Structural equation models with adaptive regression and construction ofan index to validate constructs used to distinguish the profiles of specialtycoffee consumers
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Tipo de documento: | Tese |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/55285 |
Resumo: | This work consists of presenting a new approach to Adaptive Linear Regression adapted to structural equation models and improving the index related to the Average Variance Extracted (AVE), given a plug-in approach, and replacing the error variances with the factor loadings of the estimated adaptive regressions. To do so, a Monte Carlo simulation study was performed considering scenarios with different numbers of outliers, which were generated by distributions with symmetry deviations and kurtosis excess. Sample sizes were defined as n=50, 100 and 200. In formative structural models and considering outliers generated either from symmetrical distributions or from multivariate log-normal distributions, the Adaptive Linear Regression modeling was found to be efficient in the different scenarios under analysis. Likewise, for models with specification errors, this method was proven to have low efficiency, as expected. Furthermore, constructs were elaborated with variables that could enable both the characterization and the distinction of individuals among the different groups of Brazilian specialty coffee consumers and that could provide different perspectives on the transition among them. The results made it possible to better distinguish the consumers and better characterize the proposed categories, thus contributing to the improvement and simplification of marketing strategies used by players in this market. In addition, the results also promoted the discussion on which factors stimulate the transition of an individual from an initial construct to another, and we showed that transitioning from regular consumers to enthusiasts is easier than moving from enthusiasts to specialists. |
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Structural equation models with adaptive regression and construction ofan index to validate constructs used to distinguish the profiles of specialtycoffee consumersModelos de equações estruturais com regressões adaptativas e construção de um índice para validação de construto com aplicações na discriminação de perfis de consumidores de cafés especiaisStructural equation modelsOutliersAdaptive linear regressionSpecialty coffeesConsumer behaviorModelos de equações estruturaisRegressão linear adaptativaCafés especiaisComportamento do consumidorEstatísticaThis work consists of presenting a new approach to Adaptive Linear Regression adapted to structural equation models and improving the index related to the Average Variance Extracted (AVE), given a plug-in approach, and replacing the error variances with the factor loadings of the estimated adaptive regressions. To do so, a Monte Carlo simulation study was performed considering scenarios with different numbers of outliers, which were generated by distributions with symmetry deviations and kurtosis excess. Sample sizes were defined as n=50, 100 and 200. In formative structural models and considering outliers generated either from symmetrical distributions or from multivariate log-normal distributions, the Adaptive Linear Regression modeling was found to be efficient in the different scenarios under analysis. Likewise, for models with specification errors, this method was proven to have low efficiency, as expected. Furthermore, constructs were elaborated with variables that could enable both the characterization and the distinction of individuals among the different groups of Brazilian specialty coffee consumers and that could provide different perspectives on the transition among them. The results made it possible to better distinguish the consumers and better characterize the proposed categories, thus contributing to the improvement and simplification of marketing strategies used by players in this market. In addition, the results also promoted the discussion on which factors stimulate the transition of an individual from an initial construct to another, and we showed that transitioning from regular consumers to enthusiasts is easier than moving from enthusiasts to specialists.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Este trabalho consiste na apresentação de uma nova abordagem de Regressão Linear Adaptativa (RLA) adaptada a modelos de equações estruturais e no aprimoramento do índice correspondente a variância média extraída, dada uma abordagem plug-in, substituindo as variâncias dos erros pelas cargas fatoriais das regressões adaptativas estimadas. Para tanto, realizouse um estudo de simulação Monte Carlo considerando cenários com diferentes concentrações de outliers, gerados por distribuições com desvios de simetria e excesso de curtose e tamanhos amostrais definidos como n= 50,100 e 200. Concluiu-se que, em modelos estruturais formativos, considerando outliers gerados a partir de distribuições simétricas ou da distribuição log-normal multivariada, o método RLA, apresentou boa eficiência para modelos corretamente especificados. Da mesma forma, para modelos com erros de especificação, foi evidenciado baixa eficiência desse método, sendo coerente com o que era esperado. Além disso, elaborouse construtos cujas variáveis possibilitassem a caracterização e distinção de indivíduos entre os diferentes grupos de consumidores brasileiros de cafés especiais e, fornecessem percepções sobre a transição entre eles. Os resultados permitiram uma melhoria na distinção dos consumidores e caracterização entre as categorias propostas, contribuindo para o aprimoramento e simplificação das estratégias de marketing realizadas pelos atores deste mercado. Além disso, incentivou-se a discussão sobre quais fatores estimulam a transição de um indivíduo de um construto inicial para um subsequente e demonstramos uma maior facilidade de transição dos indivíduos de consumidores regulares para entusiastas, do que de entusiastas para especialistas.Universidade Federal de LavrasPrograma de Pós-Graduação em Estatística e Experimentação AgropecuáriaUFLAbrasilDepartamento de EstatísticaCirillo, Marcelo ÂngeloCirilo, Eliandro RodriguesBarroso, Lúcia PereiraBastos, Ronaldo RochaFernandes, Tales JesusSantos, Patricia Mendes dos2022-10-17T20:52:17Z2022-10-17T20:52:17Z2021-10-042021-08-02info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfSANTOS, P. M. dos. Structural equation models with adaptive regression and construction ofan index to validate constructs used to distinguish the profiles of specialtycoffee consumers. 2021. 78 p. Tese (Doutorado em Estatística e Experimentação Agropecuária) – Universidade Federal de Lavras, Lavras, 2021.http://repositorio.ufla.br/jspui/handle/1/55285enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLA2023-05-11T15:41:56Zoai:localhost:1/55285Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2023-05-11T15:41:56Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Structural equation models with adaptive regression and construction ofan index to validate constructs used to distinguish the profiles of specialtycoffee consumers Modelos de equações estruturais com regressões adaptativas e construção de um índice para validação de construto com aplicações na discriminação de perfis de consumidores de cafés especiais |
title |
Structural equation models with adaptive regression and construction ofan index to validate constructs used to distinguish the profiles of specialtycoffee consumers |
spellingShingle |
Structural equation models with adaptive regression and construction ofan index to validate constructs used to distinguish the profiles of specialtycoffee consumers Santos, Patricia Mendes dos Structural equation models Outliers Adaptive linear regression Specialty coffees Consumer behavior Modelos de equações estruturais Regressão linear adaptativa Cafés especiais Comportamento do consumidor Estatística |
title_short |
Structural equation models with adaptive regression and construction ofan index to validate constructs used to distinguish the profiles of specialtycoffee consumers |
title_full |
Structural equation models with adaptive regression and construction ofan index to validate constructs used to distinguish the profiles of specialtycoffee consumers |
title_fullStr |
Structural equation models with adaptive regression and construction ofan index to validate constructs used to distinguish the profiles of specialtycoffee consumers |
title_full_unstemmed |
Structural equation models with adaptive regression and construction ofan index to validate constructs used to distinguish the profiles of specialtycoffee consumers |
title_sort |
Structural equation models with adaptive regression and construction ofan index to validate constructs used to distinguish the profiles of specialtycoffee consumers |
author |
Santos, Patricia Mendes dos |
author_facet |
Santos, Patricia Mendes dos |
author_role |
author |
dc.contributor.none.fl_str_mv |
Cirillo, Marcelo Ângelo Cirilo, Eliandro Rodrigues Barroso, Lúcia Pereira Bastos, Ronaldo Rocha Fernandes, Tales Jesus |
dc.contributor.author.fl_str_mv |
Santos, Patricia Mendes dos |
dc.subject.por.fl_str_mv |
Structural equation models Outliers Adaptive linear regression Specialty coffees Consumer behavior Modelos de equações estruturais Regressão linear adaptativa Cafés especiais Comportamento do consumidor Estatística |
topic |
Structural equation models Outliers Adaptive linear regression Specialty coffees Consumer behavior Modelos de equações estruturais Regressão linear adaptativa Cafés especiais Comportamento do consumidor Estatística |
description |
This work consists of presenting a new approach to Adaptive Linear Regression adapted to structural equation models and improving the index related to the Average Variance Extracted (AVE), given a plug-in approach, and replacing the error variances with the factor loadings of the estimated adaptive regressions. To do so, a Monte Carlo simulation study was performed considering scenarios with different numbers of outliers, which were generated by distributions with symmetry deviations and kurtosis excess. Sample sizes were defined as n=50, 100 and 200. In formative structural models and considering outliers generated either from symmetrical distributions or from multivariate log-normal distributions, the Adaptive Linear Regression modeling was found to be efficient in the different scenarios under analysis. Likewise, for models with specification errors, this method was proven to have low efficiency, as expected. Furthermore, constructs were elaborated with variables that could enable both the characterization and the distinction of individuals among the different groups of Brazilian specialty coffee consumers and that could provide different perspectives on the transition among them. The results made it possible to better distinguish the consumers and better characterize the proposed categories, thus contributing to the improvement and simplification of marketing strategies used by players in this market. In addition, the results also promoted the discussion on which factors stimulate the transition of an individual from an initial construct to another, and we showed that transitioning from regular consumers to enthusiasts is easier than moving from enthusiasts to specialists. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-10-04 2021-08-02 2022-10-17T20:52:17Z 2022-10-17T20:52:17Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
SANTOS, P. M. dos. Structural equation models with adaptive regression and construction ofan index to validate constructs used to distinguish the profiles of specialtycoffee consumers. 2021. 78 p. Tese (Doutorado em Estatística e Experimentação Agropecuária) – Universidade Federal de Lavras, Lavras, 2021. http://repositorio.ufla.br/jspui/handle/1/55285 |
identifier_str_mv |
SANTOS, P. M. dos. Structural equation models with adaptive regression and construction ofan index to validate constructs used to distinguish the profiles of specialtycoffee consumers. 2021. 78 p. Tese (Doutorado em Estatística e Experimentação Agropecuária) – Universidade Federal de Lavras, Lavras, 2021. |
url |
http://repositorio.ufla.br/jspui/handle/1/55285 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Lavras Programa de Pós-Graduação em Estatística e Experimentação Agropecuária UFLA brasil Departamento de Estatística |
publisher.none.fl_str_mv |
Universidade Federal de Lavras Programa de Pós-Graduação em Estatística e Experimentação Agropecuária UFLA brasil Departamento de Estatística |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFLA instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Repositório Institucional da UFLA |
collection |
Repositório Institucional da UFLA |
repository.name.fl_str_mv |
Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
nivaldo@ufla.br || repositorio.biblioteca@ufla.br |
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1807835149144948736 |