Back to Search Start Over

Artificial Intelligence and Disruptive Technologies in Service Systems: A Bibliometric Analysis.

Authors :
Marques, P. Carmona
Reis, João
Santos, Ricardo
Source :
International Journal of Innovation & Technology Management; Nov2023, Vol. 20 Issue 7, p1-33, 33p
Publication Year :
2023

Abstract

Artificial intelligence (AI) is being used in our daily lives, in all situations and in particular those concerning service systems. However, there is an absence of the ability of the conceptual structure, thematic structure, intellectual structure, and research trends of AI and disruptive technologies in service systems. The main purpose of this study was to carry out a bibliometric analysis of the scientific production of AI and disruptive technologies in service systems based on Elsevier's Scopus database. To do so, keywords were chosen and then data outputs such as the number of published documents, top authors and citations, top journals, countries, and affiliations with the highest number of productions, and network analysis using R-based "biblioshiny" software. The main results showed the growing interest in the subject in the last five years, pointed out current themes and research trends, and revealed the intellectual structure of the field, namely the importance of smart services, cloud computing, and smart sustainable cities. The number of articles for this study reached 1,323, the growth rate has increased in the last five years and the main sources have been reported. China, South Korea and the USA were the leading countries on the subject, and the top 10 authors of influence showed. The word cloud and word growth were presented, as well as the co-citation clusters and co-occurrence network revealed important aspects, and finally the thematic map and the thematic evolution of the subject showed the important concepts. It is hoped that this research will supply future directions for researchers in the area while highlighting the potential of quantitative methods. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02198770
Volume :
20
Issue :
7
Database :
Complementary Index
Journal :
International Journal of Innovation & Technology Management
Publication Type :
Academic Journal
Accession number :
173273032
Full Text :
https://doi.org/10.1142/S0219877023300033