Abstract
The Metaverse is attracting significant investment and promises to transform value creation and business competitiveness. While Small and Medium-Sized Enterprises (SMEs) are exploring its use to overcome resource limitations and enhance operations, its role in facilitating internationalization remains unclear. This study fills a research gap by investigating how the Metaverse can support SMEs in overcoming internationalization challenges through value creation, capture, and delivery. A Metaverse-based framework was developed and validated using a three-round Delphi approach with international business professionals and Metaverse specialists. This study confirmed that the Metaverse offers SMEs distinct opportunities to enhance value creation, capture, and delivery in the internationalization process. In value creation, it supports broader product offerings (e.g. digital twins), improved efficiency, and co-creation through superior knowledge management and deeper insights into consumer preferences. For value capture, the Metaverse enables access to new revenue models, demand forecasting through simulation, and better resource utilization, helping SMEs overcome regulatory and cultural barriers. In terms of value delivery, immersive interactions and real-time communication facilitate international collaboration, improve customer engagement, and extend global market reach. Overall, the Metaverse helps SMEs address internationalization challenges linked to firm size, resource constraints, and market complexity, ultimately strengthening their competitive advantage in international contexts. © 2025 Elsevier B.V., All rights reserved.

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Music therapy has emerged as a promising approach to support various mental health conditions, offering non-pharmacological therapies with evidence of improved well-being. Rapid advancements in artificial intelligence (AI) have recently opened new possibilities for ‘personalized’ musical interventions in mental health care. This article explores the application of AI in the context of mental health, focusing on the use of machine learning (ML), deep learning (DL), and generative music (GM) to personalize musical interventions. The methodology included a scoping review in the Scopus and PubMed databases, using keywords denoting emerging AI technologies, music-related contexts, and application domains within mental health and well-being. Identified research lines encompass the analysis and generation of emotional patterns in music using ML, DL, and GM techniques to create musical experiences adapted to user needs. The results highlight that these technologies effectively promote emotional and cognitive well-being, enabling personalized interventions that expand mental health therapies.

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Flexibility markets are emerging across Europe to improve the efficiency and reliability of distribution networks. This paper presents a methodology that integrates local flexibility markets into network maintenance scheduling, optimizing the process by contracting flexibility to avoid technical issues under the topology defined to operate the network during maintenance. A meta-heuristic approach, Evolutionary Particle Swarm Optimization (EPSO), is used to determine the optimal network topology.

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