Search Results (5,363)

China’s dual-carbon goals require firms to pursue low-carbon transformation, while digital infrastructure offers new opportunities for corporate emission reduction. Using data from Chinese A-share listed firms from 2010 to 2024, this study treats the establishment of National Big Data Comprehensive Pilot Zones (NBDCPZ) as a quasi-natural experiment and applies a multi-period difference-in-differences model. The results indicate a statistically significant negative relationship between policy and estimated corporate carbon emissions. This result remains robust to parallel-trend tests, propensity-score-matching difference-in-differences (PSM-DID) estimation, and lagging control variables by one period. Mechanism tests suggest that the policy is negatively associated with estimated corporate carbon emissions through pathways consistent with green innovation, digital transformation, and easing financing constraints. Heterogeneity analysis indicates stronger effects among firms in highly competitive industries, non-heavy-polluting sectors, and southern China. Moreover, the pilot policy enhances corporate Environmental, Social, and Governance (ESG) performance. Overall, this study provides evidence that big-data-related policies can facilitate corporate decarbonization and offers policy implications for carbon reduction through data sharing, openness, and governance. Full article

Hybrid renewable energy integration (HREI) has recently emerged as a promising solution to promote energy sustainability and achieve carbon emission reduction in rural regions. However, how to evaluate HREI projects in an effective and comprehensive manner remains an urgent challenge, due to substantial uncertainties and the involvement of multiple stakeholders with heterogeneous interests. To address this issue, this paper applies a structured BOCR-based fuzzy MCDM framework to assess the multidimensional characteristics of HREI projects from the perspectives of benefits, opportunities, costs, and risks (BOCR). First, an indicator system for HREI project evaluation is established considering BOCR factors, comprising four dimensions and sixteen factors that reflect key concerns of relevant stakeholders. Second, triangular fuzzy number is employed to capture the inherent uncertainty and vagueness in expert evaluation information, while the Best–Worst Method is used to determine the indicator weights and represent their relative importance. Subsequently, the Preference Ranking Organization Method for Enrichment Evaluations II is introduced to evaluate the comprehensive performance of HREI projects and provide a complete ranking of alternative HREI projects. The results indicate that alternative A2 in the Henan province, which integrates wind turbines, rooftop photovoltaic system, battery energy storage, and vehicle-to-grid interaction with electric vehicles, exhibits the highest evaluated performance among the selected alternatives under the BOCR-based evaluation framework. Furthermore, sensitivity analysis and comparative consistency analysis show that the ranking remains stable under the tested weight-variation scenarios and alternative MCDM procedures. Full article

In Latin America, road planning and prioritization have focused on selecting roads based on traffic flow demand and population growth. Under this paradigm, rural roads are often underprioritized, despite having an impact on connectivity, access to services, territorial development, and spatial equity. This has led public programs to seek alternative funding sources to offset the road deficit in rural areas. However, road improvement programs lack support tools for the early formulation of efficient projects aimed at territorial sustainability. Thus, this research proposes an early planning tool for rural road improvement projects that contribute to territorial sustainability through a categorization method. To this end, a multi-criteria multi-objective evaluation model, the intelligent optimization algorithm Harmony Search, and discriminant analysis were used to categorize the sustainable contribution of rural roads within a territory. This study was applied to a case study of 101 rural road projects in the Araucanía region of Chile. The proposed categorization method identified four key criteria that influence the overall sustainability of the territory, as well as four differentiating categories by area. The proposed tool serves as an early planning guide for the design and location of rural roads, promoting a sustainable planning approach. Full article

The Alqueva Multifunctional Project was conceived as a development infrastructure for southern Portugal, promising agricultural modernisation, demographic stabilisation, job creation and territorial cohesion. This article examines the gap between these promises and the project’s outcomes through an analysis of documents, census data, sectoral indicators and a territorial case-study approach. The results reveal a clear paradox, as significant achievements were observed in the water, agriculture, energy and tourism sectors, including the expansion of irrigation, growth in exports, greater water security and innovation in the field of renewable energy. However, these sectoral gains have coexisted with ongoing depopulation, an ageing population, the precarious nature of the migrant workforce, land concentration, poor local value retention and growing environmental pressures. The article argues that this contradiction reflects a development model shaped by neoextractivism, accumulation through dispossession and the limited capture of territorial rent. Alqueva thus demonstrates how technically successful infrastructure projects can fail to generate inclusive territorial development when redistribution, institutional coordination and local integration remain inadequate and when effective mechanisms for spatial justice are lacking. Full article

The Sustainable Development Goals (SDGs) constitute an integrated framework for global sustainability, yet progress remains inconsistent across regions and indicators four years before 2030. Identifying the key issues and factors that influence SDG performance is therefore essential for effective implementation and the post-2030 sustainable development agenda. This paper presents a systematic review and thematic synthesis of empirical studies investigating the factors associated with SDG outcomes. Peer-reviewed studies published between 2015 and 2026 were identified across Scopus, Web of Science and PubMed databases and coded according to the SDGs examined, geographic scope, methodological approach and key findings. A total of 43 studies were selected from 684 initial records, covering all 17 SDGs across diverse geographical contexts. Seven cross-cutting themes were identified: governance and institutional capacity; socioeconomic status and cultural barriers; gender equality; education; technology, digital connectivity and innovation; environmental factors; and healthcare infrastructure and access. Theoretically, this review advances sustainable development literature by shifting the paradigm from single-goal evaluations towards an integrated, cross-cutting systems framework. Practically, it highlights the necessity of multi-sectoral financing, institutional capacity building and localised policy interventions to accelerate global progress leading up to and beyond 2030. Full article

Residential electricity demand in Bahrain is strongly shaped by long cooling seasons, high air-conditioning dependence and the operation of standardised housing typologies. This paper evaluates the energy and comfort implications of applying a controlled night-ventilation mixed-mode strategy to a representative Bahraini Ministry of Housing residential unit. The study compares two DesignBuilder/EnergyPlus scenarios: S0, a replicated closed-window baseline with split air-conditioning at a 24 °C cooling setpoint, and S1, a controlled mixed-mode case in which windows are available only during night-time periods when outdoor conditions are suitable for passive cooling. The base model is grounded in a published and validated Bahraini residential dataset containing geometry, construction properties, schedules, HVAC assumptions and monthly electricity bills, and was cross-checked against this dataset (see Methods for the monthly error statistics used to qualify this comparison). The replicated baseline produced 34,729.46 kWh/year, which differs from the published reference value of 34,720.19 kWh/year by only 0.027%. The S1 case reduced annual simulated electricity consumption to 33,593.04 kWh/year, corresponding to a saving of 1136.42 kWh/year, or 3.27% relative to S0. The benefit was highly seasonal: January, February, March and December accounted for 96.2% of the annual saving, while May to September showed no meaningful reduction. Hourly January outputs showed 425 zero-cooling hours out of 744 h (57.1%), cooling electricity of 87.32 kWh and a mean operative temperature of 23.81 °C. January thermal-comfort indicators (mean PMV +0.94; only 0.5% of hours within the ±0.5 PMV band) show that the strategy delivers real electricity savings but does not, on the PMV metric, guarantee acceptable comfort in every hour; the strategy is therefore best understood as a seasonal, humidity-aware operational measure that reduces cooling electricity in cooler months while carrying a thermal-comfort trade-off that requires either a tighter control-temperature threshold or explicit acceptance of a wider comfort range. Because the strategy yields no savings during the peak summer months, it should be positioned as a complement to—not a substitute for—envelope and HVAC-efficiency upgrades, and its economic case under Bahrain’s subsidised electricity tariff is modest and is presented here as indicative potential rather than a demonstrated payback benefit. By reducing residential cooling electricity without requiring building-fabric retrofit, the findings support the United Nations’ Sustainable Development Goals (SDGs), particularly SDG 7 (affordable and clean energy), SDG 11 (sustainable cities and communities) and SDG 13 (climate action), by contributing to sustainable, low-carbon operation of the residential building stock in hot–arid Gulf climates. Full article

Public participation plays a crucial role in modernizing urban renewal and advancing social sustainability; however, micro-renewal practices often navigate complex institutional coordination and varying levels of community engagement. To better understand these operational dynamics, this study adopts an institutional–behavioral analytical framework to examine how institutional mechanisms shape public participation, grounded in an empirical investigation of pocket parks in Shenyang, China. Integrating policy text analysis with 20 in-depth interviews framed within a citywide baseline of 3198 pocket parks, qualitative content analysis reveals that coercive, mimetic, and normative institutional pressures foster three distinct implementation pathways: Mandate-Driven, Exemplar-Driven, and Collaborative Co-governance. These pathways generate differentiated behavioral responses across four key stakeholder cohorts, while highlighting specific alignment opportunities regarding governance timing, feedback channels, and inter-departmental roles. To resolve these operational friction points and secure long-term social and institutional sustainability, we propose a full-lifecycle governance strategy offering group-tailored policy recommendations. This research bridges neoinstitutional theory with participatory spatial governance, providing actionable insights for advancing sustainable urban micro-renewal and stock space management. Full article

Commercial format diversity serves as a key indicator indicative of the health and resilience of the commercial structure in rail transit station areas. This study focuses on the rail transit station areas in Shanghai, integrates multi-source geospatial data with Partial Least Squares Structural Equation Modeling (PLS-SEM), and systematically examines the differential influence paths of six categories of factors—urban form, location, facility configuration, passenger flow, land rent, and commercial spatial form—on commercial format diversity between urban core and suburban areas. Multi-group analysis (MGA) is further used to test whether path coefficients differ across concentric zones around stations. The findings are as follows: (1) Passenger flow characteristics are the primary contributing factors to commercial format diversity and serve as a key mediator through which most other factors influence diversity. Location characteristics, particularly the distance to the rail transit station, primarily play a moderating role to commercial format richness. Urban form characteristics function as the “spatial framework” providing a fundamental regulatory influence, with significant interaction effects with station distance. (2) In urban core areas, the temporal rhythm of passenger flow dominates: weekday passenger flow is positively associated with commercial format richness, whereas weekend passenger flow shows a more complex pattern—associated with an increase in format count but declines in both diversity and dominance concentration, indicating a structural reorganization rather than a simple directional effect. In suburban areas, an initial increase followed by a decrease is observed, with an “optimal synergistic zone” existing approximately 600–1000 m from stations where rail transit and other public service facilities jointly promote commercial format diversity. (3) Land rent is mainly associated with the number of format categories rather than their evenness or dominance. These findings reveal systematic differences in the influence paths of commercial format diversity between urban core and suburban rail transit station areas, as well as the distance-dependent zonal variation patterns of these effects, providing empirical evidence for differentiated spatial design in the context of station-city integration. Full article

Urban parks are “cool islands” for mitigating urban heat, yet most snapshot-based assessments overlook intraday cooling dynamics and divergent mechanisms across park typologies. This study examines 52 parks in Wuhan, a humid city with routine park irrigation, using thermal data from Landsat 9 and ECOSTRESS across morning, noon, and nightfall. Through stepwise analysis and blue–green classification, we quantify diurnal cooling dynamics and their drivers. While previous studies have examined diurnal (within-day) cooling, multidimensional indicators, or scale effects separately, our contribution lies in establishing a multi-temporal assessment framework that integrates temporal dynamics with blue, green, and grey park typologies to reveal how cooling patterns diverge across blue, green, and grey parks throughout the day. Results show park cooling intensity (PCI) and gradient (PCG) peak at noon, while cooling area (PCA) remains stable. Elevated cooling efficiency (PCE) at nightfall is driven not by ecological cooling, but by the rapid thermal response of impervious surfaces with low thermal inertia. Area, greenspace proportion, and building height are primary drivers, shifting from scale dominance in the morning to vegetation and building at noon, with a preliminary transition range of approximately 14–16 hm² identified for this regime shift, though this finding warrants further validation with larger samples. Based on blue–green composition, parks are categorised as blue, green, or grey, with divergent cooling dynamics due to thermophysical properties. Blue parks cool steadily all day, green parks peak at noon, while grey parks’ elevated PCE at nightfall is an apparent thermal response, not ecological cooling. Typological heterogeneity weakens models that pool all parks together, as water storage, vegetation evapotranspiration, and impervious thermal response vary across types and cancel out when pooled. Findings show that single-time-phase or full averaging insufficiently captures park cooling dynamics, underscoring the value of considering both diurnal and typological variations in climate-adaptive planning for dense cities. Full article

Agricultural new quality productive forces (ANQP) provide an important foundation for high-quality agricultural development and sustainable rural transformation. Using panel data for 30 Chinese provinces from 2011 to 2022, this study examines the effect of digital financial inclusion (DFI) on ANQP and the channels through which that effect operates. The results show that DFI is significantly and positively associated with ANQP. A one-standard-deviation increase in DFI is associated with an increase in ANQP equivalent to approximately 64.35% of its sample mean. Green technological innovation serves as a statistically significant transmission channel, although its indirect effect accounts for only 3.31% of the total effect. The relationship between DFI and ANQP exhibits a double-threshold pattern with respect to the level of DFI and a single-threshold pattern with respect to regional economic development, with the estimated coefficients increasing gradually across regimes. Decomposing DFI shows that coverage breadth, usage depth, and digitization all contribute positively to ANQP. Further analysis of the outcome dimensions indicates that DFI is positively associated with agricultural laborers, agricultural labor objects, and agricultural labor resources. The estimated association is also larger in regions with more developed traditional financial systems. These results provide a multidimensional and stage-based understanding of the relationship between digital finance and agricultural productive-capability upgrading. Full article

New Light Rail Transit (LRT) systems are frequently promoted as a means of reducing car dependence and supporting urban sustainability; however, their effectiveness depends on how different traveller segments respond to LRT relative to competing modes. This study examines whether car owners and non-car owners exhibit distinct preference structures and policy sensitivities towards a proposed LRT system in Kerman, Iran. A stated-preference mode-choice survey conducted in November 2023 generated 1916 valid choice observations, including 955 observations from car owners and 961 from non-car owners, based on 736 completed questionnaires. Multinomial Logit (MNL), Nested Logit (NL), and Mixed Logit (MXL) models were estimated separately for each segment. Policy implications were assessed using elasticities, marginal effects, and scenario-based simulations. The results show that, for car owners, the MXL specification provides a slightly better statistical fit, indicating modest preference heterogeneity, while the main behavioural conclusions remain consistent across model structures. For non-car owners, the NL model performs best, revealing clearer substitution between public-transport modes (bus/LRT) and on-demand services (taxi/ride-hailing). Although LRT shows a negative baseline preference, particularly among car owners, its uptake increases substantially with improved LRT travel-time performance and higher private-car operating costs. Overall, improving LRT travel-time competitiveness is critical for both groups, while attracting car owners additionally requires coordinated measures that raise the generalised cost of private-car use and strengthen the relative advantage of LRT. These findings highlight the importance of segment-sensitive policy design for maximising the contribution of LRT to sustainable urban transport and long-term urban sustainability. Full article

The operation and management of urban dynamic systems often rely on information, including holiday and event calendars, to anticipate deviations from routine demand. However, such calendars cannot capture irregularly announced holidays or undocumented physical disruptions and require continuous maintenance. This study proposes Structural Equilibrium, a reference state for interpreting urban dynamic systems without external calendars. Temporal variation is represented as Concentration–Dispersion–Relative Balance (CDR) structural states under two representative Structural Equilibria: Information-oriented and Stability-oriented Equilibria. Applying the two Equilibria to Jeju Airport electricity consumption and Gangnam Station subway passenger-flow data showed that structural representations diverged at specific times, producing structural Gaps. Moving-block bootstrap analysis showed that these divergences exceeded the range typically expected under the dataset’s own temporal dependence structure. Without calendar information, the divergences corresponded to the 2024 Chuseok holiday period in the subway data and a government-designated temporary public holiday and major snowstorm in the airport data. One high-Gap observation at Jeju Airport had no external cause despite an unremarkable raw magnitude, showing that structural analysis can reveal unusual conditions overlooked by magnitude-based monitoring. These findings indicate that Structural Equilibrium supports calendar-independent interpretation and adaptive monitoring under changing conditions, contributing to resilient and sustainable urban infrastructure operation. Full article

Mobility-as-a-Service (MaaS) has emerged as a promising approach to urban transportation by integrating multiple mobility services into a single digital platform for trip planning, booking, and payment. More recently, Artificial Intelligence (AI) has expanded the capabilities of MaaS, enabling more efficient data processing, predictive analytics, personalized services, and intelligent decision support. This narrative review examines the current state of research on AI-enabled MaaS from both technological and socioeconomic perspectives. The analysis covers five major research areas: data integration and interoperability, predictive systems and demand forecasting, AI-enabled decision support for policy and planning, fairness and ethical AI, and cybersecurity and privacy protection. The findings show that successful implementation depends not only on advances in AI algorithms but also on high-quality interoperable data, effective governance, regulatory support, public trust, and collaboration among stakeholders. The review concludes that the main challenges facing AI-enabled MaaS are no longer primarily technical but organizational, institutional, and social. Future research should focus on trustworthy and explainable AI, privacy-preserving learning, standardized evaluation methods, fairness-aware optimization, resilient cybersecurity, and long-term assessments of MaaS impacts on sustainable urban mobility. Full article

Unbalanced regional development is a long-standing spatial feature of China. Most extant studies are restricted to a single economic dimension and lack long-run comprehensive analysis that couples the economic, social and ecological dimensions. Drawing on China’s provincial panel data from 1990 to 2023, this paper constructs a comprehensive indicator system across three dimensions, measures comprehensive development levels with the entropy-weight TOPSIS method, and decomposes the overall imbalance into within-region disparity, between-region net disparity and the intensity of transvariation with the Dagum Gini coefficient, revealing the spatiotemporal evolution of imbalance across the four major zones of Southeast, Central, Western and Northeast China. The results show that the three types of imbalance are not synchronized: economic imbalance first rose and then declined, social imbalance fluctuated more strongly, and ecological imbalance changed mildly. The distribution of intra-provincial social and ecological disparities across zones is markedly crossed, whereas the cross-zone overlap of economic disparities has continuously weakened since 2000, and the gradient has become clear again. Accordingly, this paper proposes policy recommendations including three-dimensional assessment, classified governance, industrial collaboration and ecological compensation. This study enriches the multidimensional measurement paradigm of regional imbalance and provides quantitative support for coordinating innovation resources and promoting coordinated regional development. Full article

Coordinated population, economic, and land urbanization across counties is essential for sustainable metropolitan development. Factor flows between central cities and their surrounding counties are closely associated with urbanization levels across counties within metropolitan areas. Using multi-source data for 12 counties in the Hefei Metropolitan Area, China, in 2023, we measure population, economic, and land urbanization through equal weighting and characterize bidirectional population, logistics, capital, technology, and information flows between the central urban area and the counties. Fuzzy-set qualitative comparative analysis (fsQCA) identifies configurations associated with the three urbanization dimensions. Population urbanization shows the greatest intercounty disparities, followed by economic and land urbanization. Economic urbanization exhibits a clear core–periphery pattern, population urbanization a partial one, and land urbanization a dispersed pattern. Factor flows cluster mainly near the central urban area but show neither uniform distance decay nor one-way diffusion. No single flow is necessary. Inflow configurations center on capital or logistics–information for high population urbanization, capital-information for high economic urbanization, and capital–technology for high land urbanization. Outflow configurations center on information with or without capital, capital–information, and capital and/or information, respectively. These findings provide a configurational basis for differentiated county-level strategies and contribute to understanding how bidirectional metropolitan linkages can support more coordinated and sustainable urbanization within comparable metropolitan contexts. Full article