MAPPING THE RESEARCH ON AI SUPPORTED DECISION-MAKING: A BIBLIOMETRIC ANALYSIS BY DECISION TYPE
Sidor Vanesa-Luisa,
Cuc Lavinia-Denisia and
Spinu Adina-Eleonora
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Sidor Vanesa-Luisa: INTERDISCIPLINARY RESEARCH INSTITUTE, AUREL VLAICU UNIVERSITY OF ARAD
Cuc Lavinia-Denisia: FACULTY OF ECONOMIC SCIENCES, AUREL VLAICU UNIVERSITY OF ARAD
Spinu Adina-Eleonora: FACULTY OF ECONOMIC SCIENCES, AUREL VLAICU UNIVERSITY OF ARAD
Annals - Economy Series, 2026, vol. 2, 324-329
Abstract:
The literature frequently analyses the impact or implications of artificial intelligence on management and implicitly on the decision-making process in organizations. Both the changes generated by this modern technology and the outcomes it produces are frequently discussed, particularly in terms of organizational performance and adaptability. Yet, what remains interesting to analyse is the way in which AI supported decisions are discussed in terms of types of decisions and whether the literature satisfactorily covers this specific field or if it is rather focused only on a certain area. That is why, this paper offers, through bibliometric analysis, a mapping of research focusing on AI supported decision-making by decision type. Through this chosen method, the results could make important contributions to the literature, being relevant for studies that wish to delve deeper into the decision-making process and the implications that intelligent systems hold over it. In this sense, it can be said that the focus of the results leans towards strategic and group decisions. Whhile this may be motivated by the strong impact that digitalization has in changing the decision architecture. Thus, in order to conduct the said analysis, Biblioshiny was employed as a methodological tool, facilitating the generation of both relevant tables and high-impact visual representations through figures.
Keywords: AI; decision-making; decision type; bibliometric analysis (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:cbu:jrnlec:y:2026:v:2:p:324-329
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