scholarly journals An analysis on service efficiency in nursing homes and spatio-temporal variation in China

2020 ◽  
Author(s):  
Liangwen Zhang ◽  
Ying Han ◽  
Ya Fang
Keyword(s):  
Nursing Homes ◽  
Temporal Variation ◽  
Social Workers ◽  
Technical Efficiency ◽  
Influencing Factors ◽  
Tobit Model ◽  
Scale Efficiency ◽  
Eastern Region ◽  
Service Efficiency ◽  
Spatio Temporal

Abstract Background: Pension services market in China is still at the early stage, problems like low service efficiency and low quality of nursing care already exist. So it is inevitable to analyze the efficiency and productivity and spatio-temporal variation, as well as its influencing factors in nursing homes all over the country. Methods: Data Envelopment Analysis (DEA) and Tobit model were applied to integrate several quality measures into a comprehensive benchmarking model. We present nationwide results and analyze the spatio-temporal distribution of the (technical efficiency) TE and productivity of nursing homes among Eastern, Central and Western of China. Furthermore, Tobit model was performed to explore factors associated with TE. Results The average TE, pure technical efficiency (PTE) and scale efficiency (SE) of nursing homes for the 5-year period were 0.909. 0.928 and 0.979, respectively. The TE and SE decreased from 2012 to 2014, but improved after 2014. TE is 0.98 in the Eastern region, 0.93 of that in the Central region and 0.91 of that in the Western region, with a decrease range of 2%, 7% and 9%, respectively. The average improvement range of the five input indexes of the non-DEA effective nursing homes was 27.26%, 20.62%, 19.77%, 22.04%, and 38.84%, respectively. The influencing factors of efficiency value of nursing homes indicated that if there are more social workers, more patients in the nursing homes, and more employees who are aged 56 and above, the TE and productivity of nursing homes will be higher. Conclusions There was considerable space for TE improvement in nursing homes due to the low proportion of effective TE. The TE and SE presented a decreasing trend from 2012 to 2014, which implicated that the large SE in nursing homes with less previous standardized management should be emphasized. (total factor productivity changes)TFPC experienced a decrease in productivity due to the adverse alteration in technological changes and pure technical efficiency. The service efficiency in nursing homes is facing with the problem of imbalance of regional development. The efficiency value of nursing homes was influenced by age of employees, the number of social workers and the number of older people. The measures and suggestions on improving efficiency of care in nursing homes were put forward.

scholarly journals Service Efficiency of Nursing Homes Based on DEA and Tobit Model: a Longitudinal Study in China

2021 ◽  
Author(s):  
Liangwen Zhang ◽  
Ying Han ◽  
Ya Fang
Keyword(s):  
Nursing Homes ◽  
Social Workers ◽  
Influencing Factors ◽  
Rapid Development ◽  
Temporal Distribution ◽  
Tobit Model ◽  
Eastern Region ◽  
Reform Implementation ◽  
Care Services ◽  
Spatio Temporal

Abstract Background: Low utilization of care resources in China continues to be a challenging problem even though the rapid development of pension services. However, few studies have explored the utilization of care services with either the production of nursing homes at a national and longitudinal level. Methods: The present study analyzes the spatio-temporal distribution of TE and productivity of nursing homes by using the data from China Civil Affairs statistical yearbook (2012-2016). Analysis was conducted based on the Data Envelopment Analysis and Tobit model, which have been widely applied to integrate several quality measures as a comprehensive benchmark. Results: The average TE, PTE and SE of nursing homes were 0.909. 0.928 and 0.979 from 2012 to 2016, respectively. The TE and SE decreased from 2012 to 2014, but improved after 2014. TE is 0.98 in the Eastern region, 0.93 of that in the Central region and 0.91 of that in the Western region, with a decrease range of 2%, 7% and 9%, respectively. The average improvement range of the five input indexes of the non-DEA effective nursing homes was 27.26%, 20.62%, 19.77%, 22.04%, and 38.84%, respectively. The influencing factors of efficiency value of nursing homes indicated that if there are more social workers, more patients in the nursing homes, and more employees who are aged 56 and above, the TE and productivity of nursing homes will be higher.Conclusion: We find that TE of nursing homes in Western regions are all at the lowest, as the current facilities can neither provide equitable nor optimal access and utilization. The decline of the efficiency and productivity before the healthcare reform implementation in 2014 was significant, where the influencing factors could be age and gender of employees, the number of social workers, and older people. Finally, suggestions are put forward for improving the efficiency of allocation and utilization of care services.

scholarly journals Spatio-temporal variation in phytoplankton community and its influencing factors in Danjiangkou Reservoir

2016 ◽  
Vol 28 (5) ◽  
pp. 1057-1065
Author(s):  
WANG Yinghua ◽  
◽  
CHEN Lei ◽  
NIU Yuan ◽  
YU Hui ◽  
...  
Keyword(s):  
Temporal Variation ◽  
Influencing Factors ◽  
Phytoplankton Community ◽  
Danjiangkou Reservoir ◽  
Spatio Temporal

scholarly journals Does Low-Carbon City Construction Improve Total Factor Productivity? Evidence from a Quasi-Natural Experiment in China

2021 ◽  
Vol 18 (22) ◽  
pp. 11974
Author(s):  
Hongfeng Zhang ◽  
Lu Huang ◽  
Yan Zhu ◽  
Hongyun Si ◽  
Xu He
Keyword(s):  
Economic Development ◽  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Technical Progress ◽  
Scale Efficiency ◽  
Eastern Region ◽  
Low Carbon ◽  
Factor Productivity ◽  
City Construction ◽  
Low Carbon City

Low-carbon city construction (LCC) is an important strategy for countries desiring to improve environmental quality, realize cleaner production, and achieve sustainable development. Low-carbon cities have attracted widespread attention for their attempts to coordinate the relationship between environmental protection and economic development. Using the panel data from 2006 to 2017 of prefecture-level cities in China, this study applied the difference-in-differences (DID) method to analyze the effects of LCC on the total factor productivity (TFP) of the cities and its possible transmission mechanism. The results show significantly positive effects on TFP, but the effects on each component of TFP are different. Although the LCC has promoted technical progress and scale efficiency, it has inhibited technical efficiency. The accuracy of the results has been confirmed by several robustness tests. Mechanism analysis showed that the pilot policy of low-carbon cities has promoted technical progress and scale efficiency by technological innovation and the upgrading of industrial structure, but resource mismatches among enterprises have been the main reason for reduced technical efficiency. Regional heterogeneity analysis showed that the effects on TFP in the eastern region have been more significant than in the central and western regions. In the eastern region, they have promoted technical progress, while in the central and western regions, they have promoted technical progress and scale efficiency but hindered technical efficiency. This paper presents our findings for the effects of LCC on economic development and provides insightful policy implications for the improvement of technical efficiency in low-carbon cities.

scholarly journals Spatio-Temporal Variation of Health Production Efficiency Considering Environmental Pollution in China Based on Modified EBM and Spatial Econometric Model

2021 ◽  
Vol 9 ◽  
Author(s):  
Fan Liu ◽  
Gen Li ◽  
Ying Zhou ◽  
Yinghui Ma ◽  
Tao Wang
Keyword(s):  
Temporal Variation ◽  
Production Efficiency ◽  
Econometric Model ◽  
Spillover Effects ◽  
Eastern Region ◽  
Health Production ◽  
Spatial Econometric ◽  
Average Efficiency ◽  
Spatial Econometric Model ◽  
Spatio Temporal

In order to strengthen the construction of China's health industry and improve the health of the people, based on the data of 31 provinces and cities in China from 2009 to 2019, the improved EBM model is used to measure the health production efficiency of each region, and Moran index is used to study the Spatio-temporal variation of health production efficiency of each province. Finally, the spatial econometric model is applied to study the influencing factors of the Spatio-temporal variation of health production efficiency. The results show that generally speaking, the average efficiency of 31 provinces and cities is above 0.7, and the average efficiency of some regions is above 1. From the perspective of time variation, the average efficiency value in the eastern region and the middle region increases from 0.816 to 0.882 and from 0.851 to 0.861, respectively. However, the average efficiency value in the western region and northeast region decreases from 0.861 to 0.83 and from 0.864 to 0.805, respectively. From the perspective of spatial distribution, HH agglomeration and LL agglomeration exist in most regions. By comparing Moran scatter plots in 2009 and 2019, it is found that the quadrants of most regions remain unchanged, and LL agglomeration is the main agglomeration type in local space. There is a significant spatial dependence among different regions. From the perspective of spatial empirical results, Pgdp, Med, and Pd have a positive effect on health production efficiency. The direct effect and indirect effect of Pgdp, Med, and Gov all pass the significance test of 1%, indicating that there are spatial spillover effects of the three indicators. Each region should reasonably deal with the spillover effect of surrounding regions, vigorously develop economic activities, carry out cooperation with surrounding regions and apply demonstration effect to accelerate the development of overall health production.

scholarly journals Analysis on the Efficiency of Health Care Service Delivery and Influencing Factors in China: A Study Based on DEA-Malmquist Index and Tobit Model

2020 ◽  
Author(s):  
Kui Chen ◽  
Jun Ye
Keyword(s):  
Health Care ◽  
Health Service ◽  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Influencing Factors ◽  
Health Care Service ◽  
Health Care Expenditure ◽  
Tobit Model ◽  
Utilization Rate ◽  
Factor Productivity

Abstract Objective: To evaluate the changeing trend and influencing factors of medical and health service supply efficiency in 31 provinces of China.Methods: According to the input-output relevant index data of medical and health service in China from 2009 to 2018, data envelopment analysis- Malmquist(DEA-Malmquist) was used to calculate the total factor productivity, technical efficiency, and technical change. Meanwhile, Tobit model to analyzed the main effective factors of medical and health service supply efficiency in ChinaResults: In 2018, 21 provinces including Beijing, Shanghai, Zhejiang and Guangdong were effective in DEA of China's medical and health supply efficiency. Jilin, Heilongjiang, Jiangsu and Shandong were weak DEA effective, while Shanxi, Inner Mongolia, Liaoning, Anhui, Fujian and Xinjiang were not DEA effective. From 2009 to 2018, the total factor productivity of China's medical and health service supply has been decreased steadily, which was mainly affected by technological changes. From the perspective of regions, the technical efficiency and pure technical efficiency of medical and health service supply was the highest in the east, followed by the central and the western region. Associate’s degree or above, gross regional domestic product, and health care expenditure were significantly associated with the increasing of medical and health service supply efficiency.Conclusions: According to their own conditions and constraints, all localities should take targeted measures to strengthen the allocation and management level of medical and health resources, promote technological progress, give full play to the role of education and economic development, increase the expenditure on medical and health care, improve the utilization rate of beds, shorten the average hospitalization days, effectively improve the efficiency of medical and health services supply, and better provide health care for people.

scholarly journals Spatio-temporal variation characteristics of air pollution and influencing factors in Hebei province

2021 ◽  
Vol 36 (2) ◽  
pp. 411
Author(s):  
Zhen-fang HE ◽  
Qing-chun GUO ◽  
Jia-zhen LIU ◽  
Ying-ying ZHANG ◽  
Jie LIU ◽  
...  
Keyword(s):  
Air Pollution ◽  
Temporal Variation ◽  
Influencing Factors ◽  
Hebei Province ◽  
Variation Characteristics ◽  
Spatio Temporal

Spatio-temporal variation of soil moisture and its influencing factors in Chinese typical forest ecosystems

2021 ◽  
Vol 41 (2) ◽  
Author(s):  
常清青，何洪林，牛忠恩，任小丽，张黎，孙婉馨，朱晓波 CHANG Qingqing
Keyword(s):  
Soil Moisture ◽  
Temporal Variation ◽  
Influencing Factors ◽  
Forest Ecosystems ◽  
Spatio Temporal

Drivers of tourism growth

2016 ◽  
Vol 23 (5) ◽  
pp. 941-962 ◽  
Author(s):  
Jianping Zha ◽  
Zhiyong Li
Keyword(s):  
Technical Efficiency ◽  
Technological Progress ◽  
Output Growth ◽  
Tourism Industry ◽  
Central China ◽  
Scale Efficiency ◽  
Eastern Region ◽  
Main Driver ◽  
Tourism Economy ◽  
Factor Inputs

The article has constructed the nonparametric decomposition framework to measure the growth drivers of tourism economy, and analyzed the drivers with the input and output data of the tourism industry in 30 provinces of China from 2005 to 2012. The results show that the contribution of total factor productivity (TFP) was gradually overtaking that of the factor inputs in this period and became the main driver of Chinese tourism output growth, with its corresponding contribution rate jumping from 48.56% in 2006 to 76.55% in 2012. Technological progress was the key to the escalation of such contribution, while technical efficiency, scale efficiency especially, had a relatively smaller, slipping contribution to the growth and the contribution of pure technical efficiency was negligible, sliding from 51.44% in 2006 to 23.45% in 2012. The drivers for tourism economy growth differed from region to region, with the middle and western regions growing faster than the eastern region. The rise in Central China was mainly driven by scale efficiency, while that in the western region was mostly fueled by pure technical efficiency that appears to manifest in two distinct phases: drive of factor input in 2005–2008 and TFP drive in 2008–2012. The tourism economy of China became increasingly intensive from 2006 to 2012, where the contribution of TFP surpassed that of factor inputs and the growth was ever more driven by TFP.

scholarly journals Big Data Analysis of e-Commerce Efficiency and Its Influencing Factors of Agricultural Products in China

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yi Wen ◽  
Lingxi Kong ◽  
Gaoxiu Liu
Keyword(s):  
Influencing Factors ◽  
Tobit Model ◽  
Agricultural Products ◽  
Scale Efficiency ◽  
Agricultural Mechanization ◽  
Internet Users ◽  
Correlation Degree ◽  
Rural Revitalization ◽  
Dea Analysis ◽  
High Level

At present, the e-commerce industry of agricultural products plays a pivotal role in promoting income growth and helping rural revitalization. This paper collected relevant data in the recent 8 years (2012 to 2019) and used the DEA model and Tobit model to analyze the correlation degree between the efficiency and various influencing factors in China. DEA analysis results show that, in recent years, three efficiencies are quite different: the comprehensive efficiency and scale efficiency show an upward trend, while the pure technical efficiency remains at a high level. Tobit model results show that the number of urban Internet users, rural Internet users, logistics practitioners, the development of national economy are negatively correlated with e-commerce efficiency; the length of traffic construction has no significant correlation; the level of agricultural mechanization has a significant positive correlation. Hence, the paper puts forward four suggestions.

scholarly journals On Service Efficiency of Public Traditional Chinese Medicine (TCM) Hospitals of Hubei Province in 2017

2021 ◽  
Vol 271 ◽  
pp. 04039
Author(s):  
Yang Ke ◽  
Shuai Li-Na ◽  
Li Na ◽  
Chen Li
Keyword(s):  
Technical Efficiency ◽  
Returns To Scale ◽  
Hubei Province ◽  
Scale Efficiency ◽  
Management Information ◽  
Local Conditions ◽  
Policy Suggestions ◽  
Service Efficiency ◽  
Central Regions ◽  
Better Than

In order to put forward policy suggestions for improving the service efficiency of public TCM hospitals in Hubei Province, the statistics of 94 public TCM hospitals of Hubei Province in 2017 was collected by using the comprehensive statistical management information system of TCM there, and the service efficiency of TCM hospitals was analyzed with the DEA-BCC model. The research showed, in 2017, the average technical efficiency, pure technical efficiency and scale efficiency of public TCM hospitals in Hubei Province were 0.919, 0.939 and 0.979 respectively. There were 27.7% of hospitals with effective DEA, 39.4% with effective pure technical efficiency, 31.9% with effective scale efficiency, and 61.7% of public TCM hospitals with diminishing returns to scale. The pure technical efficiency is an important factor restricting the effective DEA of TCM hospitals in Hubei Province, and the scale efficiency also has to be improved. The service efficiency of grade Ⅱ hospitals of TCM are better than that of grade III, and hospitals in central regions are better than that of eastern and western regions. Therefore, local hospitals should take tailored reforms to improve service efficiency according to local conditions.

Sign in / Sign up

Export Citation Format

Share Document