Modelo para implementação da transformação digital na gestão de recursos humanos em indústrias manufatureiras

Abstract

Digital Transformation (DT) has driven significant changes in industrial organizations, impacting processes, business models, and the workforce through the pursuit of more connected, flexible, and data-driven environments. In this context, the understanding of digital transformation has expanded when examining the manufacturing sector, with Industry 4.0 focusing on process optimization and Industry 5.0 emphasizing humancentricity by promoting intelligent, connected, and autonomous systems while evolving toward human-centeredness, sustainability, and organizational resilience. Within this technological evolution, Human Resource Management (HRM) has emerged as a strategic function for preparing the workforce to meet new organizational and technological demands, while simultaneously undergoing its own transformation through the adoption of digital technologies across HR processes and people management practices. Despite the advancement of the literature, there remains a lack of decision-support models focused on the implementation of DT in HRM, and existing studies continue to address HRM dimensions in a fragmented manner. Therefore, this thesis aims to propose a model for implementing DT in HRM within manufacturing industries. To achieve this objective, a Systematic Literature Review (SLR) was conducted using the PRISMA method to identify and characterize the evolution of HRM dimensions driven by DT. These dimensions were subsequently consolidated and validated by experts working in Brazilian manufacturing industries. Of the fourteen dimensions identified, twelve were validated using the Fuzzy Delphi method. Subsequently, the Fuzzy TOPSIS method was employed to prioritize the validated dimensions based on the judgments of HRM specialists from Brazilian manufacturing organizations. The results indicated that Leadership, New Forms of Work, and HRM and Technology should be prioritized when initiating the DT process in HRM. Finally, these findings supported the development of a roadmap to guide the implementation of digital transformation in HRM by integrating perspectives associated with the evolution from Industry 4.0 to Industry 5.0. The main contribution of this thesis lies in consolidating HRM dimensions that had previously been addressed separately in the literature and expanding the understanding of DT in light of the evolution from Industry 4.0 to Industry 5.0. From a practical perspective, the proposed decision-support model provides strategic guidance for managers and organizations in directing DT initiatives, enabling alignment among technology, people, and organizational objectives. Furthermore, the proposed model contributes to the achievement of Sustainable Development Goals (SDGs) 8 (Decent Work and Economic Growth) and 9 (Industry, Innovation and Infrastructure). The findings demonstrate that DT in HRM extends beyond the digitalization of processes, assuming a strategic role in workforce management to address the challenges of Industry 4.0 and Industry 5.0. Consequently, HRM plays a central role in integrating people and technology, while fostering an innovative organizational culture, developing new competencies, strengthening leadership, and promoting new forms of work that contribute to building smarter, human-centered, sustainable, and resilient organizations. Finally, this thesis advances the field of Production Engineering, particularly within the domains of Organizational Engineering, Knowledge Management, and Innovation, while supporting the objectives of the Graduate Program in Production Engineering and contributing to the research activities of the EORE Research Group.