Sociotechnical perspectives on work in the context of Industry 4.0: a bibliometric analysisAbstract
Abstract Gaps remain in the literature regarding the integration between work organization, sociotechnical systems, and the technological solutions of Industry 4.0. From this perspective, this article aimed to conduct a bibliometric analysis of the sociotechnical approach to work in the context of Industry 4.0. To this end, an exploratory and descriptive study was developed, using a quantitative approach and secondary data from Scopus. Findings indicate that the most contemporary view of sociotechnical systems is indeed connected to Industry 4.0 and is on the rise, as evidenced by the increasing number of publications on this topic. The bibliometric indicators identified 299 distinct articles from 216 sources, with five publications surpassing 200 citations. Scientific productivity was higher in the United Kingdom, Australia, Canada, and Denmark, indicating a European predominance in the publication landscape. The results suggest both the diffusion and the contemporaneity of the research theme, confirming Lotka's Law but not Bradford's Law. Collaboration networks among researchers were identified, along with a dense keyword network.
Keywords:
Industry 4.0; Work; Sociotechnical systems; Bibliometrics
Resumo
Resumo Existem lacunas na literatura sobre a integração entre a organização do trabalho, sistemas sociotécnicos e as soluções tecnológicas da Indústria 4.0. Sob essa perspectiva, este artigo teve como objetivo realizar uma análise bibliométrica da abordagem sociotécnica no trabalho diante da Indústria 4.0. Para tanto, foi desenvolvido um estudo exploratório e descritivo, com abordagem quantitativa e baseado em dados secundários da Scopus. Constatou-se que a abordagem mais contemporânea dos sistemas sociotécnicos está, de fato, conectada à Indústria 4.0 e em ascensão, com aumento das publicações nessa temática. Os indicadores bibliométricos apontaram 299 artigos diferentes oriundos de 216 fontes, com cinco publicações alcançando mais de 200 citações. Observou-se maior produtividade científica no Reino Unido, na Austrália, no Canadá e na Dinamarca, indicando uma preponderância europeia nas publicações. Os resultados sugerem a difusão e a contemporaneidade do tema de pesquisa, sendo que a lei de Lotka foi confirmada, enquanto a de Bradford não foi validada, tendo sido identificadas redes de colaboração entre os pesquisadores, bem como uma rede densa de palavras.
Palavras-chave:
Indústria 4.0; Trabalho; Sistemas sociotécnicos; Bibliometria
1 Introduction
Industry 4.0 is characterized by the extensive use of digital technologies, including big data, cloud computing, and the Internet of Things (IoT). Dalenogare et al. (2018) indicate that these technologies are responsible for supporting others based on the dimensions of smart working, smart supply chains, smart products and services, and smart manufacturing). These technological applications in industry 4.0 include robotics, 3D printing, virtual reality, etc., which constitute the primary focus of technological application in Industry 4.0.
One would expect, according to authors such as Weichhart et al. (2019), that the technological environment of Industry 4.0 would create a setting with high automation and reduced reliance on operational workers, relegating operational work on the shop floor to cognitive activities only. However, what has in fact been observed is a conflict between jobs and the workforce, as evidenced by Schuh et al. (2020).
Fantini et al. (2020) point to three changes considered drastic, caused by technologies in industry, encompassing the decomposition of the vertical layers of the automation hierarchy; the disappearance of the horizontal boundaries of production environments; and the absence of distance between design, manufacturing, and use (a shift in the product life cycle). These changes foster scenarios with low predictability, including future impacts on work.
There are still gaps in the literature regarding how the integration between work organization and technological solutions will evolve in industry, which may evolve along two antagonistic strands: technocentric scenarios, in which cyber-physical systems will dominate and human work will be subordinated to technology, or anthropocentric perspectives, which posit that workers will dominate and make decisions based on cyber-physical systems (Dworschak & Zaiser, 2014; Fantini et al., 2020).
Authors such as Geels (2004) and Walker et al. (2008) define sociotechnical systems (or socio-technical) as a combination of the terms social (linked to people and society) and technical (related to machines and technologies), encompassing actors (natural persons or legal entities), social and technical norms, materials, and knowledge. Some synonyms, such as complex sociotechnical systems (Woo & Vicente, 2003) or sociotechnical work systems (Waterson et al., 2002), can also be found in the literature, which could lead to imprecision in the concept.
This article defines sociotechnical systems based on general system theory (von Bertalanffy, 1950) and Walker et al. (2008), treating them as an optimization applied to organizational design to address better new technologies, dynamism, environmental complexity, and competition.
The objective of this article is to investigate the knowledge structure of the sociotechnical approach to work in the context of Industry 4.0. This will be achieved by analyzing the citation landscape, publication growth trends, scientific indicators, publication characteristics, and leading journals, as well as conducting science mapping of the topic, using data obtained from the Scopus database.
2 Theoretical background
Industry 4.0 has brought technological advances that are shaping markets, consumption, and industry through the introduction of digital technologies such as Artificial Intelligence (AI), additive manufacturing, high-performance computing, robotics, and cybersecurity, among others (Aires et al., 2017). Industry 4.0 is supported by several pillars, such as cyber-physical systems (CPS), the Internet of Things (IoT), the Internet of Services (IoS), and the smart factory. It is linked to digital transformation and its incorporation into industrial processes, to improve utilization, increase yields, and maximize organizational profitability (Hermann et al., 2016).
Frank et al. (2019) report that the digital technologies that support Industry 4.0 can be divided into at least two groups: front-end and base technologies. The first group is related both to the transition of manufacturing activities toward emerging technologies – what the authors term Smart Manufacturing – and to the way products are offered – Smart Products – as well as to technologies that promote operational efficiency within the scope of smart supply chains and smart working. Among the technologies directly connected to manufacturing activities, examples include virtualization, automation, and traceability, whereas Smart Products are associated with features such as connectivity, monitoring, and autonomy. Stock et al. (2018) conceptualize smart working as a set of technologies that support tasks performed by operators, such as collaborative robots and augmented and virtual reality for remote maintenance, operations, and production monitoring. According to Frank et al. (2019), the second group of technologies supporting Industry 4.0, called the base technologies, provides connectivity and intelligence to the front end, generating an integrated manufacturing system and differentiating it from previous industrial stages, encompassing cloud computing, big data, and analytics, among others. As presented by Silva et al. (2022), these technologies have led to a transformation in the traditional view of human resource management. This was called Human Resources Management 4.0 (HRM 4.0 or Smart HR 4.0), a more agile management approach that ensures worker wellbeing and channels human potential toward new tasks.
On the other hand, according to Dornelles et al. (2022), there is a latent concern regarding smart working, since questions about the future of work still involve unknowns that require further clarification. This raises a dichotomy because it remains uncertain how digital technologies may affect workers within the scope of digital transformation: whether jobs are affected by technologies or technologies enhance workers’ capabilities. This question falls within the scope of Industry 4.0 from a human-centered perspective, as Cagliano et al. (2019) note a growing body of research on the contributions that Industry 4.0 technologies make to work, given their complexity.
Within this scope, smart working becomes increasingly important as companies seek greater flexibility in their production systems. Marcon et al. (2021) highlight that workers are the most resilient and adaptable actors in the sociotechnical production system. Other authors, such as Romero et al. (2016), refer to these workers as Operators 4.0, centered on work capability, in which smart working takes on a broader scope, particularly in how tasks are performed. Thus, the understanding is that the Operator 4.0 uses advanced technologies to enhance cognitive, sensory, and physical capabilities in the integration between the cyber-physical and human systems for better adaptation to the new work environment created by Industry 4.0.
For other authors, such as Riel et al. (2017) and Bednar & Welch (2020), there are challenges inherent to adopting Industry 4.0 technologies, including cybersecurity and privacy. That is, approaches more attuned to risk and safety issues go beyond purely technical matters to examine, from another perspective, the relationship between people and the systems with which they interact. Bednar & Welch (2020) classify the technologies as disruptive from both personal and professional standpoints and argue that the term Industry 4.0 is misleading, including because it encompasses technologies that have existed since the first half of the twentieth century.
In this context, the so-called Industry 5.0 emerges, characterized by mass personalization and the advent of interaction ecosystems among consumers and suppliers for product use, provision, and maintenance. According to Bednar & Welch (2020), the smart factories of Industry 4.0 have advanced toward synergistic relationships between people and systems, the driving force of Industry 5.0. The aim is products with higher added value, combining cognitive computing with human intelligence.
Considering the integration of people and technologies, a sociotechnical phenomenon emerges, characterized by the combination of technical and social elements to achieve desired outcomes. Among the various approaches to sociotechnical systems, more contemporary ones, such as Mohr & van Amelsvoort (2016), focus on how ecosystems, networks, organizations, and jobs function internally with a view to value creation, while leaving aside the human being as a real person.
Therefore, smart working presupposes the need for studies and for the evolution of the elements of sociotechnical systems, from a perspective focused on improving the work experience and on an employee-oriented work environment. According to Bednar & Welch (2020), the effort to bring about change in an organization adapted to smart working follows a sociotechnical perspective.
The literature indicates a greater prevalence of empirical approaches and systematic reviews on the theme of the present study (Table 1). It suggests a gap in bibliometric studies under the sociotechnical approach to work in Industry 4.0. One may infer the particular importance of adopting a holistic, exploratory, and numerically driven perspective in order to provide an overview of a contemporary topic and, considering Hérubel (1999), bibliometric analysis seeks to examine specific phenomena – such as the evolution of publications in the field – thereby enabling science mapping of the research scope that guides new exploratory studies.
3 Methodology
The bibliometric analysis was conducted through a systematic search to assess global scholarly output on Industry 4.0, work, and sociotechnical systems. To this end, a set of statistical tools was employed to evaluate the literature with the following objectives quantitatively:
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to perform a bibliometric performance analysis: adopting a temporal perspective in bibliometric indicators such as the h-index, citation density, citations per publication, impact factor, among others;
b. to obtain science mapping: carrying out analyses of authorship patterns, co-authorship, bibliographic coupling, thematic mapping, among others.
Table 2 presents the research questions. In line with the aims, network analyses assessed the number of publications, citations, and co-citations.
To address the research questions, the search encompassed the analysis of works sourced from the Scopus database, in line with other studies in the literature (Dachry et al., 2024; Minglana et al., 2021; Ahmi et al., 2019). Scopus is a multidisciplinary database maintained by Elsevier and, according to several authors (Singh et al., 2021; Gavel & Iselid, 2008; Mongeon & Paul-Hus, 2016; Martín-Martín et al., 2018), offers broader journal coverage than the Web of Science database and was therefore adopted as the search scope in the present article.
The initial search for the terms “socio-technical” or “sociotechnical” and “Industry 4.0” and “work*”, all in the default search field (Title-, Abstract-, Keywords) within Scopus, returned 124 records. However, such a configuration could limit the article's scope, given the possibility of synonyms for the expressions used. A term search across other articles was therefore carried out to expand the query, treating “Industry 4.0” as the alternative to “digital technologies” and “Industrie 4.0”, as employed by authors such as Enrique et al. (2021) and Grybauskas et al. (2022). For the term “work”, the search was broadened to include the alternative term “labor”, as in Enrique et al. (2021), yielding a total of 570 records.
It was necessary to filter by publication date, since the concept of Industry 4.0 dates back to 2011 and has become widespread mainly over the last decade (2015-2025). Screening the results for the 2011-2025 interval yielded 548 items, which were then filtered by document type (articles and review articles; 283 articles and 16 reviews), resulting in a final sample of 299 records, as detailed in Table 3.
The data were exported from Scopus in BibTeX format and analyzed using the Bibliometrix package in RStudio 2023.12.1+402. The tool enables the study of three metric levels (authors, sources, and documents) and three knowledge structures (conceptual, intellectual, and social). Bibliometric analyses were carried out for the most productive authors, the affiliations with the most significant number of articles, the most cited references, the leading journals, the keyword network, the thematic map, and the collaboration map. According to Herzog et al. (2019), the thematic map enhances understanding of thematic meanings by conceptualizing patterns and their relationships within the data through the thematic clustering of keywords and key phrases in Bibliometrix.
For the author analysis, the validity of Lotka’s Law was examined, which establishes that the number y of authors, each credited with a number x of articles, is inversely proportional to the number of articles (Pao, 1985). Bookstein (1977) notes that, in practice, this implies that for every one hundred authors publishing one article, twenty-five publish two articles, ten publish three, and so on – that is, few authors are publishing many articles, concentrating the knowledge produced in that field. For the analysis of the most frequent publishers, Bradford’s Law was considered. This law states that only a few journals publish a large portion of the literature, meaning that publications are not widely dispersed across a broad spectrum of sources (Tsay & Yang, 2005). This could indicate a reference publisher or a preferred outlet for publication.
4 Results and discussion
As an initial result, Figure 1 presents the distribution of articles in the database by year, filtered to records between 2011 and 2025. An annual growth of approximately 23% is observed in publications across 216 distinct sources, encompassing a network of 940 authors, with approximately 29% international co-authorship.
The first article identified in 2011 was published in The Information Society by Kristin R. Eschenfelder, Anuj C. Desai, and Greg Downey, entitled “The Pre-Internet Downloading Controversy: The Evolution of Use Rights for Digital Intellectual and Cultural Works” (Eschenfelder et al., 2011) The authors trace the historical evolution of the possibility of downloading linked to databases, considering issues such as usage rights for different intellectual and cultural goods. In the article, questions about work and sociotechnical systems are evident, as the authors associate the sociotechnical construct with technological change, business model shifts, and social transformations – specifically, in this case, the use of databases. However, the Industry 4.0 context remains nascent in the article, although it constitutes an important instance of digital technologies that underpin Industry 4.0, as noted earlier.
The most recent article identified was published in Digital Geography and Society by Iván Ojeda-Pereira (2025), entitled “Securitizing the technoplatformized City: How delivery workers construct urban safe spaces in Chile’s gig economy.” In this article, the author examines the impact of digital delivery platforms on workers and urban space, situating the discussion within emerging debates concerning sociotechnical and territorial issues in platform-based work.
Focusing specifically on the authorship scope within the filtered sample of 299 articles, we identified a total of 940 authors. The principal contributors are shown in Figure 2 (considering the number of fractionalized articles), with their respective countries, affiliations, and h-index values listed in Table 4. We also observed that 899 authors (95.6%) had only one publication among the documents analyzed. Also, 37 authors (4%) had two publications, while only 4 authors (0.4%) had three publications. In line with Lotka’s Law (authors' scientific productivity), this indicates that scientific production in this theme is centralized, with many authors publishing a single article and few publishing two or more.
Among the primary affiliations—based on the authors with the most publications presented in Table 4 – The University of Edinburgh, Curtin University, and the University of Oxford stand out; these institutions also rank among those with the highest number of publications, as shown in Figure 3. With respect to the h-index, which quantitatively evaluates scientific output based on productivity and the impact of publications, two Italian authors (Patriarca, R.; Constantino, F.), three British authors (Williams, R.; Cresswell, K.; Greenhalgh, T.), and one Australian author (Parker, S. K.) exhibited indices above thirty, indicating the researchers with the most significant impact on the topic under study.
As shown in Figure 3, four institutions are British, four are Australian, one is Canadian, and one is Danish. Therefore, among the ten institutions with the most publications on the chosen topic, five are located in Europe, and they also lead in citation counts. No American or Chinese universities were observed among the top ten, despite these countries’ usual leadership in academic publishing. One possible explanation for this finding is the selection of search terms; a suggestion for future studies is to examine publications originating specifically from the United States and China.
Figure 4 presents the five most-cited articles, all with more than 100 citations and published in different outlets by different authors between 2013 and 2022. Notably, the most-cited article (427 citations) is also from 2022, which suggests that the higher citation count cannot be attributed solely to time since publication, as evidenced by the paper’s elevated Field-Weighted Citation Impact (FWCI) (44.37).
The most-cited article (427 citations) is Parker & Grote (2022), Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World, published in Applied Psychology. The authors analyze work design in light of the effects of digital technologies, noting both positive and negative aspects. They emphasize that implementing technologies requires deliberate choices about work design, human-centered design, organizational intervention strategies, and employee and other stakeholder training. The application of the sociotechnical systems principle of joint optimization is evident in the choice of work design, and the paper proposes a well defined research agenda with new research questions and practical implications.
The second most-cited article (377 citations) is Bentley et al. (2016), The role of organisational support in teleworker wellbeing: A socio-technical systems approach, published in Applied Ergonomics. It focuses on telework – a work modality widely adopted during the COVID-19 pandemic. Even before the pandemic, in 2016, the authors reported the growth of this form of work and, based on a sociotechnical systems approach, examined organizational support for workers’ wellbeing, in alignment with the journal’s ergonomics scope.
The third-most-cited article (290 citations) is Bednar & Welch (2020), “Socio-technical perspectives on smart working: creating meaningful and sustainable systems,” published in Information Systems Frontiers. The authors discuss applications of digital technologies – such as artificial intelligence and virtual reality – in integrated manufacturing systems, leading to smart working, driven by Industry 4.0 and smart factories, and pointing toward Industry 5.0. As a distinguishing feature of Industry 5.0, they highlight the need for harmony between social and technological systems to enable mass personalization of products. In this context, sociotechnical systems, according to Bednar & Welch (2020), emerge as a means to support the use of intelligent technologies in organizations. To that end, they present a contemporary, open sociotechnical approach in which the work ecology is unique, and managers should be seen as “cultivators,” not “architects.”
The fourth most-cited article is Meyers et al. (2013) – the oldest among the most cited – with 277 citations: Digital literacy and informal learning environments: An introduction, published in Learning, Media and Technology. The authors focus on learning and communication, with a sociotechnical scope that includes the use of technologies and knowledge of the norms and appropriate practices for their use. The fifth article is Lewis & Westlund (2014), published in Digital Journalism, with 272 citations: Actors, actants, audiences, and activities in cross-media news work: A matrix and a research agenda, in which the authors argue for a sociotechnical emphasis in news production, addressing human-technology interaction and the influence of technology on the news business.
Therefore, among the five most-cited articles, all address the relationship among work, technology, and sociotechnical systems. However, in the context of Industry 4.0 emphasis, Bednar & Welch (2020) is the article that most closely aligns with the aim of the present study (to analyze the sociotechnical approach to work in the face of Industry 4.0). This finding indicates a substantial intersection among different research areas for the queried terms, which can be further explored in future studies centered on content analysis.
Figure 5 presents the 10 leading sources of publications, ranked by the number of articles available in each. The only journal that appears in both the most-cited and the most-published lists is Applied Ergonomics. Regarding Bradford’s Law, the bibliometric data do not conform to it: given the number of articles per journal and the topic's recentness and ongoing shaping in the literature, it was not possible to identify well defined core and dispersion zones.
The Technological Forecasting and Social Change is the journal with more publications (9) with a 2024 JCR impact factor of 13.3 and top percentiles in management and business and applied psychology; it also has the highest JCR impact factor among the journals listed. The diversity of research areas represented by the journals – already corroborated by Bradford’s Law analysis – indicates the field's interdisciplinarity.
Figure 6 presents the network of the most-cited keywords in the articles included in the study. The heterogeneity of associated terms suggests a broad thematic scope, with diverse applications and contexts for research.
The central word, with the strongest prominence, is Industry 4.0, which represents a node. Nodes are the terms that appear in abstracts, keywords, and titles; the lines are the connections; and node sizes indicate relevance within the topic under study. Three subgroups emerge:
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The first (blue) is represented by Industry 4.0. It connects to the principal terms smart working, Industry 5.0, sociotechnical systems, ergonomics, and manufacturing—a cluster in which the application to production systems is evident;
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The second (green) has digitalization as its most prominent node, directly connected to the Industry 4.0 node and to the principal terms cyber-physical and digital transformation, characterizing a grouping driven by digital technologies;
c. The third (red) is also directly connected to the Industry 4.0 node, with artificial intelligence as the connecting node, and the principal terms, digital health and healthcare, are more closely associated with human- and health-related issues.
The privacy and ethics group has not yet shown connections to the other clusters, representing a prospect for future studies that relate ethical and privacy issues to work, sociotechnical systems, and Industry 4.0.
It is important to note that Industry 4.0 serves as the linking hub among most clusters – as evident in the thematic map (Figure 7) – and is one of the motor themes. The thematic map aims to perform science mapping using a set of keywords (themes), which are assessed for density and centrality. According to Callon et al. (1991), the thematic map is organized by centrality and density: centrality measures the intensity of ties among different clusters, whereas density characterizes the strength of cohesion among the words that compose each cluster, such that the stronger this cohesion, the greater the internal consistency and integration of the corresponding research problems.
Cobo et al. (2011) indicate that themes in the upper-right quadrant (motor themes) are well developed and important for structuring the field; those in the lower-right quadrant (basic themes) are important to the field but not well developed; those in the upper-left quadrant (highly developed/isolated or specialized themes) are specialized and peripheral; and those in the lower-left quadrant (emerging or declining themes) are also peripheral and underdeveloped.
The theme Industry 4.0 forms a cluster with digitalization and digital transformation; it is a motor theme with strong centrality and high density, linked to concepts that can be applied to neighboring themes. In turn, sociotechnical systems form a cluster in the lower-left quadrant, with low density and low centrality – underdeveloped and peripheral in the field – making it a theme with scope for further exploration (emerging). The cluster, composed mainly of technologies – such as digital technologies and infrastructure – lies in the upper-left quadrant, having specialized, peripheral importance for the field. The cluster, composed primarily of artificial intelligence and digital health, is located in the lower-right quadrant, which groups more transversal and general themes.
Figure 8 presents the country collaboration map, highlighting countries with the strongest cooperation and connections.
Countries with high levels of international collaboration include the United Kingdom and its partners: Australia, Italy, the Netherlands, and Sweden. These countries also host institutions with highly cited articles in the sample. Although it is not among the top-cited articles or the institutions with the most publications, the United States collaborates with Canada, the United Kingdom, Germany, Denmark, and Italy. Italy also ranks among the countries with the strongest collaboration, including collaboration with France. For future studies, it would be valuable to deepen the analysis of the US role in this research theme, given its prominence in international collaborations.
5 Conclusions
Considering the joint approach to sociotechnical systems, work, and Industry 4.0, the field shows a growth trend: publications are recent, the sociotechnical theme is emerging and related to leadership issues, and the Industry 4.0 cluster is a motor theme, as evidenced in the thematic map.
With respect to sample size, 299 articles were analyzed across more than 200 journals and nearly 1,000 authors, demonstrating the dispersion of the theme across sources in different areas – such as ergonomics, manufacturing, information systems, psychology, and others – and indicating that the topic under study is cross-cutting.
Among countries with the highest citation counts, the United Kingdom, Australia, Canada, and Denmark stand out; they also appear among those with the most international collaboration. The United States and China did not appear among the countries with the most-cited articles, even though they are typically leaders in academic publications and citations – a gap to be examined in future studies, especially given the United States' presence among the countries with the highest levels of international collaboration.
Regarding Lotka’s Law, the author's scientific productivity in the studied theme is centralized; however, Bradford’s Law was not confirmed based on the distribution of articles across journals, with no clear core or dispersion zones observed. These results indicate that, although authorship in the theme is centralized, publication is dispersed across sources from several areas, corroborating the earlier finding on the topic's transversality.
As for article authorship, contributions are distributed worldwide, but there is an evident concentration in Europe, with international collaboration prevalent (approximately 29%). This is a research topic with a broad scope, more closely related to digital technologies, digital transformation, and the future of work.
There remains a gap in the literature for further investigations on the theme. Among the main findings of the study, there is an opportunity to conduct a content analysis of the articles comprising the sample, to expand the search to other scholarly databases – such as Web of Science – and to examine specifically the participation of China and the United States, as countries that lead academic publications, within the field under study.
As a suggestion for another future line of inquiry, primary data collection could be carried out through field research to deepen the understanding of how work organization design is being directed in firms implementing Industry 4.0, and to identify the influences of sociotechnical systems in this relationship.
Acknowledgments
The authors would like to acknowledge Fundação Carlos Alberto Vanzolini (FCAV) for its support in the revision of the manuscript.
Statement on Data Availability
All content underlying the manuscript text is fully available within the manuscript.
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Financial support:
This work received no specific funding from public, private, or not-for-profit sectors.
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How to cite:
Munhoz, I. P., Marx, R., & Zancul, E. (2026). Sociotechnical perspectives on work in the context of Industry 4.0: a bibliometric analysis. Gestão & Produção, 33, e9924. https://doi.org/10.1590/1806-9649-2025v33e9924
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Editor-in-Chief
Pedro Munari
