Title
Bibliometric review of research on decision models in uncertainty, 1990–2020
Date Issued
01 October 2022
Access level
metadata only access
Resource Type
journal article
Publisher(s)
John Wiley and Sons Ltd
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.
Start page
7300
End page
7333
Volume
37
Issue
10
Language
English
OCDE Knowledge area
Estadísticas, Probabilidad Informática y Ciencias de la Información Ingeniería de sistemas y comunicaciones
Scopus EID
2-s2.0-85127412963
Source
International Journal of Intelligent Systems
ISSN of the container
08848173
DOI of the container
10.1002/int.22882
Source funding
National Natural Science Foundation of China
SIEMCI
CENTRUM Católica Graduate Business School
Red Sistemas Inteligentes y Expertos Modelos Computacionales Iberoamericanos
Royal Academy of Economic and Financial Sciences, Spain
Universitat de Barcelona
Sponsor(s)
The authors wish to thank the Royal Academy of Economic and Financial Sciences, Spain, CENTRUM Católica Graduate Business School, Peru, and the University of Barcelona, Spain. Research supported by Red Sistemas Inteligentes y Expertos Modelos Computacionales Iberoamericanos (SIEMCI), project number 522RT0130 in Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo (CYTED). The CAS has achieved an impressive growth in the last decade, with seven papers in 1990–1999, 61 papers in 2000–2009, and 372 papers in 2010–2020. The results have revealed that the University of Chinese Academy of Sciences is its main collaborating institution with 31.8% PPI. The CAS started its activities in 1949 in Beijing and is engaged in most areas of basic science and technology, advanced strategic technologies, and areas related to public welfare and the development of emerging industries. Over the past decades, its research center was structured with 104 research institutes, 12 branch academies, 3 universities, and 11 supporting organizations in 23 regions in China. Its strategy combines research, education, and interdisciplinary and cross‐sectoral cooperation in innovation. The institution has a staff of 56,000 professional researchers, 22,800 of whom are research professors or associate professors. These researchers carry out about 30% of China's critical basic science projects under the nation's 973 Program. In addition, 40% of projects funded by the National Natural Science Foundation of China are with CAS researchers. In summary, factors such as structure, environment, external collaboration, and support for researchers justify CAS's leadership.
Sources of information: Directorio de Producción Científica Scopus