Bibliometric review of research on decision models in uncertainty

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. Th...

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Bibliographic Details
Authors: Barcellos de Paula, Luciano, Gil Lafuente, Anna Maria, Vega, Iván de la
Format: article
Status:Versión aceptada para publicación
Publication Date:2022
Country:España
Institution:Universidad de Barcelona
Repository:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/216192
Online Access:https://hdl.handle.net/2445/216192
Access Level:Open access
Keyword:Bibliometria
Presa de decisions (Estadística)
Gestió del risc
Incertesa
Bibliometrics
Statistical decision
Risk management
Uncertainty
Description
Summary: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.