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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/216192
Bibliometric review of research on decision models in uncertainty
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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.
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BARCELLOS DE PAULA, Luciano, GIL LAFUENTE, Anna Maria and VEGA, Iván de la. Bibliometric review of research on decision models in uncertainty. International Journal of Intelligent Systems. 2022. Vol. 37, num. 10, pags. 7300-7333. ISSN 0884-8173. [consulted: 14 of June of 2026]. Available at: https://hdl.handle.net/2445/216192