Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/216192
Title: Bibliometric review of research on decision models in uncertainty
Author: Barcellos de Paula, Luciano
Gil Lafuente, Anna Maria
Vega, Iván de la
Keywords: Bibliometria
Presa de decisions (Estadística)
Gestió del risc
Incertesa
Bibliometrics
Statistical decision
Risk management
Uncertainty
Issue Date: 25-Aug-2022
Publisher: Wiley
Abstract: 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.
Note: Versió postprint del document publicat a: https://doi.org/10.1002/int.22882
It is part of: International Journal of Intelligent Systems, 2022, vol. 37, num.10, p. 7300-7333
URI: https://hdl.handle.net/2445/216192
Related resource: https://doi.org/10.1002/int.22882
ISSN: 0884-8173
Appears in Collections:Articles publicats en revistes (Empresa)

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