ALGORITHM MODELING FOR CONSTRUCTING A CONCAVE EFFICIENT FRONTIER
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Pesquisa operacional (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382020000100204 |
Resumo: | ABSTRACT When analyzed from the perspective of one input and one output, the classic Data Envelop ment Analysis (DEA) model (known as BCC after its developers Banker, Charnes, and Cooper) presents an efficient frontier with “downward” concavity (convex), therefore delivering variable returns to scale. However, these returns show a decrease in marginal productivity as the number of inputs increases, that is, the frontier presents decreasing global returns to scale. Both the convex frontier (DEA BCC) and the concave frontier (“upward” concavity) present average productivities that vary along the curve; thus, the local returns to scale are variable. It is claimed that the two formats are complementary, and therefore both should be verified in the literature. Thus, this article proposes an algorithm capable of modeling an efficient frontier, for one input or one output, with increasing global returns to scale, whereby an increase in input causes an increase in marginal productivity. |
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ALGORITHM MODELING FOR CONSTRUCTING A CONCAVE EFFICIENT FRONTIERDEAalgorithmefficient frontierglobal returns to scaleABSTRACT When analyzed from the perspective of one input and one output, the classic Data Envelop ment Analysis (DEA) model (known as BCC after its developers Banker, Charnes, and Cooper) presents an efficient frontier with “downward” concavity (convex), therefore delivering variable returns to scale. However, these returns show a decrease in marginal productivity as the number of inputs increases, that is, the frontier presents decreasing global returns to scale. Both the convex frontier (DEA BCC) and the concave frontier (“upward” concavity) present average productivities that vary along the curve; thus, the local returns to scale are variable. It is claimed that the two formats are complementary, and therefore both should be verified in the literature. Thus, this article proposes an algorithm capable of modeling an efficient frontier, for one input or one output, with increasing global returns to scale, whereby an increase in input causes an increase in marginal productivity.Sociedade Brasileira de Pesquisa Operacional2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382020000100204Pesquisa Operacional v.40 2020reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/0101-7438.2020.040.00224070info:eu-repo/semantics/openAccessBenicio,JulianaMello,João Carlos Soares deeng2020-05-13T00:00:00Zoai:scielo:S0101-74382020000100204Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2020-05-13T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false |
dc.title.none.fl_str_mv |
ALGORITHM MODELING FOR CONSTRUCTING A CONCAVE EFFICIENT FRONTIER |
title |
ALGORITHM MODELING FOR CONSTRUCTING A CONCAVE EFFICIENT FRONTIER |
spellingShingle |
ALGORITHM MODELING FOR CONSTRUCTING A CONCAVE EFFICIENT FRONTIER Benicio,Juliana DEA algorithm efficient frontier global returns to scale |
title_short |
ALGORITHM MODELING FOR CONSTRUCTING A CONCAVE EFFICIENT FRONTIER |
title_full |
ALGORITHM MODELING FOR CONSTRUCTING A CONCAVE EFFICIENT FRONTIER |
title_fullStr |
ALGORITHM MODELING FOR CONSTRUCTING A CONCAVE EFFICIENT FRONTIER |
title_full_unstemmed |
ALGORITHM MODELING FOR CONSTRUCTING A CONCAVE EFFICIENT FRONTIER |
title_sort |
ALGORITHM MODELING FOR CONSTRUCTING A CONCAVE EFFICIENT FRONTIER |
author |
Benicio,Juliana |
author_facet |
Benicio,Juliana Mello,João Carlos Soares de |
author_role |
author |
author2 |
Mello,João Carlos Soares de |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Benicio,Juliana Mello,João Carlos Soares de |
dc.subject.por.fl_str_mv |
DEA algorithm efficient frontier global returns to scale |
topic |
DEA algorithm efficient frontier global returns to scale |
description |
ABSTRACT When analyzed from the perspective of one input and one output, the classic Data Envelop ment Analysis (DEA) model (known as BCC after its developers Banker, Charnes, and Cooper) presents an efficient frontier with “downward” concavity (convex), therefore delivering variable returns to scale. However, these returns show a decrease in marginal productivity as the number of inputs increases, that is, the frontier presents decreasing global returns to scale. Both the convex frontier (DEA BCC) and the concave frontier (“upward” concavity) present average productivities that vary along the curve; thus, the local returns to scale are variable. It is claimed that the two formats are complementary, and therefore both should be verified in the literature. Thus, this article proposes an algorithm capable of modeling an efficient frontier, for one input or one output, with increasing global returns to scale, whereby an increase in input causes an increase in marginal productivity. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382020000100204 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382020000100204 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0101-7438.2020.040.00224070 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Pesquisa Operacional |
publisher.none.fl_str_mv |
Sociedade Brasileira de Pesquisa Operacional |
dc.source.none.fl_str_mv |
Pesquisa Operacional v.40 2020 reponame:Pesquisa operacional (Online) instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO) instacron:SOBRAPO |
instname_str |
Sociedade Brasileira de Pesquisa Operacional (SOBRAPO) |
instacron_str |
SOBRAPO |
institution |
SOBRAPO |
reponame_str |
Pesquisa operacional (Online) |
collection |
Pesquisa operacional (Online) |
repository.name.fl_str_mv |
Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO) |
repository.mail.fl_str_mv |
||sobrapo@sobrapo.org.br |
_version_ |
1750318018441773056 |