Abstract
Small, medium, and large organizations collect vast amounts of data with the expectation of using it to generate commercial value. Machine learning is a powerful tool for extracting valuable insights from this data and serves as a pivotal sales strategy for companies to maximize profits. This paper seeks to analyze sales data and discern patterns in sales among products that exhibit similarities, such as boxes and bags. In order to achieve this goal, was used unsupervised learning methods that allow the segmentation of groups, specifically Principal Component Analysis (PCA), k-means algorithms, and hierarchical clustering. PCA was used to identify correlated variables and find hidden patterns in the data, particularly pertaining to product families with similar sales. Elbow, Silhouette, and 30 indices methods were applied to determine the optimal number of clusters. Based on these results, it was determined the optimal number of clusters. Validation methods were employed to identify the clustering algorithm exhibiting the best performance. Stability measures evaluated the consistency of the clusters, while the cophenetic coefficient aided in determining the most effective data grouping method. After validation, the clustering algorithms were implemented. The results indicated that all clustering algorithms effectively segmented the data, with particular emphasis on the performance of the k-means algorithm. This study identified product groups with similar sales patterns and key products that impact the company’s global sales. Multivariate analysis provided a deeper understanding of sales dynamics, enabling the company to implement targeted marketing strategies and optimize resource allocation to boost bag and box sales in Portugal and other countries. © 2025 Elsevier B.V., All rights reserved.

Abstract
Airborne Wind Energy (AWE) systems represent an innovative method for capturing wind energy at high altitudes, where wind conditions are typically stronger and more consistent. These systems utilize flying devices tethered to a ground station to harness wind energy. An AWE system comprises a tether connecting the flying device to a base station, a control system for maneuvering the device, and a mechanism for converting kinetic energy into electricity. Researchers are exploring various materials, designs, and control methods to enhance the efficiency and reliability of AWE systems. Over the past decade, interest in AWE has surged, leading to a substantial increase in scholarly publications on the topic. This research conducts an in-depth bibliometric analysis. This analysis highlights emerging topics, allowing researchers to identify new trends and areas of interest within a field. By emphasizing these emerging topics, researchers and stakeholders can better align their efforts with the latest developments and opportunities in their area of study. Findings reveal that research on control techniques in AWE has grown at an average annual rate of 16% since 2013. Additionally, the study identifies the most influential aspects of the literature, including key topics, articles, authors, and keywords. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Abstract

Abstract
The concept of circular economy aims to extend the end-of-life of products by reducing or reusing products and materials, being Design a central part of a successful circular product. In line with the 6Rs strategy for circularity, Redesign (applied by eco-design practices) allows the creation of products that can be easily repaired, upgraded, or disassembled, extending their life, and fomenting a circular economy. For that reason, the aim of this research is to analyse the role of Redesign in the circularity of footwear products. Exploratory qualitative research was conducted, with five in-depth interviews with founders and R&D managers of prominent footwear organizations. Results demonstrate that most interviewed companies, which were born circular, considered Redesign practices from the definition of the product concept. In conclusion, looking at Redesign strategies holistically and through its specific sub-relationships have a major impact on the company's circularity practises.

Abstract
Industry 4.0 is transforming manufacturing environments, with robotics being a key technology that enhances various capabilities. The flexibility of Autonomous Mobile Robots has led to the rise of multi-robot systems in industrial settings. Considering the high cost of these robots, it is essential to determine the best fit of number and type before making any major investments. Simulation and modeling are valuable decision-support tools, allowing the simulation of different setups to address robot fleet sizing issues. This paper introduces a decision-support framework that combines a fleet manager software stack with the FlexSim simulator, helping decision-makers determine the most suitable mobile robots fleet size tailored to their needs. Unlike previous approaches, the developed solution integrates the same real robot coordination software in both simulation and actual deployment, ensuring that tested scenarios accurately reflect real-world conditions. A case study was conducted to evaluate the framework, involving multiple tasks of loading and unloading materials within a warehouse. Five different scenarios with varying fleet sizes were simulated, and their performances assessed. The analysis concluded that, for the case study under consideration, a fleet of three robots was the most suitable, considering relevant key performance indicators. The results confirmed that the developed solution is an effective alternative for addressing the problem and represents a novel technology with no prior state-of-the-art equivalents.

Abstract
PurposeThis study seeks to develop an Environmental Sustainability Balanced Scorecard (ESBSC) articulated through a strategic map for collaborative implementation by municipalities by municipalities. In addition, it aims to elucidate the architecture of this tool.Design/methodology/approachThe research uses qualitative methodology, initiating with document analysis, followed by municipal-level surveys and an interview with the Norte Portugal Regional Coordination and Development Commission (CCDR-N).FindingsThe study constructs an ESBSC that adopts an integrative approach to sustainability, focusing on municipal joint action. The tool fosters synergies and enhances cooperation. By incorporating a strategic mix, the tool contributes to improving the environmental management performance of the participating municipalities.Practical implicationsThis study introduces a tool designed for municipalities that aspire to incorporate environmental sustainability into their strategies. This tool facilitates the implementation and management of a long-term environmental strategy, with potential implications for organization and its culture. In addition, it highlights critical environmental factors that should serve as a starting point in future studies or applications of this tool.Social implicationsInvolving both an academic institution and multiple municipalities, this research identifies critical environmental factors that enhance environmental awareness within municipalities and designs a tool that, when consciously adopted, can influence the culture dynamics of the population involved. Furthermore, it proposes a structured and systematic research method for creating an ESBSC for joint municipal action.Originality/valueTo the best of authors' knowledge, this research constitutes the first exploratory attempt to devise an environmental strategy for joint municipal action. Although the tool emphasizes the environmental component, it promotes an integrated vision of sustainability. Despite the extensive application of balanced scorecards in various organizational contexts, their utilization in fostering environmental sustainability at a municipal level remains underexplored. This study addresses this gap by developing a tailored strategic tool that operationalizes environmental priorities within municipal governance frameworks.