China's dairy farming has presented a striking development in recent years.Under the dual constraints of environment and resources,it is of practical significance to increase the output of dairy farming and ensure...China's dairy farming has presented a striking development in recent years.Under the dual constraints of environment and resources,it is of practical significance to increase the output of dairy farming and ensure the healthy and stable development of the dairy industry,by accurately comparing the differences in the farming efficiency of dairy farms at different scales and grasping key factors influencing the farming efficiency.This study,through the cost analysis of 263 scale farms across 23 provinces and regions of China in 2019,reaches a result that the cost of a single cow in a certain scale farm increases with the enlargement of the scale,and shows an inverted-U shaped curve with the relatively large scales(1001-2000 cows)at the highest point.It measures the farming efficiency of dairy farms at different scales through the data envelopment analysis and finds that the scale efficiency and allocation efficiency of scale farms in China are relatively high,while the technology efficiency and cost efficiency are relatively low.The efficiency of different scale farms is obviously different,where the cost efficiency,allocation efficiency and scale efficiency show a U-shaped curve as the scale enlarges(with the relatively large scale as the lowest point),while the technology efficiency gradually decreases as the scale expands.It is concluded that for the scale farms,feed conversion ratio and forage-to-concentrate ratio have a significantly negative impact on the scale efficiency,while the labor cost,number of employees,and depreciation of fixed assets are negatively correlated to the technology efficiency and cost efficiency of dairy farming.展开更多
Grasping the spatial correlation structure of transportation carbon emission efficiency(TCEE)and its influencing factors is significant for promoting high-quality and coordinated development of the transportation indu...Grasping the spatial correlation structure of transportation carbon emission efficiency(TCEE)and its influencing factors is significant for promoting high-quality and coordinated development of the transportation industry and the relevant region.Based on the ideal point cross-efficiency(IPCE)model,the social network analysis method was employed herein to explore the spatial correlation network structure of China’s provincial TCEE and its influencing factors.The results obtained showed the following outcomes.(1)During the study period,China’s provincial TCEE formed a complex and multithreaded network association relationship,but its network association structure was still relatively loose and presented the hierarchical gradient characteristics of dense in the east and sparse in the west.(2)The correlation of China’s TCEE formed a block segmentation based on the regional boundaries,and its factional structure was relatively obvious.The eastern region was closely connected with the central region,and generally connected with the western and northeastern regions.The central region was mainly connected with the eastern and western regions,and relatively less connected with the northeastern region.Besides,the northeastern region was weakly connected with the western region.(3)Shanghai,Beijing,Zhejiang,Guangdong,Jiangsu,Tianjin,and other developed provinces were in the core leading position in the TCEE network,which significantly impacted the spatial correlation of TCEE.However,Heilongjiang,Jilin,Xinjiang,Qinghai,and other remote provinces in the northeast and northwest were at the absolute edge of the network,which weakly impacted the spatial correlation of TCEE.(4)Provincial distance,economic development-level difference,transportation intensity difference,and transportation structure difference had significant negative impacts on the spatial correlation network of China’s provincial TCEE.In contrast,the energy-saving technology level difference had a significant positive impact on it.The regression coefficients of transportation energy structure and environmental regulation differences were positive but insignificant;their response mechanism and effects need to be improved and enhanced.展开更多
基金the Fund for Technological Innovation Project"Evaluation of Transformation Efficiency of Green Animal Husbandry Technology Achievements:Taking Dairy Industry as an Example".
文摘China's dairy farming has presented a striking development in recent years.Under the dual constraints of environment and resources,it is of practical significance to increase the output of dairy farming and ensure the healthy and stable development of the dairy industry,by accurately comparing the differences in the farming efficiency of dairy farms at different scales and grasping key factors influencing the farming efficiency.This study,through the cost analysis of 263 scale farms across 23 provinces and regions of China in 2019,reaches a result that the cost of a single cow in a certain scale farm increases with the enlargement of the scale,and shows an inverted-U shaped curve with the relatively large scales(1001-2000 cows)at the highest point.It measures the farming efficiency of dairy farms at different scales through the data envelopment analysis and finds that the scale efficiency and allocation efficiency of scale farms in China are relatively high,while the technology efficiency and cost efficiency are relatively low.The efficiency of different scale farms is obviously different,where the cost efficiency,allocation efficiency and scale efficiency show a U-shaped curve as the scale enlarges(with the relatively large scale as the lowest point),while the technology efficiency gradually decreases as the scale expands.It is concluded that for the scale farms,feed conversion ratio and forage-to-concentrate ratio have a significantly negative impact on the scale efficiency,while the labor cost,number of employees,and depreciation of fixed assets are negatively correlated to the technology efficiency and cost efficiency of dairy farming.
基金This research was funded by the National Science Foundation under the Project“Synergic evolution mechanism of intercity transportation and metropolitan tourism spatial pattern”[Grant number.41771162]It was also funded by the National First-Class Discipline Development Project in Hunan Province under the category of“Geography”[Grang number.510002].
文摘Grasping the spatial correlation structure of transportation carbon emission efficiency(TCEE)and its influencing factors is significant for promoting high-quality and coordinated development of the transportation industry and the relevant region.Based on the ideal point cross-efficiency(IPCE)model,the social network analysis method was employed herein to explore the spatial correlation network structure of China’s provincial TCEE and its influencing factors.The results obtained showed the following outcomes.(1)During the study period,China’s provincial TCEE formed a complex and multithreaded network association relationship,but its network association structure was still relatively loose and presented the hierarchical gradient characteristics of dense in the east and sparse in the west.(2)The correlation of China’s TCEE formed a block segmentation based on the regional boundaries,and its factional structure was relatively obvious.The eastern region was closely connected with the central region,and generally connected with the western and northeastern regions.The central region was mainly connected with the eastern and western regions,and relatively less connected with the northeastern region.Besides,the northeastern region was weakly connected with the western region.(3)Shanghai,Beijing,Zhejiang,Guangdong,Jiangsu,Tianjin,and other developed provinces were in the core leading position in the TCEE network,which significantly impacted the spatial correlation of TCEE.However,Heilongjiang,Jilin,Xinjiang,Qinghai,and other remote provinces in the northeast and northwest were at the absolute edge of the network,which weakly impacted the spatial correlation of TCEE.(4)Provincial distance,economic development-level difference,transportation intensity difference,and transportation structure difference had significant negative impacts on the spatial correlation network of China’s provincial TCEE.In contrast,the energy-saving technology level difference had a significant positive impact on it.The regression coefficients of transportation energy structure and environmental regulation differences were positive but insignificant;their response mechanism and effects need to be improved and enhanced.
