TY - JOUR
T1 - Bibliometric review of research on decision models in uncertainty, 1990 - 2020
AU - Gil-Lafuente, Anna Maria
AU - De Paula, Luciano Barcellos
AU - De La Vega, Iván
PY - 2022/4/1
Y1 - 2022/4/1
N2 - Societies experience intense and frequent changes in diverse environments, which increase uncertainty and complexity in decision-making. The decision-maker looks for alternatives to reduce risks and face these new challenges. In this context, science plays a vital role in proposing new solutions. The article aims to: (i) to carry out a bibliometric review of decision models in uncertainty through scientific mapping and performance analysis between 1990 and 2020; (ii) to know the scientific progress of 17 models that specialists validated. The Web of Science database and the VOSviewer, R, and Python software analyzed 26,835 articles in nine bibliometric indicators. The results revealed a positive trend of the publications in the analyzed models, being the Analytic Hierarchical Process the most used. Other findings showed China as the country with more scientific collaborations. There is enormous potential for future lines of research on the subject.
AB - Societies experience intense and frequent changes in diverse environments, which increase uncertainty and complexity in decision-making. The decision-maker looks for alternatives to reduce risks and face these new challenges. In this context, science plays a vital role in proposing new solutions. The article aims to: (i) to carry out a bibliometric review of decision models in uncertainty through scientific mapping and performance analysis between 1990 and 2020; (ii) to know the scientific progress of 17 models that specialists validated. The Web of Science database and the VOSviewer, R, and Python software analyzed 26,835 articles in nine bibliometric indicators. The results revealed a positive trend of the publications in the analyzed models, being the Analytic Hierarchical Process the most used. Other findings showed China as the country with more scientific collaborations. There is enormous potential for future lines of research on the subject.
UR - https://onlinelibrary.wiley.com/doi/10.1002/int.22882
M3 - Artículo
SN - 0884-8173
VL - 37
SP - 7300
EP - 7333
JO - International Journal of Intelligent Systems
JF - International Journal of Intelligent Systems
ER -