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Industrial companies operate in a context of dynamic technological innovation, in which new technologies are adopted with a high impact internally and externally, leveraging their competitive advantages. Usually, managers decide to adopt technologies, often without realising the impacts on the company, but mainly supported by a strategic vision and the pursuit of differentiation. This study aims to describe the impacts of adopting Industry 4.0 technologies in industrial companies, focusing on sustainability's economic, social, and environmental dimensions and explaining which Industry 4.0 technologies contribute to each impact. This study used qualitative methodology, collecting data through interviews, internal documents, and observation. The results of this study identified new impacts in the three dimensions of sustainability, as well as the relationships between impacts and respective technologies. This study contributes to the literature by enriching and validating the impacts of adopting Industry 4.0 technologies on sustainability dimensions and linking these impacts with the technologies. In practice, it provides important insights to managers and decision-makers of manufacturing companies in making more informed decisions on adopting i4.0 technologies.

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In pursuing Industry 5.0's vision, which emphasises human well-being and the seamless integration of robots into manufacturing processes, understanding the role of anthropomorphic design is crucial. Anthropomorphic design, where robots exhibit human-like, animal-like, or even entirely novel traits (e.g. a display scrolling text), aims to improve human-robot interaction (HRI) and enhance human acceptance within manufacturing contexts. Understanding the optimal degree of human-readable characteristics in robots is essential for further advancements in this domain. This systematic literature review aims to identify anthropomorphic mechanisms in HRI and their effect on human acceptance in manufacturing. Using the PRISMA methodology, a systematic literature review was conducted across the WOS, EBSCO, and SCOPUS databases, resulting in the selection of four articles for final analysis. A quality assessment of the articles was conducted. On a scale of 0 to 16, article scores ranged from 10 to 15, with an average score of 13. The findings indicate that while current research provides valuable insights, it has predominantly focused on conventional anthropomorphic mechanisms from social robotics, such as basic human-like features (e.g., facial expressions, gestures), without exploring more advanced or novel traits. This highlights significant room for further exploration and innovation in industrial settings to enhance user acceptance and interaction. The study underscores the necessity for continued research and development to leverage advanced anthropomorphic designs that can better fulfil the goals of Industry 5.0.

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This paper examines the role of digital twins (DTs) in promoting sustainability within seaport operations and logistics. DTs have emerged as promising tools for enhancing seaport performance. Despite the recognized potential of DTs in seaports, there is a paucity of research on their practical implementation and impact on seaport sustainability. Through a systematic literature review, this study seeks to elucidate how DTs contribute to the sustainability of seaports and to identify future research and practical applications. We reviewed and categorized 68 conceptual and practical digital applications into ten core areas that effectively support economic, social, and environmental objectives in seaports. Furthermore, this paper proposes five preliminary potential applications for DTs where practical implementations are currently lacking. The primary findings indicate that DTs can enhance seaport sustainability by facilitating real-time monitoring and decision-making, improving safety and security, optimizing resource utilization, enhancing collaboration and communication, and supporting the development of the seaport ecosystem. Additionally, this study addresses the challenges associated with DT implementation, including high costs, conflicting stakeholder priorities, data quality and availability, and model validation. The paper concludes with a discussion of the implications for seaport managers and policymakers.

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