Multiple-criteria decision making (MCDM) methods have been widely employed in various fields and disciplines, including decision problems regarding Sustainable Development (SD) issues. The main objective of this paper is to present a systematic literature review (SLR) on MCDM methods supporting decisions focusing on the achievement of UN Sustainable Development Goals (SDGs) and the implementation of the 2030 Agenda for Sustainable Development in regional, national, or local contexts. In this regard, 143 published scientific articles from 2016 to 2020 were retrieved from the Scopus database, selected and reviewed. They were categorized according to the decision problem associated with SDGs issues, the MCDM methodological approach, including the use (or not) of fuzzy set theory, sensitivity analysis, and multistakeholder approaches, the context of MCDM applications, and the MCDM classification (if utility-based, compromise, multi-objective, outranking, or other MCDM methods). The widespread adoption of MCDM methods in complex contexts confirms that they can help decision-makers solve multidimensional problems associated with key issues within the 2030 Agenda framework. Besides, the state-of-art review provides an improved understanding of this research field and directions for building a research agenda for those interested in advancing the research on MCDM applications in issues associated with the 2030 Agenda framework.

Smart manufacturing comprises fully integrated manufacturing systems that respond in real time to meet the changing demands and conditions in industrial activities, supply networks and customer needs. A smart manufacturing environment will face new challenges, including those concerning metrological issues, i.e., analysis of large quantities of data; communication systems for digitalization; measurement standards for automated process control; digital transformation of metrological services; and simulations and virtual measurement processes for the automatic assessment of measured data. Based on the assumption that the interplay between smart manufacturing and digitalization of metrology is an emerging research field, this paper aims to present a systematic literature review (SLR) based on a bibliographic data collection of 160 scientific articles retrieved from the Web of Science and Scopus databases over the 2016–2022 time frame. The findings presented in this review and recommendations for building a research agenda can help policy makers, researchers and practitioners by providing directions for the evolution of digital metrology and its role in the digitalization of the economy and society.

Rapid technological changes and disruptive innovations have resulted in a significant shift in people’s behavior and requirements. Electronic gadgets, including smartphones, notebooks, and other devices, are indispensable to everyday routines. Consequently, the demand for high-capacity batteries has surged, which has enabled extended device autonomy. An alternative approach to address this demand is battery swapping, which can potentially extend the battery life of electronic devices. Although battery sharing in electric vehicles has been well studied, smartphone applications still need to be explored. Crucially, assessing the batteries’ state of health (SoH) presents a challenge, necessitating consensus on the best estimation methods to develop effective battery swap strategies. This paper proposes a model for estimating the SoH curve of lithium-ion batteries using the state of charge curve. The model was designed for smartphone battery swap applications utilizing Gated Recurrent Unit (GRU) neural networks. To validate the model, a system was developed to conduct destructive tests on batteries and study their behavior over their lifetimes. The results demonstrated the high precision of the model in estimating the SoH of batteries under various charge and discharge parameters. The proposed approach exhibits low computational complexity, low cost, and easily measurable input parameters, making it an attractive solution for smartphone battery swap applications.

A fundamental issue in the implementation of the 2030 Agenda at the national level refers to the systemic analysis of interactions of global targets, considering the context-specific understanding of these interactions within a long-term vision. Another critical issue is how to apply and combine different approaches and tools to provide a consistent analysis for evidence-based decision-making on the Sustainable Development Goals (SDGs) and global targets. Consistent with both concerns, a systemic and contextual framework to prioritize SDG targets for a country’s 2030 Agenda is proposed, by integrating fuzzy multicriteria decision-making methods, prospective structural analysis, and network theory tools. The applicability of the proposed framework could be demonstrated through a socio-technical experiment carried out during 2018 for the definition of the 2030 Agenda in Brazil. The experiment is especially designed to bring methodological insights to this decision-making process, and empirical results highlight the targets that will drive the Brazilian 2030 Agenda. Although the empirical results presented in this paper are exclusive to Brazil, we believe that the proposed framework can be replicated in other countries, especially those that are going to prioritize the global targets to be included in their respective Agendas.

Increased environmental and social responsibility awareness, while producing unique opportunities for sustainability-oriented innovations, has generated important challenges for companies. The path to sustainability requires corporate strategies that guarantee profitability, managing simultaneously environmental and social responsibilities. An attempt is made to provide an understanding of sustainable development thinking in business, discussing how the combination of the transition management, adaptive planning and sociotechnical approaches can contribute towards an effective implementation of sustainability-oriented innovations in business context. The article proposes a conceptual model, which incorporates this contribution, developed through a four-year action-research project carried out within a large Brazilian energy company – Petrobras. The authors argue that the adoption of the proposed model by other large firms operating in different societal sectors might trigger organisational changes related to current corporate practices of technological innovation management.

This paper aims to propose a conceptual model to create and select smart home conceptions from the user-centric and sustainable perspective, using the Design Thinking approach. Although considerable research has been devoted to smart homes in the last two decades, gaps are evident in current research concerning the creation and selection of smart home conceptions from both user-centric and sustainable perspectives. A systematic literature review covering the period 2000–2020 indicated that Design Thinking (DT) has rarely been exploited in smart home projects. The applicability of the proposed model could be demonstrated in the context of a smart home project in Brazil (NO.V.A. Project) conducted by an energy distribution player in this country in cooperation with two local universities and other institutional partners. The replication of this approach in smart home projects will allow decision-makers and project managers to place future residents at the center of the smart home design, creating and selecting the best conceptions that will meet users’ desires, expectations, and needs that can be transformed into reality.