RESEARCH ARTICLE
Bibliometric review of research on decision models in uncertainty, 1990–2020
Luciano Barcellos-Paula,
Iván de La Vega,
Anna M. Gil-Lafuente,
Corresponding Author
Luciano Barcellos-Paula
CENTRUM Católica Graduate Business School, Lima, Perú
Pontificia Universidad Católica del Perú, Lima, Perú
Correspondence Luciano Barcellos-Paula, Jirón Daniel Alomía Robles 125, Santiago de Surco, Lima 15023, Perú.
Email: [email protected]
Search for more papers by this authorIván de La Vega
CENTRUM Católica Graduate Business School, Lima, Perú
Pontificia Universidad Católica del Perú, Lima, Perú
Search for more papers by this authorAnna M. Gil-Lafuente
Department of Business Administration, University of Barcelona, Barcelona, Spain
Search for more papers by this authorLuciano Barcellos-Paula,
Iván de La Vega,
Anna M. Gil-Lafuente,
Corresponding Author
Luciano Barcellos-Paula
CENTRUM Católica Graduate Business School, Lima, Perú
Pontificia Universidad Católica del Perú, Lima, Perú
Correspondence Luciano Barcellos-Paula, Jirón Daniel Alomía Robles 125, Santiago de Surco, Lima 15023, Perú.
Email: [email protected]
Search for more papers by this authorIván de La Vega
CENTRUM Católica Graduate Business School, Lima, Perú
Pontificia Universidad Católica del Perú, Lima, Perú
Search for more papers by this authorAnna M. Gil-Lafuente
Department of Business Administration, University of Barcelona, Barcelona, Spain
Search for more papers by this authorAbstract
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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