scholarly journals Environmental Performance Assessment of Energy-Consuming Sectors Through Novel Data Envelopment Analysis

2022 ◽  
Vol 9 ◽  
Author(s):  
Yangang Xue ◽  
Muhammad Mohsin ◽  
Farhad Taghizadeh-Hesary ◽  
Nadeem Iqbal
Keyword(s):  
Energy Consumption ◽  
Data Envelopment Analysis ◽  
Environmental Performance ◽  
Poor Performance ◽  
Electricity Sector ◽  
Data Envelopment ◽  
Primary Input ◽  
Decision Making Unit ◽  
Energy Consuming ◽  
The Government

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.

Within-group common benchmarking the environmental efficiency in China with data envelopment analysis

2018 ◽  
Vol 13 (2) ◽  
pp. 375-393 ◽  
Author(s):  
Chaoxin Cheng ◽  
Sheng Ang
Keyword(s):  
Energy Consumption ◽  
Data Envelopment Analysis ◽  
Water Consumption ◽  
Environmental Performance ◽  
Environmental Efficiency ◽  
Significant Variable ◽  
Data Envelopment ◽  
Content Type ◽  
Environmental Evaluation ◽  
Common Reference

Purpose Economic growth of China in the past decades has caused rapid increase in energy consumption and environmental deterioration. Therefore, it is critical to make an environmental evaluation and to help decision makers to know each province’s distance to the optimal target and improve environmental performance. Design/methodology/approach In such background, the authors use a within-group common benchmarking model with data envelopment analysis for China’s environmental evaluation and target setting in this paper. This model considers a common treatment of decision-making units within groups but allows for the different circumstances across groups and gives a common reference set for benchmarking. Findings The results show that there are regional difference in economic development and environmental protection. The coastal area has the best average environmental efficiency, then followed by inland area and the lowest level is the western area. The target results show that in four inputs, namely, population, capital, energy consumption and water consumption, the water consumption is the significant variable which should be decreased largely. All provinces have room to improve their economic level under the condition of a better environment. Originality/value In this research, the authors consider the similarity in geography and economy for Chinese provinces and divide 30 provinces into eight economic zones; thus, provinces in the same zone are evaluated with the same weight. Environmental performance and efficiency for each province can be obtained. Efficient targets for those inefficient provinces are provided as a possible improvement direction as well.

Environment Performance Evaluation Under Emission Quota Constraint

2014 ◽  
Vol 13 (04) ◽  
pp. 779-794 ◽  
Author(s):  
Gongbing Bi ◽  
Yan Luo ◽  
Shaofu Du
Keyword(s):  
Performance Evaluation ◽  
Data Envelopment Analysis ◽  
Environmental Performance ◽  
Pollution Abatement ◽  
Efficiency Analysis ◽  
Data Envelopment ◽  
Proposed Model ◽  
Emission Quota ◽  
The Government ◽  
Environment Performance

The primary purpose of our paper is to evaluate environmental performance as well as to model some nonseparable inputs and outputs using the data envelopment analysis (DEA) model. The efficiency analysis takes emission quota into consideration with the objectives of minimizing both total undesirable emissions and consumption of input resources. The value of emission quota that directly influences the environmental performance is obtained. The proposed model is applied to the data of power industries in 30 Chinese provinces. In addition, the sensitivity of the efficiency with respect to the value of emission quota is investigated. The results show the environmental protection in the power industry can be further improved. Our conclusion is that strict environmental regulations often enhance economic development rather than hinder it. This strongly suggests the government needs to pay more attention to pollution abatement because of its promoting effects on environmental performance.

Relative Efficiency of Decision Making Units Producing Both Desirable and Undesirable Outputs: A Case of Textile Processing Units in Pakistan.

2011 ◽  
Vol 50 (4II) ◽  
pp. 685-698
Author(s):  
Samina Khalil
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Value Added ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Textile Processing ◽  
Decision Making Unit ◽  
Desirable And Undesirable Outputs ◽  
Decision Making Units

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

scholarly journals Measuring the Productivity of Energy Consumption of Major Industries in China: A DEA-Based Method

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Xishuang Han ◽  
Xiaolong Xue ◽  
Jiaoju Ge ◽  
Hengqin Wu ◽  
Chang Su
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Data Envelopment Analysis ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Policy Makers ◽  
Time Periods ◽  
Decision Making Units

Data envelopment analysis can be applied to measure the productivity of multiple input and output decision-making units. In addition, the data envelopment analysis-based Malmquist productivity index can be used as a tool for measuring the productivity change during different time periods. In this paper, we use an input-oriented model to measure the energy consumption productivity change from 1999 to 2008 of fourteen industry sectors in China as decision-making units. The results show that there are only four sectors that experienced effective energy consumption throughout the whole reference period. It also shows that these sectors always lie on the efficiency frontier of energy consumption as benchmarks. The other ten sectors experienced inefficiency in some two-year time periods and the productivity changes were not steady. The data envelopment analysis-based Malmquist productivity index provides a good way to measure the energy consumption and can give China's policy makers the information to promote their strategy of sustainable development.

scholarly journals Measuring the Efficiency of Health Services Areas in Kingdom of Saudi Arabia Using Data Envelopment Analysis (DEA): A Comparative Study between the Years 2014 and 2006

2017 ◽  
Vol 9 (4) ◽  
pp. 172 ◽  
Author(s):  
Sanaa Mohamed Aly Helal ◽  
Haga Abdelrahman Elimam
Keyword(s):  
Saudi Arabia ◽  
Data Envelopment Analysis ◽  
Health Services ◽  
Production Efficiency ◽  
Data Envelopment ◽  
Kingdom Of Saudi Arabia ◽  
Average Production ◽  
Government Hospitals ◽  
The Government ◽  
Using Data

The study aimed to assess the efficiency of health services provided by the government hospitals in various districts of the Kingdom of Saudi Arabia. The number of beds at hospitals, doctors, nursing staff and paramedical categories were used as inputs for the model. The average productivity efficiency of government hospitals in the districts of the Kingdom of Saudi Arabia in 2014 was 92.3%; whereas, the average internal production efficiency of these districts in the provision of health services through their respective hospitals was 94.7%; and the average external productivity efficiency in the different cities of the districts in Kingdom of the Saudi Arabia was 97.5%. It has been found that the average overall productivity efficiency was 90.2%, concerning the relative efficiency indicators of government hospitals, which were based on the hospitals’ distribution of Saudi Arabian districts in 2006. An analysis of the indicator showed that the average production efficiency of the services provided (internally) by the districts of the Kingdom of Saudi Arabia was 94.7%, and that the average of the external production efficiency for such services was 95.4%. The Data Envelopment Analysis is a successful technique in measuring the performance efficiency of hospitals and it also assists to identify possible improvement and reduction in cost.

scholarly journals Analisis Efisiensi Relatif di Unit Pelaksana Teknis Badan Pengawas Obat dan Makanan Tahun 2019

2022 ◽  
Vol 6 (2) ◽  
Author(s):  
Pantri Widyastuti ◽  
Atik Nurwahyuni
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Mixed Method ◽  
Data Envelopment ◽  
Cross Sectional ◽  
Decision Making Unit

Tantangan pengawasan obat dan makanan mengharuskan Unit Pelaksana Teknis (UPT) BPOM bekerja optimal di tengah keterbatasan sumber daya. Analisis efisiensi relatif pada Unit Pelaksana Teknis BPOM tahun 2019 dilakukan bertujuan untuk perbaikan dalam perencanaan, penganggaran, dan kebijakan strategis BPOM dalam upaya peningkatan capaian kinerja pada masing-masing UPT. Perhitungan efisiensi relatif menggunakan metode DEA (Data envelopment Analysis). Penelitian ini menggunakan mixed method dengan desain penelitian cross sectional. Sampel penelitian adalah 31 UPT BPOM yang memenuhi syarat sebagai DMU (Decision Making Unit) dan menggunakan 3 input dan 4 output yang diuji dengan metode DEA. Terdapat 10 informan dalam analisis kualitatif untuk mengetahui strategi dalam pencapaian efisiensi UPT. Hasil dari analisis terdapat 15 UPT yang efisien dan 16 UPT yang tidak efisien. Hasil wawancara diketahui bahwa UPT yang efisien dan yang tidak efisien telah melaksanakan strategi efisiensi internal dengan baik. DEA merupakan analisis efisiensi relatif dengan konsep memaksimalkan rasio output dan input. Penggunaan model VRS (Variabel return to Scale) yang mempertimbangkan proses, diharapkan mengeliminasi kekurangan yang terdapat dalam perhitungan dengan DEA. Perhitungan DEA dilakukan secara mekanik, maka diperlukan pendalaman proses untuk menggali faktor efisiensi yang tidak didapatkan dari perhitungan DEA, terlebih untuk organisasi yang dalam prosesnya melibatkan faktor eksternal yang cukup besar.

scholarly journals The Efficiency of Waste Sector in Italy: An Application by Data Envelopment Analysis

2020 ◽  
Vol 24 (3) ◽  
pp. 225-238
Author(s):  
Massimo Gastaldi ◽  
Ginevra Virginia Lombardi ◽  
Agnese Rapposelli ◽  
Giulia Romano
Keyword(s):  
Data Envelopment Analysis ◽  
Environmental Performance ◽  
Returns To Scale ◽  
Sustainable Growth ◽  
Waste Reduction ◽  
Data Envelopment ◽  
Environmental Legislation ◽  
Dea Models ◽  
Developed Nations ◽  
Variable Returns To Scale

AbstractWith growing environmental legislation and mounting popular concern for the need to pursuing a sustainable growth, there has been an increasing recognition in developed nations of the importance of waste reduction, recycling and reuse maximization. This empirical study investigates both ecological and economic performances of urban waste systems in 78 major Italian towns for the years 2015 and 2016. To this purpose the study employs the non-parametric approach to efficiency measurement, represented by Data Envelopment Analysis (DEA) technique. More specifically, in the context of environmental performance we implement two output-oriented DEA models in order to consider both constant and variable returns to scale. In addition, we include an undesirable output – the total amount of waste collected – in the two models considered. The results show that there is variability among the municipalities analysed: Northern and Central major towns show higher efficiency scores than Southern and Islands ones.

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