The impact of climate change and production technology heterogeneity on China's agricultural total factor productivity and production efficiency

Assessment of the resilience factors associated with European green efficiency

Climate change mitigation and socio-economic sustainability are high on the agendas of major world leaders. The European Union (EU) leads efforts in this regard by broadening sustainability to include climate neutrality, biodiversity, and social equity. This research provides novel insights into EU Member States' progress towards sustainability goals and the factors enhancing their resilience to environmental and socio-economic challenges. It thus contributes to the green transition by meeting a threefold objective: (1) to quantify efficiency, differentiating between the two stages that define the green revolution-climate change mitigation and social protection/adaptation; (2) to assess whether productivity changes are due to better resource use or technological advances; and (3) to determine the resilience factors (economic, social, and institutional) associated with this process. The methods used are two-stage DEA-bootstrap, the Sequential Malmquist Index and the Generalized Method of Moments, applied to the EU for the period 2013-2022. The results show a lack of homogeneity across Europe in achieving established goals, both in terms of efficiency levels and in productivity advances. The latter come almost exclusively from technological innovations, with limited attention given to improving the use of available resources. Furthermore, GDP per capita, the employment rate and active labour market policies stand out as the resilience factors that have the greatest influence on ecological efficiency levels. Accordingly, a practical application of the research findings would be to strengthen these factors. This recommendation provides a basis for guiding policies and strategies that facilitate continuous adaptation in the face of environmental adversity, thus helping to build a sustainable society that can respond flexibly to future events.

Regional healthcare resource allocation and decision-making: Evaluating the effectiveness of the three-stage super-efficiency DEA model

This study addresses the challenge of achieving a more rational allocation of medical resources at the regional level, using Guangxi Province, China, as a case study. A three-stage super-efficiency Data Envelopment Analysis (DEA) model is employed to assess and analyze the effectiveness of resource allocation. The research methodology involves identifying input, output, and environmental variable indicators to construct a healthcare resource allocation index system. The indicator data are processed using Excel software. The three-stage super-efficiency DEA model is then applied to evaluate the healthcare system in Guangxi Province, focusing on Pure Technical Efficiency Change (PEC), Scale Efficiency Change (SEC), Efficiency Change (EC), Technological Change (TC), and Total Factor Productivity (TFP). Finally, the Malmquist index method is utilized to measure and dynamically analyze the efficiency of healthcare resource allocation. The study's results show that, from a static perspective, the average comprehensive efficiency is 1.067 before adjustment and 1.054 after adjustment, indicating relatively high overall efficiency in healthcare resource allocation in Guangxi Province. However, environmental factors and random errors have led to an overestimation of healthcare resource allocation efficiency, which the three-stage super-efficiency DEA model effectively corrects. Additionally, the average SEC and PEC values are 0.997 and 0.998, respectively, both below 1. This indicates that both scale efficiency and pure technical efficiency contribute to a decline in technical efficiency. Based on the results of the sensitivity analysis, the conclusions regarding the efficiency of healthcare resource allocation in Guangxi are deemed highly reliable. Despite the influence of uncertain factors, the model consistently provides stable and coherent assessment results in most scenarios. Therefore, special attention is needed to improve scale efficiency in healthcare resource allocation within the region, alongside enhancing management and technological capabilities in the healthcare sector. Overall, this study provides valuable reference and guidance for researchers and practitioners in related fields and offers scientific decision support for healthcare resource allocation.

Research on the impact and mechanism of digital economy on China's food production capacity

Enhancing and strengthening food production capacity has always been a top priority in agricultural research, serving as a cornerstone for ensuring national food security and stable economic development. This study, based on panel data spanning from 2011 to 2021 across 30 provinces in China, delves into the mechanism through which the digital economy impacts food production capacity. Employing a double fixed effect model, a mediation effect model, and a panel threshold model, we uncover several key findings: The digital economy significantly boosts food production capacity, with robustness tests affirming the reliability of our results. Mechanism analysis reveals that the digital economy enhances food production capacity by elevating total factor productivity and bolstering agricultural resilience. The threshold effect underscores that urbanization levels exhibit a single-threshold impact, wherein the influence of the digital economy on food production capacity intensifies upon crossing this threshold. Heterogeneity analysis reveals that the digital economy significantly boosts food production capacity in central and primary grain-producing regions, while its impact is comparatively weaker in the eastern and western regions, as well as in non-primary grain-producing areas. In summary, this research sheds light on the pivotal role of the digital economy in augmenting food production capacity, offering valuable insights into regional variations and thresholds in its impact across China.

The impact mechanism and empirical analysis of financial efficiency of science and technology empowering regional real economy growth

With the aim of exploring the impact mechanism of scientific and technological financial efficiency on regional real economy growth in the context of ecological civilization construction, this study introduces environmental regulation as a mediating factor. By analyzing changes in science and financial efficiency of science and technology, we provide an effective basis for regional real economy development. To achieve this goal, we define concepts such as science and financial efficiency of science and technology and regional real economy, measure data from 2012 to 2021, analyze the impact of science and financial efficiency of science and technology on economic growth using intermediary models, test mediation effects with bootstrap methods, and identify significant differences between regions. It indicates that enhancing science and financial efficiency of sci-tech benefits China's regional real economy growth, but there's unbalanced development across regions. Additionally, environmental regulation serves as a crucial intermediary in the relationship between sci-tech finance and economic growth. There exist regional disparities in the mediation effects of environmental regulation, with eastern regions demonstrating stronger effects compared to central and western regions.

Assessing energy efficiency, regional disparities in production technology, and factors influencing total factor energy productivity change in the agricultural sector of China

Efficiently utilizing the energy resources in the agriculture sector to produce more agricultural output with minimum environmental degradation is a shared global challenge. The Chinese government has introduced various policies aimed at enhancing energy efficiency (EE) and total factor energy productivity (TFEP) while addressing regional technological disparities in the agricultural sector. This study utilized DEA Super-SBM, Meta frontier Analysis, and the Malmquist-Luenberger index to assess energy efficiency, changes in total factor energy productivity, and the regional technology gap ratio (TGR) across 30 provinces in mainland China and three distinct regions during the period from 2000 to 2020. The findings reveal that the average EE in China's agricultural sector is 0.8492, indicating that, on average, there is a 15.08 % potential for improvement in EE growth within the sector. Qinghai (1.5828), Shanghai (1.3716), and Hainan (1.3582) are found to be the top 3 performers with the highest EE levels. The Eastern region demonstrates high excellence in EE, with a value of 1.0532. The TGR value of Zhejiang indicates the superior production technology utilized in the agriculture sector to utilize energy resources efficiently. Except for Zhejiang, the TGR of Liaoning, Jiangsu, Shanghai, Guangdong, Ningxia, and Hainan is above 0.96 and near 1, indicating superior production technology in the agriculture sector of China. The Technology Gap Ratio (TGR) of China's eastern region is superior to that of the central and western regions, consistently approaching 1. This suggests that the eastern provinces possess more advanced agricultural technologies, allowing them to optimize resource utilization for maximum output. The Malmquist-Luenberger index (MLI) score of 1.103 indicates a 10.3 % growth in the total factor energy productivity of China's agricultural sector. Further analysis reveals that this growth is primarily driven by technological change (TC), with a TC value of 1.080 surpassing the efficiency change (EC) value of 1.028. Among the three agricultural regions, the eastern region exhibits the highest total factor energy productivity. Specifically, Zhejiang (1.23), Shanghai (1.197), Liaoning (1.184), and Hebei (1.147) are identified as the top performers in total factor energy productivity growth in China's agricultural sector. Additionally, the Kruskal-Wallis test confirmed statistically significant differences in EE and TGR among the three regions.

Development of a new environmentally friendly and efficient centrifugal variable diameter metering device

Introduction

The design of the maize metering device involves centrifugal variable diameter pneumatic and cleaning mechanisms, aiming to enhance the performance and power efficiency of pneumatic maize metering devices. Leveraging the impact of changes in centrifugal diameter and the guidance and positioning of airflow, we optimize the hole insert, seeding plate, seed limit board, and integrated front shell. This optimization facilitates the adjustment of both the quantity and posture of seed filling. As a result, seeds can form a uniform flow within the annular cavity, reducing the wind pressure necessary for regular operation and decreasing power consumption.

Methods

A quadratic regression orthogonal rotation combination experiment is conducted using a self-made experiment bench, considering ground speed, wind pressure, and seeding rate as the experiment factors. Furthermore, a comparative experiment involving a novel centrifugal variable-diameter type metering device.

Results

The results indicate optimal seeding performance when the ground speed is 13.2 km/h, the wind pressure is 1.2 kPa, and the feeding rate is 25 seeds/s. Under these conditions, the quality of feed index reaches 95.20%, the multi-index is 3.87%, and the miss index is 0.93%. Findings reveal that the developed seed metering device achieved a quality of feed index exceeding 93.00% across varying speeds of 12~18 km/h, aligning with the production requirements. Moreover, the actual power consumption of Type B and C is about 85.00% and 98.00% lower than Type A, standing at only 32.90 W at 18 km/h. The COP of Type C is about 86 times and 12 times that of Type A and B, respectively, meeting the demands for efficient production of maize seed metering devices.

Discussion

In comparison to traditional design and structural parameter optimization methods for maize seed metering device, this study is helpful to the sustainable development of maize industry and reduce environmental pollution.

Dynamic evolution of utilization efficiency of medical and health services in China

In order to optimize the Chinese medical and health system and improve people's health level, the SFA Malmquist model, the spatial econometric model, and the standard deviation ellipse method were used to measure the efficiency of medical and health services in China's 31 provinces between 2010 and 2020. Study results indicated that the average efficiency value of the 31 provinces generally exceeded 0.8. Specifically, the average efficiency values in the eastern and central regions increased from 0.852 to 0.875 and from 0.858 to 0.88, respectively. In the western and northeastern regions, these values rose from 0.804 to 0.835 and from 0.827 to 0.854, respectively. From the perspective of spatial distribution, there were high-high and low-low clusters in most provinces with significant spatial dependence among them. This analysis reveals that medical and health services efficiency in China demonstrates a spatial pattern extending from northeast to southwest.

Spatiotemporal evolution characteristics and influencing factors of the crop water use efficiency in watersheds based on the water footprint

Climate change has exacerbated the contradiction between water scarcity and sustainable agricultural development. Assessing the crop water use efficiency and its influencing factors could provide a decision-making reference to realize Sustainable Development Goal 2. By analyzing the temporal and spatial evolution characteristics of the crop water footprint, the blue water footprint, green water footprint, and grey water footprint were introduced into the super efficiency slack-based measure model to evaluate the crop water use efficiency in basins. The influence of the driving factors was examined by using the geographic detector model. The situation in the provinces along the Yellow River Basin from 2005 to 2020 was used as a verification case. The results indicated that (1) during the study period, crop water use in the basin was mainly based on the blue water footprint, accounting for approximately 55% of the total water footprint, the grey water footprint, accounting for approximately 30% of the total water footprint, and the green water footprint, accounting for the lowest proportion, at approximately 15%. (2) The crop water use efficiency exhibited a spatial distribution pattern of high values in the east and low values in the west, with obvious upstream provinces disposable income of rural residents (0.71) > population urbanization rate (0.65) > degree of agricultural mechanization (0.63) > agricultural disaster rate (0.61). Furthermore, the interaction effects between the driving factors were greater than the effects of the single factors. The study provides an important reference for understanding the changes, driving mechanisms, and impacts of crop water use efficiency in basin areas. It promotes green agricultural transformation and development to address climate change and alleviate the pressure on water resources.

Omics approaches in understanding the benefits of plant-microbe interactions

Plant-microbe interactions are pivotal for ecosystem dynamics and sustainable agriculture, and are influenced by various factors, such as host characteristics, environmental conditions, and human activities. Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, have revolutionized our understanding of these interactions. Genomics elucidates key genes, transcriptomics reveals gene expression dynamics, proteomics identifies essential proteins, and metabolomics profiles small molecules, thereby offering a holistic perspective. This review synthesizes diverse microbial-plant interactions, showcasing the application of omics in understanding mechanisms, such as nitrogen fixation, systemic resistance induction, mycorrhizal association, and pathogen-host interactions. Despite the challenges of data integration and ethical considerations, omics approaches promise advancements in precision intervention and resilient agricultural practices. Future research should address data integration challenges, enhance omics technology resolution, explore epigenomics, and understand plant-microbe dynamics under diverse conditions. In conclusion, omics technologies hold immense promise for optimizing agricultural strategies and fortifying resilient plant-microbe alliances, paving the way for sustainable agriculture and environmental stewardship.

Can digital economy compensate the effect of aging on total factor productivity?

In China, the number of senior citizens has grown, along with the burden of old age, and aging has hampered economic growth. The advent of the digital age has led to the emergence of the digital economy as a new engine for economic growth. This paper uses DEA-Malmquist index model to measure the total factor productivity growth rate of 31 provinces in China from 2011 to 2021, and uses the moderating effects model to empirically investigate the relationship between the digital economy, aging and total factor productivity, and to verify whether the development of the digital economy can mitigate the negative impact of aging on total factor productivity. The results show that aging inhibits total factor productivity growth, and the digital economy can promote total factor productivity growth. Digital economy can alleviate the negative impact of aging on total factor productivity growth, and has a moderating effect. Digital economy plays a moderating role by improving the level of human capital and facilitating technological progress. The regional heterogeneity analysis shows that the moderating effect of the digital economy exists in the eastern and western regions and the southern region, but not in the central region and the northern region. Furthermore, the digital economy has a moderating effect on both the high and low aging groups. The research in this paper not only helps to evaluate the productivity effects of the digital economy, but also has important implications for finding ways to mitigate the negative effects of aging.

Re-measurement and influencing factors of agricultural eco-efficiency under the 'dual carbon' target in China

Given that agriculture is both a carbon source and sink, the sustainability goals of carbon peaking and neutrality place high demands on the green and low-carbon agricultural development in China, and the exploration of a realistic path for a sustainable agricultural development is urgently needed. Under the above 'dual carbon' target, this study focused on the key issue of how to improve China's agricultural eco-efficiency (AEE) and constructed an innovative AEE indicator system that can reflect carbon constraint and coordinated agricultural economic development, resource use and ecological environment. The super-efficient slack-based measured Data Envelopment Analysis (SBM-DEA) method, which considers undesirable outputs, was applied to re-measure the AEE of 30 provinces and cities in China from 2001 to 2020, and its spatial and temporal evolution was analysed in conjunction with kernel density estimation. The Tobit regression model was used to explore various influencing factors by region. The results show that the AEE re-measurements, which take into account the 'dual carbon' requirement, are significantly better than the traditional AEE. From 2001 to 2020, China had an overall V-shaped fluctuation curve AEE, with a small decline and several inter-annual fluctuations, and exhibited a large potential to rise. China's AEE showed a spatially uneven regional development at different stages of distribution and evident multi-polar differentiation. Inter-provincial differences were observed in China's AEE, and the vicious circle of low-level green and low-carbon agricultural development was difficult to break. Urbanisation had a significant positive effect on national and eastern AEE but a significant negative effect on central AEE. The agricultural carbon offset rate had a significant effect on AEE nationally and in the three regions. Thus, the introduction of 'dual carbon' target effectively drove the development of AEE. Agricultural industry structure inhibited the improvement of AEE nationally and in the western region. Agricultural economic development hindered the national AEE improvement but promoted that of the central region, where China showed an environment Kuznets curve. Hopefully, this study can provide data support and theoretical reference for the green and low-carbon agricultural development and help achieve the 'dual carbon' target.

Climate change and dairy farming sustainability; a causal loop paradox and its mitigation scenario

It is arguable at this time whether climate change is a cause or effect of the disruption in dairy farming. Climate change drastically affects the productive performance of livestock, including milk and meat production, and this could be attributed to the deviation of energy resources towards adaptive mechanisms. However, livestock farming also contributes substantially to the existing greenhouse gas pool, which is the causal of the climate change. We gathered relevant information from the recent publication and reviewed it to elaborate on sustainable dairy farming management in a changing climatic scenario, and efforts are needed to gather this material to develop methods that could help to overcome the adversities associated with livestock industries. We summarize the intervention points to reverse these adversities, such as application of genetic technology, nutrition intervention, utilization of chemical inhibitors, immunization, and application of metagenomics, which may help to sustain farm animal production in the changing climate scenario.