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Municipal leadership has become increasingly central to addressing global challenges such as war-related displacement, migration governance, and climate change, reflecting a broader shift toward polycentric and networked forms of multilateralism. This study examines how cities have expanded their international roles over the past decade, responding to governance gaps with pragmatic, people-centred action. Using a qualitative, theory-informed comparative case study design, it draws on three original case studies grounded in direct practitioner experience: European municipal cooperation supporting Ukraine during war; city engagement in shaping the Global Compact for Migration; and municipal leadership in advancing climate action and the emerging climate mobility agenda. Across these cases, the analysis identifies consistent patterns of multi-scalar municipal agency, including decentralized humanitarian action, norm-setting in international negotiations, and innovations in multilevel climate governance. Cities leverage transnational networks—such as the Mayors Migration Council and the C40 Cities Climate Leadership Group—to amplify political influence, exchange solutions, and secure resources, even as fiscal pressures and political polarization increasingly constrain local capacity. It concludes that cities are becoming important actors in shaping global governance, yet their effectiveness depends on institutionalized representation, enhanced fiscal autonomy, and stronger protections for local leaders. Embedding municipalities more fully within evolving multilateral architectures can better align global commitments with local implementation and improve the resilience and legitimacy of international policy coordination.

The UN Paris Agreement of November 2016 recognises the need for a ‘cleaner and more efficient energy system’ as a core policy goal to address climate change. The spatial and urban form of cities is a key factor in achieving more efficient energy production and consumption and becomes more important with rapid urbanisation across much of the world. City urban form and planning are therefore potentially powerful levers for the energy transition. This paper examines the extent to which city ‘energy strategies’ address the critical spatial and urban form characteristics of cities as a means to achieve a more efficient energy system. We construct an assessment framework of key aspects of the spatial and urban development of cities related to transport and accessibility and urban form. The framework is used to assess the degree to which energy strategies take into consideration aspects of urban development in four cities that are taking significant action on the energy policy: Hong Kong Oakland, Oslo, and Vancouver. We conclude that in these cities there is only fragmentary consideration of the potential of shaping spatial and urban form in the interests of energy efficiency.

Cities are increasingly expected to achieve environmentally sustainable outcomes while simultaneously adapting to rapid technological transformation and growing governance complexity. However, sustainability performance in urban systems cannot be explained by technological infrastructure alone. Institutional capacity and algorithmic governance capabilities play a critical role in shaping coherent environmental policy implementation and green urban performance, particularly in transition city contexts. This study proposes the ISAG-G Governance Framework (Institutional and Smart Algorithmic Governance for Green Performance), a governance-oriented analytical framework designed to assess green urban governance capacity. The framework integrates four governance dimensions: institutional governance capacity, algorithmic and digital governance enablement, green urban governance performance, and citizen sustainability interaction. Methodologically, the study develops a composite governance index based on a structured indicator system. Indicator weights are determined using the Best–Worst Method (BWM) through expert consultation, while Min–Max normalization and weighted aggregation are applied to construct the composite index. The framework is empirically applied through a comparative analysis of five transition municipalities (evidence from Armenia) representing different levels of administrative capacity and urban development. The findings reveal distinct governance profiles across municipalities and highlight the importance of institutional coherence and algorithmic governance capacity in shaping green urban performance. By moving beyond infrastructure-centric approaches, the proposed framework provides both an analytical and policy-oriented tool for evaluating urban sustainability governance in transition city contexts.

Artificial intelligence has become constitutive of smart city governance, yet data and algorithmic challenges remain analytically separated in existing scholarship, obscuring their recursive coupling and consequences for the built environment. This review synthesises 82 peer-reviewed studies (2020–2025) drawn from a deduplicated corpus of 876 records, combining PRISMA-guided methodology with VOSviewer and CiteSpace bibliometric mapping. Annual output rose from 78 publications in 2020 to 224 in 2024, with ten leading countries contributing roughly 84% of the corpus. The keyword network organises into five thematic clusters spanning AI technical foundations, data governance, algorithmic governance, sustainability, and built-environment governance; emerging 2023–2025 couplings between digital twin and SDG 11, and between generative AI and SDG 11, mark a shifting research frontier, while the algorithmic governance → SDG 16 linkage constitutes the strongest single ribbon in the synthesis. The study advances a double-helix coupling mechanism specifying directional propagation, reverse modulation, and structural cross-linking between data and algorithmic strands, reframing building energy management, digital-twin operation, and smart infrastructure as governance arrangements whose sustainability legitimacy depends on the simultaneous integrity of both strands.

Smart cities are rapidly gaining momentum around the world as new opportunities to shift towards a sustainable urban future. Despite their promising solutions, there is so far little evidence on how smart city initiatives can achieve urban sustainability. This study explores the impact of smartness on urban sustainability by introducing the concept of smart complementarity and investigating whether the systemic governance of smart complementarities has a positive impact on sustainability. To this end, we employ a panel vector autoregression model with panel data for 26 smart cities from 2009 to 2019 to test the complex dynamic relationships between smart city drivers and dimensions of sustainability. Such analysis seems crucial for smart city governance and whether the vision of a smart agenda is compatible with urban sustainability. The findings suggest that while smart city initiatives have improved economic sustainability, they have compromised environmental and social sustainability. This points to the need for a coordinated approach to address the complexity of urban systems and sustainability challenges.

The fusion of Artificial Intelligence and the Internet of Things (AI-IoT, also widely referred to as AIoT) offers transformative potential for smart cities, yet presents a critical challenge: how to process heterogeneous data streams from intelligent sensing—particularly crowd sensing data derived from citizen interactions like text, voice, and system logs—into reliable intelligence for sustainable urban governance. To address this challenge, we introduce the Intelligent Multimodal Ticket Processing System (IMTPS), a novel AI-IoT smart system. Unlike ad hoc solutions, the novelty of IMTPS resides in its theoretically grounded architecture, which orchestrates Information Theory and Game Theory for efficient, verifiable extraction, and employs Causal Inference and Meta-Learning for robust reasoning, thereby synergistically converting noisy, heterogeneous data streams into reliable governance intelligence. This principled design endows IMTPS with four foundational capabilities essential for modern smart city applications: Sustainable and Efficient AI-IoT Operations: Guided by Information Theory, the IMTPS compression module achieves provably efficient semantic-preserving compression, drastically reducing data storage and energy costs. Trustworthy Data Extraction: A Game Theory-based adversarial verification network ensures high reliability in extracting critical information, mitigating the risk of model hallucination in high-stakes citizen services. Robust Multimodal Fusion: The fusion engine leverages Causal Inference to distinguish true causality from spurious correlations, enabling trustworthy integration of complex, multi-source urban data. Adaptive Intelligent System: A Meta-Learning-based retrieval mechanism allows the system to rapidly adapt to new and evolving query patterns, ensuring long-term effectiveness in dynamic urban environments. We validate IMTPS on a large-scale, publicly released benchmark dataset of 14,230 multimodal records. IMTPS demonstrates state-of-the-art performance, achieving a 96.9% reduction in storage footprint and a 47% decrease in critical data extraction errors. By open-sourcing our implementation, we aim to provide a replicable blueprint for building the next generation of trustworthy and sustainable AI-IoT systems for citizen-centric smart cities.

Megacities in the Yangtze River Economic Belt (YREB) are facing severe challenges and unbalanced development. Combating megacity syndrome is crucial for achieving modernization. This study developed a Development-Autonomy-Inclusiveness governance framework to characterize megacity governance capacity modernization (MGCM). The integrated model is employed to evaluate the MGCM for nine megacities along the YREB in China from 2013 to 2022. The key determinants are identified by Geo-detector. The configuration pathways and synergistic mechanisms for high MGCM are depicted using fsQCA. The empirical study indicates that: (1) The MGCM is at a low level but displays a slight upward trend, with development capacity > autonomy capacity > inclusiveness capacity. The MGCMs of three urban agglomerations manifest as being development-driven, autonomy-constrained, and autonomy-promoted. (2) The synergistic interaction among determinants is greater than any single factor. (3) Megacities exhibited distinct pathways to achieve high MGCM: tri-capacity synergy pattern in the Yangtze River Delta, development dominant pattern in Chengdu-Chongqing, autonomy weakness pattern in the Mid-Yangtze River, and adversity survival pattern during extraordinary periods. A novel theoretical framework and practical examples are proposed for boosting the modernization of governance capacity in China’s megacities, offering valuable insights for advancing the governance modernization of megacities worldwide.

The article consists in an in-depth interpretative study of Smart City in the case of the Special Administrative Region of Hong Kong, China. It proposes a framework of analysis as a heuristic tool to interpret narratives in general and those of Smart City Hong Kong in particular. The capacity of a narrative to confer meaning draws upon three criteria: its originality (degree of endogeneity); its sincerity (internal validity and trustworthiness), and its extension (its ability to provide a convincing account to the outside world for social phenomena). They are also affected by the form of diffusion and communication. Four types of account emerged from our empirical investigation: survey responses; written responses from official agencies; face to face interviews; and collective interviews in focus groups. By reconstituting chains of meaning in relation to the Smart City, the article interrogates the utility of technology, sustainability and e-governance narratives for public administration. Taken as a whole, Smart City appears as a rather hollow narrative, an empty signifier, a general term lacking clear meaning.

This study examines the paradox in Jakarta’s smart city governance through the case of Citayam Fashion Week (CFW), a grassroots urban phenomenon initiated by digital-native youth. While urban digital transformation is intended to promote inclusivity and innovation, the inconsistent responses from local authorities reflect governance fragmentation, hindering the organic development of creative digital communities. Using qualitative analysis of secondary data, including online reports and academic sources, the study reveals that government policies often fail to integrate cultural and social dimensions into smart city frameworks. The findings emphasize the need for more adaptive, participatory governance models that acknowledge the evolving digital landscape. This research contributes to discussions on smart city governance, digital youth participation, and urban policy adaptation in a global context.

This paper investigates how social value is operationalised in urban regeneration and how digital reporting platforms shape the measurement and governance of social sustainability. Drawing on semi-structured interviews with UK social value professionals and a resident survey conducted within the Elephant and Castle regeneration programme in London, the study examines how platform-based systems translate procurement commitments into auditable performance categories. These systems embed predefined classification schemas, proxy valuation metrics and rule-based validation procedures that structure how outcomes become visible and comparable across projects. The findings indicate that digital reporting platforms enhance oversight and inter-project benchmarking but prioritise outcomes that align with measurable procurement indicators. Employment generation, apprenticeships and local procurement expenditure dominate reported performance, while relational and place-based outcomes, such as trust, belonging and neighbourhood continuity, remain marginal. Reporting requirements generate substantial evidencing burdens across supply chains, may introduce data distortions through proxy-based and threshold-led reporting, and can concentrate engagement at early project stages, limiting sustained community influence and creating technical barriers to participation. The analysis highlights how digital reporting platforms can operate as governance infrastructures within smart city environments, shaping what is prioritised, funded and recognised as credible impact. The findings provide practical insights for the design of more inclusive and proportionate digital accountability systems for sustainable local development.