scholarly journals A Revised Inverse Data Envelopment Analysis Model Based on Radial Models

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 803
Author(s):  
Xiaoyin Hu ◽  
Jianshu Li ◽  
Xiaoya Li ◽  
Jinchuan Cui
Keyword(s):  
Data Envelopment Analysis ◽  
Efficiency Index ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Numerical Examples ◽  
Wide Range ◽  
Dea Models ◽  
Overall Efficiency ◽  
Decision Making Units

In recent years, there has been an increasing interest in applying inverse data envelopment analysis (DEA) to a wide range of disciplines, and most applications have adopted radial-based inverse DEA models. However, results given by existing radial based inverse DEA models can be unreliable as they neglect slacks while evaluating decision-making units’ (DMUs) overall efficiency level, whereas classic radial DEA models measure the efficiency level through not only radial efficiency index but also slacks. This paper points out these disadvantages with a counterexample, where current inverse DEA models give results that outputs shall increase when inputs decrease. We show that these unreasonable results are the consequence of existing inverse DEA models’ failure in preserving DMU’s efficiency level. To rectify this problem, we propose a revised model for the situation where the investigated DMU has no slacks. Compared to existing radial inverse DEA models, our revised model can preserve radial efficiency index as well as eliminating all slacks, thus fulfilling the requirement of efficiency level invariant. Numerical examples are provided to illustrate the validity and limitations of the revised model.

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 Uniformization of frontiers in non-radial ZSG-DEA models: an application to airport revenues

2010 ◽  
Vol 30 (1) ◽  
pp. 175-193 ◽  
Author(s):  
Aline Bandeira de Mello Fonseca ◽  
João Carlos Correia Baptista Soares de Mello ◽  
Eliane Gonçalves Gomes ◽  
Lidia Angulo Meza
Keyword(s):  
Data Envelopment Analysis ◽  
Theoretical Approach ◽  
Approximate Algorithm ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Dea Models ◽  
Weights Restrictions ◽  
Zero Sum

We propose in this paper an extension to the Zero Sum Gains Data Envelopment Analysis model (ZSG-DEA). The proposed approach takes into account, simultaneously, non-radial projections and cone-ratio weights restrictions. We developed an iterative approximate algorithm to solve this model, as in the case study it is oriented only to the constant sum output. The theoretical approach is applied to the concession of discounts and surcharges problem, in terms of airport fees.

Use Shapley value for increasing power distinguish of data envelopment analysis model: An application for estimating environmental efficiency of industrial producers in Iran

2019 ◽  
Vol 31 (4) ◽  
pp. 656-675
Author(s):  
Hashem Omrani ◽  
Mohaddeseh Amini ◽  
Mahdieh Babaei ◽  
Khatereh Shafaat
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Shapley Value ◽  
Environmental Efficiency ◽  
Data Envelopment Analysis Model ◽  
Game Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Proposed Model ◽  
Decision Making Units

Data envelopment analysis is a linear programming model for estimating the efficiency of decision making units (DMUs). Data envelopment analysis model has two major advantages: it does not need the explicit form of production function for estimating the efficiency scores of decision making units and also, it allows decision making units to choose the weights of inputs and outputs to reach the estimated efficient frontier. In several cases, the distinguish power of data envelopment analysis model is weak and it is unable to rank decision making units, entirely. The goal of this study is to provide a better methodology to fully rank all the decision making units. First, the efficiency scores of all decision making units are generated using the cross-efficiency data envelopment analysis model and then, the cooperative game theory approach is applied to produce a fully fair ranking of decision making units. The DEA-Game model calculates the Shapley value for each coalition of decision making units and the final ranking is relied on common weights. These fair common weights are found using the Shapley value to rank decision making units, completely. To illustrate the capability of the proposed model, the industrial producers in the provinces of Iran are evaluated. First, the suitable indicators are defined and then, the actual environmental data for year 2013 is gathered. Finally, the proposed model is applied to fully rank the industrial producers in provinces of Iran from environmental perspective. The results show that the DEA-Game model can rank provinces, entirely. Based on the results, the industrial producers in big provinces such as Tehran, Fars and Yazd have undesirable performance in environmental efficiency.

Measuring Customer Satisfaction and Hotel Efficiency Analysis: An Approach Based on Data Envelopment Analysis

2020 ◽  
pp. 193896552094491
Author(s):  
Changhee Kim ◽  
Kyunghwa Chung
Keyword(s):  
Data Envelopment Analysis ◽  
Customer Satisfaction ◽  
Efficiency Score ◽  
Service Process ◽  
Future Research ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Network Dea ◽  
Overall Efficiency

We propose a network DEA (Data Envelopment Analysis) model that consists of internal and external service processes and employs customer satisfaction as an intermediate factor. Using the proposed model, we calculate four efficiency scores: service productivity score drawn from internal service process, service efficiency score drawn from external service process, overall efficiency score drawn from both internal and external service processes, and management efficiency score calculated without the intermediate output. By analyzing the four efficiency scores, we find that overall efficiency score is well suited to represent a hotel’s comprehensive productivity. Our results support the validity of a network DEA model which includes customer satisfaction for analyzing hotel efficiency. Despite its important role that plays in hotel efficiency, customer satisfaction has been barely considered in the previous hotel efficiency studies. By analyzing hotel efficiency including customer satisfaction, this study sheds new light on the hotel efficiency research area and provides a valuable basis for future research.

Energy–economy–environmental (3E) performance of Chinese regions based on the data envelopment analysis model with mixed assumptions on disposability

2018 ◽  
Vol 29 (5) ◽  
pp. 664-684 ◽  
Author(s):  
Qingyou Yan ◽  
Xu Wang ◽  
Tomas Baležentis ◽  
Dalia Streimikiene
Keyword(s):  
Data Envelopment Analysis ◽  
Central Area ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Eastern Area ◽  
Dea Models ◽  
Energy Economy

This paper presents a modified environmental production technology which imposes the proper disposability on the undesirable outputs depending on the underlying technical properties. Then, aggregate and disaggregate (Russell-type) data envelopment analysis (DEA) models are proposed to evaluate the energy–economy–environment (3E) efficiency based on the modified technology (hereafter referred to as the 3E-DEA models). The non-radial Malmquist productivity index is adapted to model the changes in the 3E productivity over time. A case study of 3E efficiency analysis for the 30 Chinese administrative regions during 2011–2013 is presented. In general, Chinese regions did not perform well in terms of 3E goals as only three of them exhibited full efficiency. It was also found out that the eastern area showed the best 3E performance, whereas the central area followed suit, thus putting the western area at end of ranking. Still, some regions in the eastern area showed 3E efficiencies lower than those of some cities in the central and eastern areas. Anyway, most of the regions showed improving 3E productivity during 2011–2013.

Measuring Performance of a Three-Stage Network Structure Using Data Envelopment Analysis and Nash Bargaining Game: A Supply Chain Application

2018 ◽  
Vol 17 (05) ◽  
pp. 1429-1467 ◽  
Author(s):  
Mohammad Amirkhan ◽  
Hosein Didehkhani ◽  
Kaveh Khalili-Damghani ◽  
Ashkan Hafezalkotob
Keyword(s):  
Supply Chain ◽  
Data Envelopment Analysis ◽  
Nash Bargaining ◽  
Data Envelopment ◽  
Second Stage ◽  
Proposed Model ◽  
Nash Bargaining Game ◽  
Dea Models ◽  
Overall Efficiency

The issue of efficiency analysis of network and multi-stage systems, as one of the most interesting fields in data envelopment analysis (DEA), has attracted much attention in recent years. A pure serial three-stage (PSTS) process is a specific kind of network in which all the outputs of the first stage are used as the only inputs in the second stage and in addition, all the outputs of the second stage are applied as the only inputs in the third stage. In this paper, a new three-stage DEA model is developed using the concept of three-player Nash bargaining game for PSTS processes. In this model, all of the stages cooperate together to improve the overall efficiency of main decision-making unit (DMU). In contrast to the centralized DEA models, the proposed model of this study provides a unique and fair decomposition of the overall efficiency among all three stages and eliminates probable confusion of centralized models for decomposing the overall efficiency score. Some theoretical aspects of proposed model, including convexity and compactness of feasible region, are discussed. Since the proposed bargaining model is a nonlinear mathematical programming, a heuristic linearization approach is also provided. A numerical example and a real-life case study in supply chain are provided to check the efficacy and applicability of the proposed model. The results of proposed model on both numerical example and real case study are compared with those of existing centralized DEA models in the literature. The comparison reveals the efficacy and suitability of proposed model while the pitfalls of centralized DEA model are also resolved. A comprehensive sensitivity analysis is also conducted on the breakdown point associated with each stage.

A multiobjective data envelopment analysis model applied to the evaluation of Brazilian electrical distributors

2018 ◽  
Author(s):  
Luciana G. Machado ◽  
Isabella C. Carlos ◽  
Lidia A. Meza ◽  
Joao Carlos C.B.S. de Mello
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model
Sign in / Sign up

Export Citation Format

Share Document