Análise de Competitividade no E-Commerce Brasileiro via Correlação Cruzada em Séries Temporais de Preços
Resumo
O comércio eletrônico brasileiro movimentou R$196,1 bilhões em 2023, impulsionado por estratégias de precificação dinâmica, como o price matching. No entanto, ainda são escassas abordagens quantitativas reprodutíveis para explorar padrões de influência temporal, como liderança e resposta, entre plataformas. Este trabalho combina correlação cruzada e janelas deslizantes como ferramenta exploratória para analisar esses padrões em séries temporais de preços. O estudo analisa dados reais de 30 produtos em 21 plataformas ao longo de 500 dias (441 mil registros). Os resultados revelam correlações não estacionárias, evidenciando comportamento sazonal e episódios compatíveis com liderança de preço.
Palavras-chave:
Séries Temporais de Preços, Correlação Cruzada, Precificação Dinâmica, Comércio Eletrônico, Análise de Competitividade
Referências
ABComm (2024). Crescimento do E-commerce Brasileiro. Technical report, [link].
Aparicio, D., Metzman, Z., e Rigobon, R. (2024). The pricing strategies of online grocery retailers. Quantitative Marketing and Economics, 22:1 – 21.
Bai, J., Choi, S. H., e Liao, Y. (2021). Feasible generalized least squares for panel data with cross-sectional and serial correlations. Empirical Economics, 60:309 – 326.
Bungert, M. (2003). Termination of Price Wars: A Signaling Approach. Deutscher Universitätsverlag.
Chen, L., Mislove, A., e Wilson, C. (2016). An empirical analysis of algorithmic pricing on amazon marketplace. In 25th International World Wide Web Conference, WWW 2016, WWW ’16, pages 1339 – 1349. International World Wide Web Conferences Steering Committee.
Chen, P., Zhao, R., Yan, Y., e Li, X. (2020). Promotional pricing and online business model choice in the presence of retail competition. Omega (United Kingdom), 94.
Faehnle, A. e Guidolin, M. (2021). Dynamic Pricing Recognition on E-Commerce Platforms with VAR Processes. Forecasting, 3:166 – 180.
Gerpott, T. J. e Berends, J. (2022). Competitive pricing on online markets: a literature review. Journal of Revenue and Pricing Management, 21:596 – 622.
González, X. e Miles-Touya, D. (2018). Price dispersion, chain heterogeneity, and search in online grocery markets. SERIEs, 9:115 – 139.
Hanspach, P., Sapi, G., e Wieting, M. (2024). Algorithms in the marketplace: An empirical analysis of automated pricing in e-commerce. Information Economics and Policy, 69.
Hyndman, R. J. e Athanasopoulos, G. (2018). Forecasting: principles and practice. OTexts.
Lock, R. H., Lock, P. F., Morgan, K. L., Lock, E. F., e Lock, D. F. (2020). Statistics: Unlocking the Power of Data. John Wiley & Sons.
Nalca, A., Ray, S., e Boyaci, T. (2018). Price Matching Strategy: Implications of Consumer Behaviour and Channel Structure.
Ogasawara, E., Salles, R., Porto, F., e Pacitti, E. (2025). Event Detection in Time Series. Synthesis Lectures on Data Management. Springer Nature Switzerland, Cham, 1 edition.
Rejón-Guardia, F. e Luna-Nevarez, C. (2017). “Showrooming” in Consumer Electronics Retailing: An Empirical Study. Journal of Internet Commerce, 16:174 – 201.
Sarwate, D. V. e Pursley, M. B. (1980). Crosscorrelation Properties of Pseudorandom and Related Sequences. Proceedings of the IEEE, 68:593 – 619.
Spann, M., Bertini, M., Koenigsberg, O., Zeithammer, R., Aparicio, D., Chen, Y., Fantini, F., Jin, G. Z., Morwitz, V. G., Popkowski Leszczyc, P., Vitorino, M. A., Williams, G. Y., e Yoo, H. (2025). Algorithmic pricing: Implications for marketing strategy and regulation. International Journal of Research in Marketing.
Wang, W. e Li, F. (2020). What determines online transaction price dispersion? Evidence from the largest online platform in China. Electronic Commerce Research and Applications, 42:100968.
Aparicio, D., Metzman, Z., e Rigobon, R. (2024). The pricing strategies of online grocery retailers. Quantitative Marketing and Economics, 22:1 – 21.
Bai, J., Choi, S. H., e Liao, Y. (2021). Feasible generalized least squares for panel data with cross-sectional and serial correlations. Empirical Economics, 60:309 – 326.
Bungert, M. (2003). Termination of Price Wars: A Signaling Approach. Deutscher Universitätsverlag.
Chen, L., Mislove, A., e Wilson, C. (2016). An empirical analysis of algorithmic pricing on amazon marketplace. In 25th International World Wide Web Conference, WWW 2016, WWW ’16, pages 1339 – 1349. International World Wide Web Conferences Steering Committee.
Chen, P., Zhao, R., Yan, Y., e Li, X. (2020). Promotional pricing and online business model choice in the presence of retail competition. Omega (United Kingdom), 94.
Faehnle, A. e Guidolin, M. (2021). Dynamic Pricing Recognition on E-Commerce Platforms with VAR Processes. Forecasting, 3:166 – 180.
Gerpott, T. J. e Berends, J. (2022). Competitive pricing on online markets: a literature review. Journal of Revenue and Pricing Management, 21:596 – 622.
González, X. e Miles-Touya, D. (2018). Price dispersion, chain heterogeneity, and search in online grocery markets. SERIEs, 9:115 – 139.
Hanspach, P., Sapi, G., e Wieting, M. (2024). Algorithms in the marketplace: An empirical analysis of automated pricing in e-commerce. Information Economics and Policy, 69.
Hyndman, R. J. e Athanasopoulos, G. (2018). Forecasting: principles and practice. OTexts.
Lock, R. H., Lock, P. F., Morgan, K. L., Lock, E. F., e Lock, D. F. (2020). Statistics: Unlocking the Power of Data. John Wiley & Sons.
Nalca, A., Ray, S., e Boyaci, T. (2018). Price Matching Strategy: Implications of Consumer Behaviour and Channel Structure.
Ogasawara, E., Salles, R., Porto, F., e Pacitti, E. (2025). Event Detection in Time Series. Synthesis Lectures on Data Management. Springer Nature Switzerland, Cham, 1 edition.
Rejón-Guardia, F. e Luna-Nevarez, C. (2017). “Showrooming” in Consumer Electronics Retailing: An Empirical Study. Journal of Internet Commerce, 16:174 – 201.
Sarwate, D. V. e Pursley, M. B. (1980). Crosscorrelation Properties of Pseudorandom and Related Sequences. Proceedings of the IEEE, 68:593 – 619.
Spann, M., Bertini, M., Koenigsberg, O., Zeithammer, R., Aparicio, D., Chen, Y., Fantini, F., Jin, G. Z., Morwitz, V. G., Popkowski Leszczyc, P., Vitorino, M. A., Williams, G. Y., e Yoo, H. (2025). Algorithmic pricing: Implications for marketing strategy and regulation. International Journal of Research in Marketing.
Wang, W. e Li, F. (2020). What determines online transaction price dispersion? Evidence from the largest online platform in China. Electronic Commerce Research and Applications, 42:100968.
Publicado
08/09/2026
Como Citar
DE CARVALHO, Pedro H. J.; STERNBERG, Alice; AMORIM, Myrna; RUBERG, Gabriela; SALLES, Rebecca; OGASAWARA, Eduardo.
Análise de Competitividade no E-Commerce Brasileiro via Correlação Cruzada em Séries Temporais de Preços. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 41. , 2026, São Carlos/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 791-797.
ISSN 2763-8979.
DOI: https://doi.org/10.5753/sbbd.2026.249346.
