scholarly journals A novel Best Worst Method Robust Data Envelopment Analysis: Incorporating Decision Makers’ preferences in an uncertain environment

2021 ◽  
pp. 100184
Author(s):  
Hashem Omrani ◽  
Mahsa Valipour ◽  
Ali Emrouznejad
Keyword(s):  
Data Envelopment Analysis ◽  
Decision Makers ◽  
Data Envelopment ◽  
Uncertain Environment ◽  
Best Worst Method

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.

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.

Measuring the operational and financial efficiency using a Malmquist data envelopment analysis: a case of Egyptian hospitals

2020 ◽  
Vol 27 (9) ◽  
pp. 2521-2536
Author(s):  
Ahmed Mohamed Habib ◽  
Tamer Mohamed Shahwan
Keyword(s):  
Data Envelopment Analysis ◽  
The United States ◽  
Decision Makers ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Mena Region ◽  
Financial Efficiency ◽  
Content Type ◽  
Factors Affecting ◽  
Dea Approach

PurposeThe efficient use of organizational resources is integral to the existence of prime firms. This study, using Malmquist data envelopment analysis (DEA), aims to assess in the level of operational and financial efficiency and its determinants for ensuring and sustaining excellent performance in 33 Egyptian private hospitals.Design/methodology/approachThis study adopted a Malmquist DEA approach to assess the changes in operational and financial efficiency in Egyptian hospitals. Tobit regression was also used to identify the significant variables affecting their efficiency. In addition, a sensitivity analysis is carried out for model validations.FindingsOut of 33 hospitals, 17 were found inefficient due to the decline in their technical efficiency. Moreover, the total value of the software programs and operational expenses and the total number of employees are common factors affecting both operational and financial efficiency. In addition, the number of physicians significantly affects the hospital's financial efficiency.Practical implicationsThe study sheds light on the value of using DEA to assess efficiency. DEA in the context of emerging economy such as Egypt's can be a useful tool for decision-makers and practitioners in identifying and addressing performance weaknesses and thus supports continuous improvement in performance.Originality/valueSeveral studies have adopted the DEA approach to assess the overall efficiency of hospitals in Europe and the United States. However, in the MENA region, these studies are uncommon. This study is thought to be one of the earliest attempts to assess hospitals' efficiency in Egypt.

Comparing Data Envelopment Analysis and Human Decision Making Unit Rankings: A Survey Approach

2014 ◽  
Vol 29 (2) ◽  
Author(s):  
Stanko Dimitrov
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Decision Makers ◽  
Data Envelopment ◽  
Rank Ordering ◽  
Decision Making Unit ◽  
Human Decision ◽  
Survey Approach ◽  
Decision Making Units ◽  
Better Than

AbstractIn this paper we compare the ordinal rankings generated through Data Envelopment Analysis (DEA) methods to ordinal rankings generated by human decision makers. Through eliciting the total rank ordering for approximately 100 individuals on all of the four different datasets of Decision Making Units (DMUs), we compare the rankings generated by individuals to those generated by ten DEA methods. We observe that depending on the characteristics of the dataset one of the DEA methods performs better than the others in matching human decision makers.

Using Data Envelopment Analysis for Green Supplier Selection in Manufacturing under Vague Environment

2012 ◽  
Vol 622-623 ◽  
pp. 1682-1685 ◽  
Author(s):  
Atefeh Amindoust ◽  
Ahmed Shamsuddin ◽  
Ali Saghafinia
Keyword(s):  
Data Envelopment Analysis ◽  
Supplier Selection ◽  
Decision Makers ◽  
Central Component ◽  
Data Envelopment ◽  
Linguistic Terms ◽  
Green Supplier Selection ◽  
Growth Of Knowledge ◽  
Using Data

In these days, considering the growth of knowledge about environmental protection and green issues in manufacturing, green supplier selection would be the central component in the management of supply chain. This paper intends to apply data envelopment analysis for supplier selection considering environmental merits. The suppliers’ performances with respect to criteria are not pure numbers and considered in linguistic terms according to decision makers’ opinion. To handle the subjectivity of decision makers’ assessments, fuzzy logic has been applied. A case study is done to present the application of the method.

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 The DEA and Intuitionistic Fuzzy TOPSIS Approach to Departments' Performances: A Pilot Study

2011 ◽  
Vol 2011 ◽  
pp. 1-16 ◽  
Author(s):  
Babak Daneshvar Rouyendegh
Keyword(s):  
Data Envelopment Analysis ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Classification Model ◽  
Data Envelopment ◽  
Alternative Evaluation ◽  
Intuitionistic Fuzzy ◽  
Evaluation Problem ◽  
Topsis Approach ◽  
Intuitionistic Fuzzy Topsis

This paper processes a unification of Fuzzy TOPSIS and Data Envelopment Analysis (DEA) to select the units with most efficiency. This research is a two-stage model designed to fully rank the organizational alternatives, where each alternative has multiple inputs and outputs. First, the alternative evaluation problem is formulated by Data Envelopment Analysis (DEA) and separately formulates each pair of units. In the second stage, we use the opinion of experts to be applied into a model of group Decision-Making (DM) called the Intuitionistic Fuzzy TOPSIS (IFT) method. The results of both methods are then multiplied to obtain the results. DEA and Intuitionistic Fuzzy TOPSIS ranking do not replace the DEA classification model; rather, it furthers the analysis by providing full ranking in the DEA context for all units by aggregate individual opinions of decision makers for rating the importance of criteria and alternatives.

scholarly journals APPLICATION OF STEPWISE DATA ENVELOPMENT ANALYSIS AND GREY INCIDENCE ANALYSIS TO EVALUATE THE EFFECTIVENESS OF EXPORT PROMOTION PROGRAMS

2013 ◽  
Vol 14 (3) ◽  
pp. 638-650 ◽  
Author(s):  
Seyed Hossein Razavi Hajiagha ◽  
Edmundas Kazimieras Zavadskas ◽  
Shide Sadat Hashemi
Keyword(s):  
Resource Allocation ◽  
Data Envelopment Analysis ◽  
International Markets ◽  
Export Promotion ◽  
Decision Makers ◽  
The Other ◽  
Data Envelopment ◽  
Different Types ◽  
Grey Incidence Analysis ◽  
Incidence Analysis

Export promotion programs are incentives to increase the participation of companies in international markets. On the other hand, governments try to help exporting companies with developing their goal markets. Therefore, for this purpose, many different programs have been created. To show the effectiveness of these programs, the paper refers to stepwise DEA and grey incidence analysis. Finally, the article determines a unified ranking of the applied programs that can be used by decision makers for resource allocation considering different types of programs based on their effectiveness.

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