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) |
Files in This Item:
File | Description | Size | Format | |
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257246.pdf | 2.15 MB | Adobe PDF | View/Open |
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