Use of iramuteq for content analysis based on descending hierarchical classification and correspondence factor analysis
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , |
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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REMark - Revista Brasileira de Marketing |
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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 |
_version_ |
1799138639594127360 |