Abstract
Collaborative robots (cobots) are emerging in manufacturing as a response to the current mass customization production paradigm and the fifth industrial revolution. Before adopting this technology in production processes and benefiting from its advantages, manufacturers need to analyze the investment. Therefore, this study aims to develop a decision -making framework for cobot adoption, incorporating a comprehensive set of quantitative and qualitative criteria, to be used by decision -makers in manufacturing companies. To achieve that objective, a qualitative study was conducted by collecting data through interviews with key actors in the cobot (or advanced manufacturing technologies) adoption decision process in manufacturing companies. The main findings of this study include, firstly, an extensive list of decision criteria, as well as some indicators to be used by decisionmakers, some of which are new to the literature. Secondly, a decision -making framework for cobot adoption is proposed, as well as a set of guidelines to use it. The framework is based on a weighted scoring method and can be customizable by the manufacturing company depending on its specific context, needs, and resources. The main contribution of this study consists in assisting decision -makers of manufacturing companies in performing more complete and sustained decision analyses regarding cobots adoption.

Abstract
The Industry 4.0 technologies and servitization are requiring manufacturers to reinvent themselves to remain competitive. In this sense, companies are putting more emphasis on the customer experience, while associating services to their products with the support of emerging technologies. At the same time, actors in the innovation ecosystem such as universities, research institutes, and service providers are involved in the value co-creation process. Thus, this study aims to systemize and present the main findings of a literature review regarding the role of digitalization, servitization, and innovation ecosystem actors in boosting innovation in business models. The study involved 585 articles in international journals and conference proceedings published till 2021. A detailed selection process led 10 articles for further analysis. As a consequence of digitalization and servitization, there has to be an alignment among ecosystem actors to capture the co-created value generated by BMI. Moreover, the combination of BMI, servitization, and digitalization may also be structured into frameworks according to the different levels of each of those factors, thus allowing for companies to assess and position themselves in such frameworks and identify the path to follow. However, any of these articles addressed the combination of the three topics proposed: digitalization, servitization, and the contribution of the innovation ecosystem actors, even if they showed a clear interdependence between these areas, leading to common findings impacting BMI. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Este trabalho analisa o processo de servitização de diferentes fornecedores na cadeia produtiva do café no Brasil. Foi realizada uma revisão da literatura sobre sistemas produto-serviço (SPS) para estabelecer uma estrutura para identificar a tipologia de serviços no setor agrícola. Os resultados destacaram que a prestação de serviços "menos avançados" não é uma condição necessária para que a empresa ofereça serviços "mais avançados". Entretanto, as características das propriedades rurais parecem afetar o número de serviços associados aos fornecedores de máquinas. Os resultados ajudam os gerentes desse setor a identificar as ofertas de serviços e ampliam a discussão sobre servitização, ao abranger um setor pouco explorado.

Abstract
Industrial companies live in a context of dynamic technological innovation, in which new technologies are adopted with a high impact internally and externally, leveraging their competitive advantages. A usual situation is managers deciding to adopt technologies, often without realising the impacts on the company but mainly supported by a strategic vision and the pursuit of differentiation factors. This article aims to present the results of a literature review on the impacts of Industry 4.0 technologies adoption in sustainability dimensions by industrial companies. These impacts were presented according to the three dimensions of sustainability: economic, environmental and social. The results of this study can be used by practitioners and researchers for an overview of the I4.0 technologies adoption by manufacturing companies and their impacts on sustainability dimensions, summarising the knowledge concerning this topic. © 2023 IEEE.

Abstract
Objective: A systematic literature review was conducted to identify relevant ergonomic and safety factors for designing collaborative workspaces in industrial settings. Background: The growing use of smart and collaborative robots in manufacturing brings some challenges for the human-robot interaction design. Human-centered manufacturing solutions will improve physical and mental well-being, performance, productivity and sustainability. Method: A systematic review of the literature was performed based on the protocol of Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Results: After a search in the databases Scopus and Web of Science, applying inclusion and exclusion criteria, 33 publications in the English language, published between the years 2010 and 2020, remained in the final analysis. Publications were categorized in cognitive ergonomic factors (13), safety factors (10), physical ergonomic factors (6) and organizational ergonomic factors (4). The analysis of results reinforced that to optimize the design of collaborative workstations it is imperative to have a holistic perspective of collaboration, integrating multiple key factors from areas such as engineering, ergonomics, safety, sociology and psychological as well as manufacturing efficiency and productivity. Application: Considering the advantages of the use of cobots in manufacturing, the results of this review will be useful to support companies in implementing human-robot collaboration. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.