Africa's rapid demographic transformation characterized by a youthful population, accelerated urbanization, and expanding metropolitan regions—has intensified pressures on urban mobility and transportation systems. This study examines how these demographic shifts contribute to growing spatial mismatch in the African cities of Accra, Lagos, and Nairobi. These cities face increasing strain on transport systems, infrastructure, and spatial planning, resulting in significant inequalities in access to opportunities.Drawing on spatial mismatch theory and mobility justice frameworks, the study explores how the geographical separation between residential areas and employment centers, combined with weak and fragmented transport systems, deepens socio-economic exclusion. Through document analysis of World Bank and UN-Habitat reports, household travel surveys, and related reports, the study adopts a comparative case study approach to identify patterns in transport systems such as trotro, matatu, and danfo. While these systems play a central role in urban mobility, they remain unreliable and poorly integrated into formal urban planning structures.The study concludes that achieving inclusive urban development requires a shift toward integrated, equitable, and sustainable transport policies, alongside investments in mass transit that prioritize vulnerable populations and support rapidly growing urban populations. It further contributes to urban theory by extending spatial mismatch to global contexts, demonstrating that mobility inequality is central to understanding urban governance, labor market access, and inclusive development in rapidly urbanizing African cities.

Jakarta, Indonesia, hosts the world’s longest Bus Rapid Transit (BRT) system, yet the network faces persistent challenges in temporal competitiveness. This study evaluates the spatiotemporal performance of this extensive network by analyzing the General Transit Feed Specification (GTFS) data of 243 unique routes, encompassing both BRT trunk lines and "Mikrotrans" feeder layers. The proposed framework is designed for universal scalability, utilizing city-agnostic metrics derived from complex network graph modeling. The methodology calculates Betweenness Centrality for node importance, while the Tortuosity Index (τ) is employed to quantify spatial sinuosity, with specialized logic to account for high-circuity loop services. Operational efficiency is further assessed through advanced numerical evaluations, including a Time Penalty Ratio against an idealized urban speed baseline and a novel Operational Waste Index (OWI) that correlates route sinuosity with service frequency. The analysis reveals a near-perfect correlation (0.99) between route tortuosity and scheduled delays, suggesting that temporal performance is fundamentally embedded in geometric design. While the primary BRT corridors maintain linear efficiency, 43% of the network, predominantly feeder services, exhibits significant circuity (τ > 1.5). By identifying a critical subset of systemic bottlenecks where high network centrality coincides with excessive tortuosity and high node density, this study highlights a strategic trade-off between maximizing spatial coverage and maintaining operational speed. These insights provide a scalable, data-driven framework for "Strategic Straightening" and network restructuring in megacities seeking to optimize first/last-mile connectivity

Since the 1972 Stockholm Conference, environmental concerns have gained prominence in the international agenda, leading to the establishment of the United Nations Environment Programme and strengthening global sustainability efforts (UNEP, 2022). Within this context, the circular economy (CE), conceptualized by Pearce and Turner (1989) based on Boulding’s earlier work, has emerged as a leading framework for aligning environmental and economic systems (Ghisellini et al., 2016). Recently, CE principles have expanded into urban mobility and transport systems (Pamucar et al., 2023), reinforcing the need to understand how circularity and sustainability are integrated in mobility research. SDG 11 – Goal 11.2 reinforces the relevance of mobility in building more resilient and sustainable cities. Therefore, this paper aims to systematically map the literature published in the Web of Science (WoS) database regarding circular mobility in sustainable cities. It also aims to identify the circular economy's strategy that could be adopted to promote a more sustainable transport system. A systematic literature review was conducted in February 2026 using a PICo-structured search strategy and PRISMA (2020) guideline. The strings “(circular econom*) AND (cit*) AND (mobilit*) AND (sustainab*)" were applied in the WoS database without any initial refinement. Only papers published in journals were selected (50). After following PICo and PRISMA guidelines, 27 papers remained for the systematic literature review. The findings indicate that, while sustainability in transport is widely discussed, explicit integration of circular economy principles into urban mobility remains limited and fragmented. Most studies focus on technological optimization and smart mobility systems, having electric vehicles and sharing vehicles as the main “sustainable strategies”. Fewer address systemic circular strategies such as resource loops, lifecycle, and governance integration. The social and governance dimensions are still overlooked. These findings revealed the absence of frameworks to support a more integrated and systemic circular mobility policy in (sustainable) cities.

Introduction:
Flooding increasingly disrupts everyday mobility in coastal cities, yet transport restoration is often assessed only in technical terms. Experience from recurrent flood events in Chennai shows that reopening roads and transit routes does not ensure equitable access. Low-income households, informal workers, women, the elderly, and persons with disabilities often face longer disruptions and higher recovery burdens. While most studies emphasise response and recovery, resilience is also shaped by mitigation and preparedness measures such as risk reduction planning, evacuation training, and institutional readiness. This study examines whether post-flood transport recovery is not only resilient but also equitable within the broader risk management cycle.

Methods:
The study develops an equity-centred framework integrating four resilience dimensions (robustness, redundancy, rapidity, and resourcefulness) with three justice dimensions (distributional, procedural, and recognition), across mitigation, preparedness, response, and recovery phases. A mixed-methods approach combines field observations, commuter and household surveys, mapping of informal mobility systems, stakeholder consultations, and spatial analysis. Indicators are standardised to generate a Resilience Index (RI), a Justice Index (JI), and an integrated Equity–Resilience Integration Index (ERII). Ward-level analysis identifies mismatches between system performance, preparedness capacity, and lived mobility experiences.

Results:
Findings reveal uneven recovery patterns. In several areas, infrastructure functionality returned quickly, yet vulnerable groups continued to face access barriers. Locations with weak preparedness—such as limited evacuation planning, low awareness, and poor institutional coordination—experienced prolonged disruptions. Informal and community-led mobility systems played a critical role in maintaining connectivity but remain under-recognised in formal planning.

Conclusions:
Evaluating resilience through a justice lens across the full risk management cycle exposes gaps overlooked by conventional metrics. The ERII framework provides a practical tool for integrating mitigation, preparedness, response, and recovery, supporting more inclusive and equitable transport recovery in flood-prone coastal cities.

Compact urban development is preferred as a central strategy for promoting sustainable urbanization worldwide. By facilitating shorter trip lengths, reduced travel demand, and promoting public transit facilities, compact urban development is widely associated with lower CO₂ emissions from transport. However, urban compactness has been mostly equated with high density, overlooking other spatial characteristics of compactness that shape travel pattern and emission outcomes. This study revisits the compact city paradigm by defining compactness through multiple spatial dimensions and examining their association with CO₂ emissions from transport in 28 Indian cities. Five dimensions of compactness—density, shape, contiguity, spatial concentration and fragmentation—are quantified using Landsat data. Spatial metrics are calculated using ArcGIS Pro and Fragstats. A two-step analytical framework is adopted to assess the relationship between dimensions of compactness and related emissions. An ordinary least squares (OLS) regression model with heteroskedasticity-consistent (HC3) standard errors examined linear effects, and a Random Forest model with leave-one-out cross-validation evaluated nonlinear patterns and verified the relative importance of each dimension. The results indicate that fragmentation is the strongest positive influencer of per-capita emissions, with spatially discontinuous urban growth considerably increasing CO₂ emissions from transport. In contrast, contiguity and spatial concentration exhibit strong negative correlations with emissions, showing that spatially aggregated development patterns reduce emissions. Density and shape compactness have negative but moderate impacts. The Random Forest analysis supports the relative importance ranking observed in the regression results. These findings imply that reducing fragmentation and strengthening contiguity and concentration could achieve greater emission reductions than increasing density alone. For rapidly urbanizing Indian cities, policies that encourage connected and concentrated compact urban developments are crucial for low-carbon mobility transitions. Future research could integrate inter-city connectivity and network centrality perspectives to better capture multi-scalar influences on transport CO₂ emissions.

Urban mass transportation research has predominantly focused on the metropolitan scale and population. However, with the growing body of urban literature on global cities and polycentric urban regions, it is timely to assess the rapid transit potential of urban regions comprising multiple cities in close proximity. Rather than relying solely on population size or spatial proximity, this study is based on the premise that high-capacity transit systems are more viable where strong business linkages exist between cities. In the Indian context, rapid transit research has largely concentrated on Tier-I cities, with limited attention to regions beyond these metropolitan areas. This study addresses the gap by focusing on urban clusters formed by Tier-II cities and evaluates their potential for regional rapid transit by assessing intercity firm linkages. However, the firm network is constructed using both Tier-I and Tier-II cities, as Tier-I cities function as key hubs in the national firm network and mediate a large share of intercity linkages. Firm linkages are derived from office location data of advanced producer service firms using the interlocking network model across 96 cities in India, thereby constructing a nationwide intercity business network. The subsequent cluster identification and evaluation focus only on spatially proximate Tier-II cities. Clusters are identified and evaluated in two configurations, city pairs and multi-city corridors. For each cluster, a composite index combines linkage intensity, network centrality, population, and intercity distance to rank clusters. The analysis is intended as a preliminary economic network based assessment of potential rather than system level feasibility. The results indicate that urban clusters with moderate population sizes can rank higher than larger clusters when strong business integration and network embeddedness are present. The findings highlight the importance of economic integration in shaping regional transit potential beyond conventional population-based criteria, informing policymakers in prioritizing capital intensive investments.

Urban planning is not merely a technocratic discipline but a socio-anthropological one. This paper advances a framework of creative sustainability to examine how cities can evolve into inclusive, adaptive, and caring ecosystems by integrating ecological intelligence, cultural continuity, participatory governance, ethically grounded digital innovation, blockchain infrastructures, and regulatory sandboxes. Responding to intersecting pressures of climate disruption, digital alienation, algorithmic governance, and widening urban inequality, the study argues that urban transformation must be guided by relational and normative principles rather than instrumental optimization alone. Drawing on Martin Heidegger’s philosophy of dwelling and the Greek ethic of synelixis, the paper critiques technocratic and corporate-driven paradigms of “smart” urbanism and emphasizes the importance of human-centered approaches.

The research employs a conceptual and comparative methodology, synthesizing insights from urban theory, sustainability studies, and digital governance frameworks to develop an integrated analytical model. It proposes combining ecological justice, social sustainability, democratic governance, and adaptive regulatory learning through responsible experimentation with digital infrastructures. Regulatory sandboxes are highlighted as mechanisms that enable cities to pilot innovative solutions safely, while blockchain is positioned as a tool for transparency, accountability, and participatory engagement in urban governance.

This paper contributes a theoretically grounded and policy-relevant model for antifragile, culturally attuned, and human-centered urban futures in which technology supports—rather than displaces—collective care, accountability, and everyday meaning. By bridging normative principles and practical experimentation, the framework offers guidance for cities seeking resilient, inclusive, and ethically responsible pathways toward sustainable urban transformation.

Air pollution represents a persistent ecological pressure in urban environments, influencing biodiversity and ecosystem functioning. Instrumental monitoring networks provide quantitative pollutant measurements but often lack fine spatial resolution and ecological integration. Epiphytic lichens are widely recognized as sensitive bioindicators of atmospheric quality due to their direct absorption of airborne substances and differential tolerance to contaminants. This study comparatively examines documented lichen diversity patterns across multiple European urban contexts, focusing on community variation along gradients of traffic intensity, urban density, and green infrastructure presence. Reported ecological indices, including species richness and atmospheric purity indicators, were evaluated in relation to environmental variables such as vehicular emissions, vegetation continuity, and urban morphology. Recurrent patterns were identified across urban areas. High-traffic zones consistently supported simplified communities dominated by pollution-tolerant crustose taxa, whereas residential and peri-urban green spaces maintained higher diversity including foliose and fruticose species sensitive to air contamination. Vegetated corridors and structurally complex green areas showed a mitigating effect, allowing greater species persistence even near emission sources. The convergence of biological responses across different geographic contexts demonstrates the robustness of lichen diversity as an indicator of urban air quality. Biological monitoring therefore represents a valuable complementary tool for spatial environmental assessment and supports its integration into sustainable urban planning and ecosystem management strategies.

Highland cities like Baguio face unique transportation challenges due to complex topography, hazard exposure, and increasing demand, yet there is limited empirical guidance on designing context-specific mass transit systems. This study aims to identify the most suitable corridor locations in Baguio City for implementing an effective urban transportation model. Using a mixed-methods approach, the research combines GIS-based terrain and hazard analyses, demand estimation, and passenger surveys to evaluate three key corridors—Marcos Highway, Naguilian Road, and Loakan Road—based on their topography, safety, demand, and operational viability. Indicators such as slope feasibility, stop catchment demand, and hazard avoidance were used to assess the suitability of each corridor for different modes of mass transit. The findings show that Naguilian Road accommodates the highest demand but has moderate hazard exposure, while Marcos Highway offers better safety and reliability with lower demand. Loakan Road, characterized by steep grades and hazard-prone terrain, presents significant challenges for fixed-guideway systems but remains critical for access to hillside communities. Based on these insights, a “BRT-lite plus feeder” network is proposed, emphasizing corridor-specific infrastructure improvements, hazard-informed station siting, and operational enhancements such as priority treatments and real-time dispatching. The recommended model aims to optimize demand, improve safety, and enhance service reliability within the city’s geographic constraints. This research contributes to urban mobility planning by demonstrating how tailored, data-driven corridor assessments can inform the development of practical, context-sensitive mass transit solutions for hazard-prone highland cities.

Smart mobility is often evaluated through congestion and travel-time indicators, yet urban transport operates within a coupled system in which digital infrastructure and energy objectives increasingly shape operational decisions. As electrification expands and cities report carbon outcomes alongside service reliability, the interaction between traffic management and energy performance becomes more visible. Data-driven control may reduce energy use indirectly by stabilising speeds, reducing stop–start driving, and improving bus reliability. However, sensors, communications, and cloud–edge systems consume power continuously, and their lifecycle costs are rarely incorporated into transport energy assessments.

This study conceptualises city-scale intelligent transportation platforms as energy-aware urban service systems and examines how energy considerations are embedded in management practice. A comparative case-study approach is applied to Hangzhou, Singapore, and Kuala Lumpur, where different governance logics have shaped the scaling of data-driven operations. Evidence is drawn from policy documents, implementation reports, and peer-reviewed literature, with attention to indicator definitions, baselines, and reporting scope.

Simulation experiments conducted on a representative metropolitan traffic network demonstrate that the proposed framework reduces overall transportation energy consumption by 21.4%, decreases average vehicle travel time by 17.8%, and improves traffic flow stability by 23.6% compared with conventional cloud-based mobility management systems. Furthermore, the system increases public transit utilization by 14.2% and reduces CO₂ emissions by approximately 18.5% through improved route coordination and congestion mitigation. These results indicate that integrating edge intelligence with energy-aware transport management can significantly enhance the sustainability, resilience, and public value of next-generation smart city mobility infrastructures. The findings suggest that differences in reported outcomes are closely linked to governance structures and evaluation frameworks, while metric heterogeneity and limited benchmarking constrain cross-city comparability.