Capacidades dinâmicas na hiperpersonalização: uma análise via modelagem de equações estruturais com clickstream
DOI:
https://doi.org/10.22277/rgo.v19i1.8724Palavras-chave:
Hiperpersonalização, Personalização digital, Capacidades dinâmicas, Visão Baseada em Recursos, ClickstreamResumo
Objetivo: Este estudo propõe e valida um modelo de mensuração da base da hiperpersonalização em ambientes digitais, operacionalizado por meio da análise de dados de clickstream de um e-commerce.
Método/abordagem: Fundamentado na Teoria da Visão Baseada em Recursos e na Teoria das Capacidades Dinâmicas, o estudo concebe os padrões de personalização digital observáveis como manifestações empíricas das capacidades organizacionais de aprendizado e reconfiguração baseadas em dados, fundamentos que constituem a base da hiperpersonalização mediada por IA generativa. O modelo empírico foi desenvolvido com registros públicos de navegação e transações, abrangendo mais de um ano de interações (2010–2011), período que antecede a popularização da IA generativa. Essa escolha permite isolar e mensurar fundamentos comportamentais e organizacionais das capacidades dinâmicas, livres do viés tecnológico. Utilizando Modelagem de Equações Estruturais, foram operacionalizados quatro indicadores comportamentais: intensidade de visualizações, diversidade de produtos, proporção de eventos de personalização e taxa de conversão, como proxies mensuráveis dos microfundamentos de sensing e seizing.
Principais Resultados: Os resultados confirmam validade fatorial, confiabilidade composta e coerência teórica com o construto proposto, evidenciando que padrões de interação digital contribuem para operacionalizar empiricamente dimensões estratégicas de adaptação, aprendizado e inovação.
Contribuições teóricas/práticas/sociais: O estudo demonstra que a mensuração empírica desses fundamentos comportamentais permite compreender a hiperpersonalização como manifestação empírica de capacidades dinâmicas digitais, oferecendo um instrumento replicável para diagnosticar a maturidade analítica em ecossistemas digitais.
Originalidade/relevância: Avança na literatura ao propor uma modelagem empírica da base da hiperpersonalização algorítmica a partir dos microfundamentos das capacidades dinâmicas digitais.
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