scholarly journals Technical Efficiency Of Social Foundations In A Multidimensional Context

2010 ◽  
Vol 9 (11) ◽  
Author(s):  
Imelda S. Dorado ◽  
Emilyn Cabanda
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Returns To Scale ◽  
The Philippines ◽  
Data Envelopment ◽  
Non Profit ◽  
Dea Model ◽  
Social Foundations ◽  
Efficiency Assessment ◽  
Constant Returns To Scale

The paper is the first attempt at examining the technical efficiency and benchmarking the performance of 15 social foundations in the Philippines for the period 2000-2005 using the data envelopment analysis (DEA) model. The 65.55% of social foundations are operating at increased returns to scale, 4.45% at decreased returns to scale and 30% at constant returns to scale. Forty percent of firms are efficiently utilizing their expenses and the majority shows resource excesses (capital and labor). All firms show output deterioration for donations and total awards to beneficiaries. With the aid of the DEA tool, measurement of the efficiency of social foundations has been verified and proven as manageable and quantifiable from a multidimensional assessment. Results reveal the importance of technical efficiency assessment for the non-profit sector.

scholarly journals Access to Credit and Farm Efficiency in Cameroon: A Data Envelopment Analysis Approach

2021 ◽  
pp. 48-62
Author(s):  
Orelien Tresor Feumba Tchamba
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Returns To Scale ◽  
Farm Households ◽  
Farm Size ◽  
Data Envelopment ◽  
Agricultural Field ◽  
Access To Credit ◽  
Farm Efficiency ◽  
Constant Returns To Scale

The aims of this paper is to analyze the effect of access to credit on the technical efficiency of farms in Cameroon’s rural area. Using a sample of 545 farm households, we first estimate a Data Envelopment Analysis (DEA) model with constant returns to scale; then a censored TOBIT model enabling us to identify factors of efficiency, especially the effect of access to credit on efficiency. Two main results emerge from our analysis. First, we find that on average, the level of technical efficiency of farms is 56.78%; showing therefore the possibility of substantial efficiency gains. Second, farm size, association membership, and fertilizer expenditure negatively affect technical efficiency, while access to credit, age and education increase it. Based on these results, we believe that it’s interesting for farm householders to organize themselves in associations to benefit from available credits and financial facilities and to share their experiences in the agricultural field in order to improve their efficiency.

Data envelopment analysis of technical efficiency and productivity growth in the US Pacific Northwest sawmill industry

2008 ◽  
Vol 38 (10) ◽  
pp. 2553-2565 ◽  
Author(s):  
Ted L. Helvoigt ◽  
Darius M. Adams
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Pacific Northwest ◽  
Productivity Growth ◽  
Returns To Scale ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Efficiency Change ◽  
Constant Returns To Scale ◽  
Sawmilling Industry

This paper uses data envelopment analysis (DEA) to characterize the changing production frontier (technical efficiency, productivity growth, technical and efficiency change, and returns to scale) of the sawmilling industry in the Pacific Northwest (PNW) US using geographical panel data for the period 1968–2002. Unlike past DEA studies, we develop confidence intervals for all estimates using an improved bootstrapping method. The results indicate that the gap between the least and most efficient regions in PNW has grown and the least efficient regions are falling further behind the most efficient regions. For the Oregon regions, the null hypothesis of constant returns to scale (CRS) could not be rejected for any year. For the Washington regions, returns to scale varied year by year, although only two of the five regions showed strong tendencies away from CRS. For PNW as a whole, mean productivity growth was 0.5% per year between 1968 and 1992. Between 1992 and 2002, the regional mean was 1.3%, although with wide variation across regions. DEA results indicate that the vast majority of productivity growth in the PNW sawmilling industry between 1968 and 2002 was due to technical change. Improvements in scale efficiency played a very small role, and efficiency change was zero or negative.

Efficiency in the Indian iron and steel industry – an application of data envelopment analysis

2014 ◽  
Vol 11 (1) ◽  
pp. 4-19 ◽  
Author(s):  
Roma Mitra Debnath ◽  
V.J. Sebastian
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Steel Industry ◽  
Returns To Scale ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Annual Income ◽  
Content Type ◽  
Steel Manufacturing ◽  
Constant Returns To Scale

Purpose – The purpose of this paper applies to Indian steel manufacturing industries to evaluate the technical and scale efficiency (SE). Design/methodology/approach – Data envelopment analysis (DEA) has been employed to calculate the relative efficiency of the steel manufacturing units. The selection criteria for the inclusion of a steel manufacturing unit in the analysis has been annual income of more than 50 crores and units manufacturing pig iron, steel and sponge iron. Within the DEA framework, the output-oriented model with constant returns to scale and variable returns to scale were studied. Four input variables, namely, gross fixed assets, total energy cost, total number of employees and currents assets were considered. Among the output variables, the four variables considered are income, sales, PBIT and PAT. Findings – The result of the efficiency scores have been categorized into three parts. The pure technical efficiency represents local efficiency and the reason of inefficiency is due to inefficient operations. Technical efficiency indicates that the respective decision-making units are globally efficient in case the efficiency is 100 per cent. The SE explains that the inefficiency is caused by disadvantageous conditions. As the result shows, that public sector undertaking (PSUs) are operating under disadvantageous conditions as compared to private manufacturing units. One of the possible reasons of location disadvantage condition is manufacturing units for PSUs are scattered throughout India. Some of the units are located in such places where, the raw material, supply chain could be difficult. It has been found that 45 per cent of the private manufacturing units are technically as well as scale inefficient units. Practical implications – The result of the study would benefit the steel industry to develop a performance benchmarking as steel companies must be profitable in the long term to ensure sustainable achievements. Originality/value – This is an original study to apply DEA to get insights on productivity efficiency of the steel manufacturing units in India. Though the manufacturing units were selected on the basis of annual income, the analysis of productivity does not reflect any impact of income on the efficiency of the manufacturing firms.

scholarly journals Does Farm Size and Specialization Matter for Productive Efficiency? Results from Kansas

2011 ◽  
Vol 43 (4) ◽  
pp. 515-528 ◽  
Author(s):  
Amin W. Mugera ◽  
Michael R. Langemeier
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Production Technology ◽  
Returns To Scale ◽  
Productive Efficiency ◽  
Farm Size ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Sample Period ◽  
Analysis Techniques

In this article, we used bootstrap data envelopment analysis techniques to examine technical and scale efficiency scores for a balanced panel of 564 farms in Kansas for the period 1993–2007. The production technology is estimated under three different assumptions of returns to scale and the results are compared. Technical and scale efficiency is disaggregated by farm size and specialization. Our results suggest that farms are both scale and technically inefficient. On average, technical efficiency has deteriorated over the sample period. Technical efficiency varies directly by farm size and the differences are significant. Differences across farm specializations are not significant.

EFFICIENCY AND PRODUCTIVITY CHANGE IN FIELD CROP AND MILK FARMS IN LUBLIN PROVINCE IN 2014-2016

2018 ◽  
Vol XX (1) ◽  
pp. 137-142
Author(s):  
Alina Syp ◽  
Dariusz Osuch
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Dairy Farms ◽  
Productivity Change ◽  
Data Envelopment ◽  
Field Crop ◽  
Dea Model ◽  
Malmquist Indices ◽  
Efficiency And Productivity ◽  
Efficiency Indicators

The aim of the study was assessment of efficiency and productivity of farms in the Lublin province in the years 2014-2016. The analysis was based on the Data Envelopment Analysis (DEA) model oriented on inputs and Malmquist indices with its components. The calculations were made for medium-sized field and dairy farms that continuously collected data for the FADN system during the period under consideration. In our research all efficiency indicators for dairy farms were larger than for field crop farms. In the years 2014-2016, the average technical efficiency of dairy farms was 0.752, which means that in those farms it is possible to reduce inputs on average by 25% and the value of production will remain at the same level. In the case of field crop farms, inputs should be limited by 33%. The applied decomposition of calculated Malmquist indices allowed to define what factors influenced changes in productivity.

scholarly journals Applying data envelopment analysis to operating performance in textile industry

2013 ◽  
Vol 13 (4) ◽  
pp. 99-103 ◽  
Author(s):  
Chia-Hui Ho
Keyword(s):  
Data Envelopment Analysis ◽  
Textile Industry ◽  
Market Competition ◽  
Operating Performance ◽  
Returns To Scale ◽  
Operating Efficiency ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Optimal Operating ◽  
Constant Returns To Scale

Abstract Operating performance could affect the survival and future development of a business that both businesses and business managers would devote to the enhancement of operating performance. Having developed for more than four decades, the consistent upstream, mid-stream and downstream system have been constructed in domestic textile industry. The output value of textiles in Taiwan has exceeded 480 billion NT dollars, which is not a sunset industry, as generally described. The impacts of high labour cost, environmental protection measures and changes of capital market as well as the competition of emerging countries, particularly Mainland China, have made textile industry in Taiwan face great market competition and pressure. Since textiles are regarded as one of the major products in Taiwan, the operating performance could affect the survival of the overall industry. In this case, operating performance survey of textile manufacturers in Taiwan during 2010–2012 is combined with Data Envelopment Analysis and Slack Variable Analysis to measure the total efficiency, pure technical efficiency and scale efficiency of top 12 textile manufacturers in Taiwan, tending to provide the reference of operating efficiency improvement for the manufacturers. The empirical results show that the overall efficiency in the 3 years appears 0.89 averagely. The relative efficiency (1) between two manufacturers, Far Eastern New Century and Ruentex Industries, achieves the optimal operating efficiency, whereas the remaining 10 are comparatively worse. Regarding the analysis of returns to scale, two textile manufacturers present constant returns to scale, with the optimal operating efficiency, whereas the remaining 10 show increasing returns to scale, revealing that expanding the scale could enhance the marginal return and further promote the efficiency.

scholarly journals Influence of Constant Returns to Scale and Variable Returns to Scale Data Envelopment Analysis Models in ICT Infrastructure Efficiency Utilization

2021 ◽  
pp. 158-181
Author(s):  
Yinka Oyerinde ◽  
Felix Bankole
Keyword(s):  
Data Envelopment Analysis ◽  
Human Development ◽  
Relative Efficiency ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Information And Communication ◽  
Ict Infrastructure ◽  
Policy Direction ◽  
Constant Returns To Scale ◽  
Variable Returns To Scale

A lot of research has been done using Data Envelopment Analysis (DEA) to measure efficiency in Education. DEA has also been used in the field of Information and Communication Technology for Development (ICT4D) to investigate and measure the efficiency of Information and Communication Technology (ICT) investments on Human Development. Education is one of the major components of the Human Development Index (HDI) which affects the core of Human Development. This research investigates the relative efficiency of ICT Infrastructure Utilization on the educational component of the HDI in order to determine the viability of Learning Analytics using DEA for policy direction and decision making. A conceptual model taking the form of a Linear Equation was used and the Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS) models of the Data Envelopment Analysis were employed to measure the relative efficiency of the components of ICT Infrastructure (Inputs) and the components of Education (Outputs). Results show a generally high relative efficiency of ICT Infrastructure utilization on Educational Attainment and Adult Literacy rates, a strong correlation between this Infrastructure and Literacy rates as well, provide an empirical support for the argument of increasing ICT infrastructure to provide an increase in Human Development, especially within the educational context. The research concludes that DEA as a methodology can be used for macroeconomic decision making and policy direction within developmental research.

scholarly journals Productivity Benchmarking Using Analytic Network Process (ANP) and Data Envelopment Analysis (DEA)

2018 ◽  
Vol 2 (3) ◽  
pp. 27 ◽  
Author(s):  
Shanta Mazumder ◽  
Golam Kabir ◽  
M. Hasin ◽  
Syed Ali
Keyword(s):  
Data Envelopment Analysis ◽  
Returns To Scale ◽  
Analytic Network Process ◽  
Data Envelopment ◽  
Contributing Factors ◽  
Productivity Measurement ◽  
Apparel Manufacturing ◽  
Network Process ◽  
Dea Approach ◽  
Constant Returns To Scale

Measuring productivity is the systematic process for both inter- and intra-organizational comparisons. The productivity measurement can be used to control and facilitate decision-making in manufacturing as well as service organizations. This study’s objective was to develop a decision support framework by integrating an analytic network process (ANP) and data envelopment analysis (DEA) approach to tackling productivity measurement and benchmarking problems in a manufacturing environment. The ANP was used to capture the interdependency between the criteria taking into consideration the ambiguity and vagueness. The nonparametric DEA approach was utilized to determine the input-oriented constant returns to scale (CRS) efficiency of different value-adding production units and to benchmark them. The proposed framework was implemented to benchmark the productivity of an apparel manufacturing company. By applying the model, industrial managers can gain benefits by identifying the possible contributing factors that play an important role in increasing the productivity of manufacturing organizations.

scholarly journals Pengukuran Efisiensi Kinerja Sekolah Dasar lewat Model Data Envelopment Analysis

2017 ◽  
Vol 36 (2) ◽  
Author(s):  
Siti Fatimah ◽  
Umi Mahmudah
Keyword(s):  
Elementary Schools ◽  
Data Envelopment Analysis ◽  
Parametric Method ◽  
Returns To Scale ◽  
Scale Model ◽  
Data Envelopment ◽  
Public Elementary Schools ◽  
Crs Model ◽  
Using Data ◽  
Constant Returns To Scale

This study aims to measure the performance efficiency of elementary schools in Special Capital Region of Jakarta, especially Central Jakarta district in the period 2014/2015 by using data envelopment analysis (DEA) approach. DEA is a non-parametric method to measure efficiency of decision making units (DMUs). DEA compares several homogeneous DMUs based on a number of inputs to produce the expected outputs. This study uses descriptive method using DMU as many as 103 public elementary schools that are A-accredited with three inputs and four outputs. Data is analyzed using DEAP version 2.1 application by comparing CRS (Constant Returns to Scale) model and VRS (Variable Returns to Scale) model. Results show that: 1) in CRS model, there are 8 public elementary schools (7.77 percent) have efficient performances while in VRS model there are 14 public elementary schools (13.59 percent) have efficient performances; 2) VRS model is better than CRS model in measuring the efficiency performance of public elementary schools in Central Jakarta.

Sign in / Sign up

Export Citation Format

Share Document