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.

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 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 Designing an Intuitionistic Fuzzy Network Data Envelopment Analysis Model for Efficiency Evaluation of Decision-Making Units with Two-Stage Structures

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Nafiseh Javaherian ◽  
Ali Hamzehee ◽  
Hossein Sayyadi Tooranloo
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Two Stage ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Dea Models ◽  
Decision Making Units

Data envelopment analysis (DEA) is a powerful tool for evaluating the efficiency of decision-making units for ranking and comparison purposes and to differentiate efficient and inefficient units. Classic DEA models are ill-suited for the problems where decision-making units consist of multiple stages with intermediate products and those where inputs and outputs are imprecise or nondeterministic, which is not uncommon in the real world. This paper presents a new DEA model for evaluating the efficiency of decision-making units with two-stage structures and triangular intuitionistic fuzzy data. The paper first introduces two-stage DEA models, then explains how these models can be modified with intuitionistic fuzzy coefficients, and finally describes how arithmetic operators for intuitionistic fuzzy numbers can be used for a conversion into crisp two-stage structures. In the end, the proposed method is used to solve an illustrative numerical example.

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.

Ranking Two-Stage Production Units in Data Envelopment Analysis

2016 ◽  
Vol 33 (01) ◽  
pp. 1650002
Author(s):  
Roza Azizi ◽  
Reza Kazemi Matin
Keyword(s):  
Data Envelopment Analysis ◽  
Production Systems ◽  
Relative Performance ◽  
Accurate Information ◽  
Data Envelopment ◽  
Two Stage ◽  
New Approach ◽  
Ranking Criterion

In this paper, we propose a new approach to rank two-stage production systems in data envelopment analysis based on performance of the stages. To do this, a method is devised to compare the stages performance of a special two-stage unit with the corresponding stages performance of other units. The relative performance of two-stage production units is investigated under new definitions of weak and strong relations and a new ranking criterion is introduced as the result. The most important features of our method is the ability to achieve ranking intervals for two-stage production units based on the introduced relations over all feasible weights, as well as the ability to generate accurate information about sources of inefficiency of two-stage production units.

Two-stage additive integer-valued data envelopment analysis models

2019 ◽  
Vol 14 (1) ◽  
pp. 199-213 ◽  
Author(s):  
Shahrooz Fathi Ajirlo ◽  
Alireza Amirteimoori ◽  
Sohrab Kordrostami
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Two Stage ◽  
Modified Model ◽  
Content Type ◽  
Multistage Processes ◽  
Multi Stage ◽  
Internal Structures ◽  
Dea Models ◽  
Analysis Models

Purpose The purpose of this paper is to propose a modified model in multi-stage processes when there are intermediate measures between the stages and in this sense, the new efficiency scores are more accurate. Conventional data envelopment analysis (DEA) models disregard the internal structures of peer decision-making units (DMUs) in evaluating their relative efficiency. Such an approach would cause managers to lose important DMU information. Therefore, in multistage processes, traditional DEA models encounter problems when intermediate measures are used for efficiency evaluation. Design/methodology/approach In this study, two-stage additive integer-valued DEA models were proposed. Three models were proposed for measuring inefficiency slacks in each stage and in the system as a whole. Findings Three models were proposed for measuring inefficiency slacks in each stage and in the system as a whole. Originality/value The advantage of the proposed models for multi-stage systems is that they can accurately determine the stages with the greatest weaknesses/strengths. By introducing an applied case in the Iranian power industry, the paper demonstrated the applications and advantages of the proposed models.

Double Frontier Two-Stage Fuzzy Data Envelopment Analysis

2020 ◽  
Vol 28 (01) ◽  
pp. 117-152 ◽  
Author(s):  
Alireza Amirteimoori ◽  
Hossein Azizi ◽  
Sohrab Kordrostami
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Efficiency Analysis ◽  
Programming Approach ◽  
Data Envelopment ◽  
Fuzzy Data ◽  
Insurance Company ◽  
Two Stage ◽  
Dea Models ◽  
Fuzzy Dea

Data envelopment analysis (DEA) is a mathematical programming approach with widespread applications in productivity and efficiency analysis. Compared with traditional DEA models, two-stage DEA models show the performance of each process and make available more information for decision making. In an article by Kao and Liu, models were proposed for combining a two-stage process to achieve overall fuzzy efficiency measures. Their method follows the simple geometric average approach and uses the product of two efficiencies. The present article applies a different angle for efficiency analysis in the two-stage fuzzy DEA. We suggest that the overall efficiency score of a decision-making unit (DMU) is defined as total weight of stage efficiencies, not as the simple product of their efficiency. Moreover, the proposed fuzzy DEA models are different from the model by Kao and Liu for fuzzy data in that our models are linear without the need for additional changes in variables and use the same set of constraints to measure the efficiency of DMUs with fuzzy input and output data. While the models by Kao and Liu are a nonlinear optimization problem that need additional changes in variables, and use different sets of constraints to measure fuzzy efficiencies. Additionally, our proposed approach evaluates the performance of DMUs from both optimistic and pessimistic viewpoints. Finally, using the proposed approach, the Taiwanese non-life insurance company problem will be investigated.

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