1. Introduction
The advent of Industry 4.0 and Industry 5.0 marks an unprecedented phenomenon in the evolution of industrial revolutions, because they appeared approximately 10 years apart, Industry 5.0 being intended to complement the aspects imagined by Industry 4.0 emphasizing sustainability, but also the central role that humans have in the production process. Traditionally, industrial revolutions unfolded in linear and chronological progression, with each successive revolution emerging approximately a century apart.
For instance, there was nearly a century between the onset of the first (1784) and second (1870) industrial revolutions, and a similar timeframe passed before the arrival of the third (1969). However, the fourth (2011) industrial revolution materialized in less than half the time previously observed, and Industry 5.0 (2020) swiftly followed within a decade. Thus, almost 100 years have passed since the implementation of mechanized production at the assembly line (at the beginning of the use of electricity); it took another 100 years to introduce technological processes and only 50 years to create cyber-physical systems. However, in less than 10 years, the emphasis is again placed on the important role of humans in the formation of the industry. This compressed timeline between the fourth and fifth revolutions underscores the rapid pace of technological advancement and its profound impact on industrial development [1]. Due to the fact that so far there have not been two industrial revolutions at the same time, it is difficult to put a label on the relationship between Industry 4.0 and Industry 5.0; the problem that arises is related to identifying the type of connection between them, if it is one of co-existence, transition, or a hybrid [2].
Industry 4.0 is a German strategy [3] that epitomizes the deployment of intelligent mechanisms aimed at revolutionizing manufacturing technologies. This strategy is based on the concept of creating a digital twin, a virtual representation of physical processes, to facilitate real-time decision-making. Through this digital twin, smart decisions can be made collaboratively by humans and machines, fostering seamless cooperation between the two entities within the manufacturing environment [3,4,5]. Furthermore, Industry 4.0 is characterized by the widespread adoption of numerous new technologies in the industrial sector. An example is Assembly 4.0 systems, on assembly lines, which represent a point of interest for researchers exploring strategic, tactical, and operational levels to improve productivity and profitability in such systems [6,7]. Industry 4.0 applications are based on various methods that make use of artificial intelligence [8,9,10,11], big data [12,13] digital twin [14,15], blockchain [16,17], Internet of Things [18,19], etc. The high demand from customers, as well as the competition in the market, led to the desire of the manufacturing industry to improve the production system. The creation of a smart manufacturing system is intended to improve performance through smart planning, monitoring, and decision-making assistance by providing quick access to data, resources, processes, etc. [20]. Furthermore, the advancement made in industrial robots tends to boost the Industry 5.0 revolution. According to Statista [21], the size of the global market for industrial robots will boost from approximately USD 43.0 billion in 2022 and is projected to reach USD 70.6 billion by 2028.
Digital twin helps form a smart manufacturing system by creating a virtual system that is able to store information and process data using artificial intelligence algorithms to facilitate decision-making, presenting the best projects in a much shorter time [22]. Increased efficiency and quality are achieved by automating the manufacturing system because it is a complex one that involves large amounts of data and models that can be created, and making such decisions manually would take far too much time [23].
Industry 5.0 has emerged as a complementary extension of the principles laid out by Industry 4.0, trying to form a symbiosis between humans and machines [24]. It seeks to implement these concepts to facilitate the transition towards a more sustainable, resilient, and human-centered industrial landscape [25,26]. A human-centered approach involves devising solutions to adapt Industry 4.0 in a manner that ensures that humans remain the primary driving force behind industrial processes [27,28,29,30,31].
Industry 5.0 transcends mere human-centric interests within the industrial process; it also addresses environmental concerns by promoting the transition towards a green, clean economy. Research on the sustainable aspects of Industry 5.0 is pivotal in bolstering the resilience of manufacturing processes [32,33,34,35,36]. According to the analysis of a number of 196 abstracts in which this concept was identified, five main themes were identified that it addresses: enterprise innovation and digitization, supply chain evaluation and optimization, smart and sustainable manufacturing, human–machine connectivity, and transformation driven by IoT, AI, and big data [37].
The aim of this study is to examine articles that address both industrial revolutions, identifying key sources, authors, and highly cited articles, while also highlighting trends in current research. By applying some selection criteria applied to the documents that contained both studied concepts in the titles, abstracts, or keywords, a total of 154 articles, published between 2020 and 2023 and indexed in the ISI Web of Science database, were analyzed using the Biblioshiny package in R. The methodology section will elucidate the steps involved in extracting and analyzing the relevant information from the selected research. The findings will include the networks delineated by the top 50 authors, the thematic content of the 10 most cited articles, and the interconnected concepts pertinent to the scope of this study.
2. Materials and Methods
The research methodology outlines the key stages involved in conducting the current study and elucidates the process for accessing the analyzed documents. The presentation of the information utilizes the Biblioshiny package [38], following a structure commonly employed in bibliometric analyses in various domains [39,40], including those focused on topics such as Industry 4.0 or Industry 5.0 [41,42].
Before conducting the bibliometric analysis, it should be stated that the papers have been extracted from the Clarivate Analytics’ Web of Science Core Collection database, formerly known as the ISI Web of Science database and referred to as the “WoS” database in the following [43]. Although other databases could have been used for the dataset extraction, we have opted for the WoS database as it provides a wide coverage for the scientific disciplines included in the database [44,45,46] and is acknowledged throughout the world for its reputation among the scientific community in various fields of research [46,47,48]. Furthermore, as the WoS database provides access to the papers based on a subscription, we need to mention that, when extracting the papers, we have had access to all the indexes offered by the database. This mention of the used indexes offered by the WoS database is in line with the observation made by Liu [49] and Liu [50] when defining the elements to be considered when comparing the results from different bibliometric analyses.
The initial step in conducting a bibliometric analysis involves identifying pertinent papers for the research endeavor (Figure 1).
Following the acquisition of documents containing the selected keywords, those that do not meet the specified temporal and linguistic criteria are excluded, resulting in a refined dataset for analysis.
Subsequently, the analysis phase commences, starting with a comprehensive overview and progressing towards a deeper examination of pertinent data related to publication sources, authors, and research content, ultimately elucidating the interrelationships among these elements.
In the case of documents retrieved from the WoS database, 668 articles incorporating the concept of Industry 5.0 were identified, while 18,268 documents referencing Industry 4.0. were identified; articles where the names of the two concepts were found in the title, abstracts, or keywords, were selected. Through the amalgamation of documents that encompass both concepts, a total of 258 articles published between 2020 and 2023 were selected for scrutiny, comprising 155 articles written in English (Table 1). It should be noted that there may be documents that discussed both concepts, but which were not chosen in the current research because they did not fit the selection criteria. Thus, based on the criteria defined in Table 1, at the time when the current study was carried out, articles from the period 2020–2023 were identified.
The language exclusion criterion which reduced the dataset from 258 to 155 papers has been used in accordance with other papers on bibliometrics from the scientific literature—please consider the works of Fatma and Haleem [51], Stefanis et al. [52], and Gorski et al. [53].
Furthermore, another exclusion criterion has been used based on the type of paper. Therefore, we have selected only the papers marked as “articles” in the WoS database. The rationale behind this decision was related to the extended definition given by the WoS database to the papers included in the “articles” category, which refer to new and valuable research published in a journal and/or presented at a symposium or conference [54]. As a result of this exclusion criterion, the number of papers included in the dataset has been further reduced by one, counting for 154 papers.
A summary of the steps needed to extract the dataset related to both Industry 4.0 and Industry 5.0, in the context of the imposed limitation criteria, is presented in Table 1.
Among the results obtained from the analysis of the identified articles, we note general information related to the average number of citations, the annual growth rate, the number of keywords, the collaboration rate between international authors, etc. Then, it goes deeper with information about the sources where these articles were published such as the most productive sources, Bradford’s law on source clustering [55], or H-index. The H-index is calculated according to the number of publications as well as the number of citations, so that an H-index whose value is h symbolizes the fact that h publications have at least h citations each [56]. Information is presented on the most productive authors and the relationships formed between them and other collaborating authors, as well as productivity and collaborations between countries. For the study of the specialized literature, the scientific contents of the first 10 most cited articles are discussed together with the most frequently encountered keywords. The research ends with the presentation of the relationships formed between the top 20 authors and their countries or affiliations and the most popular sources or keywords used by them.
3. Dataset Analysis
This section is dedicated to the analysis of the documents obtained according to Table 1 from the previous section, presenting elements related to the most relevant sources and authors who chose to research this theme, providing information about the general content, but also specific aspects of the papers chosen in this study.
3.1. Dataset Overview
This section provides a broad overview of the extracted documents. Table 2 is a result of a first analysis conducted on the dataset. As a result, it offers insights into the temporal scope of the analysis, indicating that the investigation into the relationship between Industry 4.0 and Industry 5.0 commenced in 2020 and concluded at the end of 2023. It shall be noted that the 2020–2023 time interval is a consequence of the chosen keywords and not a criterion when selecting the papers. The time of the onset of articles appearing in the WoS database discussing both concepts in the title, abstract, or keywords is the year 2020.
During this four-year period, 154 articles were penned on this topic, disseminated across 83 distinct sources. These articles garnered an average of 17.35 citations per document, with an average time lapse of 1.7 years since publication.
Notably, the annual growth rate stands at an impressive 119.47%, underscoring the escalating interest among authors in publishing papers that help them explore the ramifications of these industrial revolutions. It shall be noted that for the annual growth rate, the value is offered by Biblioshiny [38]—part of the Bibliometrix R package.
There is also a significant number of references, 11,064, which means an average of approximately 72 references per document, reflecting the thorough documentation undertaken by authors throughout their research endeavors.
An upward trend can be observed from Table 3; in the first year, seven articles were written, and in the second it seems that this number doubled, reaching fourteen published articles. This was followed by a huge expansion in the year 2022, with 59 articles published on this topic, and reaching 74 articles published in 2023.
Table 4 delineates the authorship dynamics among the 594 individuals who contributed to these articles. Only nine authors opted to publish solo-authored articles. The vast majority—585 authors—collaborated with others, underscoring the collaborative nature of research in this domain. This trend suggests that conducting comprehensive investigations in this field requires collective effort, as evidenced by the collaborative endeavors involving multiple authors.
Regarding the collaboration between authors, according to Table 5, it is found that referring to both the number of published articles and the number of authors, a number of 0.26 documents per author is identified and the ratio between the total number of authors and the number of published documents is 3.86.
Furthermore, the analysis reveals an average of 4.31 co-authors per document, indicating extensive collaboration among researchers. Additionally, the collaboration rate between authors from different countries stands at 40.26%, highlighting the imperative to transcend geographical boundaries to explore the intricacies of these concepts. This index is calculated as the ratio between multiple country publications and single country publications [38].
3.2. Sources
The identification of the sources that have chosen to publish a significant number of articles related to the analysis of the new industrial revolutions is relevant because it presents the interests as well as the directions towards which certain sources are heading.
Table 6 depicts the ranking of sources that have published articles pertaining to Industry 4.0 and 5.0, with Sustainability leading the chart with a total of 17 papers. Following closely, Applied Sciences contributed approximately half the number of papers compared to Sustainability, while Sensors published eight articles.
IEEE Access and The International Journal of Production Research each produced five articles. The Journal of Industrial Information Integration and The Journal of Manufacturing Systems followed with four articles each. Subsequently, several sources, including IEEE Transactions on Industrial Informatics, Information Systems Frontiers, The Journal of Industrial Integration and Management, The Journal of the Knowledge Economy, and Organizacija, have each published three articles on the analyzed topic.
The first five sources have the same impact factor of 3.9, except for Applied Sciences, which has a factor of 2.7. The following six journals have impact factors between 5.9 and 15.7, while the penultimate journal has a factor of 3.3, and the last one does not present such a factor. Strictly speaking of the top 10 journals, one could state that journals with a higher impact factor have a more limited number of articles published on the topic. However, it should also be remembered that the acceptance rate is lower among higher ranked journals.
Another method for assessing the significance of sources is by applying Bradford’s law, which categorizes journals into distinct zones based on the frequency of publications [57,58]. According to this law, in the case where the proportion of the articles in each category would be of one third of all articles, than the number of journals in each group would be proportional with [57,58]. As illustrated in Figure 2, Sustainability emerges as the main source, followed by journals with at least four articles related to the concept published.
In Table 7, sources with an H-index greater than three are depicted. Topping the ranking is Sustainability, boasting seven publications with at least seven citations each, followed by Sensors with five publications, garnering a minimum of five citations each. Applied Sciences and IEEE Access closely follow with an H-index of four.
Additionally, Information Systems Frontiers, The Journal of Industrial Information Integration, The Journal of Industrial Integration and Management, The Journal of Manufacturing Systems, and The Journal of the Knowledge Economy all attained an H-index of three.
Figure 3 illustrates the publication trends of various journals during the analyzed period. Notably, Applied Sciences maintained consistent publication activity, while The International Journal of Production Research began publishing articles relevant to this topic solely in 2023. Furthermore, Sustainability demonstrates a notable surge in interest in this topic, vastly exceeding the output of other journals.
3.3. Authors
In the following, information about the most productive authors, as well as the most productive countries and the collaborations between authors and countries is presented.
In Table 8, the most prolific authors are showcased along with the number of articles they have authored pertaining to the current industrial revolutions. Authors who have contributed at least three studies on this topic have been selected. Leading the pack in terms of contributions to Industry 4.0 and 5.0 research are Abonyi J. and Kumar S., each with five articles to their credit. Following closely behind are Carayannis E.G. and Ghobakloo M., with four articles each. Additionally, authors who have penned three articles each on industrial revolutions include Aguayo-Gonzalez F., Avila-Gutierrez M.J., Faccio M., Iranmanesh M., Oyekan J., Ruppert T., and Turner C.
Figure 4 shows information on the number of articles published by 11 of the most productive authors, with the size of the circle increasing when there are more articles published, while the number of citations increases when the shade of blue is more intense. Regarding the production of articles by these authors during the analyzed period, it is observed that Aguayo-Gonzalez F. and Avila-Gutierrez M.J. each authored two articles in 2021 and an additional one in 2022. These articles received relatively low numbers of citations. The most highly cited articles seem to be those published by Kumar S. and Carayannis E.G. in 2022, with each author contributing three papers.
Starting with the country of the corresponding author, it has been observed that Italy contributed to the domain with 20 articles pertaining to Industries 4.0 and 5.0 (please consider Figure 5). The majority of these articles were authored in collaboration with fellow countrymen, with a quarter of them being written in conjunction with foreign authors. Both India and the United Kingdom contributed an equal number of articles, with approximately half of Italy’s output.
In particular, in Slovakia, all articles were co-authored exclusively with authors from the same country, while in Lithuania, all papers were co-authored solely with authors from other countries. However, in the other countries within the top 20, collaborations with authors from other countries varied in percentage, ranging from lesser to greater extents.
Figure 6 provides a global perspective on countries’ production, with varying shades of blue indicating different levels of research output. Darker shades denote greater research activity in the respective countries. As anticipated, Italy exhibits the most intense coloration (with 51 contributions), followed by India (with 45 contributions), the United Kingdom (with 34 contributions), China (with 34 contributions), Spain (with 20 contributions), USA (with 17 contributions), Germany (with 17 contributions), France (with 15 contributions), and Hungary (with 14 contributions). The remainder of the countries, colored in lighter blue than the previously mentioned countries, have made contributions to up to 12 documents—as mentioned, the darker blue color indicates an increased contribution, with an overall range between one and fifty-one documents.
Figure 6 also illustrates the collaborations between authors from different countries around the world, underscoring the transcendent nature of scientific collaboration across local and continental boundaries. As for the red lines represented in Figure 6, the height of each line represents the intensity of the collaborations among countries, ranging between one and five collaborations.
Notably, a substantial number of collaborations are identified between China and the United Kingdom, as well as between the United Kingdom and India, resulting in five scientific research projects each.
Other countries that have achieved significant collaborations include India and Saudi Arabia, with four joint papers. Additionally, countries such as Lithuania, Malaysia, or China each collaborated on three papers with Australian authors. Furthermore, collaborations between France and Germany, France or the United Kingdom and Italy, as well as between Sweden or Malaysia and Lithuania, resulted in three articles each.
Another method of assessing a country’s contribution in a scientific field is by considering the number of citations, which indicates the visibility and usefulness of works authored by individuals from that country. In this context, Korea stands out with 337 citations, followed closely by New Zealand with 335 citations. The USA secures the third position in the ranking with 286 citations, trailed by Italy with 284 citations, India with 225, and China with 220. Furthermore, Poland and the United Kingdom also have impressive citation counts. Conversely, the remaining countries have citation numbers that do not surpass three figures. Please consider Figure 7 for more details.
Figure 8 shows the network of collaborations made between the first fifty authors, noting that of the 14 clusters formed, approximately half are made between two authors. The largest network, with five nodes (in yellow), is authored by Rega A., Patalano S., Vitolo F., Di Marino C., and Pasquarillo A.; the field of interest of these authors is human–robot collaboration at the workplace [59,60].
There are five cluster groups consisting of four authors. Thus, group number two (pink), formed by the authors Fortuna B., Novalija I., Mladenic D., and Kenda K., is represented by their interest in the role of artificial intelligence in the manufacturing process [61,62]. Ram P.R., Venkatasalam R., Jeyaraman N., and Jeyaraman M. form a third cluster (green), with their object of study being the role of industrial revolutions in regenerative medicine [63]. A fourth cluster is made up of authors Abonyi J., Ruppert T., Eigner G., and Tran T.A. (blue-gray), who write about reducing costs and increasing efficiency as a result of implementing Industry 5.0 and Brownfield [64,65]. Additionally, Abonyi J. and Ruppert T. (together with other authors) wrote an article about Brownfield Industry 4.0 and the development of Industry 5.0 technologies [66]. The next cluster of four authors (grey) includes Avila-Gutierrez M.J., Aguayo-Gonzalez F., De Miranda S.S.F., and Lama-Ruiz J.R. (peach), who wrote about the sustainability of the implementation of Industry 4.0 and Industry 5.0 [67,68,69]. The network formed by Iranmanesh M., Ghobakhloo M., Arman A., and Nilashi M. designates the last cluster that includes four authors, who research the contributions of Industry 5.0 transformation to sustainable development [32,33,70].
Also, there are two clusters made up of three researchers each. Oyekan J., Garn W., and Turner C. (violet–red) make up one of them; these authors study the implications of Industry 5.0 in the circular economy [71]. Oyekan J. and Turner C. have written two other articles together on Lifecycle Analysis [72] and Circular Production [73], while Garn W. and Turner C. conducted research on Discrete Event Simulation [74]. Kumar S., Chan H.I., and Choi T.M. (emerald) form the second cluster composed of three researchers; these authors have written an article on disruptive technologies and operations management [14]. Also, Chan H.I. and Choi T.M. carried out a paper about the logistics process of the future [75].
As for the clusters formed by two authors presented in Figure 8, it is noted that they are six in number, starting from Javaid M. and Hallem A. (blue) who conducted two research papers on the critical components of Industry 5.0 [76] and applications of the industrial revolution in the context of COVID-19 [77]. The next two-author cluster contains Faccio M. and Granata I., who have conducted research on collaborative robot systems from a human-centered perspective [78,79]. Saniuk S. and Grabowska S. (brown) form the next cluster; in their research, they address ways to improve the sustainability of Industry 5.0, starting from the concepts implemented by Industry 4.0 [80,81].
Javed S. and McKayed H. (purple) chose to contribute, through their research, to smart cities [82] and smart energy [83]. Luthra S. and Kumar A. (pink) researched the ability of Industry 5.0 to overcome supply chain disruptions [84], as well as its implementation as a way to improve the omitted sustainability of Industry 4.0 [85]. Dolgui A. and Ivanov D. (dark brown) research the ways in which new industrial revolutions help to create the cloud [86] and metaverse [87] supply chain.
3.4. Analysis of Literature
The literature analysis involves the presentation of the most cited articles together with the central research trends described by the current study.
3.4.1. Top 10 Most Cited Papers—Overview
Table 9 presents the 10 most cited articles, describing information on the number of authors, the regions from which they carry out their research, the total number of citations (TCs), as well as the average annual citations (noted TCYs) together with the normalized citations (NTCs). While the TC and TCY indicators are easy to read and understand, in the case of the NTCs, it should be mentioned that it is determined based on the average number of citations received in a particular year for all the papers included in the dataset, published in the same year as the paper under analysis [88,89].
The most cited paper belongs to Maddikunta et al. [90], collecting a total number of citations of 337, with a TCY score of 112.33 and a NTC score of 13.32. The high value of NTCs shows that the paper authored by Maddikunta et al. [90] has successfully gathered 13.32 times more citations than the average number of citations of the articles in the database published in the same year, 2022.
The second-most cited paper belongs to Xu et al. [91], with TCs closely positioned to the most cited paper, namely 335 citations, accompanied by a TCY score of 83.75 and a NTC score of 8.75.
The remainder of the papers included in the top 10 most cited papers succeed in gathering more than 64 citations, scoring TCYs greater than 14, and NTCs greater than 1.14—please consider Table 6 for further details.
3.4.2. Top 10 Most Cited Papers—Review
Table 10 highlights the content of the 10 most cited articles, observing a common interest in the technologies implemented through the two new industrial revolutions, showing the differences between the two concepts, specifying the technology orientation brought by Industry 4.0, and the focus on value and on the human–machine symbiosis championed by Industry 5.0.
Thus, based on the information in Table 11, it can be observed that the 10 most cited papers discuss various aspects of Industry 5.0, highlighting its potential applications in diverse domains such as health, education, manufacturing, supply chain management, disaster management, and cloud manufacturing.
Moreover, the papers highlight various technologies such as edge computing, big data analytics, digital twin, artificial intelligence, and blockchain, showcasing their role in improving production and logistics processes.
Additionally, the top 10 most cited papers delineate the distinctions between Industry 4.0 and Industry 5.0, with the former focusing on technology-driven advancements and the latter prioritizing value orientation and sustainability. The papers explore the symbiosis between humans and machines in Industry 5.0, emphasizing the transition between industrial revolutions and the integration of humans with cyber-physical production systems.
Even more, the research provides insights into the historical evolution of industrial revolutions, discussing the emergence of Industry 4.0 technologies and their impact on production processes. The papers examine the implications of Industry 5.0 on smart working, patient treatment processes, consumer demand customization, and supply chain efficiency.
Furthermore, the articles address the societal implications of Industry 5.0, promoting human-centric innovation and sustainable development.
Lastly, the papers advocate for innovative bioenergy generation using algae to address environmental and economic challenges while aligning with sustainable development goals.
3.5. Words Analysis
The role of word analysis within the framework of this research is to provide an overview of the most widely used notions by researchers. Thus, those elements that make up or are related to the Industry 4.0 and Industry 5.0 concepts can be identified.
Thus, the most frequent words in keywords plus (Table 11) define those words most frequently used in the titles of the cited papers. It is worth noting the appearance of the word “internet” 23 times and “big data” 14 times; these are elements that are integrated in the notions that define the two industrial revolutions. Words such as “management” (22 occurrences) and “framework” (15 occurrences) can constitute related elements to the analyzed concepts because through the changes brought by the two industrial revolutions, the need to change management is evident; the multiple occurrences of “future” and “challenges” also shows the intention of the authors to emphasize and improve the challenges brought by the implementation of these notions (Industry 4.0 and 5.0) at workplaces. Other words with an increased frequency of occurrence are “design”, “systems”, and “model”, each appearing a minimum of 14 times, illustrating the authors’ interest in what industry can look like by combining robots and artificial intelligence in the manufacturing process.
As expected, the most frequent keywords are “Industry 5.0”, appearing 81 times, and “Industry 4.0”, with 72 occurrences—please consider the values in Table 12. The frequency of appearance of the other keywords drops precipitously, to only 18 appearances for “artificial intelligence” and 14 for “sustainability”, which can be considered the novelty elements that differentiate Industry 5.0 from Industry 4.0.
Words such as “digital twin”, “digital transformation”, “Internet of Things”, and “digitalization” were chosen at least seven times each by the authors to describe their research, these being notions integrated with the two industrial revolutions because both concepts advocate for the introduction of digital technologies in the production process. “Society 5.0”, which appears eight times as a keyword, is associated with the concept of Industry 5.0, which aims to introduce notions such as artificial intelligence into society through the industrial revolution.
The number of keywords selected by the author is 637. This amounts to an average of four keywords per article. The number of words in keywords plus was three-hundred and fifty-two, indicating an average of two point two nine such words per document. Figure 9 shows word clouds related to the first 50 words in keywords plus (A) and the keywords chosen by the authors (B), respectively. As expected, Industry 4.0 and Industry 5.0 are the most common keywords assigned by the authors. To these are added notions such as artificial intelligence, sustainability, Internet of Things, Society 5.0, smart manufacturing, and human–robot collaboration. As for the words in keywords plus, the same frequency of occurrence discrepancies is not found. In this case, the most used words are internet, management, systems, big data, future, performance, artificial intelligence, Industry 4.0, impact, design, framework, model, technologies, and implementation. It is noted that in the case of the keywords chosen by the author, notions that make up these concepts (Industry 4.0 and 5.0) are identified, while the additional keywords tend to present related elements, or words that are derived from the analyzed concepts.
Table 13 displays the frequency of appearance of the first 10 bigrams found in the abstracts or titles of the analyzed papers. It can be seen that the 10 bigrams identified for both cases are similar, differing only in their place in the two rankings. Thus, in both cases, the most common bigram is “supply chain” with 43 appearances in abstracts and 10 appearances in titles; the term “supply chains” is also identified with 16 appearances in the abstracts proposed by the researchers. The term “industrial revolution” appears 37 times in abstracts, having the counterpart of “industry era” in titles, where it emerges three times. The term “artificial intelligence” ranks third in the ranking of the most used bigrams in abstracts, appearing thirty-four times, and fifth in the ranking of titles, where it appears three times. Other bigrams found both in abstracts and titles are “digital twin” with twenty-two and three occurrences, respectively, and “sustainable development” with twenty-three and four appearances, respectively; “digital transformation” appears twenty-two times in abstracts and three times in titles; “future research” also appears three times in titles and fifteen times in the abstracts written by the authors of the articles.
Table 14 shows the most frequent 10 trigrams from abstracts and titles. “Artificial intelligence ai” and “fourth industrial revolution” occur 12 times in abstracts, followed by “sustainable development goals” with seven occurrences, and “industrial revolution industry” occurring six times. With five occurrences each, “cloud supply chain”, “human–robot collaboration hrc”, and “systematic literature review” are identified. “Digital product passport” appears four times, along with “energy supply chain” and “positively affects shareholders”. From these appearances, the role brought by Industry 4.0 and the transition to Industry 5.0 on sustainable development and supply chain can be noted.
Regarding the titles, the most used trigram was “future research directions”; this is a rather interesting issue, in the sense that technology seems to evolve faster than humanity is capable of putting it into practice. With two occurrences each, “gold-induced cytokine goldic”, “smart energy systems”, “smart manufacturing systems”, and “supply chain management” stand out. From here, the tendency of researchers to improve systems and the supply chain can be noted.
Among the clusters that are attributed to the search engine, we find artificial intelligence, Internet of Things, industries, fourth industrial revolution, smart manufacturing, and 6G (to which we add: 5G, collaboration, industrial IoT, and production) on the border with basic themes. Also, Industry 5.0, Industry 4.0, sustainability, digital transformation, society, and digitalization clusters can be found (including notions such as human–robot collaboration, human factors, manufacturing, and ergonomics) on the border with the motor theme. Another keyword cluster found in the basic research area is digital twin, machine learning, and bibliometric analysis, to which supply chain is added. Figure 10 also shows the niche elements; two clusters, human–robot collaboration (hrc) and safety, are identified, to which resilience, sustainable development, environmental sustainability, and human-centricity are added. In the emerging or declining category, there is only one cluster that contains a single keyword—logistics.
Viewing the changes that have occurred since the beginning of the analyzed period when only a very small number of articles were published and when Industry 5.0 was only a concept that was supposed to appear, it is not surprising that the certainty given by Industry 4.0 places it among the only two dominant keywords from the period 2020–2021. This is followed by artificial intelligence, because this is one of the leading notions of the fourth industrial revolution.
With the announcement and substantiation of the concept that encapsulates Industry 5.0, the interest of researchers was captured by studying this phenomenon, emphasizing the human factor and resilience. Digital transformation and digital twin were already present in the framework of Industry 4.0, and are now being studied more closely on human centricity. In the year 2023, the study of artificial intelligence returns strongly in the context of human–robot collaboration. The interest in digital transformation remains from the previous year. Interest in Industry 5.0 remains as well, which is now divided into several levels, including industries or 6G (Figure 11).
3.6. Mixed Analysis
The relationships between countries, publication sources, affiliations, keywords, and the main 20 authors can be seen in Figure 12 and Figure 13.
Figure 12 illustrates the connections between the countries in which researchers conduct their activities and the primary sources in which they choose to publish their papers. These countries include Hungary, Italy, the United Kingdom, China, Malaysia, the USA, Sweden, and Romania, among others. The journals in which they publish their studies include Sustainability, Sensors, IEEE-Access, and Applied Sciences, among others.
The affiliations of these authors, including University of Pannonia, Uppsala University, Kaunas University of Technology, University of Sevilla, among others, are noteworthy. In describing their research, authors frequently utilized keywords such as “Industry 5.0” and “Industry 4.0”, aligning with the primary focus of our search for these articles. However, they also employed other terms to characterize their studies, such as “circular economy”, “Society 5.0”, “resilience”, and “digital twin”, among others, as depicted in Figure 13.
4. Discussion and Limitations
Based on the investigation conducted in the paper, an analysis of the most prominent authors, sources, and countries have been provided for the field of Industry 4.0 when discussing aspects related to Industry 5.0.
From the bibliometric analysis conducted in the paper, it has been observed that in terms of journals, the top contributors are journals such as Sustainability, Applied Sciences, Sensors, and IEEE Access—all of them being known by the fast track in evaluating and publishing the scientific papers, which might boost knowledge in the novel research fields of Industry 4.0 and Industry 5.0. Considering similar papers dealing with bibliometrics in the field of digital twins and supply chains, such as the paper authored by Lam et al. [96], which is also included in the extracted dataset, it has been observed that both Applied Sciences and IEEE Access can be encountered in the top 10 preferred journals by the authors publishing scientific papers in this area. Furthermore, the journal Sustainability has been placed in the third position among the most productive journals in the bibliometric analysis conducted by Gholami et al. [97] on the field of sustainable manufacturing 4.0, while Roblek et al. [98] has listed Applied Sciences and Sustainability among the top-contributing journals in a bibliometric analysis featuring the mapping of the Society 5.0.
In terms of most contributing countries, Italy emerges as a top country based on the affiliation of the first author, followed by India, United Kingdom, China, Spain, USA, and Germany. By considering similar bibliometric papers from the field, it has been observed that these countries have been listed among the top contributors by Lam et al. [96], in a paper discussing digital twins in the supply chain, and by Gholami et al. [97], in a paper dealing with sustainable manufacturing 4.0. Even more, considering the paper of Gholami et al. [97], it has been observed that Italy is listed as the top contributor; this paper highlighting the contribution of the country in the field of Industry 4.0 even more.
Furthermore, out of the one-hundred and fifty-four analyzed articles included in the dataset, it has been observed that eight of them performed bibliometric analyses, with only two evaluating documents encompassing both concepts presented in this study.
The paper written by Grabowska et al. [80] sourced documents from the WoS database and employed a Systematic Literature Network Analysis, examining articles pertaining to Industry 4.0 and Industry 5.0 separately, and focusing on the humanization and sustainability aspects of each concept. The paper presents elements related to the differences between Industry 4.0 and Industry 5.0 pertaining to various areas such as focus, human–machine collaboration, customization and personalization, sustainability and social impact, and the role of data analytics [80]. Based on the elements highlighted by Grabowska et al. [80] in their comparative study between Industry 4.0 and Industry 5.0, it can be observed that a series of keywords found by the authors in the context of Industry 4.0 are common to the n-gram extracted in the current paper, especially underlying the focus of the Industry 4.0 on technological advancement and economic benefit, leveraging technologies such as IoT, big data analytics, and artificial intelligence.
The second article utilized databases such as Scopus and Web of Science, employing Biblioshiny for the bibliometric analysis. The authors employed the “OR” operator between search terms, indicating the inclusion of articles containing either Industry 4.0 or Industry 5.0, or other specified keywords in the titles [99].
The remaining bibliometric analyses mainly focused on either the Scopus database or the Web of Science, with most employing VosViewer [69,96,97,98,100] as the analysis method. Only one article utilized SciMAT [101]. Researchers typically searched for terms like Industry 5.0, Industry 4.0, or related notions when conducting their analyses.
In our research, only articles published in the Web of Science (WoS) database were included, containing the two defining concepts of the current industrial revolutions in their abstracts, titles, or keywords. Although the results may have varied if other databases hosting relevant articles had been considered, our focus was on accessing the best-published articles, which were predominantly found on the Web of Science platform. Moreover, the addition of related keywords could have expanded the pool of articles retrieved. However, our study aimed to elucidate the differences between the two simultaneous industrial revolutions and to highlight the transition between them. The limited timeframe considered in the analysis may also be viewed as a constraint, as the concepts explored in the study are novel and relatively unknown, necessitating further exploration to identify potential applications.
Throughout the study, the transition from published research on Industry 4.0 and artificial intelligence at the beginning of the analyzed period to the focus on Industry 5.0, resilience, and the importance of the human factor in the middle of this period was noted. Since the acceptance time of an article can vary from a few weeks to a few months, in some cases even exceeding a year, it is not surprising that in 2020–2021, the phrase “Industry 5.0” is not so significantly used compared to “Industry 4.0”, because this concept was officially introduced in 2020. In 2023, artificial intelligence returns in force, being the most common keyword for this year, followed by human–robot collaboration. What can be understood from this process is the fact that researchers have realized the important role of humans in the industrial process, bringing them to its center, but they have not forgotten how important artificial intelligence is in making processes more efficient. In the future, remains to be seen if the desire for symbiosis between humans and machines has proven to be effective.
5. Conclusions
The simultaneous emergence of two industrial revolutions in quick succession presents an unprecedented phenomenon, doubling researchers’ interest in this field due to its unique nature. Industry 4.0 signifies humanity’s advancement towards the symbiosis between humans and machines, with Industry 5.0 appearing to complement this by reinforcing the sustainable aspect of this relationship, with humans at its core. Throughout this study, we highlighted the primary sources and authors who have shown particular interest in publishing research related to this remarkable industrial transition. Notable technologies supporting this transition and areas of application for these new concepts were also identified among the most cited works. Despite the relatively short time since the emergence of Industry 5.0, a significant number of articles have been written about this transition, although there were notably fewer than those focusing solely on the two concepts individually.
In terms of differences among the two types of emerging industries, it shall be noted that Industry 5.0 distinguishes itself by the focus on human–machine collaboration, by putting an accent on prioritizing the collaboration between humans and machines, acknowledging humans’ unique capabilities such as creativity, problem-solving, and adaptability. It aims to integrate these skills with advanced technologies for enhanced outcomes. On the other hand, in Industry 4.0, machines and systems are interconnected, fostering increased automation and efficiency. However, humans typically play a limited role, and are mainly focused on monitoring and controlling automated systems.
Another difference can be observed in the customization and personalization. While Industry 4.0 facilitates mass production through high automation levels and standardization, emphasizing efficiency and cost-effectiveness via economies of scale, Industry 5.0 underscores customization and personalization, aiming to deliver products and services tailored to individual customer needs and preferences.
Furthermore, in terms of sustainability and social impact, the focus of Industry 4.0 is primarily on technological advances and economic benefits, with potential efficiency and productivity enhancements, not explicitly addressing its impact on sustainability and social aspects, while Industry 5.0 places significant emphasis on sustainability and social impact, striving to establish a more sustainable and inclusive manufacturing ecosystem—by considering environmental, social, and ethical factors, including waste reduction, promoting circular economy practices, and ensuring worker well-being.
Nevertheless, in terms of data and analytics, Industry 4.0 is highly dependent on data collection, analysis, and utilization to optimize production processes and make data-driven decisions, leveraging technologies such as IoT, big data analytics, and artificial intelligence, while Industry 5.0 continues to utilize data and analytics, but places greater emphasis on human interpretation and the application of data. Thus, Industry 5.0 recognizes the importance of human judgment, intuition, and creativity in making complex decisions that surpass the capabilities of automated systems. These aspects have been observed even in the present paper by the elements extracted through the n-gram analysis.
As humanity is only at the onset of this transition and is witnessing rapid advancements in technological and digital capabilities, it is imperative to monitor the progress made by researchers, particularly in the realm of innovation. It is evident that there are numerous areas where humans and machines can collaborate to achieve high-performance outcomes. Therefore, it is essential to continue to observe this progress in the future, considering the inclusion of other databases where such works are published to broaden our knowledge and decipher future trends in the digital era. Some areas of interest for future research include identifying ways in which these industrial revolutions can support resilience and sustainability, especially but not limited to fields such as medicine, renewable energy, etc.
Conceptualization, A.N.C.-D., C.D. and A.S.; data curation, A.N.C.-D., A.S., C.A.T. and V.M.V.; formal analysis, A.N.C.-D., C.D., A.S., C.A.T. and V.M.V.; investigation, A.N.C.-D., C.D., A.S., C.A.T. and V.M.V.; methodology, A.N.C.-D., C.D. and V.M.V.; software, A.N.C.-D. and C.D.; supervision, C.D.; validation, A.N.C.-D., C.D., A.S., C.A.T. and V.M.V.; visualization, A.N.C.-D., A.S. and C.A.T.; writing—original draft, A.N.C.-D. and C.D.; writing—review and editing, A.N.C.-D., C.D., A.S., C.A.T. and V.M.V. All authors have read and agreed to the published version of the manuscript.
Not applicable.
Not applicable.
Data is contained within the article.
The authors declare no conflicts of interest.
Footnotes
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Enlarge this image.Figure 12. Three-fields plot: countries (left), authors (middle), journals (right).
Enlarge this image.Figure 13. Three-fields plot: affiliations (left), authors (middle), keywords (right).
Data selection steps.
| Exploration Steps | Questions on Web of Science | Description | Query | Query Number | Count |
|---|---|---|---|---|---|
| 1 | Title/Abstract/Keywords | Contains the specific keyword related to Industry 5.0 | ((TI = (industry_5.0)) OR AB = (industry_5.0)) OR AK = (industry_5.0) | #1 | 668 |
| 2 | Title/Abstract/Keywords | Contains the specific keyword related to Industry 4.0 | ((TI = (industry_4.0)) OR AB = (industry_4.0)) OR AK = (industry_4.0) | #2 | 18,268 |
| 3 | #1 AND #2 | #3 | 258 | ||
| 4 | Document type | Limit to Article | (#3) AND DT = (Article) | #4 | 155 |
| 5 | Language | Limit to English | (#4) AND LA = (English) | #5 | 154 |
Main information about data.
| Indicator | Value |
|---|---|
| Timespan | 2020:2023 |
| Sources | 83 |
| Documents | 154 |
| Average years from publication | 1.7 |
| Average citations per documents | 17.35 |
| Annual Growth Rate % | 119.47 |
| References | 11,064 |
Annual scientific production evolution.
| Year | Articles |
|---|---|
| 2020 | 7 |
| 2021 | 14 |
| 2022 | 59 |
| 2023 | 74 |
Authors.
| Indicator | Value |
|---|---|
| Authors | 594 |
| Authors of single-authored documents | 9 |
| Authors of multi-authored documents | 585 |
Author collaboration.
| Indicator | Value |
|---|---|
| Single-authored documents | 9 |
| Documents per author | 0.26 |
| Authors per document | 3.86 |
| Co-authors per documents | 4.31 |
| International collaboration index | 40.26 |
Journals with three or more published articles.
| Sources | Articles | Impact Factor |
|---|---|---|
| Sustainability | 17 | 3.9 |
| Applied Sciences-Basel | 9 | 2.7 |
| Sensors | 8 | 3.9 |
| IEEE Access | 5 | 3.9 |
| International Journal of Production Research | 5 | 3.9 |
| Journal of Industrial Information Integration | 4 | 15.7 |
| Journal of Manufacturing Systems | 4 | 12.1 |
| IEEE Transactions on Industrial Informatics | 3 | 12.3 |
| Information Systems Frontiers | 3 | 5.9 |
| Journal of Industrial Integration and Management-Innovation and Entrepreneurship | 3 | 9.0 |
| Journal of the Knowledge Economy | 3 | 3.3 |
| Organizacija | 3 | ESCI |
Journals’ impact based on H-index.
| Source | H-Index |
|---|---|
| Sustainability | 7 |
| Sensors | 5 |
| Applied Sciences-Basel | 4 |
| IEEE Access | 4 |
| Information Systems Frontiers | 3 |
| Journal of Industrial Information Integration | 3 |
| Journal of Industrial Integration and Management-Innovation and Entrepreneurship | 3 |
| Journal of Manufacturing Systems | 3 |
| Journal of the Knowledge Economy | 3 |
Authors with three or more published articles.
| Author | Articles |
|---|---|
| Abonyi J | 5 |
| Kumar S | 5 |
| Carayannis EG | 4 |
| Ghobakhloo M | 4 |
| Aguayo-Gonzalez F | 3 |
| Avila-Gutierrez MJ | 3 |
| Faccio M | 3 |
| Iranmanesh M | 3 |
| Oyekan J | 3 |
| Ruppert T | 3 |
| Turner C | 3 |
Top 10 most global cited documents.
| No. | Paper (First Author, Year, Journal, Reference) | Number of Authors | Region | Total Citations (TC) | Average Citations per Year (TCY) | Normalized TC (NTC) |
|---|---|---|---|---|---|---|
| 1 | Maddikunta PKR, 2022, J Ind Inf Integr, [ | 8 | India, Korea, South Africa, China, Finland | 337 | 112.33 | 13.32 |
| 2 | Xu X, 2021, J Manuf Syst, [ | 4 | New Zealand, Germany, Sweden | 335 | 83.75 | 8.75 |
| 3 | Longo F, 2020, Appl Sci-Basel, [ | 3 | Italy | 147 | 29.4 | 2.4 |
| 4 | Choi TM, 2022, Prod Oper Manag, [ | 4 | Taiwan, USA, China | 137 | 45.67 | 5.41 |
| 5 | Bednar PM, 2020, Inform Syst Front, [ | 2 | UK, Sweden | 99 | 19.8 | 1.62 |
| 6 | Javaid M, 2020, J Ind Integr Manag-A, [ | 6 | India | 83 | 16.6 | 1.35 |
| 7 | Javaid M, 2020, J Ind Integr Manag, [ | 2 | India | 70 | 14 | 1.14 |
| 8 | Ivanov D, 2022, Transport Res E-Log, [ | 3 | Germany, France, Russia | 68 | 22.67 | 2.69 |
| 9 | Carayannis EG, 2022, J Knowl Econ, [ | 2 | USA, Poland | 67 | 22.33 | 2.65 |
| 10 | Elfar OA, 2021, Energ Convers Man-X, [ | 6 | Malaysia, Taiwan, China | 64 | 16 | 1.67 |
Brief summary of the content of top 10 most global cited documents.
| No. | Paper (First Author, Year, Journal, Reference) | Title | Purpose |
|---|---|---|---|
| 1 | Maddikunta PKR, 2022, J Ind Inf Integr, [ | Industry 5.0: A survey on enabling technologies and potential applications | Extensive presentation of the concept of Industry 5.0 including potential applications such as health, education, manufacturing, supply chain management, disaster management, and cloud manufacturing. Technologies that can help increase production and logistics are also highlighted, such as edge computing, big data analytics, digital twin, artificial intelligence, blockchain, etc., but also the way in which they improve the manufacturing process. |
| 2 | Xu X, 2021, J Manuf Syst, [ | Industry 4.0 and Industry 5.0—Inception, conception and perception | The article defines the two concepts highlighting the fact that Industry 4.0 focuses on technology, while Industry 5.0 is value-oriented. Although so far, the first four industrial revolutions have been a continuation of the previous revolution, this cannot be said about Industry 5.0, which arose from the need to complement Industry 4.0 from a need for interaction between industry and society, offering a sustainable variant, with the two revolutions co-existing. |
| 3 | Longo F, 2020, Appl Sci-Basel, [ | Value-Oriented and Ethical Technology Engineering in Industry 5.0: A Human-Centric Perspective for the Design of the Factory of the Future | The article describes Industry 5.0 as the symbiosis between humans and machines to improve the technological process; in this case, the article discusses the value-oriented character of Industry 5.0, and the transition between the two industrial revolutions. The link between humans and the cyber-physical production system, factory of the future, and the use of Operator 4.0 is described, being analyzed by means of a questionnaire with 42 questions applied to 18 enterprises of different sizes. |
| 4 | Choi TM, 2022, Prod Oper Manag, [ | Disruptive Technologies and Operations Management in the Industry 4.0 Era and Beyond | The article presents a brief history of the evolution of the industrial revolutions and the new elements introduced with their appearance. The main representative technologies in the Industry 4.0 era are presented (blockchain, artificial intelligence, digital twin, etc.), as well as a series of pros and cons of their use in the production process, as well as research opportunities. Also illustrated are a series of human–machine conflicts that may occur in Industry 4.0, but also reconciliations that appear as a result of the adaptation of Industry 5.0. |
| 5 | Bednar PM, 2020, Inform Syst Front, [ | Socio-Technical Perspectives on Smart Working: Creating Meaningful and Sustainable Systems | The research approaches the phenomenon of smart working, starting from the implications brought by Industry 4.0 through the use of robotics as a method of increasing performance. The sustainable nature of smart systems is questioned in the context of the harmony between humans and machines promoted by Industry 5.0 for the delivery of personalized goods and services. |
| 6 | Javaid M, 2020, J Ind Integr Manag-A, [ | Industry 5.0: Potential Applications in COVID-19 | The implications of Industry 5.0 in the process of treating patients are discussed, highlighting the possibilities of personalizing treatment through a detailed anamnesis. Innovative technologies of the specialized literature are discussed, which can help personalize the medical process and assist doctors during the pandemic. |
| 7 | Javaid M, 2020, J Ind Integr Manag, [ | Critical Components of Industry 5.0 Towards a Successful Adoption in the Field of Manufacturing | The research illustrates the role of Industry 5.0 in personalizing consumer demands, describing the harmonious interaction between humans and machines to streamline production, where repetitive work can be eliminated through digital technologies. The role of artificial intelligence in this process is presented along with the differences between the two current industrial revolutions. |
| 8 | Ivanov D, 2022, Transport Res E-Log, [ | Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service” | The article introduces the term supply chain cloud and how it integrates Industry 4.0-specific technologies together with digital platforms to enhance the supply chain as a service. General characteristics of the cloud supply chain are presented, as well as a generalized formal model. It also discusses the role of this technology in the inclusion of resilience and sustainability, which are required by Industry 5.0. |
| 9 | Carayannis EG, 2022, J Knowl Econ, [ | The Futures of Europe: Society 5.0 and Industry 5.0 as Driving Forces of Future Universities | The article discusses the implications of a new emerging concept, namely Society 5.0, which promotes the central role of humans in innovation, starting from the technological development generated by Industry 4.0 to improve the quality of human life in a sustainable manner. The benefits to universities and society brought by the digital transformation by incorporating the policies and practices proposed by Industry 5.0 and Society 5.0 are presented. The role of universities would be to promote a social innovation and to teach the new technologies available. |
| 10 | Elfar OA, 2021, Energ Convers Man-X, [ | Prospects of Industry 5.0 in algae: Customization of production and new advance technology for clean bioenergy generation | The article promotes the environmental and economic implications of Industry 5.0, showing an innovative way to generate bioenergy using algae. A sustainable way to facilitate the role of clean and renewable energy is presented, reducing pollution and addressing the limitations of current energy resources. Additionally, it discusses the achievement of sustainable development goals starting from the innovative technologies through which this algae industry can be promoted. |
Top 10 most frequent words in keywords plus.
| Words | Occurrences |
|---|---|
| internet | 23 |
| management | 22 |
| design | 19 |
| future | 19 |
| systems | 17 |
| challenges | 16 |
| framework | 15 |
| big data | 14 |
| model | 14 |
| Industry 4.0 | 13 |
Top 10 most frequent words in authors’ keywords.
| Words | Occurrences |
|---|---|
| Industry 5.0 | 81 |
| Industry 4.0 | 72 |
| artificial intelligence | 18 |
| sustainability | 14 |
| digital twin | 10 |
| digital transformation | 9 |
| Internet of Things | 9 |
| industries | 8 |
| Society 5.0 | 8 |
| digitalization | 7 |
Top 10 most frequent bigrams in abstracts and titles.
| Bigrams in Abstracts | Occurrences | Bigrams in Titles | Occurrences |
|---|---|---|---|
| supply chain | 43 | supply chain | 10 |
| industrial revolution | 37 | human–robot collaboration | 5 |
| artificial intelligence | 34 | manufacturing systems | 5 |
| digital twin | 24 | sustainable development | 4 |
| sustainable development | 23 | artificial intelligence | 3 |
| digital transformation | 22 | digital transformation | 3 |
| manufacturing systems | 20 | digital twin | 3 |
| supply chains | 16 | edge computing | 3 |
| future research | 15 | future research | 3 |
| industry technologies | 14 | industry era | 3 |
Top 10 most frequent trigrams in abstracts and titles.
| Trigrams in Abstracts | Occurrences | Trigrams in Titles | Occurrences |
|---|---|---|---|
| artificial intelligence ai | 12 | future research directions | 3 |
| fourth industrial revolution | 12 | gold-induced cytokine goldic | 2 |
| sustainable development goals | 7 | smart energy systems | 2 |
| industrial revolution industry | 6 | smart manufacturing systems | 2 |
| cloud supply chain | 5 | supply chain management | 2 |
| Human–robot collaboration hrc | 5 | achieving quality performance | 1 |
| systematic literature review | 5 | aerial vehicle uav | 1 |
| digital product passport | 4 | ai robotic applications | 1 |
| energy supply chain | 4 | applications techniques challenges | 1 |
| positively affects shareholder | 4 | architectures standards challenges | 1 |
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; Delcea, Camelia 1
; Stănescu, Aurelia 2
; Teodorescu, Cosmin Alexandru 1
; Vargas, Vanesa Mădălina 3
1 Department of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, 010552 Bucharest, Romania
2 Department of Management, Bucharest University of Economic Studies, 010552 Bucharest, Romania
3 Faculty of Business Administration in Foreign Languages, Bucharest University of Economic Studies, 010552 Bucharest, Romania; Institute for Economic Forecasting, Romanian Academy, 050711 Bucharest, Romania