Artificial intelligence (AI) and machine learning (ML) are two related technologies in accounting and finance studies. This study maps the conceptual structure of AI and ML research with the aim of contributing to a better understanding of this research stream. A bibliometric analysis of 3,836 documents on ai and ML retrieved from the Web of Science database is conducted. The analysis of descriptive performance indicators identifies the main traits of the scientific debate about AI and ML in terms of publications, productive countries and sources. To map the conceptual structure of the dataset, the study performs a thematic evolution. The results highlight the growing academic interest in the research topic, especially in the past few years. The results of this study may provide scholars with a better understanding of AI and ML research in accounting and finance. This paper contributes to the field by providing an examination of the current state of the art of AI e ML research and identifying possible future research directions.

AI and ML in accounting and finance: a bibliometric review

Alessandra Belfiore
;
Corrado Cuccurullo;
2022

Abstract

Artificial intelligence (AI) and machine learning (ML) are two related technologies in accounting and finance studies. This study maps the conceptual structure of AI and ML research with the aim of contributing to a better understanding of this research stream. A bibliometric analysis of 3,836 documents on ai and ML retrieved from the Web of Science database is conducted. The analysis of descriptive performance indicators identifies the main traits of the scientific debate about AI and ML in terms of publications, productive countries and sources. To map the conceptual structure of the dataset, the study performs a thematic evolution. The results highlight the growing academic interest in the research topic, especially in the past few years. The results of this study may provide scholars with a better understanding of AI and ML research in accounting and finance. This paper contributes to the field by providing an examination of the current state of the art of AI e ML research and identifying possible future research directions.
2022
979-12-80153-30-2
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/490889
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact