THE SELECTION OF PROJECTS WITHIN CONSTRAINED RESOURCES USING STOCHASTIC DATA ENVELOPMENT ANALYSIS

This study aims to evaluate the level of technical efficiency of companies that perform the integrated management of basic sanitation in Brazilian municipalities. A Multiple Data Envelopment Analysis (M-DEA) model was applied to estimate the performance of water supply and sewage services in 1628 municipalities covering more than 56% of the Brazilian population, identifying the factors that most influence the efficiency of the sector in the years 2008 and 2016. The M-DEA methodology is an extension of Data Envelopment Analysis (DEA) with multiple DEA executions considering all combinations of inputs and outputs to calculate efficiency scores. The methodology reduces possible biases in the selection of resources and products of the model, ability to support decision-making in favor of improvements in the sector′s efficiency based on national regulatory framework. The analyses show that the companies analyzed can increase their operating results and attendance coverage by more than 60%, given the current levels of infrastructure, human and financial resources in the sector. Based on the simulation of potential efficiency gains in Brazilian basic sanitation companies, the estimates show that the coverage of the population with access to sanitary sewage would go from the current 59.9% to 76.5%. The evidence found provides indications to subsidize sanitation management in the country at the micro-analytical level, enabling a better competitive position in the sector for the integrated management of basic sanitation and its universalization in Brazil.

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Developing a new chance-constrained data envelopment analysis in the presence of stochastic data

International Journal of Business Excellence ◽

10.1504/ijbex.2012.046638 ◽

2012 ◽

Vol 5 (3) ◽

pp. 169 ◽

Cited By ~ 2

Author(s):

Ehsan Momeni ◽

Reza Farzipoor Saen

Keyword(s):

Data Envelopment Analysis ◽

Data Envelopment ◽

Stochastic Data

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Performance analysis and optimal temperature selection of ethylene cracking furnaces: A data envelopment analysis cross-model integrated analytic hierarchy process

Journal of Analytical and Applied Pyrolysis ◽

10.1016/j.jaap.2016.10.025 ◽

2016 ◽

Vol 122 ◽

pp. 35-44 ◽

Cited By ~ 15

Author(s):

Yongming Han ◽

Zhiqiang Geng ◽

Zun Wang ◽

Peng Mu

Keyword(s):

Data Envelopment Analysis ◽

Performance Analysis ◽

Analytic Hierarchy Process ◽

Data Envelopment ◽

Optimal Temperature ◽

Analytic Hierarchy ◽

Cross Model ◽

Temperature Selection ◽

Hierarchy Process ◽

Selection Of

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An optimistic-pessimistic DEA model based on game cross efficiency approach

RAIRO - Operations Research ◽

10.1051/ro/2019052 ◽

2020 ◽

Vol 54 (4) ◽

pp. 1215-1230

Author(s):

Mediha Örkcü ◽

Volkan Soner Özsoy ◽

H. Hasan Örkcü

Keyword(s):

Decision Making ◽

Data Envelopment Analysis ◽

Equilibrium Solution ◽

Data Envelopment ◽

Optimal Weights ◽

Discriminating Power ◽

Proposed Model ◽

Essential Problem ◽

Decision Making Units ◽

Selection Of

The ranking of the decision making units (DMUs) is an essential problem in data envelopment analysis (DEA). Numerous approaches have been proposed for fully ranking of units. Majority of these methods consider DMUs with optimistic approach, whereas their weaknesses are ignored. In this study, for fully ranking of the units, a modified optimistic–pessimistic approach, which is based on game cross efficiency idea is proposed. The proposed game like iterative optimistic-pessimistic DEA procedure calculates the efficiency scores according to weaknesses and strengths of units and is based on non-cooperative game. This study extends the optimistic-pessimistic DEA approach to obtain robust rank values for DMUs. The proposed approach yields Nash equilibrium solution, thus overcomes the problem of non-uniqueness of the DEA optimal weights that can possibly reduce the usefulness of cross efficiency. Finally, in order to verify the validity of the proposed model and to show the practicability of algorithm, we apply a real-world example for selection of industrial R&D projects. The proposed model can increase the discriminating power of DMUs and can fully rank the DMUs.

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New product concept selection: an integrated approach using data envelopment analysis (DEA) and conjoint analysis (CA)

International Journal of Engineering & Technology ◽

10.14419/ijet.v3i1.1635 ◽

2014 ◽

Vol 3 (1) ◽

pp. 44 ◽

Cited By ~ 6

Author(s):

SaEd M. Salhieh ◽

Mira Y. Al-Harris

Keyword(s):

Data Envelopment Analysis ◽

Conjoint Analysis ◽

Perceived Value ◽

New Product ◽

Data Envelopment ◽

Product Concept ◽

Customer Perceived Value ◽

Using Data ◽

Product Concepts ◽

Selection Of

New product concept development is considered to be a critical step and the main determinant for the success or failure of new product development. This paper introduces a new methodology for the evaluation and selection of new product concepts using Data Envelopment Analysis (DEA) and Conjoint Analysis (CA). The proposed methodology integrates customer perceived value of the new product concepts through the use of CA and uses this perceived value as a measure for the new concepts performance. In addition, the methodology takes into account the development burden that a company has to perform to bring the new concept into a state of market readiness. This development burden is estimated by determining two main factors, namely the burden to produce and the burden to sell the new product concept. The customer perceived value and the development burden are both used in DEA to evaluate the new product concepts resulting in the selection of the best product concept. The applicability of the proposed methodology is illustrated through a case study. Keywords: Product development, concept selection, data envelopment analysis, conjoint analysis.

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