A bibliometric study with statistical patterns of industry 4.0 on business management in the decade

In search of perpetual sustainability, companies need a continuous line of innovation, incorporating new technologies to optimize production; the adoption of Industry 4.0 is marking an important milestone in the deployment of business functions in all areas, adapting from human resources management to manufacturing operations. By leveraging these tools, operational areas can be interconnected to drive productivity. Thus, this research performs a descriptive bibliometric analysis of the influence of Industry 4.0 on business management from 2013 to 2022, using the contribution of physics through the implementation of data mining tools, such as Bibliometrix, whose foundation is given by mathematical and statistical models; in such a way, articles indexed in Scopus and Web of Science were analyzed, focusing on the indicators of citations, bibliography, abstract and keywords. The results showed an exponential growth of articles on Industry 4.0, with manufacturing as the central area of interest, especially in artificial intelligence and big data applications. The most cited articles highlight its role in process optimization. Overall, this bibliometric analysis suggests that the adoption of Industry 4.0 has a positive impact on decision-making, improving the direction of business management.


Introduction
Economic and social changes have generated those human beings, through their adaptive and creative capacity, to generate new technologies for their benefit.In industry, this evolution has been reflected in mechanization and digitalization to manage processes in real-time (the fourth industrial revolution) [1] through the application of algorithms, data compilation methods, and data processing.These technologies have various applications in the different operational areas of companies; for instance, machine learning (ML) plays an optimal role in the design, monitoring, and control of manufacturing, stimulating integrated and continuous processes [2].Likewise, it is used by marketing specialists in the segmentation of customers based on predictions [3].
The approach to the various emerging technological tools is the basis for maximizing the benefits in the business sector.Artificial intelligence (AI) is used in process quality [4] and big data in human resources management [5], together increasing the probability of a better marketing decision to impact consumer satisfaction [6].Likewise, the Internet of Things (IoT) contributes to customer relationship management, good manufacturing practices, and programmable logic control [7].Figures and tables were separately processed and analyzed.Data were extracted from Scopus [11] and WoS [12] databases in BibTeX file type; before manual manipulation, Biblioshiny's RStudio [13] cloud application was used to acquire and organize the information in these two databases.Likewise, Biblioshiny [13] provides data organized regarding the annual production of articles, authors, countries, and journals and the research fields according to keywords, impact factor, and h-index, among other aspects [14].

Limitations
The bibliometric study in the focused databases could be more perfectly aligned with each subject, given that most information is not from open access.The quantitative analysis is usually conditioned to the number of documents available to interested parties [15]; likewise, finding ambiguous information in the search results is feasible, having unavoidable drawbacks for the analysis of qualitative literature [16].

Searching strategy
We inserted a list of keywords in both databases, covering both Industry 4.0 and the areas of business management (see Figure 1); the following terms were used to describe the Industry 4.0 theme: data science, artificial intelligence, data analytics, data mining, Industry 4.0, data processing, machine learning, enormous data, deep learning, the internet of things, and 3D scanning.The following terms were used to represent business management functional areas: manufacturing, customer relationship management, human resources, marketing, production processes, corporate finance, and quality control; these words were obtained through constant interaction in the databases, updating the equation according to the new words found while revising the data delivered in the first search.The time range established covered data during the decade from 2013 to 2022; likewise, the search was reduced to titles and keywords to increase the precision of the search equation.Only original articles were considered as file types.The extraction of information in both databases was on April 3rd, 2023.

Results and discussion
The resolution of the proposed objectives is set out below in a detailed analysis of the data obtained from the Scopus [11] and WoS [12] databases using the above-mentioned methodology.

Trends in the annual production of original papers
Regarding the annual publication trends of both databases, it was possible to corroborate that the growth during the decade from 2013 to 2022 followed an exponential trend (see Figure 2).The number of documents hosted in Scopus [11] is higher than in WoS [12] during the studied timeframe.Also, the average total citation (TC) is slightly higher in Scopus [11], with a scope of 10.44 citations per year, compared to the 8.46 reached in WoS [12] (see Figure 2).The research production between 2018 and 2022 was triggered in Scopus [11] due to the boom in the new technologies from Industry 4.0.Under this temporal context, many industries bet on implementing and taking advantage of the benefits of innovation that represent such technologies in an increasingly competitive business world [18].At the same time, specifically in 2018, the weighted number of citations per year in both databases reached the top positions, which is undoubtedly a clear indicator of the importance that began to be given to the inclusion of new technologies of the fourth industrial revolution in organizations.The decay in the average number of citations per year from 2019 to 2022 is opposed to the number of articles indexed per year.It may respond to reasons such as the high demand for time in identifying newly published documents and their novelty and limited access, accompanied by the current levels of scientific productivity, among others [19].

Most cited research articles
As shown in Table 1, the three most cited articles were written by Lee J, et al. [21], Zhong R Y, et al. [22], and Tao F, et al. [23].The latter is the only one registered in both databases; this article has an average of 1167 citations.It mentions that recent advances in manufacturing have paved the way for implementing cyber-physical systems (CPS), closely monitoring, and synchronizing a factory's equipment and physical spaces, where networked machines can operate more efficiently, collaboratively, and flexibly [21].Zhong R Y, et al. [22] express that through key technologies such as IoT, CPS, cloud computing, big data analytics (BDA), and the use of ICTs, smart manufacturing can be achieved, improving quality and productivity; all of these it, based on taking advantage of data mining.On the other hand, Tao F, et al. [23] detail that manufacturing driven by big data through a digital model will promote better design, manufacture, and service of products.This can be performed using converged cyber data, enhancing their life cycle while making them more efficient, intelligent, and sustainable.The technologies of interest in these three articles are CPS, IoT, and BDA, all focused on manufacturing.These technologies are directly related to ML, as in the case of CPS, which, without ML algorithms, could not deliver high-precision diagnostics.Likewise, it is worth mentioning that these technologies were the most popular in the years of the article's publication.

Author's keywords
Keywords are a faithful reflection of what the wish to convey in their articles, and their appearance reflects the essential points of a specific field of research.The visualization of the word cloud of the Scopus [11] and WoS [12] databases extracted through Biblioshiny [13] (see Figure 3) made it possible to clarify the most relevant keywords used by the authors concerning business management and Industry 4.0.These results highlight that the key terms for business management are manufacturing, quality control, and marketing, while for digitization, they are Industry 4.0, machine learning, and big data (see Table 2).

Figure 3 .
Figure 3. Evolution of research in the areas that make up business management through applying the technologies involved in Industry 4.0 [11,13].

Table 2 .
Author's keywords, where thematic 1 refers to Industry 4.0 and thematic 2 refers to the areas of business management, while f represents the frequency of usability of the words.IMRMPT-2023 Journal of Physics: Conference Series 2726 (2024) 012009

Table 1 .
[12] cited articles in business management studies about Industry 4.0 in Scopus[11]and Web of Science[12]databases from 2013 to 2022.