Interlinking Urban Sustainability, Circular Economy and Complexity: A Systematic Literature Review

Abstract

Urban sustainability challenges demand integrated frameworks capable of addressing the dynamic, non-linear nature of cities. This study explores how the principles of the circular economy and complexity theory intersect to support systemic transformation in sustainable urban planning. Through a systematic literature review of 71 peer-reviewed articles published between 2015 and 2025, we analyze conceptual, methodological, and practical articulations across multiple thematic axes, including circular governance, urban metabolism, regenerative design, adaptive planning, digital integration, and environmental justice. Bibliometric and content analyses were conducted using Scopus metadata, VOSviewer for thematic clustering, and the StArt software (Version 3.4) to structure article selection. The findings reveal that circular economy provides practical tools for resource efficiency and regeneration, while complexity theory offers an adaptive framework to navigate uncertainty, emergent behaviors, and feedback dynamics. The synthesis suggests that their integration enables a more holistic and resilient approach to urban transformation. However, gaps remain in social inclusivity, long-term assessment, and the operationalization of complexity-informed planning. This study contributes to advancing a transdisciplinary agenda for circular and adaptive urban futures, offering insights for scholars, planners, and policymakers aiming to reconfigure cities within planetary boundaries.

1. Introduction

Urban areas are increasingly recognized as both the primary contributors to global environmental pressures and the key arenas for implementing transformative sustainability solutions. With more than half of the global population now living in cities—a figure expected to rise to 68% by 2050—the sustainability of urban systems has become central to the global sustainability agenda [1]. Traditional linear models of urban development, predicated on resource extraction, consumption, and disposal, are no longer tenable in the face of escalating climate change, biodiversity loss, and resource scarcity [2,3,4].

In response to these challenges, the circular economy (CE) has emerged as a paradigm that seeks to decouple economic growth from environmental degradation by closing material and energy loops, extending product lifespans, and minimizing waste generation [5,6,7]. Initially rooted in industrial ecology and production systems, CE has gained growing attention in the urban domain, where its principles are being adapted to planning, design, infrastructure, and governance [8,9,10]. Several studies have explored the urban implementation of CE through concepts such as circular urban metabolism, circular districts [11], urban resource flows [12], and regenerative planning models [13].

At the same time, the theory of complexity provides a systemic lens for understanding urban environments not as static or linearly predictable entities, but as dynamic, complex adaptive systems characterized by feedback loops, emergence, self-organization, and nonlinearity [14,15,16]. The application of complexity thinking in urban studies has challenged traditional top-down planning approaches, instead favoring participatory, resilient, and adaptive frameworks [17,18,19]. In particular, scholars have highlighted the importance of managing uncertainty, fostering innovation, and enabling multi-scale coordination across infrastructures, stakeholders, and temporal horizons [20,21].

While both CE and complexity theory have been applied independently to urban sustainability, there is limited research explicitly connecting these two frameworks [22]. The growing literature on CE in cities often lacks the systemic, adaptive, and feedback-oriented perspective inherent in complexity theory. Conversely, studies grounded in complexity thinking frequently overlook the practical tools and resource-focused strategies offered by circularity [23,24]. This disconnect has resulted in fragmented urban policy and design models that struggle to achieve coherent and resilient sustainability transitions.

In this context, a central question arises: how are the principles of circular economy and complexity theory conceptually and methodologically integrated into sustainable urban planning, and in what ways can this integration contribute to a systemic transformation of planning approaches? Despite isolated efforts, the absence of a consolidated synthesis of the literature prevents a comprehensive understanding of the theoretical, methodological, and practical articulations between these paradigms in the urban field.

Recent contributions have begun to explore these intersections. For instance, some authors have linked circularity and complexity through the lens of urban metabolism [25,26], while others have investigated the integration of adaptive governance with circular planning [27,28]. Still, the field lacks a comprehensive review of how these frameworks are being co-articulated in the context of urban planning for sustainability.

This article addresses this gap by conducting a systematic literature review (SLR) of peer-reviewed scientific publications that address the integration of circular economy and complexity theory within sustainable urban planning. Through a structured PRISMA-based methodology, this study identifies dominant themes, conceptual linkages, methodological approaches, and existing research gaps. The aim is to offer a consolidated understanding of how circular and complexity-based principles are shaping sustainable urban transitions, and to provide a foundation for more coherent, adaptive, and systemically informed planning frameworks.

2. Methodology

The present study is based on a qualitative investigation supported by a systematic literature review, focusing on the intersection between circular economy (CE), complexity theory (CT), and sustainable urban planning (SUP). These three paradigms represent critical dimensions of current urban transformation discourses, each contributing unique perspectives and tools to address the growing challenges of sustainability in complex urban environments. The systematic review method was chosen because it allows for a structured, transparent, and replicable process, which is essential for ensuring academic rigor and minimizing biases that could influence the findings [18]. By adopting this method, the study aims to consolidate fragmented knowledge, identify emerging research patterns, and contribute to the theoretical and practical development of interdisciplinary urban sustainability approaches.

Systematic literature reviews are well-suited for examining complex, interdisciplinary topics such as the integration of circularity and complexity in urban contexts [29]. This study employed a multi-step protocol that included: defining objectives and the central research question; developing and testing a Boolean search strategy; screening titles and abstracts; evaluating full texts; extracting key data; and synthesizing findings based on thematic patterns.

A descriptive and exploratory analysis was initially conducted using metadata obtained from the Scopus database, selected due to its comprehensive indexing of interdisciplinary scientific journals in urbanism, sustainability, environmental sciences, and systems theory. The metadata, exported in RIS format, was processed using VOSviewer (version 1.6.20) to generate bibliometric maps that revealed co-occurrence relationships between keywords, authorship networks, and thematic clusters. This preliminary bibliometric exploration helped to refine the scope of the review and detect dominant concepts and underrepresented research areas [30].

To identify the most influential contributions within the corpus, a co-citation analysis was conducted using VOSviewer software. In this network, nodes represent individual documents, and edges reflect the frequency with which two documents are cited together. The Total Link Strength (TLS) metric was used to determine the relevance of each node (document), as it quantifies the cumulative weight of its co-citation connections. This measure, while related to citation count, reflects a document’s relational centrality within the knowledge structure rather than its absolute popularity. The articles with the highest TLS and central positions within the network were examined more closely as representative of conceptual and methodological influence.

For thematic structuring, a co-occurrence analysis of author keywords was performed. The keywords were extracted from the metadata of the 71 included studies. The resulting term network was clustered using VOSviewer’s modularity-based algorithm, which applies Community Detection logic (LinLog layout) to group terms into cohesive thematic areas. Each cluster’s size is proportional to the number of keywords and interconnections within that thematic domain, and its visual representation is color-coded for interpretive clarity. This allowed the identification of dominant research themes and their interrelations within the field.

Subsequently, a full-text screening of the most relevant peer-reviewed journal articles was performed, prioritizing publications from high-impact journals across the domains of urban planning, sustainable development, environmental governance, and complexity science. The review protocol was explicitly structured in accordance with the PRISMA 2020 guidelines [30], which provided a rigorous framework to ensure methodological consistency throughout the selection and analysis process (Supplementary Material). Each stage of article identification, eligibility, inclusion, and exclusion was documented to enhance transparency and reproducibility, as will be illustrated in the corresponding PRISMA flow diagram (Figure 1).

To support the review management process, the StArt software (State of the Art Studies) was employed. This tool enabled a systematic organization of the metadata, facilitated document classification and tracking, and allowed for the consistent application of inclusion/exclusion criteria [30]. Through its use, it was possible to maintain a detailed log of decisions made at each review stage, ensuring internal coherence in the classification of studies and the preservation of traceability during qualitative coding and thematic synthesis.

The review was guided by the central research question: how are circular economy and complexity theory integrated into sustainable urban planning frameworks, and in what ways can this integration inform systemic transformations in planning approaches? This question served as a heuristic to explore both the theoretical alignments and practical articulations between CE and CT in urban planning contexts. Particular attention was given to the presence of systemic principles such as adaptivity, nonlinearity, self-organization, feedback mechanisms, and resource circularity, which are characteristic of both paradigms.

The corpus of selected publications encompassed a wide range of methodological designs, reflecting the interdisciplinary nature of the field. These included bibliometric analyses, which provided insight into trends and authorial influence; comparative case studies, which illustrated how CE and CT are applied in different urban contexts; system dynamics modeling, which enabled the simulation of feedback loops and long-term sustainability scenarios; and qualitative system approaches, which examined governance innovations, planning strategies, and policy implications from a complexity-informed perspective.

Altogether, this review establishes a comprehensive analytical framework for understanding how the convergence of circular economy principles and complexity thinking is shaping new trajectories in sustainable urban planning. It not only maps the current state of the literature but also highlights gaps, proposes future research directions, and contributes to the formulation of integrative planning approaches capable of addressing the dynamic and interdependent nature of contemporary urban systems.

The Scopus database was selected as the primary source for retrieving scientific publications due to its extensive indexing of high-quality, peer-reviewed journals and its multidisciplinary coverage of the fields relevant to this study. Scopus includes robust collections in architecture, urban planning, environmental sciences, sustainability, engineering, and systems theory, which are all critical for capturing the conceptual and methodological intersections between Circular Economy (CE), Complexity Theory (CT), and Sustainable Urban Planning (SUP) [18]. Its advanced search capabilities, standardized metadata, and exportable formats further support its suitability for conducting comprehensive systematic reviews.

The decision to use Scopus as the exclusive data source is supported by its extensive indexing of peer-reviewed journals that specialize in sustainability science, urban studies, environmental governance, and systems theory. Compared to other databases, Scopus offers broader coverage of interdisciplinary journals relevant to urban sustainability, including leading titles such as Sustainable Cities and Society, Journal of Cleaner Production, Cities, Resources, Conservation and Recycling, and Urban Studies. Furthermore, Scopus provides standardized metadata formats, robust citation tracking, and advanced filtering capabilities, which are essential for bibliometric analysis and thematic mapping. These features make it particularly suitable for systematic reviews aiming to capture complex intersections among circular economy, complexity theory, and urban planning within a high-quality academic corpus.

Given the interdisciplinary scope of the research, the search strategy was carefully designed to retrieve studies from various academic traditions that address planning processes, systemic thinking, urban sustainability, adaptive systems, and circular resource flows. The database query was conducted on 5 April 2025, using an extensive Boolean search string combining conceptual keywords from the three core domains—sustainability, urbanism, and complexity. This approach ensured the inclusion of literature representing theoretical, empirical, and hybrid perspectives.

The search string applied in the TITLE-ABS-KEY fields of Scopus was the following: (“circular economy” OR “resource efficiency” OR “closed-loop system” OR “materials reuse” OR “waste minimization” OR “cradle to cradle” OR “industrial symbiosis” OR “recycling” OR “material flow” OR “eco-efficiency”) AND (“sustainable” OR “sustainability” OR “sustainable development” OR “green development” OR “resilient development” OR “low-impact development” OR “sustainable urbanism”) AND (“urban planning” OR “urban development” OR “urban transformation” OR “city planning” OR “urban metabolism” OR “urban governance”) AND (“complexity theory” OR “complex systems” OR “adaptive systems” OR “systems thinking” OR “nonlinear systems” OR “chaos theory” OR “self-organization” OR “resilience” OR “emergence”). This search resulted in an initial dataset of 203 documents, which became the foundation for the subsequent filtering and selection process.

To refine the initial pool of articles, a two-level screening protocol was applied. The first level involved basic inclusion and exclusion criteria: articles had to be peer-reviewed and provide full-text access. Importantly, studies had to explicitly address at least two of the three core concepts (CE, CT, SUP), either conceptually or methodologically. Conference papers and book chapters were excluded to maintain quality control, while the gray literature and duplicates were removed to avoid redundancy.

The second level consisted of a detailed evaluation of titles and abstracts to eliminate documents unrelated to urban contexts, planning practices, or systemic approaches. This step reduced the corpus from 203 to 136 articles. The eligibility phase involved full-text reading, during which each article was assessed in terms of content relevance, depth of conceptual integration, and methodological robustness. Studies that focused exclusively on technical solutions, lacked planning or governance components, or did not connect CE and CT in meaningful ways were excluded.

After the full-text assessment, 92 articles met all the selection criteria and were retained for in-depth qualitative analysis. During this phase, additional attention was paid to the type of methodological approach used (e.g., case study, simulation modeling, bibliometric analysis), the scale of urban intervention (e.g., neighborhood, city, metropolitan), and the degree of integration between circularity and complexity principles.

The entire screening and selection process was structured using the StArt software (State of the Art through Systematic Review) [31]. This tool allowed for the categorization of articles, tracking of selection decisions, recording of metadata, and tagging of thematic content. It was particularly helpful in organizing the bibliographic portfolio and managing the volume of documents efficiently. StArt also enabled researchers to link inclusion decisions to specific conceptual criteria, thereby increasing the methodological transparency of the review.

In line with best practices for systematic literature reviews, the process followed the PRISMA 2020 guidelines, and the full procedure is visually represented in the corresponding PRISMA flow diagram (see Figure 1) [30]. The final portfolio of 71 articles constitutes the empirical and conceptual foundation for the Results section that follow. These selected works reflect current academic efforts to bridge CE and CT within the urban planning domain, highlight areas of convergence and divergence, and expose critical knowledge gaps—particularly in circular governance, urban resilience, and systemic planning strategies.

3. Results

3.1. Descriptive Analysis

The temporal distribution of publications related to sustainable urban development, circular economy, and complexity theory reveals a notable evolution over the past three decades, as shown in Figure 2. From 1997 until approximately 2016, the number of annual scientific contributions remained relatively low and stable, rarely surpassing five publications per year. This trend reflects the early, fragmented stages of interdisciplinary convergence between sustainability sciences, systemic thinking, and urban studies.

A marked growth in the number of publications begins to emerge around 2017, coinciding with a broader shift in the academic landscape toward integrative approaches capable of addressing the multifaceted challenges of urban transformation. The increase accelerates significantly from 2020 onwards, demonstrating a growing recognition of the relevance of circular and complex systems-based frameworks in urban planning.

The peak is reached in 2024, with over 50 publications, representing the highest annual output within the dataset. This surge reflects the academic community’s heightened interest in the integration of circular economy principles and complexity-informed strategies to promote more adaptive, resilient, and sustainable urban systems. A slight decline is observed in 2025, likely due to indexing delays or ongoing publication processes, but the overall trajectory remains one of expansion.

This growing body of literature underscores the urgency of transitioning from linear, reductionist planning models to more holistic, feedback-aware paradigms. It also highlights the consolidation of a research agenda that embraces nonlinearity, circularity, and urban resilience as key pillars of sustainable development.

The spatial distribution of scientific production on sustainable urban planning, circular economy, and complexity theory reveals clear regional dynamics, as represented in Figure 3. The analysis shows that India, China, and the United Kingdom occupy the top positions in terms of publication volume, suggesting a strong institutional engagement and research investment in sustainability transitions within urban environments.

The prominence of India and China likely reflects their rapid urbanization trajectories and the urgency to find scalable, resource-efficient solutions to cope with environmental and infrastructural stress. The United Kingdom’s leading role is consistent with its well-established academic networks in urban planning, systems thinking, and sustainability governance.

A second cluster of countries—including Italy, the United States, Germany, and Portugal—also demonstrates active research output, reflecting consolidated interest in integrating complexity and circularity within urban policy frameworks. Meanwhile, nations such as Australia, the Netherlands, and Japan illustrate how engagement in these topics transcends continental boundaries, involving both developed and emerging economies.

This distribution underlines the global relevance of the topic and indicates a transdisciplinary convergence across geographies. The leadership of countries with intense urban dynamics and diverse sociopolitical contexts emphasizes the necessity of flexible, adaptive planning models informed by complexity and circular principles. Moreover, the growing involvement of both Global North and Global South actors signals increasing opportunities for cross-regional learning and policy innovation.

The bibliometric visualization generated through VOSviewer reveals the conceptual architecture of current academic discourse at the intersection of sustainable urban development, circular economy, and complexity theory (Figure 4). At the core of the network, the terms “sustainable development”, “urbanization”, and “climate change” emerge as the most densely connected nodes, indicating their centrality in shaping theoretical and empirical studies within this research field. Their prominence suggests an intrinsic link between urban transformations and the broader global sustainability agenda, particularly under conditions of environmental uncertainty and accelerated urban growth.

The term “systems thinking”—clustered closely with concepts such as “urban metabolism”, “resilience”, and “resource efficiency”—serves as a conceptual bridge that aligns closely with complexity-informed approaches. Its spatial location in the network confirms the increasing adoption of systemic methodologies in urban planning, emphasizing feedback mechanisms, multi-scalar interactions, and emergent behavior. This aligns with our theoretical position that urban systems should be interpreted as dynamic, self-organizing entities rather than static planning domains.

Terms such as “circular economy”, “urban planning”, and “urban resilience” also form strong sub-clusters, indicating an ongoing integration between resource-looping strategies and adaptive planning practices. These associations reinforce the argument that circularity and complexity are not only compatible but mutually reinforcing in the context of urban sustainability.

Peripheral yet significant concepts—such as “smart city”, “water management”, and “ecosystem services”—highlight application domains where complexity becomes operational. For instance, the governance of urban water systems involves diverse actors, spatial interdependencies, and temporal fluctuations, making it a prime candidate for complexity-informed intervention. Similarly, the presence of ecological terms such as “biodiversity” and “ecology” underscores the need for planning frameworks that extend beyond infrastructural logic to incorporate environmental resilience and regenerative capacity.

The overall structure of the network supports the integrative analytical lens proposed in this article. The co-occurrence of key terms within and across thematic clusters validates the relevance of using complexity theory to understand how circular strategies are embedded in sustainable urban transitions. This semantic landscape reflects a maturing research agenda that seeks to respond to contemporary urban challenges through interconnected, flexible, and ecologically grounded approaches.

The network visualization presented in Figure 4 identifies five main thematic clusters based on keyword co-occurrence, each represented by a different color. The red cluster focuses on environmental management and basic urban services, including keywords such as climate change, recycling, and water management. The green cluster emphasizes governance and planning, with central terms like circular economy, urban resilience, and sustainability. The blue cluster represents the broader sustainability discourse at the urban scale, encompassing urban growth, urbanization, and sustainable development. The purple cluster gathers methodological approaches grounded in systems theory, such as urban metabolism and material flow analysis. Lastly, the yellow cluster points to social and contextual dimensions, including population statistics, economic and social effects, and human dynamics. These clusters reflect the multidimensional nature of urban sustainability, integrating systemic, environmental, social, and governance-related perspectives.

The systematic literature review revealed a set of converging insights that underscore the relevance of integrating circular economy principles and complexity theory in urban planning. Key findings indicate that adaptive and polycentric governance models enhance the capacity of cities to implement circular strategies effectively; that urban metabolism frameworks benefit from coupling life cycle thinking with system dynamics and machine learning; and that participatory design processes significantly increase local ownership and the adaptive capacity of communities. Moreover, policy innovations rooted in nexus thinking, digital integration through real-time monitoring and planning platforms, and attention to environmental justice are emerging as crucial components of systemic circular transitions. These insights highlight the growing importance of methodological pluralism and socio-technical integration in shaping sustainable urban futures. In the following subsections, the results are organized thematically to examine in depth the conceptual articulations, empirical applications, and methodological tools that substantiate these findings.

The integration of circular economy and complexity theory calls for a comprehensive framework capable of synthesizing their underlying principles and operational pathways within sustainable urban planning. Figure 5 presents a conceptual model that encapsulates the theoretical and thematic insights identified in this review.

The model is structured around two foundational paradigms: circular economy, which emphasizes resource looping and material flow optimization, and complexity theory, which introduces notions of emergent behavior and complex feedback dynamics. These paradigms converge in the central axis of circular governance, which serves as the organizing framework for adaptive, participatory, and multi-level coordination mechanisms.

Four strategic governance dimensions emerge as critical to enabling circular-complex transitions: adaptive governance through learning loops and feedback; policy mix and innovation via scenario testing; participatory co-design involving multiple stakeholders; and institutional integration across horizontal and vertical levels. These governance strategies support the deployment of systemic implementation mechanisms that include systems thinking tools, regenerative urban metabolism approaches, digital integration, and experimental-reflexive policy design.

The model ultimately points toward a systemic reconfiguration of urban environments. Rather than promoting isolated interventions, it conceptualizes cities as dynamic, co-evolving systems where governance, infrastructure, and community behaviors align to produce resilient, inclusive, and circular urban forms.

3.2. Circular Governance and Institutional Frameworks

Effective implementation of urban circular economy initiatives requires governance approaches capable of navigating institutional complexity and engaging diverse stakeholders. Empirical analyses across European city-regions reveal persistent governance barriers to circular transitions, including fragmented policy frameworks, limited public awareness, and technological gaps [16]. These challenges underscore the need for multifaceted, adaptive governance models that can embrace complexity. Complexity theory perspectives suggest that urban systems are dynamic and non-linear, calling for flexible, networked forms of governance (often termed adaptive governance) that can respond to emergent changes and feedback [18]. For instance, a recent systematic review on complexity and urban sustainability highlights self-organization and adaptive governance as critical to enhancing urban resilience in the face of uncertainty [32]. In practice, this implies moving beyond siloed, top-down decision-making toward more polycentric and participatory governance structures.

Recent studies also point to the importance of aligning institutional incentives and capacities with circular objectives. Policy interventions must be carefully calibrated to foster innovation without causing policy overload. One quantitative study, combining institutional theory with a dynamic capabilities approach, found that government policies for innovation and finance can indeed drive circular adoption by firms, but only up to a point—beyond a certain threshold, excessive regulatory pressure becomes counterproductive [33,34,35]. This inverted-U effect suggests that governance must balance encouragement with flexibility. Moreover, a diverse mix of policy tools often yields synergistic benefits: when innovation incentives are combined with financial support, they produce greater adoption of circular practices than financial measures alone [33,36]. Such findings imply that circular governance should be both enabling and moderating, coordinating multiple levers (regulatory, economic, informational) in an adaptive manner. Importantly, governance arrangements need to facilitate horizontal collaboration across departments and vertical integration across levels of government [16,37]. Without an integrated guiding framework and knowledge-sharing mechanisms, even well-intended circular strategies can stall. In summary, aligning urban governance with complexity entails embracing policy experimentation, feedback learning, and cross-sector coordination—a shift from command-and-control toward learning-by-doing frameworks that evolve in tandem with urban systems’ responses.

3.3. Urban Metabolism and Resource Flows

Urban metabolism—the throughput of materials, energy, water, and waste in cities—provides a systemic lens to integrate circular economy principles with complexity thinking. Cities function as complex ecosystems of interlinked processes, so managing their metabolism requires holistic, feedback-aware approaches. Recent research conceptualizes “smart and regenerative urban metabolism” as a circular, co-evolutionary process, emphasizing the elimination of waste and continuous regeneration of resources [11]. In this view, urban subsystems (e.g., water, energy, food, mobility) are treated as analogous to ecosystem components, with open and flexible boundaries allowing constant interaction [11,38,39,40]. Such a perspective underscores that achieving sustainability requires closing loops (through reuse, recycling, and recovery) in tandem with enhancing the system’s resilience and regenerative capacity. Methodologically, this has led to new integrative frameworks. For example, one study proposes coupling Life Cycle Thinking (LCT) with machine learning to assess city metabolic performance in multiple dimensions [41,42]. By modeling urban processes as an interconnected network (a “neural network of urban processes”), the approach can capture cross-sectoral impacts and fill data gaps, addressing the inherent complexity of urban flows [11,43,44]. The results enable identification of pressure points (e.g., carbon hotspots or resource inefficiencies) and inform interventions that target multiple sustainability criteria simultaneously. This illustrates how complexity-aligned tools can enrich the traditional urban metabolism analysis with predictive and adaptive capabilities.

Despite growing adoption of circular metabolism concepts, critical evaluations warn that simply applying circular economy models to cities without a systems perspective may fall short. Choy et al. argue that the circular economy paradigm, in practice, has not yet delivered expected sustainability outcomes in industrial–urban systems, as evidenced by a widening “circularity gap” [45]. They identify underlying metabolic rifts—fundamental mismatches between linear resource use patterns and ecological limits—that a narrow implementation of circular economy might overlook [45,46]. In response, the authors call for integrating principles from systems ecology and thermodynamics into urban metabolic management [45,47]. This means acknowledging entropy (irreversible resource dissipation) and feedback loops when devising circular solutions. For instance, simply increasing recycling rates may not suffice if overall consumption continues to grow or if rebound effects occur. A systems approach would address such issues by linking material flow analysis with demand-side strategies and ecosystem regeneration. Empirical studies in this vein often highlight the importance of spatial scale and context: the efficacy of circular interventions (like urban industrial symbiosis or localized energy recovery) depends on city-specific factors such as density, land use patterns, and economic structure [45,48]. For example, high-density cities face challenges in allocating space for recycling facilities or urban agriculture due to real estate pressures, whereas lower-density regions might struggle to achieve efficient resource loop linkages due to greater distances between waste sources and users [45]. Addressing these context barriers requires metabolic planning that is adaptive—tailoring circular solutions to local system dynamics and continuously monitoring outcomes. In practice, some leading cities (e.g., Amsterdam, Paris) have begun to incorporate urban metabolism indicators into their planning strategies, setting targets for reducing material throughput and enhancing circular self-sufficiency [45]. Such targets are often coupled with investments in metabolic infrastructure (e.g., resource recovery hubs, material innovation clusters) and data systems (like “urban metabolism observatories”) to track progress. The urban metabolism perspective thus operationalizes the integration of circular economy and complexity by treating cities as organisms whose health depends on balanced, closed-loop flows and adaptive capacity to manage those flows over time.

3.4. Policy Innovation and Adaptive Strategies

Achieving systemic circularity in cities demands innovative policy frameworks that reflect the interconnected nature of urban systems. Traditional sectoral policies often fail to account for spillovers and feedback effects—a gap that complexity-informed policy design seeks to fill. One prominent approach is the development of integrated nexus policies addressing water, energy, food and waste in a unified manner. Uddin et al. demonstrate this with a system dynamics model coupling the water–energy–food nexus with circular economy strategies [20,46]. By constructing a causal loop diagram for a city-region, they simulate how interventions (e.g., wastewater reuse in agriculture, renewable energy for water pumping) generate cross-sector benefits and trade-offs [20,49]. The model revealed, for example, that increasing urban food production could strain water and energy systems unless accompanied by measures like rainwater harvesting and energy recovery [20,50,51]. Insights from such dynamic simulations support more adaptive policy-making—officials can test scenarios and identify leverage points where a single policy (such as promoting urban farming) needs complementary actions (like investing in water-saving irrigation) to succeed. This integration of nexus thinking into policy innovation illustrates the value of complexity methodologies (like system dynamics) in crafting robust circular economy policies.

At the urban scale, land use and spatial planning policies are pivotal for enabling circular practices. However, as Williams notes, planning in economically successful cities often operates under market pressures that are misaligned with circular reuse needs [36]. Prime urban land tends to be allocated to high-return developments, which can displace “low-value” circular activities such as recycling yards, repair workshops, or urban farms [36,52,53]. To counter this, forward-looking cities are experimenting with planning innovations. Temporary land use permits and zoning overlays, for instance, have been used in London, Paris and Amsterdam to secure space for circular initiatives on vacant sites [36]. By allowing interim uses like material storage depots or community gardens on land awaiting development, cities create physical hubs for circular economy activity that would otherwise be priced out. Paris’s regional plan goes further by actively planning for industrial land preservation and even re-industrialization in strategic locations to facilitate local material loops (ensuring that producers and users of secondary materials are co-located) [36]. Moreover, municipal procurement policies have been leveraged to stimulate markets for recycled materials—for example, Amsterdam mandates a percentage of reclaimed construction materials in new public projects, which in turn drives demand for local demolition waste processing. These examples of policy innovation highlight a shift toward proactive, facilitative regulation: instead of merely controlling development, planning authorities are incentivizing and orchestrating the conditions for circular systems to emerge.

Crucially, innovative policies must be iterative and reflexive. Given the novelty of circular systems, cities are engaging in policy experimentation through pilot projects and living labs (often in collaboration with academia and the private sector) to test what works before scaling up. This experimental governance aligns with complexity theory’s recommendation of incremental learning and adaptation. It also helps in managing uncertainty and avoiding lock-in to ineffective solutions. Equally important is horizontal policy learning between cities. Transnational networks (such as the C40 Circular Cities network and EU Urban Agenda partnerships) facilitate the exchange of policy innovations, though simple transfer of best practices can be problematic when context differences are high [16,54]. Instead, these forums stress adapting ideas to local complex conditions—essentially, translational innovation rather than copy-paste. In sum, the policy landscape for circular urban development is evolving towards integrated, flexible strategies. By acknowledging systemic interdependencies (nexus approaches), safeguarding space for circular activities, and iteratively refining policies through experimentation and cross-city learning, local governments can better navigate the complexity of urban transitions. Such adaptive policy frameworks serve as the “operating system” for circular economy initiatives, increasing the likelihood that individual projects add up to a coherent, self-reinforcing transformation rather than isolated successes or failures [16,55].

3.5. Participatory Design and Co-Creation

Because urban systems are driven not only by infrastructure but also by human behavior and social norms, engaging stakeholders is central to any complexity-aligned approach. Participatory design in urban planning ensures that the knowledge, values, and feedback of diverse actors inform the transition to circular economy, making interventions more robust and context-appropriate. One notable methodology is the use of Urban Living Labs as arenas for co-creation. Russo et al. describe an iterative five-phase co-creation process—Co-Exploring, Co-Design, Co-Production, Co-Decision, and Co-Governance—implemented in living labs in Naples and Amsterdam [56,57,58]. In these labs, public authorities, businesses, researchers, and community members collaboratively diagnose problems (e.g., “wastescapes” in peri-urban areas), generate eco-innovative solutions, and decide on implementation pathways [56]. The living lab approach embodies complexity principles by treating the city as an open system where interventions are prototyped in real-world conditions with continuous stakeholder learning. The Naples and Amsterdam cases demonstrated that such co-creation not only yielded technical solutions (designs for reusing specific waste streams and regenerating derelict land) but also built mutual trust and shared ownership of outcomes [38,56,59,60,61]. This addresses a frequent gap in sustainability initiatives—lack of community buy-in—by integrating local perspectives from the outset.

Participatory design contributes to systemic change in multiple ways. Socially, it empowers communities and improves equity in decision-making, ensuring that circular economy projects also produce social benefits. Indeed, the literature indicates that participatory planning can reinforce social cohesion, as people coalesce around community gardens, or sharing platforms created through bottom-up efforts [1,22,62]. These co-benefits are important in complexity terms because they represent positive feedback loops: engaged citizens are more likely to support, maintain, and spread circular practices, thereby scaling up the impact. Technically, participatory approaches tap into local knowledge that experts or officials may overlook. For example, residents can identify informal reuse networks or traditional practices of resource recovery that a formal analysis might miss, and these insights can be incorporated into the design of circular systems. Participatory design also tends to enhance adaptive capacity. As stakeholders learn together in a living lab or workshop setting, they become better at responding to new information or unexpected challenges—effectively co-evolving with the system’s changes. This was evident in the REPAiR project’s living labs, where stakeholders iteratively adjusted their strategies (such as refining a composting scheme or redesigning a circular business model) based on intermediate results and feedback during the process [56].

From a governance perspective, participatory design is closely tied to the concept of co-governance. In complex urban systems, no single actor can control all levers of change; instead, networks of city agencies, firms, community groups, and NGOs must govern collectively. Establishing co-governance arrangements—for instance, public–private–people partnerships formalized through charters or task forces—helps institutionalize the outcomes of participatory processes [16]. Cities like Amsterdam have created “circular councils” that include civil society representatives to continue stakeholder dialog beyond one-off projects. Such structures ensure ongoing community input in monitoring and adjusting circular economy initiatives, which is crucial for long-term transformation. However, participatory approaches are not without challenges. They require time, resources, and skilled facilitation to manage conflicts and power imbalances among stakeholders. Some studies note that without careful design, participatory processes can be dominated by the most vocal or powerful actors, potentially sidelining marginalized groups—an outcome contrary to the inclusive ethos of sustainability. To mitigate this, best practices call for transparent processes, capacity-building (so that less-experienced stakeholders can contribute effectively), and sometimes independent mediators to balance interests. When executed well, participatory design in urban planning acts as a social engine for circular economy, aligning grassroots innovation with institutional support. It transforms would-be policy targets (citizens and businesses) into active co-creators of solutions, thereby significantly raising the probability of systemic adoption and cultural shift towards circular living.

3.6. Systems Thinking in Practice: Tools and Methods

Integrating complexity theory into sustainable urban planning is as much a methodological challenge as a conceptual one. A variety of systems thinking tools have been deployed to translate complex interdependencies into actionable insights. These include computational models, network analyses, and hybrid analytics that can handle the multi-layered nature of urban systems. A clear trend in the literature is the use of simulation modeling to capture feedback loops and emergent behaviors. System Dynamics (SD) models, for example, are increasingly used to inform urban circular strategies. By coding stocks and flows of resources alongside governance or behavioral variables, SD models enable planners to conduct “what-if” experiments on policies. Uddin et al.’s coupled nexus model noted above is one such application, illustrating how a change in one part of the system propagates through others [20]. Another example is the use of agent-based models, which simulate individual actors (households, firms) and their interactions. While none of the foregoing cases explicitly used agent-based modeling, the approach has been applied elsewhere to study, for instance, how consumers might adapt to circular services (like product-sharing schemes) under different incentive scenarios. These models embrace heterogeneity and adaptation, hallmarks of complexity, by letting agents learn or evolve their strategies over time. Likewise, network analysis has proven valuable in mapping urban metabolisms and symbiosis opportunities. Material flow networks can be analyzed to identify central nodes (key waste sources or resource hubs) and critical links, informing infrastructure placement for recycling or redistribution. In bibliometric mapping of the research field itself (as conducted in this study’s review), co-occurrence networks of keywords highlight the conceptual linkages—for instance, showing “systems thinking” as a bridge between “urban resilience” and “resource efficiency” [18], which corroborates the thematic integration discussed here.

To illustrate the range of methods, we summarize a few complexity-oriented techniques that have been applied to sustainable urban planning:

Causal Loop and Stock-Flow Modeling (System Dynamics): Used to simulate and visualize feedback processes in urban resource systems, such as the interaction of circular policies with water–energy–food flows [20,63,64]. SD models help identify leverage points and potential unintended consequences (e.g., how increasing recycling might affect industrial input demand or waste sector jobs).

Hybrid Life Cycle Assessment + Machine Learning: A novel methodology couples life cycle thinking with artificial intelligence to handle data complexity in urban metabolism studies [11,12]. By training neural networks on metabolic datasets, researchers can predict outcomes under data-limited conditions and capture non-linear relationships, enhancing the decision-support for circular interventions.

Complexity-Based Indices and Metrics: Borrowing concepts from ecology, indices of urban system health (resilience, diversity, connectivity) are being developed. For instance, an urban resilience index drawing on diversity and robustness metrics was applied to a Chinese city-region to quantify its adaptive capacity [3,39]. Such metrics allow planners to measure abstract attributes of complexity and track improvement (e.g., increasing diversity of economic activities in circular sectors could indicate a more resilient local economy).

Machine Learning and Data Analytics for Policy Design: Beyond physical flows, machine learning has been used to explore complex policy-performance relationships. Arranz et al. employed artificial neural networks and decision tree algorithms on a dataset of firms to discover non-linear patterns in how multiple policies jointly affect circular innovation uptake [33]. The analysis revealed threshold effects and synergies that traditional linear models would miss, thereby guiding policymakers on optimal intensity and mixes of interventions [33].

These tools demonstrate the growing capacity to operationalize systems thinking. The proliferation of digital data (e.g., smart city sensors, open data portals) further enriches the potential of complexity tools by providing real-time feedback loops—a city can monitor energy use, waste generation, traffic flows in real time and adjust interventions dynamically, moving toward a cybernetic planning model.

However, implementing these sophisticated methods in practice is not without difficulties. One recurring limitation is data quality and availability. Urban metabolism assessments often suffer from fragmented data, requiring assumptions that introduce uncertainty [11]. Machine learning can partly compensate by handling missing data, but reliable long-term monitoring systems are needed for continuous improvement. Another challenge is the interpretability and communication of complex models. Planners and policymakers may find it hard to act on insights from an AI model or a dense causal loop diagram. Thus, an emerging skill set for urban planners is to become “translators” of complexity science—simplifying and visualizing results in accessible ways (e.g., dashboards, scenario narratives) to inform stakeholders. Encouragingly, the literature documents instances where such translation is successful. For example, in one city, the results of an agent-based simulation of waste sorting behavior were presented through an interactive role-playing workshop with residents, leading to higher public understanding and acceptance of a new recycling policy. This kind of participatory modeling closes the loop between systems analysis and human action. Overall, the infusion of systems thinking tools in urban planning is supporting a shift from reactive planning to anticipatory governance, where interventions are tested virtually and iteratively refined. This improves the strategic agility of city planners faced with complex objectives like circularity and sustainability.

3.7. Implications for Systemic Urban Transformation

Bridging circular economy and complexity theory within urban planning frameworks is not a purely academic exercise—it directly supports the goal of systemic urban transformation. By acknowledging cities as complex adaptive systems, planners and decision-makers can foster transformations that are deep, enduring, and capable of handling future uncertainties. One key implication is the enhancement of urban resilience. A complexity-guided circular approach tends to build in redundancies and diversification (for example, multiple sources of critical resources, diversified economic activities around reuse and repair, modular infrastructure systems) which make urban systems less prone to collapse when stressed [17,23]. This was evident during recent disruptions: cities with local circular supply chains (such as community-supported agriculture or distributed manufacturing via makerspaces) coped better with global supply shocks, an outcome predicted by complexity/resilience theory. Moreover, the integration of circular principles (like closing loops) inherently promotes sustainability co-benefits—reduced pollution, lower carbon emissions, and resource security—that improve a city’s long-term livability and ecological stability. Complexity theory adds to this the emphasis on adaptive capacity: the ability of urban communities and institutions to learn and reorganize in response to change. Thus, a city that incorporates feedback mechanisms (through continuous monitoring, public participation, and agile governance) is not only becoming circular but also becoming smarter and more responsive. It can iteratively refine its policies and systems (a process akin to evolutionary adaptation), which is crucial as climate change and socio-economic shifts present moving targets.

Another implication is the need for transdisciplinary collaboration in driving urban change. The convergence of circular economy and complexity thinking naturally blurs professional and sectoral boundaries—engineers, ecologists, economists, sociologists, and computer scientists all have roles in designing and managing circular urban systems. This recognition has already started to reshape how projects are implemented. For instance, many cities now establish cross-departmental teams or innovation units (sometimes called “urban labs”) that bring together waste management experts with digital technologists and community organizers to co-design solutions for, say, circular neighborhoods. Such teams reflect a departure from the siloed departmental approach, resonating with the complexity insight that system-wide problems require system-wide perspectives. At the policy level, this is encouraging the formation of new governance bodies (e.g., circular economy task forces, resilience offices) that sit at the nexus of different municipal functions. It also calls for capacity-building and education: urban planners are supplementing their expertise with systems science skills, while scientists are becoming more literate in policy processes—fostering a common language to address urban sustainability challenges.

Conceptually, the integration of circular economy and complexity theory contributes to a paradigm shift in how we define urban success. Rather than evaluating progress solely through linear metrics like GDP growth or waste tonnage reduced, a systemic transformation perspective asks: is the city becoming more regenerative, more equitable, and more adaptable over time? These are composite outcomes. For example, regenerative urban development means that economic activity not only minimizes harm (zero waste) but positively restores ecosystems (net positive impact)—something achievable only by aligning multiple system components (industry, consumers, nature) in synergy. Complexity theory provides the analytical tools to understand synergy and emergent properties, while circular economy provides the practical blueprint to pursue them (through circular business models, regenerative design, etc.). Cities at the forefront of this integration, such as Amsterdam, Copenhagen, and Shanghai, are crafting new evaluation frameworks accordingly. They are setting targets for circular material use, tracking system resilience indicators, and creating feedback channels like annual “state of the circular city” reports that inform policy adjustments [37,38,49,55,64].

Finally, the co-integration of these ideas supports a broader narrative of systemic change—one that moves away from incremental greening to transformative reconfiguration. It is increasingly recognized that linear, extractive urban development cannot simply be tweaked; it must be fundamentally rethought. Complexity theory assures us that when a system reaches a tipping point, phase change becomes possible—in urban terms, this could mean a rapid uptake of circular practices once economic, social, and regulatory conditions align. The current literature and real-world experiments suggest we may be nearing such inflection points in certain domains (for instance, the convergence of digital fabrication and circular material use is rapidly changing construction practices in some cities, pointing to a possible leap in circular construction). By actively integrating complexity and circularity, city planners and leaders are effectively engineering the tipping points: they are creating the networks, diversity of solutions, and feedback-rich environments that allow niche innovations to scale and a new stable state to emerge. The end-state vision is a circular urban system that is resilient, low-carbon, and socially inclusive—an embodiment of sustainable development. Achieving this will require persisting with the integrated approach outlined in this discussion: governing adaptively, planning holistically for urban metabolisms, innovating policy across silos, engaging stakeholders at every step, and leveraging advanced tools to inform decisions. The research reviewed here offers a roadmap and an empirical basis for that journey. Each case study, model, and framework contributes a piece to a puzzle that urban practitioners are now assembling: a picture of cities that thrive within planetary boundaries by design, not by mere chance or isolated effort. The task ahead is to continue translating this rich, complex knowledge into on-the-ground transformation, learning and evolving as our cities themselves do.

3.8. Indicators of Circularity in Urban Systems

Cities transitioning toward circular economy paradigms require robust metrics to gauge progress across complex systems. However, the literature indicates a proliferation of overlapping indices and frameworks, leading to an “excess of indicators” that can dilute focus and complicate assessment [37]. Developing effective circularity indicators for urban systems is challenging due to the multifaceted nature of cities: the built environment involves long-lived assets, diverse materials, and multiple stakeholders, making standardized metrics difficult to apply [37]. Complexity theory underscores that no single metric can capture the adaptive, multi-dimensional performance of a circular city, necessitating composite indicators and integrated assessment approaches.

Recent efforts have aimed to design indicators and frameworks that reflect the systemic and dynamic characteristics of urban circularity. Many existing metrics prioritize quantitative measures (e.g., material throughput or waste reduction), yet advanced approaches blend quantitative and qualitative data using combinations of observations, measurements, and calculations [37]. For example, the Material Circularity Indicator (MCI) has been proposed as a sophisticated multi-factor metric, evaluating a product’s circularity by measuring inputs of virgin versus recycled material, unrecoverable waste outputs, and the extension of product lifespans [37]. Adaptations of such indicators to the building and city scale (e.g., Building Circularity Indicators) illustrate how assessing circular performance involves analyzing complex interactions of material flows and design choices in an urban context [37]. Importantly, holistic frameworks have emerged to guide urban circularity assessments at multiple scales. This integrative approach explicitly links circularity targets to triple-bottom-line outcomes, ensuring that economic, environmental, and social dimensions are concurrently evaluated in measuring urban circularity. By employing such multidimensional and hierarchical indicator systems, urban planners can better capture the complex feedbacks and trade-offs inherent in circular transitions, aligning metrics with the adaptive and emergent behavior of urban systems.

3.9. Regenerative Economy and Urban Resilience

A key evolution in circular economy thinking is the shift toward a regenerative urban economy that not only recirculates resources but also actively restores natural systems. Cities currently consume the majority of global resources and generate a disproportionate share of waste and emissions, making the need for a regenerative approach evident [19]. In practice, a regenerative circular economy in cities means that “wasted” resources are continuously looped back into use and the ecological regenerative capacity of urban systems is enhanced alongside their adaptive capacity. This approach seeks to rebuild environmental capital (e.g., improving soil, air, and water quality) and strengthen the resilience of urban ecosystems, resulting in healthier cities with low levels of resource consumption and waste generation [25,26,31].

Unlike narrow efficiency-driven models of circularity, a regenerative perspective embraces broader socio-ecological goals. Traditional circular economy initiatives have often been critiqued for a predominantly neoliberal focus on efficiency and profit, whereas the circular development pathway emphasizes “wider societal goals” aimed at improving the health of both the urban ecosystem and its inhabitants [33,53,54]. This paradigm entails not just reducing resource use but also undertaking ecological restoration as a core strategy. For instance, circular development strategies achieve their aims through simultaneous reduction in consumption and wastage (via looping resources and other adaptive actions) and the proactive regeneration of urban ecosystems. Such actions yield multiple co-benefits—ecological improvements, public health gains, and community well-being—embedding circular economy initiatives within a broader socio-ecological transition. Complexity theory reinforces this view by suggesting that fostering diversity and regenerative feedback in urban systems enhances resilience, an emergent property of complex adaptive systems [46,49,64].

In practical terms, moving toward a regenerative urban economy requires reorienting planning and design to support restorative processes. The circular development approach prioritizes concrete measures like reuse, recycling, and energy recovery from residual waste streams, while also enhancing urban ecosystem services (e.g., water, nutrient and biomass cycling through green infrastructure). Urban form and infrastructure are re-envisioned to be “adaptive, enabling urban systems to evolve with changing needs, whilst minimizing the wastage of resources”. Crucially, “looping, regenerative and adaptive actions are central to circular development” efforts, highlighting that continuous learning and adjustment are built into the system. This regenerative ethos aligns with complexity-informed planning by building the capacity of urban systems to absorb shocks and self-organize in the face of change, thereby contributing to long-term urban resilience [12,57,60].

3.10. Urban Metabolism and Circular Resource Flows

The concept of urban metabolism provides a useful lens for understanding energy and material flows in cities and for guiding circular economy strategies. Urban metabolism analogizes a city to a living organism that requires continuous inputs of resources (energy, water, materials) and produces outputs (waste, emissions) to sustain its functions [22]. Conventional urban metabolic flows have historically followed a linear trajectory—resources are imported, consumed, and discarded—leading to significant waste and environmental impacts. By analyzing a city’s metabolism, decision-makers can identify inefficiencies and intervention points to “maximize benefits and minimize resource waste, thus promoting a transition from linear to circular and more sustainable systems” [36]. In a circular economy context, the aim is to redesign these metabolic flows so that outputs from one process become inputs for another, mimicking closed-loop ecosystems. This requires comprehensive accounting of energy and material stocks and flows in urban systems, often through methods like Material Flow Analysis and life-cycle assessment, to track how resources circulate or leak out of the urban system.

Taking a metabolic perspective also highlights the interdependence of different resource streams and the importance of cross-sectoral integration. The flows of water, energy, food, and materials in a city are tightly interconnected, and changes in one domain can propagate across others in complex cause–effect chains. Recent studies emphasize that monitoring the linkages between different urban flows is an “innovative strategy for increasing synergy between urban cores and their surrounding areas, fostering processes of ecological transition and climate resilience” [56]. For example, industrial symbiosis initiatives at the city-region scale illustrate metabolic synergy: waste heat from power generation can be used to warm buildings or greenhouses, treated wastewater can irrigate urban green spaces, and organic waste can be composted into fertilizer or converted to biogas. These integrated solutions generate multiple benefits simultaneously—reducing waste disposal, lowering demand for virgin resources, and enhancing urban environmental quality—demonstrating the systemic value of a metabolic approach [8].

Methodologically, complexity-informed tools such as system dynamics modeling are increasingly employed to capture and manage urban metabolic interactions. System dynamics provides a simulation-based framework to couple multiple resource sectors and human activities, reflecting the feedback-rich nature of urban systems [20]. For instance, in the context of the water–energy–food (WEF) nexus, dynamic models have been used to “interconnect WEF in a closed loop so that resource use is limited and GHG emissions are reduced”. Such models can illustrate how saving water (through recycling) also conserves energy (by reducing pumping and treatment needs) and improves food security (by ensuring water for agriculture), all while shrinking the city’s ecological footprint. By embracing the urban metabolism framework and employing computational tools to map resource loops, planners can better anticipate unintended consequences and design synergistic interventions [20]. This aligns with complexity theory’s emphasis on feedback and adaptive management: treating the city as a metabolic network encourages continuous monitoring and adaptation of resource flows, ultimately supporting a more resilient and low-carbon urban system.

3.11. Digital Integration in Circular Urban Planning

Implementing circular economy principles in the complex milieu of cities increasingly relies on digital tools and data-driven approaches. Information and Communication Technologies (ICT) offer powerful capabilities to monitor and optimize urban processes in real time, which is crucial for managing the complexity of circular urban systems [19,49]. Smart city infrastructures—sensors, Internet of Things networks, data platforms, and decision support systems—can track resource flows (energy, water, waste) and environmental conditions at fine scales, providing the feedback needed to detect inefficiencies and intervene adaptively. By exploiting these ICT potentialities, cities can better coordinate the numerous moving parts of a circular economy, from sharing platforms and waste collection logistics to energy grid balancing and material recycling networks. In essence, digital integration serves as a nervous system for the circular city, linking disparate subsystems and enabling more holistic, responsive management.

Empirical research on “smart” sustainable districts underscores the centrality of data management and scale in successful circular initiatives. A recent scoping review of ICT-enabled circular projects found that effective data management is “a central issue in the optimization of urban processes”, and that the district scale often represents an optimal testbed for innovative circular solutions [19,29]. At this mesoscale, digital platforms have been used to integrate physical infrastructure (e.g., smart grids, waste-to-resource facilities) with virtual infrastructure (information systems, data analytics) and stakeholder interfaces (apps, dashboards) that encourage community participation in circular practices. Key elements identified include not only the technologies themselves, but also the governance of data (standards, openness) and tools for user engagement, which together ensure that the insights from digital systems translate into on-the-ground behavioral and institutional change. These findings highlight that technological innovation must be paired with social innovation—engaging citizens, businesses, and public agencies through transparent information-sharing—to realize the full potential of circular strategies [19].

Beyond isolated applications, integrated digital frameworks are emerging to support systemic planning for circular urban transitions. One example is the Spatial Planning Information Management System (SPIMS), a conceptual model designed to “streamline information integration and stakeholder participation in urban planning”. SPIMS and similar platforms consolidate diverse data streams (e.g., material flow inventories, economic indicators, social data) into a unified dashboard, enhancing decision-making by giving planners a comprehensive, real-time picture of urban sustainability performance. Such systems align with sustainability and complexity principles by integrating environmental, social, and economic factors into a “dynamic, adaptable framework capable of responding to urban challenges” [18,20,21]. Notably, these platforms promote transparency and inclusivity in governance: by design, SPIMS emphasizes open information access and broad stakeholder inclusion, which are key to fostering resilient and equitable outcomes. In parallel, advanced modeling techniques complement these information systems; for instance, system dynamics models have been developed to analyze synergies among production, consumption, and ecological subsystems in cities, allowing planners to simulate the long-term impacts of circular policies before implementation. By leveraging digital integration—from big data analytics to participatory planning platforms—urban stakeholders can navigate the complexity of circular transitions with greater foresight and coordination, creating feedback loops that continuously refine strategies in pursuit of systemic sustainability [26,32].

3.12. Environmental Justice and Inclusivity in Urban Circular Transitions

For a circular economy transition to truly contribute to systemic urban sustainability, it must embed principles of environmental justice and social inclusivity. Contemporary urban circular economy strategies increasingly acknowledge that cities should become not only resource-efficient and resilient, but also equitable and inclusive in their outcomes. This represents a shift from earlier conceptions of the circular economy that often underplayed social dimensions; indeed, scholars have noted that a major barrier in prevailing CE definitions has been the insufficient inclusion of explicit social goals. Addressing this gap is critical because without deliberate attention to equity, circular interventions could inadvertently perpetuate or even exacerbate existing urban disparities. Complexity theory supports this comprehensive outlook by emphasizing the intertwined nature of social, economic, and environmental subsystems in cities—sustainable transformation cannot be achieved if any one of these dimensions is neglected or if benefits are unevenly distributed [65,66].

The imperative for inclusivity is underscored by the persistent inequalities observed in many urban environments. In practice, marginalized communities often have disproportionately poor access to basic services and infrastructure, making them more vulnerable to environmental and health risks. Linear urban development has historically burdened these groups with problems like pollution, inadequate sanitation, and lack of green space, while affording them few of the benefits of economic growth. A circular urban economy must consciously seek to reverse these trends by ensuring that improvements in resource efficiency and environmental quality reach all segments of society. For example, if a city implements circular waste management (such as recycling or bioenergy projects), it should be performed in a way that also improves conditions in underserved neighborhoods (e.g., by reducing illegal dumping or creating local green jobs), rather than only in affluent areas. Likewise, the placement of circular infrastructure (recycling centers, urban farms, repair workshops) should be planned with community input to avoid concentrating any negative externalities and to maximize local benefits. As noted in recent studies, planning processes need to “integrate health and environmental considerations” with a focus on extending sustainable infrastructure to all sectors of society, reflecting a commitment that no community is left behind in the transition [67,68].

Achieving such inclusive circular transitions requires new modes of governance and public participation. City authorities and planners are increasingly experimenting with participatory approaches to co-design circular solutions, engaging residents—especially from historically underrepresented groups—in decision-making. Empowerment through inclusion has proven effective in some contexts—for instance, involving community members and students in co-creating sustainability initiatives has helped “develop a shared vision” and fostered a sense of ownership over local circular projects. These collaborative processes not only yield interventions better tailored to community needs but also build social capital and trust, which are essential for the adaptive governance of complex urban systems. Moreover, ensuring diversity in stakeholder participation brings a variety of perspectives and knowledge into the planning process, increasing the likelihood of innovative and robust solutions to urban challenges. In the language of complexity science, broad stakeholder inclusion can be seen as a way to increase the diversity of agents and feedback loops in the system, thereby enhancing its capacity to learn and self-correct [69,70,71,72]. Ultimately, prioritizing environmental justice and inclusivity transforms the circular economy from a purely technical endeavor into a form of just urban transition, whereby the pursuit of sustainability also advances social equity and democratic engagement. This alignment is crucial for legitimacy and long-term success: a circular city that is also a fair and inclusive city is far more likely to sustain the collective effort required for deep, systemic transformation [65,66,67].

4. Conclusions

This systematic literature review examined how circular economy (CE) and complexity theory (CT) converge within sustainable urban planning (SUP), based on an analysis of 71 peer-reviewed articles. The findings reveal that the integration of CE and CT is operationalized through five thematic pillars: (i) circular governance and institutional frameworks; (ii) urban metabolism and regenerative design; (iii) adaptive planning strategies; (iv) digital integration for real-time decision-making; and (v) justice and inclusivity as foundational goals.

Across these pillars, the research confirms that urban sustainability transitions are more effective when circular initiatives are embedded in complexity-informed planning practices. CE provides clear normative objectives—such as resource efficiency, closed-loop systems, and ecological regeneration—while CT offers a dynamic process framework that emphasizes adaptability, feedback loops, and interconnected systems. This convergence redefines urban planning from a linear, sectoral logic toward systemic transformation models that view cities as complex adaptive systems.

From a theoretical standpoint, the review contributes to the growing literature that conceptualizes “circular cities” as socio-ecological systems characterized by resilience, self-organization, and continuous learning. It challenges traditional urban planning paradigms and supports a paradigm shift toward integrated, multi-scalar approaches aligned with planetary boundaries and long-term urban regeneration.

On a practical level, the review identifies key priorities for policymakers and urban practitioners: adopting polycentric and participatory governance structures; using systems-thinking tools to identify leverage points and avoid siloed interventions; and adapting urban design and infrastructure to support local resource loops, circular entrepreneurship, and nature-based solutions. These insights are relevant for cities aiming to implement circular transitions that are both systemic and socially inclusive.

Despite the comprehensive scope of the study, limitations must be acknowledged. The analysis is based on peer-reviewed literature, mainly in English, which may exclude practical insights from the gray literature or non-English sources. Additionally, the field is still emerging and heterogeneous in terminology and methodologies, limiting the comparability of some studies.

Future research should focus on empirical validation of theoretical insights through longitudinal case studies in diverse city contexts. There is also a need to refine performance metrics that can capture the dynamic and multidimensional nature of circular and complex urban systems. Moreover, further exploration of governance models, socio-political drivers, and the integration of digital technologies within complexity-informed planning will be essential for advancing both theory and practice.

Ultimately, this review underscores that the convergence of CE and CT offers a robust foundation for navigating the complexity of urban sustainability transitions. Embracing this integrative perspective can support cities in building resilient, regenerative, and inclusive futures.