Deep learning diffusion by search trend: a country-level analysis


  • Carlos Kazunari 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)



Deep learning, Innovation diffusion, Search trend, Country-level analysis, BRICS, Google trends


Purpose: The theory of diffusion of innovation is the theoretical lens discussed in this research to analyze the diffusion of the deep learning theme in the BRICS and OECD countries. As little has been developed to understand country-level analysis and a theme such as innovation, this research sought to fill this gap.

Originality/Value: This research demonstrates how it is possible to use Search Trends to analyze the diffusion of a thematic, enabling the extension of the diffusion of innovation theory beyond the sale of products.

Methods: Google Trends was used for data collection and to provide up-to-date information, and two different statistical models were used: clustering to identify patterns in the first analysis, and the Bass diffusion model, aiming at comparing countries considering the curve peak, the innovation coefficient, and the imitation coefficient.

Results: The findings of this research identified that China has the highest innovation coefficient among the members of the BRICS and Japan among the members of the OECD.

Conclusions: This study brought both a theoretical contribution, allowing the expansion of the diffusion of innovations that use a theme as an object of innovation, as well as a practical implication, enabling research in an accessible and democratic way.


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Author Biographies

Carlos Kazunari 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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How to Cite

Takahashi, C. K., Figueiredo, J. C. B. de, & Favaretto , J. E. R. . (2023). Deep learning diffusion by search trend: a country-level analysis. Future Studies Research Journal: Trends and Strategies, 15(1), e0695.



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