scholarly journals Measuring the Efficiency of Turkish SMEs: A Data Envelopment Analysis Approach

2016 ◽  
Vol 8 (6) ◽  
pp. 190 ◽  
Author(s):  
Arzum Buyukkeklik ◽  
Harun Dumlu ◽  
Samet Evci

<p>Small and medium-sized enterprises (SMEs) that are undertaking significant roles in the development of the economy of Turkey and in the increase of the production and employment encounter with many problems. Financial problems take an important place among them. The resources that could be used by SMEs in meeting the financing needs to be limited require the efficient use of these resources. In this study, the resource activities of SMEs have been studied with Data Envelopment Analysis (DEA). In analysis short-term liabilities, long-term liabilities and equity values of the enterprises that are quoted continuously on SME Industrial Index within 2011-2014 have been used as input variables; and the sales revenue and net profit values have been used as output variables. The total efficiency values of each decision making unit have been attained with the use of CCR model according to the years, technical efficiency values of them have been attained with the use of BCC model and the scale efficiency values of them have been attained by comparing these values to each other. As a result, it has been determined that those providing resource efficiency are only a few among the enterprises that are proceeded in the BIST SME Industrial Index; and these enterprises could reach their existent sales revenue and net profit numbers with less resources. In this respect it has been revealed that the SMEs that have problems in providing credit and not having strong equity structure are not able to make use of their own resources efficiently.</p>

2017 ◽  
Vol 4 (9) ◽  
pp. 757
Author(s):  
Yulia Wahyu Ningsih ◽  
Noven Suprayogi

This study aims to analyze the efficiency of sharia general insurance companies in Indonesia. The input variables used are total assets, expenses, and payment of claims, while the output variable is the income and tabarru’ funds. The method were used to measure the level of efficiency is the Data Envelopment Analysis (DEA) with the assumption of Variable Return to Scale (VRS) with input and output orientation. The samples are 12 sharia general insurance companies during 2013-2015. The results of the study indicate that the average result of DEA analysis for the entire DMU (Decision Making Unit) has not been efficient. The average value of economic efficiency (CRS) by 0.978, technically efficiency (VRS) for 0.925, and scale efficiency for 0.945. Source of inefficiency sharia insurance company is the scale of operations and management of input to output is not optimal.


2021 ◽  
Vol 4 (4) ◽  
pp. 503-521
Author(s):  
Foza Hadyu Hasanatina ◽  
Risanda Alirastra Budiantoro ◽  
Vicky Oktavia

This study aims to anlyze and comparing the efficiency of Islamic Life Insurance and Conventional Life Insurance in Indonesia. This study uses a quantitative non-parametric approach with Data Envelopment Analysis (DEA) with the assumption of Constant Return to Scale (CRS) and Variable Return to Scale (VRS) with input and output orientation. The samples are 3 Islamic Life Insurance (full fledge) and 3 Conventional Life Insurance that comply with the specified sample criteria during 2012-2019. The input variables used ared cost of commissive, operational cost, total equity, while the output variables is the premi income, and investment revenue. The results of the study indicate that the average result of DEA analysis for the entire DMU (Decision Making Unit) has not been efficient. In Conventional Life Insurance, the value of economic efficiency by 64,82 percent, technically efficiency for72,22 percent, and scale efficiency 81,4 percent, while in Islamic Life Insurance, the value of economic efficiency by 17,26 percent, technically efficiency for 53,71 persen, and scale efficiency 47,41 percent. Source of inefficiency Conventional and Islamic Life Insurance company is the sacle of operations and management of input to output is not optimal.


Facilities ◽  
2015 ◽  
Vol 33 (11/12) ◽  
pp. 716-735 ◽  
Author(s):  
Kung-Jen Tu

Purpose – The purpose of this study is to present the theoretical framework of the “data envelopment analysis (DEA) Energy Management System (DEMS)” proposed to assist individual departments occupying the same buildings on university campus in assessing the energy efficiencies of their facilities, as well as to demonstrate the implementation results of the DEMS applied in the case of the Department of Architecture of NTUST in Taiwan. Design/methodology/approach – The proposed DEMS considers each “space” within a department in a given “time” (such as a month) as a decision-making unit (DMU). Then, regression analysis is performed on data of “existing environment”, “occupancy” factors and “actual energy consumption EUI (energy usage intensity)” related variables. The regression equation derived is then used to calculate the “predicted EUI” for all DMUs. The “actual EUI” is further considered as the input data and the “predicted EUI” as the output data of the DEMS, on which data envelopment analysis is conducted to produce three types of energy-efficiency scores (overall efficiency, scale efficiency, pure technical efficiency) to indicate the energy efficiencies of all DMUs. Findings – The DEMS was developed and further implemented in the Department of Architecture of NTUST in Taiwan to illustrate how it can be used to assist individual departments within universities in assessing the energy management effectiveness of their spaces. Research limitations/implications – The accuracy of the energy-efficiency scores depends greatly on the accuracy of the predicted EUIs of spaces, and, therefore, it is critical to identify a better regression model with higher predictability (R2). The relatively low actual EUIs of certain student spaces during winter and summer breaks may greatly affect the resulting energy-efficiency scores. Practical implications – The DEMS allows facility managers to assess and compare the energy-efficiency scores “among different spaces”, to further review the energy efficiency of a space “over time” and to recognize the benchmark cases and pursue actions for energy improvement. Originality/value – This study explores the research concepts of “space type” and “internal benchmark” with an analytical method “data envelopment analysis” to assess the energy efficiency of an individual department which may only occupy certain floors of a building.


2020 ◽  
Vol 3 (01) ◽  
pp. 15
Author(s):  
Aziza Hanifa Khairunnisa ◽  
Nisful Laila

<p><em>This research aimed to find out the efficiency level of financing of Islamic Rural Bak in East Java. Input variables used were the rights of third party on profit sharing and PPAP cost, while output variable used was main operational income. Method used to measure efficiency level was Data Envelopment Analysis (DEA) with the assumption of Variable Return to Scale and the input and output orientations. The measurement of efficiency value with VRS assumption resulted three efficiency values, which are Technical Efficiency (VRS), Economic Efficiency (CRS), and Scale Efficiency. Then, these three values were analyzed further to get to know the source of inefficiency of financing in inefficient Islamic Rural Bank.</em><em> </em></p><strong><em>Keywords</em></strong><em>: BPRS, Data Envelopment Analysis (DEA)Efficiency, Financing</em>


2011 ◽  
Vol 50 (4II) ◽  
pp. 685-698
Author(s):  
Samina Khalil

This paper aims at measuring the relative efficiency of the most polluting industry in terms of water pollution in Pakistan. The textile processing is country‘s leading sub sector in textile manufacturing with regard to value added production, export, employment, and foreign exchange earnings. The data envelopment analysis technique is employed to estimate the relative efficiency of decision making units that uses several inputs to produce desirable and undesirable outputs. The efficiency scores of all manufacturing units exhibit the environmental consciousness of few producers is which may be due to state regulations to control pollution but overall the situation is far from satisfactory. Effective measures and instruments are still needed to check the rising pollution levels in water resources discharged by textile processing industry of the country. JEL classification: L67, Q53 Keywords: Data Envelopment Analysis (DEA), Decision Making Unit (DMU), Relative Efficiency, Undesirable Output


Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 469
Author(s):  
Chia-Nan Wang ◽  
Thi-Ly Nguyen ◽  
Thanh-Tuan Dang ◽  
Thi-Hong Bui

In Vietnam, fishing is a crucial source of nutrition and employment, which not only affects the development of the domestic economy but is also closely related to exports, heavily influencing the economy and foreign exchange. However, the Vietnamese fishery sector has been facing many challenges in innovating production technology, improving product quality, and expanding markets. Hence, the fishery enterprises need to find solutions to increase labor productivity and enhance competitiveness while minimizing difficulties. This study implemented a performance evaluation from 2015 to 2018 of 17 fishery businesses, in decision making units (DMUs), in Vietnam by applying data envelopment analysis, namely the Malmquist model. The objective of the paper is to provide a general overview of the fishery sector in Vietnam through technical efficiency, technological progress, and the total factor productivity in the four-year period. The variables used in the model include total assets, equity, total liabilities, cost of sales, revenue, and profit. The results of the paper show that Investment Commerce Fisheries Corporation (DMU10) and Hoang Long Group (DMU8) exhibited the best performances. This paper offers a valuable reference to improve the business efficiency of Vietnamese fishery enterprises and could be a useful reference for related industries.


2015 ◽  
Vol 65 (s2) ◽  
pp. 101-113 ◽  
Author(s):  
Ling Jiang ◽  
Yunyu Jiang ◽  
Zhijun Wu ◽  
Dongsheng Liao ◽  
Runfa Xu

In the era of knowledge economy, a country’s economic competitiveness depends largely on the development level of high-tech industry. This paper evaluates the efficiency of China’s high-tech industry in 31 provinces in 2012 with data envelopment analysis. The empirical results are summarized as following. Firstly, when the effects of exogenous environmental variables are not controlled, the comprehensive technical efficiency of 31 provinces will be overestimated, the pure technical efficiency will be underestimated, and the scale efficiency value will be overestimated. Secondly, after eliminating the environmental impact, the comprehensive technical efficiency of 31 provinces with the average of 0.395 is rather low, due to the low scale efficiency.


2011 ◽  
Vol 43 (4) ◽  
pp. 515-528 ◽  
Author(s):  
Amin W. Mugera ◽  
Michael R. Langemeier

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.


2019 ◽  
Vol 14 (2) ◽  
pp. 362-378 ◽  
Author(s):  
Vikas Vikas ◽  
Rohit Bansal

Purpose Data envelopment analysis (DEA), a non-parametric technique is used to assess the efficiency of decision-making units which are producing identical set of outputs using identical set of inputs. The purpose of this paper is to find the technical efficiency (TE), pure technical efficiency and scale efficiency (SE) levels of Indian oil and gas sector companies and to provide benchmark targets to the inefficient companies in order to achieve efficiency level. Design/methodology/approach In the present study, a group of 22 oil and gas companies which are listed on the National Stock Exchange for which the data were available for the period 2013–2017 has been considered. DEA has been performed to compare the efficiency levels of all companies. To measure efficiency, three input variables, namely, combined materials consumed and manufacturing expenses, employee benefit expenses and capital investment and two output variables – operating revenues and profit after tax (PAT) have been considered. On the basis of performance for the financial year ending 2017, benchmark targets based on DEA–CCR (Charnes, Cooper and Rhodes) model have been provided to the inefficient companies that should be focused upon by them to attain the efficiency level. The performance of the companies for the past five years has been examined to check the fluctuations in the various efficiency scores of the companies considered in the study over the years. Findings From the results obtained, it is observed that 59 percent, i.e. 13 out of 22 companies are technically efficient. By considering DEA BCC (Banker, Charnes and Cooper) model, 16 companies are observed to be pure technically efficient. In terms of SE, there are 14 such companies. The inefficient units need to improve in terms of input and output variables and for this motive, specified targets are assigned to them. Some of these companies need to upgrade significantly and the managers must take the concern earnestly. The study has also thrown light on the performance of the companies over last five years which shows Oil India Ltd, Gujarat State Petronet Ltd, Petronet LNG Ltd, IGL Ltd, Mahanagar Gas, Chennai Petroleum Corporation Ltd and BPCL Ltd as consistently efficient companies. Research limitations/implications The present study has made an attempt to evaluate the efficiency of Indian oil and gas sector. The results of the study have significant inferences for the policy makers and managers of the companies operating in the sector. The results of the study provide benchmark target level to the companies of Oil and Gas sector which can help the managers of the relatively less efficient companies to focus on the ways to improve efficiency. The improvement in efficiency of a company would not only benefit the shareholders, but also the investors and other stakeholders of the company. Originality/value In the context of Indian economy, very limited number of studies have focused to measure the efficiency of oil and gas sector in the context of Indian economy. The present study aims to provide the latest insight to the efficiency of the companies especially operating in the Indian oil and gas sector. Further, as per our knowledge, this study is distinctive in terms of analyzing the efficiency of Indian oil and gas sector for a period of five years. The longitudinal study of the sector efficiency provides a bird eye view of the average efficiency level and changes in the efficiency levels of the companies over the years.


2022 ◽  
Vol 9 ◽  
Author(s):  
Yangang Xue ◽  
Muhammad Mohsin ◽  
Farhad Taghizadeh-Hesary ◽  
Nadeem Iqbal

This study evaluates the role of information in the environmental performance index (EPI) in different energy-consuming sectors in Pakistan through a novel slack-based data envelopment analysis (DEA). The index combines energy consumption as the primary input and gross domestic product (GDP) as the desirable output and CO2 emissions as the undesirable output. Yale’s EPI measures the efficiency of the sectoral level environmental performance of primary energy consumption in the country. Performance analysis was conducted from 2009 to 2018. The sectors were assigned scores between one and zero, with zero indicating maximum decision-making unit (DMU) inefficiency and one indicating maximum DMU efficiency. Despite being in the top-performing sector, agriculture scored only 0.51 in 2018, and the electricity sector obtained 0.412. Results also show that even the best-performing sector operates below the efficiency level. The mining and quarrying sector ranked second by obtaining 0.623 EPI and 0.035 SBEPI. Results also show that much of the energy supply of Pakistan (60.17%) is focused on fossil fuels, supplemented by hydropower (33%), while nuclear, wind, biogas, and solar power account for 5.15%, 0.47%, 0.32%, and 0.03%, respectively. Nonetheless, the overall results for both measures remained reasonably consistent. According to the literature and the energy crisis and climate instability dilemma, the authors conclude that changes to a diverse green power network are a possibility and an imminent need. Similarly, the government should penalize companies with poor performance. Furthermore, to ensure the capacity development and stability of environmental management and associated actions in the country, providing access to knowledge and training to groom human resources and achieve the highest performance is crucial.


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