Assessing the financial efficiency of healthcare services and its influencing factors of financial development: fresh evidences from three-stage DEA model based on Chinese provincial level data

Author(s):  
Hongda Liu ◽  
Wangqiang Wu ◽  
Pinbo Yao
1997 ◽  
Vol 17 (4) ◽  
pp. 307-336
Author(s):  
Douglas S. Frink

Contract archaeology accounts for the majority of archaeological studies conducted in Vermont. As these studies serve the development community, the focus of investigation has been to identify and avoid sites, not to research and evaluate the information they contain. Native-American site locational models have limited application because they are based primarily on the landforms' proximity to water. The Archaeology Consulting Team is developing a contextual model based on reconstructing the pre-European settlement environment. Hypotheses comparing expected size and function of Native-American sites in different environments can be posed at the Phase I level of archaeological studies. Furthermore, with Phase I level data, these hypotheses can provide the framework for research designs at Phase II and III levels of archaeological study.


Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1328
Author(s):  
Jianguo Zhou ◽  
Shiguo Wang

Carbon emission reduction is now a global issue, and the prediction of carbon trading market prices is an important means of reducing emissions. This paper innovatively proposes a second decomposition carbon price prediction model based on the nuclear extreme learning machine optimized by the Sparrow search algorithm and considers the structural and nonstructural influencing factors in the model. Firstly, empirical mode decomposition (EMD) is used to decompose the carbon price data and variational mode decomposition (VMD) is used to decompose Intrinsic Mode Function 1 (IMF1), and the decomposition of carbon prices is used as part of the input of the prediction model. Then, a maximum correlation minimum redundancy algorithm (mRMR) is used to preprocess the structural and nonstructural factors as another part of the input of the prediction model. After the Sparrow search algorithm (SSA) optimizes the relevant parameters of Extreme Learning Machine with Kernel (KELM), the model is used for prediction. Finally, in the empirical study, this paper selects two typical carbon trading markets in China for analysis. In the Guangdong and Hubei markets, the EMD-VMD-SSA-KELM model is superior to other models. It shows that this model has good robustness and validity.


2014 ◽  
Vol 1006-1007 ◽  
pp. 472-476
Author(s):  
Wei Wang ◽  
Wei Ping Yang ◽  
Ge Yi Liu

With the development of modern logistics system, the automatic logistics distribution centers have been built in most tobacco enterprises. The packaging system plays important role in the distribution center, it is necessary to construct a set of scientific method to evaluate the packaging system mode. According to the real situation of tobacco logistics distribution center, the cost and benefit are set to the general goal. For these three modes of packaging system, packaging by hand, automatic packaging and packaging by heat-shrinkable material, the evaluation index system and hierarchical structure are built. Refer to the hierarchical chart and the principle of AHP, the weight of each index is calculated. On the basis of weight that worked out by AHP, the final evaluation result can be found and analyzed follow the principle of fuzzy comprehensive evaluation. Finally, reference the consequences of the FCE, the DEA model based on FCE is used to enhance the integrality and systematic of the evaluate result.


2006 ◽  
Vol 45 (4II) ◽  
pp. 873-890 ◽  
Author(s):  
Muhammad Sabir ◽  
Zehra Aftab

It is apparent from various labour force surveys that during the past 20 years Pakistan’s employed labour force has become more “educated”. For instance, according to the Labour Force Survey 1982-83, 28 percent of the employed labour force had attained formal education.12 In comparison, the literate employed labour force in 1999- 2000 is estimated at 46 percent, while the formally educated is 43 percent. However, the pattern of growth in educated labour force is not uniform in all four provinces of the country. A closer look at disaggregated provincial level data reflects the disparity in employed labour force in the four provinces: Punjab, Sind, NWFP, and Baluchistan.


Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3081 ◽  
Author(s):  
Zeng ◽  
Lu ◽  
Liu ◽  
Zhou ◽  
Hu

With the challenge to reach targets of carbon emission reduction at the regional level, it is necessary to analyze the regional differences and influencing factors on China’s carbon emission efficiency. Based on statistics from 2005 to 2015, carbon emission efficiency and the differences in 30 provinces of China were rated by the Modified Undesirable Epsilon-based measure (EBM) Data Envelopment Analysis (DEA) Model. Additionally, we further analyzed the influencing factors of carbon emission efficiency’s differences in the Tobit model. We found that the overall carbon emission efficiency was relatively low in China. The level of carbon emission efficiency is the highest in the East region, followed by the Central and West regions. As for the influencing factors, industrial structure, external development, and science and technology level had a significant positive relationship with carbon emission efficiency, whereas government intervention and energy intensity demonstrated a negative correlation with carbon emission efficiency. The contributions of this paper include two aspects. First, we used the Modified Undesirable EBM DEA Model, which is more accurate than traditional methods. Secondly, based on the data’s unit root testing and cointegration, the paper verified the influencing factors of carbon emission efficiency by the Tobit model, which avoids the spurious regression. Based on the results, we also provide several policy implications for policymakers to improve carbon emission efficiency in different regions.


2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Wenjia Wei ◽  
Agne Ulyte ◽  
Oliver Gruebner ◽  
Viktor von Wyl ◽  
Holger Dressel ◽  
...  

Abstract Background Regional variation in healthcare utilization could reflect unequal access to care, which may lead to detrimental consequences to quality of care and costs. The aims of this study were to a) describe the degree of regional variation in utilization of 24 diverse healthcare services in eligible populations in Switzerland, and b) identify potential drivers, especially health insurance-related factors, and explore the consistency of their effects across the services. Methods We conducted a cross-sectional study using health insurance claims data for the year of 2014. The studied 24 healthcare services were predominantly outpatient services, ranging from screening to secondary prevention. For each service, a target population was identified based on applicable clinical recommendations, and outcome variable was the use of the service. Possible influencing factors included patients’ socio-demographics, health insurance-related and clinical characteristics. For each service, we performed a comprehensive methodological approach including small area variation analysis, spatial autocorrelation analysis, and multilevel multivariable modelling using 106 mobilité spaciale regions as the higher level. We further calculated the median odds ratio in model residuals to assess the unexplained regional variation. Results Unadjusted utilization rates varied considerably across the 24 healthcare services, ranging from 3.5% (osteoporosis screening) to 76.1% (recommended thyroid disease screening sequence). The effects of health insurance-related characteristics were mostly consistent. A higher annual deductible level was mostly associated with lower utilization. Supplementary insurance, supplementary hospital insurance and having chosen a managed care model were associated with higher utilization of most services. Managed care models showed a tendency towards more recommended care. After adjusting for multiple influencing factors, the unexplained regional variation was generally small across the 24 services, with all MORs below 1.5. Conclusions The observed utilization rates seemed suboptimal for many of the selected services. For all of them, the unexplained regional variation was relatively small. Our findings confirmed the importance and consistency of effects of health insurance-related factors, indicating that healthcare utilization might be further optimized through adjustment of insurance scheme designs. Our comprehensive approach aids in the identification of regional variation and influencing factors of healthcare services use in Switzerland as well as comparable settings worldwide.


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