Bavaresco, R. S., Nesi, L. C., Victória Barbosa, J. L., Antunes, R. S., da Rosa Righi, R., da Costa, C. A., Vanzin, M., Dornelles, D., Junior, S. C., Gatti, C., Ferreira, M., Silva, E., & Moreira, C. (2023). Machine learning-based automation of accounting services: An exploratory case study. International Journal of Accounting Information Systems, 49. https://doi.org/10.1016/j.accinf.2023.100618
ISO-690 (author-date, English)BAVARESCO, Rodrigo Simon, NESI, Luan Carlos, VICTÓRIA BARBOSA, Jorge Luis, ANTUNES, Rodolfo Stoffel, DA ROSA RIGHI, Rodrigo, DA COSTA, Cristiano André, VANZIN, Mariangela, DORNELLES, Daniel, JUNIOR, Saint Clair, GATTI, Clauter, FERREIRA, Mateus, SILVA, Elton und MOREIRA, Carlos, 2023. Machine learning-based automation of accounting services: An exploratory case study. International Journal of Accounting Information Systems. 1 Juni 2023. Vol. 49, , . DOI 10.1016/j.accinf.2023.100618.
Modern Language Association 9th editionBavaresco, R. S., L. C. Nesi, J. L. Victória Barbosa, R. S. Antunes, R. da Rosa Righi, C. A. da Costa, M. Vanzin, D. Dornelles, S. C. Junior, C. Gatti, M. Ferreira, E. Silva, und C. Moreira. „Machine Learning-Based Automation of Accounting Services: An Exploratory Case Study“. International Journal of Accounting Information Systems, Bd. 49, Juni 2023, https://doi.org/10.1016/j.accinf.2023.100618.
Mohr Siebeck - Recht (Deutsch - Österreich)Bavaresco, Rodrigo Simon/Nesi, Luan Carlos/Victória Barbosa, Jorge Luis/Antunes, Rodolfo Stoffel/da Rosa Righi, Rodrigo/da Costa, Cristiano André u. a.: Machine learning-based automation of accounting services: An exploratory case study, International Journal of Accounting Information Systems 2023,
Emerald - HarvardBavaresco, R.S., Nesi, L.C., Victória Barbosa, J.L., Antunes, R.S., da Rosa Righi, R., da Costa, C.A., Vanzin, M., Dornelles, D., Junior, S.C., Gatti, C., Ferreira, M., Silva, E. und Moreira, C. (2023), „Machine learning-based automation of accounting services: An exploratory case study“, International Journal of Accounting Information Systems, Vol. 49, verfügbar unter:https://doi.org/10.1016/j.accinf.2023.100618.