Logistics 4.0 and emerging technologies: A scientometric perspective on innovation in supply chains
Gabriel Antonio Moyano Londoño et al.
Abstract
Logistics 4.0 and emerging technologies have transformed supply chain management, fostering innovation, operational efficiency, and sustainability. This study conducts a scientometric analysis of 698 publications from 2005 to 2023, indexed in Scopus and Web of Science (WOS), to explore the evolution of Industry 4.0 applications in supply chains. The research follows a two-stage approach using PRISMA and Tree of Science (TOS) methodologies. First, scientific mapping was performed through RStudio Cloud and Bibliometrix. Then, co-citation network analysis in Gephi enabled the construction of the Tree of Science and the identification of three core research clusters. The first cluster links Industry 4.0 to circular economy strategies, emphasizing the integration of technologies such as blockchain and additive manufacturing to enable sustainable and regenerative supply networks. The second cluster focuses on the adoption of specific digital technologies, such as IoT and blockchain, within supply chain operations, highlighting traceability, transparency, and governance. The third cluster centers on the evolution of smart supply chains and digital maturity, integrating strategic frameworks and extending the scope of research to diverse sectors, including SMEs, healthcare, and education. This study contributes to existing knowledge by mapping the conceptual and methodological evolution of Logistics 4.0 research, revealing how digitalization and sustainability have become central to supply chain innovation. Emerging research lines include the development of integrative frameworks for circularity and digitalization, empirical validation of technology adoption models, and expansion of Industry 4.0 applications beyond manufacturing. Future work is encouraged to address regulatory challenges, sectoral adaptations, and socio-environmental impacts, while exploring concepts such as Society 5.0 and smart working.
5 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.41 × 0.4 = 0.16 |
| M · momentum | 0.63 × 0.15 = 0.09 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.