Enhancing strategic roadmapping through the integration of topic modeling and generative AI

Detalhes bibliográficos
Ano de defesa: 2025
Autor(a) principal: André Magalhães Gomes
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Universidade Federal de Minas Gerais
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Inteligência artificial
Processamento da linguagem natural (Computação)
Administração
Link de acesso: https://hdl.handle.net/1843/83547
Resumo: CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
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spelling 2025-07-14T16:52:03Z2025-09-09T01:00:08Z2025-07-14T16:52:03Z2025-05-28https://hdl.handle.net/1843/83547CNPq - Conselho Nacional de Desenvolvimento Científico e TecnológicoengUniversidade Federal de Minas GeraisStrategic RoadmappingNatural Language ProcessingLarge Language ModelsNeural Topic ModelingRetrieval Augmented GenerationGenerative AIInteligência artificialProcessamento da linguagem natural (Computação)AdministraçãoEnhancing strategic roadmapping through the integration of topic modeling and generative AIinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisAndré Magalhães Gomesinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGhttp://lattes.cnpq.br/4226121165174499Jonathan Simões Freitashttp://lattes.cnpq.br/5394006847919001Maicon Gouvea de OliveiraRobert PhaalYoungjung GeumTiago Alves Schieber de JesusLeydiana de Sousa PereiraContemporary strategic roadmapping practices are increasingly influenced by digitalization and artificial intelligence (AI), yet integrating advanced AI techniques into roadmapping processes remains limited. This thesis investigates how AI-augmented approaches, particularly neural topic modeling and generative AI, can enhance strategic roadmapping. The research begins with a comprehensive systematic review of literature dating back to the early 1980s, using bibliometrics and topic modeling to catalog the evolution of AI applications in roadmapping, revealing significant methodological advancements but also significant gaps in practical implementation. Addressing this research-practice gap, we developed and evaluated an innovative artifact that combines neural topic modeling with generative AI through Retrieval Augmented Generation (RAG) to extract strategically relevant insights for the pre-population phase of roadmapping while ensuring reliability through explicit grounding in source documents. The artifact evolved through two distinct applications: first, an initial proof-of-concept in the AgeTech domain that utilized BERTopic for clustering and topic labeling, demonstrating feasibility with 44% of final roadmap topics derived from quantitative analysis; second, an enhanced implementation incorporating RAG capabilities to produce topic-based reports with supporting scientific references. This refined artifact was applied in AgeTech and validated across eight live case studies, demonstrating how AI-generated topics can effectively augment the market, product, and technology layers of strategic roadmaps in real-world settings. Expert evaluations confirmed high reliability (98.7% of topics deemed reliable) and strategic relevance across different roadmapping contexts. The results demonstrate how AI-augmented roadmapping can enhance strategic foresight while maintaining the visual and collaborative strengths that make traditional roadmapping effective, enabling organizations to develop more comprehensive, evidence-based strategic roadmaps.https://orcid.org/0000-0002-2087-2071BrasilFACE - FACULDADE DE CIENCIAS ECONOMICASPrograma de Pós-Graduação em AdministraçãoUFMGORIGINALPhD_Thesis_Andre_Gomes.pdfapplication/pdf4278047https://repositorio.ufmg.br//bitstreams/b764a445-57fa-4253-b13d-196cdc47c9e1/downloada72c3fa0f19a6f9738e978cb46ebef9cMD51trueAnonymousREADLICENSElicense.txttext/plain2118https://repositorio.ufmg.br//bitstreams/b37e660a-94af-4d55-9d48-435483211ccc/downloadcda590c95a0b51b4d15f60c9642ca272MD52falseAnonymousREAD1843/835472025-09-08 22:00:08.894open.accessoai:repositorio.ufmg.br:1843/83547https://repositorio.ufmg.br/Repositório InstitucionalPUBhttps://repositorio.ufmg.br/oairepositorio@ufmg.bropendoar:2025-09-09T01:00:08Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)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
dc.title.none.fl_str_mv Enhancing strategic roadmapping through the integration of topic modeling and generative AI
title Enhancing strategic roadmapping through the integration of topic modeling and generative AI
spellingShingle Enhancing strategic roadmapping through the integration of topic modeling and generative AI
André Magalhães Gomes
Inteligência artificial
Processamento da linguagem natural (Computação)
Administração
Strategic Roadmapping
Natural Language Processing
Large Language Models
Neural Topic Modeling
Retrieval Augmented Generation
Generative AI
title_short Enhancing strategic roadmapping through the integration of topic modeling and generative AI
title_full Enhancing strategic roadmapping through the integration of topic modeling and generative AI
title_fullStr Enhancing strategic roadmapping through the integration of topic modeling and generative AI
title_full_unstemmed Enhancing strategic roadmapping through the integration of topic modeling and generative AI
title_sort Enhancing strategic roadmapping through the integration of topic modeling and generative AI
author André Magalhães Gomes
author_facet André Magalhães Gomes
author_role author
dc.contributor.author.fl_str_mv André Magalhães Gomes
dc.subject.por.fl_str_mv Inteligência artificial
Processamento da linguagem natural (Computação)
Administração
topic Inteligência artificial
Processamento da linguagem natural (Computação)
Administração
Strategic Roadmapping
Natural Language Processing
Large Language Models
Neural Topic Modeling
Retrieval Augmented Generation
Generative AI
dc.subject.other.none.fl_str_mv Strategic Roadmapping
Natural Language Processing
Large Language Models
Neural Topic Modeling
Retrieval Augmented Generation
Generative AI
description CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
publishDate 2025
dc.date.accessioned.fl_str_mv 2025-07-14T16:52:03Z
2025-09-09T01:00:08Z
dc.date.available.fl_str_mv 2025-07-14T16:52:03Z
dc.date.issued.fl_str_mv 2025-05-28
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 https://hdl.handle.net/1843/83547
url https://hdl.handle.net/1843/83547
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.publisher.none.fl_str_mv Universidade Federal de Minas Gerais
publisher.none.fl_str_mv Universidade Federal de Minas Gerais
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFMG
instname:Universidade Federal de Minas Gerais (UFMG)
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reponame_str Repositório Institucional da UFMG
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