Housing Ranking: a model of equilibrium between buyers and sellers expectations

The equilibrium set of housing units (alternatives) can be characterized from the standpoint of both the demander and the supplier. The current work describes an application of the multicriteria single price model to the ranking of alternatives. By a generalization of the single price model and from both viewpoints an efficiency index can be calculated. We demonstrate how, in equilibrium, the two viewpoints result inevitably in inverse orders of ranking. The model is illustrated by a sample of housing units in the city of Valencia, Spain.

Ranking Efficient DMUs Using the Variation Coefficient of Weights in DEA

Abstract One of the difficulties of Data Envelopment Analysis(DEA) is the problem of de_ciency discrimination among efficient Decision Making Units (DMUs) and hence, yielding large number of DMUs as efficient ones. The main purpose of this paper is to overcome this inability. One of the methods for ranking efficient DMUs is minimizing the Coefficient of Variation (CV) for inputs-outputs weights. In this paper, it is introduced a nonlinear model for ranking efficient DMUs based on the minimizing the mean absolute deviation of weights and then we convert the nonlinear model proposed into a linear programming form

Generalized Super Efficiency Model for Ranking Efficient Decision Making Units in Data Envelopment Analysis

Abstract: In evaluating decision making units (DMU's) by using Data Envelopment Analysis (DEA) technique, we encounter the situation in which more than one unit takes efficiency score of one. In such a case, some criteria should be considered to rank the DMU's. Some efficient techniques such as AP, MAJ,etc may be used in this way. For some sets of data, with special structure in models that above mentioned, may be infeasible and unstable. In this paper, a new model is developed that all the existing drawbacks of previously applied models remove. Some numerical examples are put forward

DEA with common set of weights based on a multi objective fractional programming problem

Data envelopment analysis operates as a tool to appraise the relative efficiency of a set of homogenous decision making units. DEA allows each DMU to take its optimal weight in comparison to other DMUs while a similar condition is considered for other units. This feature threats the comparability of different units because different weighting schemes are used for different DMUs. In this paper, a model is presented to determine a common set of weights to calculate DMUs efficiency. This model is developed based on a multi objective fractional linear programming model that considers the original DEA's results as ideal solution and seeks a set of common weights to evaluate DMUs and increases the model's discrimination power. A numerical example is solved and the proposed method's results are compared to some previous methods. This Comparison has shown the proposed method's advantages in ranking DMUs

Efficiency Calculation, Effectiveness and Productivity of Sports Federations Using the Method (DEA)

This study presents of Efficiency, effectiveness and Productivity sports federations using data envelopment analysis (DEA), respectively.This research is applied and the type of research is descriptive. Research methodology and mathematical modeling, integration of inputs, outputs and to switch production between the performance and used data envelopment analysis techniques, combined with the theory of the decision maker. The population consisted of all sports federations worked at a sports field (39 federations), respectively. The sample was defined as the 39 Association. The instrument used was a questionnaire which its content and face validity.   0/92 reliability using Cronbach's alpha was calculated. Required calculations using the software GAMS is done.Results based on mathematical formulas, among the thirty-nine Federation under review, twenty Federation of efficient and inefficient and the rest of them had only Golf Federation effectiveness and Productivity.The results showed the Federation that their outputs to their inputs towards more efficient, more effective and has had productivity

Defuzzification of groups of fuzzy numbers using data envelopment analysis

Defuzzification is a critical process in the implementation of fuzzy systems that converts fuzzy numbers to crisp representations. Few researchers have focused on cases where the crisp outputs must satisfy a set of relationships dictated in the original crisp data. This phenomenon indicates that these crisp outputs are mathematically dependent on one another. Furthermore, these fuzzy numbers may exist as a group of fuzzy numbers. Therefore, the primary aim of this thesis is to develop a method to defuzzify groups of fuzzy numbers based on Charnes, Cooper, and Rhodes (CCR)-Data Envelopment Analysis (DEA) model by modifying the Center of Gravity (COG) method as the objective function. The constraints represent the relationships and some additional restrictions on the allowable crisp outputs with their dependency property. This leads to the creation of crisp values with preserved relationships and/or properties as in the original crisp data. Comparing with Linear Programming (LP) based model, the proposed CCR-DEA model is more efficient, and also able to defuzzify non-linear fuzzy numbers with accurate solutions. Moreover, the crisp outputs obtained by the proposed method are the nearest points to the fuzzy numbers in case of crisp independent outputs, and best nearest points to the fuzzy numbers in case of dependent crisp outputs. As a conclusion, the proposed CCR-DEA defuzzification method can create either dependent crisp outputs with preserved relationship or independent crisp outputs without any relationship. Besides, the proposed method is a general method to defuzzify groups or individuals fuzzy numbers under the assumption of convexity with linear and non-linear membership functions or relationships

Staff sizing as a mechanism of efficiency : an application of a non-parametric method

The concept of staff sizing aims to estimate or determine the ideal or optimal number of people needed to perform some organizational activities, which can be considered as a trend. So, models for staff sizing constitute a fundamental part of accurately identifying staff allocation. The objective of this paper is to propose a framework for decision-making based on Data Envelopment Analysis–DEA, to estimate the staff sizing in a Brazilian entity responsible for promoting and supporting the competitiveness and sustainable development of micro and small enterprises. Data collection was carried out in the headquarters of the entity, located in Brasilia. Firstly, interviews were carried with managers in order to assess qualitatively the needs of staff for each service unit. Secondly, the documental analysis of reports from 21 units was analyzed quantitatively in order to determine their efficiency in terms of staff sizing. The results found through DEA show that only three service units can be considered efficient in terms of staff sizing. Thus, there is a need to reduce the number of workers in most of the organization. In this context, the contributions for the entity lie in the discussion on the creation of quantitative indicators and the adoption of an efficiency analysis, which can be used to better estimate or determine the optimal quantity of staff. This paper innovates by proposing a quantitative and systematized approach to estimate the staff sizing, which is the DEA