Decision-Making for Sustainable Digitalization Through Grey Systems Theory: A Bibliometric Overview

Georgiana-Alina Crișan, Adrian Domenteanu, Mădălina Ecaterina Popescu and Camelia Delcea ()
Additional contact information
Georgiana-Alina Crișan: The Faculty of Economic Cybernetics, Statistics and Informatics, The Bucharest University of Economic, Studies, 15-17 Dorobanti St., Sector 1, 010552 Bucharest, Romania
Adrian Domenteanu: The Faculty of Economic Cybernetics, Statistics and Informatics, The Bucharest University of Economic, Studies, 15-17 Dorobanti St., Sector 1, 010552 Bucharest, Romania
Mădălina Ecaterina Popescu: The Faculty of Economic Cybernetics, Statistics and Informatics, The Bucharest University of Economic, Studies, 15-17 Dorobanti St., Sector 1, 010552 Bucharest, Romania
Camelia Delcea: The Faculty of Economic Cybernetics, Statistics and Informatics, The Bucharest University of Economic, Studies, 15-17 Dorobanti St., Sector 1, 010552 Bucharest, Romania

Sustainability, 2025, vol. 17, issue 10, 1-42

Abstract: As the digitalization trend is progressively establishing a solid foundation in terms of both implementation and scientific research, its effects may be noticed across every sector of the economy. Therefore, offering sustainable solutions becomes essential for implementing digital transitions in a cohesive manner. Additionally, the study of Grey systems is another topic that has relevance when investigating the implications of digitalization in sustainability. Grey systems theory is an elaborate decision-making technique that focuses on objects that incorporate both known and unknown information. This approach emerged from the notion of a “black box” in which “black objects” are defined by the absence of information. Grey systems address the gap between the “black objects” with unknown information and the “white objects” with complete knowledge. The interaction of these domains is centered on the requirement for a decision-making framework that facilitates a sustained digital transformation. The novelty of the paper consists of tackling the theory of Grey systems’ implications in the economy’s sustainable digitalization, where the literature review is rather scarce. Having considered a generous timespan of the investigation from 1997 to 2024, we gathered a large dataset of papers extracted from the ISI Web of Science database, which allows for relevant inferences in terms of research trends and thematic directions in the field. The analysis focused on emphasizing the research capabilities and landscape of this rapidly developing subject. The annual growth rate of published papers is 11.7%, indicating the increased interest of researchers in the study of this subject. The visualizations and tables used in the analysis were generated with the help of the “ Biblioshiny” (4.3.0) library from the R programming language and highlighted the main information related to topics, authors, journals, collaborations, and research networks. The present paper reviews the ten most cited publications in the dataset in order to provide a comprehensive assessment of the study on the concepts of Grey systems theory, digitalization, and sustainability to date.

Keywords: digitalization; sustainability; grey systems; decision-making; bibliometric analysis; biblioshiny (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/10/4615/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/10/4615/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:10:p:4615-:d:1658411

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().