Mapping the evolution of production chains in the era of industry 4.0: A scientometric perspective

Assiya Zahid; Patrice Leclaire; Lamia Hammadi; Roberta Costa Affonso; Abdessamad El Ballouti

doi:10.31893/multirev.2025152

Keywords:

industry 4.0

emerging technologies

production management

bibliometric analysis

Abstract

This study presents a comprehensive bibliometric analysis of the academic literature focused on Industry 4.0 technologies in production chains, spanning from 2011 to 2024. The primary objective is to identify key research trends, influential authors, prominent publications, and emerging themes that have shaped the field over this period. To achieve this, a rigorous bibliometric methodology was employed, starting with the formulation of research questions and the development of inclusion and exclusion criteria. The Scopus database was utilized to conduct a systematic search of relevant publications, targeting leading journals and key topics within Industry 4.0 and production chains. A total of 1085 records were initially retrieved, of which 558 were selected after thorough screening for further analysis. The selected records were analyzed using RStudio and VOSviewer to visualize key metrics such as publication trends, citation analysis, and collaboration networks among researchers and institutions. The findings reveal a marked increase in research output related to Industry 4.0 technologies, particularly in areas like the integration of IoT, AI, and big data analytics into production processes. These technologies have been shown to significantly enhance operational efficiency, product quality, and value chain management. Additionally, the analysis identifies leading countries, institutions, and authors that have made substantial contributions to this field, as well as the most cited publications that have influenced current research directions.

This study provides an in-depth overview of the academic landscape surrounding Industry 4.0 in production chains, offering valuable insights for researchers, practitioners, and policymakers. By mapping out research trends and highlighting key contributions, this analysis not only enhances understanding of Industry 4.0's impact on production systems but also helps guide future research and practical implementation in industrial settings.
References
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to cite

Zahid, A., Leclaire, P., Hammadi, L., Affonso, R. C., & El Ballouti, A. (2024). Mapping the evolution of production chains in the era of industry 4.0: A scientometric perspective . Multidisciplinary Reviews, 8(5), 2025152. https://doi.org/10.31893/multirev.2025152

[1] Abdullah, F.M., Saleh, M., Al-Ahmari, A.M., Anwar, S., 2022. The Impact of Industry 4.0 Technologies on Manufacturing Strategies: Proposition of Technology-Integrated Selection. IEEE Access 10, 21574–21583. https://doi.org/10.1109/ACCESS.2022.3151898

[2] Akrami, N.E., Hanine, M., Flores, E.S., Aray, D.G., Ashraf, I., 2023. Unleashing the Potential of Blockchain and Machine Learning: Insights and Emerging Trends From Bibliometric Analysis. IEEE Access 11, 78879–78903. https://doi.org/10.1109/ACCESS.2023.3298371

[3] Bayonne, E., Marin-Garcia, J.A., Alfalla-Luque, R., 2020. Partial least squares (PLS) in Operations Management research: Insights from a systematic literature review. JIEM 13, 565. https://doi.org/10.3926/jiem.3416

[4] Blanchet, M., 2016. Industrie 4.0 Nouvelle donne industrielle, nouveau modèle économique. Outre-Terre N° 46, 62. https://doi.org/10.3917/oute1.046.0062

[5] Chen, Y., Yang, S., Zhang, Z., Shen, H., 2024. How does digital enablement affect product customization? The roles of innovation capability and network embeddedness. Technological Forecasting and Social Change 201, 123272. https://doi.org/10.1016/j.techfore.2024.123272

[6] Eck, N.J. van, Waltman, L., 2018. VOSviewer Manual.

[7] Fogaça, D., Grijalvo, M., Sacomano Neto, M., 2022. An institutional perspective in the industry 4.0 scenario: A systematic literature review. JIEM 15, 309. https://doi.org/10.3926/jiem.3724

[8] ForouzeshNejad, A.A., 2023. Leagile and sustainable supplier selection problem in the Industry 4.0 era: a case study of the medical devices using hybrid multi-criteria decision making tool. Environ. Sci. Pollut. Res. 30, 13418–13437. https://doi.org/10.1007/s11356-022-22916-x

[9] Frederiksen, R.D., Bocewicz, G., Radzki, G., Banaszak, Z., Nielsen, P., 2024. Cost-Effectiveness of Predictive Maintenance for Offshore Wind Farms: A Case Study. Energies 17, 3147. https://doi.org/10.3390/en17133147

[10] Hirsch, J.E., 2005. An index to quantify an individual’s scientific research output. Proc. Natl. Acad. Sci. U.S.A. 102, 16569–16572. https://doi.org/10.1073/pnas.0507655102

[11] Huang, K., Wang, K., Lee, P.K.C., Yeung, A.C.L., 2023. The impact of industry 4.0 on supply chain capability and supply chain resilience: A dynamic resource-based view. International Journal of Production Economics 262, 108913. https://doi.org/10.1016/j.ijpe.2023.108913

[12] Kagermann, H., Wahlster, W., 2022. Ten Years of Industrie 4.0. Sci 4, 26. https://doi.org/10.3390/sci4030026

[13] Moher, D., Liberati, A., Tetzlaff, J., Altman, D.G., The PRISMA Group, 2009. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med 6, e1000097. https://doi.org/10.1371/journal.pmed.1000097

[14] Neugebauer, R., Hippmann, S., Leis, M., Landherr, M., 2016. Industrie 4.0 - From the Perspective of Applied Research. Procedia CIRP 57, 2–7. https://doi.org/10.1016/j.procir.2016.11.002

[15] Paprocki, W., 2017. How Transport and Logistics Operators Can Implement the Solutions of “Industry 4.0,” in: Suchanek, M. (Ed.), Sustainable Transport Development, Innovation and Technology, Springer Proceedings in Business and Economics. Springer International Publishing, Cham, pp. 185–196. https://doi.org/10.1007/978-3-319-51427-7_16

[16] Polenghi, A., Cattaneo, L., Macchi, M., 2023. A framework for fault detection and diagnostics of articulated collaborative robots based on hybrid series modelling of Artificial Intelligence algorithms. J Intell Manuf. https://doi.org/10.1007/s10845-023-02076-6

[17] Popkova, E.G., Ragulina, Y.V., Bogoviz, A.V. (Eds.), 2019. Industry 4.0: Industrial Revolution of the 21st Century, Studies in Systems, Decision and Control. Springer International Publishing, Cham. https://doi.org/10.1007/978-3-319-94310-7

[18] Sanders, A., Elangeswaran, C., Wulfsberg, J., 2016. Industry 4.0 implies lean manufacturing: Research activities in industry 4.0 function as enablers for lean manufacturing. JIEM 9, 811. https://doi.org/10.3926/jiem.1940

[19] Tranfield, D., Denyer, D., Smart, P., 2003. Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review. Br J Management 14, 207–222. https://doi.org/10.1111/1467-8551.00375

[20] Wahyuni, H., Vanany, I., Ciptomulyono, U., 2019. Food safety and halal food in the supply chain: Review and bibliometric analysis. JIEM 12, 373. https://doi.org/10.3926/jiem.2803

[21] Yang, H., Sun, Z., Jiang, G., Zhao, F., Lu, X., Mei, X., 2021. Cloud-Manufacturing-Based Condition Monitoring Platform with 5G and Standard Information Model. IEEE Internet Things J. 8, 6940–6948. https://doi.org/10.1109/JIOT.2020.3036870

[22] Zahid, A, Leclaire, P., Affonso, R.C., Zahid, A., Hammadi, L., Elballouti, A., 2024. Towards Smart Scheduling in the Era of Industry 4.0 for Sustainable Manufacturing, in: 2024 IEEE 15th International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA). Presented at the 2024 IEEE 15th International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA), IEEE, Sousse, Tunisia, pp. 1–7. https://doi.org/10.1109/LOGISTIQUA61063.2024.10571537

[23] Zhao, D., Strotmann, A., 2015. Analysis and Visualization of Citation Networks, Synthesis Lectures on Information Concepts, Retrieval, and Services. Springer International Publishing, Cham. https://doi.org/10.1007/978-3-031-02291-3

[24] Zheng, P., Lin, T.-J., Chen, C.-H., Xu, X., 2018. A systematic design approach for service innovation of smart product-service systems. J. Clean. Prod. 201, 657–667. https://doi.org/10.1016/j.jclepro.2018.08.101

Abstract

References

How to cite