How to Assess Sustainability of Suppliers in the Presence of Dual-Role Factor and Volume Discounts? A Data Envelopment Analysis Approach

2017 ◽  
Vol 34 (03) ◽  
pp. 1740016 ◽  
Author(s):  
Mohammad Izadikhah ◽  
Reza Farzipoor Saen ◽  
Kourosh Ahmadi
Keyword(s):  
Data Envelopment Analysis ◽  
Supplier Selection ◽  
Selection Process ◽  
Critical Role ◽  
Dual Role ◽  
Data Envelopment ◽  
Environmental Pressures ◽  
Complete Ranking

Sustainability factors play critical role for long-term achievement of a supply chain management and purchasing process becomes more complicated with social and environmental pressures. Managing supplier selection process is a necessary step for companies seeking to manage their corporate legitimacy and reputations. Data envelopment analysis (DEA) has been widely used for supplier selection problems. In this paper, we propose a new super-efficiency method for evaluating sustainability of suppliers in the presence of dual-role factors and volume discounts. We show that enhanced Russell model (ERM) fails to present a complete ranking of suppliers. Our new model presents a complete ranking and also preserves properties of the ERM. Capabilities of our proposed method are shown using a couple of examples. A case study is presented to illustrate our proposed approach. The proposed method is used to select the best sustainable suppliers.

A Robust Data Envelopment Analysis Method with Bounded Data for Ranking Operations Strategies

2015 ◽  
Vol 6 (3) ◽  
pp. 49-64 ◽  
Author(s):  
Mohamad Amin Kaviani ◽  
Mehdi Abbasi
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Cement Industry ◽  
Data Envelopment ◽  
Analysis Method ◽  
Interval Numbers ◽  
Complete Ranking ◽  
Bounded Data ◽  
Decision Making Units

This paper introduces a new robust data envelopment analysis (RDEA) approach for analyzing and ranking the organizations' operations strategies. In the proposed RDEA method, pessimistic and optimistic efficiencies of decision making units (DMUs) obtained from the robust counterpart of the envelopment form and the optimistic counterpart of the multiplier form of DEA are introduced. The inputs and outputs data are assumed to be bounded data (interval numbers) in the proposed models. A case study in the cement industry is presented to demonstrate the applicability of the proposed RDEA approach. The results obtained from the authors' proposed RDEA approach is more robust and their method provides a more complete ranking of the DMUs compared to conventional Likert-based DEA model.

Using Data Envelopment Analysis for Green Supplier Selection in Manufacturing under Vague Environment

2012 ◽  
Vol 622-623 ◽  
pp. 1682-1685 ◽  
Author(s):  
Atefeh Amindoust ◽  
Ahmed Shamsuddin ◽  
Ali Saghafinia
Keyword(s):  
Data Envelopment Analysis ◽  
Supplier Selection ◽  
Decision Makers ◽  
Central Component ◽  
Data Envelopment ◽  
Linguistic Terms ◽  
Green Supplier Selection ◽  
Growth Of Knowledge ◽  
Using Data

In these days, considering the growth of knowledge about environmental protection and green issues in manufacturing, green supplier selection would be the central component in the management of supply chain. This paper intends to apply data envelopment analysis for supplier selection considering environmental merits. The suppliers’ performances with respect to criteria are not pure numbers and considered in linguistic terms according to decision makers’ opinion. To handle the subjectivity of decision makers’ assessments, fuzzy logic has been applied. A case study is done to present the application of the method.

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.

scholarly journals Supplier Evaluation with Environmental Aspects and Common DEA Weights

2019 ◽  
Vol 27 (1) ◽  
pp. 17-25 ◽  
Author(s):  
Gyöngyi Vörösmarty ◽  
Imre Dobos
Keyword(s):  
Data Envelopment Analysis ◽  
Supplier Selection ◽  
Selection Process ◽  
Weight System ◽  
Data Envelopment ◽  
Environmental Aspects ◽  
Traditional Management ◽  
Business Decision ◽  
Common Weights ◽  
Environmental Criteria

Supplier selection is an important business decision. Beside traditional management criteria the environmental aspects are getting often recognition. In this paper the method of Data Envelopment Analysis (DEA) is used to study the extension of traditional supplier selection methods with environmental factors. The focus will be on the weight selection process which can control the selection. In this method we divide the criteria in two manners: the traditional and environmental (green) factors. Then with the help of DEA we are searching a weight system with which the environmental criteria can influence the decision with a representation of the green factors. To choose the mentioned weight system, we apply DEA (Data Envelopment Analysis) with common weights analysis (CWA) method. In this case of DEA/CWA the common weights are calculated with a linear programming problem.

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.

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