Difusão do deep learning através do search trends: uma análise em nível de país

Autores

  • Carlos Takahashi Escola Superior de Propaganda e Marketing - ESPM, São Paulo, (Brasil)
  • Júlio César Bastos de Figueiredo Escola Superior de Propaganda e Marketing - ESPM, São Paulo, (Brasil)
  • José Eduardo Ricciardi Favaretto Escola Superior de Propaganda e Marketing - ESPM, São Paulo, (Brasil)

DOI:

https://doi.org/10.24023/FutureJournal/2175-5825/2023.v15i1.695

Palavras-chave:

Deep learning, Difusão de inovação, Search trend, Análise em nível de paí, BRICS, Google trends

Resumo

Objetivo: A teoria da difusão da inovação é a lente teórica discutida nesta pesquisa para analisar a difusão do tema deep learning nos países BRICS e OCDE. Como pouco foi desenvolvido para compreender a análise em nível de país e um tema como a própria inovação, esta pesquisa buscou preencher essa lacuna.

Originalidade/Valor: Esta pesquisa demonstra como é possível utilizar o Search Trends para analisar a difusão de uma temática, possibilitando a extensão da teoria da difusão da inovação para além da venda de produtos.

Métodos: O Google Trends foi usado para coletar dados e fornecer informações atualizadas e dois modelos estatísticos diferentes foram utilizados: clustering para identificar padrões na primeira análise, e o modelo de difusão de Bass, visando comparar países considerando o pico da curva, o coeficiente de inovação, e o coeficiente de imitação.

Resultados: Os achados desta pesquisa identificaram que a China é o país com maior coeficiente de inovação entre os membros do BRICS, e o Japão entre os membros da OCDE.

Conclusões: Este estudo trouxe tanto uma contribuição teórica, permitindo a ampliação da difusão de inovações que utilizam um tema como objeto de inovação, quanto uma implicação prática, possibilitando pesquisas de forma acessível e democrática.

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Biografia do Autor

Carlos Takahashi, Escola Superior de Propaganda e Marketing - ESPM, São Paulo, (Brasil)

PhD Candidate at Escola Superior de Propaganda e Marketing (ESPM) in São Paulo (Brazil). He holds a Master degree in Business Administration from Instituto de Ensino e Pesquisa (Insper). His research interests include Diffusion of Innovation, Business Innovation, Artificial Intelligence, Technology, and Innovation Management.

Júlio César Bastos de Figueiredo, Escola Superior de Propaganda e Marketing - ESPM, São Paulo, (Brasil)

Professor of the Masters and Doctorate Program in International Management at Escola Superior de Propaganda e Marketing (ESPM). He holds a Ph.D. in Nuclear Physics from the University of São Paulo (USP). His research interests include Business Modeling and Simulation, which deals with the study and application of mathematical modeling and computer simulation techniques, with the development of models to understand the phenomena of marketing and administration in the global environment.

José Eduardo Ricciardi Favaretto , Escola Superior de Propaganda e Marketing - ESPM, São Paulo, (Brasil)

Researcher and Professor in Innovation Diffusion and Data Science at Escola Superior de Propaganda e Marketing (ESPM) in São Paulo (Brazil). He holds a Ph.D. in Management Information Systems from Fundação Getulio Vargas (FGV EAESP). His research interests include Diffusion of Innovations, Artificial Intelligence in global markets, Data Science, technology and innovation management, big data analytics, and stage level measurement of information and communication technology (ICT) in organizations.

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Publicado

2023-03-24

Como Citar

Takahashi, C. K., Figueiredo, J. C. B. de, & Favaretto , J. E. R. . (2023). Difusão do deep learning através do search trends: uma análise em nível de país . Future Studies Research Journal: Trends and Strategies [FSRJ], 15(1), e0695. https://doi.org/10.24023/FutureJournal/2175-5825/2023.v15i1.695