This study analysed the determining factors of the concentration of “superstar firms” in specific economies, with a focus on the interaction between technological innovation, economic development, and market structures. Using global data from Statista on superstar firms for the year 2022, statistical methods such as correlation analysis, an ANOVA, and cluster analysis were applied to identify patterns and relationships between variables like the GDP, market capitalization, and the development of artificial intelligence (AI). The analysis in this paper revealed significant positive correlations between the number of superstar firms and key economic indicators such as the GDP and market capitalization, suggesting that these firms drive economic growth and technological advancement. The cluster analysis identified groupings of countries based on their technological capabilities and economic performance, highlighting that a great number of these firms are concentrated in advanced economies. This work emphasizes the importance of technological infrastructure, innovation policies, and regulatory frameworks in promoting competitive environments for superstar firms. Additionally, it addresses the socioeconomic implications, including challenges related to wealth concentration, inequality, and the transformation of the labour market. Public policies are recommended to foster inclusive innovation, STEM education, and international governance to balance global competitiveness with equitable economic growth.

The tourism industry is constantly evolving, and in recent years there has been a growing interest in the use of Artificial Intelligence (AI) to improve and transform the services offered. This article explores the role of Artificial Intelligence (AI) in the Spanish tourism industry and discusses its importance and potential impact in the near future. The study examines various cases of AI use in the tourism sector, including personalised customer experiences, optimised destination management, and improved safety measures. It also addresses the ethical and social implications of implementing AI in the industry. The article highlights the opportunities and challenges associated with AI in the Spanish tourism sector and emphasises the need to address these challenges to fully leverage the potential of AI. The findings suggest that AI has significant potential to transform and enhance the tourism industry in Spain, but careful consideration and management of the associated challenges are crucial for its successful implementation.

This study examined the impact of ChatGPT on learning financial mathematics among students in the Business Administration degree (ADE). A qualitative methodology was used through a descriptive case study involving five student groups. The objective was to assess how artificial intelligence can enhance accuracy in financial calculations and structuring responses. Results showed improved calculation accuracy and organization of problem-solving processes, with immediate feedback. However, some students became dependent on the tool, reducing their problem-solving autonomy. The study highlighted the need to balance AI use with fostering critical thinking and cognitive autonomy. Limitations included insufficient attention to technology access disparities. It concluded that while ChatGPT holds great potential to support learning, its integration must be carefully managed to prevent students from losing critical skills.

En el contexto de la creciente incorporación de algoritmos en la gestión pública, este artículo examina los desafíos que plantea la transparencia algorítmica desde una doble aproximación. Por un lado, se realiza un análisis comparativo de tres sistemas emblemáticos de decisión automatizada en el ámbito público—COMPAS, SyRI y SALER—para identificar patrones comunes de opacidad, sesgo y déficit de supervisión. Por otro lado, se diseña, aplica y valida un marco evaluativo integral centrado en los principios de explicabilidad, accesibilidad, supervisión humana y equidad, el cual se aplica empíricamente al sistema BOSCO, utilizado en España para la asignación del bono social eléctrico. Metodológicamente, se combina una revisión sistemática de literatura, un análisis comparativo de casos y una validación mediante paneles de expertos bajo enfoque Delphi. Los resultados muestran deficiencias estructurales en la transparencia de BOSCO, especialmente en cuanto a accesibilidad técnica y rendición de cuentas, lo cual pone en evidencia las limitaciones de los actuales marcos regulatorios. Se concluye proponiendo un modelo replicable de evaluación que permita a las administraciones públicas auditar de forma efectiva la transparencia de sus algoritmos, fortaleciendo así la gobernanza democrática en la era digital.

Purpose: This paper aims to examine how artificial intelligence (AI) adoption influences the construction, visibility, and valuation of intangible assets in Spanish publicly listed companies, specifically those included in the IBEX 35 index.Design/methodology/approach: The study employs a convergent mixed-methods approach, combining fixed-effects panel regression, natural language processing (NLP), sentiment analysis, and qualitative case profiling. A composite Intangible Asset Visibility Score (IAVS) is developed, incorporating disclosure frequency, reporting quality, and balance sheet data. The AI Adoption Intensity (AIAI) index is constructed based on the strategic scope and communicative presence of AI initiatives. Data is collected from 210 firm-year observations (2019–2024) and triangulated using financial reports, ESG disclosures, corporate communications, and media coverage.Findings: Results confirm a statistically significant and positive relationship between AI adoption and intangible asset visibility. Firms with higher AIAI scores tend to report intangible assets more frequently and with greater narrative quality. Sectoral asymmetries are notable: finance and telecom outperform traditional sectors like construction. Sentiment and topic modeling show that AI-enhanced disclosures are predominantly framed positively, emphasizing brand value, sustainability, and talent development. Interestingly, R&D intensity was not a significant predictor of intangible asset visibility, suggesting a paradigm shift toward narrative-driven valuation.Research limitations/implications: The reliance on disclosure-based proxies for AI and intangible value may not fully capture internal capabilities. Further studies should explore causality, investor perception, and cross-cultural differences in AI-enabled reportingPractical implications: Managers are encouraged to align AI strategies with corporate reporting frameworks to enhance transparency, stakeholder trust, and market valuation. Regulatory bodies should consider updating disclosure standards to reflect the role of emerging technologies in shaping intangible capitalSocial Implications: Transparent communication of AI initiatives can improve public trust, inform responsible innovation, and promote ethical AI governance—particularly relevant under the EU’s CSRD and AI Act.Originality/value: This study introduces novel indicators (AIAI and IAVS) to quantify the impact of AI on intangible asset disclosure. It offers empirical evidence from a European context and reframes AI not only as a technological asset but as a meta-capability that amplifies the strategic and symbolic value of intangibles.

Este artículo examina la intersección entre la inteligencia artificial (IA), el pensamiento complejo y la metodología de auditoría de sesgo, enfocándose en cómo estas herramientas pueden garantizar un desarrollo ético y equitativo de los algoritmos de IA. Se destacan las fuentes de sesgo en los modelos de IA, los métodos de detección y las estrategias de mitigación que buscan mejorar la equidad y justicia de estos sistemas. Asimismo, se discute la importancia del pensamiento complejo para comprender las múltiples dimensiones y la interconexión de los sesgos algorítmicos, y cómo la auditoría de sesgo juega un papel crucial en la identificación y corrección de estas injusticias.