Bibliometric analysis of agile methods and artificial intelligence

• Autor(a) principal: Harras, Lucas Martins
• Data de Publicação: 2023
• Tipo de documento: Trabalho de conclusão de curso
• Idioma: eng
• Título da fonte: Repositório Institucional da UFRGS
• Texto Completo: http://hdl.handle.net/10183/271696
• topic: Simpósio de Engenharia de Produção (; Inteligência artificial; Análise bibliométrica e sistemática; Agile method; Artificial intelligence; Bibliometric analysis

This study conducts a comprehensive bibliometric analysis to evaluate the trends, impact, and global contributions of academic articles focusing on agile methodologies and Artificial Intelligence (AI). For this, it used the Scopus’ database of articles, and Bibliometrix, a Rstudio package to visualize data. Utilizing metrics such as “Total Citations” and “TC per Year,” the study provides insights into the influence and significance of individual papers in the field. The findings indicate a substantial increase in research production, especially from countries like the United States, Italy, and India, demonstrating a dynamic and evolving international academic landscape. Notably, emerging countries like Pakistan have also become contributors in recent years. The study also identifies a shift in research focus towards AI and agile methodologies, that could be justified with the recent expansion of Industry 4.0 studies. Articles by key authors, such as Meinert E (2020) and Hayat F (2019), have demonstrated considerable impact within a short time frame, highlighting the rapidly evolving nature of the field. This study serves as a resource for researchers, and industry professionals looking to understand the current state and future directions of academic research in agile methodologies and AI.