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

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.

1. Introduction

The effects of digitalization can be found in every sector of the global economy. This tendency has led to the automation of operations in industry and routine citizen activities. Thus, with a major impact on the supply chain, the question of sustainability often arises. The positive effects are numerous, but the negative impact on the environment is also relevant when it comes to the study of digitalization. In this context, numerous approaches have been adopted in recent years to promote the digital changes.

For example, the European Commission has been encouraging a straightforward process to a digital economy at the European level since 2010 through the “Digital Agenda for Europe” [1]. The policy framework supports, among others, the following: (1) building the digital skills required for labor market integration; (2) the development of e-government services; and (3) the growth of small- and medium-sized enterprises (SMEs) and start-up in the IT sector. The European Commission’s “A Europe Fit for the Digital Age” [2] program, announced a decade later, maintains the continuity of these recommendations. This effort discusses innovations that must be considered when implementing digital transformation policies, specifically cyber security and the green economy. In order to increase industrial efficiency and competitiveness, investments are encouraged in domains with substantial digital potential, such as high-performance computing, blockchain, artificial intelligence (AI), and digital education. The implications of these digital transformations have an impact on society’s sustainable development [3], economic convergence [4], the business sector [5], and on the labor market by generating job opportunities based on digital skill requirements [6].

Digitalization also aligns with several Sustainable Development Goals that were emphasized by the United Nations through “Transforming our world: the 2030 Agenda for Sustainable Development” [7], to ensure sustainability on multiple levels by 2030. Sustainability is seen as the most important prerequisite because it affects both human lifestyles and economic progress. Policies that aim to reduce waste by establishing sustainable patterns of production and consumption are at the forefront of resolving the green economy conundrum. The wide range of topics impacted by the 2030 agenda further demonstrates the subject’s significance. Studies have shown that the transition to a digital economy can be accompanied by an increase in the usage of clean energy sources [8], but also by CO₂ emissions in the short run [9].

Given the importance of adopting appropriate policies in the implementation of digital transformations that support national and global sustainability, this paper attempts to investigate, through a bibliometric analysis, the topic of sustainable digitalization through a decision-making system that ensures a balanced transition. Many different decision-making systems with distinct features are available in the academic literature. Among the most complex decision-making systems are, however, the Grey systems, which use approaches from the field of artificial intelligence.

The concept of Grey systems theory was first presented in 1982, by addressing fundamental ideas pertaining to the stability and controllability of a Grey system, as well as the key concepts “grey systems” and “grey matrix” [10]. In this sense, a “gray system” is described as a collection of both known and unknown information, with the concept being derived from the idea of a “black box” in which all information about the object of study is unknown. A “white” object, on the other hand, has all of its information known. The Grey system introduces the idea of a “grey” object—an entity concerning for which information is only partially known—by merging the two concepts in an innovative manner.

Wu and Chen [11] created an integrated prediction method based on the Grey model called GMC(1,n), which also takes into consideration the convolution integral. The developed algorithm was successfully tested by predicting Taiwan’s Internet access population, together with the Grey relational grade analysis.

Moreover, Xiao et al. [12] explored the Grey system information complex interactions and coverage in the digital economy evolution, by defining a multi-attribute decision-making method founded on the Grey interaction relational. A normal cloud matrix known as GIRD-NCM was proposed. After the model was created using information principles and Grey numbers, the algorithm was tested on digital economy data in China between 2013 and 2020. The results showed an annual growth of 7.87%. The availability, feasibility, and implementation were also verified. When the interaction degree is changed, the impact on the lead provinces is limited, but it has a stronger impact on provinces with high and low values of digital economy.

Recent investigations on the Grey systems theory conducted a more holistic approach, through the use of a bibliometric analysis, as it provides information on the most representative papers, authors, journals, and themes tackled in the Grey domain [13]. The applicability of Grey methods is found in a variety of fields, such as the supply chain [14,15], economic and social sciences [16], education [17], uncertain environments [18,19], or more targeted areas, such as engineering [20]. All of these bibliometric studies have in common the use of the WoS database, as it is recognized for the relevance of the articles in the academic community, while the software used to generate the graphical analyses is either Biblioshiny or CiteSpace. Regarding the focus of the articles, the applicability of this theory proves to be relevant for real-world usage, contributing to scientific advancement. However, little has been published so far on the applicability of Grey systems theory for sustainable digitalization through a bibliometric lens.

Given the existing bibliometric analysis publications in the field of Grey systems theory, the novelty of the paper consists of tackling the theory of Grey systems’ implications for the economy’s sustainable digitalization, where the literature review is rather scarce. Moreover, the timespan of the investigation considered in the analysis is generous, from 1997 to 2024, gathering a large dataset of 9169 papers, which allows for relevant inferences in terms of research trends and thematic directions in the field. By determining how quickly the themes are spreading, it is possible to draw an emphasis to the disparities in the development paths of traditional and modern approaches, as well as the effectiveness of these studies.

Therefore, the analysis will aim to answer the following set of research questions formulated to achieve the main goal:

• RQ1: What is the trend of the production of papers in this field?

This paper will assess the evolution of the applicability of Grey systems theory upon sustainable digitalization during the reference period in terms of the annual number of publications in the field. Given the advances in technology and sustainable domains supported by the European policy framework in the last decades, we formulate the first hypothesis that will be tested in the paper:

Hypothesis 1 (H1):

There is an increasing research interest in the field of decision-making for sustainable digitalization through the Grey systems theory.

• RQ2: What are the authors, journals, and countries with the most relevant contribution to the production of papers in the field and how is the collaboration network between countries?

Through this question, the paper will highlight the most relevant sources, countries, and authors based on citations and publications from the reference period. The paper will also assess the collaboration network between countries to identify regional collaboration patterns between authors in the field. Given the general trend in and patterns of the scientific production based on the Grey system theory area during the last decades, we formulate the second hypothesis that will be tested in the paper:

Hypothesis 2 (H2):

Asian countries (especially China) have the greatest contribution to researching the implications of Grey systems theory in sustainable digitalization through published papers and total citations in the field.

• RQ3: What are the main topics addressed by the articles on the theory of Grey systems, digitalization, and sustainability?

The last research question aims to identify the main thematic domains in the field of Grey systems with implications on sustainable digitalization. Our findings will allow the third hypothesis, formulated as follows, to be tested:

Hypothesis 3 (H3):

Grey systems theory has recently become a domain with numerous digital sustainable applications.

This article is divided into five sections with specific purposes. The first section has the role of exploring the defining concepts of the analyzed field, as well as the motivation for choosing this field. The methodological aspects related to both the actual analysis and the steps necessary to extract the dataset from the ISI Web of Science (WoS) are presented in the second section. The third section focuses on extracting essential information regarding sources, authors, journals, and countries from the dataset through a bibliometric analysis. In this section, the exploration of the 10 most cited documents that combine the theory of Grey systems with digitalization and sustainability also takes place in order to highlight the main directions of scientific development. The fourth section presents the discussions based on the results obtained and the limitations of the paper, and the last section concludes by addressing the research questions initially formulated.

2. Materials and Methods

In order to extract the dataset needed for conducting the bibliometric analysis, Clarivate Analytics’ Web of Science Core Collection, known as WoS [21], was selected. The advantages of using this database have been highlighted by Bakir et al. [22] in their work, while a series of other studies has used this database in the bibliometric analysis conducted in various fields of research [23,24,25,26,27,28].

As the papers in WoS can be accessed based on a subscription, Liu [29] and Liu [30] mentioned the need to highlight the indexes to which one has access. In our case, when extracting the dataset, it should be stated that we had access to all ten indexes offered by WoS [18,19]. The data were extracted in September 2024.

Figure 1 provides the steps taken for the bibliometric analysis, according to Cobo et al. [31] and Zupic and Cater [32]. The first step consists in the data extraction based on keywords that are related to Grey systems theory, while the next step refers to dataset exploration from multiple perspectives, covering a wide range of analyses, starting from the analysis of the sources, continuing with the analysis of authors, countries, and most cited papers, and ending with a mixed analysis in which the elements provided before are put into a connection.

Figure 2 describes the steps associated with dataset extraction. The first step related to extracting the papers associated with Grey systems theory was conducted as in Domenteanu et al. [18] and Sandu et al. [19], with a total number of papers equal to 9977 papers. The use of “*” denotes the replacement of any following word, allowing in this manner various ends for the used keywords, as well as singular and plural forms. Furthermore, the use of “_” makes sure that the group of words are searched together, as a group, rather than individual words. The approach to search for articles using keywords among the titles, abstracts, and keywords that are related to the investigated topic aligns with similar papers from different areas, such as papers published by Delcea et al. [33], which explored the energy communities, or Domenteanu et al. [34], which presented the digitalization impact in the area of air traffic. Regarding the Grey system topic, Yin MS. [35], Mahala et al. [36], and Delcea C. [37] used similar keywords in order to extract documents that were further analyzed using a bibliometric approach.

The second step referred to papers containing keywords related to digitalization and sustainability in titles, which contributed to a dataset comprising 240,980 papers.

When intersecting the two datasets, the number of papers that included both Grey systems theory in titles, abstracts, or authors keywords, as well as sustainability and digitalization keywords in titles, was reduced to 154 papers.

The fourth step limited the publications by including only documents that were published in English, which did not affect the length of the dataset, with all 154 papers selected in the previous step being all written in English. The English language was chosen since it is the most used in the academical community. Thangavel and Chandra [38] explained the importance of analyzing exclusively English-written articles for bibliometric research, providing accessibility and consistency in the investigation. Including more than one language could lead to misleading results while investigating the main keywords, topics, or n-grams. In the research community, the papers that excluded any other language apart from English are the following: Ayodele et al. [39] and Delcea et al. [33].

Regarding the metrics that have been used during scientific research in order to formulate relevant conclusions, the majority are related to the number of papers, mean citations per article, mean years since publication, number of co-authors per article, growth rate, average yearly scientific production, most important authors, corresponding author’s country, most representative journals, affiliations, or themes. Based on the existing data, we have calculated all possible metrics, according to similar papers [33,36,39].

3. Dataset Investigation

The third section of the article focuses on investigating the extracted dataset by obtaining the most important authors, journals, countries, and keywords that have been used, together with the thematic evolution, factorial analysis, collaboration network, and a review of 10 most globally cited papers.

3.1. Dataset Analysis

The dataset was first explored by presenting the timespan, number of sources, documents, references, the average years from publications, average citations per document, number of single-authored documents, number of multiple-authored documents, co-authors per document, international co-authorship, number of keywords plus, and author’s keywords. The focus was also on investigating the types of documents that are included in the analysis.

Table 1. Main information.

Indicator	Value
Timespan	1997:2024
Sources	87
Documents	154
Average years from publication	4.49
Average citations per document	25.55
References	7772

includes the key details of the dataset that have been extracted from WoS, presenting the timespan, sources, documents, references, average citations per document, and average years from publication. The analysis begins in 1997 and ends in 2024, having 154 documents, 87 sources, and 7772 references. The average citations per document is 25.55 and the average years from publication is 4.49. The findings do not follow the tendency observed in specialized studies. In comparison, a database of over 200 documents focused just on the themes of sustainability and digitalization had an average of 67.45 citations per document [40]. Thus, by restricting the dataset by adding the concept of Grey systems, the number of citations is also significantly reduced.

In total, there are 434 authors, 538 author’s keywords, and 417 keywords plus, with an international co-authorship of 35.06%. Only 9 publications have a single author and 425 have multiple authors, with an average of 3.32 co-authors per document.

Since the dataset under analysis comprises a variety of document types, 154 papers are taken into consideration, of which 123 are classified as articles, 19 as proceedings papers, 5 as review documents, and 1 as a book chapter.

Figure 3 shows the annual scientific production of the researchers for the Grey system theory area during the timespan. Initially, in 1997, only one paper was published, followed by another one in 2003 and two more in 2005. In 2015, the domain started to grow exponentially, having 1 paper in 2015, 4 in 2016, 8 in 2017, and 15 in 2018. In 2019, the trend decreased from 15 to 8 papers, but starting with 2020, the number of papers grew to 12, with 20 in 2021 and 2022, and the peak was reached in 2023 with 28 articles. In 2024, there were 20 papers published. The upward trend suggests that authors are more involved in exploring the relationship among digitalization, sustainability, and Grey systems theory, with a notable increase noticed since 2015 that has continued to date.

These findings support the first hypothesis, H1, tested, confirming that there is an increasing research interest in the field of decision-making for sustainable digitalization through the Grey systems theory. The growing interest in the subject in the last decades can be justified by the favorable European policy framework that fosters innovation and digitalization while leading to sustainable development. It can also be attributed to advances in technology and sustainable domains, which provide new adjacent factors that can be researched, as well as advances in research, which provide new approaches for analyzing economic transitions.

The average citations per year is presented in Figure 4. In 1997, when the first document was published, the average citations per year was very small, at just 0.1. In 2005, the value increased to 2.3, while the peak was registered in 2010, with an average of 39.5 citations. The value decreased significantly in the following years, to 0.1 in 2012, 4 in 2013, 1.6 in 2014, and 10.5 in 2015. The trend continued to decrease after 2015, obtaining an average of 2 citations per year in 2024. Alqasemi et al. [41] examines the significance of this metric and depicts the impact of publications with below-average annual citations in a given discipline, revealing that these articles benefit from an upward trend in the number of publications when in comparison with academics with an average or higher citation density.

3.2. Source Analysis

The analysis of the sources in this sub-section mainly highlights the journals with the most relevant contribution to the current research through the total number of publications and citations and through the impact determined by the Hirsch index.

Figure 5 describes the most important sources based on the total number of publications.

In first place is Sustainability which published 20 papers related to Grey systems theory, digitalization, and sustainability, followed closely by the Journal of Cleaner Production with 19 publications. Starting with third place, the number of papers released decreased substantially to just 4 papers for Business Strategy and the Environment, Environment Development and Sustainability, Heliyon, and Sustainable Production and Consumption. In seventh place is Benchmarking-An International Journal with 3 publications, the same as Environmental Science and Pollution Research and Grey Systems-Theory and Application, while the last journal in the top 10 is Annals of Operations Research with 2 articles. Similar results were observed in Sharma et al. article [40] where, although the indicator for measuring the relevance of sources is the number of accumulated citations, the hierarchy is identical regarding the first two positions: Sustainability (440 citations) in first place and Journal of Cleaner Production (370 citations) in second place.

Figure 6 depicts how the considered journals are categorized using Bradford’s law, which separates journals with a high impact from the ones with a low impact.

Therefore, Bradford’s law classifies the retrieved journals into three distinct categories depending on the number of published papers, and if each category contains one-third of total production, the number of articles in each category is proportional to 1$:n:n^2$ [42,43]. Thus, the present analysis highlights five journals as relevant in the field that connects the theory of Grey systems with sustainable digitalization: Sustainability, Journal of Cleaner Production, Business Strategy and the Environment Development and Sustainability, and Heliyon.

Figure 7 presents the top ten journals in terms of impact, as determined by the Hirsch index (H-index). The H-index assesses a journal’s significance by taking into consideration both article production and citation volume. The journal with the highest impact is Journal of Cleaner Production with an h-index of 13, followed by Sustainability with an h-index of 9, then Business Strategy and the Environment and Sustainable Production and Consumption with 4, Environmental Science And Pollution Research, and Grey Systems-Theory and Application with 3. The rest of the four journals have an h-index of 2.

3.3. Author Analysis

The author analysis focuses on determining the most relevant authors based on citations and publications from the reference period, with this information being essential in shaping the overall picture of the research so far.

The most relevant authors in terms of the number of published works are highlighted in Figure 8. Accordingly, the author with the greatest influence is Rajesh R, who published eight papers between 1997 and 2024. With seven publications, Ali SM comes in second, separated only by one publication. The two authors collaborated on the most cited article, where an approach for identifying and eliminating barriers in order to implement sustainability measures based on supply chain systems was proposed [44]. Multiple methods for supporting supply chain sustainability are offered in Rajesh R’s most cited papers, as the main emphasis is on sustainable supply chain management. The recommended methods are based on Grey decision-making models, which, according to the results obtained, are best suited to achieving the goal of sustainability [45]. Another proposed technique aims to analyze the sustainability performance of organizations that have the supply chain as their object [46]. Ali SM, on the other hand, has produced articles on more particular themes relating to events or trends that have an impact on sustainability, but with an overall focus on reaching the sustainable development goals (SDGs). The author investigated the leather industry, which has been demonstrated to be relevant in reaching the SDGs. The findings underlined the importance of customer behavior in the circular economy, as well as the need for government laws to encourage environmental conservation methods [47]. The particular event investigated is the COVID-19 pandemic, which Ali SM links to the viability of the supply chain at the SME level. This paper emphasizes the need for digitizing supply chain systems to facilitate adapting to changes such as the pandemic [48].

These two authors are distinguished by a considerable number of publications compared to the other authors, resulting in a much greater impact than the average. The following eight authors, who are among the top ten authors with relevant impact, published three papers individually within the reference period.

The analysis presented in Figure 9 highlights the production of the top 10 authors throughout the time analyzed.

The red lines have the role of highlighting the period in which each author published articles in the field of Grey systems theory, digitalization, and sustainability, and the blue circles have the role of highlighting the number of articles published and the total number of citations from each year. As a result, in this graph, author Rajesh R stands out for the consistency with which he published papers on this subject (2018–2024), while author Liu Sf published between 2005 and 2023, but only three articles in total in three of the years in question. The authors with the most articles published in a single year are Ferasso M and Ikram M who published three articles each in 2021, which have a number of 36.5 citations per year each. The remaining top ten authors have a consistent publication rate of one paper per year for two to four years.

Lotka’s Law is a theory developed to provide an overview of the productivity of authors within a researched set, with the aim of predicting a trend in the authors’ behavior [49]. The number of published documents and the associated share of authors have a negative connection, and as shown in Figure 10, the percentage of authors declines significantly as the number of published documents rises. This fact underlines the authors’ difficulty in publishing an extensive number of papers in the field that incorporates three challenging subjects: Grey systems theory, digitalization, and sustainability. The dotted line shows the real distribution of authors productivity, while the solid line presents the predicted values of Lotka’s law.

3.4. Country Analysis

The sub-section of the country analysis focuses on identifying the countries with the highest number of publications and citations, recognizing publication preferences at a national level (Single-Country Publications or Multiple-Country Publications), identifying the most relevant institutions, and establishing a global collaboration network among countries.

Figure 11 includes the most relevant 10 universities that published scientific articles related to Grey systems theory, sustainability, and digitalization.

In first place is the Indian Institute of Technology System (IIT System) with nine publications, the same as Nanjing University of Aeronautics and Astronautics. In third place is Bangladesh University of Engineering and Technology (BIJET) with eight publications, followed by the Indian Institute of Management (IIM System) and Poznan University of Technology with 6 papers each. In sixth, seventh, and eight are three universities with same number of papers, Chongqing Technology and Business University, Indian Institute of Technology (IIT)—Delhi, and the National Institute of Technology (NIT System) with six papers. The last two universities are King Abdulaziz University and University of Southern Denmark with four articles each.

Figure 12 examines the corresponding author’s countries of publications from two different perspectives: number of Single-Country Publications (SCPs) and Multiple-Country Publications (MCPs).

As it can be observed in Figure 12, in first place is China, with 83 papers, 62 SCPs (74.7%) and 21 MCPs (25.3%). The Chinese papers represent a total of 53.9% of total papers published globally. In second place is India with 26 articles, having 18 SCPs (69.2%) and 8 MCPs (30.8%), representing a total of 16.9% of global papers published. In third place is Poland, with 6 articles, all of them SCPs (100%), representing only 3.9% of total articles released, followed by Iran with 5 papers, which has 4 SCPs (80%) and 1 MCP (20%). Representing 3.2% of total articles. In fifth place is the USA, with 4 papers, only 1 SCP (25%) and 3 MCPs (75%), representing 2.6% of total papers. The next three countries, Bangladesh, Brazil, and Turkey, each have 3 publications. Bangladesh published 1 SCP (33.3%) and 2 MCPs (66.7%), Brazil has only MCP papers (100%), while Turkey has 2 SCPs (66.7) and 1 MCP (33.7%), each one having a contribution of approximately 1.9%. The last two countries in the top 10 are Australia and Chile, with 2 papers, both of them having only MCP paper (100%). Their contribution is reduced, at only 1.3% for each one.

Figure 13 presents the 10 most cited countries. In first place is China with 1731 citations and an average article citation of 20.0. Considering Figure 12, where China is also in first place, with the most papers (83), it confirms the significant impact of Chinese authors in Grey systems theory, sustainability, and digitalization areas. In second place is USA with 649 citations with an average article citation of 162.20, followed by India with 600 citations with an average article citation of 23.10 and Australia with 248 and an average article citations of 124. Poland is fifth, with 123 citations and an average article citation of 20.50, while Iran has 112 citations and an average article citation of 22.40. The last countries have a smaller impact but are worthy of mentioning: Turkey (92 citations, 30.70 average article citation), Lithuania (79 citations, 79 average article citation), UK (58 citations, 29 average article citation) and Bangladesh (50 citations, 16.70 average article citation).

Figure 14 explores the countries’ academical collaboration. The countries with the most papers published together are China and USA with eight articles, both representing one of the most relevant countries in Grey systems theory, sustainability, and digitalization areas. In second place, there are two groups of countries: China–UK and India–Bangladesh with five papers each. The next seven collaborations led to three documents published: Bangladesh–Australia, China–Australia, China–Brazil, China–Denmark, China–Japan, and India–UK. The last collaboration in the top 10 is between Bangladesh and Canada which led to two publications.

The main inference that can be drawn from the quantity of articles produced and the total number of citations is that authors who favor international collaborations have benefited from a greater number of citations, and China is the country with the most relevant article production and the most articles included in the top 10 most cited. Thus, the preference for MCPs and cooperation with nations that are positioned favorably in the hierarchies of the number of articles and citations, like China, are crucial for better exposure.

To conclude, the second hypothesis H₂ is also confirmed, since Asian countries (especially China), have the greatest contribution to research on the implications of Grey systems theory in sustainable digitalization through published papers and total citations in the field.

3.5. Most-Cited Document Analysis

The identification and exploration of the top ten most cited documents from the dataset aims to determine the authors’ development directions, as well as to identify fundamental information about the characteristics of the articles, such as the number of authors, the type of collaboration, and citation information.

The most important publications that have been published on the Grey systems theory, digitalization, and sustainability are presented in

Table 2. Top 10 most cited documents.

No.	Paper (First Author, Year, Journal, Reference)	Number of Authors	Total Citations (TC)	Total Citations Per Year (TCY)	Normalized TC (NTC)
1	Bai C., 2010, International Journal of Production Economics, [50]	2	592	37.00	1.00
2	Su CM., 2016, Journal of Cleaner Production, [51]	6	204	20.40	2.83
3	Wu KJ., 2017, Journal of Cleaner Production, [52]	6	173	19.22	3.46
4	Moktadir MA., 2018, Journal of Cleaner Production, [44]	4	144	18.00	3.61
5	Rajesh R. 2020, Journal of Cleaner Production, [46]	1	133	22.17	3.09
6	Luthra S., 2018, Production Planning & Control, [53]	5	125	15.63	3.14
7	Golinska P., 2015, Journal of Cleaner Production, [54]	4	105	9.55	1.00
8	Zarbakhshnia N., 2020, Journal of Cleaner Production, [55]	4	104	17.33	2.41
9	Dong LJ., 2020, Journal of Cleaner Production, [56]	3	94	15.67	2.18
10	Wu WY., 2005, Applied Mathematics and Computation, [11]	2	93	4.43	2.00

, together with the number of authors, region, total citations (TC), total citations per year (TCY) and normalized total citations (NTC). NTC expresses the performance of the papers based on citations, by dividing the total citations for each document and the mean citations received by all articles. Only the documents that have been published in the same year as the one investigated will be considered.

Bai and Sarkis [50] introduced a new approach that combines Grey system theory and rough set theory by addressing the sustainability factors identified in the literature review. This multi-stage, multi-method was created mostly in regard to complex companies that have a great number of factors to consider when making a decision about supplier management and the supply chain. The authors have studied different scenarios where the extracted decision factors are considered, and they applied a sensitivity analysis in order to identify the consistency in the organization’s decisions. The results have highlighted the benefits of the new approach in maintaining consistency or improving the process for decision-making in the organization. The two authors that collaborated for this research are from China and USA, gathering, in total, 592 citations, with an average of 37 citations per year and one normalized citation.

Su et al. [51] explored the sustainable supply chain management (SSCM) from the viewpoint of the supplier prioritization process. The research identified the most relevant aspects regarding supplier prioritization by applying a Grey decision-making trial and evaluation laboratory method (grey DEMATEL). Using the proposed methodology, the study proved that the sustainable instruments linked to reusability have a positive impact on lowering the material waste percentage, with this factor being the main criterion in the supplier prioritization process. Thus, the Grey–DEMATEL methodology is recognized as having a strong impact in improving the SSCM performance. Six authors from Taiwan and the Philippines contributed to the study, obtaining 204 total citations, an average of 20.4 citations each year and 2.83 normalized citations.

Wu et al. [52] addressed the risk and uncertainties discovered in the Taiwanese LED (light-emitting diode) industry by following distinct steps: the authors aggregated the data obtained from specialists in the LED industry, fuzzy and Grey Delphi methods were applied on the dataset previously created in order to recognize a set of relevant attributes in the domain, and the big data were transformed into a manageable scale dataset that was lastly used in order to identify the impacts of this attributes. This study offers a guideline for LED companies to reduce the risks and uncertainties by categorizing the factors with the greatest impact on the decision-making process: capacity and operations. This research is the result of the collaboration of six authors from China, Taiwan, and the United Kingdom, collecting, in total, 173 citations, 19.22 citations per year on average, and 3.46 normalized citations.

Moktadir et al. [44] focused on the gap discovered in the leather industry in Bangladesh from a sustainable point of view as the country encountered barriers in adopting SSCM. The responses from specialists in a survey that addressed the context of a specific company in the leather industry were the main source in recognizing the barriers met in the SSCM transition. A Grey–DEMATEL approach was used to analyze the causality between the identified barriers, and the results presented two categories as follows: nine “causal” barriers and eleven “influenced” barriers. The research introduced a model that can assess the relationships between the barriers analyzed in the beginning of implementing SSCM. The accuracy of the results is strongly linked to the survey conducted, as the responses can have an extreme impact on the obstacles identified. An international collaboration among four authors from Bangladesh, India, and Australia was conducted in order to create this paper, and it collected a total of 144 citations, with an average of 18 citations each year and 3.61 normalized citations.

Rajesh [46] studied the possibility of improving the sustainability performance regarding the corporate level. As it was proven, a sustainable transition can bring benefits to companies, the interest in implementing sustainable tools, and improve their efficiency. The study focused on a sample of 39 companies from India, with the dataset representing the Environmental, Social, and Governance (ESG) scores between 2014 and 2018. After the Grey incidence analysis was implemented, it was noted that the indicators with the most relevant impact in sustainability performance are the resource use score, environmental innovation score, and CSR strategy score. This paper is a single-country publication as there is only one author, from India, and it collected a total of 133 citations, an average of 22.17 per year and 3.09 normalized citations.

Luthra et al. [53] studied the connection between Critical Success Factors (CSFs) relevant to implementing sustainable practices in the supply chain. The study focused on the Indian supply chain management, as the authors extracted the source data from a literature review and conducted a Grey–DEMATEL methodology on the dataset. According to the results, the most relevant factors are “Government Legalization” and “Community Welfare and Development” and, based on them, a series of recommendations on best practices was formulated. Five authors collaborated on this paper, and it collected a total of 125 citations with an average of 15.63 citations per year and 3.14 normalized citations.

Golinska et al. [54] examined the domain of remanufacturing with the aim to fill the gap of assessing the operational performance while regarding the issue of sustainability. The four authors considered, as a starting point, the indicators collected from the literature review regarding the remanufacturing indicators and the responses of a survey conducted through the experts in the domain. The application of the Grey decision making (GDM) methodology managed to create specific categories of companies based on their sustainability level in the remanufacturing context. The results have a significant impact in the prioritization operation in a supply chain. The paper has a total of 105 citations, one normalized citation, and 9.55 citations per year.

Zarbakhshnia et al. [55] proposed a new methodology that involves a fuzzy hierarchical process, as well as Grey optimization at a multi-objective level (MADM), with the aim of assessing the qualitative and uncertain character of the inputs encountered in the decision-making processes. In order to apply the MADM, the selection of criteria were retrieved from previous studies from the literature review, and they were utilized based on the survey answers of 12 experts from the car manufacturing field. The results proved the success of the implementation of the new methodology in managing the most relevant aspects, such as the economic balance, sustainability, and social dimension. The paper is a multi-country publication as the four authors are from Iran, Australia, and Denmark, gathering a total of 104 citations, an average of 17.33 per year, and 2.41 normalized citations.

The paper of Dong et al. [56] explores the safety of the mining field by focusing on disaster control and sustainability. The research consists of comparing three methods aimed at a stability analysis of a tailings dam. The relationship between the failure of the tailing dams and pollution was analyzed, resulting in negative output. By investing in the pre-alarming, monitoring, and stability of the mining area, and thus reducing the chances of failure, the level of environmental pollution can be drastically reduced. The collaboration is local as the three authors are all from China, and the paper has a total of 94 citations, 2.8 normalized citations, and an average of 15.67 citations per year.

Wu and Chen [11] define a new prediction method that includes Grey model GMC(1,n) and the improved Grey relational analysis. The methodology was tested on the dataset that includes the internet access data on Taiwan’s population, with significant prediction results. While highlighting the defects of the model, the study represents a starting point in improving the methodology for predictions by introducing Grey systems theory. The paper is a single-country publication, with two authors, both from Taiwan, collecting a total of 93 citations, 2 normalized citations, and 4.43 citations per year on average.

Table 3. Brief summary of the contents of the top 10 most globally cited documents.

No.	Paper (First Author, Year, Journal, Reference)	Title	Data	Purpose
1	Bai C., 2010, International Journal of Production Economics, [50]	Integrating sustainability into supplier selection with grey system and rough set methodologies	Metrics specific to supplier selection decision	To extend the research methodology by integrating the sustainability issue
2	Su CM., 2016, Journal of Cleaner Production, [51]	Improving sustainable supply chain management using a novel hierarchical grey-DEMATEL approach	Supplier prioritization data from a Taiwanese company	To identify relevant aspects regarding the supplier prioritization process through the hierarchical Grey decision-making method and a set of reliable criteria
3	Wu KJ., 2017, Journal of Cleaner Production, [52]	Toward sustainability: using big data to explore the decisive attributes of supply chain risks and uncertainties	Data gathered from practitioners in the Taiwanese LED (light-emitting diode) industry	To establish the impact of the risks and uncertainties of the supply chain in the context of a sustainable transition of the market
4	Moktadir MA., 2018, Journal of Cleaner Production, [44]	Modeling the interrelationships among barriers to sustainable supply chain management in leather industry	Data collected from professionals in the industry	To inspect the barriers encountered when implementing sustainable supply chain management in the Bangladeshi leather industry
5	Rajesh R. 2020, Journal of Cleaner Production, [46]	Exploring the sustainability performances of firms using environmental, social, and governance scores	Environmental, Social, and Governance (ESG) scores regarding 39 Indian firms	To analyze the sustainability performance of 39 companies from India by implementing a Grey incidence analysis in the study
6	Luthra S., 2018, Production Planning & Control, [53]	Modelling critical success factors for sustainability initiatives in supply chains in Indian context using Grey-DEMATEL	Critical Success Factors (CSFs) extracted from the literature review	To explore the causality between the factor identified as being effective in implementing sustainable actions in the Indian supply chain
7	Golinska P., 2015, Journal of Cleaner Production, [54]	Grey Decision Making as a tool for the classification of the sustainability level of remanufacturing companies	Remanufacturing indicators from previous studies and survey results	To define specific categories of companies based on the sustainability levels, in order to optimize the prioritizing process
8	Zarbakhshnia N., 2020, Journal of Cleaner Production, [55]	A novel hybrid multiple attribute decision-making approach for outsourcing sustainable reverse logistics	Survey responses from specialists in the car parts manufacturing industry	To propose a methodology that combines a fuzzy analytic hierarchy process and Grey multi-objective optimization
9	Dong LJ., 2020, Journal of Cleaner Production, [56]	Some developments and new insights for environmental sustainability and disaster control of tailings dam	Data extracted from the literature review regarding the accident statistics and method used	To compare different methods on the stability of a tailings dam, including Grey system methods, to assess the safety work and the environmental sustainability
10	Wu WY., 2005, Applied Mathematics and Computation, [11]	A prediction method using the grey model GMC(1, n) combined with the grey relational analysis: a case study on Internet access population forecast	Data concerning Taiwan’s internet access	To propose an improved prediction method that associates the Grey model and the improved Grey relational analysis

presents the most global cited documents together with the first author, year when the paper was published, journal name, title, data that have been used, and the purpose of the research.

3.6. Mixed Analysis

In this section, the analysis will focus on the themes identified in the titles, abstracts and keywords, WordClouds, and the collaboration network established between the authors and the most frequent bigrams and trigrams to identify possible patterns and provide details on the complete overview.

Figure 15 explores the most used keywords, based on the thematic.

There are four quadrants, which are defined based on the level of centrality and density. The most representative cluster is on the right part of the graph, on Motor Themes, colored yellow, which has high centrality and density values. The most important terms that are part of the cluster are “model” (31 appearances), “management” (27 appearances), “performance” (27 appearances), “selection” (18 appearances), “barriers” (13 appearances), “criteria” (11 appearances), “supply chain” (11 appearances), “indicators” (9 appearances), and “systems” (9 appearances). The terms describe applications and methods of implementation for Grey systems theory models. The second cluster, colored in brown, contains keywords that are related to China and applications of Grey systems theory, such as “China” (8 occurrences), “impact” (7 occurrences), “optimization” (6 occurrences), “consumption” (5 occurrences), “technologies” (5 occurrences), “energy” (4 occurrences), and “quality” (4 occurrences). The third cluster, colored in pink, on the top left part of the graph, in the quadrant called Niche Themes, focuses on the energy domain: “co2 emissions” (6 appearances), “energy-consumption” (5 appearances), and “sector” (4 appearances). The last three clusters, which are smaller than the previous three, contain only one word each one: “prediction” (6 appearances), “innovation” (5 appearances), and “growth” (4 appearances). The last three terms describe the potential growth of the domain, thanks to the innovation of the domain. Prediction is one of the main steps of Grey systems theory.

Figure 16 includes the thematic map of the titles, grouped based on the similarities. There are three clusters of different sizes, based on their importance. Two metrics describe the relevance of the clusters, centrality and density. The centrality defines the most relevant keywords that have been used in a specific theme by investigating external associations, while density presents the evolution rate by analyzing internal associations among the keywords of a specific theme, according to Wilczewski et al. [57]. The first cluster presents sustainability and Grey systems, while the second cluster presents the main factors and methods for selection processes, and the third cluster focuses on supply chain management. According to the existing research, similar results have been obtained. Pan et al. [58] investigated the Grey systems evolution between 1991 and 2018, observing a transition from “fuzzy” between 1991 and 1995 to the “grey system model” between 2001 and 2005, “grey incidence model” between 2011 and 2015, and “forecasting accuracy” between 2016 and 2018. Fang et al. [59] evaluated the supply chain management and Grey systems. The most representative keywords that were identified are “supply chain management” with 529 appearances in 2020, “sustainable development” with 194 occurrences in 2020, “green supply chain management” with 74 occurrences in 2020, and “supplier selection” with 21 occurrences in 2020. All keywords that were investigated had a positive trend between 2010 and 2020. A delve deeper into the most important author keywords has been performed, between 2018 and 2020, where “supply chain management” was the most representative term, with a frequency of 529 in 2020, 496 in 219, and 409 in 2018, followed by “sustainability” with 149 appearances in 2020, 108 in 2019, and 95 in 2018, while “supplier selection” had a frequency of 19 in 2018, 20 in 2019, and 21 in 2020, resulting in a positive trend for all three keywords that have been evaluated.

Similar to Figure 16, in Figure 17, the most representative keywords for the abstracts are grouped in clusters, existing only two clusters. On the top right part of the graph is the cluster that explains the sustainability of Grey systems and how the topic evolved, while on the bottom left part is the results of the models that have been developed. Similar results have been observed in the academic community. Fang et al. [59] investigated the topics of Grey systems and supply chain management, observing “sustainability”, “sustainable supply chain management”, “case study”, “sustainable development”, or “structural equation modeling” as the most representative keywords. Pan et al. [58] discovered “supply chain integration”, “environmental management”, “case study”, “performance measurement”, or “green supply chain management” as key terms in supply chain management and Grey systems areas.

Figure 18 explores the most used keywords plus, grouped in two clusters, based on the thematic.

The red cluster, which is the most representative, contains areas where Grey systems theory was applied, such as “co2 emissions”, “renewable energy”, “energy consumption”, and “management”, together with the models and factors that could influence the results of the investigation “fuzzy ahp”, “decision making model”, “fuzzy topsis”, “COVID-19”, and “data envelopment analysis”. The research conducted through this cluster focuses on linking methods of increasing the sustainability level. In order to intensify the usage of renewable energy or to reduce greenhouse gas emissions and energy consumption, the studies use different decision-making methods including the Grey systems theory to identify what tools can be used for this purpose. The second cluster, colored in blue, which is much smaller, investigates the supply chain domain and the algorithms that are used, “anp”, “topsis”, “dematel”, and “perceptron”. As opposed to the first cluster, this one focuses on a more specific theme regarding the supply chain management and on decision-making methods with reference to the characteristic processes. According to Yin MS [35], Pan et al. [58], and Fang et al. [59], the results obtained are similar, with the Grey systems theory focusing on “sustainable development”, “innovation”, “supply chain management”, “decision making”, or “relational analysis”.

Figure 19 includes the main terms that have been used in titles, grouped in three clusters. The most important cluster, colored in red, explores the implementation of Grey systems theory in sustainability and digitalization, containing the following terms: “sustainability”, “study”, “resilience”, “supply”, “production”, “development”, “grey”, “approach”, and “economy”. These documents present the collective interest towards the effects of implementing Grey systems on sustainable decisions. The containing terms suggest possible areas that are frequently influenced by sustainable policies, such as the supply chain and the level of production. As the global economy is developing on multiple levels, sustainable policies are considered in many decisions concerning the well-being of the environment and of the people. The second cluster, colored in blue, focuses on the multi-criteria decision-making selection process, including the following terms: “multi-criteria”, “selection”, “hybrid”, “uncertainty”, or “integrated”. This cluster is primarily concerned with the methodological aspects of decision-making. This type of research aims to discover new techniques for improving the effectiveness of selecting the best approach, and the content of the paper typically includes demonstrating the usage of the new proposed method using a case study. The last cluster, colored in green, presents the impact of the methods from different perspectives: “countries”, “economy”, “growth”, “emerging”, and “efficiency”. In this situation, the emphasis evolves to a more extensive level, considering several concepts that are widely acknowledged in most studies. Analyzing the academical research that has been performed on the investigated topics, the outcome has been similar to the existing results, as Yin MS [35], Pan et al. [58], and Fang et al. [59] discovered “sustainable”, “grey”, “supply chain”, “management”, and “system” as the main keywords.

Figure 20 presents the factorial analysis of the abstracts, grouping the terms into two different clusters. The most representative cluster, colored red, includes the sustainability methods, findings and results of the researchers, containing the following terms: “sustainability”, “research”, “evaluation”, “analysis”, “process”, “findings”, and “factors”. The articles included in this cluster mostly focus on evaluating the evolution of adopting sustainable actions and the factors with a significant impact on the environment. The second cluster, colored blue, focuses on three areas where the Grey systems, sustainability, and digitalization have a significant impact: “social”, “environmental”, and “economic”. Delcea and Cotfas [16,60] and Fang et al. [59] investigated the Grey systems theory and discovered that “model”, “system”, “sustainability”, or “grey theory” are the most representative terms.

Figure 21 investigates the thematic evolution of the main keywords plus between 1997 and 2024, divided into three periods: 1997–2019, 2020–2021, and 2022–2024. In the first period, the main topics discussed were about “co2 emissions”, “china”, “indicators”, and “model”. The Chinese researchers tried to apply the Grey systems theory in multiple ways, in order to achieve great results in sustainability and digitalization areas. The variety of the trends increased between 2019 and 2020, including the existing “barriers”. An important role in Grey systems theory became the “prediction” and the “performance” of the “model”. The domain extended also in the “management” area. Starting with 2022, the focus of the authors was on “frameworks” and “municipal solid waste”. The segmentation in three different periods has been chosen based on the number of publications released and the mean yearly citations. According to Figure 3 and Figure 4, in 2019, there was a significant decrease in the number of papers published, while in the 2020 and 2021 period, there was a positive trend in the number of documents released. In 2020, there was also an important increase from an average citations per year perspective. According to Fang et al. [59], the highest number of papers was observed in 2019, and numerous terms, such as “sustainable supply chain”, “environmental management”, “supply chain integration”, and “optimization”, had the highest frequency in 2019, representing a key year. At the same time, in 2020, numerous terms had the highest frequency, such as “supply chain management”, “environmental performance”, or “sustainable development”. The evolution is mainly expressing the topic changes that occurred in the Grey systems theory, which is developing from a theoretical subject to an applied topic.

Figure 22 evaluates the trends that appeared during the analyzed period on Grey systems theory, sustainability, and digitalization in authors keywords. In the first period, between 1997 and 2019, the main topics that were discussed were related to “sustainability”, “sustainable development”, and “grey prediction”. Between 2020 and 2021, the focus was still on “sustainability” and “sustainable development”, but it also moved into the “grey-dematel” method and “sustainable development goals”. Starting with 2022, the “grey model” and “sustainable development goals” became also relevant for the researchers. The reason for selecting the 1997–2019, 2020–2021, and 2022–2024 periods is similar with the one that has been explained in Figure 21, thanks to the research of Fang et al. [59]. The distribution of the words reflects the topic evolution, detailing the sustainability applicability of Grey systems theory solutions such as DEMATEL.

Figure 23 is strongly correlated with Figure 22, presenting the thematic evolution as a map.

In order to be able to outline a perspective of future development directions for authors, thematic maps play an essential role. Thus, through the perspective of authors keywords, titles, and abstracts, the conclusion is that the “motor” themes that benefit from increased attention, as predicted to be of mainstream interest in the future, are the themes that have in the foreground the very novelty brought by this study, namely Grey systems. The intersection of the three categories of themes in full ascension, “grey”, “sustainable”, and “study” for abstracts, “sustainable”, “sustainability”, and “grey” for titles, and “grey-dematel” for authors keywords is represented by the grey area.

There are six clusters in total, with different sizes, which express the importance of the cluster. The most important cluster is colored blue, in the right part of the graph, in the Basic Themes quadrant, entering a bit into the Motor Themes quadrant, having a high centrality and a medium density. The main terms are related to Grey systems theory, resilience, and sustainability: “sustainability” (seven appearances), “grey theory” (five appearances), “grey systems theory” (three appearances), “grey model” (two appearances), “resilience” (two appearances). The second cluster, which is in the Basic Themes quadrant, with a small density and a high centrality, contains information related to Grey systems evolution together with the sustainability evolution “sustainable development” (five occurrences) and “grey prediction” (three occurrences). The last four clusters, which are spread in the remaining three quadrants, Motor Themes, Emerging or Declining Themes, and Niche Themes, focuses on Grey systems theory methods, such as “grey-dematel” (two appearances), “best-worth method” (two appearances), “sustainable supplier selection” (two appearances), or the objectives that should be achieved from the environmental perspective “sustainable development goals” (two appearances) and “environmental sustainability” (three appearances). Also investigating the academical research, similar results have been observed in articles published by Fang et al. [59] and Pan et al. [58], which discovered “supplier selection”, “sustainability”, “environmental performance”, “sustainable development”, “grey model”, and “grey prediction” as the most used keywords in the topic of Grey systems. The keywords highlight the focus of the topic, on sustainable evolution and supplier selection optimization.

Having considered the findings of thematic evolution and factorial analysis, we can now confirm the third hypothesis H₃, arguing that Grey systems theory has recently become a domain with numerous applications, such as sustainable development and environmental sustainability. Further discussions on the multiple dimensions of the domain’s applicability, such as economic benefits, sustainability, environment, energy consumption, and carbon emissions will be provided in sub-Section 4.2.

Figure 24 explores the collaboration network of the 30 most important authors, which are grouped into seven clusters. The most representative cluster is colored red, and it contains the following authors: Liu SF, Tang XJ, Xie NM, and Javanmardi E. The most important authors in the Grey systems theory, Xie NM and Liu SF, together with Javanmardi and Tang XJ, explored the existing challenges of sustainable development of Grey systems theory, or explored the methods and application of Grey systems theory in sustainability or the possibility of sustainable supplier selection for a company in Senegal by using Grey relational analysis [61,62,63].

The second cluster is colored in blue and contains six authors, Rajesh R, Ali SM, Karuppiah K, Paul SK, Sankaranarayanan B, and Kabir G, who investigated the modeling of the interrelationship in supply chain management barriers in order to have a sustainable business in the leather industry or the Artificial Intelligence methods to predict the supply chain performance and which is the impact on sustainability. Other topics that were discussed are related to the exploration of the main barriers based on the integrated approach in order to have a sustainable predictive maintenance or which are the circular economy practices in the leather industry by using an integrated approach together with the impact for the sustainable objectives in the development of the growing economies [44,47,64,65].

The third cluster, represented with a green color, is formed by two authors, Ferasso M and Ikram M, focused on the prediction and assessment of the environmental sustainability by making a comparative analysis between China and USA, presenting the sustainability standards to sustainable development objectives by using an integrated Grey system method and exploring the environmental sustainability in Pakistan, based on ISO 14001, the green economy, and governance indicators [66,67,68].

The fourth cluster, colored in purple, contains two authors, Kokocinska M and Nowak M, who explored the economic growth toward sustainable growth by implementing a Grey system theory method, having a use case on small countries that are in advanced and emerging economies and creating an efficiency ranking or measuring the efficiency of the economic growth towards sustainable evolution using a Grey system theory algorithm and to understand the efficiency of economic growth by including a Grey system theory approach in the Eurozone with other European countries, measuring also the efficiency of the methods [69,70,71].

The fifth cluster, colored in yellow, is represented by two authors, Dong L and Gao ZQ, who focused on defining sustainable methods of sewage sludge-to-energy in China, also finding the barriers and technologies that should be prioritized and to understand the main success factors for sustainable evolution of the biofuel industry in China using a Grey decision-making trial and evaluation laboratory, known as DEMATEL [72,73].

The sixth cluster, colored in brown, is formed by two authors, Sarkis J and Bai CG. The authors investigated the possibility of integrating sustainability in the supplier-selection process by using the Grey system and rough set methodologies and Topsis analysis or to develop a sustainable transport fleet by testing a hybrid multi-objective decision-making algorithm [50,74,75].

The seventh cluster, represented by pink, contains two authors, Dai SY and Li Y, and the researchers evaluated the sustainability of power grid projects by applying a Topsis and Least Square Support Vector Machine algorithms, together with a Modified Fly Optimization process or to forecast the CO₂ emissions in China by using GM(1,1) and the Least Square Support Vector Machine Optimized with Modified Shuffled Frog Leaping method in Sustainability [76,77].

Table 4. Top 10 most used bigrams.

Bigram Titles	Frequency of Bigram Titles	Bigram Abstracts	Frequency of Bigram Abstracts
Sustainable development	31	Sustainable development	112
Supply chain	13	Supply chain	48
Supplier selection	11	Digital economy	34
Digital economy	7	Supplier selection	32
Grey system	7	Evaluation laboratory	28
Success factors	5	Prediction model	28
Economic growth	4	Grey model	23
Emerging economies	4	Water resource	19
Decision-making framework	3	Economic growth	16
Multi-criteria decision-making	3	Energy consumption	14

presents the most used 10 bigrams (group of two words) in titles and abstracts. The first two columns describe the titles, while the last two explore the abstracts. The most used bigram in titles is “sustainable development”, which appeared 31 times, followed by “supply chain”, with 13 occurrences, and “supplier selection”, with 11 appearances. In fourth place is “digital economy” with 7 appearances, followed by “Grey system” with 7 occurrences. The last 5 bigrams have a smaller impact but are worthy of being mentioned: “success factors” (5 occurrences), “economic growth” (4 occurrences), “emerging economies” (4 occurrences), “decision-making framework” (3 occurrences), and “multi-criteria decision-making” (3 occurrences).

The bigrams can be grouped into two categories: the first one is related to sustainability and Grey systems theory, such as “sustainable development”, “supply chain”, “supplier selection”, “digital economy”, “Grey system”, “decision-making framework”, and “multi-criteria decision-making”. The second category is related to the impact of the Grey system theory implementation “economic growth”, “success factors”, and “emerging economies”. The most used bigram in abstracts is ”sustainable development” with 112 appearances, while “supply chain” appeared 48 times, “digital economy” 34 times, “supplier selection” 32 times, “evaluation laboratory” 28 times, “Grey model” 23 times, “water resource” 19 times, “economic growth” 16 times, and “energy consumption” 14 times.

Similar with titles, the abstracts bigrams can be grouped into two categories. The first category presents the methods of implementation for Grey systems theory, sustainability and digitalization, such as “sustainable development”, “supply chain”, “digital economy”, “supplier selection”, “evaluation laboratory”, “prediction model”, and “Grey model”, while the second category contains the domains where the methods are applied and what is the impact on “water resource”, “economic growth”, and “energy consumption”.

The most frequent bigrams in Table 4 reflect the main themes addressed by the extracted articles. Regarding the use of grey systems for sustainability decisions, the focus is on supply chain systems. Specifically, supplier selection and sustainable development represent the most researched areas. The link between the two topics has been studied in the specialized literature with results that encompass the idea that there is a strong positive link between the supply chain strength and sustainable development goals [78] and the idea that strategic decisions play an important role in supply chain collaboration (SCC) and SDG performance [79]. The concept of digitalization is examined in connection to the elements previously addressed, although less frequently, as the term “digital economy” appears 34 times in the abstract and 7 times in the title. In the most cited paper on the topic of sustainable development, Liang et al. addresses the most significant success factors for applying initiatives to promote the subject [72]. The study presents a methodology for identifying such features, as well as solutions for making strategic decisions concerning how to implement the relevant policies. It shall be specified that the bigrams that have been extracted from the papers included in the dataset are pointing out the main methods of implementation and key factors of the investigated domain, but without providing any details of the correlation between the notions.

Table 5. Top 10 most used trigrams.

Trigram Titles	Frequency of Trigram Titles	Trigram Abstracts	Frequency of Trigram Abstracts
Sustainable supplier selection	5	Evaluation laboratory DEMATEL	12
Grey system theory	4	Grey systems theory	12
Supply chain management	4	Supply chain management	11
Chinas digital economy	2	Sustainable supplier selection	9
Corporate sustainable growth	2	Circular economy practices	8
Digital economy development	2	Grey decision-making trial	8
Grey prediction model	2	Chinas digital economy	7
Integrated multi-criteria decision-making	2	Natural gas industry	5
Support vector machine	2	Ecosystem sustainable development	5
Analyzing key factors	1	Analytical network process	4

includes the most used groups of three words, known as trigrams, in the titles and abstracts. The first two columns focus on titles, while the last two are on abstracts. The most used trigrams in titles are “sustainable supplier selection”, which has a frequency of five, followed by “Grey system theory”, which appeared four times, while “supply chain management” appeared four times. The rest of the trigrams have a smaller number of appearances and a smaller impact but are worthy of being mentioned: “Chinas digital economy” (two appearances), “corporate sustainable growth” (two appearances), “digital economy development” (two appearances), “Grey prediction model” (two appearances), “integrated multi-criteria decision-making” (two appearances), “support vector machine” (two appearances), and “analyzing key factors” (one appearance). On the right part, the most used trigrams in abstracts are presented. The highest frequency is for “evaluation laboratory dematel” and “Grey systems theory” with 12 appearances each ne. In third place is “supply chain management” with 11 occurrences, “sustainable supplier selection” and “Grey decision-making trial” with 8 appearances each, followed by “Chinas digital economy” with 7 occurrences. The last three trigrams are “natural gas industry”, “ecosystem sustainable development”, and “analytical network process” with 5, 5, and 4 appearances.

The trigram titles can be grouped into two categories: the first one focuses on sustainability and Grey systems theory methods, such as “sustainable supplier selection”, “Grey system theory”, “Grey prediction model”, “integrated multi-criteria decision-making”, and “support vector machine”, and the second category focuses on the domains where the methods are implemented, such as “supply chain management”, “Chinas digital economy”, “corporate sustainable growth”, “digital economy development”, and “analyzing key factors”.

Regarding abstract trigrams, two categories can also be created, with similar usage; in the sustainability and Grey systems theory methods, there are the following trigrams: “evaluation laboratory dematel”, “Grey systems theory”, “sustainable supplier selection”, “Grey decision-making trial”, “analytical network process”, and the areas where the methods are implemented, “supply chain management”, “circular economy practices”, “Chinas digital economy”, “natural gas industry”, and “ecosystem sustainable development”.

The findings regarding the themes covered are similar to ones noticed in bigrams since the articles mostly target the implementation of decision-making techniques on the subject of sustainability, mainly, and on the subject of digitalization, secondarily. The findings regarding the themes covered are similar to the ones noticed in the bigrams since the articles mostly target the implementation of decision-making techniques primarily based on the topic of sustainability and, to a lesser extent, on the topic of digitalization. The analysis becomes more focused and specific given that an increased number of terms is examined, and the novelty lies in addressing a niche theme that the trigram “laboratory evaluation dematel” presents, which has become a mainstream topic in the field of decisions according to Si et al. [80]. In collaboration with “grey systems theory”, which has the same frequency, these articles consider specific methods of approaching the issue of sustainable digitalization, with the goal of analyzing the causal relationship of the components found in the sustainable-digitalization system [80]. The significant article on sustainable supplier selection suggests an innovative approach incorporating Grey systems theory as an alternative to conventional methods [81]. Mahmoudi et al. discuss the importance of adopting high-accuracy measures considering that the supply chain has a significant impact on global sustainability. The findings of this study demonstrate that the proposed model produces useful outcomes in real-world scenarios within the setting of a Grey system characterized by uncertainty.

Figure 25 details the 50 most used author keywords and keywords plus, which are represented as a WordCloud, thanks to the R programming language Biblioshiny, which contains various graphical representations. On the left part, the 50 most used authors’ keywords are described. The most used authors’ keywords are “sustainability” (25 appearances), “sustainable development” (23 appearances), “Grey theory” (22), “dematel” (12 appearances), “Grey systems theory” (8 appearances), “Grey-dematel” (6 appearances), “Grey model” (6 appearances), “Grey prediction” (6 appearances), “Supplier selection” (6 appearances), and “COVID-19” (5 appearances). The most relevant keywords plus are presented on the right part of the graph. The most used terms are “model” (31 occurrences), “management” (27 occurrences), “performance” (27 occurrences), “selection” (18 occurrences), “barriers” (13 occurrences), “framework” (13 occurrences), “criteria” (11 occurrences), “supply chain” (11 occurrences), “indicators” (9 occurrences), and “systems” (9 occurrences). According to the most prevalent terms, the articles focus on defining the most relevant methodologies for analyzing sustainability and digitalization, as well as examining elements pertinent to the subjects in question. Therefore, among the methods studied are concepts from the field of Grey systems theory, such as Grey predictions, Grey model, Grey DEMATEL, and decision theory approaches, and the adjacent areas researched consist of quantifying performance at the economic level but also identifying possible barriers encountered in the implementation of digitalization and sustainability guidelines, as well as measures to overcome those barriers. Fang et al. [59] found “dematel”, “sustainable development”, and “sustainability” to be the main terms that have been used in the topic of Grey systems and supply chain management.

4. Discussion and Limitations

The fourth section presents the results of the bibliometric approach, together with the most important topics that were presented in the articles, and which are the main limitations.

4.1. Bibliometric Results Discussion

In the first subsection, the focus will be on detailing the results obtained during the bibliometric process, such as the most important sources, countries, and how the domain evolved from an academical perspective.

The investigation that has been performed by using bibliometric methods offered a complete perspective on Grey systems theory, sustainability, and digitalization, presenting multiple perspectives of the domain’s applicability. Thanks to technological advances in the last few years, in more and more areas, the implementation of Grey systems theory was a success, facilitating the decision-making process.

Starting with 2020, the domain grew significantly, having, in 2020, a total of 12 papers, and in 2021 and 2022, there were 21 papers published in each year, while in 2023 it achieved the peak with 28 articles. In 2024, there were, in total, 20 papers published.

The most representative journals based on the number of papers published were extracted during the investigation: Sustainability (20 papers), Journal of Cleaner Production (19 articles), Business Strategy and the Environment (4 articles), Environment Development and Sustainability (4 articles), Heliyon (4 articles), Sustainable Production and Consumption (4 articles), Benchmarking-An International Journal (3 articles), Environmental Science and Pollution Research (3 articles) and Grey Systems-Theory and Application (3 articles), and Annals of Operations Research (2 articles).

Based on the number of publications and citations, China is the most representative country, having 83 papers published and 1731 citations, having the highest impact on Grey systems theory, sustainability, and digitalization areas. In second place is India with 26 papers and 600 citations, followed by Poland with 6 papers and 123 citations. In fourth place is Iran with 5 articles and 112 citations, while USA has 4 articles and 649 citations, Bangladesh has 3 documents and 50 citations, Brazil have 3 papers and citations 28 citations, and Turkey has 3 articles and 92 citations. Australia published 2 articles, obtaining 248 citations, while the last country in top 10 is Chile with 2 documents and 3 citations. Comparable papers were analyzed, and the results were similar, with Pan et al. [58] having China as the most important country in the Grey systems theory domain, with USA, UK, India, Turkey, Australia, and Iran in the top.

The collaboration network was also a key step in the bibliometric analysis. The most significant collaboration was between China and USA with eight articles, followed by China–UK and India–Bangladesh with five papers each. The following seven collaborations achieved three documents published: Bangladesh–Australia, China–Australia, China–Brazil, China–Denmark, China–Japan, and India–UK. Bangladesh and Canada published together a total of two publications. Pan et al.’s [58] results were similar, having China and USA as the most important countries in terms of collaboration, including also Japan, India, UK, or Canada.

Given that pertinent elements pertaining to the degree of research are emphasized, this topic is essential to the study of Grey systems theory and its effects on sustainability and digitalization. The journals Sustainability, Journal of Cleaner Production, Business Strategy and the Environment, Environment Development and Sustainability, and Heliyon play an important role in providing a broad overview of the research by presenting the majority of the retrieved articles.

4.2. Discussion Based on Investigated Themes

In the second subsection, the main themes that were discovered during the bibliometric approach will be explored, offering a clear view of the domain and of multiple aspects, such as economic benefits, sustainability, the environment, energy consumption, and carbon emissions.

Effects of Grey Systems on Sustainable Development and Environmental Sustainability

The implications of Grey Systems in the area of sustainable development and the environment are important, providing a significant evolution for economic benefits, environmental protection, or social inclusion. Hi and Liu [82] discovered that the Grey Relational Analysis (GRA) method is one of the most used, together with Grey Forecasting, in the sustainable development area.

Ikram et al. [68] used the Grey Systems models, such as the optimized discrete Grey model (ODGM), nonhomogeneous discrete Grey model (NDGM), and variable speed and adaptive structure Grey model (VSSGM) to forecast the CO₂ emissions and the renewable energy production for China and USA, showing that China will pass USA starting with 2026 in the production of energy from renewable sources, but the CO₂ emissions will decrease more rapidly in USA than in China from 2026.

Nowak and Kokocinska [69] explored if the countries that are not part of the Euro area have a bigger efficiency, according to the results obtained by the Synthetic Efficiency Indicator for Economic Growth (SEI-EG), which provides sustainable development outcomes based on economic growth information. The investigation has been performed on the European Union countries between 2019 and 2021, containing multiple indicators about innovation, industry, and infrastructure.

Delcea et al. [83] discovered multiple strategies that provide optimal solutions for airplane boarding, increasing the efficiency and sustainability for airlines, also influencing the ticket policies. Airports can also benefit from the implementation of Grey systems application, optimizing the boarding strategy, and offering more services. The research included the aircraft dimensions and whether the passengers had hand luggage or that they needed more storage, together with the airplane occupancy.

Ikram et al. [67] considered Grey systems solutions for certification bodies and to understand the sustainability standards, exploring the Grey Delphi and Grey Analytical Hierarchy Process in order to extract the main factors that contribute the most to certification bodies. The outcome is important not only for researchers, but also for managers, decision-makers, and government agencies.

Ren et al. [73] combined Grey theory and a Decision Making Trial and Evaluation Laboratory (DEMATEL) in order to determine the sustainable development for sewage sludge-to-energy in China. Together with DEMATEL, a Grey Multi-Criteria Decision Making (MCDM) tool has been implemented, prioritizing the technologies. The MCDM model analyzed three different solutions for sludge-to-electricity, and the results confirmed, as a solution, the alternative technologies for sewage sludge-to-energy for the Chinese population.

Similar approaches have been used by Rajesh [84] and Duman et al. [85] in their papers, where they focus on accurately predicting the sustainability of supply chain areas using Grey theoretical methods and integrating the environmental methods in the food industry.

Effects of Grey Systems on the Energy Consumption, Carbon Emission, and Energy Generation Forecasting by using Machine Learning Models

The Grey Systems, as it was presented during the bibliometric analysis, are a domain that became popular, and this started to be applied to real scenarios, combined with other technologies, such as Machine Learning, in order to predict carbon emissions, energy generation, or energy consumption. Saxena et al. [86] applied a Grey Machine Learning polynomial algorithm, which estimated the power consumption, CO₂ emissions, and power production, providing great results compared to traditional Grey models.

Wu et al. [87] implemented the Grey systems techniques in order to predict the water demand in one of the biggest cities in China, Chongqing, also offering recommendations for the sustainable development of the urban water consumption. The Grey water-forecasting model (GWFM) simulated the water consumption level of the city between 2009 and 2015 and predicted the 2016 level, indicating optimal recommendations and measures that should be applied in order to have sustainable water consumption and to increase the economic development of Chongqing.

Dai et al. [76] used Grey systems methods to forecast the CO₂ emissions in China, implementing the Grey model and Least Squares Support Vector Machine (LSSVM) by taking into account the carbon emissions, energy consumption, coal consumption, Gross Domestic Product (GDP) per capita, urbanization development rate, imports, and exports. The results offered solutions to have sustainable development and to minimize CO₂ emissions.

Niu et al. [77] evaluated the power grid projects development by combining Grey systems theory and the Technique for Order Preference by Similarity (TOPSIS) method, investigating 17 criteria that describe the technology, environment, society, and economy. The results were obtained by also using the Modified Fly Optimization Algorithm (MFOA) and Least Square Support Vector Machine (LSSVM).

Tang and Liu [88] considered crucial the sustainable growth competences, together with the efficiency. Grey entropy is very useful to identify the suitable methodology and theory that is applicable for growth evaluations, since it has the capability to change trends and structural features.

Similar approaches have been used by Sharma YK and Sharma S [89] and Ali et al. [64], which implemented Grey methods in order to predict the success factors in the area of the food supply chain the performance of the investigated domain.

Effects of Grey Systems on Economical Activities

Agarwal et al. [90] evaluated the public and private partnership in order to obtain sustainable agriculture by implementing the Grey DEMATEL algorithm, increasing the productivity in the agriculture and food areas. Understanding the major problems in the public–private partnership (PPP) in India and how PPPs could develop the agriculture sector by providing advantages to farmers and attaining sustainable development.

Sutthichaimethee and Dockthaisong [91] explained the influence of the relationship among social, economic, and environmental factors. Multiple models have been tested, such as the Grey model, regression algorithm, artificial neural network, autoregressive integrated moving average model (ARIMA), or back propagation neural network. The variables that were included in the model were the GDP, industrial structure, net exports, energy consumption, energy intensity, and others. The Grey model had a very small mean absolute percentage error (MAPE) of just 1.01% and a root mean squared error (RMSE) of 1.25%, representing the optimum solution.

Pandey et al. [92] investigated the blockchain technology, supply chain sustainability, and resilience, implementing a Grey–DEMATEL solution, which offers an overview of the most important blockchain technology critical success factors among 21 that were included in the analysis. Standardized Data Management and Smart Ordering are the most important factors that facilitate supply chain sustainability and resilience.

Sousa et al. [93] analyzed the Brazilian companies based on the quality of sustainability, using a Grey clustering method, investigating the balance, clarity, reliability, timeliness, comparability, and accuracy, according to the Global Reporting Initiative (GRI) standards. The Grey fixed weight clustering algorithm has been utilized, and the outcomes described as crucial factors are the transparency and accountability for countries that are developing.

Diba and Xie [63] explored the Grey systems in order to obtain the optimum suppliers for the Satrec Vitalait Milk Company, which is located in Senegal, by taking into consideration the environmental, social, and economic factors, proposing supply chain management using the Deng Grey Relational Analysis (GRA), absolute GRA technique (ADGRA). In the end, decision-making has been used, as Hurwicz criteria, which are mainly used when uncertainty occurs.

Xiao et al. [12] and Bai and Sarkis [50] defined the sustainability for supplier selection and evaluated the digital economy for China by implementing Grey System methods, similar to the approaches that have been used for the economic activities.

Effects of Grey Systems in the Literature Evaluation

Hu and Liu [82] explored the sustainable development of Grey Systems Theory by performing a literature review of the documents that have been published between 2011 and 2021, presenting the applicability of the domain of the economic activities, environmental activities, and social inclusion, extracting the key studies and the outcomes of using Grey Systems theory methods. The papers that were investigated were extracted from the WoS database.

Aslani et al. [94] evaluated the Grey Systems Theory in the area of supplier selection and multi-criteria decision-making, using the existing literature, which recommended to include social, environmental, and economic into the research. A combined method that contains a best–worst method (BWM), Grey theory, and TOPSIS algorithm composed the framework that has been tested on a real case study, demonstrating the reliability of the model.

Javanmardi et al. [61] investigated the literature of Grey Systems theory related to sustainability, existing methods, and applications, which solves complex problems and increases the sustainability. The scope of the research was to identify the importance and applicability of Grey Systems Theory in sustainability problems, from economic, social, and environmental perspectives, analyzing WoS, Scopus, and ScienceDirect databases.

Yin et al. [95] elaborated on a literature review on sustainability and the environmental impact on the cryptocurrency domain and how the group decision-making process is projected. Since the topic was recently discovered, literature has not developed. The researchers developed a fuzzy weighted Grey similarity model, which evaluates the decision-making and a sustainability measure of the cryptocurrency, also classifying the currencies based on their sustainability.

Javanmardi et al. [96] performed a literature review analysis of conceptual and philosophical foundations of the Grey Systems domain, presenting the main principles. The human knowledge of Grey Systems is imbalanced among multiple disciplines, and according to the definition of the topic, the main principles are related to dynamicity, which makes the domain constantly evolve, forcing humans to continuously gather new information. As the results demonstrated, the domain has changed significantly in the last years.

Dong et al. [56] and Wang et al. [97] defined Grey Systems methods that were found based in the existing literature in order to investigate the sustainability of cotton and disaster control.

4.3. Bibliometric Limitations

Although this study manages to provide essential information based on the results obtained, a series of limitations can be identified regarding the extraction of the data used in the analyses. The main limitation identified in this paper refers to the database used to extract the data. In this case, only the WoS database was considered, but for more accurate results, the use of several databases could help outline a much more realistic perspective of the field’s research level.

The second limitation was the restriction on the language that has been added in the extraction process of the dataset. Only English papers were accepted, which, in this case, did not affect the number of the papers included in the dataset, as all the papers extracted were written in English.

The third limitation was the keywords that were used, which might have not covered the entire Grey systems theory, sustainability, and digitalization area, even though we have made all the efforts not to exclude any relevant keywords. The limited number of keywords potentially affected the total number of papers included in the database.

5. Conclusions

The paper provides an extensive overview of the association between Grey systems theory and the implementation of sustainable digital transformation. Featuring a long-term analysis period (1997–2024), the research explores the evolution of articles published in the field while providing pertinent information on authors, documents, journals, sources, countries, collaborations between authors and countries, and the keywords and trends related to the topics addressed. The results acquired in this work manage to address the scientific questions raised in the first section and to confirm the three hypotheses, as illustrated in the bullet points as follows:

• In terms of scientific output in the field, the investigation revealed that the trend is predominantly upward, confirming the increasing research interest in the field. Thus, the first hypothesis H1 was confirmed. The analyzed data revealed a wide range of fluctuations in the number of published papers; the sharpest increases and decreases occurred at the end of the analyzed period, as there was a significant increase in the volume of articles from 2015 to 2018, followed by a sharp decline from 2018; similarly, there was a noticeable increase until 2023, followed by an overall decrease.
• The most relevant authors in terms of number of papers published in the 1997–2024 timespan are as follows: Rajesh R (eight papers), Ali SM (7 papers), Ferasso M, Ikram M, Karuppiah K, Kokocinska M, Liu SF, Nowak M, Paul SK, Sankaranarayanan B, all with three published papers each. The country analysis revealed the following top-down ranking in terms of the contribution in researching the implications of Grey systems theory in sustainable digitalization: China with 83 published papers and a total of 1731 citations, India with 26 papers and 600 citations, Poland with 6 papers and 123 citations, Iran with 5 published papers and 112 citations, USA with a total of 4 papers and 649 citations, Bangladesh with 3 papers and 50 citations, Brazil with 3 papers and 28 citations, Turkey with 3 papers and 92 citations, Australia with 2 papers and 248 citations, and Chile with 2 papers and a total of 3 citations. Based on these findings, the second hypothesis H2 was also confirmed, since Asian countries (especially China), have the greatest contribution in researching the implications of Grey systems theory in sustainable digitalization through published papers and total citations in the field. Moreover, when considering international cooperation, it is important to note that China and India, the two nations with the greatest relevant contributions, prefer the publication of SCP-type papers. Nevertheless, when it comes to collaborating closely as a whole, China, India, the United States, Brazil, Australia, and Chile have the strongest connections.
• The most popular topics in the study of this subject mainly include the themes “Sustainable development”, “Supply chain”, “Supplier selection”, “Digital economy”, “Grey system”, “Success factors”, and “Sustainable supplier selection”. Besides the motor themes that are most commonly tackled in the scientific output, as they describe applications and methods of the implementation of Grey systems theory models, we particularly point towards the niche and the emerging themes in the field through thematic mapping. As niche themes, we highlight the focus on the energy domain, as CO₂ emissions and energy-consumption in the energy sector turned out to benefit from special attention in the literature review and could thus be further explored in terms of policy recommendations and implications upon economic development, the business sector, and the academic field. Thus, studying the decision-making processes of digitalization through the Grey systems theory by incorporating the environmental component represents more of a niche thematic approach in the field. Moreover, the thematic map identifies, as emerging themes, the focus on prediction, growth, and innovation. These items describe the potential growth of the domain, thanks to the innovation process, while focusing on the prediction ability of the Grey systems models. Therefore, future publications that tackle the decision-making of sustainable digitalization through Grey systems theory will focus more on testing the reliability and applicability of the decision-making models that should accurately predict the outcome of the policy implementation. Our factorial analysis indicated some possible areas that are frequently influenced by sustainable policies, such as the supply chain and the level of production.

Finally, through the findings of thematic evolution and factorial analysis, we confirm the third hypothesis, arguing that Grey systems theory has recently become a domain with numerous applications, such as sustainable development and environmental sustainability, by implementing multiple algorithms that predict the CO₂ emissions, airplane boarding, decision-making, and sewage sludge-to-energy. For energy consumption, carbon emissions and energy generation forecasting have used GWFM, LSSVM, TOSIS, and MFOA models for estimating the water consumption, CO₂ emissions, power production, and quality of sustainability. The Grey Systems can also be implemented in economic activities, such as agriculture, supplier selection, or the digital economy using GRA, Grey–DEMATEL, or ARIMA algorithms. For the literature section, the focus was on identifying the major methods that could be applied in social, economic, environmental, and cryptocurrency areas.

The effects of applying grey systems theory to sustainability and digitalization, as well as the measurement of the impact, could be studied in later research. Future analysis will take into account the possibilities of integrating multiple databases in order to extract a more pertinent collection of articles for the chosen field and to uncover related fields that could be valuable for conducting a deeper investigation. Also, for a more comprehensive bibliometric analysis, some different data-extraction criteria could be considered, such as the enlargement of the list of terms, especially the ones related to sustainability and digitalization as this field is in continuous expansion and new terms might arise with time passing.

This article primarily addresses the integration of a specific methodology in the bibliometric analysis to ensure that more precise and comparable findings are obtained. This outcome enhances the academic discussion across the application of conventional techniques for investigating world events to a novel approach suited to the complex nature of the issues such as digitalization in sustainable conditions.