Group Decision-Making Based on Artificial Intelligence: A Bibliometric Analysis

Ruben Heradio,Cristina Cerrada,David Fernandez-Amoros,Manuel J Cobo

doi:10.3390/math8091566

Ruben Heradio, Cristina Cerrada + Show 2 more

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https://doi.org/10.3390/math8091566

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Abstract

Decisions concerning crucial and complicated problems are seldom made by a single person. Instead, they require the cooperation of a group of experts in which each participant has their own individual opinions, motivations, background, and interests regarding the existing alternatives. In the last 30 years, much research has been undertaken to provide automated assistance to reach a consensual solution supported by most of the group members. Artificial intelligence techniques are commonly applied to tackle critical group decision-making difficulties. For instance, experts’ preferences are often vague and imprecise; hence, their opinions are combined using fuzzy linguistic approaches. This paper reports a bibliometric analysis of the ample literature published in this regard. In particular, our analysis: (i) shows the impact and upswing publication trend on this topic; (ii) identifies the most productive authors, institutions, and countries; (iii) discusses authors’ and journals’ productivity patterns; and (iv) recognizes the most relevant research topics and how the interest on them has evolved over the years.

Highlights

Making decisions under complex and uncertain situations frequently requires the cooperation of a team of experts, each one with their own background, opinions, motivations, etc
As this paper focuses on the application of Artificial Intelligence (AI) techniques to Group Decision-Making (GDM), Line 2 limits the scope to the Web of Science (WoS) category Computer
How Has the Number of Publications on AI-GDM Evolved over the Years? (RQ1)

Summary

Introduction

Making decisions under complex and uncertain situations frequently requires the cooperation of a team of experts, each one with their own background, opinions, motivations, etc. Already noticed in 1984, in these circumstances, experts usually need to spend considerable time in meetings to reach a collective agreement. For more than 30 years, research on Group Decision-Making (GDM) systems have pursued saving much of this time by providing automated support to accomplish consensual decisions [2,3]. They express their individual preferences on the alternatives. As typically the resulting collective preference does not achieve experts’ consensus, a feedback mechanism assists experts in changing their preferences for augmenting the consensus level.

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