scholarly journals Eco-Efficiency Analysis for the Russian Cities along the Northern Sea Route: A Data Envelopment Analysis Approach Using an Epsilon-Based Measure Model

2021 ◽  
Vol 18 (11) ◽  
pp. 6097
Author(s):  
Shuaiyu Yao ◽  
Mengmeng Chen ◽  
Dmitri Muravev ◽  
Wendi Ouyang
Keyword(s):  
Data Envelopment Analysis ◽  
Public Investment ◽  
Ghg Emissions ◽  
Real Data ◽  
Efficiency Analysis ◽  
Measure Data ◽  
Data Envelopment ◽  
Dea Model ◽  
Northern Sea Route ◽  
Regional Product

In this paper, an eco-efficiency analysis is conducted using the epsilon-based measure data envelopment analysis (EBM-DEA) model for Russian cities along the Northern Sea Route (NSR). The EBM-DEA model includes five input variables: population, capital, public investment, water supply, and energy supply and four output variables: gross regional product (GRP), greenhouse gas (GHG) emissions, solid waste, and water pollution. The pattern of eco-efficiency of 28 Russian cities along the NSR is empirically analyzed based on the associated real data across the years from 2010 to 2019. The empirical results obtained from the analysis show that St. Petersburg, Provideniya, Nadym, N. Urengoy, and Noyabrsk are eco-efficient throughout the 10 years. The results also indicate that the cities along the central section of the NSR are generally more eco-efficient than those along other sections, and the cities with higher level of GRPs per capita have relatively higher eco-efficiency with a few exceptions. The study provides deeper insights into the causes of disparity in eco-efficiency, and gives further implications on eco-efficiency improvement strategies. The contributions of this study lie in the fact that new variables are taken into account and new modeling techniques are employed for the assessment of the eco-efficiency of the Russian cities.

Webinar Analisis Efisiensi Perusahaan Dengan DEA

2021 ◽  
Vol 1 (02) ◽  
pp. 80-87
Author(s):  
JMV Mulyadi
Keyword(s):  
Data Envelopment Analysis ◽  
Efficiency Analysis ◽  
Analysis Tool ◽  
Data Envelopment ◽  
Dea Model ◽  
Dea Method ◽  
A Company

Abstrak        Tujuan pelatihan ini adalah menjelaskan metode Data Envelopment Analyisis (DEA) sebagai alat analisis efisiensi perusahaan. Penjelasan mencakup pengertian, manfaat, mekanisme, formulasi model DEA dan penggunaan Software Banxia Frotier Analist dan MaxDEA. Pelatihan dilakukan dengan Webinar Nasional  yang dilaksanakan atas kerjasama Sekolah Pascasarjana Universitas Pancasila dengan Muhammadiyah Ranting Mampang Kota Depok. Hasilnya menunjukkan bahwa metode DEA sangat bermanfaat dan jika dimungkinkan waktunya ditambah dan diperdalam dengan contoh-contoh. Implikasi akademisnya peserta membuat tutorial youtube bagaimana mengoperasikan software Banxia Frontier Analist dan dapat membantu mahasiswa dalam menyusun tesis.  Kata Kunci: data envelopment analysis, efisiensi, banxia frontier analist,        maxdea.   Abstract        The purpose of this training is to explain the Data Envelopment Analysis (DEA) method as a company efficiency analysis tool. The explanation includes the meaning, benefits, mechanisms, formulation of the DEA model and the use of the Banxia Frotier Analist and MaxDEA Software. The training was carried out with a National Webinar which was held in collaboration with the Postgraduate School of Pancasila University and the Muhammadiyah Branch of Mampang Depok City. The results show that the DEA method is very useful and if possible the time is added and deepened with examples. The academic implication is that the participants make a youtube tutorial on how to operate the Banxia Frontier Analist software and can help students in preparing a thesis. Keywords: data envelopment analysis, efficiency, banxia frontier analist, maxdea.

scholarly journals Long-Term Economic Sustainability of Humanitarian Logistics—A Multi-Level and Time-Series Data Envelopment Analysis

2021 ◽  
Vol 18 (5) ◽  
pp. 2219
Author(s):  
Matthias Klumpp ◽  
Dominic Loske
Keyword(s):  
Data Envelopment Analysis ◽  
Time Series Data ◽  
Malmquist Index ◽  
Developed Countries ◽  
Efficiency Analysis ◽  
Humanitarian Logistics ◽  
Series Data ◽  
Data Envelopment ◽  
Least Developed Countries ◽  
Window Analysis

Although resources are scarce and outputs incorporate the potential to save human lives, efficiency measurement endeavors with data envelopment analysis (DEA) methods are not yet commonplace in the research and practice of non-government organizations (NGO) and states involved in humanitarian logistics. We present a boot-strapped DEA window analysis and Malmquist index application as a methodological state of the art for a multi-input and multi-output efficiency analysis and discuss specific adaptions to typical core challenges in humanitarian logistics. A characteristic feature of humanitarian operations is the fact that a multitude of organizations are involved on at least two levels, national and supra-national, as well as in two sectors, private NGO and government agencies. This is modeled and implemented in an international empirical analysis: First, a comprehensive dataset from the 34 least developed countries in Africa from 2002 to 2015 is applied for the first time in such a DEA Malmquist index efficiency analysis setting regarding the national state actor level. Second, an analysis of different sections in a Rohingya refugee camp in Bangladesh is analyzed based on a bootstrapped DEA with window analysis application for 2017, 2018, and 2019 quarter data regarding the private NGO level of operations in humanitarian logistics.

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.

scholarly journals A Range Adjusted Measure of Super-Efficiency in Integer-Valued Data Envelopment Analysis with Undesirable Outputs

2021 ◽  
Vol 9 (4) ◽  
pp. 378-398
Author(s):  
Chunhua Chen ◽  
Haohua Liu ◽  
Lijun Tang ◽  
Jianwei Ren
Keyword(s):  
Data Envelopment Analysis ◽  
Transportation Systems ◽  
Decision Makers ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Super Efficiency ◽  
Dea Model ◽  
Dea Models ◽  
Analysis Models ◽  
Transport Accidents

Abstract DEA (data envelopment analysis) models can be divided into two groups: Radial DEA and non-radial DEA, and the latter has higher discriminatory power than the former. The range adjusted measure (RAM) is an effective and widely used non-radial DEA approach. However, to the best of our knowledge, there is no literature on the integer-valued super-efficiency RAM-DEA model, especially when undesirable outputs are included. We first propose an integer-valued RAM-DEA model with undesirable outputs and then extend this model to an integer-valued super-efficiency RAM-DEA model with undesirable outputs. Compared with other DEA models, the two novel models have many advantages: 1) They are non-oriented and non-radial DEA models, which enable decision makers to simultaneously and non-proportionally improve inputs and outputs; 2) They can handle integer-valued variables and undesirable outputs, so the results obtained are more reliable; 3) The results can be easily obtained as it is based on linear programming; 4) The integer-valued super-efficiency RAM-DEA model with undesirable outputs can be used to accurately rank efficient DMUs. The proposed models are applied to evaluate the efficiency of China’s regional transportation systems (RTSs) considering the number of transport accidents (an undesirable output). The results help decision makers improve the performance of inefficient RTSs and analyze the strengths of efficient RTSs.

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