Modelo de maturidade para o uso de Big Data Analytics em startups
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Tipo de documento: | Tese |
Idioma: | por |
Título da fonte: | Biblioteca Digital de Teses e Dissertações do UFSM |
Texto Completo: | http://repositorio.ufsm.br/handle/1/28625 |
Resumo: | With the advancement of internet use, the term startup became popular to designate innovative companies in their initial prospecting phase. In addition, the internet gathers a large amount of data which is constantly being generated from various sources, becoming Big Data. In this context, the new era of the data economy enables new disruptive business models based on the analysis of said data, which can be supported by startups. Amidst this, startups can use maturity models as a tool for selfassessment, which makes it possible to verify their preparation in incorporating data analysis into their business models. Given this scenario, this thesis sought to build a maturity model to evaluate and guide startups in their journey of using Big Data Analytics. In addition, the levels, dimensions, items and sub-items necessary for Big Data Analytics usage in startups were identified, and a Delphi debate panel was established on the elements necessary for Big Data Analytics usage in startups. This model was consolidated through the arguments and evaluations of the panel of experts and, then, the model behavior in the research field was analyzed via startups feedback during the application of the real model. For this, DRS - Design Science Research - was adopted as a research method. Thus, we used the nature of applied research through the generation of practical and prescriptive knowledge through the presentation of use feasibility. The research approach was qualitative and processoriented. Based on the DSR procedure, two literature reviews were performed. In a second moment, a field study with startups and the analysis of the thematic axes of EnAnpad outlined the class of problems. Thus, a maturity model was proposed through abductive reasoning and was submitted to the survey through the Delphi method. The outlined model evaluation took place during its practical application in startups of excellence in Big Data Analytics usage and, for the necessary adjustments, notes from the field were used and an interview with a specialist was carried out. A useful and applicable maturity model was then obtained to support the solution of the problem and, in addition to it, a calculation spreadsheet was built to automate the results. Also, an analysis of the theoretical development on the field, on the instrument and on the research object was presented. Furthermore, a non-linear and a helical maturity model were proposed. Thus, this study brought advances to the academic field and managerial contributions. |
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2023-04-11T20:57:15Z2023-04-11T20:57:15Z2023-02-15http://repositorio.ufsm.br/handle/1/28625With the advancement of internet use, the term startup became popular to designate innovative companies in their initial prospecting phase. In addition, the internet gathers a large amount of data which is constantly being generated from various sources, becoming Big Data. In this context, the new era of the data economy enables new disruptive business models based on the analysis of said data, which can be supported by startups. Amidst this, startups can use maturity models as a tool for selfassessment, which makes it possible to verify their preparation in incorporating data analysis into their business models. Given this scenario, this thesis sought to build a maturity model to evaluate and guide startups in their journey of using Big Data Analytics. In addition, the levels, dimensions, items and sub-items necessary for Big Data Analytics usage in startups were identified, and a Delphi debate panel was established on the elements necessary for Big Data Analytics usage in startups. This model was consolidated through the arguments and evaluations of the panel of experts and, then, the model behavior in the research field was analyzed via startups feedback during the application of the real model. For this, DRS - Design Science Research - was adopted as a research method. Thus, we used the nature of applied research through the generation of practical and prescriptive knowledge through the presentation of use feasibility. The research approach was qualitative and processoriented. Based on the DSR procedure, two literature reviews were performed. In a second moment, a field study with startups and the analysis of the thematic axes of EnAnpad outlined the class of problems. Thus, a maturity model was proposed through abductive reasoning and was submitted to the survey through the Delphi method. The outlined model evaluation took place during its practical application in startups of excellence in Big Data Analytics usage and, for the necessary adjustments, notes from the field were used and an interview with a specialist was carried out. A useful and applicable maturity model was then obtained to support the solution of the problem and, in addition to it, a calculation spreadsheet was built to automate the results. Also, an analysis of the theoretical development on the field, on the instrument and on the research object was presented. Furthermore, a non-linear and a helical maturity model were proposed. Thus, this study brought advances to the academic field and managerial contributions.Com o avanço do uso da internet, popularizou-se o termo startup para designar empresas inovadoras em fase inicial de prospecção. Além disso, a internet reúne uma grande quantidade dados que vêm sendo constantemente gerados a partir de diversas fontes, tornando-se Big Data. Nesse contexto, a nova era da economia de dados possibilita novos modelos de negócios disruptivos embasados na análise desses dados, o que pode ser apoiado por startups. Em meio a isso, as startups podem utilizar modelos de maturidade como ferramenta para autoavaliação, o que possibilita verificar a sua preparação em incorporar análise de dados aos seus modelos de negócio. Diante desse cenário, a presente tese buscou construir um modelo de maturidade para avaliar e orientar startups em sua jornada de uso de Big Data Analytics. Para além, identificaram-se os níveis, as dimensões, os itens e subitens necessários ao uso de Big Data Analytics nas startups, bem como estabeleceu-se um painel de debate Delphi sobre os elementos necessários ao uso de Big Data Analytics nas startups. Esse modelo foi consolidado através dos argumentos e avaliações do painel de especialistas e, então, o comportamento do modelo no campo de pesquisa foi analisado através do retorno das startups durante a aplicação do modelo real. Para tal, adotou-se DRS - Design Science Research - como método de pesquisa. Desse modo, trabalhou-se com natureza de pesquisa aplicada por meio da geração de conhecimento prático e prescritivo através da apresentação de viabilidade de utilização. A abordagem da pesquisa foi qualitativa e orientada ao processo. Com base no procedimento do DSR, realizaram-se duas revisões de literatura. Em um segundo momento, um estudo de campo com startups e a análise dos eixos temáticos do EnAnpad delineou a classe de problemas. Assim, um modelo de maturidade foi proposto por meio de um raciocínio abdutivo e foi submetido ao levantamento através do método Delphi. A avaliação do modelo esboçado ocorreu com a aplicação prática em startups de excelência em uso de Big Data Analytics e, para os ajustes necessários, foram utilizados os apontamentos do campo e foi realizada uma entrevista com especialista. Obteve-se, então, um modelo de maturidade útil e aplicável para apoiar a solução do problema e, além dele, construiu-se uma planilha de cálculo para a automatização dos resultados. Também, apresentou-se uma análise do desenvolvimento teórico sobre o campo, sobre o instrumento e sobre o objeto de pesquisa. Outrossim, foram propostos um modelo de maturidade não-linear e outro helicoidal. Desse modo, este estudo trouxe avanços para o campo acadêmico e contribuições gerenciais.porUniversidade Federal de Santa MariaCentro de Ciências Sociais e HumanasPrograma de Pós-Graduação em AdministraçãoUFSMBrasilAdministraçãoAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessBig Data AnalyticsStartupsStartups businessMaturity modelModelo de maturidadeCNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAOModelo de maturidade para o uso de Big Data Analytics em startupsMaturity model for statups companies Big Data Analyticsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisBobsin, Deborahttp://lattes.cnpq.br/9741757650191659Dresch, AlineBorchardt, MiriamSimonetto, Eugênio de OliveiraLöbler, Mauri Leodirhttp://lattes.cnpq.br/5114024839768228Romio, Alexsandra Matos6002000000066006006006006006006005fd9695e-cd07-42c4-a77e-a3de3a43668523a829fb-f6c7-4673-be6d-c340c6c03088a7f115e2-e4f1-4cf7-b866-d55fe8030d50f894ea3a-7c39-4a15-b499-f671804871c2a283824c-1503-461f-af8c-43ef532289214f2dcd77-bb6c-40a4-a72d-dfbea72785b5reponame:Biblioteca Digital de Teses e Dissertações do UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALTES_ADMINISTRAÇÃO_2023_ROMIO_ALEXSANDRA.pdfTES_ADMINISTRAÇÃO_2023_ROMIO_ALEXSANDRA.pdfTese de doutoradoapplication/pdf10998844http://repositorio.ufsm.br/bitstream/1/28625/1/TES_ADMINISTRA%c3%87%c3%83O_2023_ROMIO_ALEXSANDRA.pdf75dbd3941dd62ae0ec06429a79197f10MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805http://repositorio.ufsm.br/bitstream/1/28625/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81956http://repositorio.ufsm.br/bitstream/1/28625/3/license.txt2f0571ecee68693bd5cd3f17c1e075dfMD531/286252023-04-11 17:57:15.7oai:repositorio.ufsm.br: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 Digital de Teses e Dissertaçõeshttps://repositorio.ufsm.br/ONGhttps://repositorio.ufsm.br/oai/requestatendimento.sib@ufsm.br||tedebc@gmail.comopendoar:2023-04-11T20:57:15Biblioteca Digital de Teses e Dissertações do UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.por.fl_str_mv |
Modelo de maturidade para o uso de Big Data Analytics em startups |
dc.title.alternative.eng.fl_str_mv |
Maturity model for statups companies Big Data Analytics |
title |
Modelo de maturidade para o uso de Big Data Analytics em startups |
spellingShingle |
Modelo de maturidade para o uso de Big Data Analytics em startups Romio, Alexsandra Matos Big Data Analytics Startups Startups business Maturity model Modelo de maturidade CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO |
title_short |
Modelo de maturidade para o uso de Big Data Analytics em startups |
title_full |
Modelo de maturidade para o uso de Big Data Analytics em startups |
title_fullStr |
Modelo de maturidade para o uso de Big Data Analytics em startups |
title_full_unstemmed |
Modelo de maturidade para o uso de Big Data Analytics em startups |
title_sort |
Modelo de maturidade para o uso de Big Data Analytics em startups |
author |
Romio, Alexsandra Matos |
author_facet |
Romio, Alexsandra Matos |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Bobsin, Debora |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/9741757650191659 |
dc.contributor.referee1.fl_str_mv |
Dresch, Aline |
dc.contributor.referee2.fl_str_mv |
Borchardt, Miriam |
dc.contributor.referee3.fl_str_mv |
Simonetto, Eugênio de Oliveira |
dc.contributor.referee4.fl_str_mv |
Löbler, Mauri Leodir |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/5114024839768228 |
dc.contributor.author.fl_str_mv |
Romio, Alexsandra Matos |
contributor_str_mv |
Bobsin, Debora Dresch, Aline Borchardt, Miriam Simonetto, Eugênio de Oliveira Löbler, Mauri Leodir |
dc.subject.eng.fl_str_mv |
Big Data Analytics Startups Startups business Maturity model |
topic |
Big Data Analytics Startups Startups business Maturity model Modelo de maturidade CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO |
dc.subject.por.fl_str_mv |
Modelo de maturidade |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO |
description |
With the advancement of internet use, the term startup became popular to designate innovative companies in their initial prospecting phase. In addition, the internet gathers a large amount of data which is constantly being generated from various sources, becoming Big Data. In this context, the new era of the data economy enables new disruptive business models based on the analysis of said data, which can be supported by startups. Amidst this, startups can use maturity models as a tool for selfassessment, which makes it possible to verify their preparation in incorporating data analysis into their business models. Given this scenario, this thesis sought to build a maturity model to evaluate and guide startups in their journey of using Big Data Analytics. In addition, the levels, dimensions, items and sub-items necessary for Big Data Analytics usage in startups were identified, and a Delphi debate panel was established on the elements necessary for Big Data Analytics usage in startups. This model was consolidated through the arguments and evaluations of the panel of experts and, then, the model behavior in the research field was analyzed via startups feedback during the application of the real model. For this, DRS - Design Science Research - was adopted as a research method. Thus, we used the nature of applied research through the generation of practical and prescriptive knowledge through the presentation of use feasibility. The research approach was qualitative and processoriented. Based on the DSR procedure, two literature reviews were performed. In a second moment, a field study with startups and the analysis of the thematic axes of EnAnpad outlined the class of problems. Thus, a maturity model was proposed through abductive reasoning and was submitted to the survey through the Delphi method. The outlined model evaluation took place during its practical application in startups of excellence in Big Data Analytics usage and, for the necessary adjustments, notes from the field were used and an interview with a specialist was carried out. A useful and applicable maturity model was then obtained to support the solution of the problem and, in addition to it, a calculation spreadsheet was built to automate the results. Also, an analysis of the theoretical development on the field, on the instrument and on the research object was presented. Furthermore, a non-linear and a helical maturity model were proposed. Thus, this study brought advances to the academic field and managerial contributions. |
publishDate |
2023 |
dc.date.accessioned.fl_str_mv |
2023-04-11T20:57:15Z |
dc.date.available.fl_str_mv |
2023-04-11T20:57:15Z |
dc.date.issued.fl_str_mv |
2023-02-15 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
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doctoralThesis |
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publishedVersion |
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http://repositorio.ufsm.br/handle/1/28625 |
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http://repositorio.ufsm.br/handle/1/28625 |
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por |
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por |
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600200000006 |
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600 600 600 600 600 600 600 |
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Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
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Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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openAccess |
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Universidade Federal de Santa Maria Centro de Ciências Sociais e Humanas |
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Programa de Pós-Graduação em Administração |
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UFSM |
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Brasil |
dc.publisher.department.fl_str_mv |
Administração |
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Universidade Federal de Santa Maria Centro de Ciências Sociais e Humanas |
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