scholarly journals Determinants of Efficiency in Health Sector: DEA Approach and Second Stage Analysis

2016 ◽  
Vol 2 (2) ◽  
pp. 83-92
Author(s):  
Rabia Adil ◽  
Muhammad Abbas ◽  
Asif Yaseen

There are several factors that influence the performance of health structure. Achieving efficiency in healthcare sector is the goal of every economy in the world. To accomplish this end, it is dominant to find out the efficiency. The present study is designed to measure the efficiency of selected Asian countries. A Non-parametric data envelopment analysis input-oriented approach under constant returns to scale is applied to measure the technical efficiency for the time span of 2012. By applying CRS model of DEA, 11 countries out of 26 are found to be efficient. The study provides suggestions to enhance the efficiency as well productivity of these Asian countries.

2012 ◽  
Vol 150 (6) ◽  
pp. 738-754 ◽  
Author(s):  
E. KELLY ◽  
L. SHALLOO ◽  
U. GEARY ◽  
A. KINSELLA ◽  
F. THORNE ◽  
...  

SUMMARYThe phasing out of the European Union (EU) milk quota will create opportunities for producers to expand without the constraint of quota which has limited expansion since 1984. Therefore, it will be necessary for Irish dairy producers to become more competitive by increasing performance using the least amount of inputs per unit of output and maximizing the level of technical and economic efficiency. The objectives of the current study were to measure technical, allocative and economic efficiency, and to investigate the associations of key management, qualitative and demographic characteristics on efficiency. Efficiency scores were calculated using the non-parametric methodology data envelopment analysis (DEA). The DEA results showed that on average the sample of Irish dairy producers were not fully efficient in 2008 with technical, allocative and economic efficiency results under variable returns to scale (VRS) of 0·771, 0·740 and 0·571, respectively. In a second stage analysis, Tobit regressions were used to determine the associations of key variables with the technical, allocative and economic efficiency scores. The efficiency scores were included as dependent variables and the key independent variables were a variety of management and demographic variables. Mean calving date, number of grazing days, breeding season length, milk quality, discussion group membership and soil quality were all associated with technical and economic efficiency. Milk recording, use of artificial insemination (AI) and level of dairy specialization were associated with allocative and economic efficiency only. Age and age squared were the only significant demographic associations with the efficiency scores.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Simona Alfiero ◽  
Valerio Brescia ◽  
Fabrizio Bert

Abstract Background Knowledge resources are in most productive sectors distinctive in terms of competitiveness. Still, in the health sector, they can have an impact on the health of the population, help make the organisations more efficient and can help improve decision-making processes. The purpose of this paper is to investigate the Intellectual Capital impact on healthcare organization’ performance in the Italian healthcare system. Methods The theoretical framework linked to intellectual Capital in the health sector and the performance evaluation related to efficiency supports the analysis carried out in two stages to determine the right placement of resources and the exogenous variables that influence performance level. The evaluation of the impact of the ICs on performance is determined through the Data envelopment analysis. The incidence of the exogenous variables has been established through linear regression. Results Empirical results in Italy show some IC components influence organization ‘performance (Essential Levels of Assistance) and could be used for defining the policy of allocation of resources in healthcare sector. The efficiency of 16 regions considered in 2016 based on Slack-Based-Model constant returns-to-scale (SBM-CRS) and Slack-Based-Model variable returns-to-scale (SBM-VRS) identifies a different ability to balance IC and performance. Current healthcare expenditure and the number of residents is correlated with the identified efficiency and performance levels. Conclusions This paper embeds an innovative link between healthcare performance, in term of efficiency and IC which aligns resource management with future strategy. The study provides a new decision-making approach.


2013 ◽  
Vol 13 (4) ◽  
pp. 99-103 ◽  
Author(s):  
Chia-Hui Ho

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.


Author(s):  
Yinka Oyerinde ◽  
Felix Bankole

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.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Beata Gavurova ◽  
Kristina Kocisova ◽  
Jakub Sopko

Abstract Background In recent years, measuring and evaluating the efficiency of health systems has been explored in the context of seeking resources to ensure the sustainability of ‘countries’ health and social systems and addressing various crises in the health sector. The study aims to quantify and compare the efficiency of OECD health systems in 2000, 2008, and 2016. The contribution to research in the field of efficiency in the healthcare system can be seen in the application of Dynamic Network Data Envelopment Analysis (DNDEA), which help us to analyse not only the overall efficiency of the healthcare system but analyse the overall efficiency as the result of the efficiencies of individual interconnected areas (public and medical care area). By applying the DNDEA model, we can realise the analysis not only within one year, but we can find out if the measures and improvements taken in the healthcare sector have a positive impact on its efficiency in a later period (eight-year interval). Methods The analysis focuses on assessing the efficiency of the health systems of OECD countries over three periods: 2000, 2008, and 2016. Data for this study were derived from the existing OECD database, which provides aggregated data on OECD countries on a comparable basis. In this way, it was possible to compare different countries whose national health statistics may have their characteristics. The input-oriented Dynamic Network Data Envelopment Analysis model was used for data processing. The efficiency of OECD health systems has been analysed and evaluated comprehensively and also separately in two divisions: public health sub-division and medical care sub-division. The analysis combines the application of conventional and unconventional methods of measuring efficiency in the health sector. Results The results for the public health sub-division, medical care sub-division and overall health system for OECD countries under the assumption of constant returns to scale indicate that the average overall efficiency was 0.8801 in 2000, 0.8807 in 2008 and 0.8472 in 2016. The results of the input-oriented model with the assumption of constant returns to scale point to the overall average efficiency of health systems at the level of 0.8693 during the period. According to the Malmquist Index results, the OECD countries improved the efficiency over the years, with performance improvements of 19% in the public health division and 8% in the medical care division. Conclusions The results of the study are beneficial for health policymakers to assess and compare health systems in countries and to develop strategic national and regional health plans. Similarly, the result will support the development of international benchmarks in this area. The issue of health efficiency is an intriguing one that could be usefully explored in further research. A greater focus on combining non-parametric and parametric models could produce interesting findings for further research. The consistency in the publication and updating of the data on health statistics would help us establish a greater degree of accuracy.


2018 ◽  
Vol 2 (3) ◽  
pp. 27 ◽  
Author(s):  
Shanta Mazumder ◽  
Golam Kabir ◽  
M. Hasin ◽  
Syed Ali

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.


2017 ◽  
Vol 36 (2) ◽  
Author(s):  
Siti Fatimah ◽  
Umi Mahmudah

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.


2016 ◽  
Vol 8 (6) ◽  
pp. 114 ◽  
Author(s):  
Oumar Sow ◽  
Amar Oukil ◽  
Babacar M. Ndiaye ◽  
Aboubacar Marcos

Transportation is a sector which plays an important role in the process of development of countries around the world. A crucial step in transportation planning process is the measure of the efficiency of transportation systems in order to guarantee the desired service. This paper investigates the relative efficiencies of lines of the main public transportation company Dakar Dem Dikk (DDD)\footnote{\textit{Dem Dikk} meaning \guillemotleft Go-Return\guillemotright} in Dakar (Senegal). The objective is to apply Data Envelopment Analysis (DEA) and bootstrapping approaches in order to identify opportunities for improvement. In this study, we examine technical efficiency for the 24 lines of DDD using Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS) DEA output oriented models. We apply bootstrap approach for bias correction and for confidence intervals creation of our estimates. Finally, we examine the returns to scale characterization of lines. The results establish that there exist possibilities for improvement for the lines and also shown that there are potential for restructure for some lines.


2020 ◽  
Vol 14 (3) ◽  
pp. 332-352
Author(s):  
Abdulai Adams ◽  
Bedru Balana ◽  
Nicole Lefore

This study measures and explains technical efficiency (TE), economic efficiency and allocative efficiency of 110 small-scale vegetable farmers practicing various irrigation technologies for increased productivity. We employed the two-stage approach to estimate efficiency scores under constant returns to scale (CRS) and variable returns to scale (VRS) specifications. First, using a linear programming method, efficiency scores of the irrigated vegetable farmers were measured using the data envelopment analysis approach. The results show that about 27.3 per cent of the farmers currently operate on the production possibility frontier and are technically efficient, while 3.6 per cent were found to be both economically and allocatively efficient. The mean TE score for CRS was 50.6 per cent, compared with 78.1 per cent under the VRS. A Tobit regression at the second-stage analysis revealed that gender, experience, health and credit utilization have significant effects on TE. These results are valuable for stakeholders interested in promoting efficiency in smallholder irrigated production. JEL Classification: C14, C61, D24, D61, Q12


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