Text-Based Insights on Generative AI Applications in Economics and Business

Morteza Alaeddini (), Asgari Alireza and Shahab Ahmadi ()
Additional contact information
Morteza Alaeddini: ICN Business School, CEREFIGE - Centre Européen de Recherche en Economie Financière et Gestion des Entreprises - UL - Université de Lorraine
Asgari Alireza: UGA INP IAE - Grenoble Institut d'Administration des Entreprises - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes, CERAG - Centre d'études et de recherches appliquées à la gestion - UGA - Université Grenoble Alpes
Shahab Ahmadi: UGA - Université Grenoble Alpes

Post-Print from HAL

Abstract: This study provides a thorough bibliometric text-based analysis of generative artificial intelligence (GenAI) research in economics and business. Based on an analysis of 1,613 peer-reviewed articles from Scopus and Web of Science published between 2021 and 2025, the study uses co-occurrence networks, topic modelling and burst analysis to map the intellectual structure of GenAI literature. The key findings reveal GenAI to be a rapidly evolving and increasingly interdisciplinary field, with research hotspots in AI ethics, sentiment analysis, digital transformation, and higher education. Emerging trends include AI-assisted writing, consumer behaviour and strategic management applications. The study highlights the growing integration of GenAI in business functions and educational contexts, while also identifying ethical and methodological challenges. This work offers valuable insights for scholars, educators and practitioners seeking to understand the dynamic landscape and future directions of GenAI in business and economics.

Date: 2025
References: Add references at CitEc
Citations:

Published in International Journal of Generative Artificial Intelligence in Business, 2025, 1 (1), ⟨10.1504/IJGAIB.2025.10073998⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05356064

DOI: 10.1504/IJGAIB.2025.10073998

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().