scholarly journals Determinants of Efficiency of Zakat Institutions in Indonesia: Two-Stage Data Envelopment Analysis Approach

2019 ◽  
Author(s):  
Rizki Kurniawan
Keyword(s):  
Data Envelopment Analysis ◽  
Quantitative Research ◽  
Positive Trend ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Two Stage ◽  
Analysis Technique ◽  
Negative Effect ◽  
Input Variables ◽  
Research Period

This study aims to analyze the level of efficiency and determine the factors that affect the efficiency of the National Zakat Management Organization (OPZ). This research is descriptive quantitative research. Samples in this study are six National Zakat Management Organizations with research period from 2012-2016. The analysis technique used is two-stage data envelopment analysis. First stage, using DEA to measure OPZ efficiency level with production approach and assumption of output-oriented CRS and VRS. The input variables used are amil salary, operational costs, and socialization costs, the output variables used are collected funds and funds disbursed. Second stage, using tobit regression model to see the factors that affect OPZ efficiency. Based on the results of DEA, during the period of 2012-2016 OPZ efficiency experienced a positive trend. In general there had been an increase in OPZ performance efficiency from 2012 to 2016. BNUIS BNI became the most efficient OPZ compared to other OPZ. Based on the results of Tobit regression, the total of human resources has a significant negative effect on the level of efficiency, transparency and OPZ type significantly positive, while the zakat payment system and ACR ratio do not affect the efficiency level of OPZ.

scholarly journals Efficiency Institution Baitul Maal Tamwill in The Westdistrict Bandung

2020 ◽  
Vol 1 (1) ◽  
pp. 18-24
Author(s):  
Annisa Nur Hakim ◽  
A Jajang W Mahri ◽  
Aas Nurasyiah
Keyword(s):  
Data Envelopment Analysis ◽  
Research Method ◽  
Secondary Data ◽  
Data Envelopment ◽  
Analysis Technique ◽  
Dea Analysis ◽  
Input Variables ◽  
Operational Activities ◽  
A Company ◽  
Descriptive Method

Abstract.     Baitul Maal Wat Tamwil has experienced development in recent years. However, based on BMT performance data in West Bandung regency is less optimal. It is known that there are one efficient BMTs in West Bandung Regency and three BMTs that are inefficient. The cause of BMT's less optimal performance is inefficiency in operational activities. This study aims to determine the level of efficiency of BMT in West Bandung 2011-2017 period and find out the causes of inefficiency. This study uses secondary data from four BMTs in West Bandung District which are sampled. The research method used is descriptive method with Data Envelopment Analysis (DEA) analysis technique which is to measure the level of efficiency of a company. Input variables used are operating expenses, total assets, and TPF. Furthermore, the output variables used are SHU, income, and financing. Based on the results of research conducted, the conditions of the BMT in West Bandung Regency have not been perfectly efficient. There are three BMTs that have experienced inefficiencies including BMT Dana Ukhuwah, BMT Mustama, and BMT Rabbani. Keywords.          Efficiency, Baitul Maal Wat Tamwil, Data Envelopment Analysis

scholarly journals Performance Through Efficiency in the Public Healthcare System – A DEA Approach in an Emergent Country

2017 ◽  
Vol 62 (1) ◽  
pp. 31-49 ◽  
Author(s):  
Cristina Silvia Nistor ◽  
Cristina Alexandrina Ștefănescu ◽  
Andrei-Răzvan Crișan
Keyword(s):  
Data Envelopment Analysis ◽  
Public Sector ◽  
Healthcare System ◽  
Emerging Countries ◽  
Public Healthcare ◽  
Data Envelopment ◽  
Tobit Regression ◽  
The Public ◽  
System A ◽  
Analysis Technique

AbstractAiming to analyze the efficiency of the public sector, this paper enriches the literature by providing insights of the healthcare system for an emergent country - Romania. The empirical findings reached by applying the input orientated-variable return to scale (VRS) model of Data Envelopment Analysis (DEA) and Tobit regression method are determined on two key levels of the study. The Data Envelopment Analysis technique quantifies the efficiency within 20 representative hospitals located in the four administrative macro-regions, highlighting the ways of increasing efficiency, while the Tobit regression identifies the factors that influence the efficiency level. The results of the investigation allow for comparisons with other emerging countries, as efficiency has become an increasingly significant factor for public sector evolution.

scholarly journals Effects of Input Composition on Technical Efficiencies of Textile Industries in Pakistan

2012 ◽  
Vol 51 (2) ◽  
pp. 117-130
Author(s):  
Tariq Mahmood
Keyword(s):  
Data Envelopment Analysis ◽  
Returns To Scale ◽  
Jel Classification ◽  
Manufacturing Industries ◽  
Raw Material ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Analysis Technique ◽  
Tobit Analysis ◽  
Positive Effect

This paper studies the technical efficiencies of the textile manufacturing industries in Pakistan using 5-digit level industry data. Technical efficiencies are computed by the Data Envelopment Analysis technique assuming constant as well as variable returns to scale. The efficiency scores thus obtained are analysed by the TOBIT regression technique to determine how input composition influences these efficiency scores. It is found that imported raw material and machinery exercises a positive effect, whereas non-industrial costs affect technical efficiencies in a negative way. Electricity does not play its due role in affecting technical efficiencies. JEL Classification: C24, D24, L6, O14 Keywords: Technical Efficiency, Data Envelopment Analysis, TOBIT Analysis, Manufacturing Industries

scholarly journals Determinants of tomato farmers efficiency in Mymensingh district of Bangladesh: Data Envelopment Analysis approach

2018 ◽  
Vol 16 (1) ◽  
pp. 93-97 ◽  
Author(s):  
Sandip Mitra ◽  
Muhammad Yunus
Keyword(s):  
Data Envelopment Analysis ◽  
Sampling Technique ◽  
Data Envelopment ◽  
Tobit Regression ◽  
High Yielding Variety ◽  
Factors Affecting ◽  
Input Use ◽  
Measuring Efficiency ◽  
Negative Effect ◽  
Education Training

Tomato is one of the major vegetables in Bangladesh that experienced massive productivity growth after independence. Nevertheless, farmers are struggling to find out optimal input combination in their farm that causes inefficient input use. Therefore, this study estimated the factors affecting efficiency of tomato farmers in Mymensingh of Bangladesh. Input oriented Data Envelopment Analysis (DEA) was employed for measuring efficiency while Tobit regression model was used to estimate the factors affecting efficiency. A total of 60 tomato farmers were selected using random sampling technique. Mean technical efficiency for tomato farmers was 0.83 implies that tomato farmers can reduce their input use by 17%. Education, training and high yielding variety adoption had positive effect on efficiency while age of tomato farmer’s had negative effect on efficiency. Efficiency increased with the farmer’s education, training and variety adoption. Farmer’s adopting local high yielding variety was more efficient than that of exotic high yielding variety. In addition, efficiency of farmers reduced with their age. Improvement of tomato farmer’s efficiency is possible if farmers received education, training and local high yielding variety.J. Bangladesh Agril. Univ. 16(1): 93-97, April 2018

scholarly journals Determinants of Cost Efficiency of Takaful and Conventional Insurance Firms of Pakistan

2018 ◽  
Vol 4 (2) ◽  
pp. 331-340
Author(s):  
Muhammad Abbas ◽  
Allah Bakhsh Khan ◽  
Salman Abbasi ◽  
Zeeshan Mahmood
Keyword(s):  
Data Envelopment Analysis ◽  
Equity Capital ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Fixed Assets ◽  
Efficiency Performance ◽  
Dea Efficiency ◽  
Insurance Firms ◽  
Input Variables ◽  
Tobit Regression Analysis

This study investigates the Efficiency Performance of Takaful and Conventional Insurance Firms of Pakistan in terms of Cost, Allocative and Technical efficiencies for the period of 2010-2015. Six years panel data of Takaful and listed Conventional Insurance Firms of Pakistan is taken under consideration. The Methodology of Data Envelopment Analysis (DEA) is used in order to estimate efficiencies scores. Furthermore, Tobit Regression Analysis is carried out for determination of the real contributors of efficiencies in Insurance and takaful Industry of Pakistan. In Data Envelopment Analysis, Labor, Total Fixed Assets and Total Equity Capital are used as input variables. Simultaneously, the price variables are used along with input variables such as Price of Labor, Price of Total Fixed Assets and Price of Total Equity Capital. The output variables include Invested Assets, Investment Incomes and Net Premiums. In second Stage Analysis (i.e. Tobit regression), DEA efficiency scores are used as dependent variable, whereas Age, Size, and Leverage are used as independent variables along with the dummy for conventional and Takaful firms of Pakistan. This study found that Takaful and insurance firms have been operating on almost equal efficiency levels. Furthermore LEVERAGE is the main contributor for efficiency optimization, followed by the firm SIZE, whereas, firm’s AGE has no contribution in efficiency scores.

scholarly journals Efficiency Considering Credit Risk in Banking Industry, Using Two-stage DEA

2013 ◽  
Vol 4 (8) ◽  
pp. 356-360
Author(s):  
Hadi Ghafoorian ◽  
NikIntan Norhan . ◽  
Mohammed Ndaliman Abubakar . ◽  
Fazel Mohammadi Nodeh .
Keyword(s):  
Data Envelopment Analysis ◽  
Credit Risk ◽  
Banking Industry ◽  
Bank Performance ◽  
Data Envelopment ◽  
Two Stage ◽  
New Markets ◽  
Second Stage ◽  
Analysis Technique ◽  
Strong Competition

The increased competition in the banking industry and banks' efforts to participate in new markets has affected bank performance and credit risk. Their presence in new markets and strong competition from other competitors today makes them face more uncertain situation. Given the importance of this issue, there are few studies about the efficiency calculated with regard to credit risk. Banking literature on this subject is poor. This paper introduces two-stage data envelopment analysis technique for estimation of their efficiency with regard to credit risk, its output and inputs in the first and second stage. Non-performing loans is output to proxy credit risk.

Technical efficiency of private sector hospitals in India using data envelopment analysis

2018 ◽  
Vol 25 (9) ◽  
pp. 3570-3591 ◽  
Author(s):  
Aradhana Vikas Gandhi ◽  
Dipasha Sharma
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
Hospital Industry ◽  
Technological Advancement ◽  
Tobit Regression ◽  
Content Type ◽  
Input Variables

Purpose The purpose of this paper is to ascertain the performance of Indian hospitals in recent past and derive meaningful insights for policy makers and practicing managers in this area. Design/methodology/approach This paper analyses the technical efficiency of select Indian private hospitals using three related methodologies: data envelopment analysis (DEA), Malmquist Productivity Index (MPI) and Tobit regression. Two output variables (i.e. total income and profit after tax) and four input variables (i.e. cost of labour, net fixed assets, current assets and other operating expenses) were selected for the purpose of the study. Findings DEA analysis has shown that 14 out of 37 hospitals are found to be efficient under the Cooper and Rhodes model of DEA and 20 out of 37 hospitals are efficient under the Banker, Charles and Cooper model of DEA. The empirical results pertaining to MPI indicate an overall productivity progress in the private Indian hospital industry during the study period, which is largely due to technological advancement in the industry. Tobit regression demonstrates that chain affiliated, specialized and multi-city located hospitals exhibit a higher technical efficiency. Research limitations/implications This study has a limitation with reference to the unavailability of data on the input and output parameters of the model. The data related to the number of beds, number of doctors, number of nurses, etc., were not available for the period under consideration. Originality/value This study seems to be one of the few studies applying productivity and performance analysis using DEA, MPI and Tobit regression for the Indian private hospital industry.

Two-Stage Double Bootstrap Data Envelopment Analysis for Efficiency Evaluation of Shared-Bicycle Stations in Urban Cities

2020 ◽  
Vol 2674 (6) ◽  
pp. 211-224 ◽  
Author(s):  
Jungyeol Hong ◽  
Reuben Tamakloe ◽  
Jihoon Tak ◽  
Dongjoo Park
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Truncated Regression ◽  
Trajectory Data ◽  
Two Stage ◽  
Factors Affecting ◽  
Input Variables ◽  
Shared Bicycle ◽  
Station Location ◽  
The City

To optimize the performance and operation of shared-bicycle systems, this study aims to evaluate the efficiency of shared-bicycle stations and to find factors affecting their efficiency scores. We analyzed the efficiency of 1,260 shared-bicycle stations in the City of Seoul using shared-bicycle rental and trajectory data as of June 2018. In this study, the two-stage bootstrap data envelopment analysis, which is a non-parametric frontier technique, was applied to estimate each shared-bicycle station’s efficiency. In the first stage, we evaluated efficiency scores by employing the number of bicycle racks and bicycle path ratio as input variables, and bicycle turnover rate and balancing rate as output variables. The efficiency scores were regressed on potential covariates using a bootstrapped truncated regression in the second stage. From our results, the efficiencies of shared-bicycle stations were found to be diverse depending on the nature of land use around the station location. The results present evidence to show that shared-bicycle stations located in residential and school-dominated areas are likely to be efficient, whereas those in semi-industrial areas, commercial, and business districts are generally inefficient. Furthermore, the effect of variables like the commuting population, the number of registered vehicles, and the number of bicycle-related accidents per year were statistically significant, thus affecting shared-bicycle station performance. This study offers essential insights into the efficiency of shared-bicycle stations, which could be incorporated into shared-transportation strategies to improve mobility in urban cities.

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