MOONA software for survey classification and evaluation of criteria to support decision-making for properties portfolio
The MOORA for Neural Networks Analysis (MONNA) software was created to classify variables and evaluate the degree of correlation between them, helping to choose a property portfolio and facilitating decision making involving multiple criteria. The MONNA software presents the classification of the a...
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doaj-53a54c13c87347abb586c1871f54185a2021-07-02T10:59:08ZengVilnius Gediminas Technical UniversityInternational Journal of Strategic Property Management1648-715X1648-91792020-05-0124410.3846/ijspm.2020.12338MOONA software for survey classification and evaluation of criteria to support decision-making for properties portfolioIsmael Cristofer Baierle0Jones Luis Schaefer1Miguel Afonso Sellitto2Leandro Pinto Fava3João Carlos Furtado4Elpidio Oscar Benitez Nara5Department of Production Engineering, Universidade Federal de Santa Maria, Av. Roraima, 1000, 950, 97.105-900, Santa Maria, RS, BrazilDepartment of Production Engineering, Universidade Federal de Santa Maria, Av. Roraima, 1000, 950, 97.105-900, Santa Maria, RS, BrazilDepartment of Production and Systems Engineering, University of Vale do Rio dos Sinos, Av. Unisinos, 950, 93.022-750, Sao Leopoldo, RS, BrazilDepartment of Industrial Systems and Process, University of Santa Cruz do Sul, Av. Independencia, 2293, 55 51 3717-7632, CEP: 96815-900 Santa Cruz do Sul, RS, BrazilDepartment of Industrial Systems and Process, University of Santa Cruz do Sul, Av. Independencia, 2293, 55 51 3717-7632, CEP: 96815-900 Santa Cruz do Sul, RS, BrazilDepartment of Industrial Systems and Process, University of Santa Cruz do Sul, Av. Independencia, 2293, 55 51 3717-7632, CEP: 96815-900 Santa Cruz do Sul, RS, Brazil The MOORA for Neural Networks Analysis (MONNA) software was created to classify variables and evaluate the degree of correlation between them, helping to choose a property portfolio and facilitating decision making involving multiple criteria. The MONNA software presents the classification of the alternatives calculated automatically by the MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) and provides a Global Average Rate (GAR). Artificial Neural Networks (ANNs) analysis provides the degree of correlation between variables and uses GAR as the output parameter. The degree of correlation between the variables allows us to assess whether these variables are dependent on each other and can capture customer preferences. For the application we used a survey that sought to know the preferences of customers, which will serve to make the decision of which properties should be part of the company’s portfolio. The contribution and originality of the MONNA software is that through the integration of the MOORA and ANN methods, the classification and criterion evaluation calculations are faster and standardized. The use of software by decision makers helps to have more accurately find and classify available options, preventing simulations from being done by iterative processes and providing validated numerical data for management evaluation. https://www.bme.vgtu.lt/index.php/IJSPM/article/view/12338MOORAMONNAartificial neural networkdecision-makingcriteria evaluationproperties portfolio |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ismael Cristofer Baierle Jones Luis Schaefer Miguel Afonso Sellitto Leandro Pinto Fava João Carlos Furtado Elpidio Oscar Benitez Nara |
spellingShingle |
Ismael Cristofer Baierle Jones Luis Schaefer Miguel Afonso Sellitto Leandro Pinto Fava João Carlos Furtado Elpidio Oscar Benitez Nara MOONA software for survey classification and evaluation of criteria to support decision-making for properties portfolio International Journal of Strategic Property Management MOORA MONNA artificial neural network decision-making criteria evaluation properties portfolio |
author_facet |
Ismael Cristofer Baierle Jones Luis Schaefer Miguel Afonso Sellitto Leandro Pinto Fava João Carlos Furtado Elpidio Oscar Benitez Nara |
author_sort |
Ismael Cristofer Baierle |
title |
MOONA software for survey classification and evaluation of criteria to support decision-making for properties portfolio |
title_short |
MOONA software for survey classification and evaluation of criteria to support decision-making for properties portfolio |
title_full |
MOONA software for survey classification and evaluation of criteria to support decision-making for properties portfolio |
title_fullStr |
MOONA software for survey classification and evaluation of criteria to support decision-making for properties portfolio |
title_full_unstemmed |
MOONA software for survey classification and evaluation of criteria to support decision-making for properties portfolio |
title_sort |
moona software for survey classification and evaluation of criteria to support decision-making for properties portfolio |
publisher |
Vilnius Gediminas Technical University |
series |
International Journal of Strategic Property Management |
issn |
1648-715X 1648-9179 |
publishDate |
2020-05-01 |
description |
The MOORA for Neural Networks Analysis (MONNA) software was created to classify variables and evaluate the degree of correlation between them, helping to choose a property portfolio and facilitating decision making involving multiple criteria. The MONNA software presents the classification of the alternatives calculated automatically by the MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) and provides a Global Average Rate (GAR). Artificial Neural Networks (ANNs) analysis provides the degree of correlation between variables and uses GAR as the output parameter. The degree of correlation between the variables allows us to assess whether these variables are dependent on each other and can capture customer preferences. For the application we used a survey that sought to know the preferences of customers, which will serve to make the decision of which properties should be part of the company’s portfolio. The contribution and originality of the MONNA software is that through the integration of the MOORA and ANN methods, the classification and criterion evaluation calculations are faster and standardized. The use of software by decision makers helps to have more accurately find and classify available options, preventing simulations from being done by iterative processes and providing validated numerical data for management evaluation.
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topic |
MOORA MONNA artificial neural network decision-making criteria evaluation properties portfolio |
url |
https://www.bme.vgtu.lt/index.php/IJSPM/article/view/12338 |
work_keys_str_mv |
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