A group decision-making method for target setting in data envelopment analysis

Author(s):  
Reza Kiani Mavi ◽  
Ahmad Makui ◽  
Alireza Alinezhad
2018 ◽  
Vol 13 (1) ◽  
pp. 101-118 ◽  
Author(s):  
Dujun Zhai ◽  
Minyue Jin ◽  
Jennifer Shang ◽  
Chenfeng Ji

Purpose The purpose of this paper is to apply data envelopment analysis (DEA) techniques to the collective decision-making environment to appraise two-stage production process under different decision preferences. Design/methodology/approach The authors propose a novel multi-criteria group decision-making approach that uses consensus-strategic data envelopment analysis (CSDEA) to appraise two-stage production process under two different decision strategies, which are efficiency- and fairness-based group decision preferences. Findings The authors find that the proposed CSDEA model evaluates the performance of the decision-making units (DMUs) not by diminishing other competitors but rather based on group interests of the entire decision set. Originality/value The authors extend Li’s two-stage model to cases that consider both intermediate inputs and outputs. The authors address the issue of incorporating collective managerial strategy into multi-criteria group decision-making and propose a novel CSDEA model that considers not only the individual-level performance of a DMU but also the group-level or collective decision strategies.


2021 ◽  
Author(s):  
Imran Khan ◽  
Anjana Gupta ◽  
Aparna Mehra

Abstract The linguistic terms in a balanced linguistic term set describing qualitative data are symmetrical around the central linguistic word. With the growing complexity of the problems, the symmetric linguistic term set appears to be confined. This work examines the multiple criteria group decision-making problems where decision-makers employ a 2-tuple unbalanced linguistic term set to provide entries of alternative-criteria matrices.We adopt a data envelopment analysis (DEA) method and create a linear programming model to evaluate alternative-criteria weights for each decision-maker. The value function from prospect theory models the non-rational aspect of risk in criteria. The values of prospect gain and prospect loss on cost and benefit criteria are computed and used to create a DEA model that evaluates the weights of each criterion on each alternative. Finally, the entropy values of the cross-efficiency scores deliver a ranking of the alternatives. A numerical example illustrates the proposed methodology


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.


2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Tiantan Yang ◽  
Pingchun Wang ◽  
Feng Li

This paper aims to develop a data envelopment analysis (DEA) based model for allocating input resources and deciding output targets in organizations with a centralized decision-making environment, for example, banks, police stations, and supermarket chains. The central decision-maker has an interest in maximizing the total output production and at the same time minimizing the total input consumption. Traditionally, all decision-making units (DMUs) can be easily projected to the efficient frontier, which is a mathematical feasibility; however, it does not guarantee the managerial feasibility during the planning period. In this paper, we will take potential limitations of input-output changes into account by building a difficulty coefficient matrix of modifying their production in the current production possibility set so that the solution guarantees managerial feasibilities. Three objectives, namely, maximizing aggregated outputs, minimizing the consumption of input resources, and minimizing the total difficulty coefficient, are proposed and incorporated into the formation of resource allocation and target setting scheme. Building on this, we combine DEA and multiobjective programming to solve the resource allocation and target setting problem. In the end, we apply our proposed approach to a real-world problem of sixteen chain hotels to illustrate the efficacy and usefulness of the proposed approach.


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