scholarly journals Measuring the Efficiency of Public Hospitals in Kuwait: A Two-Stage Data Envelopment Analysis and a Qualitative Survey Study

2020 ◽  
Vol 12 (3) ◽  
pp. 121
Author(s):  
Abdullah M. Alsabah ◽  
Hassan Haghparast-Bidgoli ◽  
Jolene Skordis
Keyword(s):  
Technical Efficiency ◽  
Efficiency Score ◽  
Hospital Efficiency ◽  
Public Hospitals ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Factors Affecting ◽  
The Mean ◽  
Technical Efficiency Score

The recent drop in oil prices has challenged public sector financing in Kuwait. Technical and scale efficiency scores for fifteen public hospitals in Kuwait from 2010 to 2014 were estimated using a two-stage data envelopment analysis (DEA). Technical efficiency scores were regressed against institutional characteristics using Tobit regression to investigate the determinants of efficiency differences in hospitals. Semi-structured interviews were also carried out with fourteen public and private hospital managers to qualitatively explore their perceptions and experience about about factors affecting hospital efficiency. The mean technical efficiency score for all hospitals was 85.8%, an improvement of 2% since 2010. The mean pure technical efficiency score was 79.6%, improving from 75% in 2010 to 81.2% in 2014. The mean scale efficiency score was 91.8%, improving from 87.6% in 2010 to 94.2% in 2014. Only three hospitals were constantly technically and scale efficient. Tobit regression showed that hospital efficiency was significantly associated with the average length of patient stay. Hospitals with more than 400 beds were potentially more technically and scale efficient. The qualitative study revealed that external factors affecting efficiency commonly included implemention of legislative changes and decreasing bureaucracy, while internal factors included increasing bed capacity and improving qualifications and training of human resources. Most public hospitals in Kuwait were not technically and scale efficient, but improvements were observed. Potential factors that affected the efficiency of hospitals in Kuwait were identified. These findings are useful to decision-makers in Kuwait for developing strategies to improve public hospital efficiency.

scholarly journals Significant inefficiency in running community health systems: The case of health posts in Southwest Ethiopia

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246559
Author(s):  
Kiddus Yitbarek ◽  
Gelila Abraham ◽  
Melkamu Berhane ◽  
Sarah Hurlburt ◽  
Carlyn Mann ◽  
...  
Keyword(s):  
Data Envelopment Analysis ◽  
Health Services ◽  
Technical Efficiency ◽  
Efficiency Score ◽  
Fiscal Year ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Southwestern Ethiopia ◽  
Technical Efficiency Score

Background Although much has been documented about the performance of the health extension program, there is a lack of information on how efficiently the program is running. Furthermore, the rising cost of health services and the absence of competition among publicly owned health facilities demands strong follow up of efficiency. Therefore, this study aimed to assess the technical efficiency of the health posts and determinants in Southwestern Ethiopia. Methods and materials We used data for one Ethiopian fiscal year (from July 2016 to June 2017) to estimate the technical efficiency of health posts. A total of 66 health posts were included in the analysis. We employed a two-stage data envelopment analysis to estimate technical efficiency. At the first stage, technical efficiency scores were calculated using data envelopment analysis program version 2.1. Predictors of technical efficiency were then identified at the second stage using Tobit regression, with STATA version 14. Results The findings revealed that 21.2% were technically efficient with a mean technical efficiency score of 0.6 (± 0.3), indicating that health posts could increase their service volume by 36% with no change made to the inputs they received. On the other hand, health posts had an average scale efficiency score of 0.8 (± 0.2) implying that the facilities have the potential to increase service volume by 16% with the existing resources. The regression model has indicated average waiting time for service has negatively affected technical efficiency. Conclusion More than three-quarters of health posts were found inefficient. The technical efficiency score of more than one-third of the health posts is even less than 50%. Community mobilization to enhance the uptake of health services at the health posts coupled with a possible reallocation of resources in less efficient health posts is a possible approach to improve the efficiency of the program.

Analisis Efisiensi Teknis Multi-Stage Menggunakan Data Envelopment Analysis (DEA) dan Regresi Tobit pada Usahatani Bawang Merah, Studi Kasus di Desa Torongrejo, Kecamatan Junrejo, Kota Batu, Jawa Timur

2021 ◽  
Vol 5 (4) ◽  
pp. 1191-1205
Author(s):  
Ryan Winarso ◽  
◽  
Syafrial Syafrial ◽  
Wiwit Widyawati
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Production Efficiency ◽  
Formal Education ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Factors Affecting ◽  
Profitability Analysis ◽  
Production Value

Shallot has the highest production value in Indonesia. High production value indicates that shallot is an important commodity, therefore, its potential must be improved. Technical efficiency analysis can be used to measure production efficiency and possible input reduction to maximize the production potential of shallot. The chosen location for this research is Torongrejo Village Batu City, East Java. Shallot productivity value of Batu City is comparable to other central shallot production areas in East Java. The purpose of this research is to understand the farming system and production efficiency of shallot alongside with socio-economics factors affecting its efficiency level. Research method used in this research consists of: profitability analysis of shallot farming, analysis using Data Envelopment Analysis (DEA) to analyze the technical efficiency of shallot production, and Tobit regression to analyze socio-economics factors affecting technical efficiency level. The results from the analyses shows that shallot farming in Torongrejo Village has the R/C ratio of 2,09, with the DEA-CRS technical qfficiency value of 87,7 percent, DEA-VRS technical efficiency value of 99 percent and scale efficiency value of 88,6 percent. The result from Tobit regression using DEA-VRS as dependent variable shows that farming experience and formal education has positive and significant effect on technical efficiency (TE) level, and land ownership status has negative and significant effect on TE level. Shallot production efficiency can be increased by using reduced inputs therefore able to increase farming profit while keep improving farmers’ education and agriculture extension programs for the next generation of farmers.

Measurement of Technical and Scale Efficiency of Dairy Farms in Pune District of Maharashtra: Data Envelopment Analysis Approach

2021 ◽  
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Management Practices ◽  
Dairy Farms ◽  
Herd Size ◽  
Efficiency Score ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Resource Saving ◽  
Technical Efficiency Score

The present study intended to determine the technical and scale efficiency of sample dairy farms for evaluating their performance. Data Envelopment Analysis (DEA) technique was used to estimate the technical and scale efficiency of 80 each of member and nonmember dairy farms in the Pune district of Maharashtra state during 2019. Technical efficiency score further partitioned into pure technical efficiency and overall technical efficiency. The technical efficiency score was more for member dairy farms as compared to the non-members under the assumption of constant return to scale (CRS) and variable return to scale (VRS). It highlighted that the non-members of dairy cooperatives had more potential to reduce the input use without affecting the output level compared to the member group. It was also observed that the technical efficiency under the CRS assumption was more than VRS for both member and non-member groups. It revealed that the farms were scaled inefficient (SE<1) and not operating at optimal scale. The study further revealed a positive relationship between technical efficiency and herd size. It also revealed that the resource-saving potential due to the scale effect. So, it supported the policy of providing technical advice on the use of feed and fodder resources, better management practices, and increasing the herd size to increase the technical and scale efficiency.

Labour-use Efficiency of Assam Gramin Vikash Bank: Branch- and District-level Analysis

2021 ◽  
pp. 232102222110243
Author(s):  
Mohuya Deb Purkayastha ◽  
Joyeeta Deb ◽  
Ram Pratap Sinha
Keyword(s):  
Efficiency Score ◽  
Significant Variable ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Second Stage ◽  
Time Period ◽  
Use Efficiency ◽  
The Mean ◽  
The Impact ◽  
Observation Period

The present study estimated labour-use efficiency of 48 branches of Assam Gramin Vikash Bank at its branch level, covering three districts of Barak Valley, which falls under Silchar region of the bank for the time period from 2010–2011 to 2017–2018. The study applied data envelopment analysis for estimating labour-use efficiency. In the second stage, the study applied censored Tobit regression for determining the impact of several contextual variables on efficiency. The study reveals that the mean labour-use efficiency score of the selected branches is 76% when averaged for the in-sample branches over the observation period. Results of the Tobit regression identified cluster 2 and total business of the branches as the significant factors for determining efficiency and the number of employees as a significant variable influencing inefficiency. JEL Classifications: G2, G20, G21, J3

scholarly journals Performance Assessment Based on the Relative Efficiency of Indian Opencast Coal Mines Using Data Envelopment Analysis and Malmquist Productivity Index

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4902
Author(s):  
Biswaranjita Mahapatra ◽  
Chandan Bhar ◽  
Sandeep Mondal
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Primary Source ◽  
Efficiency Score ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Significant Difference ◽  
Using Data

Coal is the primary source of energy in India. Despite being the second-largest coal-producingcountry, there exists a significant difference in demand and production in India. In this study, the relativeefficiency of twenty-eight selected opencast mines from a large public sector undertaking coal companyin India for 2018–2019 was assessed and ranked by using data envelopment analysis (DEA). This studyused input-oriented DEA with efficiency decomposition to pure technical efficiency, technical efficiency,and scale efficiency. The result showed that 25% and 36% of mines were efficient in technical efficiencyand pure technical efficiency, respectively, whereas the eight mines scale efficiency was inefficient witha decreasing return to scale. Further, in this study, theMalmquist Productivity Index (MPI)was employedto measure the efficiency of the selected mines for three consecutive years (2016–2017 to 2018–2019).The result shows that in only three mines the efficiency is continuously improving from 2016–2017 to2018–2019, whereas in more than 20% of mines the efficiency score is decreasing. Comparing theMPIefficiency and productivity assessment throughout the years, changes in innovation and technology areincreasing from 2017–2018 to 2018–2019. Finally, the study concluded with a comprehensive evaluationof each variable with mines performance. The author formulated the strategies, which in turn help coalprofessionals to improve the efficiency of the mine.

Operating Efficiency Analysis of Energy Industries in Taiwan

2013 ◽  
Vol 869-870 ◽  
pp. 612-620 ◽  
Author(s):  
Nattanin Ueasin ◽  
Anupong Wongchai
Keyword(s):  
Regression Model ◽  
Stock Exchange ◽  
Efficiency Score ◽  
Operating Efficiency ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Factors Affecting ◽  
Taiwan Stock Exchange ◽  
Energy Companies ◽  
Tobit Regression Model

The energy business has played an important role in an economic growth of Taiwan because the market share is in the high value that can make a significant contribution towards regional and local employment. However, Taiwan is lack of energy resources, making the country highly relies on an import for more than 98 percent of its all energy. At present, a top priority of the countrys policy is to develop clean, sustainable, independent, and efficient energy in order to eliminate the vulnerability from external disruption. Therefore, this research aims to assess the operating efficiency and to analyze factors affecting the efficiency scores of the registered energy companies in the Taiwan Stock Exchange (TWSE) recorded during 2003-2012. The super-efficiency data envelopment analysis (SE-DEA) was initially applied to reveal the additional efficiency scores, followed by the Tobit regression model used to analyze what factors determine the efficiency scores. The empirical results showed that seven DMUs performed efficiently, ranking from 7.29 to 1.02. The company with the best operating performance was Taiwan Cogeneration Corporation (TCC), while the Great Taipei Gas Corporation (GTG) revealed the worst efficiency score. Furthermore, the Tobit regression model explained that the higher number of the local employees, the greater the efficiency scores were. Besides, the lower number of the shareholders, the greater the efficiency scores were. As a result, the Taiwans government is supposed to encourage all energy companies to have a higher number of local employees and shareholders to increase their efficiency scores.

scholarly journals BANKING SECTOR EFFICIENCY: A DEA AND TIME SERIES APPROACH

Ekonomika ◽  
2010 ◽  
Vol 89 (2) ◽  
pp. 111-119 ◽  
Author(s):  
Fadzlan Suflan
Keyword(s):  
Technical Efficiency ◽  
Banking Sector ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Bank Efficiency ◽  
New Approach ◽  
Time Series Approach ◽  
The Mean ◽  
Dea Method

The paper provides a new approach to modeling bank efficiency. Unlike previous bank efficiency studies, the present paper employs the data envelopment analysis (DEA) method on quarterly data to construct the efficiency frontiers. The Malaysian banking sector is used for a case study. The results show that the Malaysian banking sector has exhibited the mean technical efficiency of 97.3%, suggesting the minimal input waste of 2.7%. The empirical findings suggest that the pure technical efficiency outweighs the scale efficiency in determining the Malaysian banking sector’s technical efficiency. The results imply that, although the Malaysian banking sector has been efficient in managerial terms, it has been operating at a non-optimal scale of operations.p>

scholarly journals Technical Efficiency of White Leg Shrimp Production Using Data Envelopment Analysis (DEA), Case Study: Jiangsu Province, China

2018 ◽  
pp. 1-9
Author(s):  
Mamoud Mansaray ◽  
Agbekpornu Hayford ◽  
Zhang Zongli ◽  
Zhu Weifan ◽  
Yuan Xinhua
Keyword(s):  
Technical Efficiency ◽  
Efficiency Score ◽  
Jiangsu Province ◽  
Shrimp Farming ◽  
Penaeus Vannamei ◽  
Data Envelopment ◽  
Statistical Regression ◽  
Shrimp Production ◽  
Level Of Significance ◽  
Technical Efficiency Score

Production of white leg shrimp (Penaeus vannamei) is a very important economic activity in the overall farming system in China. In spite of the present successes witnessed by white leg shrimp farming, there are many challenges (disease, overfeeding, effluent discharge, lack of technical knowledge, low educational level, inexperienced managers, the high cost of production among others) continuing to set back the growth of this sector in China. The study was conducted in Jiangsu province because is one of the leading producing provinces of White-leg shrimp (Penaeus vannamei) in China. The research examines the technical efficiency level of white leg shrimp production in Jiangsu Province, China. Three seasonal crops data in 2016 crop year were collected from 52 white leg shrimp farmers in the study area. All data were coded in Excel 2007 spreadsheet package and analysed with SPSS version 20 and DEAP version 2.1 software at 95% confidence level. Descriptive statistical, regression and Data Envelopment Analyses (DEA) were used to analyse the data. Results revealed an average technical efficiency score of 83.1%, under a constant return to scale. Majority of the farmers (62%) were technically inefficient in utilising input resources with technical efficiency score less than 1. Twenty farmers were technically efficient with technical efficiency (TE) score equal to 1. Feed, fingerlings and chemical showed significant negative influence on technical efficiency at 5% level of significance while labor, fixed cost and age exhibited strong negative impact at 1% level of significance.

scholarly journals Technical Efficiency and the Determinants of Price to Book Value: An Empirical Study of Category-IV Banks in Indonesia Stock Exchange

2017 ◽  
Author(s):  
chandra setiawan ◽  
Felicia Putri Tjiasaka
Keyword(s):  
Technical Efficiency ◽  
Value Relevance ◽  
Stock Exchange ◽  
Efficiency Score ◽  
Least Square ◽  
Financial Statement ◽  
Data Envelopment ◽  
Book Value ◽  
Operating Profit ◽  
Technical Efficiency Score

This research aimed to empirically determine the value relevance of price to book value (PBV) and technical efficiency (TE) within Category-IV banks in Indonesia Stock Exchange in the time horizon of 1Q2007 to 4Q2015. This research uses time series and quarterly-published financial statement from the listed Category-IV banks. In term of variables that determine PBV by using panel least square, the research reveals that pre-provision operating profit (PPOP) and return on total assets (ROTA) have positive and significant effect towards PBV, while non-performing loan (NPL) and dividend yield have negative and significant effect towards PBV. Contrarily, firm size has negative and insignificant effect towards PBV. Additionally, the result of data envelopment analysis (DEA) which is used to measure technical efficiency, indicates that PT. Bank Mandiri Tbk. (BMRI) is the most efficient Category-IV bank. BMRI led with average technical efficiency score of 98.95%, followed by PT. Bank Rakyat Indonesia Tbk. (BBRI) 98.02%, PT. Bank Negara Indonesia Tbk. (BBNI) 96.04% and PT. Bank Central Asia Tbk. 94.94%. The average technical efficiency of Category-IV banks within the period of research is 96.99%.

scholarly journals INTERTEMPORAL EFFICIENCY AND PRODUCTIVITY CHANGING ON TELECOMMUNICATION INDUSTRY (TI) IN ASEAN-5

2021 ◽  
Vol 6 (1) ◽  
pp. 123
Author(s):  
Dyah Wulan Sari ◽  
Lusi Sulistyaningsih ◽  
Haura Azzahra Tarbiyah Islamiya ◽  
Wenny Restikasari
Keyword(s):  
Technical Efficiency ◽  
Malmquist Index ◽  
Primary Source ◽  
Efficiency Score ◽  
Productivity Change ◽  
Telecommunication Industry ◽  
Data Envelopment ◽  
The Mean ◽  
Intertemporal Efficiency ◽  
Efficiency And Productivity

The study aims to measure the technical and intertemporal efficiency and find the primary source of productivity change on top three telecommunication firms in each country of ASEAN-5 (Indonesia, Malaysia, Thailand, Philippines, and Singapore) from 2010 to 2016. Data Envelopment Analysis (DEA) bootstrapping with 2000 iterations, DEA window, and Malmquist index are applied to calculate technical efficiency, intertemporal efficiency, and productivity change. The estimation results elucidate that, on average, the technical efficiency of firms is relatively low. On the opposite, the intertemporal efficiency results indicate that the mean efficiency score of each window is high. However, the LDW and LDP tend to be high, showing that the efficiency scores fluctuate. The Malmquist index calculation yields that technological progress possesses a significant contribution to productivity change.Keywords: Technical Efficiency, Intertemporal Efficiency, Productivity Change, Telecommunication Industry, ASEAN-5  JEL Classifications: L8, F6, O5, O1, O3

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