Background: The global climate crisis has intensified the demand for sustainable solutions, positioning Reverse Logistics (RL) as a critical strategy for minimizing environmental impacts. Simultaneously, Industry 4.0 technologies are transforming RL operations by enhancing their collection, transportation, storage, sorting, remanufacturing, recycling, and disposal processes. Understanding the roles of these technologies is essential for improving efficiency and sustainability. Methods: This study employs a systematic literature review, following the PRISMA methodology, to identify key Industry 4.0 technologies applicable to RL. Publications from Scopus and Web of Science were analyzed, leading to the development of a theoretical framework linking these technologies to RL activities. Results: The findings highlight the fact that technologies like the Internet of Things (IoT), Artificial Intelligence (AI), Big Data Analytics, Cloud Computing, and Blockchain enhance RL by improving traceability, automation, and sustainability. Their application optimizes execution time, reduces operational costs, and mitigates environmental impacts. Conclusions: For the transportation and manufacturing sectors, integrating Industry 4.0 technologies into RL can streamline supply chains, enhance decision-making, and improve resource utilization. Smart tracking, predictive maintenance, and automated sorting systems reduce waste and improve operational resilience, reinforcing the transition toward a circular economy. By adopting these innovations, stakeholders can achieve economic and environmental benefits while ensuring regulatory compliance and long-term competitiveness.

Integrating Industry 4.0 technologies into food manufacturing processes transforms traditional quality management practices. This study aims to understand how these technologies are applied across managerial quality functions in the food industry. A systematic literature review was conducted using the Scopus and Web of Science databases, selecting 69 peer-reviewed articles. The analysis identified quality control (QC) and quality assurance (QA) as the most frequently addressed functions. Sensor technology was the most cited, followed by blockchain and artificial intelligence, mainly supporting food safety, process monitoring, and traceability. In contrast, quality design (QD), quality improvement (QI), and quality policy and strategy (QPS) were underrepresented, revealing a gap in strategic and innovation-focused applications. Based on these insights, the Food Quality Management 4.0 (FQM 4.0) framework was developed, mapping the relationship between Industry 4.0 technologies and the five managerial quality functions, with food safety positioned as a transversal dimension. The framework contributes to academia and industry by offering a structured view of technological integration in food quality management and identifying future research and implementation directions. This study highlights the need for broader adoption of advanced technologies to improve transparency, responsiveness, and overall quality performance in the food sector.

O tema gestão colaborativa vem sendo abordado como forma de gerar vantagem competitiva. Iniciativas colaborativas em cadeias de suprimentos (CS) proporcionaram o surgimento de métodos e práticas que corroboram a ideia de que a competitividade não se dá mais entre empresas isoladas, e sim entre cadeias. Na literatura, além de métodos colaborativos para a gestão da cadeia de suprimentos (GCS), é possível encontrar iniciativas para projeto, configuração, otimização, entre outras. Porém, observa-se baixa adesão de métodos colaborativos para a GCS, assim como dificuldades de implementação. O objetivo do artigo é investigar os métodos colaborativos referentes à coordenação de CS e analisar suas características e dificuldades de implementação. Uma revisão sistemática apontou o Collaborative Planning, Forecasting and Replenishment (CPFR) como o método colaborativo mais abordado e, posteriormente, um estudo de caso identificou dificuldades na implementação que colaboraram com o que foi pesquisado na literatura.

The search for competitiveness has led organizations to recognize the importance of implementing collaborative methods. In this context, Collaborative Planning, Forecasting, and Replenishment (CPFR) seek to relate customer demands to replenishment needs throughout the supply chain. The literature points to implementation difficulties, such as trust between partners and commitment, and to overcome these difficulties, the digital technologies of Industry 4.0 are emerging as an essential support. This paper aims to research the applicability and contribution of Industry 4.0 digital technologies to the CPFR, considering each stage of the CPFR. A systematic literature review identified an unexplored gap: the use and contribution of Industry 4.0 digital technologies to the functioning of the CPFR. Considering the sequence of the CPFR stages and their dependence on each other, a roadmap can be developed for using Industry 4.0 digital technologies in each stage of the CPFR. It was, therefore, possible to create a roadmap indicating, based on current literature, which Industry 4.0 digital technologies can enhance SCM at each stage of the CPFR. This roadmap has two significant contributions: (i) to guide companies in prioritizing the implementation of these technologies in support of supply chain objectives and (ii) to serve as a basis for further empirical studies, highlighting the development of this roadmap through its application in real situations.