scholarly journals Evaluation of Energy-Environment Efficiency of European Transport Sectors: Non-Radial DEA and TOPSIS Approach

Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 2907 ◽  
Author(s):  
Boban Djordjević ◽  
Evelin Krmac
Keyword(s):  
Joint Production ◽  
Transport Sector ◽  
Data Envelopment ◽  
Topsis Method ◽  
Dea Model ◽  
The Road ◽  
Energy Inputs ◽  
Energy Environment ◽  
Topsis Approach ◽  
Desirable And Undesirable Outputs

Transport is recognized as a major energy consumer and environment pollutant. Recently scholars have paid considerable attention to the evaluation of transport energy and environmental efficiency (EEE). In this paper, the non-radial Data Envelopment Analysis (DEA) model was employed to evaluate EEE on a macro level—i.e., of European road, rail and air sectors. The evaluation was conducted under the joint production framework, which considers energy and non-energy inputs, and desirable and undesirable outputs for the last ten years period. To rank decision-making units and check the aptness of this non-radial DEA model in transport EEE evaluation, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method has been proposed. An empirical study has been conducted for as many European countries as possible, depending on availability of data. Based on the non-radial DEA model, it could be said that the level of EEE is improving for the road sector, while many evaluated countries have low EEE for the rail transport sector. Additionally, results have indicated that the TOPSIS method is more suitable than the non-radial DEA model in transport EEE evaluation and for identification of best practices.

scholarly journals Recommending investment opportunities given congestion by adaptive network data envelopment analysis model: Assessing sustainability of supply chains

2019 ◽  
Author(s):  
Hossein Hajaji ◽  
Sara Yousefi ◽  
Reza Farzipoor Saen ◽  
Amir Hassanzadeh
Keyword(s):  
Data Envelopment Analysis ◽  
Supply Chains ◽  
Data Envelopment Analysis Model ◽  
Network Data ◽  
Data Envelopment ◽  
Analysis Model ◽  
Adaptive Network ◽  
Dea Model ◽  
Network Data Envelopment Analysis ◽  
Desirable And Undesirable Outputs

Nowadays, forward-thinking companies move beyond conventional structures of organizations and consider all parties of the supply chain. The objective of this paper is to present an adaptive network data envelopment analysis (DEA) model to evaluate overall and divisional efficiency of sustainable supply chains in the presence of desirable and undesirable outputs. Our adaptive network DEA model can assess overall and divisional efficiency of supply chains given managerial and natural disposability. Also, it suggests new investment opportunity given congestion type. A case study is presented.

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 How Will Digitalization Change Road Freight Transport? Scenarios Tested in Sweden

2020 ◽  
Vol 13 (1) ◽  
pp. 304
Author(s):  
Anna Pernestål ◽  
Albin Engholm ◽  
Marie Bemler ◽  
Gyözö Gidofalvi
Keyword(s):  
Freight Transport ◽  
Sustainable Transportation ◽  
Transport Sector ◽  
Strategic Uncertainty ◽  
Scenario Development ◽  
Service Levels ◽  
Urban Freight ◽  
The Road ◽  
Road Freight ◽  
On The Road

Road freight transport is a key function of modern societies. At the same time, road freight transport accounts for significant emissions. Digitalization, including automation, digitized information, and artificial intelligence, provide opportunities to improve efficiency, reduce costs, and increase service levels in road freight transport. Digitalization may also radically change the business ecosystem in the sector. In this paper, the question, “How will digitalization change the road freight transport landscape?” is addressed by developing four exploratory future scenarios, using Sweden as a case study. The results are based on input from 52 experts. For each of the four scenarios, the impacts on the road freight transport sector are investigated, and opportunities and barriers to achieving a sustainable transportation system in each of the scenarios are discussed. In all scenarios, an increase in vehicle kilometers traveled is predicted, and in three of the four scenarios, significant increases in recycling and urban freight flows are predicted. The scenario development process highlighted how there are important uncertainties in the development of the society that will be highly important for the development of the digitized freight transport landscape. One example is the sustainability paradigm, which was identified as a strategic uncertainty.

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 Validation of CO dispersion model due to the road position on the dominant wind direction on transport sector

2018 ◽  
Vol 197 ◽  
pp. 13017 ◽  
Author(s):  
Vera Surtia Bachtiar ◽  
Purnawan ◽  
Reri Afrianita ◽  
Randa Anugerah
Keyword(s):  
Wind Direction ◽  
Dispersion Model ◽  
Transport Sector ◽  
The Road ◽  
Validation Test ◽  
Traffic Characteristics ◽  
Significant Difference ◽  
Co Concentration ◽  
On The Road ◽  
Co Dispersion

This study aims to validate CO dispersion model due to the position of the road toward the dominant wind direction on the transport sector. Sampling for modelling was done on the road with the road angle to wind direction is 0 degree (Jend. A. Yani Road), 30 degree (Andalas Road) and 60 degree (Prof. Dr. Hamka Road). CO dispersion model was obtained from the relations between CO concentration with traffic volume, traffic speed, wind speed and dominant wind direction. Sampling for validation was done at three location points, i.e. Jend. Ahmad Yani Road, By Pass Road and Dr. Wahidin Road, each of which has a position of 0, 45 and 90 degrees toward dominant wind direction. Sampling for CO was done using impinger. Measurement of traffic characteristics and meteorological conditions was performed in conjunction with CO sampling. Validation test was done by using Pearson Product Moment formula and Test of Two Variance. Results of the Two-Variance Test showed no significant difference between two concentrations of CO model and CO measurement. It showed the Test Ratio (RUf) smaller than the Critical Point. Validation test using Pearson Product Moment showed that the CO model can be used for predicting CO dispersion.

scholarly journals HIV-targeted health promotion: Can we learn from the experience in Tanzania?

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
M Gross
Keyword(s):  
Health Promotion ◽  
Migrant Workers ◽  
Road Construction ◽  
Hiv And Aids ◽  
Construction Workers ◽  
Sub Saharan Africa ◽  
Basic Knowledge ◽  
Transport Sector ◽  
The Road ◽  
Road Project

Abstract The overall rise in deaths from preventable communicable diseases in the African Region is of utmost concern from a public health perspective. Sub-Saharan Africa (SSA) is home to a severe generalized HIV epidemic with the value of targeted health promotion only recently gaining momentum. The transport sector and transport corridors represent a major transmission route for HIV, fueled by unemployment, multiple sexual partnerships, gender-based violence (GBV), migrant workers and poor access to quality health information and services. In Tanzania, targeted sensitization and health promotion interventions spanning two major road corridors and their large-scale construction projects led to improved knowledge and behavior change among the road construction workers, community leaders and local residents in the communities along the road project as measured during a baseline and end line survey. Taking a comprehensive approach to health promotion the road project in Tanzania focused on: Educational and behavioral change campaigns, aimed via road shows at creating awareness on HIV and AIDS, STI, TB and GBV and encouraged people to know their sero status at mobile outlets of the HIV Counselling and Testing Services (HTS) during community bonanzas, featuring edutainment.Training peer educators from communities and road construction workers on basic knowledge and communication skills to transfer information along the roads, within the communities and in the nearby schools.Establishing village multi-sectoral HIV/AIDS committees.Development of SBCC materials with targeted messages to road construction workers and community members, developed jointly with multiple stakeholders.HIV Testing Services in collaboration with districts and health facilities along the roads.Capacity development of health workers and relevant stakeholders. Lessons learnt can provide guidance for similar settings in SSA and stimulate also a fresh view on promotive activities in Europe.

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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