Search Results (425)

To address surging and uncertain electricity customer demands, this paper proposes a data-driven electricity customer service scheduling (ECSS) optimization model to improve customer service quality and alleviate agent scheduling pressure. The method begins by building a demand analysis model based on customer feature extraction using the maximal information coefficient (MIC). An agent workforce sizing model is then developed by integrating the AHP–fuzzy comprehensive evaluation and Z-score standardization, accounting for call-volume proportion, hourly call-handling capacity, and time-period length. Furthermore, a demand–skill matching method is introduced between customer calls and agent skills. A particle swarm optimization (PSO)-based intelligent scheduling algorithm is established, with queuing time, skill level, and handling time as key objectives and constraints. Case-study validation shows that the model improves operational efficiency by approximately 26.28% and reduces annual labor costs by about 6.13%, thereby enhancing customer satisfaction, service center efficiency, and scheduling system economy. Full article

To address the technical challenge where traditional high-pressure, large-flow emulsion pump stations cannot adapt to the drastic flow rate changes in hydraulic supports due to the fixed displacement of their quantitative pumps—leading to frequent system unloading, severe impacts, and damage—this study proposes an intelligent flow control method based on the digital flow distribution principle for actively perceiving and matching support demands. Building on this method, a compact, electro-hydraulically separated prototype with stepless flow regulation was developed. The system integrates high-speed switching solenoid valves, a piston push rod, a plunger pump, sensors, and a controller. By monitoring piston position in real time, the controller employs an optimized combined regulation strategy that integrates adjustable duty cycles across single, dual, and multiple cycles. This dynamically adjusts the switching timing of the pilot solenoid valve, thereby precisely controlling the closure of the inlet valve. As a result, part of the fluid can return to the suction line during the compression phase, fundamentally achieving accurate and smooth matching between the pump output flow and support demand, while significantly reducing system fluctuations and impacts. This research adopts a combined approach of co-simulation and experimental validation to deeply investigate the dynamic coupling relationship between the piston’s extreme position and delayed valve closure. It further establishes a comprehensive dynamic coupling model covering the response of the pilot valve, actuator motion, and backflow control characteristics. By analyzing key parameters such as reset spring stiffness, piston cylinder diameter, and actuator load, the system reliability is optimized. Evaluation of the backflow strategy and delay phase verifies the effectiveness of the multi-mode composite regulation strategy based on digital displacement pump technology, which extends the effective flow range of the pump to 20–100% of its rated flow. Experimental results show that the system achieves a flow regulation range of 83% under load and 57% without load, with energy efficiency improved by 15–20% due to a significant reduction in overflow losses. Compared with traditional unloading methods, this approach demonstrates markedly higher control precision and stability, with substantial reductions in both flow root mean square error (53.4 L/min vs. 357.2 L/min) and fluctuation amplitude (±3.5 L/min vs. ±12.8 L/min). The system can intelligently respond to support conditions, providing high pressure with small flow during the lowering stage and low pressure with large flow during the lifting stage, effectively achieving on-demand and precise supply of dynamic flow and pressure. The proposed “demand feedforward–flow coordination” control architecture, the innovative electro-hydraulically separated structure, and the multi-cycle optimized regulation strategy collectively provide a practical and feasible solution for upgrading the fluid supply system in fully mechanized mining faces toward fast response, high energy efficiency, and intelligent operation. Full article

Food supply veterinarians, those who service the dairy, swine, poultry, small ruminant, and beef cattle industries, benefit society by protecting animal and public health and ensuring a safe, wholesome food supply. However, there are not enough entering the workforce to meet current and future demands. Non-formal learning environments can be used as a recruitment tool to provide participants with positive interactions and hands-on experiences. To build awareness of food supply veterinary medicine (FSVM) in youth, we developed an immersion program designed to provide high school students with hands-on experiences with food animal species. Day camps were held during the summers of 2022 and 2023, each coordinated with multiple partners at different locations in central Ohio. Year One camp utilized registration and post-test surveys and Year Two utilized matching pre- and post-test for analysis. Over the two programs, 110 participants engaged in hands-on experiences, including: outbreak investigations, measuring clinical parameters, performing diagnostics, and basic veterinarian procedures. Pre- and post-test evaluations were performed to measure changes in participants’ attitudes and perceptions, and a McNemars test was used to evaluate Year Two data. In Year One, we saw positive shifts in those interested in FSVM careers. In Year Two, we saw positive shifts in knowledge of FVSM careers, with biosecurity knowledge increasing. Outreach activities like day camps can be replicated in other locations to increase interest in FSVM careers. Full article

Cultural ecosystem services (CESs) are the non-material benefits people derive from ecosystems and are important for human well-being. Most research has focused on individual CES supply–demand relationships, with little systematic study of the overall CES structure, interactions, and mechanisms in metropolitan areas. This study takes the Nanjing Metropolitan Area as a case study, integrating multi-source geospatial data and employing the MaxEnt model, self-organizing maps (SOMs), Spearman correlation analysis, and the Optimal Parameters-based Geographical Detector (OPGD). It analyzes supply–demand matching, trade-offs, synergies, and drivers for four CES categories: aesthetic (AE), recreational entertainment (RE), knowledge education (KE), and cultural diversity (CD). The main findings are as follows: (1) CES supply and demand are spatially zoned: the core area has surplus supply, secondary centers are balanced, and the periphery has both weak supply and demand. (2) Three supply–demand bundles have distinct synergy and trade-off patterns: Bundle 1 primarily exhibits strong synergy between AE and CD; Bundle 2 shows a weak trade-off relationship; and Bundle 3 forms a synergy centered on AE. (3) The explanatory power of driving factors exhibits pronounced spatial heterogeneity: Bundle 1 is dominated by non-quantifiable social factors; Bundle 2 features dual synergistic drivers of population and transportation; and Bundle 3 demonstrates synergistic effects driven by facilities and economic factors. Overall, this study contributes an integrated metropolitan-scale framework that connects CES supply–demand mismatch patterns with bundle typologies, interaction structures, and bundle-specific drivers. The results provide an operational basis for targeted planning and coordinated ecological–cultural governance in the Nanjing Metropolitan Area and offer a transferable reference for other metropolitan regions. Full article

Community public sport facilities are core carriers of the national fitness public service system, with their supply–demand alignment directly linked to megacity governance efficiency and residents’ well-being. To address structural issues, such as “human–land imbalance” in facility layout, this study uses the 2010–2024 panel data from Shanghai’s 16 districts, applies supply–demand equilibrium theory, and integrates quantitative methods to analyze spatio-temporal supply–demand coupling and identify key influencing factors. The study yields four key findings: (1) The spatial distribution of facilities and population demonstrates a differentiated evolutionary trajectory marked by “central dispersion and suburban stability”. (2) Supply–demand alignment has continuously improved, as evidenced by the increase in coordinated administrative districts from six to thirteen. Nonetheless, the distance between sports facilities and population centers widened, suggesting that spatial adaptation remains incomplete. (3) Urban population growth exerts a significant positive impact on facility supply. Elasticity coefficients are generally high in suburban areas, while negative elasticity is detected in some central urban areas due to population outflow. (4) Facility construction intensity and residential activity intensity are core driving factors, with economic conditions, transportation infrastructure, and housing prices acting as key supporting factors. This study overcomes traditional aggregate-quantity research limitations, reveals megacity facility supply–demand “spatial mismatch” dynamics, and provides a scientific basis for targeted public sports facility layout and refined governance. Full article

Cultural ecosystem services (CESs) represent a critical link between ecosystems and human well-being and constitute a core foundation for regional sustainable development. The balance between CES supply and demand directly affects the coordination efficiency between ecological conservation and socio-economic development, making it a key prerequisite for ecosystem management, conservation planning, and policy formulation. This study focuses on the circum-Taihu region and integrates multi-source data to assess public perceived demand and spatial supply capacity of CESs. Supply–demand matching relationships are examined across three dimensions, namely, scenic beauty, cultural heritage, and recreation, through the construction of a region-specific CES quantitative indicator system. The impacts of multiple environmental factors on CES supply–demand dynamics are further explored to provide scientific support for coordinated ecological, cultural, and economic sustainability at the regional scale. The findings demonstrate the following: (1) the proposed methodology effectively quantifies CES perception and supply capacity in the circum-Taihu region. Scenic beauty exhibits the highest perception levels, whereas cultural heritage and recreation show lower perception. Cultural heritage displays the strongest supply capacity, whereas scenic beauty and recreation exhibit weaker supply. (2) Significant spatial imbalances exist between CES perception levels and supply capacity across the circum-Taihu region. Areas exhibiting mismatches constitute the largest proportion for cultural heritage CESs, followed by scenic beauty, with recreation displaying the smallest amounts of imbalance. (3) Environmental drivers exert differentiated effects on CES supply–demand relationships. Slope, road network density, and elevation have significant positive effects, whereas the normalized difference vegetation index (NDVI), distance to water bodies, and distance to roads exhibit significant negative effects. Distance to roads imposes the strongest inhibitory influence on CES perception, whereas elevation emerges as the most influential driver of public perceived CES levels. Full article

Investigating the spatio-temporal differentiation patterns and driving factors of ecosystem services (ESs) supply and demand is of great significance for early warning of ecosystem imbalance risks and identifying regional natural resource supply–demand conflicts. This study takes the typical coal-grain overlapping area (CGOA) in Eastern China as the research object, dividing it into mining townships (MT) and non-mining townships (NMT) for comparative analysis. By integrating the InVEST model, ESs supply–demand ratio (ESDR) index, four-quadrant model, and the XGBoost-SHAP algorithm, the study systematically reveals the spatiotemporal differentiation characteristics and driving mechanisms of ESs supply and demand from 2000 to 2020. The results indicated that: (1) grain production (GP) service maintained a continuous supply–demand surplus, with the ESDR of NMT areas surpassing that of MT areas in 2020. The ESDR of water yield (WY) service was significantly influenced by interannual fluctuations in supply, showing deficits in multiple years. The decline in carbon sequestration (CS) service and sharp increase in carbon emissions led to a continuous decrease in the ESDR of CS service, with MT areas facing a higher risk of carbon deficit. (2) The spatial heterogeneity of ESs supply and demand was significant, with GP and CS services exhibiting a typical urban-rural dual spatial structure, and the overall region was dominated by the Type II ESs supply–demand matching (ESDM) pattern. The ESDR of WY service generally decreases from Southeast to Northwest across the region. with the Type IV ESDM pattern dominating in most years. (3) Human activities are the core driving force shaping the supply–demand patterns of ESs. Among these, land use intensity exhibits a nonlinear effect, high population density demonstrates an inhibitory effect, and MT areas are more significantly affected by coal mining subsidence. Natural environmental factors primarily drive WY service. The research findings can provide a scientific reference for the coordinated allocation of regional natural resources and the sustainable development of the human–land system. Full article

Grounded in the United Nations Sustainable Development Goal 4 (SDG4), specifically addressing the urgent need to increase relevant skills for decent work (Target 4.4) while ensuring inclusive access and quality (Targets 4.3, 4.5, 4.c), this study develops a province-level indicator system for the “talent chain” and “industry chain” and integrates entropy-weighted composite evaluation, a coupling coordination model, correlation tests, and mismatch typology classification to systematically assess the alignment between higher education talent formation and industrial demand across 31 Chinese provinces during 2000–2022. The analysis aims to characterize China’s phase-specific progress in SDG4-consistent development at the education–industry interface and to provide a theoretical and empirical basis for improving graduate job matching. The results show that (1) overall talent–industry matching improved steadily from 2000 to 2022, yet pronounced regional disparities persist, with eastern provinces generally outperforming central and western regions; (2) educational quality and structural inputs—such as faculty capacity, per-student expenditure, and the composition of human capital—are the primary drivers of talent-chain performance, whereas expansion-oriented indicators exhibit limited marginal contributions, implying that sustainable graduate job matching hinges more on quality upgrading and supply-structure optimization than on quantitative expansion alone; (3) industry-chain advancement is jointly driven by industrial scale, structural upgrading, and employment absorptive capacity, with the tertiary sector playing a particularly prominent role in shaping demand for higher-skilled labor; and (4) a divergence in driving mechanisms—quality- and structure-oriented on the education side versus scale- and structure-oriented on the industry side—combined with regional heterogeneity produces stage-specific mismatch typologies, suggesting remaining scope for structural alignment between higher education systems and industrial upgrading. Overall, strengthening regional coordination, integration, quality, and upgrading drives synergistic development, advancing SDG 4 targets by validating that quality-driven education reform is the key lever for sustainable employment in China. Full article

(1) Background. The rapid development of the digital economy provides a new perspective for enhancing industrial chain resilience. This study examines how manufacturing firms’ digitalization affects their industrial chain resilience, drawing on resource dependence and dynamic capability theories, and explores spillover effects on upstream and downstream enterprises. (2) Data and Methods. Using panel data from Chinese listed manufacturing firms (2011–2023), we employ ordinary least squares (OLS) models to analyze the relationship, its mechanisms, and heterogeneity. We further match firms with their suppliers and customers to identify spillover effects. (3) Results. Digitalization significantly improves resilience, particularly by enhancing supply–demand matching and competitive capabilities. Effects are stronger for small, labor-intensive, and high-environment, social and governance (ESG) firms. Bargaining power and governance capability are key channels. Spillover effects are heterogeneous, with a stronger impact on downstream customers. (4) Discussion. The positive impact of digitalization varies by firm characteristics, and spillovers differ across the chain. These findings offer precise insights and policy implications for leveraging digitalization to strengthen industrial chain resilience. Full article

In recent years, global supply chains have become increasingly vulnerable to geopolitical tensions, pandemics, and energy crises, particularly in resource-constrained regions characterized by weak infrastructure and high transaction costs. Using panel data on A-share listed firms in China’s central and western regions from 2010 to 2022, this study examines the effect of firm-level digital transformation on supply chain resilience. We construct a digital transformation index and employ an instrumental-variable approach based on the interaction between terrain ruggedness and lagged digital transformation to address endogeneity concerns. Empirical results show that the digital transformation of enterprises has significantly enhanced the resistance and recovery capabilities of the supply chain, verifying its effectiveness in resource-constrained environments. Mechanism analyses reveal that this effect operates through increased supply chain diversification—especially customer diversification—and improved supply–demand matching enabled by more accurate demand forecasting and inventory management. Heterogeneity tests indicate that the resilience-enhancing effects are more pronounced among non-state-owned firms, manufacturing enterprises, and firms in less technology-intensive industries. Overall, our findings provide empirical support for transaction cost economics, dynamic capability theory, and the resource-based view, highlighting the strategic role of digital investment in strengthening supply chain resilience in infrastructure-constrained settings and contributing to the aims of Sustainable Development Goal 9. Full article

Shared manufacturing platforms improve the utilization of manufacturing resources by digitally matching demand with competing manufacturers and providing value-added services (VAS). Because VAS is costly and its benefits are jointly created, an appropriate cooperation mechanism between the platform and manufacturers is essential for achieving sustainable profitability. This study explores three cooperation strategies: (1) no-cooperation strategy (Model N); (2) cost-sharing strategy (Model CS); and (3) revenue-sharing (Model RS) strategy. This study establishes a shared supply chain model for each strategy, derives the equilibrium results, and compares the optimal performances. The results show that neither cost sharing nor revenue sharing guarantees a Pareto improvement: both parties benefit only when the negotiated cost-sharing ratio or revenue-sharing rate lies within a feasible range that properly balances the platform’s service cost burden and the manufacturers’ participation incentives. Additionally, equilibrium profits for both manufacturers and the sharing platform are decreasing as the value-added services (VAS) cost coefficient increases. Thus, the sharing platform should endeavor to decrease the VAS cost efficiency to reduce the VAS cost and enhance profits for all participants. These findings provide actionable guidance for selecting cooperation strategies and setting sharing parameters to achieve mutually beneficial outcomes in platform-enabled shared manufacturing. Full article

Against the global backdrop of urbanization and sustainable development, urban parks—key public spaces for carbon sequestration, heat island mitigation, and public health promotion—have made their service performance a critical metric for evaluating urban human settlement quality. However, traditional evaluations relying on static questionnaires and aggregate indicators often fail to capture the spatiotemporal dynamics of park usage and complex supply–demand relationships. To address this gap, this study developed a three-dimensional dynamic evaluation model (“Vitality Level, Demand Matching, Service Supply”) for 59 urban parks in Gongshu District, Hangzhou, integrating multi-source data (mobile phone signaling, POIs, park vectors, demographic statistics). The model includes nine indicators (e.g., Temporal Activity Difference, Vitality Stability Index) with weights determined via the entropy weight method. Empirical results show: (1) Gongshu’s park service performance presents a “core-periphery” spatial disparity, with high-performance parks concentrated in central areas (e.g., West Lake Culture Square) due to convenient transportation and diverse functions; (2) Performance levels vary significantly between weekdays and weekends, with higher stability on weekdays and more pronounced supply–demand mismatches on weekends; (3) Time-series cross-validation and Monte Carlo simulations confirmed the model’s robustness. This framework shifts park research from “static quantitative description” to “dynamic performance diagnosis,” providing a scientific basis for refined planning and efficient management of parks in high-density cities. Full article

Blue–green spaces are essential for mitigating urban heat islands. The matching between their supply and demand affects the fairness and effectiveness of urban cooling facilities. This study focuses on the third ring area of Urumqi, Xinjiang, China. Cooling supply indicators and cooling demand indicators for blue–green spaces are established. Using coupling coordination and bivariate spatial autocorrelation models, it evaluates the cooling supply-demand relationship during 2010–2020. Results show that: (1) There is a “suburban cold sources dominated, urban supply turned positive” pattern in the cooling supply of Urumqi’s blue–green spaces. (2) Cooling demand has a significant “dual-core spatial separation”. The physical demands are concentrated in the high-temperature patches around the city, while the social demands are mainly distributed in the core area of the urban district. (3) There is a severe supply–demand spatial mismatch, with extremely low coupling coordination. The core issue is that high-supply cropland cold sources are far from the high-social-demand urban area. This study provides an important scientific basis for formulating effective cooling strategies for oasis cities through the analysis of the supply and demand matching of blue and green space. It uniquely helps safeguard ecological security and residents’ health in arid-zone cities. Full article

Systematically assessing the supply–demand disparities of urban–rural ecosystem services (ES) is a key pathway to optimizing resource allocation, promoting urban–rural integration and advancing regional sustainable development. Taking Zhengzhou City as a case study, this research evaluates and compares urban–rural differences across four dimensions: potential supply, actual supply, real human needs (RHN), and effective supply. Furthermore, focusing on actual supply, the study integrates a geographical detector and Bayesian belief network to identify key driving factors, delineate optimal optimization zones, and propose differentiated management strategies. The results show that: (1) Urban RHN accounts for 69.70% of the total in Zhengzhou, with a spatial pattern of “higher in the east and core, lower in the west and periphery”, and the internal heterogeneity is significantly greater than that of rural areas. (2) Potential supply is “higher in rural areas and in the west”, whereas actual supply is concentrated in central urban districts, reflecting a net service flow from rural to urban areas. (3) High-level effective supply areas cover 37.28% of urban regions, about 18 percentage points higher than rural regions. Rural deficits are primarily caused by low conversion efficiency of supply rather than insufficient potential. (4) Optimal urban optimization zones are mainly distributed in peripheral urban streets, while rural zones are concentrated in eastern townships. Through multidimensional supply–demand comparison and spatial optimization, this study provides a scientific basis for the coordinated enhancement of urban–rural ES, differentiated governance and regional sustainable development. Full article

The supply–demand relationship of flood regulation services (FRS) plays a vital role in mitigating urban flooding. Yet, existing studies still fall short in the comprehensiveness of FRS indicators, the accuracy of assessment scope, and the fine-scale analysis needed to delineate spatial supply–demand features and precisely identify critical areas. Using Xiamen Island as a case study, we first quantify ecosystem-based FRS supply with the InVEST model and assess socioeconomic FRS demand under the H-E-V framework; second, we perform parcel-level supply–demand matching to identify spatial patterns and typologies; then, we diagnose FRS status via the coupling–coordination degree model (CCDM); and finally, we delineate flood-risk hotspots through priority-intervention grading. The results indicate that (1) higher FRS supply clusters in the south, southwest, and northeast, whereas demand is markedly higher in the central–northern sector, yielding an overall pattern of “pronounced mismatch in the central and north, with relatively sufficient supply along the periphery.” (2) Low supply–high demand zones exhibit the highest flood risk and contain higher proportions of industrial, transportation, and residential land. (3) These low supply–high demand zones are further subdivided into five priority-intervention levels, for which we propose tiered, differentiated risk-management strategies. Collectively, the findings clarify supply–demand mechanisms and mismatch characteristics, providing decision support for urban flood safety and sustainable development. Full article