Purpose: Although prior studies have identified several technologies related to Industry 4.0 and their individual potential, it is still unclear how these technologies could be integrated to achieve better results. Based on this, we propose several collaborative networks combining technologies associated with Industry 4.0.Design/methodology/approach: A literature review was performed using a research model to support the evaluation and identification of key and collaborative technologies related to Industry 4.0. We examined these technologies using hierarchical cluster analysis and principal components analysis, based on their characteristics.Findings: The study identified big data, cloud computing, the internet of Things and cyber-physical systems as key technologies for Industry 4.0, and a further eight collaborative technologies that are strongly related to industrial performance. We found five collaborative networks with distinct goals in the context of Industry 4.0: (1) smart manufacturing; (2) technological platforms; (3) market reactiveness; (4) smart products and (5) flexibility.Practical implications: The findings allowed us to create five pathways for future work on Industry 4.0 technologies via collaborative networks. In practice, this will help managers to improve their focus on priorities regarding the implementation of Industry 4.0 technologies.Originality/value: This study provides insights into how to establish links between technologies through collaborative networks for certain purposes. In addition, we propose five future directions for these collaborative networks that require further investigation by researchers.

Industry 4.0 digital technologies in agribusiness will enable traditional farming systems to migrate to Agriculture 4.0. Open innovation emerges as an enabler for implementing these technologies and increased sector competitiveness. However, there are still doubts and questions about how technologies and open innovation relate to and will drive Agriculture 4.0. This study identified which digital technologies of Industry 4.0 have more adherence to agribusiness, what the barriers and facilitators for using these technologies are, and how open innovation can increase the competitiveness of agribusiness. The results show that of the Industry 4.0 technologies related to agribusiness, the Internet of Things (IoT) is the most prominent. The main barriers are the users’ need for more knowledge and advanced skills, which evidences the need for investment in training operators. Among the facilitators stand the pre-existence of several technologies, which bring with them already defined basic structures, control of the technology, and communication between systems. To overcome the barriers and enhance the migration to Agriculture 4.0, developing devices, tools, systems, software, and machines is essential. More stakeholders, managers, and practitioners may share such opportunities for innovation in agribusiness through the concept of Open Innovation. To benefit from it, facilitators, managers, and practitioners of agribusiness should search for alternatives for their problems with engineering solutions providers.

The purpose of this study is to identify how open innovation variables influence the competitive capability of manufacturing small and medium enterprises (SMEs) in a regional territory in Southern Brazil. The research method is a survey of 67 SMEs in Southern Brazil that provided data for an ordinary least squares (OLS) regression model encompassing seven innovation variables and five competitiveness constructs. The results indicate that most innovation initiatives have a low impact on creating a competitive edge in the surveyed companies. The most remarkable positive impacts are (i) technology trends influencing the shop floor productivity, (ii) flexibility influencing internal aspects, and (iii) customer satisfaction and innovative ideas and customized supplies influencing the market orientation. The study also reports that innovation processes are not safe from failures. Some ill-defined innovation initiatives may jeopardize the competitive edge.

Industry 4.0 and its technologies can potentially increase business competitiveness in the age of digital transformation through the implementation of its technologies. These digital technologies are increasingly present in the food industry, characterizing the concept of Agriculture 4.0. This digital transformation is a reality; however, it is unclear which digital technologies are most useful for each industry sector. Therefore, this paper seeks to explore the current state of implementation of digital technologies in different industrial sectors and which digital technologies should be leveraged to increase the performance of the agribusiness system. To do so, we used secondary data from a large-scale survey of 28 industrial sectors, representing 2225 companies in the Brazilian industry. Analyzing the different industrial sectors allowed us to present a framework of digital transformation to boost food industry competitiveness towards Agriculture 4.0. The results show that the food industry usually uses only one digital technology, showing the need for simultaneous and joint investments in the other technologies presented in this research. Public policies must be directed to encourage the expansion of digital technologies in the food industry.

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.