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.

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.

Construction and Performance Analysis of a Two-Stage Traveling-Wave Thermo-Acoustic Generator

2020 ◽  
Author(s):  
H. S. Shamase ◽  
L. K. Tartibu
Keyword(s):  
Sound Wave ◽  
Traveling Wave ◽  
Onset Time ◽  
Two Stage ◽  
Study Guides ◽  
Linear Alternator ◽  
Stage System ◽  
Parallel Configuration ◽  
And Performance ◽  
Insight Into

Abstract Thermo-acoustic technology offers the possibility to convert heat energy into a sound-wave that can potentially be used to generate electricity through a linear alternator. The construction of a two-stage traveling-wave thermo-acoustic generator is described in this paper. The potential of conversion of heat into electricity has been investigated experimentally. The effect of the geometrical configurations of the thermo-acoustic system on its performance has been analyzed. The two thermo-acoustic engine cores were tested separately and subsequently combined to build a two-stage system. Two different configurations of engine cores have been considered namely series and parallel configuration. Hence, the effect of the orientation of the engine core has been investigated to get an insight into its effect on the output of the device. Parallel arrangement was found to be the most efficient configuration. An onset time of 3.15 minutes was recorded for the device to generate a sound wave. This system has achieved 125.7 dB corresponding to an output voltage of 486 mV. This study guides the development of more efficient electricity generators using thermo-acoustic technology.

Evaluating the efficiency of a two-stage network structure with the use of fractional programming

2017 ◽  
Vol 09 (03) ◽  
pp. 1750034 ◽  
Author(s):  
Reza Ahmadzadeh ◽  
Sohrab Kordrostami ◽  
Alireza Amirteimoori
Keyword(s):  
Linear Model ◽  
Fractional Programming ◽  
Nonlinear Models ◽  
Heuristic Method ◽  
Data Envelopment ◽  
Network Structures ◽  
Two Stage ◽  
Second Stage ◽  
Internal Structures ◽  
Stage Process

Recently, network data envelopment analysis (NDEA) models have been developed to evaluate the efficiency of decision making units (DMUs) with internal structures. The network structures range from a simple two-stage process to a complex system. Looking through the literature on two-stage network structures, we see that Li et al. (2012) extended a model by assuming that the inputs to the second stage include both the outputs from the first stage and additional inputs to the second stage. In the current study, a model is proposed to evaluate the performance of these types of general two-stage network structures. To this end, we provide a linear model using fractional programming. In fact, previous models were often nonlinear models which were solved with heuristic methods. But, since the model presented in this paper is a linear model, then it can be solved easily as a linear programming problem. In order to clarify the newly proposed approach of this study, it has been applied to a case of regional Research and Development (R&D) system related to 30 provincial level regions in China and results have been compared with the heuristic method of Li et al. (2012).

scholarly journals Development of Two-Stage Network Data Envelopment Analysis (DEA) Model to Measure Production Line’s Performance: Combination of Automation and Labor

2016 ◽  
Vol 3 (2) ◽  
pp. 37-43
Author(s):  
N.A. C.Azhar ◽  
M.A. Mansor ◽  
S.A. Rusdan ◽  
S.N.M. Saffe
Keyword(s):  
Data Envelopment Analysis ◽  
Production Line ◽  
Manufacturing Industry ◽  
Performance Indicator ◽  
Data Envelopment ◽  
Two Stage ◽  
Network Dea ◽  
Increase Productivity ◽  
To Come ◽  
The Cost

Nowadays, the growth of industry can be seen as a nature of the world. Each company race again each other to increase productivity to produce new, high quality and product that fulfil customer demand. One can achieve the Key Performance Indicator (KPI) or targeted goal but without considering the cost, manpower, time or others elements is inefficient toward productivity. Upgrade production line in manufacturing industry needs huge investment to come out with good performance. The company can receive Return of Investment (ROI) and save more money from paying labor salary and increase productivity. However, the company also may have the risk of losing their money from the investment done. In this research, we studied the effectiveness of production line that equipped with automation usage to determine the productivity and quality of the product produced. We apply Data Envelopment Analysis (DEA) to measure efficiencies of the production line where DEA is one of an excellent tool that can evaluate efficiencies and have been using widely in many sectors. The model that will be used in this study is Two-Stage Network DEA. As a case study, this research focuses on the production line that producing a product with a high and continues demand to observe how the investment on automation can give good return or otherwise.

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.

Two-Stage Evaluation Method of Dynamic Network DEA

2011 ◽  
Vol 204-210 ◽  
pp. 583-588
Author(s):  
Jian Yong Liu ◽  
Kun Pang ◽  
Ling Li ◽  
Cheng Qun Fu ◽  
Jie Guo
Keyword(s):  
Network Structure ◽  
Systems Analysis ◽  
Evaluation Method ◽  
Dynamic Network ◽  
Data Envelopment ◽  
Two Stage ◽  
Good Tool ◽  
Network Dea ◽  
Dea Efficiency ◽  
Set Up

In view of the defect that network DEA (data envelopment analysis) can not reflect the network structure when it comes to dynamic evaluation, we proposed a two-stage evaluation method of dynamic network DEA. Time parameter was introduced to network DEA and dynamic network DEA model was established. In order to evaluate the efficiency of dynamic network DEA in several time spans, we built a two-stage evaluation method. In the first stage, dynamic network DEA efficiency matrix was formulated. In the second one, a new input-output DEA unit was set up to evaluate the synthetical efficiency of dynamic network DEA. The two-stage method can manifest the real dynamic property in network DEA, as well as consider the network structure which involves intermediate products by dynamic measure. A numerical example indicated that the two-stage evaluation method can solve dynamic network DEA problem efficiently, it can also provide improved information between inefficient DMU and optimum values by slacks. The new measure can be a good tool of systems analysis.

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.

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.

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