BIBLIOMETRIC ANALYSIS OF FINANCIAL EDUCATION RESEARCH BASED ON SCIENTIFIC MAPS · ANÁLISIS BIBLIOMÉTRICO DE LA INVESTIGACIÓN EN EDUCACIÓN FINANCIERA BASADO EN MAPAS CIENTÍFICOS · Author · Abstract

The aim of this study is to carry out an analysis of the intellectual structure of the introduction of AI into finance, in the period from 1995 to 2023, using SciMAT v.1.1.04 software. The results indicate how research on the incorporation of AI in finance has grown significantly, which shows the evolution and importance of this area of research. Eight main topics were obtained in this area: bank, prediction, impact, decision, valuesstock, genetic algorithm, big data analysis, and social data analysis. This study shows us how the incorporation of AI can strongly support the analysis of different financial situations such as decision making or the prediction of movements.

Since the beginning of the research on the family business and rural economy, there has been a problem with the delimitation of the concepts. Given this problem, this study’s main objective was to identify and visualize the intellectual structure of these two issues through scientific maps. To meet this objective, an evaluation of scientific performance and production was carried out with bibliometric indicators to extract the main research topics around these two areas through an analysis of the co-occurrence of keywords with scientific maps. The results show that research on family businesses and rural economy is booming, especially on family businesses that have higher productivity and performance. Regarding the main topics studied regarding family businesses and the rural economy, a total of 16 main themes were detected, highlighting the topic of entrepreneurship. The study of land management in transboundary environments is a potential line of future research.