Leadership Perspectives on the Transition from Industry 4.0 to Industry 5.0: A Broad Systematic Literature Review
The objective of this article is to present a systematic review of the literature on leadership in the transition from Industry 4.0 to Industry 5.0 and to highlight potential for future research. A bibliometric and content analysis of a wide range of scientific production was carried out in order to present the main trends and critical points of this subject. Through the evaluation of a sample group of two hundred and forty-one articles, it was possible to trace paths and understand approaches, identifying features, highlights and challenges of the Industry 5.0 leader. The literature analyzed shows that this leadership is mainly based on the knowledge, skills and attitudes necessary for performance and overcoming difficulties inherent to the demands of the industrial segment, which involve technological transformation, sustainability, resilience and human factors. This study fills a gap in the Industry 5.0 leadership literature by systematically exploring human-machine collaboration and sustainability-oriented leadership traits. Additionally, in addition to discussing how to address the demands inherent to Industry 5.0, this paper highlights that the consolidation of the transition from I4.0 to I5.0 is indeed in progress. In this scenario, this paper provides reflections for organizations that are experiencing this transition process.
Authors
- Cristiano Hora Fontes (ORCID: https://orcid.org/0000-0001-8020-6815)
- Sandro Breval Santiago (ORCID: https://orcid.org/0000-0002-0184-9845)
- Cristina Santos (ORCID: https://orcid.org/0000-0002-9854-5097)
- Jorge Laureano Moya Rodríguez (ORCID: https://orcid.org/0000-0003-0541-0191)
Institutions
- Universidade Federal da Bahia (BR)
- The Federal Polytechnic, Ado-Ekiti (NG)
- Universidade Federal do Amazonas (BR)
Publication Details
- Journal
- Journal of Scientometric Research
- Published
- 2025-09-01
- DOI
- https://doi.org/10.5530/jscires.20251691
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Conselho Nacional de Desenvolvimento Científico e Tecnológico