Purpose: The purpose of this research is to identify the sustainable practices of luxury fashion brands through their communications via official reporting documents to classify practices used for communicating sustainability performance.Design/methodology/approach: This research uses the qualitative content analysis of Global Reporting Initiative (GRI)-oriented sustainability reports to examine the sustainable practices of 31 companies within the top 100 global luxury brands.Findings: The authors classify the sample into four clusters: sustainability driven, sustainability newcomers, sustainability potential and sustainability passive. Results indicate that companies in this sector are focused on the issue of sustainability even though there is a remarkable fragmentation in terms of practices.Originality/value: The study contributes to a better understanding of sustainability reporting activities and approaches in the fashion luxury industry by describing best practices and the effect of sustainability in corporate communications.

Purpose: This study explores luxury wine hospitality by considering (1) physical activities and (2) activities created by integrating the physical domain with digital technology. In doing so, it aims to identify the different types of wine tourism-related luxury experiences and build a framework for interpreting hybrid luxury experiences in wine hospitality in the digital era. Design/methodology/approach: An explorative mixed-methods approach was adopted to investigate types of luxury wine hospitality using cluster analysis and in-depth interviews with producers of wines with controlled and guaranteed designation of origin in Italy’s Sangiovese area. Findings: This study presents a framework for understanding hybrid digital and physical experiences in wine hospitality by examining the core components of luxury experiences. We identify six types of luxury experiences in wine hospitality that combine a physical experiential component with varying degrees of integration with digital technologies. Practical implications: Our findings (1) provide wine businesses operating in hospitality within the luxury segment with a useful tool for optimising the integration of digital technology into physical experiences to add value to visitors’ activities and (2) highlight the importance of digital skills for wineries that organise luxury experiences. Originality/value: This study systematises the integration of digital technologies into physical activities related to wine hospitality. It presents a hybrid physical–digital analytical framework that adopts an experiential outline of the strategic design of wine hospitality businesses.

This study explores the evolving impact of technology on cultural heritage encounters, specifically within museum settings. It introduces a comprehensive conceptual framework that encompasses various aspects of the museum experience influenced by technology and assesses its effects on visitor satisfaction and loyalty intentions. Through an empirical investigation involving 300 individuals visiting archaeological sites in Rome (Italy), including both permanent and temporary exhibitions with varying levels of technological integration, this research employs a self-administered questionnaire to validate its hypotheses. The results underscore the significance of technology in shaping diverse facets of the visitor experience, such as education-entertainment fusion, engagement, and ambience, with substantial implications for enhancing customer satisfaction and fostering visitor loyalty. This research adopts a mixed-methods approach to investigate the evolving role of technology in cultural heritage encounters within museums. In a first phase, a comprehensive conceptual model that captures various dimensions of the museum experience influenced by technology was designed. Subsequently, data was collected from a purposive sample of 300 individuals visiting archaeological sites in Rome, encompassing both permanent and temporary exhibitions. This sample is intentionally diverse in terms of technology integration, allowing for a nuanced analysis. Data is gathered through the administration of a self-administered questionnaire designed to empirically test the hypotheses formulated in the conceptual model. Statistical analyses, including regression analysis and structural equation modeling, are employed to assess the impact of technology on visitor satisfaction and loyalty intentions. This research contributes to the field by introducing a comprehensive conceptual framework that holistically examines the multifaceted influence of technology on the museum experience, including dimensions such as edutainment, engagement, and ambience. Furthermore, it provides empirical evidence of these effects through a diverse sample of museum visitors. This study offers valuable insights into the evolving role of technology in cultural heritage contexts, filling a gap in the existing literature and providing actionable guidance for cultural institutions seeking to enhance visitor engagement and loyalty. The findings of this research hold practical significance for cultural institutions, particularly museums, aiming to leverage technology to enrich visitor experiences. By understanding how technology influences dimensions such as edutainment, engagement, and ambience, museums can strategically integrate technology to enhance customer satisfaction and foster visitor loyalty. This research encourages museums to adopt innovative technological solutions that cater to diverse visitor preferences, ultimately ensuring a more immersive and satisfying cultural heritage encounter.

Purpose: This study addresses competency requirements for senior organizational leaders navigating artificial intelligence (AI) integration. Existing managerial frameworks inadequately address algorithmic decision-making contexts; this research investigates which AI-related competencies are essential for C-suite executives and board directors, how managerial roles evolve with AI adoption, and what ethical and regulatory competencies constitute responsible AI leadership. Grounded in socio-technical systems and dynamic capabilities perspectives, the study develops a theory-informed taxonomy integrating classical management scholarship with contemporary AI organizational realities. Design/methodology/approach: The study employs a preferred reporting items for systematic reviews and meta-analyses (PRISMA)-guided systematic literature review, searching Scopus and Web of Science databases (2010–2024) using Boolean strings targeting AI technologies, competencies and managerial contexts. From 2,456 unique records, 92 articles meeting inclusion criteria underwent analysis. A novel large language model (LLM)-assisted extraction protocol utilizing Gemini Flash 2.0 with human-in-the-loop validation processed content systematically. Structured content analysis, employing iterative expert-driven coding with intercoder reliability (Cohen's κ > 0.80), generated a hierarchical competency taxonomy. Quantitative descriptive analysis characterized methodological, sectoral and thematic corpus distributions. Findings: The analysis yields a four-family competency taxonomy encompassing 18 subcategories. Strategic and Decision-Making Competencies include AI strategic thinking, risk management, economic evaluation and data-driven decision-making. Technical and Analytical Competencies comprise AI literacy, data governance, computational thinking and systems architecture knowledge. Ethical and Regulatory Knowledge encompasses algorethics and legal compliance. Leadership and Change Management Competencies involve engagement leadership, multidisciplinary team coordination, resistance management, human–AI collaboration design, technical communication and continuous organizational learning. The taxonomy reveals executive role evolution from directive authority toward socio-technical orchestration. Practical implications: The taxonomy provides actionable guidance for human resource executives conducting competency gap analyses, informing targeted development interventions rather than generic leadership training. Organizations can incorporate AI-related competencies into executive recruitment, board nominations and succession planning. Recommendations differentiate by context: SMEs might prioritize strategic and ethical competencies while accessing technical expertise externally; large corporations in regulated sectors should build comprehensive competencies; public organizations should emphasize ethical dimensions; technology startups should focus on strategic and leadership domains as founders transition to executive roles. Originality/value: This research contributes three theoretical advances: first, a theory-informed synthesis integrating socio-technical systems and dynamic capabilities perspectives, extending classical competency frameworks and upper echelons theory for AI contexts; second, demonstration of transparent, replicable LLM-assisted systematic review protocols addressing hallucination and reliability concerns; third, establishment of validated taxonomic structure, operational definitions and testable propositions enabling cumulative empirical research. The study addresses a critical gap by providing the first comprehensive, multi-sector synthesis specifically targeting senior leadership competencies for AI-driven organizations, grounded in established theoretical frameworks.