A lexicographic radial projection onto the efficient frontier in Data Envelopment Analysis

2018 ◽  
Vol 265 (3) ◽  
pp. 1005-1012 ◽  
Author(s):  
Pekka J. Korhonen ◽  
Akram Dehnokhalaji ◽  
Nasim Nasrabadi
Keyword(s):  
Data Envelopment Analysis ◽  
Efficient Frontier ◽  
Data Envelopment ◽  
Radial Projection

Interval Data Envelopment Analysis for Inter-Group Data Usage

2020 ◽  
Vol 24 (1) ◽  
pp. 113-122
Author(s):  
Tomoe Entani ◽  
Keyword(s):  
Data Envelopment Analysis ◽  
Efficient Frontier ◽  
Original Data ◽  
Weight Vector ◽  
The Other ◽  
Data Envelopment ◽  
Broad Perspective ◽  
Data Usage ◽  
Group Data ◽  
Multiple Groups

Organizations are interested in exploiting the data from the other organizations for better analyses. Therefore, the data related policies of organizations should be sensitive to the data privacy issue, which has been widely discussed recently. The present study is focused on inter-group data usage for a relative evaluation. This research is based on the data envelopment analysis (DEA), which is used to measure the efficiency of a decision making unit (DMU) relatively employed within a group. In DEA, establishing an efficient frontier consisting of efficient DMUs is essential. We can obtain the efficiency values of a DMU by projecting it to the efficient frontier, and including in the efficiency interval via the interval DEA. When the original data of multiple groups are not open to each other, the alternative is to exchange the information corresponding to the efficient frontiers to estimate the efficiency intervals of a DMU in such a manner that the alternative is in the other groups. Therefore, in this paper, we propose a method to replace the efficient frontier with a weight vector set, from which it is not possible to reconstruct the original data. Considering the weight vector sets of multiple groups, a DMU has three types of efficiency intervals: in its own group, in each of the other groups, and in the integrated group. They provide rich insights on the DMU from a broad perspective, and this encourages inter-group data usage. In this process, we focus on two types of information reduction: one is from the efficient frontier to the weight vector set, and the other is from a union of the groups to the integrated group.

scholarly journals MEASURING TECHNICAL EFFICIENCY OF MALAYSIAN REAL ESTATE INVESTMENT TRUSTS: A DATA ENVELOPMENT ANALYSIS APPROACH

2019 ◽  
Vol 17 (9) ◽  
Author(s):  
Nor Nazihah Chuweni
Keyword(s):  
Data Envelopment Analysis ◽  
Real Estate ◽  
Technical Efficiency ◽  
Economies Of Scale ◽  
Efficient Frontier ◽  
Data Envelopment ◽  
Real Estate Investment ◽  
Nonparametric Approach ◽  
Efficiency Measures ◽  
Efficiency Performance

The research examines the technical efficiency (TE) and economies of scale for the Malaysian Real Estate Investment Trust (M-REITs) from 2010 to 2014, using a non-parametric approach of Data Envelopment Analysis (DEA). The nonparametric approach of Variable Return to Scale DEA (VRS-DEA model) was used to estimate the efficiency scores for M-REITs. The negative inefficient value for the technical inefficiencies is identified as a result of both poor input utilisation (managerial inefficiency) and failure of M-REITs to operate at optimum scale (scale inefficiency). The mean technical efficiency (TE) measures ranged from as low as 41.70% in 2011 to as high as 84.30% in 2014. Despite having the Sharia requirement, Islamic REITs in Malaysia provide an effective investment opportunity evidenced by the higher scores for all efficiency measures, as compared to conventional REITs for the period under study. Pure technical inefficiency has a greater deviation in the efficient frontier than scale inefficiency, suggesting that M-REITs inputs are not fully minimised to produce more outputs. With regard to scale inefficiency, M-REITs are operating at economies of scale, indicating the importance of expansion or growth to improve on efficiency performance. This will then allow M-REIT managers to formulate better strategic investment decisions.

Evaluation of Supplier Performance and Efficiency

2017 ◽  
pp. 184-216
Author(s):  
Chandra Sekhar Patro
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Efficient Frontier ◽  
Business Environment ◽  
Vital Role ◽  
Data Envelopment ◽  
Supplier Performance ◽  
Decision Making Units

In the present competitive business environment, it is essential for the management of any organisation to take wise decisions regarding supplier evaluation. It plays a vital role in establishing an effective supply chain for any organisation. Most of the experts agreed that there is no one best way to evaluate the suppliers and different organizations use different approaches for evaluating supplier efficiency. The overall objective of any approach is to reduce purchase risk and maximize overall value to the purchaser. In this paper Data Envelopment Analysis (DEA) technique is developed to evaluate the supplier efficiency for an organisation. DEA is a multifactor productivity technique to measure the relative efficiency of the decision making units. The super efficiency method of DEA provides a way, which indicates the extent to which the efficient suppliers exceed the efficient frontier formed by other efficient suppliers. A case study is undertaken to evaluate the supplier performance and efficiency using DEA approach.

scholarly journals Alternative Trade-Offs in Data Envelopment Analysis: An Application to Hydropower Plants

2016 ◽  
Vol 2016 ◽  
pp. 1-8
Author(s):  
Mohsen Mirzaei ◽  
Sohrab Kordrostami ◽  
Alireza Amirteimoori ◽  
Mehrdad G. Chegini
Keyword(s):  
Data Envelopment Analysis ◽  
Piecewise Linear ◽  
Extreme Points ◽  
Efficient Frontier ◽  
Data Envelopment ◽  
Frontier Point ◽  
Trade Offs ◽  
Hydropower Plants ◽  
Alternative Trade ◽  
Output Space

In multidimensional input/output space, the behavior of the firms can be analyzed by using efficient frontier or supporting surfaces of production technology. To this end, mathematicians are interested to use marginal rates of substitutions. The piecewise linear frontier of data envelopment analysis (DEA) technology is not differentiable at the extreme points and marginal rates calculation is valid only for small changes in one or more variables. The existing trade-off analysis methods calculate the maximum changes in a specific throughput when another throughput is changed. We will show that binding efficient supporting surfaces of an efficient point may be used to define different marginal rates of substitutions and in this sense, we get different marginal rates to each frontier point.

Restricted variation in data envelopment analysis with undesirable factors in nature

2015 ◽  
Vol 08 (03) ◽  
pp. 1550034 ◽  
Author(s):  
Sohrab Kordrostami ◽  
Alireza Amirteimoori ◽  
Monireh Jahani Sayyad Noveiri
Keyword(s):  
Data Envelopment Analysis ◽  
Efficient Frontier ◽  
Data Envelopment ◽  
Standard Data ◽  
Weak Disposability ◽  
Dea Models ◽  
Restricted Environment ◽  
Restricted Variation ◽  
Decision Making Units ◽  
Inputs And Outputs

In standard data envelopment analysis (DEA) models, inefficient decision-making units (DMUs) should change their inputs and outputs arbitrarily to meet the efficient frontier. However, in many real applications of DEA, because of some limitations in resources and DMU's ability, these variations cannot be made arbitrarily. Moreover, in some situations, undesirable factors with different disposability, strong or weak disposability, are found. In this paper, a DEA-based model is proposed to determine the relative efficiency of DMUs in such a restricted environment and in presence of undesirable factors. Indeed, variation levels of inputs and outputs are pre-defined and are considered to evaluate the performance of DMUs. Numerical examples are utilized to demonstrate the approach.

scholarly journals Novel models for obtaining the closest weak and strong efficient projections in data envelopment analysis

2021 ◽  
Vol 39 (5) ◽  
pp. 9-24
Author(s):  
Javad Vakili ◽  
Hanieh Amirmoshiri ◽  
Mir Kamal Mirnia
Keyword(s):  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Efficient Frontier ◽  
Data Envelopment ◽  
Nonparametric Method ◽  
Target Setting ◽  
Production Possibility ◽  
Production Possibility Set ◽  
And Performance ◽  
Decision Making Units

Data Envelopment Analysis (DEA) is a nonparametric method for measuring the relative efficiency and performance of Decision Making Units (DMUs). Traditionally, there are two issues regarding the DEA simultaneously i.e., the identification of a reference point on the efficient boundary of the production possibility set (PPS) and the use of some measures of distance from the unit under assessment to the efficient frontier. Due to its importance, in this paper, two alternative target setting models were developed to allow for lowefficient DMUs find the easiest way to improve its efficiency and reach to the efficient boundary. One seeks the closest weak efficient projection and the other suggests the most appropriate direction towards the strong efficient frontier surface. Both of these models provides the closest projection in one stage. Finally, a proposed problem is empirically checked by using a recent data related to 30 European airports.

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