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Against the backdrop of China’s urban modernization pathway, the core value of urban innovation systems is increasingly shifting toward an inclusive orientation. Grounded in the theoretical connotation of inclusive urban innovation, this study establishes an evaluation index system covering equal participation opportunities, procedural fairness, and outcome sharing, and applies the entropy method, kernel density analysis, and spatial autocorrelation to empirically examine the spatial distribution characteristics and formation mechanisms of inclusive innovation spaces in Changsha. The results show that (1) Changsha’s inclusive innovation level presents a gradient decline from the central urban area to the periphery; (2) high–high clusters mainly in areas with stronger innovation–resource concentration and better public service conditions, such as Yuelu District and other districts associated with major innovation platforms. Low–low agglomeration zones cluster in peripheral urban areas like certain townships in Liuyang City and remote regions of Ningxiang City; (3) the spatial differentiation of inclusive innovation is jointly shaped by multiple factors, among which Cultural Education and Industrial Structure show relatively stronger explanatory power; and (4) improving inclusive innovation requires enhancing not only innovation agglomeration, but also public service accessibility, talent support, employment inclusion, and the local sharing of innovation outcomes. This study provides a systematic framework for evaluating urban inclusive innovation space and offers policy insights for promoting balanced and inclusive innovation development in regional innovation cities. Full article

Although sustainability has consolidated as a central criterion of value and performance in project management, a deep gap persists between its conceptual recognition and its effective application, making it difficult to structure and measure its real scope. Faced with this complexity, this study aims to dimension sustainable project management in productive sectors by analyzing its strategic alignment and operational trends. Methodologically, the research relies on a meta-aggregative review of 124 articles, integrating qualitative synthesis with quantitative structural analysis to decipher how the field is operationalized. Qualitatively, the results reveal that sustainability redefines project success, shifting toward the integral generation of long-term economic, social, and environmental value, contingent upon its anchoring in corporate strategy, governance, and the project lifecycle. However, quantitative analysis exposes an inherent thematic multidimensionality. The Latent Dirichlet Allocation (LDA) model identifies multiple simultaneous dimensions (entropy = 0.74), and the Principal Component Analysis (PCA) explains 27.24% of the cumulative variance. While these values align with the standard benchmarks for high-dimensional textual data, they empirically represent a highly complex and distributed knowledge structure rather than a unified theoretical framework. Consequently, while consolidated nuclei exist around management and governance, critical empirical gaps persist regarding risk integration, performance metrics, and, particularly, the circular economy. It is concluded that, although the discipline enjoys high theoretical legitimacy and growing measurement capabilities, its integration into operational decision-making remains partial. The ultimate challenge lies in articulating conceptual knowledge, tangible metrics, and strategic governance, ensuring that sustainability evolves from a declarative ideal into the inescapable, cross-cutting operational framework of project management. Full article

The past few years has witnessed the rapid development of China’s logistics industry. However, the industry still faces problems such as uneven regional development, low-cost efficiency, insufficient technology application, and pressure for green transformation. To support more effective policy and strategic planning, this study used composite location entropy, spatial autocorrelation analysis, and kernel density estimation to analyze the spatiotemporal evolution of logistics industry agglomeration based on China’s city-level panel data from 2010 to 2023. Geographic detectors and geographically weighted regression were used to explore its driving mechanisms from multiple perspectives. The results indicated that (1) China’s logistics industry agglomeration exhibited a decreasing gradient from east to west and the regional disparities gradually narrowed down over time. (2) China’s logistics industry showed significantly positive spatial autocorrelation, characterized mainly by high-high and low-low clusters. Northeastern China experienced the most active and tortuous local spatial evolution of logistics agglomeration, while Eastern China exhibited high tortuosity but stable spatial structure. Western China showed a smooth evolution, and Central China followed a relatively independent evolutionary path. Spatially, China’s logistics industry presented a pattern of high concentration in the southeast and sparse distribution in the northwest, with high-value zones expanding toward the central and western regions. (3) Transportation accessibility was the primary factor influencing logistics industry agglomeration, and the interaction among factors was stronger than the effect of individual factors. Specifically, the degree of openness exhibited a driving pattern centered on coastal areas and decreasing towards inland regions; the level of commercial development showed a positive correlation in the west and a negative correlation in the east; the spatial pattern of transportation capacity shifted from a pronounced east–west polarization to a more fragmented multi-cluster distribution; and transportation accessibility demonstrated spatial heterogeneity, with positive correlation in the southeast coastal areas and negative correlation in the west. Full article

The deep integration of the digital economy and education is a critical pathway to addressing the common challenges in less-developed regions, such as human capital shortages, unequal public service provision, and low developmental inclusiveness during new-type urbanization. Using panel data from 11 prefecture-level cities in Jiangxi Province from 2017 to 2024, this study first constructs a comprehensive index system to measure the integration level of the digital economy and education, as well as the inclusive development level of new-type urbanization. The entropy method is employed for objective weighting and composite score calculation. The spatiotemporal patterns of these two variables are visualized using hot spot analysis. A spatial Durbin model (SDM) with dual fixed effects is then applied to empirically examine the direct effect, spatial spillover effects, and regional heterogeneity of the digital-education integration. The main findings are as follows: (1) Both the integration level of the digital economy and education and the inclusive development of new-type urbanization in Jiangxi Province exhibit a distinct spatial pattern characterized as “high in the north, low in the south, and weak in the central region”, with significant spatiotemporal coupling between the two. (2) The digital-education integration exerts a significant positive direct effect on the local inclusive development of new-type urbanization. The core transmission mechanisms are the inclusive sharing of digital educational resources and the effective enhancement of human capital. (3) The integration generates a positive, albeit relatively weak, spatial spillover effect on neighboring areas. The strength of this spillover effect shows pronounced regional heterogeneity, being strongest in Northern Jiangxi, followed by Southern Jiangxi, and weakest in Central Jiangxi. (4) Economic development and industrial upgrading synergistically drive inclusive development alongside the digital-education integration. However, unequal social security provision remains a significant inhibiting factor for inclusive development. Full article

As a core driver of high-quality urban–rural integration, digital inclusive finance plays a key role in the process of Chinese-style modernization. After measuring the level of high-quality urban–rural integration development using the TOPSIS entropy method, this study employs fixed-effects models and mediation models to empirically examine how digital inclusive finance influences high-quality urban–rural integration development over the period from 2012 to 2022. The main findings are as follows: (1) Digital inclusive finance has a significantly positive promoting effect on high-quality urban–rural integration. (2) The enabling effect of digital inclusive finance exhibits significant regional heterogeneity, following a gradient pattern of “strongest in the Eastern region, followed by the Central region, and weakest in the Western region.” (3) In terms of dimensional effects, the breadth of coverage contributes the most, followed by the depth of use, while the degree of digitalization has the smallest impact. (4) The mediation mechanism indicates that factor mobility indirectly promotes high-quality urban–rural integration. Based on the above findings, this paper proposes policy recommendations to foster high-quality urban–rural integration development in China. Full article

Enhancing agricultural economic resilience (AER) is essential for global food security. As a key policy tool for stabilizing agricultural production, policy-based agricultural insurance lacks rigorous causal evidence on its impact on resilience. In this study, AER is operationalized as a composite index capturing resistance and recovery capacities across pressure, state, and response dimensions. Using 2012–2023 provincial panel data from China (31 provinces × 12 years = 372 observations), we measure AER via the entropy method and identify policy effects using a staggered multi-timepoint difference-in-differences (DID) model. We find that policy-based staple crop insurance significantly increases AER by approximately 2.5 percentage points, primarily by promoting agricultural technological innovation (ATI) and regional industrial structure upgrading (RIS). The improvement effects are more pronounced in central and western regions, non-major staple-crop producing areas, and regions with higher natural risks. Robustness is confirmed via event study, alternative weighting schemes (PCA and equal weighting), and placebo tests. This study provides reliable causal evidence for the resilience-enhancing effect of agricultural insurance and clarifies its internal transmission mechanisms, offering empirical support for the optimization of agricultural risk governance policies. Limitations include the use of provincial-level aggregate data and the lack of analysis of spatial spillover effects between regions. Our findings suggest that differentiated policy implementation can support more sustainable and targeted agricultural risk governance. Full article

This study investigates the coupling relationship between urban–rural integration and the value realization efficiency of agricultural ecological products in China. Based on panel data from 30 provinces from 2012 to 2022, the SBM-GML model is used to measure agricultural ecological product value realization efficiency, and the entropy method is used to measure urban–rural integration. The coupling coordination model, Dagum Gini coefficient, kernel density estimation, and Markov chain analysis are then used to examine the spatiotemporal pattern, regional differences, dynamic evolution, and convergence characteristics of the coupling system. The results show that urban–rural integration and agricultural ecological product value realization improved overall, but regional disparities remain significant. The coupling coordination level presents a clear spatial gradient, with the eastern region performing better than the central, western, and northeastern regions. Regional disparities continue to widen, mainly due to inter-regional differences and trans-variation density. The Markov chain results show strong path dependence and spatial spillover effects, while the convergence analysis indicates limited long-term convergence. This study provides an integrated framework for understanding the interaction between urban–rural integration and ecological value realization. It also highlights China’s mixed pathway of government guidance, market participation, factor flow, and ecological value transformation, offering policy implications for coordinated regional development and ecological product value realization. Full article

This study aims to reveal the spatial-temporal evolution rule and driving mechanism of cropland multifunctionality in major grain-producing areas. Taking Henan Province as the research case, we establish a comprehensive evaluation index system covering production, living, ecological and cultural functions based on multi-source datasets spanning 2013–2022. It adopts the entropy weight method, spatial analysis and geographical detector (GeoDetector) model to analyze the spatial-temporal differentiation characteristics and influencing mechanism of cropland multifunctionality systematically. The results show that the overall level of cropland multifunctionality in Henan Province rose from 2013 to 2022. Its spatial pattern presents a feature of high in the south and low in the north, with obvious agglomeration in southern Henan. The production function is high in the east and low in the west with a stable pattern. The living, ecological and cultural functions all show a distribution of high in the south and low in the north, with prominent regional differences. Factor detection results indicate that average slope, population density and average annual temperature are the core driving factors. The overall influence of natural factors is stronger than that of socio-economic factors. Interaction detection shows that all factors produce a strengthening effect, mainly in the form of nonlinear enhancement effects. Based on this, the research has proposed targeted and differentiated strategies for the management of cultivated land. Specifically, southern Henan should consolidate its inherent multifunctional advantages and strengthen the coordinated development of production, ecological and cultural functions. Northern and western Henan needs to mitigate terrain and climatic constraints, optimize agricultural infrastructure, and improve overall cropland service capacity. Eastern plain areas should further stabilize grain production function while balancing ecological protection. Central urban agglomerations should coordinate urban expansion and cropland protection to restrain multifunctional degradation. Full article

Against the backdrop of intensifying global uncertainties, enhancing the livelihood resilience of urban and rural residents is of paramount importance for promoting balanced regional development. This research establishes a 29-indicator evaluation system based on a three-dimensional analytical framework encompassing “buffering, adaptive, and transformative capacities”. resilience capacities. Utilizing county-level panel data from five pivotal former revolutionary base areas, specifically the Jiangxi–Fujian–Guangdong Former Central Soviet Area, Sichuan–Shaanxi Revolutionary Base Area, Shaanxi–Gansu–Ningxia Revolutionary Base Area, Dabie Mountains Revolutionary Base Area, and Zuojiang–Youjiang Revolutionary Base Area regions spanning from 2011 to 2023, through the integrated application of methodologies, including entropy weighting, kernel density estimation, the Theil index, and convergence analysis, we systematically examine the spatio-temporal variations and evolutionary mechanisms of livelihood resilience. Research findings indicate a general enhancement of livelihood resilience in old revolutionary base areas, albeit with notable regional disparities, presenting a tiered pattern characterized by Jiangxi–Fujian–Guangdong leading, Dabie Mountains and Sichuan–Shaanxi regions being intermediate, while Shaanxi–Gansu–Ningxia and Zuojiang–Youjiang areas lag behind. Buffering capacity predominates, while regenerative capacity constitutes the critical driver of regional disparities. The overall regional disparities are primarily driven by internal differences, with significant conditional β-convergence observed in livelihood resilience. This study proposes sustained advancement in infrastructure development to consolidate buffering capacity, a reinforcement of public services and technological innovation to enhance adaptive and regenerative capabilities, and the implementation of differentiated governance strategies, thereby fostering an overall improvement in livelihood resilience and coordinated regional development in old revolutionary base areas. Full article

Water Resource Carrying Capacity (WRCC) is a crucial measure for assessing the balance between regional water availability, socioeconomic development, and ecological needs, especially in arid and semi-arid regions. This study evaluates the spatiotemporal evolution of WRCC across 14 prefecture-level units in Gansu Province, China, from 2000 to 2023. A multi-dimensional evaluation system comprising 29 indicators across water resources, ecological environment, economy, society, and coordination subsystems was established. The Entropy Weight Method was applied to determine indicator weights and calculate a comprehensive index (CI) to quantify carrying pressure. A Random Forest model identified dominant influencing factors, and an autoregressive integrated moving average model projected trends from 2024 to 2028. The results show the provincial mean CI increased from 0.49 to 0.91, indicating intensifying pressure and a shift toward mild overload. Spatially, pressure exhibits a stable west–east gradient, with the highest levels persistently in western prefectures like Jiuquan, Jinchang, and Baiyin. In contrast, Gannan and Longnan in the south maintain lower pressure but show high interannual variability, indicating ecological sensitivity. The Random Forest model demonstrated strong performance, with training R² values exceeding 0.88 across all regions and mean absolute error mostly below 0.10. Projections suggest continued high pressure from 2024 to 2028 in the west, while central and southern regions show stable or slightly decreasing trends. These findings provide a quantitative basis for establishing differentiated, zoned water resource management and sustainable demand-side regulation strategies in water-limited regions. Full article

Energy system resilience is essential for maintaining energy security and system stability under growing global uncertainty. Based on panel data for 30 Chinese provinces over the period 2012–2023, this paper investigates the relationship between digital technology and energy system resilience. Digital technology and energy system resilience are measured with entropy-weighted composite indices, and the empirical tests are conducted using a two-way fixed-effects model, mediation-effect models, and a panel threshold model. The results show that digital technology significantly improves energy system resilience, and this finding remains stable after endogeneity treatment and several robustness checks. The mechanism analysis further shows that industrial structure upgrading, digital industrial agglomeration, and green innovation serve as important channels linking digital technology to energy system resilience. The threshold results further show that the effect of digital technology is stage-dependent. Digital technology has a positive effect in all three stages, with the strongest effect occurring in the medium digital development stage, followed by slower marginal improvement in the high digital development stage. The heterogeneity results show that the effect is more pronounced in provinces with high resource dependence and in the central and western regions. By contrast, the eastern region presents a weaker marginal effect, while the northeastern region faces stronger constraints in transforming digital technology into resilience improvement. These findings suggest that digital technology is an important driver of energy system resilience and can support a more stable and sustainable energy transition, although its effect varies across development stages and regional conditions. Full article

Urban flood susceptibility mapping is essential for disaster risk management in rapidly urbanizing regions. Although high-resolution Earth observation (EO) data provide detailed information for fine-scale flood analysis, existing studies are often limited by inadequate representation of drainage capacity, inappropriate spatial scales, and model uncertainty under sparse flood sample conditions. To address these issues, this study develops a multi-scale urban flood susceptibility mapping framework based on the Maximum Entropy (MaxEnt) model, integrating multi-source high-resolution geospatial data. A three-tier spatial unit system, including catchment, street, and grid scales, was constructed. Two models were developed at each scale using per capita drainage density (PCDD) and pipe density (PipeDen) as drainage capacity indicators. The results reveal significant scale-dependent differences in spatial autocorrelation, model performance, and variable responses. Compared with the PipeDen-based model, the standard deviation of AUC decreased by 37.5% and 25.0% at the catchment and street scales, respectively, and the model produced a more physically consistent relationship between drainage capacity and urban flood susceptibility. Considering the combined results of model performance, spatial autocorrelation, and response-curve analysis, the street scale PCDD-based model achieved the best overall performance among the six multi-scale models. Impervious area ratio, distance to roads, and annual maximum daily precipitation were identified as dominant factors influencing urban flood susceptibility. Based on the optimal street scale PCDD-based model, a 2 m resolution susceptibility map was generated, showing that high-susceptibility areas are mainly concentrated in highly urbanized central districts and along major transportation corridors. This study highlights the importance of spatial scale and drainage capacity representation in high-resolution urban flood susceptibility mapping. Full article

In response to increasingly complex risks and challenges and to safeguard national agricultural product supply security, this study constructs a four-dimensional evaluation index system encompassing “Resistance-Adaptation-Recovery-Innovation”. Utilizing panel data from 30 provincial-level regions in China from 2017 to 2023, and employing a comprehensive methodology including the entropy method, Dagum Gini coefficient, Markov chain, kernel density estimation, and convergence models, this research measures the resilience of China’s agricultural product supply chain and investigates its spatiotemporal evolution patterns. The findings are as follows: Firstly, the resilience level of the national agricultural product supply chain shows overall steady improvement, but regional development is uneven, presenting a pattern of eastern regions leading, central regions maintaining steady progress, and western regions catching up. Secondly, the overall resilience difference is strongly correlated with regional variability, with the most pronounced internal disparity observed in the western region. Thirdly, the evolution of resilience exhibits path dependency characterized by the coexistence of a “low-level trap” and “high-level stability”, and less developed regions demonstrate a significant “catch-up effect” towards their more developed counterparts. Based on these findings, this study proposes countermeasures such as implementing targeted policies for different regions, establishing cross-regional coordination mechanisms, strengthening dynamic monitoring and early warning systems, and promoting innovation-driven development and structural upgrading. These efforts aim not only to enhance China’s capacity to respond to risks in its agricultural product supply chain and ensure national food security, but also to provide valuable insights for other countries facing similar challenges in building resilient agricultural systems in an increasingly uncertain global environment. Full article

In the context of global market volatility and the pursuit of sustainable development, improving the financial resilience of manufacturing firms lays a critical foundation for high-quality development of the real economy. To explore the key channels through which ESG practices sustain financial stability amid external shocks, this study selects listed manufacturing enterprises in the Shanghai and Shenzhen A-share markets from 2015 to 2024 as the research sample based on the CSMAR database. It employs the entropy weight method to measure corporate financial resilience, uses a two-way fixed-effects model for benchmark regression, and conducts mechanism tests through mediation and moderation analyses to explore the underlying channels between ESG performance and financial resilience in manufacturing enterprises. The results indicate that improved ESG performance significantly enhances corporate financial resilience, and these findings remain robust after robustness tests and endogeneity treatments. ESG performance primarily enhances the financial resilience of manufacturing enterprises by alleviating financing constraints, increasing R&D investment intensity, and strengthening corporate environmental governance. Heterogeneity tests show that the positive impact of ESG performance on financial resilience is more pronounced in state-owned enterprises, manufacturing enterprises located in Central China, and those in the recession phase. Based on the above conclusions, this paper puts forward targeted suggestions for the government, manufacturing firms, and investors to promote ESG practices and boost financial resilience. Full article

Engineering consultants and design firms are central to the success of construction projects. However, the systematic evaluation of their performance in the Saudi Arabian context remains methodologically fragmented and empirically underdeveloped. Existing prequalification frameworks rely predominantly on administrative criteria and single-method ranking approaches that cannot adequately differentiate between high- and low-performing firms. To address this gap, the study proceeds in two distinct parts. Part I—Literature Review: A PRISMA-compliant systematic literature review across five major academic databases was conducted to map the existing evidence base, identify three substantive gaps in the Saudi and GCC engineering firm evaluation literature, and derive a consensus-based set of 29 performance criteria grouped into seven dimensions. This review constitutes an independent contribution: it establishes the gap that motivates the empirical work and provides the criterion framework on which that work is built. Part II—Practical Application: A structured questionnaire was administered to 288 construction professionals in Saudi Arabia (Cronbach’s α = 0.936), and the collected data were analyzed through a hybrid RII–Shannon Entropy Weighting (EWM)–TOPSIS pipeline that produced a Composite Priority Index (CPI) for each criterion, enabling a stable and discriminating ranking that integrates subjective expert consensus with objective distributional information. The main finding revealed that five criteria attained Very High Priority status (CPI > 0.70): Supervisory Experience (CPI = 0.740), Engineers’ Capability Index (CPI = 0.717), License Class (CPI = 0.709), Client Satisfaction Index (CPI = 0.708), and Average Delay Time (CPI = 0.705). These top-ranked criteria collectively center on technical leadership, regulatory standing, client-reported outcomes, and schedule reliability, indicating that procurement decisions should prioritize demonstrable competence over structural size or geographic footprint. The consistently lower importance of physical branch networks and headquarters location further suggests that remote management capabilities and digital coordination tools are reshaping performance expectations under Saudi Vision 2030. The Quality Indicators dimension achieved the highest mean CPI across all seven dimensions. The findings provide actionable evidence for procurement authorities, regulatory bodies, and engineering firms seeking to strengthen performance-evaluation practices in the Saudi construction sector. Full article