scholarly journals Operational Efficiency of Mexican Water Utilities: Results of a Double-Bootstrap Data Envelopment Analysis

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 553 ◽  
Author(s):  
Jose Humberto Ablanedo-Rosas ◽  
Aaron Guerrero Campanur ◽  
Elias Olivares-Benitez ◽  
Jacqueline Y. Sánchez-García ◽  
Juan Enrique Nuñez-Ríos
Keyword(s):  
Distribution Function ◽  
Data Envelopment Analysis ◽  
Research Method ◽  
Operational Efficiency ◽  
Water Utilities ◽  
Data Envelopment ◽  
Truncated Regression ◽  
Context Variable ◽  
Context Variables ◽  
Double Bootstrap

The objective of this paper is to estimate the operational efficiency of Mexican water utilities and identify the context variables that impact their efficiency. In particular, a bootstrap data envelopment analysis (DEA) and a bootstrap truncated regression analysis are combined in a two-stage research method. In the first stage, an input-oriented DEA model is used to determine bootstrap efficiency scores. Then, the corrected distribution function of the efficiency scores is used to estimate a truncated regression which is aimed to identify the significant influential context variables. Three categorical and two continuous context variables are considered in the analysis. Results show that only one context variable has a significant impact on the water utilities efficiency scores. Managerial recommendations are drawn from the analysis. It is suggested that water utilities continue or implement wastewater treatment, persist in decreasing and controlling leakage across the distribution network, and maximizing sewer coverage.

scholarly journals Operational Efficiency of Chinese Provincial Electricity Grid Enterprises: An Evaluation Employing a Three-Stage Data Envelopment Analysis (DEA) Model

2018 ◽  
Vol 10 (9) ◽  
pp. 3168 ◽  
Author(s):  
Haoran Zhao ◽  
Huiru Zhao ◽  
Sen Guo
Keyword(s):  
Data Envelopment Analysis ◽  
Environmental Variables ◽  
Market Competition ◽  
Environmental Values ◽  
Operational Efficiency ◽  
Data Envelopment ◽  
Electricity Grid ◽  
Frontier Analysis ◽  
Dea Model ◽  
Statistical Noise

With the implementation of new round electricity system reform in China, the provincial electricity grid enterprises (EGEs) of China should focus on improving their operational efficiency to adapt to the increasingly fierce market competition and satisfy the requirements of the electricity industry reform. Therefore, it is essential to conduct operational efficiency evaluation on provincial EGEs. While considering the influences of exterior environmental variables on the operational efficiency of provincial EGEs, a three-stage data envelopment analysis (DEA) methodology is first utilized to accurately assess the real operational efficiency of provincial EGEs excluding the exterior environmental values and statistical noise. The three-stage DEA model takes the amount of employees, the fixed assets investment, the 110 kV and below distribution line length, and the 110 kV and below transformer capacity as input variables and the electricity sales amount, the amount of consumers, and the line loss rate as output variables. The regression results of the stochastic frontier analysis model indicate that the operational efficiencies of provincial EGEs are significantly affected by exterior environmental variables. Results of the three-stage DEA model imply that the exterior environmental values and statistical noise result in the overestimation of operational efficiency of provincial EGEs, and the exclusion of exterior environmental values and statistical noise has provincial-EGE-specific influences. Furthermore, 26 provincial EGEs are divided into four categories to better understand the differences of operational efficiencies before and after the exclusion of exterior environmental values and statistical noise.

Benchmarking the efficiencies of Indonesia’s municipal water utilities using Stackelberg data envelopment analysis

2015 ◽  
Vol 22 (4) ◽  
pp. 588-609 ◽  
Author(s):  
Andreas Wibowo ◽  
Hans Wilhelm Alfen
Keyword(s):  
Data Envelopment Analysis ◽  
The Body ◽  
Water Utilities ◽  
Data Envelopment ◽  
Two Stage ◽  
Restrictive Assumption ◽  
Content Type ◽  
Second Stage ◽  
Municipal Water ◽  
The Impact

Purpose – The purpose of this paper is to present a yardstick efficiency comparison of 269 Indonesian municipal water utilities (MWUs) and measures the impact of exogenous environmental variables on efficiency scores. Design/methodology/approach – Two-stage Stackelberg leader-follower data envelopment analysis (DEA) and artificial neural networks (ANN) were employed. Findings – Given that serviceability was treated as the leader and profitability as the follower, the first and second stage DEA scores were 55 and 32 percent (0 percent = totally inefficient, 100 percent = perfectly efficient), respectively. This indicates sizeable opportunities for improvement, with 39 percent of the total sample facing serious problems in both first- and second-stage efficiencies. When profitability instead leads serviceability, this results in more decreased efficiency. The size of the population served was the most important exogenous environmental variable affecting DEA efficiency scores in both the first and second stages. Research limitations/implications – The present study was limited by the overly restrictive assumption that all MWUs operate at a constant-return-to-scale. Practical implications – These research findings will enable better management of the MWUs in question, allowing their current level of performance to be objectively compared with that of their peers, both in terms of scale and area of operation. These findings will also help the government prioritize assistance measures for MWUs that are suffering from acute performance gaps, and to devise a strategic national plan to revitalize Indonesia’s water sector. Originality/value – This paper enriches the body of knowledge by filling in knowledge gaps relating to benchmarking in Indonesia’s water industry, as well as in the application of ensemble two-stage DEA and ANN, which are still rare in the literature.

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 Keterkaitan Efisiensi Kredit Usaha Rakyat (KUR) dengan Topografi Wilayah di Kabupaten Pati, Provinsi Jawa Tengah

2019 ◽  
Vol 3 (2) ◽  
pp. 117-130
Author(s):  
Farida Farida ◽  
Nur Wahyuni ◽  
Ida Zulfida
Keyword(s):  
Spatial Distribution ◽  
Data Envelopment Analysis ◽  
Economic Activity ◽  
Research Method ◽  
Secondary Data ◽  
Data Envelopment ◽  
Economic Activities ◽  
Central Java ◽  
Exogenous Factors ◽  
Descriptive Qualitative

Exogenous factors such as topography of the region are often overlooked in determining the pattern of economic activity. In fact, the geographical surface contributes to the spatial distribution of varied economic activities. The purpose of this study was to see the linkage between the efficiency of the disbursement of People’s Business Credit (KUR) program and the topography of the region in Pati Regency-Central Java. The research method is descriptive qualitative by overlaying the efficiency level of 35 KUR channeling banks with polygon maps of each subdistrict in Pati regency. Data on the efficiency level of unit banks are secondary data of each bank unit which has been calculated with Data Envelopment Analysis (DEA) application. Is it dicovered that unit banks are very inefficient at topographies bordered with arid limestone mountains or along rivers that often overflows. As a result, economic activity is not optimal and the disbursement of KUR is not efficient at the area. On the contrary, at topographies in the lowlands, the trade, agriculture, and fisheries sectors are advanced, population is large,  economic activities are fast, thus encourage efficient credit disbursement.

Systematic Review: Penilaian Efisiensi Rumah Sakit dengan Metode Data Envelopment Analysis (DEA)

2021 ◽  
Vol 10 (04) ◽  
pp. 258-268
Author(s):  
Pantri Widyastuti ◽  
Atik Nurwahyuni
Keyword(s):  
Systematic Review ◽  
Data Envelopment Analysis ◽  
Hospital Efficiency ◽  
Data Envelopment ◽  
Truncated Regression ◽  
Tobit Regression

Dalam sistem kesehatan yang berkembang saat ini, efisiensi merupakan hal yang utama. Pengukuran efisiensi bermanfaat untuk pemerintah maupun swasta untuk dapat mengambil keputusan yang berhubungan dengan tinggi rendahnya biaya perawatan di rumah sakit. Penelitian ini bertujuan untuk mengkaji metode Data Envelopment Analysis (DEA) yang digunakan dalam berbagai penelitian dalam pengukuran efisiensi rumah sakit. Desain penelitian yang digunakan adalah dengan sistematic review dengan metode PRISMA tanpa meta analisis. Sumber data didapatkan dari Proquest, Sciencedirect dan Pubmed pada tahun 2019 hingga 2020. Pencarian data dilakukan pada bulan Oktober 2020 dengan kata kunci Hospital Efficiency dan Data Envelopment Analysis. Hasilnya adalah penilaian efisiensi rumah sakit menggunakan metode DEA lebih banyak dilakukan dengan analisa dua tahap menggunakan tobit regression atau truncated regression. Perhitungan index malmquist juga banyak digunakan setelah perhitungan DEA dilakukan untuk melihat efisiensi rumah sakit dalam periode waktu tertentu.

scholarly journals A comparative evaluation of operational efficiency of wood industry using data envelopment analysis and Malmquist productivity index

2019 ◽  
Vol 70 (3) ◽  
pp. 287-298 ◽  
Author(s):  
Jože Kropivšek ◽  
Matej Jošt ◽  
Petra Grošelj ◽  
Darko Motik ◽  
Andreja Pirc Barčić ◽  
...  
Keyword(s):  
Data Envelopment Analysis ◽  
Comparative Evaluation ◽  
Operational Efficiency ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
Low Carbon ◽  
Wood Industry ◽  
International Comparative ◽  
Using Data

The wood industry, as a traditional sector, represents a very important part of the economy in terms of ensuring a sustainable development of society and transition to a low-carbon society in both countries studied, Slovenia and Croatia. For its further development, it is crucial to know the current position of the industry. The best way to achieve this is an analysis of financial data and international comparative evaluation of its operational efficiency. The aim of the research is to compare the relative efficiency of the wood industry using Data Envelopment Analysis (DEA) and the Malmquist Productivity Index (MI), focusing on the Slovenian and Croatian wood industry sectors (C16 and C31) for a recent five-year period (from 2013-2017). With this purpose, the combined measure DEA/MI was applied. The analysis includes only the highest rated companies with more than fi ve employees, divided into 12 clusters regarding the company size. As a result, it was established that clusters CRO-C31- micro, CRO-C16-micro and SI-C16-larger have the highest operational efficiency, due to the effects of different financial indicators, especially activity and liquidity ratios. In general, within the grouped clusters regarding country and subsector, groups SI-C16 and CRO-C31 achieve the highest values for the average of weighted score of efficiency, while CRO-C16 achieves the lowest values.

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