Bridging the socio-technical lag: a systematic literature review of regulation, collaboration, and inclusive governance in smart city infrastructure

1 Introduction

Contemporary urban governance operates under the dual pressures of population agglomeration and resource constraints. Consequently, driving the digital and intelligent transformation of municipal infrastructure has emerged as a vital research domain in global public administration. Supported by emerging information technologies (EITs)—such as the Internet of Things (IoT), digital twins, and building information modeling (BIM)—the application scope of the digital built environment continues to expand (Aldehim et al., 2025). These tools offer tangible value. They optimize urban operational efficiency and bolster infrastructure resilience against complex public events, macroscopically advancing the United Nations Sustainable Development Goals (specifically SDG 9 and SDG 11) (Allan et al., 2024). Rapid engineering advancements now enable the technological reinvention of traditional urban spaces via massive sensor networks and data flows. However, realizing these benefits requires aligning computational tools with civic participation (Gün, 2023) and addressing socioeconomic sustainability, particularly in diverse regional contexts such as Southeast Asia (Sohaimi et al., 2025).

A narrative dominated by technological determinism has long steered the theoretical trajectory of smart city research (Nochta et al., 2021). This perspective reduces the city to a pure engineering system manageable via algorithmic optimization and hardware deployment, thereby obscuring the complex social and political attributes inherent to urban governance (Charitonidou, 2022). However, empirical evidence increasingly demonstrates that isolated technological interventions fail to resolve structural governance challenges. Hardware accumulation divorced from institutional foundations often spawns new risks across data collection, cross-departmental coordination, and resource allocation (Lotfi-Jam, 2025). Drawing on socio-technical systems theory, effective smart city governance requires continuous mutual adaptation and co-evolution between technological innovation and social elements (Zhai and Gao, 2024). When this alignment fails, a pronounced “socio-technical lag” emerges, wherein the rapid iteration of engineering applications drastically outpaces the evolution of public management institutions (Mondschein et al., 2021). Institutional context decisively shapes how digital governance materializes (Tomor et al., 2021); therefore, treating the smart city merely as a digital control platform is fundamentally inadequate. Researchers must recenter institutional design, organizational collaboration, and social value as core analytical dimensions of urban digital transformation (Mortati et al., 2025).

This relative institutional lag manifests centrally across three intertwined public administration dimensions. In the regulatory dimension, the ubiquitous deployment of sensor networks and the aggregation of massive urban data pose severe tests to traditional data ownership, privacy boundaries, and information interoperability (Shaffer, 2021). The absence of systematic data governance policies not only risks vendor lock-in but also triggers public trust crises regarding information abuse and concerns over algorithmic surveillance (Alvarez et al., 2022). Operationally, siloed structures within traditional bureaucracies obstruct the data sharing and cross-domain collaboration required by digital infrastructure. Existing public-private partnerships (PPPs) often encounter transparency challenges stemming from the opacity of algorithmic decisions when handling complex digital projects, highlighting the urgency for local governments to optimize platform governance architectures (Gupta et al., 2020). Normatively, prohibitive technological retrofitting costs and the unequal distribution of spatial infrastructure exacerbate digital exclusion (De Jaeger and Swerts, 2026). Top-down technocratic management models often reduce citizens to mere data generators, weakening bottom-up social inclusion and substantive public participation. This dynamic has consequently provoked extensive academic debate over “the right to the digital twin city” and spatial justice (Sharma et al., 2023). Addressing these deep-seated inequalities requires revitalizing urban governance through municipal empowerment and decolonial perspectives, a shift that is especially critical in emerging and non-Western urban landscapes (Alhowaily, 2023).

Given these theoretical conflicts and practical challenges, systematically synthesizing literature on digital urban infrastructure across policy regulation, organizational collaboration, and social equity is critical. While previous systematic reviews have extensively mapped the technical architectures of smart cities or isolated sector applications, they rarely provide a structured critique from an institutional public administration perspective. To address this unresolved theoretical gap, this study employs a systematic literature review (SLR) approach to transcend singular technical evaluation paradigms and construct a socio-technical governance evaluation model. Specifically, this study advances three analytical questions: First, how do institutional frictions within data governance disrupt public regulatory frameworks in smart cities (RQ1)? Second, how must local bureaucracies reconfigure their collaborative mechanisms and platform structures to manage the operational complexities of digital infrastructure (RQ2)? Finally, in what ways do current digital city policies either mitigate or exacerbate spatial injustice and social exclusion (RQ3)? In subsequent sections, this study first details the literature screening and descriptive analysis based on the PRISMA protocol, then conducts an in-depth thematic synthesis around the three major dimensions, and ultimately distills an actionable policy framework and research implications for urban decision-makers.

2 Research design and methodology

Investigating the socio-technical lag within urban digital transformation requires extracting reliable governance insights and policy evidence from a vast body of interdisciplinary literature. To mitigate subjective selection bias, this study employs a Systematic Literature Review (SLR). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol constitutes the procedural framework for this literature search and screening. PRISMA has emerged as a widely recognized methodological benchmark in recent research on the digital built environment and smart city policy (Habe, 2025; Lindblad, 2026). By establishing transparent search boundaries and verifiable exclusion criteria, this protocol specifically aims to enhance screening objectivity and the overall reproducibility of the findings.

2.1 Search strategy construction and foundational data acquisition

Given the distribution of literature across the interdisciplinary intersection of public administration and engineering technology, this study designates the Web of Science (WoS) Core Collection as its exclusive data source. Its rigorous peer-review mechanism ensures the academic credibility of the foundational literature required for subsequent policy evaluations. The search strategy aligns directly with the three core research questions previously outlined. To achieve precise retrieval, the research team designed a Boolean search string comprising three topic sets (Topic Search, TS), linked via logical intersection (AND) operations. This search matrix systematically encompasses spatial contexts, technological carriers, and governance dimensions (see Table 1). It is important to note that Module 2 specifically targets the foundational spatial-sensing layers of smart cities (such as IoT and digital twins). Rather than predefining all possible algorithmic tools (e.g., Artificial Intelligence or Blockchain) in the search string, this strategy captures the core physical-digital infrastructure, allowing specific computational applications to emerge naturally during the subsequent full-text inductive coding process.

Table 1. Core search strategy and Boolean logic matrix.

To delineate the longitudinal evolution of local governments’ policy responses, the formal search—conducted on March 26, 2026—excluded any predefined temporal restrictions. Regarding document types, the results were strictly limited to peer-reviewed “Articles.” We deliberately excluded conference proceedings, editorial materials, and non-academic grey literature (such as government white papers or municipal policy reports). While acknowledging that excluding grey literature omits certain practical administrative text, this methodological trade-off was a deliberate boundary-setting choice. Given the highly interdisciplinary nature of smart city governance, restricting the sample exclusively to the WoS Core Collection and peer-reviewed articles serves as a strict quality control mechanism. This approach ensures that the foundational literature possesses high academic credibility, allowing the study to rigorously map the established theoretical discourse surrounding socio-technical governance before evaluating practical policy implementations. Ultimately, this standardized procedure yielded 1,163 initial records, laying a robust and peer-validated documentary foundation for the subsequent multi-round double-blind screening.

2.2 Hierarchical exclusion screening and inter-rater reliability testing

The initial search yielded 1,163 records, forming a vast interdisciplinary sample. Filtering out engineering-dominated technical papers and identifying core samples aligned with the public governance dimension was critical for ensuring the validity of this systematic review. Based on an extended PICOS framework, the research team established a five-tier progressive “Hierarchical Exclusion” mechanism (see Figure 1).

By setting stringent criteria, this mechanism precisely filtered out irrelevant records that deviated from policy and socio-technical perspectives:

• Invalid study design: Non-academic articles, conference abstracts, or records missing data sources.
• Out of context: Research subjects detached from physical urban spaces or physical infrastructure, such as purely virtual online public opinion or medical clinical studies.
• Out of intervention I (Missing intelligent attributes): Studies focusing on traditional civil engineering without incorporating emerging information technologies (EITs) like the IoT or digital twins.
• Out of intervention II (Missing governance perspective): Papers confined entirely to the pure engineering logic of algorithmic derivation or hardware testing, lacking discussions on government regulation, collaborative mechanisms, or social ethics.
• Out of scope: Papers meeting the hardware and spatial conditions above, but with core issues residing outside the realm of public policy.

The literature screening procedure strictly followed a two-round double-blind review mechanism. The first round focused on titles and abstracts, during which two independent researchers excluded 811 irrelevant records from the foundational literature. Review logs indicated that the fourth criterion (pure technical engineering) accounted for a massive exclusion share of 708 papers. Rather than definitively proving a disciplinary bias, this large exclusion share naturally reflects the broad interdisciplinary nature of our initial search. It also highlights that a substantial portion of the retrieved smart city literature remains heavily focused on pure engineering solutions rather than institutional governance. The first-round double-blind agreement rate reached 96.99%, with a Cohen’s Kappa coefficient of 0.9295, demonstrating excellent inter-rater reliability. For the 25 disputed papers, a third senior researcher intervened to adjudicate. Ultimately, 352 papers entered the preliminary analysis pool.

The subsequent full-text screening involved a comprehensive review of the 352 candidate papers. To avoid missing studies where governance implications were embedded rather than explicitly stated in the abstract, researchers systematically scanned the full text—specifically targeting discussion sections, conceptual framework diagrams, and policy recommendation paragraphs—to verify the presence of substantive public administration discourse. This stage eliminated another 114 pseudo-relevant records, among which the fourth category of technical engineering papers still maintained absolute dominance (110 papers). The double-blind agreement rate for this round remained high at 94.03% (Cohen’s Kappa = 0.8641). Following this rigorous step-by-step screening, 238 papers were confirmed for the final sample pool intended for qualitative and quantitative synthesis.

2.3 Data extraction and thematic synthesis

Following the finalization of the 238 core papers, the research team implemented a dual-stage analytical strategy comprising quantitative descriptive mapping and qualitative thematic synthesis. First, all 238 articles were exhaustively utilized to extract bibliometric metadata, core technological foci, and specific governance challenges into a standardized matrix for descriptive mapping (Section 3). It is crucial to clarify that specific technological sub-categories reported in subsequent descriptive sections—such as Big Data/AI, Blockchain, and Building Information Modeling (BIM)—were not predefined in our initial Boolean search string. Instead, they emerged inductively during this data extraction phase as critical computational carriers that frequently co-occurred with IoT and digital twins in the full texts of the governance discourse.

Subsequently, for the qualitative thematic synthesis (Section 4), we adopted a purposive theoretical sampling approach. Rather than coding articles heavily skewed toward pure algorithmic optimization with minimal institutional nuance, approximately 120 articles exhibiting substantive theoretical resonance and direct public administration implications were subjected to an in-depth, bottom-up thematic coding procedure. Two researchers independently coded the textual data regarding institutional frictions and policy responses. Initial open codes reflecting specific urban challenges (e.g., “vendor lock-in,” “privacy risks,” “departmental data silos,” “algorithmic bias,” and “digital divide”) were systematically grouped into broader descriptive categories. Through iterative discussion and alignment with public administration theory, these categories were ultimately abstracted into three overarching, interdependent dimensions: (1) the Regulatory dimension, focusing on data sovereignty and risk compliance; (2) the Operational dimension, centering on bureaucratic reconfiguration and polycentric collaborative networks; and (3) the Normative dimension, highlighting spatial justice and social inclusion. This transparent, multi-stage coding protocol ensures a robust, evidence-based linkage between the selected literature sample and the proposed socio-technical governance model.

3 Descriptive analysis and mapping the research landscape

Based on the 238 core papers ultimately included through systematic retrieval and double-blind screening, this section delineates the macro-characteristics of digital urban infrastructure governance research. By transcending the micro-details of individual cases, the metadata distribution across publication years, technological carriers, geographical scopes, and methodological preferences objectively maps the evolutionary trajectory of the field’s research focus. Consequently, it exposes the current academic imbalance between theoretical construction and empirical strategies.

3.1 Evolutionary trajectory and core technological carriers

An analysis of the literature’s time-series distribution over the past decade reveals a clear shift: the governance of digital city infrastructure has transitioned from the periphery to the center (see Figure 2).

This non-linear temporal growth is not coincidental. The post-2020 surge in publication volume largely reflects the urgent demand of global cities for contactless digital infrastructure when confronting sudden public health crises and systemic climate risks (Allam and Jones, 2020; Strielkowski et al., 2022). Accompanying this process, the technological core supporting smart city operations exhibits distinct clustering characteristics (see Figure 3).

Examining the data structure in Figure 3A, the Internet of Things (IoT) and big data/artificial intelligence constitute the dominant core technological elements in current research. They occupy central positions in nearly 80 and 70% of the literature, respectively. Widely distributed sensor networks resolve the sensing of physical space, while data analysis models attempt to parse the resulting massive volumes of information. Furthermore, as a higher-order systemic integration modality, the digital twin has recently emerged as a critical technological carrier. Beyond merely supporting urban planning and real-time decision-making (El-Agamy et al., 2024), current empirical work increasingly positions digital twins as a paradigm for urban lifecycle governance, bridging physical and digital domains to manage long-term infrastructural sustainability (Lu and Li, 2026). However, this intense technological focus conceals a latent governance risk. For smart cities deeply reliant on IoT sensing and algorithmic models, operational complexity often hides behind technological specialization. When the speed of technological iteration drastically outpaces the adaptation cycles of existing regulatory frameworks, issues such as data privacy, algorithmic bias, and ownership boundaries inevitably transcend the engineering domain. They transform into pressing institutional gaps that public administration scholars must urgently address.

3.2 Spatial geographic distribution and methodological mode preferences

Moving beyond the technological dimension, the distribution characteristics of the literature across geographical contexts and research methods further reveal a path dependence in how contemporary academia explores smart city governance (see Figure 4).

Regarding geographical attributes (Figure 4A), over half of the empirical studies are confined to the micro-contexts of single countries or cities; comparative analyses across borders or cross-institutional environments remain a distinct minority. The prominence of specific countries in the sample distribution (Figure 4B) often correlates closely with their macro-strategies for digital infrastructure. As the largest single source of empirical data, China—with its top-down, state-led smart city development—relies on massive policy momentum and the scale of pilot programs. This environment provides scholars with rich empirical arenas to examine the government’s role in digital infrastructure investment and resource allocation (Wang et al., 2025).

These highly contextualized single-case tendencies directly mirror the field’s methodological choices. Examining the methodological statistical distribution in Figure 3B reveals a significant structural imbalance. More than one-third of the studies focus on local case analyses, typically describing the successful implementation of specific technologies within a singular urban node. Meanwhile, over 20 % dedicate themselves to deducing abstract conceptual frameworks. While these case-specific insights are valuable, this heavy methodological concentration on isolated nodes and abstract models suggests a pressing need for more robust, cross-contextual evaluation methods to enhance generalizable explanatory power (Noori et al., 2020).

An even more critical theoretical gap emerges within our sampled literature: studies employing formal policy document analysis—defined here as the systematic coding of municipal strategies, legislative texts, or regulatory frameworks within peer-reviewed articles—account for a mere 2.52%. We acknowledge that this statistically low proportion is partially an artifact of our methodological decision to exclude grey literature. Nonetheless, it highlights a significant disciplinary tendency within mainstream academic journals. Rather than serving as definitive proof of technological determinism, this distribution suggests that peer-reviewed research resources are disproportionately funneled into observing technological facades and constructing management models. Consequently, scholars often neglect in-depth analyses of power distribution, the allocation of data rights, and the contestation over social resources hidden behind policy texts (Kummitha and Crutzen, 2019). Confronting the complex evolution of digital cities, a lack of systematic scrutiny of formal institutional documents makes it exceedingly difficult to transcend the opacity of technological mediation and expose the core logic of public administration. This research void establishes the necessity for this study to engage deeply in institutional analysis, carving a clear argumentative path for the subsequent thematic synthesis.

4 Thematic synthesis: a socio-technical governance framework for smart cities

The preceding descriptive analysis quantitatively exposes the centrality of the technological orientation in contemporary digital city research. Transcending this purely technical perspective is essential. Shifting the analytical lens from algorithmic logic to a socio-technical paradigm represents the logical trajectory for addressing the complex governance challenges of urban digital transformation. The smart city is not merely a set of value-neutral computational protocols. Rather, it constitutes a complex institutional architecture embedded with contestations over capital interests, the restructuring of administrative power, and demands for social equity. Grounded in socio-technical systems theory, this chapter transcends simple thematic reclassification to construct an integrated smart city governance framework. We propose that effective urban digital transformation requires continuous mutual adaptation and co-evolution between technical artifacts and social institutions (Zhai and Gao, 2024). To capture this dynamic, the framework delineates three highly interdependent dimensions: regulatory policies, operational mechanisms, and normative values. Rather than acting as isolated domains, these dimensions interact continuously to mediate the transition of urban regimes, ultimately serving to apply rigorous institutional scrutiny to the field’s existing paths of technological evolution.

4.1 Examining the regulatory dimension: data sovereignty, privacy crises, and interoperability barriers

Amidst the rapid expansion of the digital built environment, data has firmly established its status as a new core factor of production. However, as massive physical urban trajectories virtualize and data flows accelerate, a stark reality emerges: significant institutional voids plague related ownership rights, privacy boundaries, and interoperability standards. This pronounced misalignment between widespread technological deployment and regulatory lag precipitates a severe regulatory crisis for urban public administration (see Table 2).

Table 2. Synthesis of core challenges and regulatory pathways regarding smart city data policy and the regulatory dimension.

The fragility of privacy protection mechanisms and the risks of algorithmic surveillance are becoming increasingly acute. While statutory frameworks like the General Data Protection Regulation (GDPR) delineate a global baseline for data compliance, ubiquitous urban sensor networks objectively dissolve the physical boundaries of public and private spaces. Driven by capital-driven impulses to forcibly convert citizens’ daily behavioral trajectories into economic resources, privacy protection mechanisms within digital infrastructures are being systematically weakened (Tierney, 2019). Absent strict contextual integrity constraints, a severe rupture emerges between the public’s default privacy norms and the reality of excessive data harvesting (Shaffer, 2021). Through infrastructure provisioning, certain private tech giants covertly acquire sensitive data. This practice not only triggers infringement risks tied to data commodification but also—shielded by algorithmic opacity and lacking administrative oversight—mutates into an informal network of social control (Allam, 2019). Such unfettered capture and predictive profiling of urban data threaten to drag urban governance into the abyss of surveillance capitalism, thereby profoundly destabilizing the digital social contract between citizens and the state (Argota Sánchez-Vaquerizo, 2025; Losavio, 2024).

Beyond the compromise of privacy ethics, the enclosed nature of data architectures constitutes another formidable public regulatory barrier. From an institutional perspective, data integration must be understood not merely as a technical fix for software compatibility, but as a deeply contested socio-technical urban transition (Zhang et al., 2026). Current municipal digital systems often suffer from fragmented legal frameworks and a lack of unified metadata protocols (Quek et al., 2023). The proliferation of proprietary protocols forces urban data into disparate operational silos, subsequently trapping local governments in severe vendor lock-in during technological iterations (Kang et al., 2026). This de facto monopoly fundamentally strips city governments of their data sovereignty and governance autonomy (Gupta et al., 2020). Overcoming this interoperability dilemma demands political deliberation concerning the distribution of public value. Recent policy analyses emphasize that reclaiming public authority requires enacting dedicated smart city legal frameworks and statutory mandates to enforce interoperability (Zaiarnyi and Katerynych, 2025), alongside establishing civic data trusts. This institutional mediation is essential to safeguard urban data as a public good against commercial control (Mammone et al., 2026; Raetzsch et al., 2019).

While technological tools alone cannot resolve institutional deficits, mechanisms like blockchain are being cautiously explored not as panaceas, but as infrastructural supports for distributed digital trust. Rather than focusing on cryptographic execution, public administration emphasizes deploying these technologies to strictly enforce legal principles such as “data minimization” and robust property rights confirmation (Potts et al., 2017; Shehadeh, 2025). Furthermore, relying on smart contracts to establish fine-grained access control, dynamic consent management frameworks attempt to partially return the decision-making power over data flows to urban residents. This approach seeks to reconstruct digital autonomy within cryptographic verification mechanisms (Kundu, 2019; Raes et al., 2022). Meanwhile, federated learning and zero-knowledge proofs (ZKPs)—specifically tailored to protect vulnerable populations—effectively mitigate the vulnerabilities of centralized cloud storage (Chen et al., 2025). Mandating sufficient transparency and explainability (Explainable AI) for predictive algorithms involved in resource allocation is rapidly emerging as a consensus regulatory pathway. This pathway is essential to prevent the overreach of technological rationality, striking a critical balance between data-driven innovation and the safeguarding of fundamental rights (Mohammadi et al., 2026).

4.2 Examining the operational dimension: polycentric collaborative governance and the reconfiguration of bureaucratic mechanisms

Institutional voids within the regulatory dimension ultimately cascade down into concrete urban operational networks. The deployment of digital infrastructure is not merely a contestation over legal norms. Rather, it directly precipitates organizational reconfiguration and the redistribution of power within city governments. An inherent organizational friction exists between traditional bureaucratic structures in public administration and highly dynamic digital technology systems. Consequently, how local governments reshape their collaborative mechanisms to unleash technological efficacy constitutes the core operational challenge of smart city governance (see Table 3).

Table 3. Multidimensional analysis matrix of collaborative governance and operational mechanisms.

Enhancing algorithmic transparency and constructing platform governance frameworks constitute the core logic for reshaping Public-Private Partnerships (PPPs) in the digital age. When confronting highly dynamic digital infrastructure, public-private cooperation under traditional concession frameworks frequently exposes deep-seated institutional flaws. Constrained by market-oriented resource allocation and the stark reality of local fiscal austerity, some local governments rely excessively on tech giants to provide “turnkey” foundational solutions. Consequently, this model severely exacerbates the opacity of core digital assets (Rodrigues et al., 2022; Jeannot, 2019). When commercial profit motives collide with public value, the influence of private tech platforms frequently oversteps their functional boundaries. This constitutes a de facto intervention into administrative logic, thereby debilitating public accountability mechanisms and the overall efficacy of public governance (Ranchordás and Goanta, 2020). Confronting the dual challenges of capital and technology, city managers must urgently transcend their roles as passive procurers of services. To navigate this, contemporary public administration discourse suggests local governments pivot toward acting as “platform orchestrators” within the ecosystem (Nesse et al., 2021; Shamsuzzoha et al., 2021). By establishing Special Purpose Vehicles (SPVs) or open innovation frameworks, governments attempt to embed rigid public interest principles into contractual bargaining (Del Giudice et al., 2016; Pramanik et al., 2026; Belli and Doneda, 2020). However, this transition must be evaluated critically. Recent empirical evidence from municipal governments indicates that deploying collaborative platforms is not a uniformly beneficial panacea; in some instances, municipalities relying heavily on such platforms perform no better, or even worse, in terms of horizontal coordination and decision-making power than those without them (Beckers et al., 2025). Therefore, merely adopting platform architectures without calibrating them to local institutional capacities may yield limited collaborative governance outcomes.

While reshaping external collaborative networks, city governments face an urgent need to overcome internal institutional barriers: specifically, the pitfalls of “sandbox urbanism” and the impediments to cross-departmental collaboration (silo-breaking). Under relentless pressure from technological iteration, many cities gravitate toward a strategy of “sandbox urbanism” devoid of long-term planning for institutional evolution (Steiner, 2025). Overrelying on short-term pilots and flexible project definitions may project a facade of technological innovation. However, this approach ultimately obscures critical scrutiny of deep-seated institutional rigidity. Absent institutionalized, long-term mechanisms to translate these efforts into daily administrative routines, a multitude of smart projects are reduced to isolated pilot projects. Consequently, they fail to catalyze structural adjustments within the operational processes of public organizations (Velsberg et al., 2020; Janssen et al., 2019). At a more micro-operational level, deep-rooted siloed fragmentation constitutes a prominent barrier hindering digital governance. Constrained historically by vertical budget allocations and performance evaluations, core municipal departments—such as environmental protection, drainage, land management, and emergency response—severely lack horizontal collaboration. This entrenched dynamic creates insurmountable data and operational silos (Kaginalkar et al., 2023; Mai et al., 2025; Ahsan et al., 2024). These bureaucratic barriers significantly inflate integration costs and severely debilitate the systemic responsiveness of holistic platforms, such as digital twins, when confronting complex crises. While formal structural remedies—such as constructing unified urban data hubs and adopting comprehensive Enterprise Architecture (EA) models—are widely recognized as effective pathways (Lu and Li, 2026; Choudhuri et al., 2025; Jacobs et al., 2020; Guo and Zhou, 2025; Soyata et al., 2019), they are insufficient on their own. Institutional analysis reveals that breaking silos deeply relies on the evolution of informal rules and non-bureaucratic work modes (Lekkas and Souitaris, 2023). For example, informal interdepartmental coordination meetings can significantly reduce information asymmetries and transaction costs during digital transformation, even though they may face sustainability challenges (Zhou and Wu, 2026). Consequently, overcoming bureaucratic fragmentation is not merely an architectural integration process, but rather a dynamic adaptation where traditional bureaucracies temporarily adopt flexible practices and subsequently formalize them to manage digital reality.

Beyond the administrative boundaries of single cities, deploying digital infrastructure typically involves multi-level institutional tensions between national macro-strategies and differentiated local governance demands. Within top-down dominated networks (such as the “state-led entrepreneurialism” model in Xiong’an, China), the central government leverages unique institutional advantages and the execution capabilities of state-owned enterprises. Consequently, it can rapidly dissolve fundamental institutional impediments and achieve the cross-level coordination of infrastructure (Wang et al., 2025). Similarly, emerging empirical work from the Global South—such as in Vietnam—demonstrates the rise of hybrid models characterized by “state-led collaborative governance.” In these contexts, hierarchical political coordination coexists with negotiated stakeholder engagement to overcome resource constraints and implement digital strategies (Kim Hoang, 2026). However, when national-level innovation policies cascade downward on a massive scale, they frequently deviate from local endogenous resource endowments. This misalignment manifests as a coercive diffusion of supply-side policies (Parks, 2022). For instance, in emerging domains such as urban low-altitude unmanned aerial vehicle (UAV) airspace management, unified safety regulations issued by central industry authorities frequently trigger jurisdictional conflicts with the spatial planning authority of local governments (Stelmach-Fita, 2025). To address these recalibration challenges, “the Scandinavian Third Way” pioneered by certain European cities offers an alternative reference emphasizing polycentric collaborative governance. Its core lies in utilizing flat steering committees to forge a stable governance consensus between rigid central standards and customized local demands (Baraniewicz-Kotasińska, 2022). Furthermore, the stark inequalities in fiscal support and technological absorptive capacity among cities of varying sizes must be confronted directly. National central cities and regional hubs exhibit divergent execution barriers when advancing policy alignment. This reality urgently compels top-level designers to provide differentiated transfer payments and cross-jurisdictional knowledge-sharing networks. Such interventions are imperative to prevent risks of structural imbalances in regional digital governance capabilities (Varzeshi et al., 2025).

4.3 Examining the normative dimension: algorithmic bias, social inclusion, and the right to the digital city

When the instrumental rationality of technological evolution transgresses public value constraints, smart city development risks abandoning its foundational mission to serve the public. Compared to institutional recalibration at the operational level, the scrutiny of digital infrastructure demands a return to a human-centric normative dimension. Through this analytical lens, smart sensors and predictive models are no longer neutral engineering components. Rather, they function as deeply embedded institutional variables that reshape the distribution of social resources and propel the structural evolution of civic rights (see Table 4).

Table 4. Synthesis of social tensions and inclusive governance strategies within the normative dimension of smart cities.

The capital-intensive nature of digital infrastructure precipitates spatial and distributional inequities, subsequently engendering digital exclusion and algorithmic bias. Exorbitant technological deployment costs frequently dictate that smart upgrades disproportionately prioritize core commercial districts or affluent neighborhoods. Conversely, in marginalized peripheries lacking financial subsidies, low-income groups confront systemic “digital exclusion” (Haraguchi et al., 2024). Using Shenzhen’s smart transportation transition as an empirical case, data reveals a stark reality: constrained dually by rental deposit requirements and the spatial maldistribution of charging facilities, the participation rate of low-income households in new energy car-sharing projects is a mere 12% (Zhao, 2025). Furthermore, purchasing power-based thresholds for technological access and insufficiently inclusive interaction designs similarly constitute functional access barriers for vulnerable populations seeking to utilize basic public services, such as mobility and healthcare (Villanueva-Merino et al., 2024; Almaghlouth et al., 2024). Drawing on Amartya Sen’s capability approach, recent studies argue that bridging the digital divide requires more than merely providing hardware; it necessitates aligning personal and social “conversion factors” so marginalized groups can actively navigate smart environments (Colding et al., 2024). Furthermore, a multidimensional and intersectional perspective reveals that socio-cultural factors severely compound this exclusion, particularly for vulnerable populations such as undocumented migrants or the elderly, who face intersecting deficits in digital literacy and digital capital (Lintner and Zadra, 2026). Beyond hardware and literacy, an even more insidious form of exclusion resides within algorithmic opacity. Historical socioeconomic biases are frequently encoded into the weight systems of machine learning algorithms. Consequently, predictive policing and resource dispatch models generate systemic algorithmic exclusion against specific groups during their operation (Yigitcanlar et al., 2021; Hu et al., 2026). Racial bias in facial recognition technology and the deprioritization of vulnerable groups by health models trained on historical medical records both expose the deep institutional limitations of purely data-driven decision-making within the dimension of social equity (Buckwald and Marchant, 2021; Singh and Murukannaiah, 2023).

The expansion of instrumental rationality may induce technocratic managerialism, thereby debilitating the substantiveness of civic participation. Within numerous smart city projects dominated by governments or large tech enterprises, citizens are frequently objectified as passive data generators or terminal consumers. Consequently, the exertion of their civic agency is severely stifled (Choi and Kenney, 2024; Lemos, 2016). The exclusionary effect of technological thresholds manifests in the public’s inaccessibility to core algorithmic logic and urban planning boundaries. As a result, the public consultation mechanisms of certain local governments confront the dilemma of “tokenistic participation” (Leung and Lee, 2023; Calzati, 2023). Addressing these participatory barriers requires analyzing how interaction structures between governments and citizens are being reshaped. Theoretical models increasingly conceptualize citizens not merely as system “users,” but as “co-creators” of public value (Ruohomaa et al., 2019; Sahoo et al., 2024). In developed contexts, this often materializes through Urban Living Labs and hybrid phygital spaces designed to lower participatory barriers for non-tech-savvy groups (Ravid and Gutman, 2024; Popescul et al., 2024). Conversely, in the Global South—where formal digital initiatives often face resource constraints—empirical evidence points to “urban commoning” as a vital organizing process. This grassroots approach allows marginalized residents to negotiate local bureaucracies and exert their right to the city, fostering inclusion that formal smart city agendas might otherwise overlook (Peter and Meyer, 2023). Furthermore, relying on task-oriented synthetic data generation and crowdsourced sensing networks, grassroots communities can utilize their own mobile devices to upload place-based environmental and transportation demands. This enables a bottom-up recalibration of top-down policy deviations (Ravn, 2024; Nasifuhan et al., 2024; Cvar et al., 2020). However, the long-term viability of this co-creation model must be supported by digital literacy education for citizens and rational incentive structures (reward-penalty mechanisms). These interventions are critical to mitigating the public’s risk perception and the erosion of trust during the data-sharing process (Tan et al., 2024; Madsen, 2018).

The pursuit of technological efficiency must not come at the expense of spatial justice and the right to the digital twin city. Concomitant with the virtualization of physical cities, scholars have extended Lefebvre’s classic theories into the digital age, developing the concept of “the right to the digital twin city” (Domaradzka et al., 2022). This concept asserts that urban residents not only possess the right to equitably enjoy improvements in the physical spatial environment but should also have the right to intervene in digital infrastructure design, monitor data flows, and safeguard against the risks of technological alienation (Allam et al., 2022). This rights-based discourse is gaining critical traction through the “Southern urban critique.” Scholars emphasize that conceptualizing a “just smart city” in the Global South requires politicizing technological deployments to ensure they address, rather than mask, profound local socio-economic disparities (Alizadeh and Prasad, 2024). This demand for rights manifests with particular urgency in the realm of environmental justice. Given that traditional official monitoring stations frequently bypass pollution-intensive marginalized communities, deploying targeted, low-cost smart sensor networks and providing public access to unfiltered baseline data has become a critical technological pathway. This approach empowers marginalized groups and low-income communities in their environmental advocacy (Alegria et al., 2024). However, a potential institutional challenge emerges: absent complementary interventions in the social dimension, ecological restoration-oriented smart greening projects (such as sponge cities and vertical greening) can easily inflate surrounding land prices. This dynamic triggers “green gentrification” and the displacement of incumbent residents (Duggal et al., 2025; Marfo et al., 2026). Therefore, institutionalizing Social Equity Impact Assessments (SEIA) within the procurement and approval processes of all large-scale digital infrastructures, alongside constructing a monitoring matrix encompassing inclusivity, accessibility, and anti-displacement metrics, serve as critical institutional safeguards. These measures are essential to ensure the inclusive distribution of benefits generated by digital cities (Rasoulzadeh Aghdam et al., 2025).

5 Discussion: an actionable policy framework for urban decision-makers

Transcending theoretical deconstruction and critique, the functional orientation of public administration research lies in translating normative value propositions into actionable institutional arrangements. The preceding thematic synthesis has elucidated the systemic failures confronting digital urban infrastructure across regulatory, operational, and social inclusion dimensions. Empirical evidence from the reviewed literature suggests that piecemeal technical fixes are insufficient for managing highly complex socio-technical systems. Instead, successful governance transitions observed in the literature increasingly rely on integrated portfolios of policy instruments characterized by clear accountability and dynamic responsiveness. This chapter endeavors to systematically integrate the dispersed policy recommendations within the included literature, extract common intervention strategies, and subsequently propose a multidimensional policy evaluation and execution model for smart cities.

5.1 Systematic extraction and synthesis of policy intervention instruments

Synthesizing empirical evidence of digital city governance globally reveals a shifting landscape: local governments are gradually rolling out a series of effective administrative interventions and policy regulation tools to counter technological uncertainty and market monopolies. Logically, these common recommendations converge upon three core policy fulcrums: agile regulation and the reconstruction of data sovereignty; market steering through procurement power; and safety-net social inclusion mechanisms (see Table 5).

Table 5. Actionable policy intervention toolbox for smart city decision-makers.

Confronting the governance dilemma where technological iteration cycles vastly outpace legislative cycles, the critical entry point for policy design lies in constructing agile regulation mechanisms and fortifying standards for the allocation of data rights. Traditional command-and-control regulation may stifle innovation or succumb to regulatory lag. Against this backdrop, establishing “regulatory sandboxes” with explicit “sunset clauses” constitutes a representative policy instrument to mitigate technological uncertainty (Galkin et al., 2025; Sha and Taeihagh, 2024). By granting technological experiments regulatory exemptions within defined spatial and temporal boundaries, local governments can accurately assess the potential risks of data flows in real-world environments. This approach provides robust empirical support for subsequent institutionalization (Alreshidi, 2025). Regarding data sovereignty governance, establishing mandatory interoperability protocols and tiered open data strategies is extensively debated in the literature. However, recent legal analyses emphasize that experimental zones like sandboxes must explicitly navigate existing legal liabilities and accountability frameworks to be effective (Voorwinden et al., 2023). To effectively dismantle organizational fragmentation and vendor lock-in, policy scholars emphasize the transition away from proprietary protocols. Empirical cases highlight that enforcing machine-readable data formats and Application Programming Interfaces (APIs) based on international standards (e.g., OGC, IFC) serves as a vital structural intervention (Lindblad, 2026; Klar et al., 2023). Furthermore, robust localized privacy regulation strategies are increasingly identified as essential safeguards to protect civilian data from corporate extraction in public-private environments (McCrory, 2024). At the operational level of information sharing, policy design should introduce Data Protection Impact Assessment (DPIA) toolkits to implement tiered opening based on data sensitivity. Specifically, public infrastructure data should default to open. Conversely, telemetry information involving personal trajectories strictly requires differential privacy processing or must be utilized solely in the form of synthetic data for policy simulation (Korchenko et al., 2026; Papyshev and Yarime, 2021). Furthermore, in response to frequent privacy breach incidents, mandatory data breach notification legislation and continuous cybersecurity audits have become foundational requirements to sustain public trust in digital infrastructure deployment (Aslam et al., 2022; Mylrea, 2017).

Another core dimension of policy intervention lies in achieving the structural regulation of the technology market through the strategic allocation of public procurement budgets. This intervention transcends the mere acquisition of technical hardware and software; rather, it is being fundamentally redefined as a binding policy instrument (Corrado et al., 2022). When issuing outsourcing tenders for digital infrastructure, local governments must institute Social Equity Impact Assessments (SEIA) and Privacy by Design as mandatory ex-ante qualification criteria. This explicitly compels bidders to integrate innovative and secure technological solutions (de Bruyn et al., 2026; Pérez-González and Díaz-Díaz, 2015). To coordinate increasingly complex cross-departmental collaborative networks, the structural recalibration of administrative organizational architectures is equally indispensable. Numerous studies strongly advocate establishing Chief Data Governance Officers at the upper echelons of municipal systems or forming joint data trust committees that transcend single jurisdictions (Marchesani and Ceci, 2026; Zali et al., 2024). This institutional design introduces unified Enterprise Architecture (EA) models and accountability matrices. Its objective is to unambiguously delineate the jurisdictional boundaries and cybersecurity accountability mechanisms among the government, general contractors, and technology vendors throughout the data lifecycle. Consequently, such structural clarity effectively curbs blame-avoidance tendencies inherent within bureaucratic systems (Pärn et al., 2024; Szpilko, 2025).

Regarding the construction of the social inclusion dimension, the institutionalization of safety-net interventions and civic data trusts is critical to alleviating digital exclusion. The distribution of technological dividends is not a spontaneous market process; rather, it necessitates mandatory policy regulation. Confronting the digital exclusion induced by exorbitant technological costs, implementing targeted inclusive subsidies and tiered financing support is pivotal for safeguarding spatial justice (Sharma et al., 2020; Dorostkar and Ziari, 2025). Empirical studies on ICT investment strategies confirm that aligning funding—such as earmarked transfer payments or tax exemptions for green smart retrofitting in low-income communities—with evidence-informed local needs effectively bridges territorial digital divides (Reggi and Gil-Garcia, 2021). This targeted support is essential to offset the risk of “green gentrification” triggered by technological upgrades (Benseny et al., 2023; Nelson et al., 2019). Moreover, analyses of urban energy transitions suggest that public utility frameworks must actively prioritize the accrual of collective public interest benefits over purely commercial interests to ensure equitable outcomes (Britton, 2019). Regarding the construction of public participation mechanisms, traditional unidirectional public consultation is transitioning toward an institutionalized devolution of rights. The literature strongly advocates exploring “civic data trusts” and regulated co-design mandates (Jacobs et al., 2022). This paradigm shift requires mandating representative seats for marginalized groups during the initial phases of technology deployment. Furthermore, by providing low-barrier transparency toolkits and localized digital literacy training, local governments must ensure that vulnerable groups retain substantive oversight rights and the right to data dividends throughout the evolution of digital cities (Cho and Kim, 2022; Schrotter and Hürzeler, 2020; Bolshakov et al., 2024; Kim, 2025).

5.2 The proposed governance model: a three-dimensional policy evaluation framework from a socio-technical integration perspective

While the policy instruments synthesized in the preceding section serve as discrete tools for local governments to counter technological shocks, within the context of Complex Adaptive Systems (CAS), fragmented administrative interventions are patently inadequate to steer the holistic digital transformation of cities. Transcending the mere accretion of technological artifacts, a modern urban governance model aimed at bridging the “socio-technical divide” must logically achieve cross-disciplinary and cross-sectoral systemic integration (Chang et al., 2023; Anthopoulos et al., 2016). Based on the empirical extraction of the preceding literature evidence, this study formally proposes the “Tripartite Socio-Technical Urban Governance Framework (T-STUG)” (see Figure 5).

Rather than reducing the smart city to a mere physical superimposition of engineering hardware (Lim et al., 2018), this model advances existing socio-technical theories by illustrating the systemic interrelationships among its three subsystems (Principale et al., 2023). Specifically, regulatory rules shape the boundaries of operational platforms, which in turn strongly influence whether normative goals like social equity are achieved in practice (Lartey and Law, 2026). By mapping these interactions, the T-STUG framework moves beyond static categorization to provide a structured system for evaluating urban digital transformation (see Table 6).

Table 6. Multidimensional assessment indicators and governance mapping system of the T-STUG model.

First, the model establishes “regulatory and risk governance” as its core institutional safeguard. At this echelon, the paramount task of policy design is to effectively mitigate the systemic risks induced by data-driven processes. Relying on the interconnectivity inherent within Cyber-Physical-Social Systems (CPSS) (Xiahou et al., 2022), recent studies suggest that urban administrators benefit from shifting away from traditional passive approvals toward ex-ante normative guidelines encompassing data security, privacy ethics, and the delineation of data property rights (Wu et al., 2018). Within this dimension, indicators such as the adoption rate of open data standards and audit frequencies serve as measurable proxies for systemic risk mitigation (Sayed et al., 2026). Evidence indicates that internalizing risk management and compliance auditing throughout the entire lifecycle of digital infrastructure (Freitas et al., 2026) can effectively condition the procurement and deployment of smart systems on strict adherence to open interoperability standards. Such a prerequisite effectively circumvents the proprietary enclosure and commercial monopolization of urban public data by technology vendors at the source (Ullah et al., 2021).

Second, the model establishes “polycentric operational synergy” as the operational mechanism driving policy implementation. The actualization of digital infrastructure policies is fundamentally constrained by the efficacy of resource integration within the administrative system (Kuru and Ansell, 2020). Within this dimension, evidence shows that legacy bureaucratic silos often require a structural transition toward a horizontally integrated Enterprise Architecture (EA) (Flores Lara et al., 2025). Consequently, the functional locus of local governments increasingly pivots from sole providers within the innovation ecosystem to core orchestrators. By introducing cross-departmental joint command mechanisms and agile sandbox strategies, governments can substantively reduce the transaction costs associated with multi-party collaboration (James et al., 2022; Yadav et al., 2023). When confronting boundary-spanning wicked problems—such as the management of urban greening systems or complex waste treatment—the model advocates substituting traditional bilateral contracts with Public-Private-People Partnerships (PPPPs) (Pham Anh, 2021; Shao and Min, 2025). Anchored in this systemic collaborative network, cities can successfully transition their traditional administrative paradigms into highly agile dynamic response mechanisms calibrated to public demands (Phu et al., 2026).

Finally, the model establishes “Normative Value & Social Inclusion” as the navigational imperatives calibrating the trajectories of technological evolution. Divorced from public value constraints, the optimization of any smart system risks degenerating into the systemic exclusion of vulnerable populations. Consequently, the T-STUG model highlights the value of embedding “Civic Intelligence” and spatial justice indicators squarely into the core of technological assessment frameworks (Domaradzka et al., 2022; Nechesov and Ruponen, 2024) to systematically evaluate inclusive urban development (Paramaiah et al., 2026). Empirical findings advocate for pivoting policymaking away from supply-side technocratic dominance toward citizen-centric requirement alignment (Mortaheb and Jankowski, 2023; Heaton and Parlikad, 2019). By extending Policies-Actuated-Planning down to hyper-local community units, local governments can ensure the equitable distribution of technological retrofitting benefits across all societal strata (Marsal-Llacuna, 2019). On the other hand, the model advocates elevating nature-positive outcomes to equal priority with human well-being (Russo, 2025; Han, 2025). This necessitates establishing an ethical constraint matrix—encompassing algorithmic explainability, the prevention of algorithmic bias, and safeguards against green gentrification. Such institutional guardrails ultimately ensure that the urban digital twin space consistently serves substantive social equity and justice.

6 Conclusion and future research implications

Synthesizing a decade of interdisciplinary literature, this systematic review establishes a fundamental premise: the governance efficacy of the digital built environment and smart city infrastructure is not a mere engineering upgrade. Rather, it constitutes a profound organizational, institutional, and social imperative. As sensors, digital twins, and predictive algorithms increasingly permeate physical urban spaces, their impact transcends simple efficiency gains. They precipitate systemic governance challenges that strike at the core of data sovereignty, cross-departmental power restructuring, and the redistribution of social resources.

6.1 Theoretical synthesis of core findings

Revisiting the three core research questions anchoring this study, the empirical evidence reveals a definitive logical trajectory. Within the regulatory dimension (RQ1), traditional data management frameworks exhibit severe institutional supply lag when confronting the rapid proliferation of IoT and big data. The absence of unified machine-readable standards and open Application Programming Interfaces (APIs) directly plunges public finance into the dilemma of technological dependency—effectively cementing vendor lock-in (Shaddick et al., 2025). Concurrently, covert data extractivism and algorithmic black boxes threaten to drag urban governance into the perils of dataveillance. To reconstruct digital trust, the literature emphasizes the necessity of introducing Privacy by Design based on contextual integrity, alongside property-defining technologies such as blockchain (Jacobs et al., 2022; Çetin et al., 2022). Within the operational dimension (RQ2), mere hardware procurement is utterly incapable of dismantling inherent vertical operational silos within the bureaucracy. Confronting fragmented municipal architectures, evidence suggests local governments benefit from transforming their role from passive service purchasers into platform orchestrators within the ecosystem (Wu et al., 2025). Leveraging the horizontal integration of Enterprise Architecture (EA) and the institutional innovation of Public-Private-People Partnerships (PPPPs) to address data silos across transportation, environmental protection, and emergency response departments serves as a key organizational prerequisite for enhancing governance efficacy (Mossberger et al., 2023; Song et al., 2021). Within the normative dimension (RQ3), rapid technological iteration frequently camouflages exacerbating spatial inequality and digital exclusion. Exorbitant technological retrofitting costs, coupled with a lack of inclusive interactive interfaces, persistently marginalize low-income cohorts and aging populations (Ning and Lu, 2021). To address this, studies advocate utilizing Urban Living Labs and crowdsourced sensing networks to support citizens in transitioning from passive data providers to co-creators of public value. This paradigm shift, fortified by the mandatory execution of Social Equity Impact Assessments (SEIA), constitutes the institutional cornerstone for safeguarding “the right to the digital twin city” (Losavio et al., 2018; Shabha et al., 2023).

6.2 Limitations and referencing strategy

Scrutinizing the methodological boundaries of this study, several inherent limitations provide necessary contextual caveats to prevent overstating the generalizability of these conclusions. First, driven by the imperative for consistent interdisciplinary peer-review quality, this study restricted the search scope exclusively to the Web of Science (WoS) Core Collection and strictly excluded non-English academic publications and informal government policy white papers (grey literature). We fully acknowledge that omitting grey literature limits our capacity to capture real-time administrative law and policy implementations. Second, the empirical evidence within the sampled literature exhibits strong geographical concentration, which may introduce publication bias and limit the universal applicability of the findings, particularly concerning the Global South (Joynes and Dwivedy, 2026; Aldehim et al., 2025; Wu et al., 2020). Finally, despite achieving high inter-rater reliability, the qualitative nature of thematic synthesis and the inductive coding process inevitably entail conceptual subjectivity. Consequently, the final research conclusions carry a bias toward established research paradigms within mainstream academia and should be interpreted as theoretical reflections rather than universally.

Furthermore, we must transparently articulate the dual-stage synthesis strategy applied to the final 238-article corpus. Following PRISMA guidelines, all 238 articles were exhaustively utilized in the quantitative descriptive mapping (Section 3) to objectively delineate macro-trends and technological clusters. However, for the subsequent qualitative thematic synthesis (Section 4), we adopted a “purposive theoretical sampling” approach, a recognized method for managing large, highly heterogeneous datasets in social science reviews (Behrendt, 2019; Çelik et al., 2025). Rather than omitting valid data, articles heavily skewed toward pure algorithmic optimization with low institutional relevance were synthetically categorized as contextual background. Conversely, approximately 120 articles exhibiting substantive theoretical resonance and direct public administration implications were subjected to in-depth, granular coding. This methodological design ensures comprehensive macro-level reproducibility while enabling deep, theory-driven policy critique, avoiding the degradation of the synthesis into a superficial catalog of technical specifications (Hijazi and Das, 2026).

6.3 Toward a future public administration research agenda

The “Tripartite Socio-Technical Urban Governance Framework (T-STUG)” constructed in this review represents not merely a systematic synthesis of the extant literature; rather, it endeavors to expand the research horizons for future smart city policy inquiries. To address the structural imbalances prevalent in current academic research, future public administration explorations urgently require paradigm breakthroughs across the following three domains.

First, there must be a transition from conceptual deduction toward rigorous quantitative policy evaluation. Current smart city governance research relies excessively on localized, single-case descriptive studies and the construction of abstract theoretical frameworks (Naiki, 2024). Confronting capital-intensive digital infrastructure investments, the academic community urgently needs to introduce quasi-natural experimental methods—such as Difference-in-Differences (DID) and Propensity Score Matching (PSM). By leveraging large-sample panel data, researchers can effectively identify the causal mechanisms of smart pilot policies on urban green development, emergency management, and economic resilience (Li and Wang, 2024; Lawelai et al., 2025). Eliminating the endogeneity biases caused by non-institutional factors to provide quantitative evidence-based policy performance evaluations constitutes a critical focal point for future research.

Second, researchers must transcend the context of developed nations to focus squarely on the localized governance dilemmas of the Global South. Existing empirical research exhibits a pronounced skew toward resource-abundant Euro-American metropolises and early-adopting Asian cities. Consequently, the establishment of technical standards and ethical norms reflects a pervasive “Global North” discursive dominance (Oliveira et al., 2024; Razmjoo et al., 2021). Within developing nations characterized by pervasive infrastructural deficits, the prevalence of informal economies, and acute fiscal stress, the direct imposition of exorbitant digital twin or IoT standards invariably triggers severe crises of adaptability (Demirel, 2023; Carrato-Gómez and Roig-Segovia, 2022). Future comparative research must deeply dissect how nations across Latin America, Africa, and Southeast Asia leverage low-cost open-source smart technologies, mobile-based alternative solutions, and informal public-private collaborative networks. Operating under severe resource constraints, these regions can pioneer smart city governance models that exhibit genuine localized adaptability (Clever et al., 2018; Yousaf, 2026).

Third, future research must deepen the exploration of spatial justice and the rights of marginalized populations through an intersectional perspective. Technological exclusion is not a single-dimensional phenomenon; rather, it is deeply intertwined with socioeconomic vulnerabilities such as class, race, age, and geographic location (du Toit and Stimie, 2023). Future inquiries must critically reflect upon the presupposition of a singular “rational user” and integrate intersectionality analytical frameworks into algorithmic auditing and technological access assessments. By investigating the differentiated experiences of diverse demographic groups when engaging with smart mobility, digital environmental monitoring, or public safety algorithms, researchers can formulate inclusive interventionist policies that accurately identify and bridge structural digital divides. Ultimately, such efforts ensure that technological advancements serve the public value objective of fostering universal human flourishing (Paes et al., 2023).

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Footnotes

Edited by: Miguel Valdez, The Open University, United Kingdom

Reviewed by: Rokhsaneh Rahbarianyazd, Alanya University, Türkiye

Qing Lu, Chinese Research Academy of Environmental Sciences, China