Job-home linkages connect residential locations to employment centers, forming a relational structure within urban systems. The emergence of hybrid work raises the question of whether different levels of hybrid work correspond to distinct spatial networks. Using district-level mobility data for Spain from 2022 to 2024, this study combines home-to-work flows with recurrent mobility and uses workplace-attendance frequency as a proxy for hybrid-work intensity in constructing layered networks. A graded and directed network approach compares national structures, examines within-district relationships, and traces variation across settlement urbanity and established network position. It also distinguishes districts as residential origins and employment destinations, allowing the residential and employment sides of spatial flexibility to be examined separately. The results show that greater inferred hybrid-work intensity corresponds to broader and less concentrated job-home networks, with the greatest geographic reach appearing at the most flexible end of the gradient. These associations remain directional and uneven across settlement contexts and network positions. The associations are stronger for employment catchments than for residents’ employment fields, while established centers retain their structural advantages. Higher hybrid-work intensity is therefore associated with a broader geography of labor-market matching alongside a persistent hierarchy of employment destinations. The findings suggest that the spatial flexibility associated with hybrid work can coexist with uneven network advantages across regions, with implications for regional inequality.
Climate change amplifies urban extreme precipitation (UEP), seriously jeopardizing the housing markets’ sustainability in developing economies. However, the nonlinear and spatially heterogeneous economic effects of UEP on housing prices remain underexplored. Consequently, an illustrative framework was proposed to quantify UEP’s impacts on property values. Taking Shanghai as a testbed, UEP was estimated using a percentile-based method with high-resolution remote sensing datasets from an intra-urban perspective. After multi-model benchmarking, a Monte Carlo Simulation-based interpretable ensemble learning model was developed to decouple the spatially nonlinear and heterogeneous association between UEP and housing prices across varied intra-urban submarkets (e.g., topographical, morphological, functional, and locational typologies). The modelling results unveil a nonlinear response and threshold effects: the impacts oscillated around + 1,500 RMB/m2 as UEP fell below 34 mm due to the potential trade-offs between environmental performance and housing prices. Above the threshold, housing prices experienced a significant decrease of approximately 4,000 RMB/m² (from + 1,500 to -2,500 RMB/m²), as the UEP increased from 34 to 42 mm. Moreover, the heterogeneous patterns of property values were explored across varied UEP types. The adverse effects were 2.5 times larger in low‑lying than in high‑elevation submarkets, twice as large in high‑density as in low‑density neighbourhoods, most severe in industrial zones, and highest in peripheral areas, followed by central areas. These spatially heterogeneous findings directly inform policy implications, including prioritising sponge‑city retrofits in low‑lying and high‑density neighbourhoods; mandating flood‑proofing certificates and risk‑based mortgage terms for industrial and peripheral properties; and adjusting property taxes or resilience bonds according to local vulnerability.
As Uzbekistan undergoes rapid economic transformation, this study investigates how the structural shift toward a diversified, non-farm labour market alleviates poverty across its 14 administrative regions. We quantify how this transition is conditioned by localised thresholds in physical infrastructure, digital connectivity, and human capital. Analysing a 2010–2024 macro-panel dataset, our empirical strategy employs a rigorous general-to-specific spatial econometric framework. Following exploratory spatial data analysis that confirms significant regional clustering, we primarily utilise a Two-Way Fixed Effects Spatial Durbin Model (SDM) to robustly handle cross-sectional dependence and explicitly quantify inter-regional spillovers, while deploying a Spatial Autoregressive (SAR) model to evaluate core-periphery heterogeneity. While initial estimates suggest non-farm employment (NFE) directly reduces poverty, robust spatial models reveal that this structural shift is highly conditional and often spatially conditioned. Crucially, a core-periphery heterogeneity analysis shows that expanding the NFE share yields significant poverty reduction only within Urban Core regions. In contrast, structural labour shifts in the Rural Periphery fail to reduce local poverty without a foundational baseline; instead, these isolated regions rely heavily on regional capital investment for inter-regional welfare spillovers and digital infrastructure expansion for local economic inclusion. Consequently, to sustainably bridge the spatial welfare divide, policymakers must abandon uniform interventions in favour of spatially tailored strategies, transitioning from basic digital and transport capacity-building in peripheral regions to advanced economic absorption strategies in developed hubs.
Mass rapid transit can reduce congestion, emissions and road-safety externalities in rapidly urbanizing cities, but only if passengers can conveniently reach and leave its stations — access and egress are often the weakest link in the door-to-door journey. This reciprocal relationship, in which Non-Motorized Transport (NMT) provision shapes metro accessibility and ridership while metro investment creates the case for NMT infrastructure spending, is termed here the NMT–Metro Nexus. This paper is a structured literature review of 99 sources (92 via a documented search-and-screening protocol, plus 7 later additions; see Methodology) from Scopus, Web of Science and Google Scholar, organised across four themes: sustainable public transport in Indian cities, travel behaviour of NMT users in station catchments, policy and planning frameworks, and public-transport accessibility and NMT integration in Indian metros, using Nagpur Maha Metro as a contextual, illustrative application rather than an empirical case study. The review compares findings across contexts, notes where Tier-1 (Delhi, Mumbai) and Tier-2/mid-sized-city evidence diverge, and identifies three gaps: limited station-level empirical evidence for Indian metros, no integrated NMT planning framework, and limited attention to rapidly motorising mid-sized cities such as Nagpur. Drawing on accessibility, distance-decay and node–place theory, the review interprets station catchments as a distance-decay function of access-mode speed, comfort and safety rather than a fixed radius, and reads Nagpur’s stations as exhibiting a node–place imbalance in which line-haul capacity has outpaced first/last-mile place-quality. Building on this evidence, the review proposes a preliminary NMT-catchment planning framework pairing distance-based catchment bands (walking, cycling, feeder Intermediate Public Transport) with four integration dimensions — physical, network, fare-operational and institutional — plus indicative implementation steps for Nagpur Metro planners; the framework is conceptual and requires station-level validation before wider application.
Under the background of rapid urbanization and vigorous development of night economy, night living street is the core place for residents’ outdoor activities at night, and its spatial quality optimization has attracted wide attention. However, at present, the night living street space mostly depends on the traditional subjective evaluation system, and lacks the quantitative support of objective physiological data. This study presents a systematic application of electroencephalography (EEG) technology to quantify the multi-space elements of night living streets. It systematically investigates the potential effects of these spatial elements on residents’ physiological responses, and achieves bidirectional validation between subjective and objective physiological data by combining EEG data with subjective questionnaires. The experimental results indicate that the continuity and moderate enclosure of sidewalks enclosure are positively correlated with security and perceived order. The rich color, commercial activities and other interface vitality characteristics are also positively correlated with the spatial attraction, while the high spatial complexity is negatively correlated with the spatial clarity. At the level of lighting environment, especially high lighting density and warm color temperature lighting, there is a potential correlation with pedestrian comprehensive perception experience. This study provides empirical evidence for understanding the physiological response in the night living street environment, and provides a preliminary reference for urban night living street renewal.
