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Introduction, defining collaborative governance: scope and origins, an integrative framework for collaborative governance, discussion and conclusion, an integrative framework for collaborative governance.

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Kirk Emerson, Tina Nabatchi, Stephen Balogh, An Integrative Framework for Collaborative Governance, Journal of Public Administration Research and Theory , Volume 22, Issue 1, January 2012, Pages 1–29, https://doi.org/10.1093/jopart/mur011

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Collaborative governance draws from diverse realms of practice and research in public administration. This article synthesizes and extends a suite of conceptual frameworks, research findings, and practice-based knowledge into an integrative framework for collaborative governance. The framework specifies a set of nested dimensions that encompass a larger system context, a collaborative governance regime, and its internal collaborative dynamics and actions that can generate impacts and adaptations across the systems. The framework provides a broad conceptual map for situating and exploring components of cross-boundary governance systems that range from policy or program-based intergovernmental cooperation to place-based regional collaboration with nongovernmental stakeholders to public-private partnerships. The framework integrates knowledge about individual incentives and barriers to collection action, collaborative social learning and conflict resolution processes, and institutional arrangements for cross-boundary collaboration. It is presented as a general framework that might be applied to analyses at different scales, in different policy arenas, and varying levels of complexity. The article also offers 10 propositions about the dynamic interactions among components within the framework and concludes with a discussion about the implications of the framework for theory, research, evaluation, and practice.

Colaborativa gobernanza extrae de diversas esferas de la practica e investigación de la administración pública. Este articulo sintetiza y extiende marcos conceptuales, resultados de investigación y conocimiento basado en la práctica dentro de un marco integrativo de gobernanza colaborativa. El marco específica un conjunto de dimensiones anidadas, abarcando un gran contexto del sistema, un régimen de gobernanza colaborativa, y las dinámicas y acciones colaborativas internas que pueden generar impactos y adaptaciones a través de los sistemas. El marco proporciona un mapa conceptual amplio para situar y explorar los componentes más allá de los límites del sistema de gobernanza los cuales van desde cooperación regional intergubernamental in base a programas o políticas hasta cooperación con interesados non gubernamentales en base a su localización hasta incluir asociaciones entre entes públicas y privadas. El marco integra información acerca de los incentivos y dificultades individuales de acción colectiva, el aprendizaje social y colaborativo, los procesos de resolución de conflicto, y las configuraciones institucionales para colaboración fuera de límites. El marco general que se presenta podría ser aplicado a análisis de escalas diferentes, en diferentes áreas de política, y en diferentes niveles de complejidad. El artículo también proporciona 10 proposiciones acerca de las interacciones dinámicas entre los componentes del marco y concluye con una discusión de las implicaciones del marco para teoría, investigación, evaluación y la práctica.

Translations by Claudia N. Avellaneda, University of North Carolina Charlotte

and Nicolai Petrovsky, University of Kentucky

Collaborative governance has become a common term in the public administration literature, yet its definition remains amorphous and its use inconsistent. Moreover, the variation in the scope and scale of perspectives on collaborative governance restricts the ability of researchers to further develop and test theory. This article addresses some of the conceptual limitations associated with the study of collaborative governance. It synthesizes and extends a suite of conceptual frameworks, research findings, and practice-basedknowledge into an integrative framework for researching, practicing, and evaluating collaborative governance.

The framework for collaborative governance is integrative in several ways. First, our definition of collaborative governance is broader than what is commonly seen in the literature, and our framework draws on and applies knowledge and concepts from a wide range of fields (such as public administration, conflict resolution, and environmental management among others) to collaborative governance. This makes the framework potentially relevant to scholars and practitioners working in several applications and settings, such as collaborative public management, multipartner governance, joined-up or network government, hybrid sectoral arrangements, co-management regimes, participatory governance, and civic engagement, all of which share common characteristics with collaborative governance writ large. Second, the framework integrates numerous components of collaborative governance—from system context and external drivers through collaborative dynamics to actions, impacts, and adaptation. This enables scholars to study a collaborative governance regime (CGR) as a whole, or to focus on its various components and/or elements, while facilitating interdisciplinary research on complex, multilevel systems. Finally, it organizes several variables into a multilevel framework, enabling further analysis of the internal dynamics and causal pathways of collaborative governance and its performance. Together, these attributes can allow for the broad application of the integrative framework across sectors, settings, processes, issues, and time.

In this article, we first define collaborative governance and explore its scope and origins in the public administration and related literatures. We then present the framework for collaborative governance along with 10 propositions to guide future inquiry and theory building. We conclude with a discussion about the implications of the framework for public administration theory, research, and practice.

As a general term, “governance” refers to the act of governing, be it in the public and/or private sector. Within the context of collective action, Ostrom (1990) considers governance as a dimension of jointly determined norms and rules designed to regulate individual and group behavior. O'Leary, Bingham, and Gerard (2006 , 7) define governance as the “means to steer the process that influences decisions and actions within the private, public, and civic sectors.” More specifically, governance is “a set of coordinating and monitoring activities” that enables the survival of the collaborative partnership or institution ( Bryson, Crosby, and Stone 2006 ).

We define collaborative governance broadly as the processes and structures of public policy decision making and management that engage people constructively across the boundaries of public agencies, levels of government, and/or the public, private and civic spheres in order to carry out a public purpose that could not otherwise be accomplished. This definition allows collaborative governance to be used as a broader analytic construct in public administration and enables distinctions among different applications, classes, and scales. It responds, in part, to the observation by Ansell and Gash (2008, 544) that scholars have been focusing more “on the species rather than the genus” of collaborative governance.

Moreover, our definition of collaborative governance captures a fuller range of emergent forms of cross-boundary governance, extending beyond the conventional focus on the public manager or the formal public sector. Thus, it is broader than the definition proposed by Ansell and Gash (2008, 544) : “A governing arrangement where one or more public agencies directly engage non-state stakeholders in a collective decision-making-process that is formal, consensus-oriented, and deliberative and that aims to make or implement public policy or manage public programs or assets.” Unlike the Ansell and Gash definition, our definition does not limit collaborative governance to only formal, state-initiated arrangements, and to engagement between government and nongovernmental stakeholders. For example, our definition encompasses “multipartner governance,” which can include partnerships among the state, the private sector, civil society, and the community, as well as joined-up government and hybrid arrangements such as public-private and private-social partnerships and co-management regimes ( Agrawal and Lemos 2007 ). It also includes the myriad of community-based collaboratives involved in collective resource management (that often invite the participation of public agencies), as well as intergovernmental collaborative structures such as interstate river basin commissions governed by state and federal government representatives, and federal interagency collaboration among on public health policy or climate change science, among other types of collaborative arrangements initiated in the private or civic sectors (Emerson and Murchie 2010) . Finally, it can also be applied to or used to inform participatory governance and civic engagement, although we recognize that the extent of involvement by citizens and the public in collaborative governance can vary considerably.

Recently, several scholars have traced the multifaceted provenance of collaborative governance ( Ansell and Gash 2008 ; Bingham and O'Leary 2008 ; Cooper, Bryer, and Meek 2006 ; Fung 2006 ; Sirianni 2009 ), thus, only a brief review of some of its major connections to public administration is presented here. Specifically, we identify some of its origins in theory, its connection to broader notions of public administration and democracy, and its application to various management practices and in different management settings.

In terms of theory, several scholars connect the concept of collaborative governance with the study of intergovernmental cooperation in the 1960s ( Agranoff and McGuire 2003 ; Elazar 1962 , 1984 ), whereas others trace its roots back to the birth of American federalism itself—“the most enduring model of collaborative problem resolution” ( McGuire 2006 ). Collaborative governance has also been connected to Bentley's (1949) group theory and the subsequent theoretical reaction and evolution from Olsen's (1965) , Logic of Collective Action , to the prisoner's dilemma and game theory ( Axelrod 1984 ; Dawes 1973 ), and to the extensive common-pool resource literature ( Ostrom 1990 ).

Similarly, collaborative governance strikes at the heart of broader concepts of public administration and democracy. For many public administration scholars, collaborative governance is the new paradigm for governing in democratic systems ( Frederickson 1991 ; Jun 2002 ; Kettl 2002 ). Democracy theorists and researchers have long commented on the decline in American civic institutions, voting behavior, and social capital ( Fishkin 1991 ; Nabatchi 2010 ; Putnam 1995 ; Sirianni 2009 ; Skocpol 2002 ). Such observations have inspired new forms of public involvement and civic engagement, referred to by many as the deliberative democracy movement ( Fung and Wright 2001 ; Nabatchi 2010 ; Sirianni 2009 ; Torres 2003 ). Deliberative democracy promises citizens opportunities to exercise voice and a more responsive, citizen-centered government by embedding “governance systems and institutions with greater levels of transparency, accountability and legitimacy” ( Henton, Melville, Amsler, and Kopell 2005 , 5; see also Bryson, Crosby, and Stone 2006 ; Nabatchi 2010 ).

Collaborative governance also has roots in management practices. At its core, Kettl (2006) describes “the collaboration imperative” as cross-boundary . McGuire (2006) points out that the importance of shared administration was recognized at the start of the literature on policy implementation (see also Pressman and Wildavsky 1973 ). Intergovernmental relations and network theory helped give rise to studies about horizontal network management and collaborative public management ( Agranoff and McGuire 2001 ; Kamensky and Burlin 2004 ; Wright 1988 ). Game theory promulgated attention to interest-based negotiation and mutual gains bargaining ( Fisher, Ury, and Patton 1991 ; Raiffa 1982 ) and informed the practice of alternative dispute resolution, conflict management, and consensus building in labor relations, personnel management, contracting, and environmental and public policy ( Goldberg, Sanders, and Rogers 1992 ; O'Leary and Bingham 2003 ; Susskind, McKearnan, and Thomas-Larmer 1999 ).

Within these streams of theory and research, collaborative governance has been applied and studied in several policy contexts. It has been used by law enforcement agencies (e.g., Nicholson-Crotty and O‘Toole 2004 ), the Veteran's Health Administration (e.g., Dudley and Raymer 2001 ), and the Department of Homeland Security (e.g., Jenkins 2006 ; Taylor 2006 ). It has been applied to child and family service delivery (e.g., Berry et al. 2008 ; Graddy and Chen 2006 ; Page 2003 ; Sowa 2008 ) and to government contracting (e.g., Bloomfield 2006 ; Brown, Potoski, and Van Slyke 2007 ; Romzek and Johnston 2005 ). Collaborative governance approaches have been instrumental to local economic policy (e.g., Agranoff and McGuire 1998 ), crisis management (e.g., Farazamand 2007 ; Kettl 2006 ), collaboration between environmental agencies and state and local public health departments (e.g., Daley 2009 ), and on environmental issues such as the protection of open-spaces (e.g., Smith 2009 ), natural resources management (e.g., Durant et al. 2004 ; Koontz and Thomas 2006 ), and forest management in both the United States (e.g., Manring 2005 ) and India (e.g., Ebrahim 2004 ; Kumar, Kant, and Amburgey 2007 ).

In order to develop a useful framework for collaborative governance with which to better understand, develop, and test theory, as well as improve practice, we needed to explore and synthesize a broad array of literature. This included work in many different applied fields, such as public administration, planning, conflict management, and environmental governance among others. We began with literature that speaks directly to collaborative governance, then moved to those literatures that are more tangentially related to collaborative governance, and finally to literatures that connect to particular concepts that we identified and/or developed in the integrative framework. Our goal was to look across various research lenses to see how they might inform collaborative governance, that is, to see how different research streams could illuminate the drivers, engagement processes, motivational attributes, and joint capacities that enable shared decision making, management, implementation, and other activities across organizations, jurisdictions, and sectors.

We also searched for relevant conceptual frameworks that were grounded in empirical studies. Chief among the frameworks we reviewed are those for: cross-sector collaboration ( Bryson, Crosby, and Stone 2006 ), collaborative planning ( Bentrup 2001 ; Innes and Booher 1999 ; Selin and Chavez 1995 ), collaboration processes ( Daniels and Walker 2001 ; Ring and Van de Ven 1994 ; Thomson and Perry 2006 ; Wood and Gray 1991 ), network management ( Koppenjan and Klijn 2004 ; Milward and Provan 2000 ), collaborative public management ( Agranoff and McGuire 2001 ; Cooper, Bryer, and Meek 2006 ; Leach 2006 ), environmental governance and conflict resolution ( Agrawal and Lemos 2007 ; Emerson et al. 2009 ), and collaborative governance ( Ansell and Gash 2008 ).

In comparing these frameworks, we found expected overlap and considerable variation. The variations stem, in part, from the different research traditions, policy arenas, and scales in which these scholars work. 1 Another common challenge we encountered with these frameworks is a lack of generalizability, that is, their inapplicability across different settings, sectors, geographic and temporal scales, policy arenas, and process mechanisms. 2 Despite these variations, each of the above frameworks (and the research streams in which they are located) helped inform and refine our a priori assumptions about categories and variables in the integrative framework and helped to identify important categories and variables that we had missed.

Ostrom (2007) warns about the perils associated with constructing frameworks of this sort and the problems of creating “panaceas,” models that are either overly simplistic or overly specified and burdened with long lists of variables and exacting conditions to meet and test. We approached this dilemma by identifying a relatively small number of dimensions within which components are posited to work together in a nonlinear, interactive fashion to produce actions, which lead to outcomes (actions and impacts), and in turn adaptation.

Our integrative framework for collaborative governance is depicted in figure 1 as three nested dimensions, shown as boxes, representing the general system context, the collaborative governance regime (CGR), and its collaborative dynamics and actions. The outermost box, depicted by solid lines, represents the surrounding system context or the host of political, legal, socioeconomic, environmental and other influences that affect and are affected by the CGR. This system context generates opportunities and constraints and influences the dynamics of the collaboration at the outset and over time. From this system context emerge drivers , including leadership, consequential incentives, interdependence, and uncertainty, which help initiate and set the direction for a CGR.

The Integrative Framework for Collaborative Governance

The concept of a CGR is a central feature in this framework. We use the term “regime” to encompass the particular mode of, or system for, public decision making in which cross-boundary collaboration represents the prevailing pattern of behavior and activity. Crosby and Bryson (2005, 51) also use this term in their work, drawing on Krasner's (1983, 2) definition of regime as “sets of implicit and explicit principles, rules, norms, and decision-making procedures around which actors’ expectations converge in a given area.” In this framework, the CGR is depicted by the middle box with the dashed lines and contains both the collaborative dynamics and collaborative actions. Together, collaborative dynamics and actions shape the overall quality and extent to which a CGR is developed and effective.

Collaborative dynamics , represented by the innermost box with dotted lines, consist of three interactive components: principled engagement, shared motivation, and capacity for joint action. The three components of collaborative dynamics work together in an interactive and iterative way to produce collaborative actions or the steps taken in order to implement the shared purpose of the CGR. The actions of the CGR can lead to outcomes both within and external to the regime; thus, in the figure, arrows extend from the action box to demonstrate impacts (i.e., the results on the ground) and potential adaptation (the transformation of a complex situation or issue) both within the system context and the CGR itself.

In short, the structure of the integrative framework incorporates nested dimensions and their respective components. Specific elements within the components are listed in table 1 and described in more detail below. It is important to note that our framework incorporates many of the components identified in other frameworks but configures them in a way that posits causal relationships among the dimensions and their components and elements.

A Diagnostic or Logic Model Approach to Collaborative Governance

As we describe the framework in more detail below, we relate it to other frameworks and present general propositions about how these dimensions, components, and elements interact. These propositions represent first steps in theory building (and can be used for future theory testing) as they set forth general preliminary working assumptions about what factors lead to collaboration and how the components work together to produce desired states. In this sense, we offer not only an integrative framework (i.e., we identify the overarching variables that are important to the study of collaborative governance and how they generally relate) but also offer some initial pathways for integrating existing theory and building new theory based on the framework (i.e., through the propositions, we begin to develop theory, for example, about what factors lead to collaboration, what leads to the success and effectiveness of collaborative governance, and how a CGR may achieve adaptation). 3

General System Context

Collaborative governance is initiated and evolves within a multilayered context of political, legal, socioeconomic, environmental, and other influences ( Borrini-Feyerabend 1996 ). This external system context creates opportunities and constraints and influences the general parameters within which a CGR unfolds. Not only does the system context shape the overall CGR but the regime itself can also affect the system context through the impact of its collaborative actions. 4

Researchers have recognized several chief elements in the system context that may distinguish or influence the nature and prospects of a CGR, including resource conditions in need of improving, increasing, or limiting (e.g., Ostrom 1990 ); policy and legal frameworks, including administrative, regulatory, or judicial (e.g., Bingham 2008 ); prior failure to address the issues through conventional channels and authorities (e.g., Bryson and Crosby 2008 ); political dynamics and power relations within communities and among/across levels of government (e.g., Ansell and Gash 2008 ); degree of connectedness within and across existing networks (e.g., Selin and Chavez 1995 ); historic levels of conflict among recognized interests and the resulting levels of trust and impact on working relationships (e.g., Ansell and Gash 2008 ; Radin 1996 ; Thomson and Perry 2006 ); and socioeconomic and cultural health and diversity (e.g., Sabatier et al. 2005 ).

The system context is represented in this framework, not as a set of starting conditions but as a surrounding three-dimensional space because external conditions (e.g., an election, economic downturn, extreme weather event, or newly enacted regulation) may influence the dynamics and performance of collaboration not only at the outset but at any time during the life of the CGR, thus opening up new possibilities or posing unanticipated challenges.

Although the literature broadly recognizes that the “conditions present at the outset of collaboration can either facilitate or discourage cooperation among stakeholders and between agencies and stakeholders” ( Ansell and Gash 2008, 550 ), many frameworks tend to conflate system context and conditions with the specific drivers of collaboration (e.g., Ansell and Gash 2008 ; Bentrup 2001 ; Thomson and Perry 2006 ; for an exception, see Bryson, Crosby, and Stone 2006 ). In contrast, our framework separates the contextual variables from essential drivers, without which the impetus for collaboration would not successfully unfold. These drivers include leadership, consequential incentives, interdependence, and uncertainty.

Leadership , the first essential driver, refers to the presence of an identified leader who is in a position to initiate and help secure resources and support for a CGR. The leader may, by virtue of her own stature, be a member of one of the parties or the deciding official or may be located within a trusted boundary organization. Regardless, she should possess a commitment to collaborative problem solving, a willingness not to advocate for a particular solution, and exhibit impartiality with respect to the preferences of participants ( Bryson, Crosby, and Stone 2006 ; Selin and Chavez 1995 ). In addition, the willingness of a leader to absorb the high (and potentially constraining) transaction costs of initiating a collaborative effort, for example, by providing staffing, technologies, and other resources may help reinforce the endeavor (e.g., Schneider et al. 2003 ).

Consequential incentives refer to either internal (problems, resource needs, interests, or opportunities) or external (situational or institutional crises, threats, or opportunities) drivers for collaborative action. Such incentives are consequential in that the presenting issues are salient to participants, the timing or pressure for solutions is ripe, and the absence of attention to the incentives may have negative impacts ( Selin and Chavez 1995 ). It should be noted, however, that not all consequential incentives are negative. For example, the availability of a grant or new funding opportunity may lead to the development of a collaborative initiative. Nevertheless, such incentives (positive or negative) must exist to induce leaders and participants to engage together.

Interdependence , or when individuals and organizations are unable to accomplish something on their own, is a broadly recognized precondition for collaborative action ( Gray 1989 ; Thomson and Perry 2006 ). In a sense, this is the ultimate consequential incentive. This driver is referred to as “sector failure” by Bryson, Crosby, and Stone (2006) and as “constraints on participation” by Ansell and Gash (2008) .

The final driver, uncertainty , is a primary challenge for managing “wicked” societal problems ( Koppenjan and Klijn 2004 ; Rittel and Webber 1973 ). Uncertainty that cannot be resolved internally can drive groups to collaborate in order to reduce, diffuse, and share risk. Collective uncertainty about how to manage societal problems is also related to the driver of interdependence. Were parties or organizations endowed with perfect information about a problem and its solution, they would be able to act independently to pursue their interests or respond to risk ( Bentrup 2001 ). There can also be individual uncertainty about the extent to which conventional avenues for solutions or satisfaction (sometimes referred to as the Best Alternative to a Negotiated Agreement in conflict management literature) can be relied on to produce the intended result.

One or more of the drivers of leadership, consequential incentives, interdependence, or uncertainty are necessary for a CGR to begin. The more drivers present and recognized by participants, the more likely a CGR will be initiated.

Collaborative Governance Regime

As previously described, the integrative framework introduces the term CGR, to denote a system in which cross-boundary collaboration represents the predominate mode for conduct, decision making, and activity. The form and direction of the CGR is shaped initially by the drivers that emerge from the system context; however, the development of the CGR, as well as the degree to which it is effective, is influenced over time by its two components: collaborative dynamics and collaborative actions. Below, we describe these two components, as well as the various elements embedded within them.

Collaborative Dynamics

Essential drivers energize or induce the convening of participants by reducing the initial formative costs of collective action and setting the collaborative dynamics in motion. These dynamics and the actions they produce over time constitute a CGR. Several scholars portray collaborative processes as a linear sequence of cognitive steps or stages that occur over time from problem definition to direction setting and implementation ( Daniels and Walker 2001 ; Gray 1989 ; Selin and Chavez 1995 ). In contrast, and consistent with Ansell and Gash (2008) and Thomson and Perry (2006) , we view the stages within collaborative dynamics as cyclical or iterative interactions. We focus on three interacting components of collaborative dynamics: principled engagement, shared motivation, and capacity for joint action.

Principled Engagement

Principled engagement occurs over time and may include different stakeholders at different points and take place in face-to-face or virtual formats, cross-organizational networks, or private and public meetings, among other settings. Through principled engagement, people with differing content, relational, and identity goals work across their respective institutional, sectoral, or jurisdictional boundaries to solve problems, resolve conflicts, or create value ( Cahn 1994 ; Cupach and Canary 1997 ; Lulofs and Cahn 2000 ). Although face-to-face dialogue is advantageous at the outset, it is not always essential, particularly when conflict may be low and shared values and objectives quickly surface.

We call this component in our framework “principled” engagement to adhere to the basic espoused principles articulated broadly in both practice and research, including fair and civil discourse, open and inclusive communications, balanced by representation of “all relevant and significant different interests” ( Innes and Booher 1999, 419 ), and informed by the perspectives and knowledge of all participants (see also Ansell and Gash 2008 ; Carlson 2007 ; Henton et al. 2005 ; Leach 2006 ; O'Leary, Bingham, and Gerard 2006 ; Susskind, McKearnan, and Thomas-Larmer 1999 ). 5

Before specifying the nested elements within principled engagement, it is important to discuss the participants. Who the participants are and who they represent are of signal importance to collaboration. Participants may also be called members, stakeholders, parties, partners, or collaborators, depending on the context and objectives of the CGR. They may represent themselves, a client, a constituency, a decision maker, a public agency, an NGO, a business or corporation, a community, or the public at large. Their selection may vary considerably, ranging from state-based participants (e.g., expert administrators and elected representatives), to mini-publics (e.g., professional or lay stakeholders or randomly selected, self-selected, or recruited individuals), and diffuse members of the public ( Fung 2006 ). Their number may range from 2 to 10,000 or more ( Emerson et al. 2009 ). Moreover, each participant brings a set of individual attitudes, values, interests, and knowledge in addition to the cultures, missions, and mandates of the organizations or constituents they represent ( Bardach 2001 ).

There is general agreement in practice and research that getting the “right” people to the table is important ( Ansell and Gash 2008 ; Carlson 2007 ; Carpenter and Kennedy 2001 ; Emerson et al. 2009 ; Susskind, McKearnan, and Thomas-Larmer 1999 ). Inclusion and diversity are valued not only as normative organizing principles but also for instrumental reasons—they give voice to multiple perspectives and different interests, allowing the development of more thoughtful decisions that take a broader view of who will benefit or be harmed by an action ( Beierle and Cayford 2002 ; Sirianni 2009 ). Moreover, the relative and combined power of the participants can enable or disable subsequent agreements or collective courses of action. 6

Principled engagement occurs over time through the iteration of four basic process elements: discovery, definition, deliberation, and determination. These build on collaborative learning phases by Daniels and Walker (2001) and may be thought of as elements of a dynamic social learning process (e.g., Bandura 1977 ). Through this iterative process, collaboration partners develop a shared sense of purpose and a shared theory of action for achieving that purpose. This shared theory of action includes the group's understanding of the size of the problem or challenge it is addressing, as well as the scope and scale of the group's chosen activities or interventions ( Koontz et al. 2004 ; Leach and Pelkey 2001 ).

Discovery refers to the revealing of individual and shared interests, concerns, and values, as well as to the identification and analysis of relevant and significant information and its implications. At the outset, discovery may be focused on identifying shared interests; later, it might be observed in joint fact-finding and more analytic investigation ( Ehrmann and Stinson 1999 ; Ozawa 1991 ). The definition process characterizes the continuous efforts to build shared meaning by articulating common purpose and objectives; agreeing on the concepts and terminology participants will use to describe and discuss problems and opportunities; clarifying and adjusting tasks and expectations of one another; and setting forth shared criteria with which to assess information and alternatives (for discussions, see Bentrup 2001 ; Pahl-Wostl 2007 ).

Deliberation , or candid and reasoned communication, is broadly celebrated as a hallmark and essential ingredient of successful engagement. The quality of deliberation, especially when participants have differing interests and perspectives, depends on both the skillful advocacy of individual and represented interests and the effectiveness of conflict resolution strategies and interventions, described in a recent National Research Council (2009) report as “deliberation with analysis.” Hard conversations, constructive self-assertion, asking and answering challenging questions, and expressing honest disagreements are part and parcel of effective communication across boundaries. Collaborative governance creates the “safe” space for such deliberation to take place. Advocates of deliberative democracy, public engagement, and alternative dispute resolution agree on the importance of enabling the exercise of meaningful “voice” through deliberation. As Roberts (2004 , 332) notes, “Deliberation is not ‘the aggregation of interests.’ It requires thoughtful examination of issues, listening to others' perspectives, and coming to a public judgment on what represents the common good.”

Finally, principled engagement incorporates the processes of making enumerable joint determinations , including procedural decisions (e.g., setting agendas, tabling a discussion, assigning a work group) and substantive determinations (e.g., reaching agreements on action items or final recommendations). Substantive determinations are often considered one of the outputs or end products of collaboration or conflict resolution ( Dukes 2004 ; Emerson et al. 2009 ). In an ongoing CGR, however, many substantive determinations are made over time; these are integrated in the framework as a repeating element within principled engagement.

Collaboration theory and practice suggest that determinations produced through strong engagement processes will be fairer and more durable, robust, and efficacious ( Innes and Booher 1999 ; Sipe and Stiftel 1995 ; Susskind and Cruikshank 1987 ). However, there is limited research on the quality of collaborative determinations and the extent to which they lead to actions required for implementation ( Bingham and O'Leary 2008 ). Most practitioners and researchers, however, advance consensus building as the foundational method for making group determinations (e.g., Innes and Booher, 1999 ; Susskind and Cruikshank 1987 ), although this does not mean that consensus as a decision rule is always required or achieved ( Susskind, McKearnan, and Thomas-Larmer 1999 ).

Principled engagement is generated and sustained by the interactive processes of discovery, definition, deliberation, and determination. The effectiveness of principled engagement is determined, in part, by the quality of these interactive processes.

Shared Motivation

We define shared motivation as a self-reinforcing cycle consisting of four elements: mutual trust, understanding, internal legitimacy, and commitment. All but legitimacy are included in the Ansell and Gash (2008) configuration of collaborative process. Shared motivation highlights the interpersonal and relational elements of the collaborative dynamics and is sometimes referred to as social capital ( Colman 1988 ; Putnam 2000 ; Putnam, Leonardi, and Nanetti 1993 ). Shared motivation is, in part, initiated by principled engagement, and in that sense, it is an intermediate outcome; however, once initiated, shared motivation also reinforces or accelerates the principled engagement process ( Huxham and Vangen 2005 ).

The first element of shared motivation (and the initial outgrowth of principled engagement) is the development of trust , which happens over time as parties work together, get to know each other, and prove to each other that they are reasonable, predictable, and dependable ( Fisher and Brown 1989 ). Trust has been a long-recognized sine qua non of collaboration ( Huxham and Vangen 2005 ; Koppenjan and Klijn 2004 ; Leach and Sabatier 2005 ; Ostrom 1998 ). In networks, for example, trust has been found to be instrumental in reducing transaction costs, improving investments and stability in relations, and stimulating learning, knowledge exchange, and innovation ( Koppenjan and Klijn 2004 ). We conceptualize the mechanism by which trust produces such outcomes as an initial pivotal element within the cycle of shared motivation, that is, trust generates mutual understanding, which in turn generates legitimacy and finally commitment. Trust enables people to go beyond their own personal, institutional, and jurisdictional frames of reference and perspectives toward understanding other peoples’ interests, needs, values, and constraints ( Bardach 1998 ; Ring and Van de Ven 1994 ; Thomson and Perry 2006 ).

This forms the basis of mutual understanding , the second element in shared motivation. At an interpersonal level, trust enables people to see and then appreciate differences in others. It enables people to reveal themselves to others and hence be seen and appreciated by them ( Daniels and Walker 2001 ; Gray 1989 ). Mutual understanding is not “shared understanding” as discussed by Ansell and Gash (2008) where participants agree on a shared set of values or goals; rather, mutual understanding specifically refers to the ability to understand and respect others’ positions and interests even when one might not agree.

Repeated, quality interactions through principled engagement will help foster trust, mutual understanding, internal legitimacy, and shared commitment, thereby generating and sustaining shared motivation.

Once generated, shared motivation will enhance and help sustain principled engagement and vice versa in a “virtuous cycle.”

Capacity for Joint Action

The purpose of collaboration is to generate desired outcomes together that could not be accomplished separately. As Himmelman (1994) describes it, collaboration is engaging in cooperative activities to enhance the capacity of both self and others to achieve a common purpose. Thus, the CGR must generate a new capacity for joint action that did not exist before and sustain or grow that capacity for the duration of the shared purpose. The necessary capacity building is specified during principled engagement, derived from the participants’ explicit or tacit theory of action needed to accomplish their collaborative purpose, and likely to be influenced by the scope and scale of the group's objectives and activities. This new capacity is also the basis for group empowerment, which is frequently discussed as a democratic principle underlying collaboration (e.g., Leach 2006 ).

Borrowing from Saint-Onge and Armstrong's (2004, 17) definition of capabilities for conductive organizations, we view the capacity for joint action as “a collection of cross-functional elements that come together to create the potential for taking effective action” and serve “as the link between strategy and performance” (2004, 19). In our framework, capacity for joint action is conceptualized as the combination of four necessary elements: procedural and institutional arrangements, leadership, knowledge, and resources. All the collaborative frameworks we studied recognize the importance of formal and informal rules and protocols, institutional design, and other structural dimensions to on-going collaboration. Most also identify leadership as an important element. The levels of these elements must be sufficient enough to accomplish agreed upon goals. Moreover, capacity for joint action can be viewed as an intermediate outcome of the interacting cycles of principled engagement and shared motivation. However, as joint capacity develops, it can also strengthen or improve the engagement and shared motivation cycles, and in synergy, assure more effective actions and impacts. One or more of the elements of capacity for joint action may be offered upfront as an inducement to collaboration by the initiating leader and/or be developed over time through the interaction of principled engagement and shared motivation.

Procedural and institutional arrangements encompass the range of process protocols and organizational structures necessary to manage repeated interactions over time. The conflict resolution literature indentifies dimensions such as agreements to mediate ground rules, operating protocols, decision rules, and so forth, but these are insufficient for longer term collaborations where informal norms must be supplemented with more formal institutional design factors such as charters, by-laws, rules, and regulations. In other words, larger, more complex, and long-lived collaborative networks require more explicit structures and protocols for the administration and management of work ( Milward and Provan 2000 , 2006 ).

These procedural and institutional arrangements must be defined at both the intraorganizational level (i.e., how a single group or organization will govern and manage itself in the collaborative initiative) and at the interorganizational level (i.e., how the groups of organizations will govern and manage together in the CGR and integrate with external decision making authorities). In general, the internal authority structure of collaborative institutions tends to be less hierarchical and stable, and more complex and fluid, than those found in traditional bureaucracies ( Bryson, Crosby, and Stone 2006 ; Huxham and Vangen 2005 ). Such structures and protocols may vary by function, for example, taking on the shape of informational, developmental, outreach, or action networks ( Agranoff and McGuire 2003 ), and by form, for example, being administered as a self-managing system, by a designated lead agency or agencies, or with the creation of a new governmental structure ( Milward and Provan 2006 ).

The protocols that govern collaborative endeavors may be informal “norms of reciprocity” and/or more formal rules of network interactions ( Thomson and Perry 2006 ). They may also distinguish interaction rules from arena rules in networks ( Koppenjan and Klijn 2004 ). The common pool resource literature has contributed greatly to our understanding of the importance of rules, including constitutional rules, laying out the basic scope and authorities for joint effort, decision making rules, and operating procedures ( Bingham 2009 ; Ostrom 1990 ).

The second element in capacity for joint action is leadership . The importance of leadership in collaborative governance is widely confirmed ( Ansell and Gash 2008 ; Bingham and O'Leary 2008 ; Carlson 2007 ; Saint-Onge and Armstrong 2004 ; Susskind and Cruikshank 1987 ). Leadership can be an external driver (as we posited earlier), an essential ingredient of collaborative governance itself, and a significant outgrowth of collaboration. Moreover, collaborative governance demands and cultivates multiple opportunities and roles for leadership ( Agranoff and McGuire 2003 ; Bryson, Crosby, and Stone 2006 ). These include the leadership roles of sponsor, convener, facilitator/mediator, representative of an organization or constituency, science translator, technologist, and public advocate, among others. Certain leadership roles are essential at the outset, others more critical during moments of deliberation or conflict, and still others in championing the collaborative determinations through to implementation ( Agranoff 2006 ; Bryson, Crosby, and Stone 2006 ; Carlson 2007 ).

Knowledge is the third element in the capacity for joint action. In many ways, it is the currency of collaboration. It is knowledge, once guarded, that is shared with others; knowledge jointly needed that is generated together. It is contested knowledge that requires full consideration; and incomplete knowledge that must be balanced and enhanced with new knowledge. In essence, collaboration requires the aggregation, separation, and reassembly of data and information, as well as the generation of new, shared knowledge. “Knowledge is information combined with understanding and capability: it lives in the minds of people … Knowledge guides action, whereas information and data can merely inform or confuse” ( Groff and Jones 2003 ). Called part of the assets of human capital by Agranoff (2008, 165) , the term “knowledge” in this framework refers to the social capital of shared knowledge that has been weighed, processed, and integrated with the values and judgments of all participants.

Ansell and Gash (2008, 544) note, “As knowledge becomes increasingly specialized and distributed and as institutional infrastructures become more complex and interdependent, the demand for collaboration increases.” Scholars seem to agree, and several have studied and written explicitly about the importance of knowledge management to collaboration across networks (e.g., Agranoff 2007 , 2008 ; Cross and Parker 2004 ). For Saint-Onge and Armstrong (2004) , the ability to transmit high-quality knowledge effectively within and across organizations is the essence of “conductivity” in high-performance organizations and networks. Knowledge is also the central element in adaptive resource management models, where conditions of scientific or resource uncertainty lead parties to cooperate in management experiments to test and build knowledge for better and more enduring management practices ( Holling 1978 ).

Principled engagement and shared motivation will stimulate the development of institutional arrangements, leadership, knowledge, and resources, thereby generating and sustaining capacity for joint action.

The necessary levels for the four elements of capacity for joint action are determined by the CGR's purpose, shared theory of action, and targeted outcomes.

The quality and extent of collaborative dynamics depends on the productive and self-reinforcing interactions among principled engagement, shared motivation, and the capacity for joint action.

Collaborative Actions

Collaborative governance is “generally initiated with an instrumental purpose in mind” ( Huxham et al. 2000, 340 ), that is, to propel actions that “could not have been attained by any of the organizations acting alone” ( Huxham 2003 , 403; see also Agranoff and McGuire 2003 ; Bingham and O'Leary 2008 ). Collaborative actions should be at the heart of any collaborative governance framework, but they have received limited attention and are often left unspecified ( Thomas and Koontz, 2011 ). When addressed, collaborative action is usually seen as the major outcome of a linear process and is sometimes conflated with impacts. However, “Processes and outcomes cannot be neatly separated in consensus building [and CGRs] because the process matters in and of itself and because the process and outcome are likely to be tied together” ( Innes and Booher 1999, 415 ).

Nevertheless, effective CGRs should provide new mechanisms for collective action (e.g., Donahue 2004 ) determined by collaboration partners in accordance with their expressed or implied theory of action for accomplishing their preferred outcomes. Depending on the context and charge of the CGR, such actions may include, for example, securing endorsements, educating constituents or the public, enacting policy measures (new laws or regulations), marshalling external resources, deploying staff, siting and permitting facilities, building or cleaning up, carrying out new management practices, monitoring implementation, and enforcing compliance. Some CGRs have very broad aims (e.g., taking actions related to strategic development or within a particular policy issue or area), whereas others have narrower goals (e.g., taking action on a particular project or gathering and analyzing specific information) ( Huxham et al. 2000 ). Collaborative actions may be conducted in concert by all the partners or their agents, by individual partners carrying out tasks agreed on through the CGR or by external entities responding to recommendations or directions from the CGR.

The appropriateness of the actions should be viewed in light of the CGR's shared theory of action and understood within the system context, where such actions by individual people or organizations would not otherwise be taken. Collaborative action will be difficult to accomplish, much less assess, if shared goals and an operating rationale for taking action are not made explicit. “Common wisdom” implies “that it is necessary to be clear about the aims of joint working if partners are to work together to operationalize policies … . The common practice, however, appears to be that the variety of organizational and individual agendas that are present in collaborative situations make it difficult to agree on aims in practice” ( Huxham 2003, 404 ).

Collaborative actions are more likely to be implemented if 1) a shared theory of action is identified explicitly among the collaboration partners and 2) the collaborative dynamics function to generate the needed capacity for joint action.

The impacts derived from CGRs have also been challenging to operationalize, in part because of the confusion in the literature about the impacts, effects, outputs, and/or outcomes of collaboration ( Thomas and Koontz, 2011 ). For example, Innes and Booher (1999) refer to a range of direct and indirect impacts as first-, second-, and third-order effects that may emerge from a collaborative initiative. Similarly, Lubell, Leach, and Sabatier (2009) refer to different kinds of first-order, second-order, and third-order outputs. Problematically, these constructions of impacts/effects/outputs tend to conflate collaborative dynamics with the overall CGR and its outcomes. For the theory and practice of collaborative governance to develop, we need to generate better conceptual clarity about impacts.

The impacts resulting from collaborative action are likely to be closer to the targeted outcomes with fewer unintended negative consequences when they are specified and derived from a shared theory of action during collaborative dynamics.

Collaborative governance is frequently advocated because of its potential to transform the context of a complex situation or issue. Indeed, one of the “most important consequences [of collaborative governance] may be to change the direction of a complex, uncertain, evolving situation, and to help move a community toward higher levels of social and environmental importance” ( Innes and Booher 1999, 413 ). In our framework, we identify such potential transformative change as adaptation to impacts fostered by CGRs. For example, based on the impacts of collaborative action, problems are solved (or not), new research findings confirm selected management practices (or do not), and different sets of challenges or opportunities arise. Each of these may alter the general system context.

We also propose in our framework the potential for adaptation in the CGR itself. This may occur indirectly as a result of changes in the system context (e.g., thus changing the drivers to collaboration) or directly in response to the perceived effectiveness of actions and impacts (e.g., leading to a new charge or mandate, the addition of new stakeholders, a new round of knowledge generation or resource leverage, or the decision to disband the collaboration). Innes and Booher (1999) classify many of these adaptations as third-order effects.

CGRs will be more sustainable over time when they adapt to the nature and level of impacts resulting from their joint actions.

A review of the integrative framework for collaborative governance and the resulting propositions is in order. These propositions are a first cut at describing the causal mechanisms that link the components and elements of the nested dimensions in the framework; they are presented as preliminary working assumptions in need of future testing and validation.

We assert that collaborative governance unfolds within a system context that consists of a host of political, legal, socioeconomic, environmental, and other influences. This system context creates opportunities and constraints, and influences the dynamics and performance of collaboration at the outset and over time. Emerging from this system context are drivers , including leadership, consequential incentives, interdependence, and uncertainty. These drivers generate the energy for the initiation of a CGR and set its initial direction. We propose that one or more of these four drivers must be present to start a CGR and that the presence of more drivers increases the likelihood that such a regime will be initiated (Proposition 1).

Once a CGR has been initiated, collaborative dynamics and its three components are set in motion. The first component, principled engagement , encompasses the interaction of four basic process elements: discovery, definition, deliberation, and determination. We posit that the principled engagement is generated and sustained by these four elements and that quality and effectiveness of principled engagement will depend on the nature of the interaction among these four elements over time (Proposition 2). The second component, shared motivation , also consists of four elements: trust, mutual understanding, internal legitimacy, and shared commitment. We posit that principled engagement fosters these four elements, thus generating and sustaining shared motivation (Proposition 3). Moreover, we argue that once generated, shared motivation will further enhance and sustain principled engagement and vice versa in a “virtuous cycle” (Proposition 4). The third component of collaborative dynamics is the generation of capacity for joint action , which is also a function of four elements: procedural and institutional arrangements, leadership, knowledge, and resources. We posit that principled engagement and shared motivation assist with the development of these elements, thus generating and sustaining capacity for joint action (Proposition 5). Moreover, we suggest that the necessary levels of each element will vary based on the CGR's purpose, shared theory of action, and targeted outcomes (Proposition 6). Finally, with regard to collaborative dynamics, our summative proposition asserts that the quality and extent of these dynamics depends on the nature of the self-reinforcing interactions among principled engagement, shared motivation, and the capacity for joint action (Proposition 7).

The components of collaborative dynamics (principled engagement, shared motivation, and capacity for joint action) interact over time synergistically and propel collaborative action by the CGR. We posit that collaborative actions are more likely to be implemented if they are in line with an articulated shared theory of action and supported by the necessary capacity for joint action (Proposition 8). We also propose that the resulting impacts from collaborative action are likely to be closer to those intended and targeted by the regime with fewer unintended negative consequences if they have been specified in a shared theory of action developed through collaborative dynamics (Proposition 9). Finally, the potential for adaptation exists both within the system context and the CGR itself. We suggest that CGRs will be more sustainable over time when they adapt to the nature and level of impacts resulting from their joint actions (Proposition 10).

We recognize that this integrative framework covers a lot of ground. It incorporates concepts from a wide range of literature and broadens the scope of collaborative governance beyond previous constructs. The framework identifies several general sets of variables (i.e., dimensions, components, and elements), as well as the relationships among those variables, that will be of interest to scholars and practitioners of collaborative governance. In addition, derived from the framework are several propositions that both integrate existing theory and seek to build new theory about how the variables of collaborative governance interact to shape events and outcomes. Although the breadth of the framework is a strength, it also makes it difficult to adequately describe within the bounds of this article. By developing a framework that encompasses the context, drivers, engagement processes, motivational attributes, and joint capacities that enable shared decision making, management, implementation, and other activities across organizations, jurisdictions, and sectors, we have limited the space available to cover in depth the elements of each component and develop the full suite of causal pathways proposed.

Nevertheless, the framework itself improves upon existing frameworks for collaborative governance in several ways. First, it examines collaborative governance broadly and treats it as an emergent system, a new kind of regime for cross-boundary governance. In doing so, it encompasses a wider range of collaborative initiatives than other definitions and extends beyond the typical focus on the public sector and the public manager to include the myriad of collaboratives initiated in the public, private, and civic sectors. Second, the framework specifies the components of the CGR in a way that integrates a range of factors identified in research into an operational system and suggests some general and very specific causal linkages. Although several frameworks acknowledge the iterative and dynamic nature of collaboration, this framework more explicitly builds that vibrant nature into its construction. Third, the framework also situates the CGR in the broader context with which it interacts. The regime is influenced by surrounding conditions and initiated by specific drivers, and the regime produces impacts affecting those surrounding conditions, as well as the regime itself and its collaborative dynamics. Finally, the framework goes beyond others in distinguishing actions from impacts and tracing the potential for adaptation of the system context and the CGR itself.

The framework also provides a wealth of opportunities for future empirical research. At the most basic level, the generic nature of the framework should enable comparative analyses of CGRs across different system contexts and policy arenas. The depth of the framework, from the dimensions to individual elements, lends itself to thick description in individual or comparative case studies. The breadth of the framework enables efforts to gather more consistent data on a range of indicators from a large set of cases to test the propositions or specific hypotheses relating to the components, their elements, and their interactions.

More specifically, there are numerous research opportunities at the framework, theory, and model levels articulated by Ostrom (2005) . First, the framework itself would benefit from critical applications to cases and examples of collaborative governance. It would be useful to closely examine the components and their interrelationships to describe their strengths and weaknesses, limits of applicability, areas where we have the most and least empirical evidence, and the potential role of various disciplines in contributing to pieces of the framework. Doing so could help identify the pieces of the framework that have the most empirical or practical support, as opposed to the pieces that are, at this point, more speculative. In turn, such research could help confirm or adjust the more speculative pieces. Moreover, we believe that the integrative framework can be applied usefully at different scales, in diverse policy arenas, and various levels of complexity. Future research can examine these assumptions, for example, by exploring how certain pieces of the framework apply in different settings such as community policing, environmental issues, or social services. Typologies of different kinds of CGRs can be envisioned, which in turn can generate future empirical analyses of the framework overall or of the interactions among different components and elements.

Second, several theory testing possibilities exist. The propositions derived from the framework begin to build a general predictive theory for collaborative governance through an instrumental systems approach, as opposed to a prescriptive theory based on normative assumptions. As noted before, these working assumptions need to be tested and validated or revised. Moreover, although the framework encompasses many interactive components and elements, we do not mean to suggest that all are necessary all the time or at the same level of quality or to the same extent. Additional research is needed to discover which relationships matter in what contexts, that is, researchers need to identify where, when, and why which components are necessary, and to what degree, for collaborative success. For instance, in studying the four specified drivers, one might test which are most important. Our preliminary thought on this is that leadership is an essential driver, without which collaborative regimes would not be initiated. However, without at least one or some combination of the other drivers (consequential incentives, interdependence, and/or uncertainty), a CGR is unlikely to continue. Likewise, scholars could examine which element or elements in each of the components of collaborative dynamics (principled engagement, shared motivation, and capacity for joint action) are essential for collaborative success. In a similar research direction, some of the coauthors are currently working on the relationship between collaborative capacity and adaptation, addressing how collaborative capacity might generate specific adaptive capacity and enhance adaptive action in CGRs addressing natural resource issues.

More work is also needed to identify and explain the causal mechanisms that drive collaborative initiatives. Future research will be helpful in clarifying how the different components and elements in the framework emerge and how they relate to one another. For example, the drivers identified in the framework explain why collaboration might emerge but do not yet explain how specific drivers might affect the nature of the CGR differently or if and how the drivers continue to sustain the CGR as it evolves over time. Likewise, future research can explore the critical factors that influence the sustainability of CGRs. For example, one might examine what many have proposed in the literature that small initial successes (low hanging fruit) are essential to keep a CGR going in the its early stages (or that such successes are not sufficient in the long run). This would require defining different levels of success (e.g., initial development of joint capacity for action, different kinds of actions, actions plus impacts, and so forth), as well as tracking the longevity of the CGR, holding other components and elements constant.

Finally, researchers can develop and test specific models and hypotheses relating to the components, their elements, and their interactions. For example, table 1 suggests a way in which to view the integrative framework as a logic model that can be used to test intermediate outputs (actions) and end outcomes (impacts and adaptation) and become the basis for case evaluation and performance evaluation for program management ( Thomas and Koontz, 2011 ). Similarly, other multilevel modeling methodologies may be employed to test more rigorously the contributions of several interrelated factors to specified outcomes ( Arnold 1992 ; Emerson et al. 2009 ; O'Connell and McCoach 2004 ). For such evaluation to begin, however, additional research is needed to operationalize the components and elements so that they can be tested. Work to develop indicators and measures for the dimensions, components, and elements in the integrative framework is currently underway.

In terms of practice, the framework offers public managers and collaboration and conflict resolution practitioners a conceptual map by which to navigate the various dimensions, components, and elements of collaborative governance. The set of drivers provide useful considerations for deciding whether and when to invest in a CGR. Making the collaborative dynamics dimension explicit with participants at the outset can assist with the codesign of the most effective and appropriate CGR. Drawing attention to the elements within principled engagement, shared motivation, and the capacity for joint action can stimulate a shared perspective on needed strategic directions and on progress made to date. Working to articulate the targeted outcomes and coproduce a shared theory of action to affect those outcomes and the criteria by which to assess effective outcomes can enable participants to sharpen their sights and their pencils. Finally, understanding that a CGR is likely, if not expected, to adapt over time further enables the development of innovative learning systems for government and reflective practice ( Argyris and Schon 1974 ; Schon 1971 ).

There can be little argument that the notion of collaborative governance is attracting considerable attention as a new paradigm in public administration. It is the subject of a growing number of books, articles, and monographs. It is seen by many as the new way of doing the business of government. Despite the popularity of the term in research, and claims of its wide-spread use in practice, the study of collaborative governance continues to suffer from a lack of conceptual clarity and consistency. In this article, we have sought to address this by developing an integrative framework that we hope will engender improvements in the theory, research, evaluation, and practice of collaborative governance.

Morris K. and Stewart L. Udall Foundation; Syracuse University; the State University of New York—College of Environmental Science and Forestry.

The authors would like to express sincere gratitude for the detailed comments and suggestions received from the anonymous reviewers. The quality of their reviews was remarkable and significantly improved the quality of this work. Special thanks to Olivier Barreteau, Charles Curtin, Neda Farahbakhshazad, Peter Murchie, and Marilyn Tenbrink for their formative comments on the framework and to Christine Carlson, Andrea Gerlak, and Rosemary O'Leary for their initial review of this article. We are also indebted to those who provided feedback on earlier presentations of the framework at the Udall Center for Studies in Public Policy at The University of Arizona and at the Collaborative Governance and Climate Change Conference in June 2009 sponsored by the Association for Conflict Resolution's Environment and Public Policy Section.

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For example, Selin and Chavez (1995) focus on environmental planning and management generally, whereas Bentrup (2001) focuses specifically on watershed planning. Koppenjan and Klijn (2004) study problem solving and decision making in networks, whereas Ring and Van de Ven (1994) examine business transactions. Moreover, the frameworks vary by the nature of the conceptual problem addressed. For example, Thomson and Perry (2006) focus on the processes of interorganizational partnerships, whereas Cooper, Bryer and Meek (2006) examine dynamics of engaging stakeholders and the public in community planning.

For example, the conflict resolution research often focuses on short time frames for reaching explicit agreements, thus missing the longer term implementation challenges or institutional dimensions ( Emerson et al. 2009 ). The intergovernmental and network management analyses tend to be focused on delivery of public services, often at local scales ( Agranoff and McGuire 2001 ; Milward and Provan 2000). As noted above, Ansell and Gash (2007) emphasize government-initiated processes with nongovernmental stakeholders.

This discussion is based on Ostrom's (2005) distinctions among frameworks, theories, and models. Frameworks specify general sets of variables (and the relationships among the variables) that are of interest to a researcher. Theories are more specific and provide an interpretive structure for frameworks. Theories enable the researcher to make working assumptions about how the variables in a framework interact, for example, to explain why events occur or to make predictions about relationships or phenomena. Finally, models are even more specific than theories and allow researchers to make precise assumptions about a limited set of variables, for example, to test hypotheses and predict outcomes.

For example, in the absence of federal action on climate change issues, state and local governments began developing their own climate change policies. In 2003, then New York Governor George Pataki invited fellow governors in the Northeast to explore the possibility of a regional climate change strategy. The result was the development of the Regional Greenhouse Gas Initiative (RGGI). In this case, the system context in which collaboration unfolded was shaped by local, state, national, and international politics, the lack of federal law and action, environmental concerns, and other issues. In turn, RGGI changed the landscape of the system context by altering political, legal, regulatory, socioeconomic, environmental, and other forces in multiple northeastern states ( Rabe 2010 ).

We have elevated “principled engagement” to the framework level (as opposed to Ostrom's [2005] theory level) because it is a fundamental component within the definition of collaborative governance. Arguably, not all engagement will in fact be principled, that is, the de jure notion of principled engagement may not be what happens in de facto engagement. Nevertheless, the notion of principled engagement is consistent with the general definitions of collaborative governance, as well as our broader definition of collaborative governance. Moreover, the elements of principled engagement in this framework are articulated broadly enough to allow for different theories of engagement to be applied and different models to be tested.

It should be noted that increasing diversity in participation may have undesired consequences as well. In some situations, more diversity can generate higher levels of conflict and erode principled engagement, whereas in other situations, less diversity can lead to different, though not necessarily inferior actions and accomplishments ( Korfmacher 2000 ; Schlager and Blomquist 2008 ; Steelman and Carmin 2002 ).

Changing conditions in the system context and the collaboration itself also occur for reasons other than in response to the impacts of CGRs. This framework is focused, however, on the resulting from regime impacts.

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Theories of Motivation in Education: an Integrative Framework

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• Volume 35 , article number  45 , ( 2023 )

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Several major theories have been established in research on motivation in education to describe, explain, and predict the direction, initiation, intensity, and persistence of learning behaviors. The most commonly cited theories of academic motivation include expectancy-value theory, social cognitive theory, self-determination theory, interest theory, achievement goal theory, and attribution theory. To gain a deeper understanding of the similarities and differences among these prominent theories, we present an integrative framework based on an action model (Heckhausen & Heckhausen, 2018 ). The basic model is deliberately parsimonious, consisting of six stages of action: the situation, the self, the goal, the action, the outcome, and the consequences. Motivational constructs from each major theory are related to these determinants in the course of action, mainly revealing differences and to a lesser extent commonalities. In the integrative model, learning outcomes represent a typical indicator of goal-directed behavior. Associated recent meta-analyses demonstrate the empirical relationship between the motivational constructs of the six central theories and academic achievement. They provide evidence for the explanatory value of each theory for students’ learning.

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Introduction

Motivation is one of the most studied psychological constructs in educational psychology (Koenka, 2020 ). The term is derived from the Latin word “movere,” which means “to move,” as motivation provides the necessary energy to people’s actions (Eccles et al., 1998 ; T. Jansen et al., 2022 ). In the scientific literature, motivation is often defined as “a process in which goal-directed activity is instigated and sustained” (Schunk et al., 2014 , p. 5). Research on academic motivation focuses on explaining why students behave the way they do and how this affects learning and performance (Schunk et al., 2014 ).

Several major theories have been established in research on motivation in education to describe, explain and predict the direction, initiation, intensity, and persistence of learning behaviors (cf. Linnenbrink-Garcia & Patall, 2016 ). Each theory has its own terms and concepts to designate aspects of motivated behavior, contributing to a certain inaccessibility of the field of motivation theories. In addition, motivation researchers create their own terminology, differentiate, and extend existing theoretical conceptions, making it difficult to draw precise boundaries between the models (Murphy & Alexander, 2000 ; Schunk, 2000 ). This leads to the question of whether it would be possible to consider the most important theories of academic motivation against a common background to gain a deeper understanding of the similarities and differences among these prominent theories.

In the past, several researchers have worked to provide an integrative meta-theoretical framework for classifying motivational processes. Hyland’s ( 1988 ) motivational control theory used a system of hierarchically organized control loops to explain the direction and intensity of goal-orientated behavior. Locke ( 1997 ) postulated an integrated model for theories of work motivation, starting from needs, values and personality, and environmental incentives through goal choice and mediating goal and efficacy mechanisms to performance, outcomes, satisfaction, and organizational commitment. Murphy and Alexander ( 2000 ) classified achievement motivation terms into the four domains of goal, interest, intrinsic vs. extrinsic motivation, and self-schema. De Brabander and Martens ( 2014 ) tried to predict a person’s readiness for action primarily from positive and negative, affective and cognitive valences in their unified model of task-specific motivation. Linnenbrink-Garcia and Wormington ( 2019 ) proposed perceived competence, task values, and achievement goals as essential categories to study person-oriented motivation from an integrative perspective. Hattie et al. ( 2020 ) grouped various models of motivation around the essential components of person factors (subdivided into self, social, and cognitive factors), task attributes, goals, perceived costs, and benefits. Finally, Fong ( 2022 ) developed the motivation within changing culturalized contexts model to account for instructional, social, future-oriented, and sociocultural dynamics affecting student motivation in a pandemic context.

In this contribution, we present an integrative framework for theories of motivation in education based on an action model (Heckhausen & Heckhausen, 2018 ). The action model is a further development of an idea by Urhahne ( 2008 ) to classify the most commonly cited theories focusing on academic motivation, including expectancy-value theory, social cognitive theory, self-determination theory, interest theory, achievement goal theory, and attribution theory, into a common frame (Schunk et al., 2014 ). We begin with introducing the basic motivational model and then sort the main concepts and terms of the prominent motivation theories into the action model. Associated recent meta-analyses will illustrate the empirically documented value of each theory in explaining academic achievement.

The Basic Motivational Model

The basic motivational model in Fig. 1 shows the determinants and course of motivated action. The model is grounded on the general model of motivation by Heckhausen and Heckhausen ( 2018 , p. 4) to introduce the universal characteristics of motivated human action. Heckhausen ( 1977 ) had worked early on to organize constructs from different theories into a cognitive model of motivation. The initial model differentiated four types of expectations attached to four different stages in a sequence of events and helped group intrinsic and extrinsic incentive values of an action as well (Heckhausen, 1977 ). Later, Heckhausen and Gollwitzer ( 1987 ) extended the model to the Rubicon model of action phases to define clear boundaries between phases of motivational and volitional mindsets (Achtziger & Gollwitzer, 2018 ; Gollwitzer et al., 1990 ). The four phases of the Rubicon model can be described as follows: In the predecisional phase of motivation, individuals select or set a goal for action on the basis of their wishes and desires. The postdecisional phase of volition is a time of preparation and planning to translate the goal into action. This is followed by the actional phase of volition that involves the actual process of action. Once the action is completed or abandoned, the postactional phase of evaluating the outcome and its consequences has begun (Heckhausen & Heckhausen, 2018 ). Since the Rubicon model depicts the entire action process from an emerging desire to the final evaluation of the action outcome, it provides a broad basis for classifying various current motivational theories.

The basic motivational model

Specifically, our model proposes that motivated behavior arises from the interaction between the person and the environment (Murray, 1938 ). In Fig. 1 , possible incentives such as the prospect of rewards and opportunities of the situation stimulate the motives, needs, wishes, and emotions of a person’s self, which come to life through generating an action goal (Dweck et al., 2003 ; Roeser & Peck, 2009 ). A person’s current goal is translated into an action at a suitable opportunity. The action is carried out, and the action’s outcome indicates whether and to what extent the intended goal has been achieved. The outcome has to be distinguished from the consequences of the action, which may consist of self- and other evaluations, rewards and punishments, achievement emotions, or effects of the outcome on long-term goals (Heckhausen & Heckhausen, 2018 ). The basic model is intentionally parsimonious and somewhat reflects considerations by Hattie et al. ( 2020 ) on integrating theories of motivation that distinguish between self, goals, task (action), and costs and benefits (consequences) as major dimensions of motivation. Similarities also emerge to Locke ( 1997 ), who bases the integrative model of work motivation theories on a comparable action sequence. The specificities of each component of the basic motivational model are now explained in more detail.

The situation represents the social, cultural, and environmental context in which individuals perform motivated actions (Ford, 1992 ). Recently, there has been a trend within motivation research to place greater emphasis on situating motivation (Eccles & Wigfield, 2020 ; Nolen, 2020 ; Nolen et al., 2015 ; Pekrun & Marsh, 2022 ; Wentzel & Skinner, 2022 ). Researchers want to better account for the social and cultural differences between persons (Usher, 2018 ) or take note of the embeddedness of individuals in multiple contexts (Nolen et al., 2015 ). The basic motivational model includes these extensions of current motivation theories and refers to the situatedness of motivation. The situation represents the overarching context for the complete action sequence, even though it is depicted in the basic motivational model by only one box. The situation and the person’s self are intimately interwoven, and motivation can be regarded as a result of their interaction (Roeser & Peck, 2009 ). The situation evokes motivational tendencies in the self, and the self contains experiences about the motivation to avoid or master certain situations (King & McInerney, 2014 ).

The self has not played a major role in motivation research for a long time (Weiner, 1990 ). This was partly due to Freud’s psychoanalytic theories, which recognized the id rather than the ego as the motivational driver of behavior. Moreover, behavioristic approaches that characterized motivation and learning as fully controllable from the outside also neglected mental constructs such as the self (McCombs, 1991 ). It was only with the greater prevalence of cognitive and social-cognitive theories that the self found its way back to motivational research (Weiner, 1990 ). The self is now frequently addressed in hypothetical constructs such as self-efficacy (Bandura, 1977 ), self-determination (Deci & Ryan, 1985 ), self-regulation (Bandura, 1988 ), self-theories (Dweck, 1999 ), ego orientation (Nicholls, 1989 ), self-based goals (Elliot et al., 2011 ), self-serving bias (McAllister, 1996 ; Miller & Ross, 1975 ), and identity (Eccles, 2009 ).

In our model, the self is the starting point of motivated action. It enables people to select goals, initiate behaviors, and sustain them until goals are accomplished (Baumeister, 2010 ; McCombs & Marzano, 1990 ; Osborne & Jones, 2011 ). Thus understood, the self is an active agent that translates a person’s basic psychological needs, motives, feelings, values, and beliefs into volitional actions (McCombs, 1991 ; Roeser & Peck, 2009 ). James ( 1999 ) referred to this part of the self as the “I-self,” the thinking and acting person itself, to distinguish it from the “Me-self,” the reflection of oneself through its physical and mental attributes. The “Me-self” is central to constructs such as self-concept, self-worth, or self-esteem (Harter, 1988 ) and remains important in depicting different motivational constructs in the course of action. However, in the basic motivational model, the “I-self” is recognized as the repository of motivational tendencies and the energizer of motivated action (King & McInerney, 2014 ).

This view of the self corresponds with insights from neuroscientific research. In Northoff’s ( 2016 ) basis model of self-specificity, the self, and in particular self-specificity, is viewed as the most fundamental function of the brain. Self-specificity and self-relatedness refers to “the degree to which internal or external stimuli are related to the self” (Hidi et al., 2019 , p. 15) and references the I-self, the self as subject and agent (Christoff et al., 2011 ). Self-specificity involves spontaneous brain activity—the resting state of the brain and independent of specific tasks or stimuli external to the brain—and is viewed as fundamental in influencing basic and higher-order functions, such as perception, the processing of reward, emotion, memory, and decision-making (Hidi et al., 2019 ; Northoff, 2016 ). Furthermore, Sui and Humphreys ( 2015 ) indicated that self-related information processing functions as an “integrative glue” that influences the integration of different stages of processing, such as linking attention to decision-making. Neuroscientific findings, therefore, seem to support the view of the self as the starting point of motivated behavior.

The goal contains the cognitive representation of an action’s anticipated incentives and consequences. Goals are the basis of all motivated behavior (cf. Elliot & Fryer, 2008 ). This view is consistent with Schunk et al. ( 2014 ), who defined motivation as a process to instigate and sustain goal-directed behavior. Cognitive theories on motivation place special emphasis on the goals that people pursue (Elliot & Hulleman, 2017 ). Goals are intentional rather than impulsive, consciously or unconsciously represented, and guide an individual’s behavior. People are not always aware of the various influences on their goals. Sensations, perceptions, thoughts, beliefs, and emotions that affect goal pursuit are potentially experiential, but typically not consciously perceived (Bargh & Gollwitzer, 2023 ; Dweck et al., 2023 ). Goals are closely related to the person’s self. In line with Dweck et al. ( 2003 , p. 239), we assume that “contents of the self—self-defining beliefs and values—come to life through people’s goals.”

The action is carried out to either approach or avoid an anticipatory goal state (Beckmann & Heckhausen, 2018 ). Thus, motivated behavior can be directed to either approach a positive event or avoid a negative one (Elliot & Covington, 2001 ). An action can be brief or extended over a longer period. If an action goal is considered unattainable, it is devalued, and the action is directed toward other more attractive goals (Heckhausen & Heckhausen, 2018 ). The action may or may not be visible to an observer. Thus, to act is to engage in any form of noticeable or indiscernible behavior, especially cognitive behavior, to reach a desired or avoid an undesired goal state.

The outcome is any physical, affective, or social result of an individual’s behavior. The action outcome is an important indicator of mastering a standard of excellence (Heckhausen, 1991 ). It is often accompanied by intrinsic valences such as feelings of self-worth, self-actualization, or appropriate accomplishment (Mitchell & Albright, 1972 ).

The consequences of an action are far more varied than the mere outcome. Vroom’s ( 1964 ) instrumentality theory considered the outcome of an action as instrumental for reaching subsequent consequences. Vroom ( 1964 ) suggested that the valence of an outcome depends on the valence of the consequences. For example, the value of school grades should depend on how the students themselves, classmates, and parents evaluate the grades achieved, what rewards, punishments, and achievement emotions are associated with the school grades, and whether the grades help achieve long-term goals such as moving up to the next grade level. The consequences of an action are often accompanied by extrinsic valences such as authority, prestige, security, promotion, or recognition (Mitchell & Albright, 1972 ).

In addition, the manifold consequences of an action affect the design of future situations and the goals that can be pursued within these situations. New possibilities to act open up and novel incentives of the situation start to interact with the self. A new action sequence, as shown in Fig. 1 , has begun.

In the following sections, we will use the action model to explain and classify six central motivation theories. Motivated action in the educational context serves to attain academic achievement, and we will make use of meta-analyses to underline what is currently known about the predictive strength of the major theoretical models. Academic achievement is certainly not the only reportable variable related to motivation. However, this visible evidence of learning is an appropriate indicator to convince individuals of the theory’s nature and value (Hattie, 2009 ). The role of affective factors in the action model is explained in more detail in the discussion.

Expectancy-Value Theory

Grounded on the research by Tolman ( 1932 ) and Lewin ( 1951 ), expectancy-value theories depict motivation as the result of the feasibility and desirability of an anticipated action (Achtziger & Gollwitzer, 2018 ; Schnettler et al., 2020 ). The expectancy is usually triggered by the incentives of the situation and expresses the subjective probability of the feasibility of the current action (Atkinson, 1957 ). The value indicates the desirability of an action which is determined by the incentives of the situation and the anticipated consequences of the action. In Atkinson’s ( 1957 ) achievement motivation theory, expectancy and value were assumed to be inversely related. The greater the desirability, the more difficult the feasibility of an action and vice versa. Thus, knowing the subjective probability of success was regarded as sufficient to determine the incentive value of a task. However, it turned out that the assumption of a negative correlation between expectancy and value was not tenable (Wigfield & Eccles, 1992 ). In a more modern view, expectancy and value beliefs are assumed to jointly predict achievement-related choices and performance (Eccles et al., 1983 ; Trautwein et al., 2012 ).

Situated expectancy-value theory (Eccles & Wigfield, 2020 ; Wigfield & Eccles, 2000 ) is a modern theoretical framework for explaining and predicting achievement-related choices and behavior. Expectancy of success and subjective task values are regarded as proximal explanatory factors determined by a person’s goals and self-schemas. These, in turn, are shaped by the individual’s perception and interpretation of their developmental history and sociocultural background. Eccles and Wigfield ( 2020 ) refer to their theory as situated to highlight the importance of the underlying influences on currently held expectancy and value beliefs.

The expectancy component in the situated model (Eccles & Wigfield, 2020 ) is called expectation of success (Atkinson, 1957 ; Tolman, 1932 ). It represents individuals’ belief about how well they will do on an upcoming task, targeting the anticipated outcome of an action. The expectancy component of Eccles’ motivation theory shows some similarity to self-concept of ability and self-efficacy (Bandura, 1977 ; Harter, 2015 ; Schunk & DiBenedetto, 2016 ; Schunk & Pajares, 2009 ). However, the expectation of success does not focus on the present ability (Bong & Skaalvik, 2003 ) but the future (Wigfield & Eccles, 2000 ), and it targets the perceived chances of success rather than the perceived probability of performing an action which may lead to success (Bandura, 1977 ; Muenks et al., 2018 ).

The value component of the situated model is divided into three types of value beliefs and three types of costs that contribute to approaching or avoiding certain tasks (Eccles & Wigfield, 2020 ). The three value beliefs are attainment value, intrinsic value, and utility value. The three types of costs are named opportunity costs, effort costs, and emotional costs (cf. Flake et al., 2015 ; Jiang et al., 2018 ).

Attainment value represents the importance of doing well on a task (Eccles & Wigfield, 2020 ). This belief is strongly associated with the person’s self, as aspects of one’s identity are touched upon during performing an important task (Wigfield et al., 2016 ). Intrinsic value is the enjoyment a person gets from doing a task. Intrinsic value is considered a counterpart to intrinsic motivation in self-determination theory (Ryan & Deci, 2009 ) and interest in person-object theory (Krapp, 1999 ). However, enjoyment and interest should not be viewed as synonyms, making differentiations necessary (Ainley & Hidi, 2014 ; Reeve, 1989 ). Utility value is derived from the meaning of a task in achieving current and future goals (Wigfield et al., 2006 ). Accomplishing the task is only a means to an end; therefore, utility value can be considered a form of extrinsic motivation. Utility value is derived from the meaning of a task in achieving current and future goals (Wigfield et al., 2006 ) in social, educational, professional, or everyday contexts (Gaspard et al., 2015 ).

Opportunity costs arise because the time invested in a task is no longer available for other valued activities. Especially in the case of learning, conflicts with other interests threaten learners’ self-regulation, and opportunity costs can be high (Grund & Fries, 2012 ). Effort costs address the perceived effort in pursuing a task and whether it is worthwhile to finish the task at hand (Eccles, 2005 ). Emotional costs include the perceived affective consequences of participating in an academic activity, such as fear of failure or other negative emotional states (Eccles & Wigfield, 2020 ; Wigfield et al., 2017 ).

Central constructs of the situated expectancy-value framework (Eccles & Wigfield, 2020 ) can be placed within the basic motivational model (see Fig. 2 ). Expectation of success, a person’s subjective estimate of the chances of obtaining a particular outcome, can be represented as a directed link between self and outcome. The expectation of achieving a future outcome with a certain probability is formed in the self and is directed on the desired outcome of the prospective action. This view of expectancy of success is consistent with Skinner’s ( 1996 ) classification of agent-ends relations as individuals’ beliefs about how well they will do on an upcoming task.

Integrating situated expectancy-value theory into the basic motivational model

Figure 2 further shows that the three task values are linked to different processes in the action model. The attainment value of a task is related to the personal significance of the outcome (Eccles & Wigfield, 2020 ). The higher the relative personal importance of the outcome, the higher the attainment value. More recent analyses show that the attainment value can be divided and measured as the importance of achievement and personal importance related to one’s identity (Gaspard et al., 2015 , 2018 , 2020 ). The self, however, is not the valued object but the importance of accomplishing a task to an individual’s identity (Perez et al., 2014 ). In classifying this construct, we chose to focus more on the importance of the outcome and less on the reference to the self. At this point, however, a different mode of presentation is also conceivable. The intrinsic value of the task is linked to the positive aspects of the action. The more pleasurable the action, the higher the intrinsic value. Eccles and Wigfield ( 2020 ) conceptualized the intrinsic value as the anticipated enjoyment of doing a particular task as well as the experienced enjoyment when performing the task. The utility value of a task is linked to the consequences. The more positive the anticipated consequences of an action, the higher the perceived usefulness. As a form of extrinsic motivation, the utility value does not result from performing the task, but from the anticipated consequences of an action to fulfill an individual’s present or future plans (Eccles & Wigfield, 2020 ).

The three types of costs also become relevant at different stages in the action process (see Fig. 2 ). Opportunity costs occur when a decision has been made in favor of a certain action. Alternative courses of action are ruled out as soon as a person is committed to a goal (Locke et al., 1988 ). Opportunity costs are consequently linked to the goal of the action. The person’s time and skills, which from now on are put into the pursuit of intentions, are no longer available for other activities (Eccles & Wigfield, 2020 ). Effort costs are tied to the action itself and are based on the anticipated effort of conducting the task. Effort costs rise with the duration and intensity of an action so that the person needs to anticipate whether the desired action is worth the effort required (Eccles & Wigfield, 2020 ). Finally, emotional costs such as anticipated fear of failure or negative emotional states are connected to the anticipated consequences of an action. These costs arise when the action does not go as desired and are therefore considered as the “perceptions of the negative emotional or psychological consequences in pursuing a task” (Rosenzweig et al., 2019 , p. 622).

Eccles’ expectancy-value framework has often been used to investigate and understand gender differences in motivational beliefs, performance, and career choices, especially in science, technology, engineering, and mathematics (Lesperance et al., 2022 ; Parker et al., 2020 ; Wan et al., 2021 ). In contrast, there has been less meta-analytic research as to whether constructs of the expectancy-value model can predict academic achievement. To not preempt other theoretical conceptions, we only report here findings with a clear relation to the Eccles model.

Generally, expectations of success compared to achievement values are stronger predictors of subsequent performance (cf. Wigfield et al., 2017 ). A meta-analysis by Pinquart and Ebeling ( 2020 ) found a moderate association of expectancies for success with both current ( r = .34) and future academic achievement ( r = .41). Conversely, however, past academic performance could also predict expectancies for success ( r = .35). Credé and Phillips ( 2011 ) reported small relationships for a combination of the three task values with GPA ( r = .12) and grades ( r = .17). The relations in meta-analyses were somewhat higher when individual task values were examined. Camacho-Morles et al. ( 2021 ) found an association of r = .27 between activity-related enjoyment represented in the intrinsic value and academic performance. Barroso et al. ( 2021 ) reported a meta-analytic relationship of r = − .28 between math anxiety, as a form of emotional costs, and mathematics achievement.

Social Cognitive Theory

Within the frame of social cognitive theory, Bandura ( 1977 , 1986 , 1997 ) extended the expectancy concept from achievement motivation theory (Atkinson, 1957 ). Expectancy of success, the subjective probability of attaining a particular outcome, was differentiated by means of two beliefs (Schunk & Zimmerman, 2006 ; Usher, 2016 ). Competence beliefs take effect when learners consider means and processes to accomplish certain tasks (Skinner, 1996 ). Control beliefs signify the perceived extent to which the chosen means and processes lead to the desired outcomes (Schunk & Zimmerman, 2006 ).

For competence beliefs, Bandura ( 1977 ) coined the term self-efficacy to express expectations about one’s capabilities to organize and execute courses of action to produce specific outcomes (Bandura, 1997 ; Schunk & Zimmerman, 2006 ). The belief in self-efficacy is regarded as an essential condition to initiate actions leading to academic success (Klassen & Usher, 2010 ). For control beliefs, Bandura ( 1977 ) used the term outcome expectations to express the perceived relations between possible actions and anticipated outcomes. While expectancy of success sometimes involves competence beliefs, sometimes control beliefs, and sometimes both (Schunk & Zimmerman, 2006 ), Bandura’s construct of self-efficacy has contributed to a necessary differentiation in the course of action and can be viewed as a central variable in research on motivation in education (Schunk & DiBenedetto, 2016 ).

Social cognitive theory is much broader than self-efficacy and outcome expectations and assumes a system of interacting personal, behavioral, and environmental factors (Schunk & diBenedetto, 2021 ). The idea that human agency is neither completely autonomous nor completely mechanical, but is subject to reciprocal determinism, plays a decisive role (Linnenbrink-Garcia & Patall, 2016 ). Thus, personal factors such as perceived self-efficacy enable individuals to initiate and sustain behaviors that translate to effects on the environment. Thoughtful reflection on those actions and their impact feeds back to the person and can, in turn, influence their sense of self-efficacy (Bandura, 1989 ).

Figure 3 shows how the key components of social cognitive theory fit into the action model. The upper part of Fig. 3 is devoted to expectations. Self-efficacy expectations arise when the self has the necessary capabilities to organize and execute courses of action. Outcome expectations, in contrast, refer to the assessment of whether the anticipated action will lead to the desired outcome. The presentation of the two expectations is consistent with Skinner’s ( 1996 ) view in which self-efficacy expectations are referred to as agent-means relations and outcome expectations are referred to as means-ends relations. The lower part of Fig. 3 depicts the model of reciprocal interactions consisting of personal, behavioral, and environmental processes (Schunk & DiBenedetto, 2020 ). Personal processes, as described by Schunk and DiBenedetto ( 2020 ) in a publication on motivation and social cognitive theory, are primarily associated with the self and the goal. The self contains information on self-efficacy, values, expectations, attribution patterns and enables social comparison processes. The goal contains standards for self-evaluations of the action’s progress. Behavioral processes such as activity selection, effort, persistence, regulation, and achievement are closely related to action and outcome of the action model. Environmental processes such as acting of social models, providing instructions, or setting standards for action stem, on the one hand, from the situation, where they set the stage for action. Environmental processes are, on the other hand, located in the consequences, where feedback, opportunities for self-evaluation, and rewards indicate an action’s success or failure (Schunk & DiBenedetto, 2020 ). The listing of the individual components that make up the three interacting processes in reciprocal determinism is not always done in the same way. For example, Schunk and DiBenedetto ( 2021 ) referred to self-efficacy, cognitions, and emotions as personal factors; classroom attendance and task completion as behavioral factors; and classroom, teachers, peers, and classroom climate as environmental factors. However, this does not affect the representation of the three main classes of reciprocal determinism in the basic motivational model and opens up space for the classification of different components.

Integrating social cognitive theory into the basic motivational model

Several meta-analyses have shown that self-efficacy is moderately positively related to academic achievement (Multon et al., 1991 ; Robbins et al., 2004 ). Credé and Phillips ( 2011 ) examined several constructs of social cognitive theory based on the Motivated Strategies for Learning Questionnaire (Pintrich & De Groot, 1990 ). Control beliefs showed small positive correlations with college GPA ( r = .12) and current semester grades ( r = .14). However, of all the constructs measured, self-efficacy showed the strongest associations with GPA ( r =. 18) and grades ( r = .30). Further meta-analyses with university students supported the significant but moderate relationship between academic self-efficacy and academic achievement with correlation coefficients of r = .31 (Richardson et al., 2012 ) and r = .33 (Honicke & Broadbent, 2016 ). Sitzmann and Ely ( 2011 ) reported meta-analytic correlations of r = .18 for pre-training self-efficacy and r = .29 for self-efficacy with learning.

To further clarify the direction of the relationship, Sitzmann and Yeo ( 2013 ) conducted an insightful meta-analysis. They were able to show that self-efficacy expectations are more likely to be a product of past performance ( r = .40) than a driver of future performance ( r = .23). Talsma et al. ( 2018 ) supported these findings with a meta-analytic cross-lagged panel study. They found that prior performance exerted a stronger effect on self-efficacy (β = .21) than existing self-efficacy on subsequent performance (β = .07).

Self-Determination Theory

Self-determination theory by Deci and Ryan ( 1985 , 2000 ) is macro-theory for understanding human motivation, personality, and well-being. The theory has its roots in early explorations of the concept of intrinsic motivation (Deci, 1971 , 1975 ; Ryan & Deci, 2019 ). Self-determination is regarded as the basis for explaining intrinsically motivated behavior where the action is experienced as autonomous and does not rely on controls and reinforcers (Deci & Ryan, 1985 ). Self-determination theory provides a counterweight to expectancy-value theory and social cognitive theory, where the external incentives such as expected or real rewards to motivate behavior are still visible.

The overarching framework of self-determination theory encompasses six mini-theories: basic psychological needs theory, cognitive evaluation theory, organismic integration theory, causality orientations theory, goal contents theory, and relationship motivation theory (Ryan & Deci, 2017 ). Each mini-theory explains specific motivational phenomena that have been tested empirically (Reeve, 2012 ; Ryan & Deci, 2017 ; Vansteenkiste et al., 2010 ; see also Ryan et al., in press ). In the following explanations, we focus on the first three sub-theories with the highest popularity.

Basic psychological needs theory argues that humans are intrinsically motivated and experience well-being when their three innate basic psychological needs for autonomy, competence, and relatedness are satisfied (Conesa et al., 2022 ; Deci & Ryan, 1985 , 2000 ; Ryan & Deci, 2000a , 2000b , 2017 , 2020 ; Vansteenkiste et al., 2020 ). Autonomy refers to a sense of ownership and the need for behavior to emanate from the self. Competence concerns a person’s need to succeed, grow, and feel effective in their goal pursuits (Deci & Ryan, 2000 ; White, 1959 ). Finally, relatedness refers to establishing close emotional connections to others and a sense of belonging to significant others such as parents, teachers, or peers.

Cognitive evaluation theory describes how the social environment affects intrinsic motivation (Deci & Ryan, 1985 , 2000 ; Ryan & Deci, 2000b , 2017 , 2020 ). The mini-theory states that cognitive evaluation of external rewards impacts learners’ perception of their intrinsically motivated behavior. Rewards perceived as controlling weaken intrinsic motivation, whereas rewards providing informational feedback can strengthen acting on one’s own initiative (Deci et al., 1999 ).

Organismic integration theory focuses on the development of extrinsic motivation toward more autonomous or self-determined motivation through the process of internalization (Ryan & Deci, 2017 ). The mini-theory proposes a self-determination continuum that ranges from intrinsic motivation to amotivation, with several types of extrinsic motivation in between (Deci & Ryan, 1985 , 2000 ; Ryan & Deci, 2000a , 2000b , 2017 , 2020 ). The results from the meta-analysis by Howard et al. ( 2017 ) largely supported the continuum-like structure of self-determination theory. Intrinsically motivated individuals engage in activities because they are fun or interesting, whereas extrinsic motivation concerns all other reasons for engaging in activities. Four types of extrinsic motivation are distinguished, and two of these types are assumed to be higher in quality than the other two (Deci & Ryan, 2008 ; Ryan & Deci, 2000b ).

Integrated and identified regulations are considered high-quality autonomous, extrinsic motivation types characterized by volitional engagement in activities. Integrated regulation is the most autonomous form of extrinsic motivation. People with integrated regulation recognize and identify with the activity’s value and find it congruent with their core values and interests (e.g., attending school because it is part of who you are; see Ryan & Deci, 2020 ). In identified regulation, people identify with or personally endorse the value of the activity (e.g., doing schoolwork to learn something from it) and, therefore, experience high degrees of volition.

The other two types of extrinsic motivation are forms of controlled motivation (Deci & Ryan, 2008 ; Ryan & Deci, 2000a , 2000b ). Introjected regulation concerns partially internalized extrinsic motivation; people’s behavior is regulated by an internal pressure to feel pride or self-esteem or to avoid feelings of anxiety, shame, or guilt. Extrinsic regulation refers to behavior regulated by externally imposed rewards and punishments, such as demands from parents or teachers.

The action model in Fig. 4 shows how core concepts of the self-determination theory fit into the course of action. The three basic psychological needs for autonomy, competence, and social relatedness are an integral part of the self (Connell & Wellborn, 1991 ). Ryan and Deci ( 2019 ) regarded the self as responsible for assimilating and aligning a person’s internal needs, drives, and emotions to the external determinants of the sociocultural situation. Intrinsic motivation is part of the action when the activity itself is experienced as exciting, interesting, or intrinsically satisfying. On the other hand, extrinsic motivation is tied to an action’s consequences, as externally motivated learners seek pleasant consequences and try to avoid unpleasant ones.

Integrating self-determination theory into the basic motivational model

Forms of extrinsic motivation of the organismic integration theory can be distinguished according to the extent to which the action is integrated into the self. The more internalized the motivation, the more it becomes part of a learner’s identity (Ryan & Deci, 2020 ). In external regulation, there is no involvement of the self, as the person’s actions are entirely determined by the incentives of the situation and the action’s consequences (see Fig. 4 ). In introjected regulation, there is already some ego involvement: The self becomes involved with the consequences of one’s action to experience approval from oneself or others (Ryan & Deci, 2000a ). In identified regulation, the individual starts to value an activity consciously, and the self connects with the action. In integrated regulation, a congruence is established between the self and the self-initiated action (Ryan & Deci, 2000a ). Values and needs of the self are in balance with the autonomous and unconflicted action (see Fig. 4 ). As seen in Fig. 4 , identified and integrated regulation share overlap. In line with this presentation, the meta-analysis by Howard et al. ( 2017 ) showed that integrated regulation was hard to distinguish from intrinsic and identified regulation and called for a revision of the theory by either excluding integrated regulation or finding new ways to operationalize and conceptualize the hypothetical construct.

In line with basic psychological needs theory, the Bureau et al. ( 2022 ) meta-analysis confirmed that the satisfaction of basic psychological needs is positively associated with autonomous forms of motivation. Relative weight analysis showed that the need for competence most strongly predicted intrinsic and identified motivation, followed by the needs for autonomy and social relatedness.

Several meta-analyses investigated the association between the different motivation types and academic achievement, and some of these meta-analyses only reported the association between intrinsic motivation and school performance. For example, Cerasoli et al. ( 2014 ) reported a meta-analytic correlation between intrinsic motivation and school performance of ρ = .26, whereas Richardson et al. ( 2012 ) reported a small positive correlation of r = .17 with the GPA at college or university.

Taylor et al. ( 2014 ) and Howard et al. ( 2021 ) investigated the meta-analytic correlations of the different types of motivation with school performance. Concerning the autonomous motivation types, Taylor et al. ( 2014 ) reported positive associations of intrinsic motivation ( d = .27) and identified regulation ( d = .35) with school achievement. Howard et al. ( 2021 ) also found that both identified and intrinsic motivation were equally positively associated with school performance. However, higher associations were found for self-reported (intrinsic ρ = .32, identified ρ = .29) than for objective performance measures (intrinsic ρ = .13, identified ρ = .11).

Concerning the controlled motivation types, Taylor et al. ( 2014 ) reported weak but significant negative associations with academic achievement for introjected ( d = − .12) and external regulation ( d = − .22). In contrast, Howard et al. ( 2021 ) found that introjected and external regulation were not significantly related to self-reported (introjected ρ = .07, external ρ = − .02) or objective school performance (introjected ρ = − .01, external ρ = − .03).

Interest Theory

Interest stems from the Latin word “interesse” and etymologically indicates that there is something in between. Interest connects two entities that would otherwise be separated from each other. Dewey ( 1913 ) viewed interest as an engagement and absorption of the self with an objective subject matter. In today’s person-object theory (Krapp, 2002 ), interest is similarly understood as a relational concept that builds a connection between a person and an object. Objects of interest can be very diverse and may include tangible things, people, topics, abstract ideas, tasks, events but also activities such as sports (Hidi & Renninger, 2006 ). A prerequisite for interest to arise is an object in the real world and a person who has at least rudimentary but often considerable knowledge about this object (Alexander et al., 1994 ; Renninger & Wozniak, 1985 ; Rotgans & Schmidt, 2017 ). Interest is a unique motivational concept (Hidi, 2006 ) that establishes a link between the objective appearance and the subjective representation of an object and triggers actions with the object of interest.

Being in a state of interest is accompanied by certain intrinsic qualities (Krapp, 2002 ). Interest-driven activities need no external incentives or rewards to be initiated and sustained. Interest is a form of intrinsic motivation that is characterized by the three components of affect, knowledge, and value (Hidi & Renninger, 2006 ) and can thereby be distinguished from related constructs such as curiosity (Berlyne, 1960 ; Donnellan et al., 2022 ; Peterson & Hidi, 2019 ) or flow experience (Csikszentmihalyi, 2000 ). The affective component of interest is typically associated with a state of pleasant tension, an optimal level of arousal, and positive feelings in the engagement with the object of interest. The cognitive component shows itself in the epistemic tendency to want to learn about the object of interest (Hidi, 1990 ). The value component becomes evident in the object’s connection to the self through the attribution of personal significance (Schiefele, 1991 ).

The most important distinction in interest theory is between long-lasting individual interest and short-term situational interest (Hidi & Renninger, 2006 ; Rotgans & Schmidt, 2018 ). Individual interest describes a motivational disposition toward a particular domain. It resembles a temporally stable personality trait and is an important goal of education concerning developing subject-specific and vocational interests for life-long learning (Hoff et al., 2018 ). Situational interest arises from the stimulus conditions of the environment, without any individual interest of the person having to be simultaneously present. Situational interest provides favorable motivation for learning and leads to increased short-term attention and enhanced information processing (Hidi, 2006 ). This interested turn of the person to certain topics, tasks, or activities is due to favorable characteristics of environmental stimuli such as novelty, importance, or attractiveness and is considered to be well-studied in research on text comprehension (Schraw et al., 2001 ). The change and maintenance of short-term situational interest to long-term individual interest are explicitly described in the four-phase model of interest development (Hidi & Renninger, 2006 ).

It is important to note that both individual and situational interest can be associated with a psychological state of interest (Ainley, 2017 ; Hidi, 2006 ) that arises when individuals interact with the object of interest. This state can be promoted both by the individual interest that a person brings to the situation and situational interest due to salient environmental cues (Knogler, 2017 ). In this state of interest, the two basic components of interest complement and merge with each other (Krapp, 2002 ; Renninger et al., 1992 ).

Figure 5 shows the classification of the three central constructs of interest theory in the action model. Situational interest is triggered by environmental stimuli (Hidi & Renninger, 2006 ) and is thus associated with the situation. This fleeting and malleable psychological state needs support from others or through instructional design to not disappear right away (Renninger & Hidi, 2019 , 2022a ). Individual interest is a relatively enduring disposition of the person to re-engage particular content over time (Hidi & Renninger, 2006 ) and is thus a fixed characteristic of the self. This psychological predisposition is independent of the concrete content and represented as stored knowledge and stored value with relations to the self (Renninger & Hidi, 2022b ). “The self … may also provide an explanation of why interest, once triggered, is then maintained and continues to develop” (Hidi et al., 2019 , p. 28). The state of interest arises in interaction with the object of interest (Knogler, 2017 ) and is connected with the action in the model. This state of interest can be differentiated from a less-developed situational interest. While state of interest refers to an action-related, current experience (Knogler, 2017 ), less-developed situational interest marks the initial phase of a well-developed individual interest (Renninger & Hidi, 2022a ).

Integrating interest theory into the basic motivational model

Individual interest in content or subject matter is a stable predictor of academic achievement. Schiefele et al. ( 1992 ) determined a mean correlation coefficient of r = .31 between interest and academic achievement for studies in K-12 classes. In a more recent large-scale study, Lee and Stankov ( 2018 ) examined the relationship between mathematics interest and mathematics achievement in standardized tests. They found mean within-country correlations of r = .16 and r = .15 for data from PISA 2003 and PISA 2012, respectively. The effect of individual interest on academic achievement remained significant even when researchers controlled for students’ gender, nonverbal intelligence, or socio-economic status (M. Jansen et al., 2016 ). The strongest associations were found in the domains of mathematics and science (M. Jansen et al., 2016 ; Schiefele et al., 1992 ), which seem to be particularly suitable for initiating interventive measures (e.g., Crouch et al., 2018 ; Renninger et al., 2023 ). No meta-analyses are yet known for situational interest. However, Sundararajan and Adesope ( 2020 ) have analyzed how seductive details (i.e., interesting but irrelevant information) can affect learning outcomes. They found an average negative effect of g = − .33 for the relation between seductive details and recall or transfer of presented information.

Achievement Goal Theory

Anyone working as a teacher may have noticed that some students are very interested in learning something new, while others are motivated by obtaining good grades and avoiding poor ones (Eison, 1981 ; Eison et al., 1986 ). This fundamental distinction between individuals concentrating on the process of learning and individuals focusing on the external reasons for learning, can also be found in achievement goal theory (Elliot & Thrash, 2001 ). The theoretical framework has evolved steadily over four decades and is nowadays a key approach in motivation research (Elliot, 2005 ; Elliot & Hulleman, 2017 ; Urdan & Kaplan, 2020 ).

Achievement goals can be characterized by the intention to engage in competence-related behaviors (Elliot & Hulleman, 2017 ). In an attempt to further develop achievement motivation theory, Nicholls ( 1984 ); Nicholls & Dweck, 1979 ) called attention to two types of achievement behavior. Task-oriented individuals pursue the goal of developing high abilities. Ego-oriented learners care deeply about proving high abilities to themselves or others and avoid demonstrating low abilities. Later, the terms mastery goal and performance goal have been established to signify this basic distinction between the two achievement goals (Ames & Archer, 1988 ; Dweck, 1986 ; Elliot & Hulleman, 2017 ).

A first differentiation of the achievement goal theory has been made by including an approach and an avoidance component (Elliot, 1999 ). Research findings made clear that performance-approach goals were mainly associated with adaptive outcomes, whereas performance-avoidance goals were often associated with maladaptive outcomes (Harackiewicz et al., 2002 ). Originally, approach and avoidance components were assumed only for performance goals (Elliot & Harackiewicz, 1996 ). Later, researchers also addressed mastery avoidance goals, which concerns an individual’s striving to avoid mastering tasks worse than before or avoiding a decline in skills or knowledge (Elliot & McGregor, 2001 ; Van Yperen et al., 2009 ).

A second differentiation became necessary because competence-related behavior can be oriented toward very different standards (Elliot et al., 2011 ). Competencies may be reflected in whether certain tasks are fulfilled, performance is improved, or is better than the performance of others. The 3 × 2 achievement goal model by Elliot et al. ( 2011 ) incorporates the different aims of attaining competencies by differentiating between task-based, self-based, and other-based goals. Task-based goals are oriented toward the absolute demands of a task where the action’s outcome signals the attainment of an absolute standard. Self-based goals are a bit more complicated and require reference back to past performance anchored in the “Me-self” (Elliot et al., 2011 ). Competencies in terms of self-based goals refer to meeting or exceeding intrapersonal evaluation standards. Individuals with other-based goals, however, strive to meet interpersonal evaluation standards and to perform tasks better than others in a normative sense. The full 3 × 2 achievement goal model results from completely crossing absolute, intrapersonal, and interpersonal evaluation standards with approach and avoidance tendencies (Elliot et al., 2011 ).

Furthermore, the empirical distinction of performance goals into normative and appearance goals has gained a lot of popularity (Hulleman et al., 2010 ; Senko & Dawson, 2017 ; Urdan & Mestas, 2006 ). However, performance goals in the sense of seeking normative comparisons express the achievement goal concept of attaining competence much better than demonstrating ability to others (Elliot & Hulleman, 2017 ; Senko, 2019 ; Urdan & Kaplan, 2020 ). Therefore, we omit the distinction between normative and appearance goals in the model representation and report their effects only in the meta-analytic part.

Figure 6 illustrates how the 3 × 2 achievement goal model (Elliot et al., 2011 ) can be placed within the basic motivational model. The arrows in the illustration point to the cognitively represented aim of the action in a particular goal state. In task-based goals, the focus is on striving for a desired outcome or avoiding not to attain a desired outcome (see Fig. 6 ). The conceptualization of task-based goals is consistent with the original idea of mastery goals of understanding the content and doing well (Ames & Archer, 1988 ). To represent mastery goals, however, a second arrow would be appropriate from the goal to the action and not just to the outcome of learning. Through the action and the continuous comparison of the current and intended outcome of the action, the individual can master the task, develop new competencies or enhance existing ones (Dweck, 1999 ; Grant & Dweck, 2003 ). We have chosen to present the 3 × 2 achievement goal model (Elliot et al., 2011 ) with task-based goals oriented to the standard of task accomplishment and with a clear focus on the outcome (cf. Senko & Tropiano, 2016 ). Also belonging to mastery goals are the newly added self-based goals (Elliot et al., 2011 ). In self-based goals, the focus is on being better or avoiding being worse than in the past or as it corresponds to one’s own potential. For this purpose, the agent’s view goes back to the abilities and skills of the self (see Fig. 6 ) before the person tries to expand their competencies or avoid the loss of competencies in the action process. Self-based goals use one’s own intraindividual trajectory as the standard for evaluation. Goal setting starts with a look at one’s past, but more important seems to be a look on one’s future potential (Elliot et al., 2015 ). In other-based goals, the course of action is dominated by the anticipated consequences (see Fig. 6 ). The aim of attaining competence is based on an interpersonal standard of being better than others or not being worse than others. This conceptualization of other-based goals coincides with the normative notion of performance goals (Dweck, 1986 ; Senko et al., 2011 ).

Integrating the 3 × 2 achievement goal framework into the basic motivational model

Several meta-analyses have accumulated evidence on the empirical relationships of achievement goals with academic achievement (Baranik et al., 2010 ; Burnette et al., 2013 ; Huang, 2012 ; Hulleman et al., 2010 ; Murayama & Elliot, 2012 ; Richardson et al., 2012 ; Van Yperen et al., 2014 ; Wirthwein et al., 2013 ). The small but significant effects are remarkably consistent across different meta-analyses (for an overview, Scherrer et al., 2020 ). Mastery approach goals correlate between r = .10 (Baranik et al., 2010 ; Huang, 2012 ; Richardson et al., 2012 ) and r = .14 (Burnette et al., 2013 ; Van Yperen et al., 2014 ) with grades and test performance. Mastery avoidance goals show small negative relationships to academic achievement with correlations ranging from r = − .07 (Van Yperen et al., 2014 ) to r = − .12 (Hulleman et al., 2010 ). The correlation coefficients of performance approach goals to academic achievement are consistently positive, ranging from r = .06 (Hulleman et al., 2010 ) to r = .16 (Burnette et al., 2013 ). However, Hulleman et al. ( 2010 ) caveated that normative performance goals ( r = .14) were associated with significantly better performance outcomes than appearance performance goals ( r = − .14). Negative associations were also found between performance avoidance goals and academic achievement with values ranging from r = − .12 (Murayama & Elliot, 2012 ; Wirthwein et al., 2013 ) to r = -.22 (Burnette et al., 2013 ).

Attribution Theory

Attribution theory addresses the issue of how individuals make causal ascriptions about events in the environment (Graham & Taylor, 2016 ). Persons act like intuitive scientists searching for the perceived causes of success and failure (Stiensmeier-Pelster & Heckhausen, 2018 ). In the attribution process, the person tries to determine the cause of an outcome. Causal inferences are drawn based on the covariation of an observed effect with its possible causes (Kelley, 1973 ). The attributional process starts when the outcome of an event is considered important, unexpected, or negative (Graham, 2020 ), which is often accompanied by happiness in case of success or sadness and frustration in case of failure (Weiner, 1986 ).

The causes are then located in a three-dimensional space. The first fundamental dimension of the attribution theory is called the locus of causality (deCharms, 1968 ; Rotter, 1966 ; Weiner, 1986 ). It can be traced back to the pioneering ideas of Heider ( 1958 ), who found that people identify either the situation or dispositional characteristics of the person as the main reasons for people’s behavior. Individuals differentiate between external causes such as task characteristics or luck and internal causes such as ability or effort. The second causal dimension of attribution theory is entitled stability over time. Weiner ( 1971 ) distinguished between stable causes of outcomes such as ability or task characteristics and unstable causes such as effort or luck. Complete crossing of the locus and stability dimensions yielded a 2 × 2 classification scheme for the perceived causes of achievement outcomes. An outcome can be attributed either internally to the person or externally to circumstances. Furthermore, the cause of the outcome can be perceived as stable or variable over time. Finally, Weiner ( 1979 ) introduced a third causal dimension, controllability, as there was still considerable variability within the cells of the suggested classification scheme. For example, mood and effort are both internal and unstable causes, but effort is more subject to volitional control than mood. By combining two levels of locus with two levels of stability and two levels of control, Weiner ( 1979 ) extended the classification scheme to its current state of eight separable causes of success and failure.

The action model in Fig. 7 depicts the basic idea of attribution theory as stated by Heider ( 1958 ) and Weiner ( 1986 ). Attributions occur at the end of an action process. These causal ascriptions are elicited when the outcome is particularly important, unexpected, or negative (Weiner, 1985 ). Depending on the outcome, the person responds with positive affect in case of success or negative affect in case of failure. This front part of Fig. 7 coincides with current illustrations of the attributional theory of motivation (cf. Graham, 2020 ). Representing causal ascriptions and classifying reasons for success or failure on causal dimensions can only be done in a simplified manner in the basic motivational model. The action outcome is further attributed to dispositions of the self, such as perceived ability or effort, or the characteristics of the situation, such as task difficulty or chance (Stiensmeier-Pelster & Heckhausen, 2018 ). After ascribing the outcome to different causal dimensions, other emotions and future achievement strivings emerge as psychological and behavioral consequences of the attribution process (Weiner, 1986 ).

Integrating attribution theory into the basic motivational model

The three causal dimensions are linked to particular psychological and academic outcomes (Graham, 2020 ). Using meta-analytic structural equation modeling, Brun et al. ( 2021 ) found direct relationships between controllability and performance as well as mediated relationships of locus of causality, perceived competence, and performance. While the latter was most evident in the case of success, in the case of failure, the mediated relationship between the stability dimension, expectancy of success, and performance turned out to be significant. Further meta-analytic research showed that school children attribute success more to internal causes and failure more to external causes (Whitley Jr. & Frieze, 1985 ). This egotistic bias manifests in relating success to ability ( g = .56) and effort ( g = .29), and failure to task difficulty ( g = .45) but not to luck ( g = − .03). Fittingly, Fong et al. ( 2017 ) reported that greater internality and controllability of causal ascriptions are associated with better academic achievement among college students ( r = .14). In addition, Gordeeva et al. ( 2020 ) found that an optimistic attribution style, in which positive events are attributed to stable, internal, and global causes, is weakly related to academic performance ( r = .11). In contrast, a meta-analysis by Richardson et al. ( 2012 ) with university students did not reveal any relationships between academic performance and a pessimistic attribution style ( r =. 01).

The integrative model presented in this paper aims to provide a better overview of the most prominent motivation theories in education. The basic motivational model relies on the general model of motivation by Heckhausen and Heckhausen ( 2018 ) in its sequence of events and adopts considerations from Locke ( 1997 ) and Hattie et al. ( 2020 ) on the integration of motivation theories. The basic model allows for the classification of central motivation constructs into the course of action, highlighting in particular the differences between and within the six most popular motivation theories of our time. It makes us aware of the fact that the major theories cannot be easily merged into one another. Expectancy-value theory, social cognitive theory, self-determination theory, interest theory, achievement goal theory, and attribution theory have all shaped our understanding of why, when, and how individuals learn (Anderman, 2020 ). In the basic motivational model, learning outcomes represent a typical indicator of goal-directed behavior. Associated recent meta-analyses demonstrate the empirical relationship between the motivational constructs of the six central theories and academic achievement. They provide evidence for the explanatory value of each theory for students’ learning.

Particular features of the basic motivational model include parsimony (Hattie et al., 2020 ) and the role of situation, self, and goal as cornerstones of a modern conception for building motivation theories (Eccles & Wigfield, 2020 ; Graham, 2020 ; Liem & Senko, 2022 ; Ryan & Deci, 2020 ; Schunk & DiBenedetto, 2021 ; Urdan & Kaplan, 2020 ). Occam’s razor ensures to give preference to a model with fewer parameters over a more complex one. A theory with few variables in a clear, logical relationship to each other can be easily tested and can lead more quickly to unambiguous findings than a more expansive one. A basic motivational model should therefore be deliberately kept simple and specify only the decisive factors. This is what we have been trying to achieve. A closer look at current research on motivation in education shows that often only a particular set of constructs from much broader psychological theories is empirically investigated: self-efficacy expectations from social cognitive theory (Schunk & diBenedetto, 2020 ), expectancy and value beliefs from situated expectancy-value theory (Eccles & Wigfield, 2020 ), or causal ascriptions from attribution theory (Graham, 2020 ). Therefore, for reasons of parsimony, it seems advisable not to try to represent the entire wealth of motivation theories in an integrative model, but only their most important constructs (cf. Anderman, 2020 ; Hattie et al., 2020 ).

While achievement motivation theory posits an interplay of incentives of the situation and motives of the person as the basis for all motivated behavior (Atkinson, 1957 ), social-cognitive and sociocultural theories have significantly altered views on motivation (Eccles & Wigfield, 2020 ; Graham & Weiner, 1996 ; Liem & Elliot, 2018 ; Roeser & Peck, 2009 ; Wigfield et al., 2015 ). We attempted to account for these changing views in our basic motivational model. First, rather than viewing the situation as limited to its potential incentives, we recognized the social, cultural, historical, and environmental context represented in the situation as having a significant impact on the opportunities for motivated action (Nolen, 2020 ). Second, by differentiating the person into self and goal, we could more accurately describe the process of motivated behavior. We mapped the person’s needs, motives, and wishes to the self-system (Roeser & Peck, 2009 ). Driven by its needs, motives, aspirations, and desires, the “I-self”, the consciously experiencing subject, takes influence on the selection of goals and decision-making (Dweck et al., 2003 ; Sui & Humphreys, 2015 ). The self offers the underlying reason for behavior, whereas the goal contains the concrete aim to guide behavior (cf. Elliot et al., 2011 ; Sommet & Elliot, 2017 ).

Affective factors can be active in all phases of the motivation process and take influence on the course of action. At the beginning of the action process, there is typically an awareness of contextual cues or situational stimuli that can trigger emotions such as situational interest, curiosity, or surprise (Gendolla, 1997 ; Hidi & Renninger, 2019 ). Anchored in the self are emotional dispositions of the person such as hope for success, fear of failure, or individual interest. These activating emotions, aroused by situational incentives, are energizers of the action process (Atkinson, 1957 ; Pekrun et al., 2023 ; Renninger & Bachrach, 2015 ). Having goals and being oriented toward them, is also accompanied by emotional states (Linnenbrink & Pintrich, 2002 ). Mastery approach goals are typically associated with the presence of positive emotions and performance avoidance goals with the presence of negative emotions, whereas performance approach goals show weak relations to both positive and negative emotions (Huang, 2011 ; Korn et al., 2019 ). Research within the frame of the 3 × 2 achievement goal model could confirm these findings (Lüftenegger et al., 2016 ; Thomas, 2022 ). Positive emotions such as enjoyment and the state of interest (Hidi & Baird, 1986 ; Krapp et al., 1992 ) or negative emotions such as boredom and anger are expressed in accomplishing the action (Pekrun et al., 2023 ). Other emotions are attached to the outcome of the action: Positive outcomes are related to feelings of happiness, and negative outcomes go along with feelings of frustration and sadness (Graham, 2020 ). As consequences of the action, emotions such as pride, relief, or gratitude are prevalent in the case of success, whereas emotions such as guilt, shame, or disappointment emerge in the case of failure (Pekrun et al., 2023 ; Weiner, 1986 ). Overall, each phase of the action process is accompanied by certain affective states, which makes us aware of the close relationship between motivation and emotion.

While we have limited ourselves in this contribution to the six most common theoretical approaches (cf. Linnenbrink-Garcia & Patall, 2016 ), there are considerations of how other theories of motivation in education fit into the basic motivational model. These theories have not been researched by the same amount of scientists as the theories presented. Nevertheless, constructs such as grit, flow, and social motivation also offer suitable explanations for understanding the reasons behind human action. Grit theory (Duckworth et al., 2007 ) holds two trait-like constructs responsible for high motivation during task engagement. Meta-analytic results show that grit ( r = .19) is a consistent predictor of academic achievement with its dimension perseverance of effort ( r = .21) being more strongly related to academic achievement than the dimension consistency of interest ( r = .08; Lam & Zhou, 2022 ). In the integrative model, these two personality traits would be associated with the self and constantly impact goal pursuit (Duckworth et al., 2007 ). Flow theory (Csikszentmihalyi, 1990 , 2000 ) focuses on experiencing an optimal state of simultaneous absorption, concentration, and enjoyment (Tse et al., 2022 ). As a form of intrinsic motivation (Rheinberg, 2020 ), flow experience would be assigned to the action of the integrative model. Social goals (Wentzel et al., 2018 ) are not located on an intrapersonal level but on an interpersonal level. Two basic motivational models arranged in parallel could be used to map, for example, motivation in teacher-student relationships (Wentzel, 2016 ). This would provide a simple way to represent the reciprocal interactions between the goals and actions of teachers and students.

The integrative model also facilitates an understanding of the interrelationships between different motivational constructs. Howard et al. ( 2021 ) examined in a meta-analysis the relations of different types of motivation from self-determination theory with achievement goals and self-efficacy. Intrinsic and identified motivation showed high correlations with mastery-approach goals, moderate correlations with self-efficacy, and low correlations with performance-approach goals. In contrast, introjected and external motivation showed a reserve pattern and lowly correlated with mastery-approach goals and self-efficacy but moderately with performance-approach goals. To explain these correlative patterns, it can be deduced from the integrative motivation model that intrinsic motivation, identified motivation, mastery-approach goals, and self-efficacy share a common focus on action. In contrast, introjected motivation, extrinsic motivation, and performance-approach goals share a common focus on the consequences of the action. While such post-hoc explanations are of modest scientific value, it may be possible in the future to derive and empirically test predictions about the relationships among motivational constructs based on the integrative model.

A future application of the integrative model is to combine it with neuroscientific research on motivation (Kim, 2013 ; Kim et al., 2017 ). Kim ( 2013 ) proposed a tentative neuroscientific model of motivation processes, in which—similar to the action model—motivation is viewed as a series of dynamic processes. An added value of neuroscientific research is that it can help determine if seemingly overlapping constructs from different theories are unique or similar by examining the patterns of neural activity that are triggered (Kim, 2013 ; Kim et al., 2017 ). It additionally allows for the investigation of unconscious aspects of motivation. Neuroscientific studies can further help identify the mechanism of motivational processes relating to the generation, maintenance, and regulation of motivation. The integrative model can help in identifying overlapping constructs and investigating the mechanisms of motivational processes.

Another application of the integrative model is in using a person-oriented approach to study motivation (Linnenbrink-Garcia & Wormington, 2019 ; Ratelle et al., 2007 ; Wormington & Linnenbrink-Garcia, 2017 ). The person-oriented approach takes advantage of the fact that many motivational variables are often highly correlated with each other. Therefore, rather than singling out one motivational variable and analyzing its influences, it seems useful to create groups or profiles of students based on several different motivational variables. Thereby, it is recommended to use an integrative framework to relate the different motivational constructs: “A person-oriented approach can be particularly useful with an integrative theoretical perspective because it allows researchers to model the relations among motivation constructs across theoretical frameworks that may be conceptually related to one another” (Linnenbrink-Garcia & Wormington, 2019 , p. 748).

In the context of the integrative model, we have presented meta-analytic results on the relationship between motivation and academic achievement. Small to medium correlations emerged for the different types of motivation with students’ learning outcomes. Through its sequence of action stages, the integrative model suggests a causal order in which motivation is crucial for achieving academic outcomes. However, findings on the expectancy component show that the other direction may be considered equally probable, and academic achievement influences learners’ motivation (Pinquart & Ebeling, 2020 ; Sitzmann & Yeo, 2013 ). Therefore, the basic motivational model should also be understood as suggesting that prior academic achievement, cognitively represented in the self, helps shape motivation for new learning tasks.

Theories of motivation in education have increasingly expanded and differentiated over time (Schunk et al., 2014 ). Six major theories of motivation have been established (Linnenbrink-Garcia & Patall, 2016 ), which we have considered against the background of an integrative action model. The framework model is intended to contribute to a deeper understanding of the major theories of academic motivation and to show the focus of each theoretical conception. In this way, difficulties of understanding with which novices try to open up the field of academic motivation theories should be overcome to a certain extent. From the placement of the theories in the basic motivational model, it becomes clear that the various approaches to motivation cannot simply be merged into one another. Nonetheless, opportunities arise from the integrative model to reflect on the meta-analytic findings regarding the interrelations of motivational theories and constructs (Howard et al., 2021 ; Huang, 2016 ) and to speculate about the underlying mechanims of the connection. Similarly, possibilities arise to debate the changing understanding of motivational constructs or to situate new theories and constructs in the course of action to clarify their meaning.

Motivation in education is a very lively field of research with a variety of approaches and ideas to develop further beyond the basic theories. This includes a stronger inclusion of situational, social, and cultural characteristics in the explanatory context (Nolen, 2020 ), the use of findings from neuroscience to objectify assumptions about motivational processes (Hidi et al., 2019 ), the interaction of motivation and emotion in learning and performance (Pekrun & Marsh, 2022 ), the analysis of motivational profiles based on a person-centered approach (Linnenbrink-Garcia & Wormington, 2019 ), or the development of motivation interventions originating in sound theoretical approaches (Lazowski & Hulleman, 2016 ). To ensure that these developments in an increasingly broad field of research do not diverge, it is important to obtain a common understanding of the basic models and conceptions of motivation research. We hope to have made such a contribution by placing key theories and constructs of motivation within an integrative framework model.

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The Theoretical Integrative Review—A Reader’s Guide

Michael j. battistone.

Michael J. Battistone, MD, is Director, Advanced Fellowship in Health Professions Education, Evaluation, and Research, Co-Director, Center of Excellence in Musculoskeletal Care and Education, George E. Wahlen Salt Lake City Veterans Affairs Healthcare System, and Associate Professor, Department of Medicine, Division of Rheumatology, University of Utah Health Sciences Center

Line Kemeyou

Line Kemeyou, MD, FHFSA, is Associate Program Director, Advanced Heart Failure and Transplant Fellowship, and Assistant Dean, Health Equity, Diversity, and Inclusion, George E. Wahlen Salt Lake City Veterans Affairs Healthcare System, University of Utah Health Sciences Center; and

Lara Varpio

Lara Varpio, PhD, is Professor, Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, and Co-Director of Research in Medical Education, The Children’s Hospital of Philadelphia

The term integrative review has been used in different ways by knowledge synthesis scholars. Some have considered it broadly, as an overarching term for various types of knowledge syntheses, including scoping, critical, and meta-narrative reviews. The integrative review term has also been applied more narrowly to describe a single, specific form of knowledge synthesis. In this narrower framing, these empirical integrative reviews communicate the analysis and synthesis of prior evidence-based studies to offer a more comprehensive account of a specific phenomenon: they focus on the integration of data and other research findings from multiple empirical studies pertaining to a single topic. 1 The theoretical integrative review (TIR), however, is unique from other forms of knowledge synthesis and is the focus of this article. TIRs offer health professions education (HPE) scholars an important method for examining available theories related to a specific phenomenon, critically appraising those theories, and constructing an argument supporting the next iteration in theory evolution.

Foundations

What is a tir.

A TIR focuses on theories offered in the literature that explain a particular phenomenon. The TIR compares these theories and examines their constitutive premises, the breadth of their explanatory power and internal inconsistencies, and the nature of the contribution that these theories offer (eg, predictive, emancipatory, explanatory). The purpose of a TIR is to offer reformulations or integrations of theories relating to a phenomenon and an interpretation or argument about them. For example, reformulations of theories might propose one theory to be more compelling in a given context than others, suggest a new conceptualization that extends or modifies the effectiveness of an existing theory, or articulate an altogether new theory that differs markedly from those already described in the literature.

Importantly, TIRs offer researchers the opportunity to bring together theories from a wide array of disciplines. Paradigmatic continuity is not a precondition for a theory’s inclusion in the review; TIRs can gather theories from a wide range of disciplines, with differing purposes and different foci on the phenomenon. 2

How Are TIRs Different From Other Knowledge Syntheses?

TIRs are dissimilar from other forms of knowledge synthesis because of their focus on the theories that explain a phenomenon. Most other forms of literature reviews bring together data from empirical studies into a coherent whole that can answer a specific question (eg, systematic reviews address narrowly focused questions) or that generates new insights by synthesizing a particular type of data (eg, a meta-ethnography integrates qualitative data). In contrast to these aims, TIRs clarify the theoretical groundings that shape the research investigating a particular phenomenon.

When to Consider TIRs in Graduate Medical Education

Professional identity formation provides a good example of a phenomenon in which a TIR might enhance focus for HPE scholars working in graduate medical education. There are numerous theories relevant to identity, which range from those that focus on a better conceptualization of what constitutes an individual’s sense of self (internal cognitive theories) to those that are concerned with how it is shaped (social interaction theories). In studying the former, an HPE scholar might prepare a project informed by Erikson’s theory of adolescent role confusion and the quartet of Marcia’s identity statuses, with the goal of extending our understanding of professional identity within the individual learner. 3 , 4 Alternatively, another researcher might be interested in the process of identity formation and work to integrate Lave and Wegner’s notions of the novice’s entrance into a community of practice through legitimate peripheral participation, with Blasi’s triadic self-model of moral behavior (responsibility, moral identity, and self-consistency). 5 - 7 These social interaction theories direct researchers’ attentions to how moral behavior may “legitimize” peripheral participation and facilitate a learner’s new identity as a member of the community of practice.

Given how different theories offer different foci for studying professional identity formation, engaging in a TIR could enable review research teams to explore (1) which theories to attend to; (2) which foci to examine; and (3) how those distinctive orientations affect the development of a learner’s professional identity. Such an analysis of the available professional identity formation theories would help program directors work with learners toward goals and outcomes based on learner needs. As this example illustrates, TIR reviews are valuable tools for knowledge synthesis in graduate medical education. Another example in Box 1 illustrates the case of Dr Smith, which continues throughout this special review series, considering the same question using different review methodologies.

BOX 1 The Case of Dr. Smith

Dr Smith, a program director, has been tasked to develop an interprofessional education (IPE) experience for the residency program. She decides that conducting a literature review would be a savvy way to examine the evidence and generate a publication potentially useful to others.

After running a quick Google search using the term “interprofessional education,” Dr Smith finds more than 11 000 000 hits. Turning to PubMed and using a general subject search with the same term, “interprofessional education,” Dr Smith identifies 24 000 matches. She randomly samples a few papers and notes the huge diversity of types and approaches, including randomized trials, qualitative investigations, and critical perspectives. She begins to think that the large diversity in the literature may reflect very disparate views as to the nature of IPE as a phenomenon, why it is important, and what impact it has on learners, teachers, and patients.

Dr Smith has read that a strong theoretical grounding is critical for scholarship in health professions education; she decides to explore the theoretical underpinnings of the phenomenon of IPE. Dr Smith plans a theoretical integrative review of IPE to map the landscape of the existing theoretical foundations and synthesize a more complete framework—or to propose one de novo.

Processes and Considerations

What are the orienting assumptions of tirs.

The focus of a TIR is on the analysis, critique, and advancement of theories that explain a phenomenon. This kind of knowledge synthesis does not aim to generate a single “correct” understanding of the phenomenon. Instead, TIRs recognize that theories can change; that some premises of a theory may hold while others do not; that application and understanding of a theory can vary across contexts; and that any theory constructed or revised via a TIR is a proposition that is open to interpretation and refutation. These characteristics of TIRs rest on specific ontological and epistemological assumptions.

Ontology of the TIR: Relativism

In terms of ontology (ie, the nature of reality), TIRs are grounded in the premise that reality is socially constructed and that the phenomenon a given theory seeks to explain is not available for full and complete understanding. Instead, the reality of the phenomenon is built through conversations, interactions, and/or debate that exist between the review authors and other members of the research community through their professional work. The phenomenon will be understood by some individuals within a specific context in one way but experienced by others working in a different context in a different way. Thus, multiple mental constructions (interpretations) of the phenomenon are possible. It is important to note that conflict between interpretations is not a threat to validity. The reality of the phenomenon is simply variable depending on the subjective interpretations of the individual.

Epistemology of the TIR: Subjectivism

In a TIR the author interacts with the source documents—existing theories to be integrated together—in an iterative process to explore, challenge, and construct an understanding of the phenomenon. The knowledge built in this integration is not an objective fact; instead, it is an interpretation that is developed by and that reflects the subjectivity of the individual(s) who conducted the synthesis. Knowledge—the interpretation of theories offered in a TIR—is not value-free. Knowledge created by the TIR is imbued with the values of the researchers doing the study, shaped by the context in which it was created, and fitted to the purpose for which it was intended.

Purpose of the TIR

The TIR’s purpose is the critical examination of theories related to a specific phenomenon. Through this examination, the TIR can fulfill many different goals, such as revising an existing theory based on insights gleaned from examining multiple theories, suggesting the appropriateness of individual theories to different kinds of research purposes, integrating premises from a variety of theories into a new theory, and explaining the weaknesses limiting the applicability of individual theories.

The Types of Questions TIRs Can Address and the Answers They Generate

Since TIRs can address several different purposes, they can also address many types of questions. However, the question will focus on the interpretation and synthesis of theory. TIRs can be used to propose a theoretical framework for an undertheorized phenomenon. To illustrate, a TIR focused on the phenomenon of ethical behavior might ask: What theories can help inform our understanding of residents’ experiences of ethical decision-making? What premises of these theories are particularly relevant in palliative care contexts? TIRs can also be harnessed to challenge mature, dominant paradigms with new theory. For example, regarding the phenomenon of ethical behavior a TIR might ask: How do theories of moral judgement challenge our understanding of residents’ ethical decision-making practices?

Strengths, Limitations, and Rigor

TIRs have several unique strengths. They offer a clearly described approach to the critical examination of existing theory, a goal not shared by other types of reviews or knowledge syntheses. Because TIRs bring theories from many different domains into conversation with each other, these reviews are particularly well-suited for interdisciplinary research. Finally, in its identity as an integrative review, a TIR is explicitly forward-thinking, by seeking to create new knowledge, insights, and even new theory through the work of integration.

Limitations

While TIRs may advance existing theory or generate a new one, they typically do not provide a concrete outcome. A TIR will not present a defined, readily applicable, “evidence-based” solution to a specific problem. Instead, the product of the TIR is advancement of theory, not refinement of practice. Furthermore, TIRs place significant demands on authors and readers, as they require careful analytical study of theories drawn from diverse and unfamiliar disciplines. Such analysis is abstract and requires authors and readers to focus on the premises that explain a phenomenon—a task that is often reserved to philosophers and theorists. Finally, the relativist and subjectivist underpinnings of TIRs may provoke controversy in many HPE contexts where post-positivism continues as the dominant paradigm.

Markers of a TIR’s Rigor

To critically appraise the strength of a TIR, readers should look for evidence of rigor in each step of the project, which should be communicated in each section of the paper. In the introduction, a statement should explicitly classify the work as a TIR. The authors should identify the phenomenon of interest (eg, professional identity formation, ethical decision-making, interprofessional education) around which the TIR is developed, describe the phenomenon’s importance in HPE, and provide an overview of the theories that have been used to examine the phenomenon. If the phenomenon of interest is new or emerging in HPE, a theoretical foundation may have not yet been developed. In this case, authors should describe how theories from other disciplines can meaningfully contribute to a new understanding of the phenomenon in HPE and provide a rationale for selecting theories within or across these disciplines as a starting point.

In a rigorous TIR, 3 processes should be clearly visible in the methods: (1) the literature search used to identify the theories in the TIR, including the specific databases, search terms, and secondary search strategies; (2) the critical examination of these theories, including descriptions of the ways in which each theory is analyzed, evaluated, and deconstructed; and (3) the theoretical integration facilitated by the authors, with clear communication of the critical thinking that produces a synthesis of new ideas, knowledge, theory, or research questions.

Finally, a key characteristic of a strong TIR is its clarity of writing. This is challenging for authors, because it requires the communication of new ideas and concepts that are abstract and often unfamiliar within HPE. A high-quality TIR should ignite new interest in HPE researchers by offering revised ways of thinking about a phenomenon and suggesting important areas and directions for future scholarship. Box 2 identifies 3 resources that may be of particular value to those preparing to develop a TIR.

BOX 2 Resources to Read in Preparation for a Theoretical Integrative Review

• Kirkevold M. Integrative nursing research—an important strategy to further the development of nursing science and nursing practice. J Adv Nurs . 1997;25(5):977-984. doi: 10.1046/j.1365-2648.1997.1997025977.x
• Fawcett J. Criteria for evaluation of theory. Nurs Sci Q . 2005;18(2):131-135. doi: 10.1177/0894318405274823
• Parse RR. Parse’s criteria for evaluation of theory with a comparison of Fawcett’s and Parse’s approaches. Nurs Sci Q . 2005;18(2):135-137; discussion 137. doi: 10.1177/0894318405275860

Conclusions

TIRs represent a powerful approach within an array of knowledge syntheses available to HPE scholars. TIRs provide a unique function: the critical examination of existing theory in relation to a phenomenon of interest, which is essential in HPE. As HPE develops as a recognized discipline, one measure of the maturity of our field is an increased understanding and use of theory.

Funding Statement

This work was supported in part by the Department of Veterans Affairs Office of Academic Affiliation Advanced Fellowship in Health Professions Education, Evaluation, and Research, and by the George E. Wahlen Veterans Affairs Medical Center of Excellence in Musculoskeletal Care and Education.

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Writing a compelling integrated discussion: a guide for integrated discussions in article-based theses and dissertations

• Krystina B. Lewis , Ian D. Graham , Laura Boland and Dawn Stacey

Article-based theses and dissertations are increasingly being used in nursing and the health sciences as an alternate format to the traditional five-chapter monograph. A unique chapter in the article-based thesis is the integrated discussion, which differs in breadth and depth as compared to the discussion for a traditional thesis monograph or journal article. For many students and faculty, the integrated discussion is a challenging chapter to write, with minimal or no published guidance available. In this article, we offer a four-step approach with templates for planning and writing an integrated discussion. We also share several lessons learned with examples from published theses and dissertations. Writing an integrated discussion can be facilitated and written more efficiently by developing a clear and detailed outline of the chapter and broad discussion points prior to drafting the text, to achieve a higher-level synthesis, analysis, and interpretation of the overall significance of the thesis findings.

Introduction

An increasing number of university graduate programs in nursing and the health sciences offer the option of writing an article-based thesis or dissertation as an alternate format to the traditional five-chapter monograph ( De Jong, Moser, & Hall, 2005 ; Graves et al., 2018 ; Robinson & Dracup, 2008 ; Smaldone, Heitkemper, Jackman, Joanne Woo, & Kelson, 2019 ). This format has gained traction internationally to facilitate the earlier and more frequent publication of graduate student research for the timelier advancement of knowledge and impact on clinical practice ( Evans, Amaro, Herbert, Blossom, & Roberts, 2018 ; Maynard, Vaughn, Sarteschi, & Berglund, 2012 ; Smaldone et al., 2019 ). An article-based thesis, also known as the manuscript option, thesis-by manuscript, integrated thesis, or PhD by published works, typically includes one or more articles suitable for publication in peer-reviewed journals and bounded together with an introduction chapter and integrated discussion chapter ( Baggs, 2011 ). The integrated discussion is a unique chapter in an article-based thesis. Integrated (2020) is defined as “ many different parts [that] are closely connected and work successfully together ” (“Integrated,” 2020). The general purpose of the integrated discussion chapter is to provide an overall synthesis and demonstrate high level abstraction, analysis, and interpretation of the thesis findings. It is an opportunity to showcase the thesis’ findings, the student’s reflections about the findings, and its implications ( Smith, 2015 ).

Requirements and expectations for the integrated discussion chapter vary by institution and department. Supervising faculty within individual institutions may also have differing approaches and expectations. We found no general rules or expectations in the literature for writing an integrated discussion. An inquiry of select institutional guidance documents in various international jurisdictions revealed that academic institutions provide few details about this chapter. Descriptions focus more on the overall contribution of the integrated discussion chapter to the thesis, rather than guidance on how to write it ( Table 1 ).

Examples of institutional guidelines for the integrated discussion chapter in an article-based thesis.

Writing a compelling integrated discussion can be challenging, and there is a scarcity of resources, instructions, or published guidance for students and supervising faculty on this subject. Existing guidance is focused primarily on writing discussions for a single journal article or a traditional thesis monograph. Yet, the integrated discussion chapter differs in breadth and depth. In journal articles, a discussion usually consists of a statement of the main findings, interpretation of the results in the context of the broader literature, strengths and limitations of the study, and implications for potential users of the findings (clinicians, administrators, policy makers, and others), the discipline, and future research ( Makar, Foltz, Lendner, & Vaccaro, 2018 ). The discussion section of the traditional monograph thesis has a similar format to that of a journal article as it discusses a single study but is often more detailed. In comparison, the integrated discussion chapter of the article-based thesis provides students with a space in which to weave the results and discussion points from the individual articles comprising the thesis, elaborate on the logic and linkages between them, and convincingly argue for the unified, coherent, and original nature of their findings and contributions to the field-at-large. Smith (2015) refers to this as the golden thread. Grant (2011) refers to it as the logic of connectivity . Ultimately, it is about how the student links the key ideas from the individual papers and articulates the connectedness between them, so as to make readers understand the thesis’ broader meaning which make it accessible to a larger audience ( Smith, 2015 ).

The educational value of conceptualizing and writing an integrated discussion can be best classified at the highest level of Bloom’s revised taxonomy of educational objectives, to Create  — formerly known as Synthesis in Bloom’s original taxonomy — whereby parts are combined in novel ways to produce a coherent whole and to formulate new points of view ( Anderson & Krathwohl, 2001 ; Bloom, 1956 ). According to the taxonomy, the integrated discussion represents the pinnacle of cognitive tasks and processes by requiring higher-order thinking and critical reflections expected of graduate level students. Hence, the integrated discussion chapter provides the graduate student an opportunity to synthesize, integrate, and raise the discussion to a higher level of abstraction; allowing them to demonstrate the coherence between all articles reported in the thesis. It is often in the integrated discussion where thesis advisory committee members and examiners can assess the student’s depth of theoretical and applied knowledge of the subject matter, capacity for critical inquiry, and judge the overall value of the student’s conclusions and contributions to the substantive area of study ( Gould, 2016 ). Specifically in nursing, this higher-level thinking can be articulated by discussing how the knowledge generated advances nursing practice, education and research, and how it contributes to the delivery of high quality health care, and improved health and health system outcomes ( Institute of Medicine [US] Committee on the Robert Wood Johnson Foundation Initiative on the Future of Nursing, 2011 ). Yet, with little guidance available on how to think about and write an integrated discussion, graduate students may miss the opportunity to engage in this higher-order thinking and critical reflections.

In this paper, we offer a practical four-step approach with templates for writing an integrated discussion for article-based theses. KBL initially developed the steps and templates as she conceptualized and wrote her integrated discussion for her PhD dissertation. The steps and templates were refined as a result of (a) her own integrated discussion writing process; (b) discussion with her thesis supervisor and thesis advisory committee members; and, (c) feedback from several graduate students who have used it successfully. As recent doctoral graduates and faculty supervisors, we are sharing this approach and our lessons learned with examples from published theses and dissertations.

Writing an integrated discussion chapter

Step 1: outlining the integrated discussion chapter.

To begin, we propose drafting an outline for the integrated discussion chapter with six major sections ( Table 2 ). First, provide an opening paragraph introducing the information to be presented in the chapter. Second, present a summary of the overall purpose of the thesis as a unified piece of work and a brief summary of each individual article prepared for publication. Each article summary should include the study aim, study design, and key results. Keep in mind that by the time supervisors, thesis advisory committee members, and examiners read the integrated discussion chapter, they have probably just finished reading the previous chapters and articles, so there is no need to repeat information in detail. Rather, the purpose of this section is to refresh the readers’ focus and to begin demonstrating how the articles logically link to each other. Third, outline the main points of the integrated discussion as clearly and concisely as possible (see Step 2 and 3 for more details). Fourth, discuss the strengths and limitations of the thesis, as a whole, if applicable. Typically, strengths and limitations are only presented at the individual article level, but if there are broader strengths or limitations that apply to the thesis, they can be discussed in this chapter. Fifth, discuss the implications of the thesis for the specific discipline (e.g., nursing, medicine, population health, epidemiology, rehabilitation) in terms of the findings’ applicability to practice, education, leadership, and/or policy. Sixth, describe implications for future research. Finally, this chapter should end with a strong, clear, and logical conclusion summarizing the entire work across all elements of the thesis. The conclusions should clearly state the original contribution(s) to the advancement of knowledge and overall significance for the field at-large.

Suggested structure for an integrated discussion.

a Approximate length based on 12-point type font, double spacing, left-justified, 1-inch margins, and format for 8 ½ × 11 paper.

Step 2. Mapping individual articles’ findings to inform the integrated discussion

The next step is to draft the main integrated discussion points. Using Template I, capture the main discussion points from each individual article ( Table 3 ). If there is only one article in the thesis, these can be generated from the literature review, guiding theoretical framework, and/or chosen methodology. This exercise is intended to facilitate the student’s thinking about how to build convincing overarching discussion points and explore the key messages they want readers to come away with after reading the thesis.

Template I to summarize individual article discussion points to identify overarching discussion points.

a If there is only one article in the thesis, additional discussion points/contributions/implications can come from the literature review, guiding theoretical framework, and/or chosen methodology. b Whether these implications are included in the individual article or not, this explicitly offers a starting point to think of the implications arising from individual articles.

The last row in this template is reserved for listing the actual and potential disciplinary implications arising from each article, which may address any of the following domains: practice, education, leadership, policy and/or research. Depending on journal requirements, these implications may be directly discussed in the individual articles. If not, this section offers the student a starting point for thinking about the disciplinary implications arising from their thesis as a whole.

Completing Template I as individual articles are finalized, and sharing it with a faculty supervisor or thesis advisory committee can facilitate discussion about the evolving integrated discussion points. It can also facilitate requisite critical thinking and reflection necessary for linking findings across the individual articles.

Step 3. Drafting the main integrated discussion points

Consider the discussion points and disciplinary implications across all individual articles of the thesis to identify commonalities or differences;

Draft main integrated discussion points, logically connecting the individual articles;

Identify findings from, ideally, two individual articles that support (or refute) the proposed main integrated discussion points (aiming for evidence from two articles helps achieve a higher level integrated discussion); and

Identify and classify theoretical and empirical literature relevant to the main integrated discussion points. Select regional, national, and international empirical studies, theoretical works, clinical practice guidelines, technical reports, and/or policy documents; highlight what the thesis adds to the field (of knowledge) and how it will enhance understanding of the subject.

Template II to build the main integrated discussion points from the individual articles and summarize implications.

a If there is only one article in the thesis, the supporting contributions/arguments can come from the literature review, guiding theoretical framework, and/or chosen methodology. b Broader literature can include empirical studies, theoretical works, practice guidelines, technical reports, and/or policy documents. c List the disciplinary implications identified across all articles. This explicitly offers a starting point to think of the disciplinary implications arising across the individual articles’ findings and discussion points.

This exercise is intended to help organize the content of the integrated discussion early in the writing process. We recommend sharing the evolving Templates I and II with the faculty supervisor or thesis advisory committee and use it as a tool for discussion before writing the integrated discussion chapter. As supervisors (DS, IDG), we also initiate Template I in discussion with our graduate students – often using a blank piece of paper. This reflective exercise may save time in the long run, as it facilitates staying focused on the key points and avoids repeating elements of the discussions within the individual papers. The more detailed the completed templates, the more content is available to transform into text.

Step 4. Writing the integrated discussion chapter

The final step is to turn the planned outline (Step 1) and the drafted main integrated discussion points (Step 3) into narrative prose. To remain focused, start by adding subheadings from the outline and lower level subheadings for each of the main integrated discussion points. A compelling integrated discussion is often preceded by multiple revisions. It should not be written when rushing to meet the thesis submission deadline as writing this chapter requires considerable reflection and introspection. For these reasons, we remind students that the integrated discussion is the last chapter their examiners will read, and it will leave a lasting impression. Getting this chapter right allows the student to demonstrate their mastery of the totality of their thesis work and sets the stage for the examination. In our experience, when an integrated discussion is well-written, the examiners’ comments indicate that the integrated discussion chapter tied all elements of the thesis together and helped them understand the thesis in its entirety.

Lessons learned

When applying this approach for writing our own integrated discussions, or when guiding graduate students through the process, we have learned several lessons. To exemplify these lessons, we offer examples of published theses and dissertations in nursing and other health professions.

Lesson 1. Use stepwise approach with templates to plan and structure the chapter

Using the attached templates and proposed stepwise approach to structure the writing process reduces the inclination to simply repeat the discussion points found in the individual articles. The templates may also help graduate students overcome procrastination resulting from not knowing where to start with the integrated discussion. Further, Templates I and II may be used to guide discussions between graduate student and faculty supervisor, allowing for progress to be monitored prior to writing. Another advantage to doing this early is that some supervisors are less familiar with the article-based thesis format and may have little experience guiding their students in writing the integrated discussion. As such, using the template to walk through this process may be helpful for both parties.

Lesson 2. Think ahead

Avoid delaying until all the individual thesis articles are written before thinking about the integrated discussion. We recommend filling out the templates as individual articles are completed. When analyzing the results for individual articles and thinking about the discussion sections for these, we often identified relevant discussion points that were too broad for the articles. Keeping a log of discussions with faculty supervisors and thesis advisory committee members throughout the thesis writing process, and keeping record of personal reflections that were beyond the scope of individual articles, may help gather ideas early. For example, when first considering her integrated discussion, Hoefel (2019) chose the Walker and Avant (2011) theory testing approach to validate the decisional needs concept and test the main hypothesis of the Ottawa Decision Support Framework ( O’Connor et al., 1998 ). For her thesis, Hoefel (2019) wrote two articles based upon this framework. Her first was a systematic review article on decisional needs of people making health decisions and the second was a sub-analysis of a systematic review on patient decision aids. Hence, evidence from these articles contributed to the higher level discussion about validating the concepts and testing the hypotheses in the framework.

Lesson 3. Dedicate sufficient time

Dedicating sufficient time to writing the integrated discussion is important. For many students, the integrated discussion is a challenging chapter to write. It calls for a different style of writing than that which is required for individual research study articles. It requires conveying abstract and conceptual ideas to generate broader insights. Prior to developing and using these templates, our experience with many students has been that it can take many months of re-writing the integrated discussion chapter for it to adequately reflect the breadth and depth of the student’s thesis work and its vital contribution to the field. We have found that our stepwise approach involves more careful planning and conceptualizing of the integrated discussion prior to drafting the chapter, and therefore results in a more efficient writing and editing process.

Lesson 4. Consider theoretical and methodological implications

Theoretical and methodological implications may be considered as integrated discussion points. A student may choose to closely examine their selected theoretical perspective in light of their thesis findings. For example, in Lewis’ (2018) integrated discussion, she provided a discourse on the use of complementary theoretical frameworks across individual studies: the Ottawa Decision Support Framework ( O’Connor et al., 1998 ) and Normalization Process Theory ( May et al., 2009 ). This provided a link between intervention development and implementation planning, proposing a novel theory-informed approach for the development of decision support interventions ( Lewis, 2018 ). Likewise, methodological implications may be discussed in cases where a student’s thesis advances methods, or to discuss the influence of chosen methodology on key findings where similar research questions are answered using distinct study designs. Wu’s (2014) integrated discussion focused on the methods used for conducting a survey for data collection. He used a set of reminders, with the last reminder being a courier package and return envelope. He then discussed how testing this reminder strategy in his thesis study contributed to survey design methods.

Lesson 5. An integrated discussion is feasible with one article

In cases where there is only one article comprising an article-based thesis, key findings from a more detailed literature review, a theoretical framework guiding the entire research project, or chosen methodology can provide the additional linkages to build the main integrated discussion points. For instance, in her Master of Nursing thesis integrated discussion, Demery Varin (2018) compared and contrasted her secondary analysis findings on the predictors of nurses’ research use in long-term care settings (as reported in one published article) with her review of the literature on the individual and contextual factors to nurses’ research use in all settings.

Lesson 6. Integrated discussions are publishable

The integrated discussion (or elements of it) may be publishable in its own right. When written well, the integrated discussion often results in an important academic contribution to the body of knowledge. Some graduate students have used the integrated discussion as the basis for a commentary paper or an updated theoretical framework paper. In her integrated discussion chapter of her doctoral thesis, Jull (2014) described the development of a collaborative framework for community-research partnerships co-produced by First Nations, Inuit, and Metis women’s community members and researchers. This framework was based on her findings and experience conducting the studies comprising her thesis. Jull et al. (2018) subsequently published a paper based on her integrated discussion.

Lesson 7. Integrated discussions can lay the foundation for subsequent research

Many students who are completing a Master’s or PhD thesis also intend to pursue further research. A well thought out and articulated integrated discussion can inform subsequent research projects, grant proposals, or programs of research. For example, Boland (2018) drew from her PhD integrated discussion to identify evidence-practice gaps and potential solutions in pediatric shared decision-making, which she used to underpin a successful Canadian Institutes of Health Research post-doctoral fellowship and guide the establishment of her research program.

In this paper, we propose an approach to writing an integrated discussion chapter for an article-based thesis. Our advice provided in this paper is intended to position graduate students to adequately plan and produce a unified, coherent, and higher-level synthesis of the articles comprising their thesis. Challenges in writing an integrated discussion include avoiding repetition of discussion points already included within the individual articles comprising the thesis and achieving a higher-level discussion to integrate findings across the individual articles. Writing an integrated discussion can be facilitated by developing a clear and detailed outline of the chapter and, in particular, by identifying broader, more overarching points of discussion, than those presented within the individual articles. We encourage graduate students, faculty supervisors and thesis advisory committees to use the templates provided and share their experiences.

Acknowledgments

The authors wish to thank the graduate students who have used this approach, reported that it was useful, and offered feedback to improve it. The authors also wish to thank the reviewers. Their critical read and constructive comments strengthened this manuscript.

Research funding: The authors received no financial support for the authorship and publication of this manuscript. IDG is a recipient of a CIHR Foundation Grant (FDN# 143237). DS holds a University Research Chair in Knowledge Translation to Patients at the University of Ottawa.

Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

Competing interest: Authors state no conflict of interest.

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• Published: 22 August 2024

Advancing urban sustainability transitions: A framework for understanding urban complexity and enhancing integrative transformations

• Ying Li   ORCID: orcid.org/0000-0001-7240-4037 1 ,
• Robert J. S. Beeton 2 ,
• Xiaofeng Zhao 3 ,
• Yeting Fan 1 , 4 ,
• Qingke Yang 1 ,
• Jianbao Li 1 &
• Linlin Ding 1  

Humanities and Social Sciences Communications volume  11 , Article number:  1064 ( 2024 ) Cite this article

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• Development studies
• Environmental studies
• Social policy

Rapid urbanization and industrialization with their negative repercussions draw attention to the need for urban sustainability. This research built on the urban systems understanding linked with resource utilization, environmental effects, people-environment interactions, and adaptive management by integrating quantitative modelling of urban metabolism with a qualitative investigation into human responses. A hybrid methodology was applied in a typical industrial city of Jinchang, China, which exemplified a model of how complex urban dynamics link to and inform sustainability transitions. The study found that Jinchang City had taken on an unsustainable trajectory underpinned by continuous growth of material consumption, whereas a potential for sustainability transitions was also observed in decoupled negative material outputs, improved material efficiency, and environment regeneration collectively. The challenges in industrial cities have been framed in terms of development model lock-in, conceptual and institutional constraints, innovation and human capital deficiencies, and governance failure. The research proposed a government-led transformation system that integrates multi-level and multi-perspective transformations and management employing discipline insights to facilitate urban sustainability transitions. This involves governance, economic and technological innovations, social transformations, and implementations, in which urban governance and public engagement are essential elements for adapting to undesirable difficulties and exploring locally appropriate strategies. This research provided a theoretical and empirical basis along with scientific and policy implications, which contributed to the developing interdisciplinary knowledge on the understanding of complex urban systems and provided insights into real-world sustainability solutions.

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Introduction.

Economic expansion, intensive resource usage, energy consumption, waste creation, environmental contamination, and accompanying social issues all occur in tandem with urbanization. Although urbanization is not the unique and direct cause to environmental issues, it will continue to have a profound effect on the natural environment (Bettencourt and West, 2010 ; Mumford, 1961 ), while ecological problems, social conflicts, health problems, and a slew of other negative consequences will occur if urbanization is not treated effectively (Asabere et al. 2020 ; Bateman and Hochman, 1971 ). Nonetheless, urbanization contributes to environmental conservation and social-economic prosperity by improved resource use efficiency and environmental management (Fan and Qi, 2010 ; Hui et al. 2023 ; Wang and Su, 2019 ). Cities are predicted to be utilized as major venues for creating issues and answers for huge environmental concerns and global sustainable development, as centers of human activity that directly and indirectly govern biophysical systemic changes (Angelo and Wachsmuth, 2020 ; Camagni et al. 1998 ; Elmqvist et al. 2019 ; Grimm et al. 2008 ; Repette et al. 2021 ; Yang and Zhao, 2023 ). These viewpoints are backed up by research from both established large cities and emerging cities experiencing significant expansion (Bai et al. 2010 ; Haas, 2012 ; Newton, 2008 ). The residents and administrations of these cities are confronted with a plethora of issues related to fast transformation. Cities would face shrinkage and unsustainability in the absence of rational planning and management, especially for many industrial cities (Li et al. 2016 ; Long and Wu, 2016 ; Wu and Wang, 2020 ). Most of these concerns are associated with the United Nations 2030 Agenda for Sustainable Development in achieving the SDG11 of sustainable cities and human settlements (Berisha et al. 2022 ; United Nations, 2015 ).

Sustainability research has been transdisciplinary and experienced a shift from protecting the environment and maintaining natural systems to social dimensions involving perception and values, behavioural options, governance, and politics (Loorbach et al. 2017 ; Wittmayer et al. 2016 ). It emphasises the cross-complementarities across the environmental, economic, and social dimensions, to illustrate complex systems, understand human-environment interactions, respond to realistic needs, and encourage a “revolution” in sustainability (Clark, 2007 ; Giddings et al. 2002 ; Kates et al. 2001 ). The concept of urban sustainability or sustainable cities has been as an essential subject in seeking global sustainability. Urban sustainability research is developing towards interdisciplinary research integrating the resources, ecology, environment, social and institutional aspects, which enlightens the importance of multiple approaches integration in research and practical world (Li et al. 2020 ; Ribeiro and Gonçalves, 2019 ; Spiekermann and Wegener, 2003 ). Transitions toward urban sustainability need to address the key issues framed in social and ethical considerations, technical capability, political and cultural settings, and knowledge-to-action linkages (Peter, 2021 ; Pira, 2021 ; Weinstein, 2010 ). It was acknowledged that the sociocultural environment has transcended the influence of the natural environment on urban development to dominate the interaction between people and urban systems. This implies that combining scientific research with governance aids in achieving sustainability objectives (Beeton and Lynch, 2012 ; Chan and Siu, 2015 ; Smedby and Neij, 2013 ).

Understanding how the urban systems work plays an essential role in promoting transitions toward sustainability. While a variety of methods and strategies have been employed to the understanding of urban systems and to support multifaceted urban transition initiatives, from conceptual framework building to urban systems modelling, spatial-temporal analysis, sustainability evaluation, transition governance et al., in context of diverse social-cultural-institutional background and perspectives (Chang et al. 2020 ; Mutisya and Yarime, 2014 ; Nevens et al. 2013 ; Turcu, 2013 ; Wamsler, 2015 ; Yin et al. 2023 ). Among the numerous studies, the urban metabolism models are widely adopted as approaches to simulate the operation of urban systems and find solutions to sustainable issues. The notion of urban metabolism views the city as an ecosystem where materials and energy circulate, are converted and used in different ways, and are subsequently released as waste, valuable products, or pollutants into the environment (Wolman, 1965 ; Girardet, 2014 ; Goldstein et al. 2013 ; Zhang, 2023 ). A highly efficient metabolism enables high rates of material reuse and recycling as a practical means of enhancing urban sustainability.

In addition to being a physical issue, urban sustainability has become more socially relevant, as cities are self-organizing entities that integrate the interrelated components of material distribution and social networks as they grow as coupled human and natural systems (Liu et al. 2007 ; Wong, 2021 ). Sustainable transitions have been a non-linear multilevel dynamic equilibrium transformation process that has a strong societal base (Loorbach et al. 2017 ). Multidisciplinary efforts have been made to attempt sustainable solutions that incorporate transitions from environmental preservation and resource conservation to social changes within a cultural setting (Hopwood et al. 2005 ; Todorov and Marinova, 2011 ). Many studies have endeavoured to advance urban transitions based on frameworks of sustainability, adaptation, and resilience et al. (Childers et al. 2014 ; McCormick et al. 2013 ; Nevens et al. 2013 ; Wang et al. 2023 ). There are few successful efforts and structural changes that have the potential to dramatically reorient urbanization toward sustainability (Castán Broto et al. 2019 ). The importance of human actions and initiatives that link with sustainable actions has been emphasised for urban transitions, which calls for bottom-up, participatory, and negotiated approaches (Neuhoff et al. 2023 ; Turcu, 2013 ). Consequently, finding solutions for sustainable urban transitions involves more consideration of governance, social factors, and their practical applications (Chan and Siu, 2015 ; Colantonio and Dixon, 2011 ; Ernst et al. 2016 ; Sareen and Waagsaether, 2023 ; Weinstein, 2010 ).

Despite notable transformations in the urban sustainability paradigm, there is a relative paucity of systematic research on sustainability transition that combines knowledge of urban physical and social systems with strategic responses to sustainability concerns. Especially less attention has been paid to the effects attributed to social elements and human responses, which are critical to the practical dimensions of sustainable transitions. These concerns bring a sense of urgency to understand the complex urban system, by answering questions of how the urban biophysical system works, how humans act in the urban social system, and how to facilitate urban sustainability transitions in regional resource-environmental and socio-economic status quo. Therefore, our research was organized to address the issues above. The main objective of this research is to gain deeper insights into urban systems and seek possibilities in societal regimes for urban transitions toward sustainability.

To support the theoretical and analytical arguments, our study took Jinchang City, a natural resource-dependent industrial city in China, as an example to gather empirical evidence. With the advancement of the global sustainable process and the increasing prominence of the historical legacy of resource cities, most of the resource cities are facing a series of sustainable development problems. The intensification of conflicts between resource dependence, ecological environmental protection, and economic and social development has aggravated the problems of sustainable development in these cities. Environmental management plays a critical role in promoting sustainability transitions (Mosgaard and Kristensen, 2023 ). This is especially true for industrial cities in fast-growing nations, where the externalities of industrialization and urbanization have a major influence on citizens and urban natural systems (Dong et al., 2016 ; He et al., 2017 ). This challenge of sustainability transition is global, but industrial cities in particular offer appropriate opportunities to test innovative systemic changes.

Our research places a premium on sustainability theories, a knowledge of urban systems including subsets on urban metabolism and social systems, and adaptive strategies to urban sustainability transitions. Our interdisciplinary perspectives are conductive to deepen the understanding of urban sustainability and explore the social relevance of urban transitions that consider the complexities inherent in the real world. The research contributes to transcending knowledge gaps and advances the scientific discourse of urban sustainability transitions in the following aspects: a hybrid methodology for a systematic knowledge of complex urban systems by linking urban metabolic dynamics with human response, and an innovative framework of urban sustainability research by integrating grass-roots initiatives in research paradigm and multi-perspective adaptive strategies. The research findings would enhance the understanding of the complex socialized urban systems, and provide important insights about how to handle such shifts toward urban sustainability. It also has broader ramifications for other regions of the world that are going through comparable trajectories.

Theoretical framework and methodology

Conceptual framework.

The central hypothesis of this study is that transitions to urban sustainability might be facilitated by better urban environmental management informed by the optimization of urban biophysical structure with high efficiency of material flows, along with a wider public exploration as to how the urban social systems function. This was based on two theses leading the literature to research questions. First, understanding the complex urban dynamics is of importance for urban management; Second, urban transitions toward sustainability are dependent on integrated transformations that are culturally and politically appropriate. To explore these, three research questions (RQ) were developed to guide this research: RQ 1: How can urban metabolism be applied to understand urban biophysical systems? RQ 2: How to understand the urban social system of human-urban interaction in the context of sustainable urban development? and RQ 3: How can urban transitions toward sustainability be facilitated? These questions were resolved by using a holistic strategy that incorporates a variety of approaches that are applicable to various parts of the study.

In the field of discovering how humans change and adapt to the urban environment, human-environment interactions have become an important issue that reveals the dynamics of the complex systems of cities (Fig. 1 ). In the complex urban physical-social system, the human response is in the pivotal position linking the urban physical system and the human-social system. The relationship between the human response and the urban physical system is based on material sourcing and environmental dependence. While the value orientation of human response depends on the norms and institutions of the human-social system. High efficiency of urbanization and environmental-friendly ecologicalization facilitate cities to address the resource and environmental crisis. In this course of transition, there is an increasing emphasis on the importance of the fundamental role of urban environmental systems and suggests integrated urban management systems that incorporate environmental principles into social and economic decision-making through positive human responses.

Theoretical model of the complex urban physical-social system.

This study adopted systems thinking to comprehend and manage dynamic urban systems in the context of China’s adaptation to its changing environment. Systems thinking along with multi-level viewpoints that emphasize the interrelationships among the major variables of a complex system were required to consider the urban system as a full entity with multi-level interactions. It offers a framework for researching complex and multi-faceted urban systems and improves decision-makers’ capacity to implement successful strategies and actions.

The DPSIR (Driver-Pressure-State-Impact-Response) model was used as a framework for urban research in this study (Fig. 2 ). This model was designed to identify causal linkages between human activities and the urban environment. It may be used to assess the status of the environment, assess human responses, and aid decision-making (EEA, 1999 ; Liu et al. 2019 ; Tscherning et al. 2012 ). In particular, the phase of response could be directed at any previous phase and motivate substantial changes.

Conceptual framework of DPSIR model.

According to the DPSIR model, human activities put strain on natural resources and the environment, and these pressures influence the quantity and quality of the natural environment and people. Policies, rules, planning, and individual behaviour are used by governments and communities to adapt to these changes (Ness et al. 2010 ). Based on the causal linkages between human activities and natural, societal, and environmental changes, the model could inform effective actions that may decrease or avert negative pressures and repercussions.

Empirical case study research is critical for addressing the complexities inherent in examining substantive and real-world topics (Robson, 2011 ). Jinchang City, a mature resource-dependent industrial city recognized by the State Council in 2013, was used as a case study in this research. The city is in the Hexi Corridor in Gansu province of north-western China. It is China’s top producer of nickel and cobalt, as well as a refiner of platinum group metals. The city’s output of nickel and platinum group metals accounts for 90% of China’s total production.

Jinchang City has been growing rapidly since 1959 following the discovery of a nickel mine located at Longshou Mountain in the west of the city. The first inhabitants of the city were the immigrants from neighbouring cities and rural areas, as well as young intellectuals and decentralized cadres from eastern China. Natural resource-dependent industries are the key to Jinchang’s economy. Over the past two decades, Jinchang City’s GDP had an average annual growth rate of around 12%. By the end of 2022, the city had a population of 209,950. The gross domestic product (GDP) achieved 32.8 billion yuan (CNY), with the industrial added value accounting for 77.6%. The GDP per capita reached 125,542 yuan per year, which was much higher than the Chinese average (85,698 yuan per year) and the Gansu provincial average (44,968 yuan per year).

Cities with a substantial industrial component usually transition over time from a focus on fast development with major negative effects on the environment and people, to a phase of recovery and then to a maturity or irreversible decline. As one of China’s 126 resource-dependent cities, Jinchang City is currently in a fast-growing phase. However, its fast development of both industrial output and urban construction comes with related negative externalities. In 2004, it was one of the ten most polluted Chinese cities. The constraints of resources, environmental deterioration, and people’s increasing demand for a better environment, have prompted the city to change its brutal way of development in the past. How to avoid urban decline and regenerate cities toward sustainable development is of great importance to Jinchang City. Whilst, this combination of circumstances makes the city an ideal case study for emerging industrial cities seeking paths to a long survival. The exploration of a sustainable urban development path for Jinchang provides an experiment in making a smooth transition that will be relevant to many other industrial cities, and cities similarly constrained in their development by resource and environmental constraints, in China and around the world.

Methodological Procedure

This research, which considers cities to be hybrids of biophysical and social systems, focuses on the quantitative modelling of urban metabolism and the qualitative investigation of the human-urban interaction of Jinchang City. For a more comprehensive knowledge of urban processes, many analytical methodologies were used in conjunction with one another (Fig. 3 ).

Mixed analytical methods for urban systems understanding.

Quantitative research techniques were utilized to explain correlations between variables, establish a visible numerical backdrop of urban systems, and draw judgments using quantitative statistical analysis. Energy and materials go through the urban metabolic system, where they are converted and used in different ways before being released as waste, useful products, or contaminants into the environment. This research treats the metropolitan system as a “black box” and only considers material inflows and outflows, ignoring internal dynamics. The material inflows in Jinchang City mainly included industrial minerals and metals, energy consumption, construction materials, and biomass. Each major category includes many types of material inputs. Such as industrial minerals and metals were composed of total mining minerals, imported metals, and chemical materials. Energy consumption consisted of coal, coke, heavy oil, diesel oil, petrol, and electricity. The material outflows consisted of industrial products, solid waste, water pollutants, and air pollutants, while the air pollutants were measured by SO 2 emissions, nitrogen oxides, and dust.

In this study, material flow analysis (MFA) was applied to open the “black box” of urban metabolism by transforming the actual urban system into a collection of numerical quantities that can be readily comprehended (Goldstein et al. 2013 ). Although MFA was first applied in the social and economic spheres, it is now being used more and more to comprehend the intricate relationships that material flows have with the environment in urban systems (Fischer-Kowalski, 1998 ; Nong et al. 2023 ; Schandl and West, 2012 ). This method of investigating resource metabolism in economic and industrial operations permits the evaluation of resource utilisation efficiency. Then the urban system’s sustainability was assessed utilizing decoupling approaches (Fischer-Kowalski and Swilling, 2011 ; OECD, 2002 ; Tapio, 2005 ). The decoupling model uses a “flexible concept” to reflect the decoupling relationship between variables, to evaluate the potential of urban sustainability. The elasticity value of “T” was used to measure the decoupling relationship between material flows and economic growth and indicate the potential of urban sustainability.

in Equation 1, \({T}_{{MF},{GDP}}\) represents the decoupling elasticity between material flow (material inflow or outflow) and economic growth; \(\Delta {\rm{MF}}\) and \(\Delta {\rm{GDP}}\) refer to the changes of material flow (material inflow or outflow) and GDP respectively. Decoupling status in a given period depends on the value “T” ( T  < 0, 0 ≤  T  < 0.8, 0.8 ≤  T  ≤ 1.2, or T  > 1.2) and the changing trend of MF and GDP ( \(\Delta {\rm{MF}}\)  > 0 or <0, \(\Delta {\rm{GDP}}\)  > 0 or <0). There are 8 decoupling states based on three basic states of negatively decoupled, decoupled, and coupled.

Qualitative research methods were adopted to interpret the urban social structure. To gain a bottom-up understanding of the real world, semi-structured interviews with representatives of local government, corporate, and civil society were conducted. The main goal of the interviews was to gather knowledge and insights from the target population that are pertinent to the research questions. The findings of the qualitative investigation were applied to identify sustainability issues, determine the roles of various stakeholders, triangulate our understanding of urban systems and human reactions, and offer tactics for incorporating human elements in decision-making. These helped to understand human-urban system interactions and some fundamental concerns driving sustainable urbanization. It defined the nature of the urban system, provided complementing knowledge of the actual world, and suggested a potential for public engagement in sustainable urban administration. Specifically, certain public inquiry data helped clarify and filter complicated and contradicting data, allowing for a better knowledge of urban processes. With a focus on improving urban sustainability, this research built an improved urban environmental management system by combining top-down and bottom-up approaches. The synthesis of top-down and bottom-up techniques is beneficial to environmental management since they complement one another (Böhringer and Rutherford, 2008 ; Harder et al. 2014 ). The semi-structured interview materials were open-coded and categorised to build the qualitative data structure (Corbin and Strauss, 2015 ; Yin, 2009 ). These were then linked into nodes to create causal loop diagrams (CLD) for representing human-urban system interactions.

It is possible to acquire a more complete knowledge of urban systems by combining various methodologies and avoiding biased outcomes by presenting multi-angle evidence. In two related studies, detailed analytical approaches aimed at urban metabolic modelling (Li et al. 2016 ) and urban social system comprehension (Li et al. 2019 ) have been outlined and tested, and those will not be elaborated tautologically here.

Data sources

Multiple data-gathering approaches that complement one another are required to gather sufficient information and prevent biased outcomes to solidify the framework. A variety of data collection techniques were employed in this study, including documentation of literal and numerical documents from various sources, semi-structured interviews with questions aimed at gathering consolidated information from the target population, self-reporting of personal feelings, attitudes, and beliefs via a field log book, and visual evidence through observation as an essential complementary approach to gathering evidence. All these methods were used to gather data for this study.

Statistical Yearbooks of the city, a collection of major manufacture’s records of production, environmental statistical reports, and environmental monitoring records were sources of quantitative data. Official reports and network databases, such as China’s environmental quality report, were used to supplement the original data. Semi-structured interviews were the main sources of qualitative data. As a result of the interviews, open-ended replies and follow-up questions were used. Four groups of people, including representatives from the government, business leaders, manufacturing employees, and ordinary residents of the city were consulted. The identical questions were asked to each informant, and the sessions lasted around an hour each.

Urban system understanding

Urban biophysical system modelling.

The material flow analysis between 1995 and 2020 in the case study city indicated that the urban metabolism of the city was characterized by high levels of material consumption and waste generation, posing significant challenges to urban sustainability (Fig. 4 ). However, during the two decades of accessible data, the implementation of MFA and accompanying analytical approaches enabled knowledge of the concrete causes of deterioration in the face of increased output. Over the studied period, Jinchang City’s material inputs and outputs showed a scenario of high resource consumption, with the total volume quadrupling from 5.24 million tonnes to 20.67 million tonnes. The consumption of industrial minerals and metals increased from 2.24 million tonnes to 12.26 million tonnes, reflecting an increasing scale of production. It was also observed that the share of energy consumption kept decreasing, while the share of industrial minerals and metals in total material inputs continued to rise. The trend of declining energy usage per unit of metal production demonstrated the increasing efficiency of industrial production.

Material inputs and main pollutants in Jinchang City.

During the same period, the major pollutant of sulphur dioxide accounted for 60–75% of total air pollution, but its emissions have been decreasing as production scales expand. The SO 2 emission per unit of industrial product outputs has declined from 3.34 to 0.10, indicating an effective SO 2 reduction from the existing production and restraint from the enlarged production. In addition, the increase in nitrogen oxide emissions reflected the improvement in household income and the associated increase in private cars in Jinchang City. The fast increase in automobile ownership since 2008 has countered the beneficial effects of renewable energy adoption and vehicle emission control systems. Meanwhile, the dust declined continuously from 54.66 thousand tonnes to 14.96 thousand tonnes during the studied period. This corresponded with environmental regeneration involving extensive tree planting, ground stabilisation, and landscape renovation around the urban area to reduce ambient dust, and the utilisation of industrial dust removal techniques in both production processes and winter heating systems.

Despite a large dependence on material/energy consumption and the complexity of environmental concerns, sustainable tendencies have been observed most notably economic development being significantly decoupled from SO 2 emissions. This supported the hypothesis that enhanced resource use and environmental circumstances, when combined with prudent investment, would enable urban sustainability transitions. The correlations between GDP and material inputs-outputs shifted often and tended to be decoupled, showing increased material/energy efficiency and improved environment (Fig. 5 ). This featured advancements in technology and industrial restructuring aimed at changing the trajectory of economic growth. There could be a chance that other variables will decouple later when SO 2 emission undergoes a strong decoupling. Positive developments represented the benefits of pollution control investments, industrial technological advancements, and urban economic structural adjustment. The findings also confirmed the approach’s use for tracking progress toward a more sustainable city.

Decoupling economic growth from material inputs and material outputs factors.

Jinchang City’s economy is primarily reliant on mining and mineral processing, which directly contradicts urban sustainability. However, improvements have been proven to be achievable via creative investment, the adoption of cleaner manufacturing in conjunction with circular economy techniques, and structural reforms to the economy. Total air pollution has significantly decreased in recent years, owing to increased industrial output, economic expansion, and household spending. Additionally, major advancements in water quality, water reuse, and eco-environmental conservation have occurred. Simultaneously, societal wealth has multiplied several-fold. Taken together, this demonstrates significant progress has been made in the urban economy, society, and environment, implying that urban sustainability is theoretically attainable.

In addition to what the data shows, it is worth noting that there is a wide range of viewpoints on the problem of air quality, which is directly related to the urban environment. When it came to the environmental costs of air pollution, health was the most important issue. Most of the residents acknowledged the visible progress in environmental improvement over the last decade, yet a few insider anecdotes provided important facts that contradicted official claims. The investigation uncovered a discrepancy between people’s subjective perceptions and government statistics on pollution emissions. Residents in the area have reported seeing emissions in the dark of night, suggesting that the officially recorded pollution levels may have been higher than they really were. According to this implication, the information provided by local governments and businesses was subject to debate or error. The MFA modelling revealed that the favourable trend in the urban environment found should be considered with caution. This emphasizes the importance of using a variety of approaches to get a comprehensive understanding of a given scenario.

Urban social system of human-urban interaction

Understanding the urban social system in the context of sustainable development was facilitated by the modelling of causal relationships between humans and urban systems. It revealed that stakeholder commitment, institutional development, and personal development are the three main clusters that determine how urban social systems influence sustainable urban development. These entwined components contribute to the formation of an integrated metropolitan social system with many feedback loops (Fig. 6 ).

Source: Adapted from Li et al. ( 2019 ). Note: positive (+) and negative (-) arrows demonstrate reinforce and reverse feedbacks between variables.

Numerous governmental and societal issues are linked to institutional constraints. The key to boosting institutional development is reforming governance evaluation, building decision-making capacity, and improving decision-making processes. Unblocking GDP-based “yardstick competition” on urban governance is critical, as is improving the efficacy of plan execution by boosting decision- and policy-makers’ capabilities. In addition, stakeholder engagement in decision-making is critical to balancing interests and creating a knowledge basis for sustainable urban governance.

Government commitment is critical in conducting and coordinating urban environmental management via a variety of measures. The ability of local governance to integrate various and multi-level resources and strengths is essential for fostering departmental collaboration, bringing together specialists from many disciplines, and including the public in decision-making processes. Government informants generally had a more positive perspective on the economy due to their specialized knowledge and the fact that they had prioritized economic transformation in the work routine. Those who were less optimistic about the economic transition said that a better urban environment and a sustainable economy should be the government’s two major considerations. Because of this, the local government was expected to make wise decisions and assist in the execution of plans. Moreover, collaboration between government and business, as well as public engagement in urban governance, are critical for innovation and knowledge-based policies. Notably, public engagement has become a critical component of environmental decision-making since it helps explain local issues and promotes a commitment to sustainable urban management. However, the obstacles to establishing a participatory decision-making process centre on overcoming the communication framework’s deficiencies and the local citizens’ inadequate desire to participate. To address local environmental concerns brought forth by the public, this calls for local governments—or ideally national levels of government—to define cooperative mechanisms and offer fundamental support for public participation.

There are several ways in which people’s efforts might impact their pro-environmental behaviour and performance. When they are combined with cultural development, which helps people grow by giving them moral support and a positive social environment for pro-environmental behaviour, they make up an important soft power foundation for sustainability transitions. Although the local people’s self-assessed level of environmental consciousness was low, their expectations for the sustainability of urban futures were higher. Local people’s attitudes and lifestyles impact their real actions in decision-making and everyday behaviours, and bridging the gap between knowledge and practice is a critical problem for the development of pro-environmental behaviour. This demonstrates that people’s actual behaviours are often inconsistent with their beliefs due to the need to make trade-offs. Intellectual capital, as the primary source of information and experience, facilitates pro-environmental behavioural adaptation in administrative choices and everyday life by increasing stakeholder understanding, motivation, and commitment. Enhanced policy interventions via education, training, information distribution, and talent introduction tactics, together with better social and environmental infrastructure, might help individuals acquire pro-environmental behaviours.

Integrative transformations toward sustainability

In addition to the conventional fundamentals and goals of urban sustainability, the residents also have their own opinions and aspirations for sustainability. They emphasized on issues related to the habitable environment, improved living standards, social harmony, and civilized behaviours (Fig. 7 ). Higher standards of living, a liveable environment, social peace, and civilized behaviours were of the utmost significance to local inhabitants. People’s sense of happiness is ingrained in sustainability since the word “happiness” was applied a lot. It was also reported by several informants as “feeling better” or as a “comfortable smile”. Each facet of urban sustainability is defined by a set of norms that informants feel necessary. These grass-roots perspectives offer an objective orientation for the urban sustainability transition.

The font size is based on the frequency of words spoken by the interviewees while discussing their views on sustainable urban development.

To facilitate urban transitions toward sustainability, adaptive policies, and creative thinking are needed to enhance decision-making mechanisms in dynamic urban systems, which are always confronted with new difficulties (Beck and Conti, 2021 ). It takes into consideration a variety of choices made by many actors from the public and corporate sectors, as well as civil society. However, initiatives that have the potential to transform people’s behaviour and society were few. It was believed that a government-led integrated decision-making and regulatory framework suited to the specific context should be developed. In this framework, multiple goals of economic, environmental, and social sustainability, as well as their interconnections, need to be considered throughout the decision-making process to arrive at more effective solutions. It is concerned with innovations and adaptations in governance, planning, and social management as they relate to the development of cities. Governance and public engagement are two critical and interdependent variables that impact decision-making and strategy implementation in this procedure (Li et al. 2019 ). At their nexus are the well-recognized techniques for enhancing environmental outcomes.

To be sustainable, cities’ dynamic systems must be continually improved and adapted to new conditions. This requires a thorough comprehension of urban dynamics, as well as adaptive reactions and a variety of techniques to deal with the city’s challenges. Challenges in sustainable urbanization are presented due to institutional limits, economic growth patterns, and innovation and intellectual capital deficits as well as a lack of public engagement in both decision-making and everyday performance, as established in the previous research. Multi-level reforms and their synergy across levels are needed to strengthen governance and innovation in both the economy and the environment, as well as to incorporate people’s lives into a sustainable society. Fitting the study’s findings in the DPSIR framework, it showed the reaction component with the adaptive responses of various stakeholders (Fig. 8 ). In the framework of the social system, responses are diverse and geared toward the other four stages. This depicts the reaction process that results in solutions aimed at reorienting urbanization toward sustainability.

Adaptive responses (R) of stakeholders to urban DPSI.

These reactions engage in a variety of activities and interactions. It points to a system of integrative transformations driven by the government that is appropriate to the local setting. This solution is designed to integrate multi-level and multi-perspective innovation and adaptive management employing discipline insights (Fig. 9 ). More flexible combinations of institutional and economic transformation, eco-environmental reconstruction, human initiatives, and social transitions are needed to establish transitional paths. These factors propose primary paths for urban transformation planning and execution. Interactions between these strategic choices are especially critical, since physical changes in urban metabolism are pertaining to economic activity, environmental circumstances, and social dimensions (McCormick et al. 2013 ).

A system of integrative transformations for urban sustainability transitions.

As a typical industrial city with a sound economic basis, Jinchang City can use the advantages of specialist industries to revolutionize urban environmental management and promote sustainable urbanization. To efficiently accomplish environmental goals while also adapting to local conditions, it is critical to integrate multi-perspective thinking and public engagement. This implies that all tactics should be employed contextually. Economic growth may reorient itself toward more efficient, clean, circular, eco-friendly, and diverse development. This might be facilitated through strengthened governance and multi-stakeholder participation, as well as expanded efforts and capacities of decision-makers. Local governments could set locally appropriate goals and strategies based on the actual state of the urban system and coordinate multi-level choices. The government is required to take proactive measures to identify crucial urban transition touchpoints, define realistic targets, stimulate economic transformation and diversification, delegate authority, and support plan execution progressively. This requires an enhanced environmental management system that is based on integrated decision-making and regulation, organized around accountable departments and agents, promotes cooperation and supervision, and inspires public enthusiasm and involvement within a cultural context of harmonious development. In north-western China and similar less-developed regions, challenges in ideological transformation, economic structural adjustment, and intellectual capital management are crucial to local development, which may be facilitated by education, targeted incentives, and preferential policies.

Research implications for understanding urban system and urban sustainability

Our study, with a focus on the specific challenge of a resource-dependent city in northwest China, provided broad research implications for enhancing the understanding of coupled human-nature urban systems and urban sustainability of industrial cities in general. In the succeeding industrialization and urbanization processes, negotiating the trade-offs between sustaining the environment and maintaining economic growth toward improving human well-being is the principal sustainability challenge in industrial cities. The urban metabolism of the industrial city of Jinchang generally shifted from high resource dependence to high material and environmental efficiency. Synchronised progress in economic development and environmental improvement requires radical transformations of dematerialisation and decoupling of economic growth from material consumption by adopting technical approaches of cleaner production, circular economy, and economic structural adjustment. Nevertheless, its sustainability potential needs to be supported by broader transformations in the social dimension that determines the mechanisms of human-environment interactions. Yet, this urban sustainability challenge is far from being addressed.

Since the city is an environment-based social-economical system, our research demonstrated that an integrative transition with a holistic view is needed for urban sustainability rather than a collection of one-off initiatives, which are in line with those of previous studies (Dendler et al. 2012 ; Geels, 2011 ; Smith et al. 2010 ). The change necessitates integrated management rather than an understanding of discrete indicators or single parts of sustainable issues. This requires a wide range of viewpoints, techniques, and management to grasp and explore real-world solutions. Our study found that locals’ requirements and opinions toward the urban environment varied, and some revealed necessary information conflicting with the official statements. This highlighted the importance of public investigation and calls for attention to the value of grass-roots information and initiatives in real-world research. Our study suggested that it is impossible to accomplish a complex urban transformation with a single action, but involves adaptive solutions at several levels. This process of generating integrated and targeted tactics entails an ongoing examination of complementary and competing routes, drawing on the merits of a variety of models.

Our empirical study demonstrated that industrial cities could be more environmentally friendly as the city tends to mature and regenerate. Such a scenario is already possible that greatly improved urban conditions are emerging in some cities in developed countries, where environmental regulation and better technology are dominant (Beeton and Lynch, 2012 ). This means that cities may and should play a key role in assisting the transition to sustainable development. Our study emphasised the importance of considering integrated approaches and regulatory systems informed by a systematic understanding of the socialized urban systems. It projected a possibility of achieving a dynamic equilibrium between economic, environmental, and social advantages via urbanization that is sustainable. Consistent with Purvis et al. ( 2019 )’s opinion, our research argued that transitioning to a more sustainable urbanization entails looking at the three-pillar system of sustainability from a holistic and local perspective and developing solutions that benefit all. Urbanization is shifting toward sustainability, with increased contributions from economic growth, capital accumulation, technological innovation, public engagement, and developing theories and practices of sustainable development. There are similarities between the attitudes expressed by Clune and Zehnder ( 2020 ) who claimed that sustainability solutions integrating good governance, technology implementation, and market incentives are more effective.

Still, more work needs to be done to develop ideas, frameworks, and methodologies that might deepen both academic debate and practical implementation. Further research could be carried out to address sustainability transitions at multiple levels and scales. To create a dynamic platform to track the effectiveness of urban transitions, in which more social indicators connected to public response and participation might be created, documented, and assessed to provide timely grassroots information. Nevertheless, sustainability challenges are different for cities with different resource endowments, local financial strength, development difficulties, and social and humanistic environments. The prominent contradiction and path dependency are distinctive. There is no uniform model applicable to all. Urban transition research must fit in regional specificity by linking complex sustainability challenges to adaptive governance. Moreover, transitions toward sustainability require continuous learning and adaptation. Research on sustainability transitions would still be challenging due to the expanding diversity and societal importance of this field. It could be beneficial to consider the ways in which intentional activities and greater social transitions are mutually reinforced.

Policy implications for urban transitions in industrial cities

Jinchang City is no exception facing problems that hinder urban transitions from “unsustainable” to “sustainable”. The challenges have been framed in terms of conceptual and institutional constraints, economic development models, innovation and human capital deficiencies, governance failure, and public participation in both decision-making and daily performance. These challenges are representative of most industrial cities. As many previous studies have proven, our case study also found that it is not easy for resource-dependent cities to accomplish economic transformation just via market forces and fragmented company self-adjustment. Path-dependencies related to economic growth modes and governance paradigms might continue to hinder the disruptive transformation of resource-dependent cities. However, the city might use its advantages in specialty industries and creative environmental renovation initiatives to change its traditional development mode and build new sectors that support a sustainable image. This transformation is dependent on effective local adaptations and new tactics tailored to the local context. Managing the transitions toward sustainability is not a matter for the government alone, but governance is of great importance to deal with the complexities, conflicts, and interdependencies during this transitional process.

Our findings suggested that the sustainability transitions of industrial cities would be framed into resource sustainability and social sustainability. The former focuses on improving material use efficiency and sustaining economic growth, which could profit from its early preparation for changing existing industrial systems, adopting circular and cleaner techniques, and regrowing new industries. The latter needs to be rooted in deeper societal transformations to bring into effect the multifunctionality of cities, consider socio-human elements, and adopt inclusive and differentiated strategies and paths. Positive changes in the urban ecological environment and liveability could benefit from both above via mitigating negative environmental impacts. All these transformations do not happen alone, but across domains, in practice, they involve the coevolution of technological, social, and governance changes from a system’s perspective (Frantzeskaki et al. 2021 ; Loorbach et al. 2017 ).

Transitions toward sustainability is not only proposing a strategy for change but involve the stages of collecting large amounts of data and information, learning, and identifying problems within the system, setting practical targets and approaches, interacting with multiple stakeholders with different interests, and evaluating and readjusting to new problems and objectives. Notably, sustainable transitions take account of various decisions made by multi-agents of governments, private sectors, and civil society, where the importance of individual behavioural change for social transformation is particularly integrated. The complexity of urban systems determines that the urban transitions may confront structural, technological, financing, and social constraints, and not all efforts would get the desired results or sometimes the negative rebound effects may exceed the expected benefit. Few successful initiatives and structural reforms may dramatically alter urban growth in the direction of sustainability (Khan et al. 2020 ; McCormick et al. 2013 ). Governance failure is often the result of a lack of knowledge and expertise, the need to incorporate environmental-based analysis and democratic involvement in integrated urban decision-making cannot be overstated (Maiello et al. 2013 ; Santos, 2017 ), while constant practices and experience learning are also indispensable.

Making the shift to sustainable urban development calls for a complex combination of policies and multilevel collaboration. There are several options for promoting urban transitions. Firstly, promoting enterprise vitalities and policy support in industrial transformation and diversification to meet both environmental and resource depletion challenges. Specific measures could be applicable through utilizing comparative advantages to reform the industrial and energy structure for optimizing the allocation of resources, reducing the proportion of mining industries to extend industrial chains and cultivate successive industries, and encouraging technological innovation and enterprise openness to generate pathways of industrial diversification for both resource-based and non-resource-based industries. Secondly, improving urban governance, particularly in government-led transition management maximizes the government’s advantages in mobilizing resources and institutionalizing multi-level cooperation. In this process, policy orientation and framework at the national level are crucial for breaking down institutional barriers, particularly in GDP-based “yardstick competition”, and establishing behavioural choices for officials. Local government should actively create favourable market, educational, and cultural environments for stimulating disruptive transformations. Through on-the-job training and personnel exchange within and outside the system, government employees could become transformational governors. Thirdly, promoting a greater level of public engagement and multistakeholder cooperation in decision-making to increase local strategic competency and exert authority over the direction and fundamental approaches to urban transitions. Fourthly, developing effective incentive programs and environmental infrastructure to encourage a broader social transformation. This contributes, but is not limited to changing values and beliefs, bridging the gaps between knowledge and practices, and establishing eco-friendly lifestyles. Finally, promoting human capital management, reaching out to external forces to break path dependency, and expanding cross-regional cooperation is critical for cities in underdeveloped regions. Local governments should create preferential policies and a humanistic environment to deal with these intellectual and technological deficits inherent in less developed regions.

Advancing urban sustainability transitions might be promoted by integrative transformations informed by a comprehensive understanding of urban systems connected to greater knowledge from both biophysical and social perspectives. Our study found the primary obstacles to sustainable transitions in industrial cities have been defined in terms of development model lock-in, conceptual and institutional limitations, innovation and human capital inadequacies, and governance failure. The strong dependence of Jinchang City on non-renewable resources drove the unsustainable trajectory of urban metabolism, but decoupling negative material outputs, increased material efficiency, and environmental regeneration all point to the possibility of sustainability transitions. The simultaneous progress of the economy and the environment requires the dematerialization process and disentanglement of economic growth from extensive material consumption. Our study also found that the commitment of stakeholders, institutional setting, and personal development create a strong societal base for urban transitions. Bridging the knowledge-practice gap is a major barrier to sustainable choices and behaviours in many spheres of production, management, and social life. To address the key challenges defined in this research, we suggested a system of integrative transformations that is government-led, multi-faceted, and environment-adaptive. These transformations encompass cross-level synthesis of institutional reform, technical innovation, economic transformation, environmental rehabilitation, social and behavioural changes, and intellectual capital management. In this transitional process, the competence of government officials and urban governance plays a critical role in overcoming the hindrances from the trade-offs and institutional limits, formulating locally appropriate industrial planning, and creating a favourable environment for economic, educational, and cultural development. Governments could be both the agents of planning and reform as well as the facilitators of creating conditions required for long-term transformation. This necessitates the government taking the lead and organizing multiple resources for urban transformations, while encouraging participatory and collaborative techniques to incorporate multiple stakeholders’ innovative solutions to urban problems.

This study serves as an urban transition model for China’s fast-industrializing cities. Successful urban sustainability transitions in fast-industrializing cities have far-reaching consequences for numerous cities. There is no standard template for all cities, but many common strategies and behaviours can be applied to most industrial cities and many other parts of the world with similar economic-societal-environmental considerations. It is suggested that a sustainable future can only be made possible by efforts that reflect the interconnected complexities of urban sustainability transition research that have been defined in this study.

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Acknowledgements

This research was supported by the National Natural Science Foundation of China [Grant number 42201317, 42001225, 41901245, 41871173], the Foundation of the Key Laboratory of Carbon Neutrality and Territory Optimization, Ministry of Natural Resources [Grant number CNTO-KFJJ-202305], the Humanities and Social Sciences Fund of the Ministry of Education of China [Grant number 23YJCZH102], the Nanjing University of Finance and Economics General Program of School-level Research Projects [Grant number XKYC3202304]. We would like to thank all the local participants for their cooperation in providing interviews and thank the Jinchang Municipal Government and the Jinchuan Group Co., Ltd for providing access to senior officials, managers, and documentation.

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Ying Li: Conceptualization, Methodology, Writing- original draft, Formal analysis, Resources; R.J.S. Beeton: Conceptualization, Writing- review & editing, Supervision; Xiaofeng Zhao: Supervision, Project administration; Yeting Fan: Software, Visualization; Qingke Yang: Resources, Formal analysis; Jianbao Li: Conceptualization, Proofreading; Linlin Ding: Resources, Proofreading.

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Li, Y., Beeton, R.J.S., Zhao, X. et al. Advancing urban sustainability transitions: A framework for understanding urban complexity and enhancing integrative transformations. Humanit Soc Sci Commun 11 , 1064 (2024). https://doi.org/10.1057/s41599-024-03598-x

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DOI : https://doi.org/10.1057/s41599-024-03598-x

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