scholarly journals Evaluating productive performance: A new approach based on the product-mix problem consistent with Data Envelopment Analysis

Omega ◽  
2017 ◽  
Vol 67 ◽  
pp. 134-144 ◽  
Author(s):  
Juan Aparicio ◽  
Jesús T. Pastor ◽  
Fernando Vidal ◽  
José L. Zofío
2012 ◽  
Vol 14 (2) ◽  
pp. 135 ◽  
Author(s):  
Abdollah Noorizadeh ◽  
Mahdi Mahdiloo ◽  
Reza Farzipoor Saen

2020 ◽  
Vol 13 (6) ◽  
pp. 1187-1217
Author(s):  
Negin Berjis ◽  
Hadi Shirouyehzad ◽  
Javid Jouzdani

PurposeThe main purpose of this paper is to propose a new approach to determine the project activities weight factors using data envelopment analysis. Afterward, the model is applied in Mobarkeh Steel Company as a case study. Accordingly, the project schedule and plans can be written on the basis of the gained weight factors.Design/methodology/approachThis study proposed an approach to determine the weights of activities using Data Envelopment Analysis. This approach consists of four phases. In the first phase, project activities are extracted based on the work breakdown structure. In the second phase, the parameters affecting the importance of activities are determined through a review of the related literature and based on the experts' opinions. In the third phase, the proper data envelopment analysis model is chosen and the inputs and outputs are signified. Then, the activities' weights are determined based on the efficiency numbers. Finally, the model is solved for the case of Isfahan Mobarakeh Steel Company.FindingsThe proposed method aimed to calculate the project activities weight factor. Thus, influential parameters on project activities importance include activity duration, activity cost, activity importance which includes successors and predecessors, activity difficulty which includes skill related (education and experience), safety, communication rate, intellectual effort, physical effort, unfavorable work conditions and work related hazards, have been recognized. Then, Projects' data were extracted from the organizational expert's opinions and recorded data in documents. Thereupon, applying DEA, the activities weight factor were calculated based on the efficiency numbers. The results show that the model is applicable and has promising benefits in real-world problems.Originality/valuePlanning is one the most fundamental steps of project management. The ever-growing business environment demands for more complex projects with larger number of activities wants more efficient project managers. Organizational resources are limited; therefore, activities planning is a critical from the perspectives of both managers and researchers. Knowing the importance of the activities can help to manage activities more efficient and to allocate time, budget, cost and other resources more accurate. Different elements such as cost, time, complexity, and difficulty can affect the activity weight factor. In this study, the proposed approach aims to determine the weights of activities using Data Envelopment Analysis.


Author(s):  
Ali Ebrahimnejad ◽  
Naser Amani

Abstract Data envelopment analysis (DEA) is a prominent technique for evaluating relative efficiency of a set of entities called decision making units (DMUs) with homogeneous structures. In order to implement a comprehensive assessment, undesirable factors should be included in the efficiency analysis. The present study endeavors to propose a novel approach for solving DEA model in the presence of undesirable outputs in which all input/output data are represented by triangular fuzzy numbers. To this end, two virtual fuzzy DMUs called fuzzy ideal DMU (FIDMU) and fuzzy anti-ideal DMU (FADMU) are introduced into proposed fuzzy DEA framework. Then, a lexicographic approach is used to find the best and the worst fuzzy efficiencies of FIDMU and FADMU, respectively. Moreover, the resulting fuzzy efficiencies are used to measure the best and worst fuzzy relative efficiencies of DMUs to construct a fuzzy relative closeness index. To address the overall assessment, a new approach is proposed for ranking fuzzy relative closeness indexes based on which the DMUs are ranked. The developed framework greatly reduces the complexity of computation compared with commonly used existing methods in the literature. To validate the proposed methodology and proposed ranking method, a numerical example is illustrated and compared the results with an existing approach.


Complexity ◽  
2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Marzieh Ghasemi ◽  
Mohammad Reza Mozaffari ◽  
Farhad Hosseinzadeh Lotfi ◽  
Mohsen Rostamy malkhalifeh ◽  
Mohammad Hasan Behzadi

One of the mathematical programming techniques is data envelopment analysis (DEA), which is used for evaluating the efficiency of a set of similar decision-making units (DMUs). Fixed resource allocation and target setting with the help of DEA is a subject that has gained much attention from researchers. A new model was proposed by determining a common set of weights (CSW). All DMUs were involved with the aim of achieving higher efficiency in every DMU after the procedure. The minimum resources and targets allocated to each DMU were commensurate to the efficiency of that DMU and the share of DMU in the input resources and the output productions. To examine the proposed method, other methods in the DEA literature were examined as well, and then, the efficiency of the method was demonstrated through a numerical example.


Author(s):  
Salaman Abbasian-Naghneh ◽  
Mahboobeh Samiei ◽  
Marziyeh Felahat ◽  
Marziyeh Mahdavi

The objective of this chapter is to propose a new approach for evaluating Research and Development (R&D) projects at different stages of their life cycle. The approach is based on the integration of the balanced scorecard, Data Envelopment Analysis (DEA), and Multiple Objective (MO) linear programming. An interactive MO-DEA model is presented to incorporate Decision Maker's (DM) preference to effectively establish a common basis for fully ranking projects. The approach is illustrated on 50 R&D projects from the literature to highlight the effectiveness of the approach to fully rank all competing projects, hence increasing the discrimination power of DEA approach.


Author(s):  
Koki Kyo ◽  
◽  
Hideo Noda ◽  

In this paper, we propose a new approach for determining the unknown quantities in Banker–Charnes–Cooper models for data envelopment analysis by developing the marginal model synthesization algorithm. In this algorithm, several marginal fractional programming models are first constructed based on a simple numeric optimization. Then, a set of synthetic Banker–Charnes–Cooper models is obtained by compounding the marginal fractional programming models. A comparison of the proposed and existing approaches in terms of computational cost and stability of results shows that the former approach has distinct advantages. We also present an application of the proposed approach for analyzing the efficiency of industries in Japanese prefectures.


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