Palavras-chave
Aplicações de tecnologia da informação
Otimização de processos de negócio
Inovação no modelo de gestão
PLS-SEM
Análise multigrupos
Mineração de processos
Como Citar
Resumo
Objetivo: Este estudo investiga como a transformação digital contribui para a inteligência competitiva organizacional, analisando as relações entre maturidade das aplicações de Tecnologia da Informação (TI), Otimização de Processos de Negócio (OPN) e Inovação no Modelo de Gestão (IMG). O objetivo é explicar como as capacidades digitais evoluem de ganhos operacionais para inteligência relevante à tomada de decisão estratégica.
Metodologia/abordagem: Adotou-se um desenho de métodos mistos com predominância quantitativa, combinando dados de survey e indicadores objetivos de desempenho de sistemas, obtidos junto a 362 empresas dos setores de manufatura, finanças, saúde e logística. Foram utilizados Modelagem de Equações Estruturais por Mínimos Quadrados Parciais (PLS-SEM), análise multigrupos e testes de mediação. Técnicas de process mining foram aplicadas para validar melhorias operacionais com base em dados de sistemas ERP e BPM.
Originalidade/Relevância: O estudo avança a literatura ao conceituar explicitamente a transformação digital como uma capacidade de inteligência competitiva, e não apenas como um fenômeno tecnológico ou de eficiência operacional. A integração entre maturidade em TI, processos e inovação gerencial preenche lacunas teóricas e empíricas relevantes.
Principais resultados: Os resultados indicam que a maturidade em TI exerce forte influência positiva sobre a otimização de processos e um efeito direto moderado sobre a inovação no modelo de gestão. A otimização de processos atua como mediadora parcial, evidenciando seu papel central na conversão de capacidades digitais em inteligência gerencial. Diferenças setoriais também foram identificadas.
Contribuições teóricas/metodológicas: O estudo propõe um framework empiricamente validado que conecta transformação digital e inteligência competitiva por meio de capacidades sequenciais. Metodologicamente, contribui ao integrar PLS-SEM, análise multigrupos e process mining, conectando dados operacionais à tomada de decisão estratégica.
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