Use of iramuteq for content analysis based on descending hierarchical classification and correspondence factor analysis

Detalhes bibliográficos
Autor(a) principal: Mazieri, Marcos Rogério
Data de Publicação: 2023
Outros Autores: Quoniam, Luc Marie, Reymond, David, Cunha, Katia Cinara Tregnago
Tipo de documento: Artigo
Idioma: eng
Título da fonte: REMark - Revista Brasileira de Marketing
Texto Completo: https://periodicos.uninove.br/remark/article/view/21290
Resumo: Objective: To present content analysis based on descending hierarchical classification and factorial correspondence analysis as complementary and sequential techniques, with possible application in the area of innovation management.Method: Content analysis based on Computer-Aided Text Analysis (CATA) techniques using the IRAMUTEQ softwareOriginality/Relevance: The research paradigm usually influences the researcher's own knowledge bases and domain methodologies. Manual text analysis can eventually be attributed to the interpretivist paradigm and CATA techniques can eventually be attributed to the post-positivist paradigm, however, there seems to be no reason to make this distinction.Results: Presentation of a framework that demonstrates the technological choices of the most innovative companies in the world (Google, Apple and Amazon), common and different choices, among them.Theoretical/methodological contributions: Development of a method for analyzing the technological choices of the most innovative companies in the world, applying content analysis based on descending hierarchical classification and factorial analysis of correspondence in a sequential and complementary way.Social / management contributions: Decision-making for innovation management can be revised according to the technological choices presented. Competitive advantage has distinctiveness by nature. We demonstrate that it is not a problem to master the same technologies, that is, companies can have similar technological domains and still have different marketing approaches.
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spelling Use of iramuteq for content analysis based on descending hierarchical classification and correspondence factor analysisUso do iramuteq para análise de conteúdo baseada em classificação hierarquica descendente e análise fatorial de correspondênciaContent analysisdescending hierarchical classificationcorrespondence factorial analysispatentsinnovation managementdigital transformationIramuteqAnálise de conteúdoClassificação hierárquica descendenteAnálise fatorial de correspondênciaPatentesGestão da inovaçãoTransformação digitalIramuteqObjective: To present content analysis based on descending hierarchical classification and factorial correspondence analysis as complementary and sequential techniques, with possible application in the area of innovation management.Method: Content analysis based on Computer-Aided Text Analysis (CATA) techniques using the IRAMUTEQ softwareOriginality/Relevance: The research paradigm usually influences the researcher's own knowledge bases and domain methodologies. Manual text analysis can eventually be attributed to the interpretivist paradigm and CATA techniques can eventually be attributed to the post-positivist paradigm, however, there seems to be no reason to make this distinction.Results: Presentation of a framework that demonstrates the technological choices of the most innovative companies in the world (Google, Apple and Amazon), common and different choices, among them.Theoretical/methodological contributions: Development of a method for analyzing the technological choices of the most innovative companies in the world, applying content analysis based on descending hierarchical classification and factorial analysis of correspondence in a sequential and complementary way.Social / management contributions: Decision-making for innovation management can be revised according to the technological choices presented. Competitive advantage has distinctiveness by nature. We demonstrate that it is not a problem to master the same technologies, that is, companies can have similar technological domains and still have different marketing approaches.Objetivo:  Apresentar a análise de conteúdo baseada em classificação hierárquica descendente e a análise fatorial de correspondência como técnicas complementares e sequenciais, com possível aplicação na área de gestão da inovaçãoMétodo: Análise de conteúdo baseada em técnicas de Computer-Aided Text Analisys (CATA) por meio do software IRAMUTEQ.Originalidade/Relevância: O paradigma de pesquisa, normalmente influencia as próprias bases de conhecimento e metodologias de domínio do pesquisador. A análise de textos manual pode eventualmente ser atribuída ao paradigma interpretativista e as técnicas CATA podem ser eventualmente atribuídas ao paradigma pós-positivista, no entanto, não parece haver razão para fazer essa distinção.Resultados: Apresentação de framework que demonstra as escolhas tecnológicas das empresas mais inovadoras do mundo (Google, Apple e Amazon), as escolhas comuns e as distintas, entre elas.Contribuições teóricas/metodológicas: Desenvolvimento de método de análise de escolhas tecnológicas das empresas mais inovadoras do mundo, aplicando a análise de conteúdo com base na classificação hierárquica descendente e a análise fatorial de correspondência de forma sequencial e complementar.Contribuições sociais / para a gestão: As tomadas de decisões para a gestão da inovação podem ser revistas de acordo com as escolhas tecnológicas apresentadas. A vantagem competitiva tem por natureza a distintividade. Demonstramos que não é um problema dominar as mesmas tecnologias, ou seja, empresas podem ter domínios tecnológicos similares e ainda assim terem abordagens mercadológicas diferentes.Universidade Nove de Julho - Uninove2023-01-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.uninove.br/remark/article/view/2129010.5585/remark.v21i5.21290ReMark - Revista Brasileira de Marketing; v. 21 n. 5 (2022): (out.dez.); 1978-20482177-5184reponame:REMark - Revista Brasileira de Marketinginstname:Universidade Nove de Julho (UNINOVE)instacron:RBMenghttps://periodicos.uninove.br/remark/article/view/21290/10007Copyright (c) 2022 ReMark - Revista Brasileira de Marketinghttps://creativecommons.org/licenses/by-nc-sa/4.0info:eu-repo/semantics/openAccessMazieri, Marcos RogérioQuoniam, Luc MarieReymond, DavidCunha, Katia Cinara Tregnago2023-01-04T17:58:20Zoai:ojs.periodicos.uninove.br:article/21290Revistahttps://periodicos.uninove.br/remarkPRIhttps://periodicos.uninove.br/remark/oaiclaudiaraac@uol.com.br || admin@revistabrasileiramarketing.org || admin@revistabrasileiramarketing.org2177-51842177-5184opendoar:2023-01-04T17:58:20REMark - Revista Brasileira de Marketing - Universidade Nove de Julho (UNINOVE)false
dc.title.none.fl_str_mv Use of iramuteq for content analysis based on descending hierarchical classification and correspondence factor analysis
Uso do iramuteq para análise de conteúdo baseada em classificação hierarquica descendente e análise fatorial de correspondência
title Use of iramuteq for content analysis based on descending hierarchical classification and correspondence factor analysis
spellingShingle Use of iramuteq for content analysis based on descending hierarchical classification and correspondence factor analysis
Mazieri, Marcos Rogério
Content analysis
descending hierarchical classification
correspondence factorial analysis
patents
innovation management
digital transformation
Iramuteq
Análise de conteúdo
Classificação hierárquica descendente
Análise fatorial de correspondência
Patentes
Gestão da inovação
Transformação digital
Iramuteq
title_short Use of iramuteq for content analysis based on descending hierarchical classification and correspondence factor analysis
title_full Use of iramuteq for content analysis based on descending hierarchical classification and correspondence factor analysis
title_fullStr Use of iramuteq for content analysis based on descending hierarchical classification and correspondence factor analysis
title_full_unstemmed Use of iramuteq for content analysis based on descending hierarchical classification and correspondence factor analysis
title_sort Use of iramuteq for content analysis based on descending hierarchical classification and correspondence factor analysis
author Mazieri, Marcos Rogério
author_facet Mazieri, Marcos Rogério
Quoniam, Luc Marie
Reymond, David
Cunha, Katia Cinara Tregnago
author_role author
author2 Quoniam, Luc Marie
Reymond, David
Cunha, Katia Cinara Tregnago
author2_role author
author
author
dc.contributor.author.fl_str_mv Mazieri, Marcos Rogério
Quoniam, Luc Marie
Reymond, David
Cunha, Katia Cinara Tregnago
dc.subject.por.fl_str_mv Content analysis
descending hierarchical classification
correspondence factorial analysis
patents
innovation management
digital transformation
Iramuteq
Análise de conteúdo
Classificação hierárquica descendente
Análise fatorial de correspondência
Patentes
Gestão da inovação
Transformação digital
Iramuteq
topic Content analysis
descending hierarchical classification
correspondence factorial analysis
patents
innovation management
digital transformation
Iramuteq
Análise de conteúdo
Classificação hierárquica descendente
Análise fatorial de correspondência
Patentes
Gestão da inovação
Transformação digital
Iramuteq
description Objective: To present content analysis based on descending hierarchical classification and factorial correspondence analysis as complementary and sequential techniques, with possible application in the area of innovation management.Method: Content analysis based on Computer-Aided Text Analysis (CATA) techniques using the IRAMUTEQ softwareOriginality/Relevance: The research paradigm usually influences the researcher's own knowledge bases and domain methodologies. Manual text analysis can eventually be attributed to the interpretivist paradigm and CATA techniques can eventually be attributed to the post-positivist paradigm, however, there seems to be no reason to make this distinction.Results: Presentation of a framework that demonstrates the technological choices of the most innovative companies in the world (Google, Apple and Amazon), common and different choices, among them.Theoretical/methodological contributions: Development of a method for analyzing the technological choices of the most innovative companies in the world, applying content analysis based on descending hierarchical classification and factorial analysis of correspondence in a sequential and complementary way.Social / management contributions: Decision-making for innovation management can be revised according to the technological choices presented. Competitive advantage has distinctiveness by nature. We demonstrate that it is not a problem to master the same technologies, that is, companies can have similar technological domains and still have different marketing approaches.
publishDate 2023
dc.date.none.fl_str_mv 2023-01-04
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.uninove.br/remark/article/view/21290
10.5585/remark.v21i5.21290
url https://periodicos.uninove.br/remark/article/view/21290
identifier_str_mv 10.5585/remark.v21i5.21290
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.uninove.br/remark/article/view/21290/10007
dc.rights.driver.fl_str_mv Copyright (c) 2022 ReMark - Revista Brasileira de Marketing
https://creativecommons.org/licenses/by-nc-sa/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2022 ReMark - Revista Brasileira de Marketing
https://creativecommons.org/licenses/by-nc-sa/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Nove de Julho - Uninove
publisher.none.fl_str_mv Universidade Nove de Julho - Uninove
dc.source.none.fl_str_mv ReMark - Revista Brasileira de Marketing; v. 21 n. 5 (2022): (out.dez.); 1978-2048
2177-5184
reponame:REMark - Revista Brasileira de Marketing
instname:Universidade Nove de Julho (UNINOVE)
instacron:RBM
instname_str Universidade Nove de Julho (UNINOVE)
instacron_str RBM
institution RBM
reponame_str REMark - Revista Brasileira de Marketing
collection REMark - Revista Brasileira de Marketing
repository.name.fl_str_mv REMark - Revista Brasileira de Marketing - Universidade Nove de Julho (UNINOVE)
repository.mail.fl_str_mv claudiaraac@uol.com.br || admin@revistabrasileiramarketing.org || admin@revistabrasileiramarketing.org
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