scholarly journals Assessment of mixed network processes with shared inputs and undesirable factors

2020 ◽  
Vol 30 (1) ◽  
Author(s):  
Maryam Nematizadeh ◽  
Alireza Amirteimoori ◽  
Sohrab Kordrostami ◽  
Mohsen Vaez-Ghasemi
Keyword(s):  
Data Envelopment Analysis ◽  
Real World ◽  
Network Data ◽  
Data Envelopment ◽  
Parallel Section ◽  
Mixed Network ◽  
Weak Disposability ◽  
Proposed Model ◽  
Shared Inputs

In the real world, there are processes whose structures are like a parallel-series mixed network. Network data envelopment analysis (NDEA) is one of the appropriate methods for assessing the performance of processes with these structures. In the paper, mixed processes with two parallel and series components are considered, in which the first component or parallel section consists of the shared in-puts, and the second component or series section consists of undesirable factors. By considering the weak disposability assumption for undesirable factors, a DEA approach as based on network slack-based measure (NSBM) is introduced to evaluate the performance of processes with mixed structures. The proposed model is illustrated with a real case study. Then, the model is developed to discriminate efficient units.

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.

Developing a New Theory of Integer-Valued Data Envelopment Analysis for Supplier Selection in the Presence of Stochastic Data

2014 ◽  
Vol 7 (3) ◽  
pp. 80-103 ◽  
Author(s):  
Majid Azadi ◽  
Reza Farzipoor Saen
Keyword(s):  
Data Envelopment Analysis ◽  
Supplier Selection ◽  
Quadratic Program ◽  
Data Envelopment ◽  
Nonlinear Program ◽  
Deterministic Equivalent ◽  
Proposed Model ◽  
Successful Approach ◽  
Stochastic Data

Supplier selection has a strategic importance for every company. Hybrid integer data is one of the models in data envelopment analysis (DEA). In many real world applications, data are often stochastic. A successful approach to address uncertainty in data is to replace deterministic data via random variables, leading to chance-constrained DEA. In this paper, a chance-constrained hybrid integer data envelopment analysis (CCHIDEA) model is developed and also its deterministic equivalent which is a nonlinear program is derived. Furthermore, it is shown that the deterministic equivalent of the CCHIDEA model can be converted into a quadratic program. In addition, sensitivity analysis of the CCHIDEA model is discussed with respect to changes on parameters. Finally, a case study demonstrates the application of the proposed model.

A new method for eco-efficiency assessment using carbon footprint and network data envelopment analysis applied to a beekeeping case study

2021 ◽  
pp. 129585
Author(s):  
Ricardo Rebolledo-Leiva ◽  
Lidia Angulo-Meza ◽  
Marcela C. González-Araya ◽  
Alfredo Iriarte ◽  
Leonardo Vásquez-Ibarra ◽  
...  
Keyword(s):  
Data Envelopment Analysis ◽  
Carbon Footprint ◽  
New Method ◽  
Network Data ◽  
Data Envelopment ◽  
Network Data Envelopment Analysis ◽  
Efficiency Assessment

scholarly journals A bi-level multi-objective data envelopment analysis model for estimating profit and operational efficiency of bank branches

2019 ◽  
Vol 53 (5) ◽  
pp. 1633-1648 ◽  
Author(s):  
Hashem Omrani ◽  
Setareh Mohammadi ◽  
Ali Emrouznejad
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Dea Model ◽  
Bank Branches ◽  
Multi Objective ◽  
Proposed Model ◽  
Simultaneous Measuring

Data Envelopment Analysis (DEA) is a powerful method for analyzing the performance of decision making units (DMUs). Traditionally, DEA is applied for estimating the performance of a set of DMUs through measuring a single perspective of efficiency. However, in recent years, due to increasing competition in various industries, modern enterprises focus on enhancing their performance by measuring efficiencies in different aspects, separately or simultaneously. This paper proposes a bi-level multi-objective DEA (BLMO DEA) model which is able to assess the performance of DMUs in two different hierarchical dimensions, simultaneously. In the proposed model, we define two level efficiency scores for each DMU. The aim is to maximize these two efficiencies, simultaneously, for each DMU. Since the objective functions at both levels are fractional, a fuzzy fractional goal programming (FGP) methodology is used to solve the proposed BLMO DEA model. The capability of the proposed model is illustrated by a numerical example. Finally, to practically validate the proposed model, a real case study from 45 bank’s branches is applied. The results show that the proposed model can provide a more comprehensive measure for efficiency of each bank’s branch based on simultaneous measuring of two different efficiencies, profit and operational efficiencies, and by considering the level of their importance.

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