Performance evaluation of general network production processes with undesirable outputs: A DEA approach

2018 ◽  
Vol 52 (1) ◽  
pp. 17-34 ◽  
Author(s):  
Amir Kalhor ◽  
Reza Kazemi Matin
Keyword(s):  
Performance Evaluation ◽  
Production Systems ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Network Dea ◽  
Production Processes ◽  
Real World Applications ◽  
Dea Models ◽  
General Network ◽  
Literature Production

Performance evaluation of production systems with network structure has been widely studied in recent data envelopment analysis (DEA) literature. Production systems in which outputs of some stages are consumed as the inputs of some other stages in producing final outputs. In real world applications, production processes are often complex and may produce not only desirable but also undesirable intermediate or final outputs. In this paper modelling a general network DEA is considered in the presence of undesirable outputs. A weak disposable production set consistent with undesirable outputs is introduced and some network DEA models are also proposed for performance evaluation of the production units. The proposed method is illustrated by some numerical example, including an empirical application.

scholarly journals Efficiency Bounds for Two-Stage Production Systems

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Xiao Shi
Keyword(s):  
Production Systems ◽  
Efficiency Score ◽  
Insurance Companies ◽  
Practical Case ◽  
Data Envelopment ◽  
Production Structure ◽  
Two Stage ◽  
Decision Making Unit ◽  
Real World Applications ◽  
Dea Models

Traditional data envelopment analysis (DEA) models find the most desirable weights for each decision-making unit (DMU) in order to estimate the highest efficiency score as possible. These efficiency scores are then used for ranking the DMUs. The main drawback is that the efficiency scores based on weights obtained from the standard DEA models ignore other feasible weights; this is due to the fact that DEA may have multiple solutions for each DMU. To overcome this problem, Salo and Punkka (2011) deemed each DMU as a “Black Box” and developed models to obtain the efficiency bounds for each DMU over sets of all its feasible weights. In many real world applications, there are DMUs that have a two-stage production system. In this paper, we extend the Salo and Punkka’s (2011) model to a more common and practical case considering the two-stage production structure. The proposed approach calculates each DMU’s efficiency bounds for the overall system as well as efficiency bounds for each subsystem/substage. An application for nonlife insurance companies has been discussed to illustrate the applicability of the proposed approach and show the usefulness of this method.

scholarly journals A Neutrosophic-Based Approach in Data Envelopment Analysis with Undesirable Outputs

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Xinna Mao ◽  
Zhao Guoxi ◽  
Mohammad Fallah ◽  
S. A. Edalatpanah
Keyword(s):  
Data Envelopment Analysis ◽  
Manufacturing System ◽  
Aggregation Operator ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Simple Construction ◽  
Mathematical Methods ◽  
Reliable Measurement ◽  
Real World Applications ◽  
Dea Models

Data Envelopment Analysis is one of the paramount mathematical methods to compute the general performance of organizations, which utilizes similar sources to produce similar outputs. Original DEA schemes involve crisp information of inputs and outputs that may not always be accessible in real-world applications. Nevertheless, in some cases, the values of the data are information with indeterminacy, impreciseness, vagueness, inconsistent, and incompleteness. Furthermore, the conventional DEA models have been originally formulated solely for desirable outputs. However, undesirable outputs may additionally be present in the manufacturing system, which wishes to be minimized. To tackle the mentioned issues and in order to obtain a reliable measurement that keeps original advantage of DEA and considers the influence of undesirable factors under the indeterminate environments, this paper presents a neutrosophic DEA model with undesirable outputs. The recommended technique is based on the aggregation operator and has a simple construction. Finally, an example is given to illustrate the new model and ranking approach in details.

Economies of scope in two-stage production systems: A data envelopment analysis approach

2018 ◽  
Vol 52 (2) ◽  
pp. 335-349 ◽  
Author(s):  
Leila Zeinalzadeh Ahranjani ◽  
Reza Kazemi Matin ◽  
Reza Farzipoor Saen
Keyword(s):  
Data Envelopment Analysis ◽  
Production Systems ◽  
Efficiency Score ◽  
Joint Production ◽  
Economies Of Scope ◽  
Data Envelopment ◽  
Two Stage ◽  
Network Dea ◽  
Second Stage ◽  
Dea Models

Traditional data envelopment analysis (DEA) models consider a production system as a black-box without taking into consideration its internal linked activities. In recent years, a number of DEA studies have been presented to estimate efficiency score of two-stage network production systems in which all outputs of the first stage (intermediate products) are used as inputs of the second stage to produce final outputs. This paper aims to develop a two-stage network DEA model to study economic notion of economies of scope (ES) between two products. It intends to determine profitability of joint production of two products by one firm. Numerical illustrations are presented to show applicability of proposed methods.

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.

scholarly journals Performance analysis in the presence of bounded, discrete and flexible measures_

2021 ◽  
Vol 31 (3) ◽  
Author(s):  
Sohrab Kordrostami ◽  
Monireh Jahani Sayyad Noveiri
Keyword(s):  
Relative Efficiency ◽  
Data Envelopment ◽  
Highway Maintenance ◽  
Real World Applications ◽  
The Status ◽  
Dea Models ◽  
Discrete Values ◽  
Flexible Measure ◽  
The Individual ◽  
University Performance

In conventional data envelopment analysis (DEA) models, the relative efficiency of decision making units (DMUs) is evaluated while all measures with certain input and/or output status are considered as continuous data without upper and/or lower bounds. However, there are occasions in real-world applications that the efficiency of firms must be assessed while bounded elements, discrete values, and flexible measures are present. For this purpose, the current study proposes DEA-based approaches to estimate the relative efficiency of DMUs where bounded factors, integer values, and flexible measures exist. To illustrate it, radial models based on two aspects, individual and aggregate, are introduced to measure the performance of entities and to handle the status of the flexible measure such that there are bounded components and discrete data. Applications of approaches proposed in the areas of quality management, highway maintenance patrols, and university performance measurement are given to clarify the issue and to show their practicability. It was found that the introduced procedure can determine practical projection points for bounded measures and integer values (from the individual DMU viewpoint) and can classify flexible measures along with evaluation of DMUs relative efficiency.

scholarly journals Centralized resource allocation with the possibility of downsizing in two-stage network production systems

2021 ◽  
Author(s):  
Amir Hossein Yadollahi ◽  
Reza Kazemi Matin
Keyword(s):  
Resource Allocation ◽  
Resource Constraints ◽  
Production Systems ◽  
Data Envelopment ◽  
Two Stage ◽  
New Approach ◽  
Organizational Perspective ◽  
Dea Models ◽  
Common Resource ◽  
Component Processes

The network data envelopment analysis (NDEA) technique has been recently developed to measure the relative efficiency of complex production systems. NDEA models provide more meaningful and informative results in comparison to the conventional black-box DEA approach that ignores the operations of the component processes. Regarding the centralized decision-making systems, normal management imposes common resource constraints to maximize produced outputs and minimize consumed inputs. The present study seeks to introduce new centralized resource allocation models in two-stage network production systems. This intra-organizational perspective also provides the possibility of closing down some of the existing units to improve system efficiency. To do so, three scenarios of centralized DEA models are introduced to take advantage of this possibility. A simple numerical example is used for illustration purposes. An empirical application of the proposed approach to the twenty branches of a university is also presented to show the applicability of the new approach.

A slacks-based measure approach for efficiency decomposition in multi-period two-stage systems

2020 ◽  
Vol 54 (6) ◽  
pp. 1657-1671
Author(s):  
Samaneh Esfidani ◽  
Farhad Hosseinzadeh Lotfi ◽  
Shabnam Razavyan ◽  
Ali Ebrahimnejad
Keyword(s):  
Production Systems ◽  
Weighted Average ◽  
Real Data ◽  
Stage Structure ◽  
Data Envelopment ◽  
Two Stage ◽  
Bank Branches ◽  
Proposed Model ◽  
Efficiency Decomposition ◽  
Dea Models

Two-stage production systems are often encountered in many real applications where the production process is divided into two processes. In contrast to the conventional data envelopment analysis (DEA) models, two-stage DEA models take the operations of the internal processes into account. A number of studies have used two-stage DEA models in order to evaluate the performance of decision making units (DMUs) having a network structure. In this paper, we use a non-radial DEA model called the network slacks-based measure (NSBM) model to measure the efficiency of a system with a multi-period two-stage structure. Then we describe the properties of the proposed model in details. Moreover, we shall decompose the overall efficiency of the system over a number of time periods as a weighted average of the efficiency in each period. The efficiency of the stages, in respect to the entire periods shall be decomposed in terms of the weighted average efficiency of the stages in each period. Finally, the real data of Mellat bank branches in Tehran extracted from extant literature is used to illustrate the proposed approach.

scholarly journals A Review of Data Envelopment Analysis in Airline Efficiency: State of the Art and Prospects

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Qiang Cui ◽  
Li-Ting Yu
Keyword(s):  
Data Envelopment Analysis ◽  
Rapid Development ◽  
Aviation Industry ◽  
Future Research ◽  
Data Envelopment ◽  
Social Concern ◽  
Network Dea ◽  
Advantages And Disadvantages ◽  
Dea Models ◽  
Future Research Directions

The rapid development of the aviation industry has brought about the deterioration of the climate, which makes airline efficiency become a hot issue of social concern. As an important nonparametric method, Data Envelopment Analysis (DEA), has been widely applied in efficiency evaluation. This paper examines 130 papers published in the period of 1993–2020 to summarize the literature involving the special application of DEA models in airline efficiency. The paper begins with an overall review of the existing literature, and then the radial DEA, nonradial DEA, network DEA, dynamic DEA, and DEA models with undesirable outputs applied in airline efficiency are introduced. The main advantages and disadvantages of the above models are summarized, and the drivers of airline efficiency are analyzed. Finally, the literature review ends up with future research directions and conclusions.

scholarly journals Group ranking of two-stage production units in network data envelopment analysis

2021 ◽  
Author(s):  
Mohammad Sajjad Shahbazifar ◽  
Reza Kazemi Matin ◽  
Mohsen Khounsiavash ◽  
Fereshteh Koushki
Keyword(s):  
Data Envelopment Analysis ◽  
Group Performance ◽  
Production Systems ◽  
Performance Criteria ◽  
Data Envelopment ◽  
Mathematical Tool ◽  
Two Stage ◽  
Group Ranking ◽  
Group Efficiency ◽  
Dea Models

Data envelopment analysis (DEA) is a useful mathematical tool for evaluating the performance of production units and ranking their relative efficiency. In many real-world applications, production units belong to several separate groups and also consist of several sub-units. In this paper, we introduce a new method of evaluating group efficiency of two-stage production systems. To this end, some new DEA models are introduced for evaluating and ranking groups of production systems based on the average and weakest group performance criteria. Some numerical examples, including an empirical application in the banking industry, are also provided for illustration.

scholarly journals Performance Evaluation of Portfolios with Margin Requirements

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Hui Ding ◽  
Zhongbao Zhou ◽  
Helu Xiao ◽  
Chaoqun Ma ◽  
Wenbin Liu
Keyword(s):  
Performance Evaluation ◽  
Data Envelopment ◽  
Risky Assets ◽  
Margin Requirements ◽  
Short Sellers ◽  
Classical Economics ◽  
Dea Models ◽  
And Performance ◽  
Mean Variance ◽  
Optimization And Performance

In financial markets, short sellers will be required to post margin to cover possible losses in case the prices of the risky assets go up. Only a few studies focus on the optimization and performance evaluation of portfolios in the presence of margin requirements. In this paper, we investigate the theoretical foundation of DEA (data envelopment analysis) approach to evaluate the performance of portfolios with margin requirements from a different perspective. Under the mean-variance framework, we construct the optimization model and portfolio possibility set on considering margin requirements. The convexity of the portfolio possibility set is proved and the concept of efficiency in classical economics is extended to the portfolio case. The DEA models are then developed to evaluate the performance of portfolios with margin requirements. Through the simulations carried out in the end, we show that, with adequate portfolios, DEA can be used as an effective tool in computing the efficiencies of portfolios with margin requirements for the performance evaluation purpose. This study can be viewed as a justification of DEA into performance evaluation of portfolios with margin requirements.

Sign in / Sign up

Export Citation Format

Share Document