Digital transformation (DT) is crucial for SMEs to streamline operational efficiency, foster innovation, and meet upcoming challenges. Integrating sustainability into this process not only enhances a company’s reputation but also attracts customers and investors who value environmental responsibility. Despite this opportunity, many SMEs operate without clear plans and strategies. The literature review identified a lack of roadmaps that integrate sustainability into the digital transformation process for SMEs. Thus, this paper aims to propose a sustainable digital transformation roadmap for SMEs that evaluates their digital maturity and facilitates gradual implementation in alignment with their strategic objectives. A systematic literature review using the Methodi Ordinatio defined six key dimensions of digital transformation. Consequently, the SDT-SMEs Roadmap was developed, drawing on ISO/IEC 33000 standards to offer well-defined processes for enhancing digital competencies. The roadmap features three organizational planning levels—strategic, tactical, and operational—and includes a maturity model that evaluates 75 processes across six dimensions: Digital Technologies, Customer Focus, Organizational Culture, Organizational Governance, People, and Sustainability. Validation through a case study confirmed the roadmap’s effectiveness in addressing real-world challenges and guiding SMEs through the digitization process. The SDT-SMEs Roadmap provides a comprehensive and integrated approach, ensuring continuous adaptation and improvement in sustainable digital transformation efforts. This roadmap addresses a significant gap in the literature and presents a practical, strategic, and adaptable pathway for SMEs embarking on their digital transformation journeys.

Sustainable digital transformation in SMEs not only simplifies operations and increases efficiency but also fosters innovation, facilitates data-driven decision-making, and minimizes negative environmental and social impacts, paving the way for a sustainable competitive advantage in the digital age. However, SMEs still face significant barriers to implementing this transformation. In addition to limited financial resources, a critical obstacle is the lack of specific and comprehensible roadmaps. Thus, this paper aims to analyze existing roadmaps for sustainable digital transformation in SMEs. A systematic literature review was conducted using the PRISMA and Methodi Ordinatio methods, with data collection and analysis performed using the NVivo 12 and VOSviewer software (version 1.6.20). Content analysis was used to assess how these papers align with the study’s context. The analysis identified whether the roadmaps address aspects related to the triple bottom line (TBL), their specificity to SMEs, the principles of digital transformation they incorporate, and the aspect of digital maturity. The findings indicate that none of the current literature provides a fully developed roadmap for sustainable digital transformation in SMEs. Consequently, future studies are suggested to develop a comprehensive roadmap that addresses these issues. Finally, this study highlights the main gaps and opportunities in each studied roadmap and formulates 14 research questions divided into six categories for future investigation. Addressing these questions can help close the current gaps in the literature and provide SMEs with robust, adaptable, and sustainable digital transformation strategies.

In order to aid professionals in disaster management, efficient procedures and technologies are developed and adopted. This paper intends to present the results of a literature review on the use of the Internet of Things (IoT) in disaster management. Even though the IoT approach was defined many years ago, only recently its technologies have been enhanced and acquired greater clarity and scope. Internationally, scientific studies indexed in two databases, Scopus and Web of Science were found, selected and analyzed. Two portfolios of papers were generated: the first for the bibliometric analysis and, the second, leaner, for qualitative analysis retaining the contributions pertinent to the proposed theme. The literature review identified macro-discussions on the IoT in disaster management and applications of more specific devices or technologies. In disaster operations, the IoT is a target theme in the fields of Computer Science, Electronic Engineering and Environmental Engineering, especially useful in disaster mitigation, rescue, response, and recovery. The main positive impact is the facilitated communication between professionals, more robust data and monitoring of data for environmental management, first aid, people tracking, distribution of supplies and medicines, among other purposes.

The concept of smart cities has gained relevance over the past few years. Public managers have been planning investments to turn their cities into smart cities. Maturity models can help managers to monitor the performance of urban indicators; however, these maturity models are not always capable of meeting their proposed goals. In this sense, this research aims to develop a maturity model that ranks the “smartness” of a city based on social and technological indicators. The Smart Cities Maturity Model (MMSC) variables were extracted from ISO’s 37153:2017, 37120:2018, 37107:2019. The MMSC is structured on a hybrid TOPSIS multicriteria decision-making method. In this paper, we modified TOPSIS and used it to generate a synthetic indicator, called smart index, that designates the level of maturity of a real city. For this change to be possible, we fixed some alternatives and changed the positive ideal and negative ideal solution. The methodology is proven to be very efficient in measuring the smart city maturity level, and it can be easily adapted for the upcoming ISOs.

The emission of pollutants from vehicles is presented as a prime factor deteriorating air quality. Thus, seeking public policies encouraging the use and the development of more sustainable vehicles is paramount to preserve populations’ health. To better understand the health risks caused by air pollution and exclusively by mobile sources urges the question of which input variables should be considered. Therefore, this research aims to estimate the impacts on populations’ health related to road transport variables for São Paulo, Brazil, the largest metropolis in South America. We used three Artificial Neural Networks (ANN) (Multilayer Perceptron—MLP, Extreme Learning Machines—ELM, and Echo State Neural Networks—ESN) to estimate the impacts of carbon monoxide, nitrogen oxides, ozone, sulfur dioxide, and particulate matter on outcomes for respiratory diseases (morbidity—hospital admissions and mortality). We also used unusual inputs, such as road vehicles fleet, distributed and sold fuels amount, and vehicle average mileage. We also used deseasonalization and the Variable Selection Methods (VSM) (Mutual Information Filter and Wrapper). The results showed that the VSM excluded some variables, but the best performances were reached considering all of them. The ELM achieved the best overall results to morbidity, and the ESN to mortality, both using deseasonalization. Our study makes an important contribution to the following United Nations Sustainable Development Goals: 3—good health and well-being, 7—affordable and clean energy, and 11—sustainable cities and communities. These research findings will guide government about future legislations, public policies aiming to warranty and improve the health system.