scholarly journals ANALISIS STRUKTUR, KONSENTRASI, DAN EFISIENSI PASAR INDUSTRI TELEKOMUNIKASI DI INDONESIA

Media Ekonomi ◽  
2016 ◽  
Vol 24 (2) ◽  
pp. 113
Author(s):  
Zulfikar Adi Satria ◽  
Tri Kunawangsih P
Keyword(s):  
Data Envelopment Analysis ◽  
Market Structure ◽  
Concentration Ratio ◽  
Telecommunications Industry ◽  
Telecommunication Industry ◽  
Data Envelopment ◽  
Total Revenue ◽  
Analysis Technique ◽  
Efficient Level ◽  
Very High

<p><em>The purpose of this study was to determine how the structure, market concentration and efficiency of the telecommunication industry in Indonesia. The analysis technique used in this research is Concentration Ratio (CR4) and Data Envelopment Analysis (DEA). Total revenue of the Indonesia telecommunication industry from 2010-2015 were used to calculate Concentration Ratio (CR4) and Data Envelopment Analysis (DEA) are input and output, the input consists of total assets, debt and equity, the output consists of total revenue and gross profits. Based on the analysis results of Concentration Ratio (CR4) is quite of very high ranging from 98,17% - 99,67%, the market structure in property industry classified within a very high concentrated oligopoly. Results from Data Envelopment Analysis (DEA) in 2010-2015 there were 1 efficient company. As a result of an oligopoly market structure is very tight, then in the telecommunications industry is a lot to make improvements to network sharing and speed the delivery of messages, telephone, and internet as well as to achieve efficient company should refer to the telecommunications industry, which reached the maximum efficient level. In order to achieve an efficient level that has not been efficient, the company must conduct debt reduction, labor usage more efficient and increase product sales.</em></p>

scholarly journals ANALISIS SCP PADA INDUSTRI PROPERTI DI INDONESIA

Media Ekonomi ◽  
2016 ◽  
Vol 24 (2) ◽  
pp. 139
Author(s):  
Nurhayati , ◽  
Husna Leila Yusran
Keyword(s):  
Data Envelopment Analysis ◽  
Concentration Ratio ◽  
Data Envelopment ◽  
Herfindahl Index ◽  
Total Revenue ◽  
High Concentration ◽  
Input And Output ◽  
Analysis Technique ◽  
Competitive Nature ◽  
Total Sales

<em>The purpose of this study is to determine how the structure, market concentration and efficiency of the property industry in Indonesia. The analysis technique used in this research is Concentration Ratio (CR10), Herfindahl Index-Hirschman (IHH) and Data Envelopment Analysis (DEA). Total revenue of the Indonesia property industry from 2010-2014 is used to calculate Concentration Ratio (CR10) and Herfindahl Index-Hirschman (IHH), while the Data Envelopment Analysis (DEA) is input and output, the input consists of total assets, debt, and equity, the output consists of total sales and profits. Based on the analysis the results of Concentration Ratio (CR10) is quite high, ranging from 74.65% - 77.16%, the market structure in the property industry classified within a tight oligopoly. Based on IHH has a range of numbers from 0.1013 to 0.56667, which means competition Indonesian property industry and the competitive nature of high concentration. Results DEA in 2010-2010 there are 4-8 efficient companies. As a result of which are oligopolistic and competitive, the companies in the property industry are doing a lot in marketing strategy as well as to achieve efficient companies should refer to the property industry has already reached the maximum efficient rate.</em>

scholarly journals ANALISA STRUKTUR PASAR DAN EFISIENSI INDUSTRI PERBANKAN DI INDONESIA PERIODE 2017-2012

Media Ekonomi ◽  
2014 ◽  
Vol 22 (1) ◽  
pp. 27
Author(s):  
Nuraini Chaniago
Keyword(s):  
Data Envelopment Analysis ◽  
Market Structure ◽  
Market Share ◽  
Concentration Ratio ◽  
Banking Industry ◽  
Maximum Level ◽  
Data Envelopment ◽  
High Concentration ◽  
Input And Output ◽  
Analysis Technique

<p><em>The purpose of this study was to determine how the market structure and efficiency of banking industry in Indonesia.</em><em>The analysis technique used in this research is to use the concentration ratio (CR20) and the Herfindahl Hirchman Index (HHI), and DEA (Data Envelopment Analysis). This study uses data on the number of banking and corporate assets to determine the efficiency of using the 20 banks in the Input and Output of the report Indonesian banking in the period 2007-2012. </em><em>The results showed the level of concentration ratio (CR20) range from 77.69% - 79.47%. The figure shows the structure of the banking industry 2007-2012 period was a tight oligopoly. which means that the structure of the banking industry in Indonesia is not structured oligopoly monopoly but because it is not close to 1. When viewed competition banks in Indonesia is competitive with high concentration and competitive, it is characterized by competition between the market share of twenty dominant company in the Indonesian banking industry in the number of assets. In the calculation of the twenty study Indonesian banking industry in the period 2007-2012 by using the method of DEA (Data Envelopment Analysis) produced differences in the efficiency of each bank, Of the twenty 20 Indonesian banking industry that has not reached the maximum level of efficiency that is 100% should refer to the banking has reached a maximum level of 100% in accordance with the characteristics of banking itself.</em></p><p> </p>

scholarly journals STRUKTUR PASAR DAN EFISIENSI INDUSTRI PERBANKAN DI INDONESIA

Media Ekonomi ◽  
2018 ◽  
Vol 22 (2) ◽  
pp. 157
Author(s):  
Muhammad Rizky Ramadhan ◽  
Nur’aini Chaniago
Keyword(s):  
Data Envelopment Analysis ◽  
Market Structure ◽  
Market Share ◽  
Concentration Ratio ◽  
Banking Industry ◽  
Maximum Level ◽  
Data Envelopment ◽  
Input And Output ◽  
Analysis Technique

<span>The purpose of this study was to determine how the market structure and efficiency of <span>banking industry in Indonesia. The analysis technique used in this research is to use the <span>concentration ratio (CR20) and the Herfindahl Hirchman Index (HHI), and DEA (Data <span>Envelopment Analysis). This study uses data on the number of banking and corporate assets <span>to determine the efficiency of using the 20 banks in the Input and Output of the report <span>Indonesian banking in the period 2007-2012. The results showed the level of concentration <span>ratio (CR20) range from 77.69% - 79.47%. The figure shows the structure of the banking <span>industry 2007-2012 period was a tight oligopoly. Which means that the structure of the<br /><span>banking industry in Indonesia is not structured oligopoly monopoly but because it is not <span>close to 1. When viewed competition banks in Indonesia is competitive with high <span>concentration and competitive, it is characterized by competition between the market share <span>of twenty dominant company in the Indonesian banking industry in the number of assets. In <span>the calculation of the twenty study Indonesian banking industry in the period 2007-2012 by <span>using the method of DEA (Data Envelopment Analysis) produced differences in the <span>efficiency of each bank, Of the twenty 20 Indonesian banking industry that has not reached<br /><span>the maximum level of efficiency that is 100% should refer to the banking has reached a<span>maximum level of 100% in accordance with the characteristics of banking it self.</span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span><br /></span>

scholarly journals ASSESSMENT OF TFP IN EUROPEAN AND AMERICAN HIGHER EDUCATION INSTITUTIONS – APPLICATION OF MALMQUIST INDICES

2016 ◽  
Vol 24 (2) ◽  
pp. 467-488 ◽  
Author(s):  
Joanna WOLSZCZAK-DERLACZ
Keyword(s):  
Higher Education ◽  
Data Envelopment Analysis ◽  
Productivity Growth ◽  
Negative Association ◽  
Distance Measures ◽  
Data Envelopment ◽  
Total Revenue ◽  
American Higher Education ◽  
Malmquist Indices ◽  
The U.S

In this study we apply Malmquist methodology, based on the estimation of distance measures through Data Envelopment Analysis (DEA), to a sample of 500 universities (in 10 European countries and the U.S.) over the period 2000 to 2010 in order to assess and compare their productivity. On average, a rise in TFP is registered for the whole European sample (strongest for Dutch and Italian HEIs), while the productivity of American HEIs suffered a slight decline. Additionally, we show that productivity growth is negatively associated with size of the institution and revenues from government, and positively with regional development in the case of the European sample, while American HEI productivity growth is characterised by a negative association with GDP and a positive one with the share of government resources out of total revenue.

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

Evaluating Predictive power of Data Envelopment Analysis Technique Compared with Logit and Probit Models in Predicting Corporate Bankruptcy

2012 ◽  
Vol 02 (09) ◽  
pp. 38-46
Author(s):  
Khalili Araghi Maryam ◽  
Makvandi Sara
Keyword(s):  
Data Envelopment Analysis ◽  
Predictive Power ◽  
Environmental Changes ◽  
Stock Exchange ◽  
Rapid Development ◽  
Manufacturing Firms ◽  
Data Envelopment ◽  
Probit Models ◽  
Analysis Technique ◽  
Logit And Probit Models

Simultaneous with extensive environmental changes and the rapid development of technology which has increasingly accelerated economy, competitiveness economical enterprises have restricted earning profit and make probable closing of bankrupt firms. Thus it seems necessary to find a model that can predict financial crisis and bankruptcy of companies. Nowadays occurrence of significant progress in other sciences, such as computer and math attract the attention of the financial scholars toward designing and using more exact patterns like Data Envelopment Analysis (DEA). For this purpose, this study uses DEA technique to predict the bankruptcy likelihood of manufacturing firms and also compare its predictability with2 methods : Logit and Probit models. Study sample includes all manufacturing firms listed in Stock Exchange of Tehran from 2000-2010. The results showed that the accuracy of the designed model under DEA technique is %72 and the predictability of Logit and Probit models has been81, and %80 respectively. The results also showed DEA was proved to be an effective tool for predicting bankruptcy likelihood of manufacturing firms; but,it acted less efficient than Logit and Probit models.

Empirical Analysis of Operational Efficiency of China’s Telecommunication Industry: Based on DEA Approach

2013 ◽  
Vol 291-294 ◽  
pp. 3019-3023
Author(s):  
Chang Jian Qi ◽  
Ting Jie Lv
Keyword(s):  
Data Envelopment Analysis ◽  
Technological Progress ◽  
Evaluation Model ◽  
Indicator System ◽  
Telecommunication Industry ◽  
Data Envelopment ◽  
Resource Allocation Efficiency ◽  
Major Factors ◽  
Infinite Model ◽  
Inputs And Outputs

By combining the Data Envelopment Analysis (DEA) method, from the view of time and district, this paper carries out a dynamic evaluation of resource allocation efficiency of China’s telecommunication industry from 1973 to 2008. The results show that technical efficiency indicator and technological progress indicator are the major factors of resources allocation of China’s telecommunication industry. It analyzed and studied all previous reorganization and regulation effects to the telecom with the reference to the efficiency changes of the telecom industry. Based on the non-Archimedean infinite model C2R of the Data Envelopment Analysis, combined with characteristics of inputs and outputs of China’s telecommunication industry, the paper sets up an indicator system of inputs and outputs as well as an overall efficiency evaluation model China’s telecommunication industry.

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.

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