovereignty and whether procedural weaknesses or breaches exists that lead to an invalid process or results. Legitimate processes are defined by Carr et al. (2012) as processes that include consensual decision making and shared power.
A transparent process that provides clarity about the procedure, deliverables, tasks, and responsibilities as well as the principles and rules is seen to establish legitimacy and increase learning opportunities (Tippett et al. 2005, van de Kerkhof and Wieczorek 2005). Mostert et al. (2007) found that clarity regarding the definition of roles as well as the means, timing, and purpose of participation are the most important factors influencing social learning. Schusler et al. (2003) stress the importance of following a “democratic structure”, which refers to participants’ ability to decide on an agenda and procedures. This structure could provide unplanned opportunities for collaboration and thus push the limits of predetermined agendas set by government authorities. Muro and Jeffrey’s (2012) and Schusler et al.’s (2003) research indicates that participants’ greater process control enhances social learning. The perception of the problem may differ from participant to participant, which calls for joint definition of the problem and consideration of all perspectives to create a learning atmosphere (Mostert et al. 2007, Kumler and Lemos 2008). Ultimately, a group agreement of this kind may indicate shared understanding (Koontz 2014).
Rowe and Frewer (2000:24) argue that for successful participation in decision making, it is necessary to “enhance trust in regulators and transparency in regulatory systems.” However, empirical studies investigating the issue of trust in participation indicate that the relationship between trust and successful participation is more complex (Beierle and Konisky 2000, Yandle et al. 2011).
Many scholars emphasize the importance of trust in learning processes. Leach et al. (2014) found that the level of social learning is correlated with trust among participants. This correlation can be explained by the enhancement of a smooth process and the exchange of knowledge due to a trustworthy environment. More precisely, scholars argue that trust helps participants to open up and share insights and information (Reed 2008) or to deal with uncertainties and elements of social learning such as change (Pahl-Wostl et al. 2007). Koontz (2014) argues that the process of trust building indicates a perception of other participants as being true to their word or commitments, meaning that people are also willing to expose weaknesses to others. De Vries et al.’s (2017) study indicates that trust between participants depends on interaction patterns that are characterized by listening and showing concern for each other’s position and perspective. They conclude that respect and appreciation are more important drivers of trust than are long dialogic processes. Webler et al. (1995) point out that trust in facilitators is especially important and, thus, a trust-building process must take place to establish such a relationship. This idea implies that a longer process is needed to build trust. In summary, trust seems to be both influenced by other factors and influences other factors (in addition to social learning) such as procedural fairness.
Network building refers to processes that either establish new or strengthen existing relationships between participants, creating benefits of gaining resources, insights, and cooperation on tasks (Koontz 2014).
Existing networks affect social learning because access to sources and integration of information and knowledge depend on the composition of the members involved (Gerlak and Heikkila 2011). Thus, network building can expand access to a wider variety of information and knowledge sources that influence social learning (Crona and Parker 2012). Network building is assumed to foster the integration of multiple interests and thus enhance social learning, but this requires further investigation (Benson et al. 2016).
Resolving or reducing conflict is often a seen as a goal of participation (Beierle and Cayford 2002). Following Cuppen’s (2018) definition, conflict is an attempt by people to articulate and advocate their concerns and interests that are perceived as being insufficiently represented and considered by decision makers. Conflict is a process closely tied to the participation process and can encourage participation, enable learning processes, and avoid unproductive outcomes (Cuppen 2018). Consensus is often understood as having overcome a conflict or indicates that participants have reached an agreeable decision, which does not necessarily result in a high-quality decision (Carr et al. 2012).
The degree of conflict or tension between parties within the process is assumed to affect social learning (Muro and Jeffrey 2012). Beers et al. (2016) highlight that disagreement is important for social learning because constructive conflict, rather than participants merely complementing each other’s information and ideas, would enhance shared mental models. These conflicts and tensions should not be avoided but mediated by skilled facilitation (Brown et al. 2005). In contrast, Knoepfel and Kissling-Näf (1998) argue that consensus on problem recognition, the need for action, and selection of instruments and processes during the implementation phase needs to form among participants to enable negotiation and ultimately to reach a valid decision. There is a lack of research providing a more in-depth look at the causes of conflict, such as different values, vested interests (Siebenhüner et al. 2016), and power relationships (Egunyu and Reed 2015, Gerlak et al. 2018).
Previous studies have found that social learning varies in its intensity (Muro and Jeffrey 2012) and that a participatory process can enhance knowledge of a specific environmental problem and about the interests and concerns of various stakeholders (Webler et al. 1995, Schusler et al. 2003, Muro and Jeffrey 2012). Knoepfel and Kissling-Näf (1998) reason that it is essential for collective learning processes that knowledge is developed on a cooperative basis and made accessible to various actors. They suggest that the dissemination of knowledge depends on individual cognitive change, the compatibility of information with existing beliefs, the quality of information, and political pressure for change. According to Brown et al. (2005) and Tippett et al. (2005), the participatory format should form spaces for reflection and open exchange, which are considered key elements for the successful integration of different knowledge types, norms, and values. Such a learning environment is supposedly characterized by the establishment of new perspectives for the actors involved, helping them to become aware of their knowledge and conduct from a distance (Westberg and Polk 2016).
However, the metareviews of Gerlak et al. (2018) and Siebenhüner et al. (2016) found that the causes of social learning are insufficiently studied. My narrative literature analyzed empirical findings to detect factors that influence social learning. In Table 1, I summarize these findings and show how the factors influencing social learning are interconnected.
My narrative literature review demonstrates how empirical findings suggest different desirable values for single factors. Furthermore, the desirable target values of factors might be conflicting. For instance, inclusive participation aiming to involve everyone might contradict in-depth, face-to-face dialogue, which is only possible with a limited number of participants. Thus, in practice, there is a need to balance different factors. The review not only showed that social learning processes within the scope of participatory environmental governance are multidimensional and dynamic (Muro and Jeffrey 2012), but that the factors influencing social learning are interconnected and interdependent. For instance, a trustworthy relationship between facilitator and participants is necessary to foster productive knowledge exchange. However, trust needs to evolve and may depend on other factors such as the duration of the participation process. Therefore, in line with several other scholars (Webler 1995, Beierle and Cayford 2002, Carr et al. 2012, Biddle and Koontz 2014), I conclude that to understand social learning processes fully, the interconnections between participation process characteristics, intermediate outcomes, normative process factors, and elements of social learning such as acquisition of information and cognitive change need to be investigated explicitly.
Fig. 1 further illustrates the interconnections and dependencies of factors influencing social learning. The factors categorized as intermediate outcomes and normative process factors represent a hybrid form of dependent and independent variables because they are influenced by participation process characteristics and also explain social learning. The directions of influence and interdependencies (Fig. 1) represent assumptions, to some extent. Whether these connections are causalities or correlations needs to be tested. My review shows that certain relations and effects have not been sufficiently analyzed, such as the influence of gender or age on social learning. These interconnections between causes and effects are addressed by the reviewed literature, but a systematic analysis is lacking. The concept is a product of existing research but with research gaps that need to be further investigated.
The literature evaluating participation processes is often concerned with normative goals such as effectiveness and efficiency. However, these goals were rarely considered in the literature on social learning. These differences might be explained by the different research foci of the two fields. Nevertheless, the comparison of the two research strands made it possible to identify additional potential factors such as effectiveness, efficiency, and satisfaction, which otherwise would have been overlooked. Findings from other research fields (Ringberg and Reihlen 2008, Glowacki and Molleman 2017) imply that the inclusion of individuals’ characteristics and preexisting attitudes could further improve assessments of social learning in participatory environmental governance.
The majority of literature reviewed comprised case studies from Western democratic countries (Appendix 1). Thus, the findings discussed here may not be applicable in other political and cultural contexts. Contextual factors such as existing institutions, rules, and social norms influence social learning, but these factors have not been analyzed fully. Factors such as access to information, legitimacy, and procedural fairness describe democratic decision-making procedures. It is assumed that participatory spaces that provide options of codecision and open negotiations do not exist in nondemocratic regimes. Therefore, it can be questioned how social learning can take place in autocratic regimes that deny access to information. Social learning is assumed to lead to social change, i.e., change in institutions, norms, and behaviors, which is not desired by autocratic regimes. These factors are closely connected to the question of which governance formats promote sustainable development (Adger and Jordan 2009, Atkinson et al. 2011).
The reviewed literature revealed some important research gaps. Although cognitive change is considered to be the main element of a social learning process, this aspect has hardly been studied. Most of the reviewed literature reported on acquiring new information. To account for the variety of factors influencing outcomes, an evaluation of participation should not only measure whether goals were achieved but investigate the specific factors determining each participation process (Koebele 2015). Most literature focused on the process and hardly discussed aspects taking place after the participation process had ended. However, Jami and Walsh (2016) argue that the outcomes only become apparent beyond the immediate end of the participation process, especially when it comes to learning processes that lead to community building and improved trust in decision making. This perspective calls for research designs that collect data after the participation process has ended. Further research in this field should test the deduced factors using a noncase-study design and investigate participation processes characterized by less intensive communication and dialogue to provide broader methodical and contextual variety to the body of empirical evidence. Each research technique and method measuring social learning has limitations, so the research design must be chosen based on the specific research interest and may also depend on the resources (money, time) available.
I report on the current and ongoing debate concerning how social learning is stimulated by participatory environmental governance. I applied a narrative review and offered an in-depth qualitative description of factors that influence social learning by comparing empirical results. The findings provide a conceptual and empirical understanding of how participatory environmental governance fosters social learning and contributes to a transformation toward sustainable development.
The literature review supports previous findings that research is focused on process-related factors such as facilitation and participation format and rarely on intermediate outcomes such as trust (Biddle and Koontz 2014). The most commonly applied methods are ex-post evaluations looking at case studies, case surveys, or empirical studies focusing on a specific region mainly in Western democracies. Many studies focus on water governance, which indicates a long tradition of participatory governance in water governance, especially in the USA (Sabatier et al. 2005). Participation within the context of energy-related issues appears to be an emerging research field. The concept of social learning has been an aspect of scientific investigation for some time. Although cognitive change is an essential element of social learning and is discussed as the main driver of social change processes, empirical evidence of cognitive change was detected less often than other elements of social learning such as acquisition of information. Furthermore, Muro and Jeffrey (2012) point out that acquiring knowledge does not necessarily lead to a change in perspective. This result indicates the need for more empirical assessments of social learning within the scope of participatory environmental governance.
Evaluation studies are not excluded from bias because the values and attitudes of the authors are reflected in the evaluation criteria (Conley and Moote 2003), which greatly influence the results (Carr et al. 2012). I first identified the factors influencing social learning by evaluating theory-based literature in the field of participation research, and then I discussed each factor with empirical findings from literature assessing social learning in participatory environmental governance. Reviewing papers from two strands of research and comparing theoretical assumptions with empirical evidence has not only helped to deduce factors that are less biased, but also to provide an in-depth understanding of the interconnections and interdependencies among the factors influencing social learning. However, the identified research gaps need to be addressed to understand social learning fully. Because of the amount of literature reviewed (72 publications) and the significant overlap of factors and issues cited in the literature, it can be assumed that this review provides a holistic assessment of the empirical evidence.
Although some participation research studies as well as studies assessing social learning have highlighted the importance of differentiating between causes (processes) and effects (outcomes), most studies did not clearly define independent and dependent variables. The findings suggest that there might not be a direct causal relationship between the design of participation processes and social learning, but perceptions of the process as fair or legitimate, and intermediate outcomes such as trust, have a strong influence on social learning. For instance, the intensity and duration of the participation process influences the intermediate outcome of trust, which in turn enhances social learning. The further and in-depth investigation of these interconnections might help in making informed choices about how to facilitate participation processes. Some process characteristics conflict in the sense that an inclusive process might not result in intensive face-to-face dialogue. Therefore, future investigation of how factors and their interactions affect outcomes can help to provide recommendations for facilitating participation processes in practice.
I am grateful to Doris Fuchs, Diana Schumann, Carolin Märker, and Wolfgang Fischer for their valuable feedback, which helped to sharpen the paper. The comments of two anonymous reviewers helped to improve the structure and logic of the arguments presented.
Adger, W. N., and A. Jordan, editors. 2009. Governing sustainability. Cambridge University Press, Cambridge, UK. http://dx.doi.org/10.1017/CBO9780511807756
Armitage, D., M. Marschke, and R. Plummer. 2008. Adaptive co-management and the paradox of learning. Global Environmental Change 18(1):86-98. http://dx.doi.org/10.1016/j.gloenvcha.2007.07.002
Atkinson, R., G. Terizakis, and K. Zimmermann, editors. 2011. Sustainability in European environmental policy: challenges of governance and knowledge. Routledge, London, UK. http://dx.doi.org/10.4324/9780203841716
Baird, J., R. Plummer, C. Haug, and D. Huitema. 2014. Learning effects of interactive decision-making processes for climate change adaptation. Global Environmental Change 27:51-63. http://dx.doi.org/10.1016/j.gloenvcha.2014.04.019
Baumeister, R. F., and M. R. Leary. 1997. Writing narrative literature reviews. Review of General Psychology 1(3):311-320. http://dx.doi.org/10.1037/1089-26126.96.36.1991
Beers, P. J., B. van Mierlo, and A.-C. Hoes. 2016. Toward an integrative perspective on social learning in system innovation initiatives. Ecology and Society 21(1):33. http://dx.doi.org/10.5751/ES-08148-210133
Beierle, T. C. 2002. The quality of stakeholder-based decisions. Risk Analysis 22(4):739-749. http://dx.doi.org/10.1111/0272-4332.00065
Beierle, T. C., and J. Cayford. 2002. Democracy in practice: public participation in environmental decisions. Resources for the Future, Washington, D.C., USA.
Beierle, T. C., and D. M. Konisky. 2000. Values, conflict, and trust in participatory environmental planning. Journal of Policy Analysis and Management 19(4):587-602. http://dx.doi.org/10.1002/1520-6688(200023)19:4<587::AID-PAM4>3.0.CO;2-Q
Benson, D., I. Lorenzoni, and H. Cook. 2016. Evaluating social learning in England flood risk management: An ‘individual-community interaction’ perspective. Environmental Science and Policy 55(2):326-334. http://dx.doi.org/10.1016/j.envsci.2015.05.013
Berman, T. 2017. Public participation as a tool for integrating local knowledge into spatial planning: planning, participation, and knowledge. Springer, Cham, Switzerland. http://dx.doi.org/10.1007/978-3-319-48063-3
Biddle, J. C., and T. M. Koontz. 2014. Goal specificity: a proxy measure for improvements in environmental outcomes in collaborative governance. Journal of Environmental Management 145:268-276. http://dx.doi.org/10.1016/j.jenvman.2014.06.029
Brown, V. A., M. Keen, and R. Dyball. 2005. Lessons from the past, learning for the future. Pages 247-264 in M. Keen, V. A. Brown, and R. Dyball, editors. Social learning in environmental management: towards a sustainable future. Earthscan, London, UK.
Burgess, J., and J. Clark. 2009. Practitioner evaluations of participatory processes in environmental decision making. Pages 159-190 in W. N. Adger and A. Jordan, editors. Governing sustainability. Cambridge University Press, Cambridge, UK. http://dx.doi.org/10.1017/CBO9780511807756.010
Carr, G., G. Blöschl, and D. P. Loucks. 2012. Evaluating participation in water resource management: a review. Water Resources Research 48(11):W11401. http://dx.doi.org/10.1029/2011WR011662
Caspersen, J., J.-C. Smeby, and P. O. Aamodt. 2017. Measuring learning outcomes. European Journal of Education 52(1):20-30. http://dx.doi.org/10.1111/ejed.12205
Coenen, F. H. J. M. 2009. Introduction. Pages 1-20 in F. H. J. M. Coenen, editor. Public participation and better environmental decisions. Springer, Cham, Switzerland.
Coenen, F. H. J. M., D. Huitema, and L. J. O’Toole. 1998. Participation and envrionmental decsion quality: an assessment. Pages 307-326 in F. H. J. M. Coenen, D. Huitema, and L. J. O’Toole, editors. Participation and the quality of envrionmental decision making. Kluwer, Dodrecht, The Netherlands.
Conley, A., and M. A. Moote. 2003. Evaluating collaborative natural resource management. Society and Natural Resources 16(5):371-386. https://doi.org/10.1080/08941920309181
Crona, B. I., and J. N. Parker. 2012. Learning in support of governance: theories, methods, and a framework to assess how bridging organizations contribute to adaptive resource governance. Ecology and Society 17(1):32. http://dx.doi.org/10.5751/ES-04534-170132
Cundill, G. 2010. Monitoring social learning processes in adaptive comanagement: three case studies from South Africa. Ecology and Society 15(3):28. http://dx.doi.org/10.5751/ES-03467-150328
Cuppen, E. 2018. The value of social conflicts. Critiquing invited participation in energy projects. Energy Research and Social Science 38:28-32. https://doi.org/10.1016/j.erss.2018.01.016
de Vries, J. R., S. van Bommel, C. Blackmore, and Y. Asano. 2017. Where there is no history: how to create trust and connection in learning for transformation in water governance. Water 9(2):130. http://dx.doi.org/10.3390/w9020130
Duram, L. A., and K. G. Brown. 1999. Assessing public participation in U.S. watershed planning initiatives. Society and Natural Resources 12(5):455-467. https://doi.org/10.1080/089419299279533
Edelenbos, J., A. van Buuren, and N. van Schie. 2011. Co-producing knowledge: joint knowledge production between experts, bureaucrats and stakeholders in Dutch water management projects. Environmental Science and Policy 14(6):675-684. http://dx.doi.org/10.1016/j.envsci.2011.04.004
Egunyu, F., and M. G. Reed. 2015. Social learning by whom? Assessing gendered opportunities for participation and social learning in collaborative forest governance. Ecology and Society 20(4):44. http://dx.doi.org/10.5751/ES-08126-200444
Elbakidze, M., L. Dawson, K. Andersson, R. Axelsson, P. Angelstam, I. Stjernquist, S. Teitelbaum, P. Schlyter, and C. Thellbro. 2015. Is spatial planning a collaborative learning process? A case study from a rural–urban gradient in Sweden. Land Use Policy 48:270-285. http://dx.doi.org/10.1016/j.landusepol.2015.05.001
Ernst, A., A. Fischer-Hotzel, and D. Schumann. 2017. Transforming knowledge for sustainability: insights from an inclusive science-practice dialogue on low-carbon society in Germany. Energy Research and Social Science 29:23-35. http://dx.doi.org/10.1016/j.erss.2017.04.006
Fiorino, D. J. 1990. Citizen participation and environmental risk: a survey of institutional mechanisms. Science, Technology, and Human Values 15(2):226-243. http://dx.doi.org/10.1177/016224399001500204
Garmendia, E., and S. Stagl. 2010. Public participation for sustainability and social learning: concepts and lessons from three case studies in Europe. Ecological Economics 69(8):1712-1722. http://dx.doi.org/10.1016/j.ecolecon.2010.03.027
Gerlak, A. K., and T. Heikkila. 2011. Building a theory of learning in collaboratives: evidence from the Everglades restoration program. Journal of Public Administration Research and Theory 21(4):619-644. http://dx.doi.org/10.1093/jopart/muq089
Gerlak, A. K., T. Heikkila, S. L. Smolinski, D. Huitema, and D. Armitage. 2018. Learning our way out of environmental policy problems: a review of the scholarship. Policy Sciences 51(3):335-371. http://dx.doi.org/10.1007/s11077-017-9278-0
Giebels, D., A. van Buuren, and J. Edelenbos. 2016. Knowledge governance for ecosystem-based management: understanding its context-dependency. Environmental Science and Policy 55(3):424-435. http://dx.doi.org/10.1016/j.envsci.2015.08.019
Glowacki, L., and L. Molleman. 2017. Subsistence styles shape human social learning strategies. Nature Human Behaviour 1:0098. http://dx.doi.org/10.1038/s41562-017-0098
Green, B. N., C. D. Johnson, and A. Adams. 2006. Writing narrative literature reviews for peer-reviewed journals: secrets of the trade. Journal of Chiropractic Medicine 5(3):101-117. http://dx.doi.org/10.1016/S0899-3467(07)60142-6
Heikkila, T., and A. K. Gerlak. 2013. Building a conceptual approach to collective learning: lessons for public policy scholars. Policy Studies Journal 41(3):484-512. http://dx.doi.org/10.1111/psj.12026
Huitema, D., C. Cornelisse, and B. Ottow. 2010. Is the jury still out? Toward greater insight in policy learning in participatory decision processes—the case of Dutch citizens’ juries on water management in the Rhine basin. Ecology and Society 15(1):16. [online] URL: http://www.ecologyandsociety.org/vol15/iss1/art16/
Jami, A. A., and P. R. Walsh. 2016. Wind power deployment: the role of public participation in the decision-making process in Ontario, Canada. Sustainability 8(8):713. http://dx.doi.org/10.3390/su8080713
Jennings, E. T. Jr., and J. L. Hall. 2012. Evidence-based practice and the use of information in state agency decision making. Journal of Public Administration Research and Theory 22(2):245-266. http://dx.doi.org/10.1093/jopart/mur040
Knoepfel, P., and I. Kissling-Näf. 1998. Social learning in policy networks. Policy and Politics 26(3):343-367. http://dx.doi.org/10.1332/030557398782213638
Koebele, E. A. 2015. Assessing outputs, outcomes, and barriers in collaborative water governance: a case study. Journal of Contemporary Water Research and Education 155(1):63-72. http://dx.doi.org/10.1111/j.1936-704X.2015.03196.x
Koontz, T. M. 2014. Social learning in collaborative watershed planning: the importance of process control and efficacy. Journal of Environmental Planning and Management 57(10):1572-1593. http://dx.doi.org/10.1080/09640568.2013.820658
Koontz, T. M., and E. M. Johnson. 2004. One size does not fit all: matching breadth of stakeholder participation to watershed group accomplishments. Policy Sciences 37(2):185-204. http://dx.doi.org/10.1023/B:OLIC.0000048532.94150.07
Kumler, L. M., and M. C. Lemos. 2008. Managing waters of the Paraíba do Sul River basin, Brazil: a case study in institutional change and social learning. Ecology and Society 13(2):22. [online] URL: http://www.ecologyandsociety.org/vol13/iss2/art22/
Leach, W. D., and N. W. Pelkey. 2001. Making watershed partnerships work: a review of the empirical literature. Journal of Water Resources Planning and Management 127(6):378-385. http://dx.doi.org/10.1061/(ASCE)0733-9496(2001)127:6(378)
Leach, W. D., N. W. Pelkey, and P. A. Sabatier. 2002. Stakeholder partnerships as collaborative policymaking: evaluation criteria applied to watershed management in California and Washington. Journal of Policy Analysis and Management 21(4):645-670. http://dx.doi.org/10.1002/pam.10079
Leach, W. D., and P. A. Sabatier. 2005. To trust an adversary: integrating rational and psychological models of collaborative policymaking. American Political Science Review 99(4):491-503. http://dx.doi.org/10.1017/S000305540505183X
Leach, W. D., C. M. Weible, S. R. Vince, S. N. Siddiki, and J. C. Calanni. 2014. Fostering learning through collaboration: knowledge acquisition and belief change in marine aquaculture partnerships. Journal of Public Administration Research and Theory 24(3):591-622. http://dx.doi.org/10.1093/jopart/mut011
Mostert, E., C. Pahl-Wostl, Y. Rees, B. Searle, D. Tàbara, and J. Tippett. 2007. Social learning in European river-basin management: barriers and fostering mechanisms from 10 river basins. Ecology and Society 12(1):19. [online] URL: http://www.ecologyandsociety.org/vol12/iss1/art19/
Muro, M. 2008. The role of social learning in participatory planning and management of water resources. Dissertation. Cranfield University, Cranfield, UK. [online] URL: http://hdl.handle.net/1826/3513
Muro, M., and P. Jeffrey. 2008. A critical review of the theory and application of social learning in participatory natural resource management processes. Journal of Environmental Planning and Management 51(3):325-344. http://dx.doi.org/10.1080/09640560801977190
Muro, M., and P. Jeffrey. 2012. Time to talk? How the structure of dialog processes shapes stakeholder learning in participatory water resources management. Ecology and Society 17(1):3. http://dx.doi.org/10.5751/ES-04476-170103
Natarajan, L. 2017. Socio-spatial learning: a case study of community knowledge in participatory spatial planning. Progress in Planning 111:1-23. http://dx.doi.org/10.1016/j.progress.2015.06.002
Newig, J., E. Challies, N. W. Jager, E. Kochskaemper, and A. Adzersen. 2018. The environmental performance of participatory and collaborative governance: a framework of causal mechanisms. Policy Studies Journal 46(2):269-297. http://dx.doi.org/10.1111/psj.12209
O’Toole, L. J. Jr., and K. J. Meier. 2014. Public management, context, and performance: in quest of a more general theory. Journal of Public Administration Research and Theory 25(1):237-256. http://dx.doi.org/10.1093/jopart/muu011
Pahl-Wostl, C., M. Craps, A. Dewulf, E. Mostert, D. Tabara, and T. Taillieu. 2007. Social learning and water resources management. Ecology and Society 12(2):5. http://dx.doi.org/10.5751/ES-02037-120205
Palm, J., and J. Thoresson. 2014. Strategies and implications for network participation in regional climate and energy planning. Journal of Environmental Policy and Planning 16(1):3-19. http://dx.doi.org/10.1080/1523908X.2013.807212
Parés, M., Q. Brugué, J. Espluga, J. Miralles, and A. Ballester. 2015. The strengths and weaknesses of deliberation on river basin management planning: analysing the water framework directive implementation in Catalonia (Spain). Environmental Policy and Governance 25(2):97-110. http://dx.doi.org/10.1002/eet.1662
Peterson, N. D., K. Broad, B. Orlove, C. Roncoli, R. Taddei, and M.-A. Velez. 2010. Participatory processes and climate forecast use: socio-cultural context, discussion, and consensus. Climate and Development 2(1):14-29. http://dx.doi.org/10.3763/cdev.2010.0033
Petts, J. 2006. Managing public engagement to optimize learning: reflections from urban river restoration. Human Ecology Review 13(2):172-181. [online] URL: http://www.apjh.humanecologyreview.org/pastissues/her132/petts.pdf
Podestá, G. P., C. E. Natenzon, C. Hidalgo, and F. R. Toranzo. 2013. Interdisciplinary production of knowledge with participation of stakeholders: a case study of a collaborative project on climate variability, human decisions and agricultural ecosystems in the Argentine Pampas. Environmental Science and Policy 26:40-48. http://dx.doi.org/10.1016/j.envsci.2012.07.008
Pohl, C., S. Rist, A. Zimmermann, P. Fry, G. S. Gurung, F. Schneider, C. I. Speranza, B. Kiteme, S. Boillat, E. Serrano, G. Hirsch Hadorn, and U. Wiesmann. 2010. Researchers’ roles in knowledge co-production: experience from sustainability research in Kenya, Switzerland, Bolivia and Nepal. Science and Public Policy 37(4):267-281. http://dx.doi.org/10.3152/030234210X496628
Reed, M. S. 2008. Stakeholder participation for environmental management: a literature review. Biological Conservation 141(10):2417-2431. http://dx.doi.org/10.1016/j.biocon.2008.07.014
Reed, M. S., A. C. Evely, G. Cundill, I. Fazey, J. Glass, A. Laing, J. Newig, B. Parrish, C. Prell, C. Raymond, and L. C. Stringer. 2010. What is social learning? Ecology and Society 15(4):r1. [online] URL: http://www.ecologyandsociety.org/vol15/iss4/resp1/
Renn, O. 2005. Partizipation - ein schillernder Begriff: reaktion auf drei Beiträge zum thema “Partizipation” in GAIA 14/1 (2005) und GAIA 14/3 (2005). GAIA - Ecological Perspectives for Science and Society 14(3):227-228. https://doi.org/10.14512/gaia.14.3.8
Renn, O. 2006. Participatory processes for designing environmental policies. Land Use Policy 23(1):34-43. http://dx.doi.org/10.1016/j.landusepol.2004.08.005
Ringberg, T., and M. Reihlen. 2008. Towards a socio-cognitive approach to knowledge transfer. Journal of Management Studies 45(5):912-935. http://dx.doi.org/10.1111/j.1467-6486.2007.00757.x
Roberts, P. D., G. B. Stewart, and A. S. Pullin. 2006. Are review articles a reliable source of evidence to support conservation and environmental management? A comparison with medicine. Biological Conservation 132(4):409-423. http://dx.doi.org/10.1016/j.biocon.2006.04.034
Roldán, A. M. 2017. Political regime and learning outcomes of stakeholder participation: cross-national study of 81 Biosphere Reserves. Sustainability 9(4):553. https://doi.org/10.3390/su9040553
Rowe, G., and L. J. Frewer. 2000. Public participation methods: a framework for evaluation. Science, Technology, and Human Values 25(1):3-29. http://dx.doi.org/10.1177/016224390002500101
Sabatier, P. A., C. Weible, and J. Ficker. 2005. Eras of water management in the United States: implications for collaborative watershed approaches. Pages 23-52 in P. A. Sabatier, W. Focht, M. Lubell, Z. Trachtenberg, A. Vedlitz, and M. Matlock, editors. Swimming upstream: collaborative approaches to watershed management. MIT Press, Cambridge, Massachusetts, USA.
Schroeter, R., O. Scheel, O. Renn, and P.-J. Schweizer. 2016. Testing the value of public participation in Germany: theory, operationalization and a case study on the evaluation of participation. Energy Research and Social Science 13:116-125. http://dx.doi.org/10.1016/j.erss.2015.12.013
Schusler, T. M., D. J. Decker, and M. J. Pfeffer. 2003. Social learning for collaborative natural resource management. Society and Natural Resources 16(4):309-326. http://dx.doi.org/10.1080/08941920390178874
Siebenhüner, B., R. Rodela, and F. Ecker. 2016. Social learning research in ecological economics: a survey. Environmental Science and Policy 55(1):116-126. http://dx.doi.org/10.1016/j.envsci.2015.09.010
Squires, H., and O. Renn. 2011. Can participatory modelling support social learning in marine fisheries? Reflections from the Invest in Fish South West project. Environmental Policy and Governance 21(6):403-416. http://dx.doi.org/10.1002/eet.588
Tippett, J., B. Searle, C. Pahl-Wostl, and Y. Rees. 2005. Social learning in public participation in river basin management—early findings from HarmoniCOP European case studies. Environmental Science and Policy 8(3):287-299. http://dx.doi.org/10.1016/j.envsci.2005.03.003
van de Kerkhof, M., and A. Wieczorek. 2005. Learning and stakeholder participation in transition processes towards sustainability: methodological considerations. Technological Forecasting and Social Change 72(6):733-747. http://dx.doi.org/10.1016/j.techfore.2004.10.002
van der Wal, M., J. De Kraker, A. Offermans, C. Kroeze, P. A. Kirschner, and M. van Ittersum. 2014. Measuring social learning in participatory approaches to natural resource management. Environmental Policy and Governance 24(1):1-15. http://dx.doi.org/10.1002/eet.1627
Verba, S., K. L. Schlozman, and H. E. Brady. 1995. Voice and equality: civic voluntarism in American politics. Harvard University Press, Cambridge, Massachusetts, USA.
von Korff, Y., K. A. Daniell, S. Moellenkamp, P. Bots, and R. M. Bijlsma. 2012. Implementing participatory water management: recent advances in theory, practice, and evaluation. Ecology and Society 17(1):30. http://dx.doi.org/10.5751/ES-04733-170130
Waylen, K. A., K. L. Blackstock, K. B. Marshall, and J. Dunglinson. 2015. Participation-prescription tension in natural resource management: the case of diffuse pollution in Scottish water management. Environmental Policy and Governance 25(2):111-124. http://dx.doi.org/10.1002/eet.1666
Webler, T. 1995. “Right” discourse in citizen participation: an evaluative yardstick. Pages 35-86 in O. Renn, T. Webler, and P. Wiedemann, editors. Fairness and competence in citizen participation: evaluating models for environmental discourse. Kluwer, Dordrecht, The Netherlands.
Webler, T., H. Kastenholz, and O. Renn. 1995. Public participation in impact assessment: a social learning perspective. Environmental Impact Assessment Review 15(5):443-463. http://dx.doi.org/10.1016/0195-9255(95)00043-E
Webler, T., and S. Tuler. 2000. Fairness and competence in citizen participation: theoretical reflections from a case study. Administration and Society 32(5):566-595. http://dx.doi.org/10.1177/00953990022019588
Westberg, L., and M. Polk. 2016. The role of learning in transdisciplinary research: moving from a normative concept to an analytical tool through a practice-based approach. Sustainability Science 11(3):385-397. http://dx.doi.org/10.1007/s11625-016-0358-4
Wiek, A. 2007. Challenges of transdisciplinary research as interactive knowledge generation - experiences from transdisciplinary case study research. Gaia - Ecological Perspectives for Science and Society 16(1):52-57. http://dx.doi.org/10.14512/gaia.16.1.14
Wilner, K. B., M. Wiber, A. Charles, J. Kearney, M. Landry, L. Wilson, and on behalf of the Coastal CURA Team. 2012. Transformative learning for better resource management: the role of critical reflection. Journal of Environmental Planning and Management 55(10):1331-1347. http://dx.doi.org/10.1080/09640568.2011.646679
Yandle, T., N. Hajj, and R. Raciborski. 2011. The goldilocks solution: exploring the relationship between trust and participation in resource management within the New Zealand commercial rock lobster fishery. Policy Studies Journal 39(4):631-658. http://dx.doi.org/10.1111/j.1541-0072.2011.00425.x
Young, O. R. 1997. Rigths, rules, and resources in world affairs. Pages 1-24 in O. R. Young, editor. Global governance: drawing insights from the environmental experience. MIT Press, Cambridge, Massachusetts, USA.