scholarly journals Network DEA based on DEA-ratio

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Dariush Akbarian
Keyword(s):  
Insurance Companies ◽  
Data Envelopment ◽  
Validity And Reliability ◽  
Two Stage ◽  
Network Dea ◽  
Black Boxes ◽  
Internal Structures ◽  
Dea Models ◽  
Tchebycheff Norm ◽  
Special Case

AbstractData envelopment analysis (DEA) is a technique to measure the performance of decision-making units (DMUs). Conventional DEA treats DMUs as black boxes and the internal structure of DMUs is ignored. Two-stage DEA models are special case network DEA models that explore the internal structures of DMUs. Most often, one output cannot be produced by certain input data and/or the data may be expressed as ratio output/input. In these cases, traditional two-stage DEA models can no longer be used. To deal with these situations, we applied DEA-Ratio (DEA-R) to evaluate two-stage DMUs instead of traditional DEA. To this end, we developed two novel DEA-R models, namely, range directional DEA-R (RDD-R) and (weighted) Tchebycheff norm DEA-R (TND-R). The validity and reliability of our proposed approaches are shown by some examples. The Taiwanese non-life insurance companies are revisited using these proposed approaches and the results from the proposed methods are compared with those from some other 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.

Two-Stage Data Envelopment Analysis Efficiency of Indian General Insurance Companies

2021 ◽  
pp. 097215092110476
Author(s):  
Ram Pratap Sinha
Keyword(s):  
Data Envelopment Analysis ◽  
Asset Management ◽  
Evaluation Model ◽  
Insurance Companies ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Two Stage ◽  
Network Dea ◽  
Second Stage ◽  
General Insurance

The present study compares efficiency-related performance of 15 Indian general insurance companies using a two-stage efficiency evaluation model. Efficiency evaluation has been made for the span 2009–2010 to 2017–2018 using network DEA (data envelopment analysis). The results indicate that the in-sample private sector general insurance companies outcompeted the public sector insurers with regard to first-stage activity (premium mobilization), while the reverse was observed in terms of the second-stage activity (asset management and provision of claim benefits). The study also carried out regression of efficiency scores on several contextual variables. The results indicate that ownership is an influential contextual variable in both stages of productivity while solvency significantly impacts efficiency in the second stage.

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.

scholarly journals Incorporation of Inefficiency Associated with Link Flows in Efficiency Measurement in Network DEA

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Abolghasem Shamsijamkhaneh ◽  
Seyed Mohammad Hadjimolana ◽  
Bijan Rahmani Parchicolaie ◽  
Farhad Hosseinzadehlotfi
Keyword(s):  
Dual Role ◽  
Programming Approach ◽  
Data Envelopment ◽  
Network Dea ◽  
New Approach ◽  
Internal Structures ◽  
Dea Models ◽  
Mathematical Programming Approach ◽  
Decision Making Units

Data Envelopment Analysis (DEA) is a mathematical programming approach to measure the relative efficiency of peer decision making units (DMUs) which use multiple inputs to produce multiple outputs. One of the drawbacks of traditional DEA models is the neglect of internal structures of the DMUs. Network DEA models are able to overcome the shortcoming of the traditional DEA models. In network DEA a DMU is made up of some divisions linked together by intermediate products. An intermediate product has the dual role of output from one division and input to another one. Improving the efficiency of one process may reduce the efficiency of another process. To address the conflict caused by the dual role of intermediate measures, this paper presents a new approach which categorizes the intermediate measures into either input or output type endogenously, while keeping the continuity of link flows between divisions. This categorization allows us to measure the inefficiencies associated with intermediate measures and account their indirect effects on the objective function. In this paper we propose a new Slacks-based measure which includes any nonzero slacks identified by the model and inherits the properties of monotonicity in slacks and units invariance from the conventional SBM approach.

scholarly journals The Theoretical Relationship between the CCR Model and the Two-Stage DEA Model with an Application in the Efficiency Analysis of the Financial Industry

Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 712
Author(s):  
Ming-Chi Tsai ◽  
Ching-Hsue Cheng ◽  
Van Trung Nguyen ◽  
Meei-Ing Tsai
Keyword(s):  
Insurance Companies ◽  
Data Envelopment ◽  
Financial Industry ◽  
Two Stage ◽  
Theoretical Relationship ◽  
Dea Model ◽  
Bank Branches ◽  
Dea Models ◽  
The Relationship ◽  
Ccr Model

Since Charnes, Cooper, and Rhodes introduced data envelopment analysis (DEA) in 1978, later called the DEA-CCR model, many studies applied this technique to different fields. Based on the original CCR model, many modified DEA models were developed by researchers. Since 1999, Seiford and Zhu presented a two-stage DEA model. Later, these models were widely used in many studies. However, the relationship between the efficiency scores that are obtained from the original CCR model and the two-stage DEA model remains unknown. To fill this gap, this study proposed a theoretical relationship between the efficiency scores that are calculated from the two-stage DEA model and those that are obtained from the original CCR model. How the sets of nonsymmetrical weights affected the efficiency scores were also investigated. Theorems regarding the relationship were developed, and then the model was utilized to evaluate the two-stage efficiency scores of the insurance companies (non-life) and bank branches. The results show that using a two-stage DEA model can get more information about operational efficiency than the traditional CCR model does. The findings from this study about the two-stage DEA technique can provide significant reasons for using this model to evaluate performance efficiency.

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 Common set of weights and efficiency improvement on the basis of separation vector in two-stage network data envelopment analysis

2019 ◽  
Vol 14 (1) ◽  
pp. 53-65
Author(s):  
Hamid Kiaei ◽  
Reza Kazemi Matin
Keyword(s):  
Network Data ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Efficiency Improvement ◽  
Ranking Methods ◽  
Two Stage ◽  
Black Boxes ◽  
Dea Models ◽  
Common Set Of Weights ◽  
Single Objective

AbstractCommon set of weights (CSWs) method is one of the popular ranking methods in DEA which can rank efficient and inefficient units. Based on an identical criterion, the method selects the most favorable weight set for all units. An important issue is that in most common DEA models, the internal structure of the production units is ignored and the units are often considered as black boxes. In this paper, in order to evaluate the units and subunits in the two-stage NDEA based on an identical criterion, it is suggested to use CSWs method on the basis of separation vector. Our research contribution in this paper includes: (1) CSWs method is formulated in two-stage NDEA as a multiple objective fractional programming (MOFP) problem. (2) A method is suggested based on separation vector to change MOFP problem into single objective linear programming (SOLP) problem in two-stage NDEA. In the theorem, it is shown that the obtained solutions from MOFP and SOLP in two-stage NDEA are identical. (3) In the framework of the new models of two-stage NDEA, a process is introduced to improve efficiency evaluation by CSWs on the basis of separation vector which is based on the radial improvement of inputs and final outputs. Finally, an enlightening application is presented.

scholarly journals The Uncertain Network DEA Model for Two-Stage System with Additive Relationship

Symmetry ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1893
Author(s):  
Bao Jiang ◽  
Chen Yang ◽  
Jian Li
Keyword(s):  
Equivalent Form ◽  
Data Envelopment ◽  
Deep Insight ◽  
Two Stage ◽  
Network Dea ◽  
Uncertain Network ◽  
Internal Structures ◽  
Stage System ◽  
Stage 1 ◽  
Insight Into

When decision making units (DMUs) have internal structures with imprecise inputs and outputs, uncertain network data envelopment analysis (UNDEA) is appropriate to deal with the efficiency evaluation of these DMUs. However, a deep insight into clarifying the power’s differences between the internal structures of DMUs is a deficiency in the current UNDEA model. To address this issue, in this paper, we propose a new UNDEA model by differentiating the power asymmetry of each sub-stage with assumption of a two-stage system and demonstrate an additive relationship between stage 1 and stage 2 of each DMU. Moreover, the equivalent form and its proof of the new model are also presented for accurate calculation. Finally, a numerical example reflecting three different additive relationships between two sub-stages of DMUs is given to illustrate the results of evaluation.

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