Interval enhanced Russell measure with undesirable outputs based on data envelopment analysis: An efficiency measurement of industry in China

2021 ◽  
Vol 40 (1) ◽  
pp. 103-115
Author(s):  
Xu Wang ◽  
Ying-Ming Wang
Keyword(s):  
Industrial Development ◽  
Efficiency Measurement ◽  
Decision Makers ◽  
Data Envelopment ◽  
Fuzzy Data ◽  
Undesirable Outputs ◽  
Undesirable Output ◽  
The World ◽  
Chinese Industry ◽  
Complex Production System

China has attracted the attention of the world owing its significant economic achievements, which are supported significantly by its booming industry. However, the issues of energy and pollutants have severely challenged the sustainability of the industry. The efficiency measurement is the premise intended to realize sustainability within the Chinese industry. Because the industry is a complex production system, there exists uncertainties and fuzziness regarding its inputs and outputs. This study proposes the application of an interval to describe these fuzzy data and employ the Enhanced Russell Measure to assess the performance of the Chinese industry, accounting for undesirable output such as pollution. In addition, for the ranking between interval efficiencies, a novel ranking approach based on the holistic acceptability of a possibility degree is proposed. The proposed method provides advice and guidance for decision makers to make appropriate and effective policies to balance industrial development and environmental protection in spite of uncertain and fuzzy data.

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.

A common-weights approach for efficiency evaluation in fuzzy data envelopment analysis with undesirable outputs: Application in banking industry

2020 ◽  
Vol 39 (5) ◽  
pp. 7705-7722
Author(s):  
Mohammad Kachouei ◽  
Ali Ebrahimnejad ◽  
Hadi Bagherzadeh-Valami
Keyword(s):  
Data Envelopment Analysis ◽  
Performance Management ◽  
Banking Industry ◽  
Evaluation Process ◽  
Fuzzy Arithmetic ◽  
Data Envelopment ◽  
Fuzzy Data ◽  
Undesirable Outputs ◽  
Dea Model ◽  
The Impact

Data Envelopment Analysis (DEA) is a non-parametric approach based on linear programming for evaluating the performance of decision making units (DMUs) with multiple inputs and multiple outputs. The lack of the ability to generate the actual weights, not considering the impact of undesirable outputs in the evaluation process and the measuring of efficiencies of DMUs based upon precise observations are three main drawbacks of the conventional DEA models. This paper proposes a novel approach for finding the common set of weights (CSW) to compute efficiencies in DEA model with undesirable outputs when the data are represented by fuzzy numbers. The proposed approach is based on fuzzy arithmetic which formulates the fuzzy additive DEA model as a linear programing problem and gives fuzzy efficiencies of all DMUs based on resulting CSW. We demonstrate the applicability of the proposed model with a simple numerical example. Finally, in the context of performance management, an application of banking industry in Iran is presented for analyzing the influence of fuzzy data and depicting the impact of undesirable outputs over the efficiency results.

Evaluation of Supply Chain Efficiency Based on a Novel Network of Data Envelopment Analysis Model

2015 ◽  
Vol 25 (14) ◽  
pp. 1540036 ◽  
Author(s):  
Li Fang Fu ◽  
Jun Meng ◽  
Ying Liu
Keyword(s):  
Supply Chain ◽  
Data Envelopment Analysis ◽  
Decision Makers ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Analysis Model ◽  
Multilayer Network ◽  
Supply Chain Efficiency ◽  
Proposed Model

Performance evaluation of supply chain (SC) is a vital topic in SC management and inherently complex problems with multilayered internal linkages and activities of multiple entities. Recently, various Network Data Envelopment Analysis (NDEA) models, which opened the “black box” of conventional DEA, were developed and applied to evaluate the complex SC with a multilayer network structure. However, most of them are input or output oriented models which cannot take into consideration the nonproportional changes of inputs and outputs simultaneously. This paper extends the Slack-based measure (SBM) model to a nonradial, nonoriented network model named as U-NSBM with the presence of undesirable outputs in the SC. A numerical example is presented to demonstrate the applicability of the model in quantifying the efficiency and ranking the supply chain performance. By comparing with the CCR and U-SBM models, it is shown that the proposed model has higher distinguishing ability and gives feasible solution in the presence of undesirable outputs. Meanwhile, it provides more insights for decision makers about the source of inefficiency as well as the guidance to improve the SC performance.

DEA based production planning considering technology heterogeneity with undesirable outputs

2020 ◽  
Vol 54 (2) ◽  
pp. 325-339
Author(s):  
Changyong Liang ◽  
Binyou Wang ◽  
Tao Ding ◽  
Yinchao Ma
Keyword(s):  
Data Envelopment Analysis ◽  
Production Planning ◽  
Industrial Development ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Planning Approach ◽  
Technology Heterogeneity ◽  
Using Data ◽  
Planning Problems ◽  
Decision Making Units

Many researchers have concentrated on production planning issues by using data envelopment analysis (DEA). However, the assumption made by existing approaches that all decision making units (DMUs) are equipped with the same level of production technology is not realistic. Additionally, with the development in the society, environmental factors have come to play important roles in the production process as well. Thus, undesirable outputs should be considered in production planning problems. Therefore, this paper considers the technology heterogeneity factors and undesirable outputs using the data envelopment analysis-based production planning approach. Two examples containing a numerical example that compare with other method and a real sample that concerns the industrial development of 30 provinces in China are used to validate the applicability of our approach.

Slacks-Based Efficiency Measurements with Undesirable Outputs in Data Envelopment Analysis

2014 ◽  
Vol 16 (04) ◽  
pp. 1005-1021 ◽  
Author(s):  
Jie Wu ◽  
Xiang Lu ◽  
Dong Guo ◽  
Liang Liang
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Production Process ◽  
Environmental Performance ◽  
Decision Makers ◽  
European Countries ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Theoretical Justification ◽  
Decision Making Units

Data envelopment analysis (DEA) has recently gained great popularity in modeling environmental performance because it provides condensed information to decision makers when the production process includes undesirable outputs. In this paper, we develop a new slacks-based efficiency measurement for modeling environmental performance using the environmental DEA technology. The proposed index has more theoretical justification, and distinguishes among different decision making units (DMUs) better in practice. Then we further extend it to the nonoriented index with double aim of increasing desirable outputs and reducing undesirable outputs. Finally, we calculate the index for each of 25 OECD European countries in a model of CO2 emission performance from 2007 to 2009 and the results obtained are presented.

scholarly journals Estimating Relative Efficiency of Electricity Consumption in 42 Countries during the Period of 2008–2017

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3037 ◽  
Author(s):  
Chia-Nan Wang ◽  
Quoc-Chien Luu ◽  
Thi-Kim-Lien Nguyen
Keyword(s):  
Relative Efficiency ◽  
Human Life ◽  
Electricity Consumption ◽  
Electrical Equipment ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
The World ◽  
Desirable Output ◽  
Output Factors ◽  
Carbon Dioxide Co2

Augmentation of electrical equipment is pushing for an increase in energy supply sources all over the world, as electricity consumption (EC) typically rises with growing populations. The value of EC reveals economic development and degree of emissions. Therefore, this research uses the undesirable outputs model in data envelopment analysis (DEA) for estimating relative efficiency of electricity consumption in 42 countries from 2008 to 2017. According to the principle of an undesirable outputs model and studied objectives, variables are selected that included population and EC as inputs, gross domestic product (GDP) as desirable output, and carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) as undesirable outputs. The empirical results indicate that 420 terms of 42 countries during the period of 2008–2017 have 102 efficient and 310 inefficient terms. Moreover, the interplay level between input and output factors every year is presented via scores. The study suggests the effect of EC to human life and propounds the emission status to look for directions to overcome inefficient terms.

Ranking of DMUs Based on Efficiency Intervals

2011 ◽  
Vol 15 (1) ◽  
pp. 63-67
Author(s):  
Tomoe Entani ◽  
Keyword(s):  
Order Relation ◽  
Interval Data ◽  
Efficiency Measurement ◽  
Decision Makers ◽  
Data Envelopment ◽  
Partial Order Relation ◽  
Output Data ◽  
Decision Making Unit ◽  
The Difference ◽  
Analysis Interval

The efficiency of the Interval Data Envelopment Analysis (Interval DEA), we proposed, obtains its bounds from optimistic and pessimistic viewpoints. Intervals represent the uncertainty of given input-output data and the intuitive evaluation of decision makers. The partial order relation that intervals give elements may be complex, especially when elements are numerous. The efficiency measurement we propose combining optimistic and pessimistic efficiency in Interval DEA is comparable because both represent the difference of the analyzed Decision Making Unit (DMU) from the most efficient one. The efficiency measurement is defined as their minimum and determined mainly by pessimistic efficiency. Optimistic efficiency is considered if it is inadequate compared to pessimistic efficiency. Pessimistic efficiency based evaluation resembles natural evaluation and DMUs are arranged linearly.

Green-Efficiency Assessment of Chinese Industry Based on Principal Component Analysis and Super-Efficiency Data Envelopment Analysis

2012 ◽  
Vol 490-495 ◽  
pp. 2264-2268 ◽  
Author(s):  
Rui Jie Liu ◽  
Zhi Hui Zhang
Keyword(s):  
Principal Component Analysis ◽  
Data Envelopment Analysis ◽  
Industrial Development ◽  
Principal Component ◽  
Component Analysis ◽  
Data Envelopment ◽  
Super Efficiency ◽  
Chinese Industry ◽  
Year 2000 ◽  
Efficiency Data

Industry is playing an important role in national economy, the efficiency and developing trend of which is widely being paid attention to. However, severe environmental problems always emerge along with rapid industrial development at the same time. Based on the method integrating Principal Component Analysis and Super-efficiency Data Envelopment Analysis, this article introduces environmental factors into the system to evaluate Chinese industrial green-efficiency of year 2000~2008, indicating the current major problems which hinder coordinated economic-environmental development of Chinese industry, and putting forward the improving direction.

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