Do hospital reform and ownership matter to Shenzhen hospitals in China? A Productivity Analysis

Author(s):  
Kok Fong See ◽  
Ying Chu Ng
BMJ ◽  
1897 ◽  
Vol 1 (1901) ◽  
pp. 1451-1451
Author(s):  
T. G. Horder
Keyword(s):  

BMJ ◽  
1896 ◽  
Vol 2 (1875) ◽  
pp. 1689-1689
Author(s):  
T. G. Horder
Keyword(s):  

BMJ ◽  
1867 ◽  
Vol 2 (358) ◽  
pp. 439-439
Keyword(s):  

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 284
Author(s):  
Ebru Bilici

With the advancement of technology in forestry, the utilization of advanced machines in forest operations has been increasing in the last decades. Due to their high operating costs, it is crucial to select the right machinery, which is mostly done by using productivity analysis. In this study, a productivity estimation model was developed in order to determine the timber volume cut per unit time for a feller-buncher. The Weibull distribution method was used to develop the productivity model. In the study, the model of the theoretical (estimated) volume distributions obtained with the Weibull probability density function was generated. It was found that the c value was 1.96 and the b value was 0.58 (i.e., b is the scale parameter, and c is the shape parameter). The model indicated that the frequency of the volume data had moved away from 0 as the shape parameter of the Weibull distribution increased. Thus, it was revealed that the shape parameter gives preliminary information about the distribution of the volume frequency. The consistency of the measured timber volume with the estimated timber volume strongly indicated that this approach can be effectively used by decision makers as a key tool to predict the productivity of a feller-buncher used in harvesting operations.


2021 ◽  
Vol 13 (13) ◽  
pp. 7401
Author(s):  
Sedef E. Kara ◽  
Mustapha D. Ibrahim ◽  
Sahand Daneshvar

This paper examines the dual efficiency of bioenergy, renewable hydro energy, solar energy, wind energy, and geothermal energy for selected OECD countries through an integrated model with energy, economic, environmental, and social dimensions. Two questions are explored: Which renewable energy alternative is more dual efficient and productive? Which renewable energy alternative is best for a particular country? Data envelopment analysis (DEA) is used for the efficiency evaluation, and the global Malmquist productivity index is applied for productivity analysis. Results indicate bioenergy as the most efficient renewable energy alternative with a 20% increase in average efficiency in 2016 compared to 2012. Renewable hydro energy, wind energy, and solar energy show a 17.5%, 16%, and 11% increase, respectively. The average efficiency growth across all renewable energy alternatives signifies major advancement. Country performance in renewable energy is non-monolithic; therefore, they should customize their renewable energy portfolio accordingly to their strengths to enhance renewable energy efficiency. Renewable hydro appears to have the most positive productivity change in 2016 compared to 2012, while solar energy regressed in productivity due to its scale inefficiency. All renewable energy alternatives have relatively equal average pure efficiency change. The positive trend in efficiency and productivity provides an incentive for policy makers to pursue further development of renewable energy technologies with a focus on improving scale efficiency.


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