https://www.um.edu.mt/library/oar/handle/123456789/296 Thu, 05 Nov 2026 08:58:01 GMT 2026-11-05T08:58:01Z https://www.um.edu.mt/library/oar/handle/123456789/150769 Title: Designing, developing, and evaluating XR experiences – selected aspects Authors: Antonopoulou, Caterina; Arsenopoulou, Natalia; Calì, Fabrizio; Papageorgopoulou, Penny; Rizopoulos, Charalampos Abstract: This paper aims to highlight various aspects of the design, development, and evaluation processes of immersive XR experiences. It focuses on the creative and expressive aspects of virtual environments (VEs), following the design and implementation processes of artistic VEs as conducted by the under- graduate students of the Department of Digital Arts and Cinema at the National and Kapodistrian University of Athens (NKUA) and the Department of Digital Arts at the University of Malta (UoM), in the course of three laboratory classes of Digital Artistic Creation and Immersive Experience Design, during the academic years 2020–2021 and 2022–2023. Medium-related challenges are discussed in relation to the design and implementation of user interaction, 3D content creation, 3D composition and social engagement in VEs. Furthermore, theoretical approaches of storytelling within VEs and the narrative design process of artistic VEs are discussed. Selected case studies from the students’ virtual artworks are analysed in relation to the applied narrative types and structures. As a further elaboration on the evaluation of XR experiences, a CAVE system is analysed in terms of various characteristics that may affect the quality of the experience. Sun, 01 Jan 2023 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/150769 2023-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/150761 Title: From AI-enabled capabilities to agentic AI orchestration : a framework for open circular innovation and industrial symbiosis Authors: Camilleri, Mark Anthony Abstract: Industrial symbiosis supports circular economies through resource exchanges. Yet, this collaborative approach faces information asymmetries, fragmented networks and coordination challenges. This study synthesises the extant literature and examines five industrial symbiosis initiatives with varying levels of digital maturity. Cross-case analyses identify five interconnected capabilities, including knowledge discovery, ecosystem orchestration, resource matching, resource exchange facilitation and value-chain integration. The findings indicate that, for the time being, existing platforms remain are AI-assisted rather than fully autonomous. Building on these empirical insights, the study proposes an Agentic Industrial Symbiosis (AIS) framework that conceptualises how these capabilities could support future Agentic AI orchestration. The framework extends existing research on industrial symbiosis by clearly explaining the potential transition from AI-enabled capabilities towards autonomous ecosystem coordination. It offers novel theoretical and practical implications for circular innovation. Moreover, it provides a foundation for future empirical research. Thu, 01 Jan 2026 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/150761 2026-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/150742 Title: Responsible AI governance for student-centred digital transformation in higher education Authors: Camilleri, Mark Anthony Abstract: The digitalisation of higher education as well as the recent advances in generative and agentic artificial intelligence (AI) are transforming teaching and learning, academic leadership, institutional governance and student support services. AI-enabled technologies provide opportunities to personalise learning, improve educational decision-making, enhance administrative efficiency and foster innovation across universities. However, their widespread adoption also raises concerns regarding their algorithms’ transparency, explainability, fairness, accountability, privacy, academic integrity and stakeholder trust. Consequently, responsible AI governance is emerging as a strategic institutional capability that facilitates student-centred digital transformation while safeguarding ethical, educational and societal values. This conceptual paper examines how responsible AI governance can support higher education institutions in fostering digital transformation within an increasingly complex technological and regulatory environment. Building on recent advances in AI governance and explainable artificial intelligence (XAI), it proposes a conceptual framework that integrates governance mechanisms with institutional capabilities to promote transparent, trustworthy and student-centred AI adoption. The framework synthesises principles of ethical oversight, algorithmic transparency, explainability, risk management, regulatory compliance, stakeholder engagement, human oversight, and continuous evaluation. It argues that explainability should be regarded as an institutional capability that empowers educators, supports informed student engagement, strengthens academic decision-making and reinforces institutional legitimacy. The proposed framework demonstrates how responsible AI governance can enhance strategic alignment, organisational learning, interdisciplinary collaboration, knowledge sharing and digital resilience while supporting equitable educational innovation. It also considers the implications of AI for curriculum design, assessment, student engagement, academic work and human-AI collaboration. This contribution extends the literature on responsible AI in a higher educational context. It offers practical guidance for university leaders, educators, policymakers and quality assurance bodies who are seeking to implement trustworthy AI systems that strengthen institutional effectiveness and promote student-centred digital transformation. Therefore, it supports the achievement of SDG 4 (Quality Education) and SDG 9 (Industry, Innovation and Infrastructure) by advancing responsible AI governance and digital innovation in higher education. Thu, 01 Jan 2026 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/150742 2026-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/149670 Title: Digital transformation and AI-enabled accommodation platforms: Implications for destination marketing, governance and development Editors: Lehto, Xinran Abstract: This special issue seeks to advance understanding of how digital platforms and AI are reshaping destination marketing and management through their influence on accommodation systems. The guest editors invite contributions that reconceptualize accommodation from a traditional infrastructural requirement for tourism growth, into a strategic and digitally mediated component of destination marketing ecosystems, where platforms: (i) Curate and prioritize destination visibility through algorithms; (ii) Influence destination image formation via reviews, ratings and content; (iii) Shape demand distribution across locations and property types; and (iv) Mediate pricing and perceived value through AI-driven tools. Therefore, prospective contributions can examine the interplay between digital platforms, AI systems and destination stakeholders, including DMOs, local authorities, hotels, hosts and residents. It is imperative that all submissions include empirical testing based on multiple sources of data (e.g., mixed datasets, multi-level data, stakeholder perspectives, longitudinal evidence, and/or triangulated methods). Studies should move beyond descriptive analysis to offer theoretically grounded insights and meaningful implications for policy, governance and managerial practice. Interdisciplinary perspectives are welcome, provided that the study maintains a clear focus on destination-level outcomes and implications. Indicative themes Topics of interest include, but are not limited to: Digital intermediation and destination marketing • The role of accommodation platforms in shaping destination visibility and image • Algorithmic curation and its impact on destination branding and positioning • User-generated content, reviews and AI-generated content in destination representation • Platform-mediated storytelling and the construction of place narratives AI and the transformation of tourism demand: • AI-driven recommendation systems and their influence on destination choice • Dynamic pricing and perceived destination value • Personalization, segmentation and demand forecasting in platform ecosystems • The role of generative AI in marketing accommodation and destinations Destination governance and strategic management • The evolving role of DMOs in platform-dominated ecosystems • Governance challenges arising from platform power and data asymmetries • Regulatory responses to platform-mediated accommodation and AI systems • Public–private coordination in destination marketing and management Spatial dynamics and demand distribution • The redistribution of tourist flows through platform algorithms • Neighbourhood-level impacts and micro-destination development • Overtourism, undertourism and spatial imbalances linked to platform visibility Competition and destination competitiveness • Competitive dynamics between hotels and P2P accommodation in digital marketplaces • The influence of platform metrics (ratings, rankings) on destination competitiveness • The effects of market concentration and platform dominance on destination offerings Sustainability and destination development • Impacts of accommodation platforms on sustainable destination development • Community well-being, housing pressures and social carrying capacity • Infrastructure and environmental implications of platform-driven demand Stakeholders and power relations • Power asymmetries between platforms, DMOs, accommodation providers and regulators • Stakeholder collaboration and conflict in destination marketing ecosystems • The impact of data access and digital skills on stakeholder’s decisionmaking Future trajectories of destination systems • The integration of AI in destination marketing strategies • The future of hotels within platform-mediated ecosystems • Future scenarios for the evolution of destination management in the context of platform-based ecosystems. In sum, this special issue seeks to develop a system-level perspective that positions AI-enabled accommodation platforms as both market mechanisms (i.e., systems that match supply and demand, set prices and govern transactions) as well as promotional channels. It calls for research that critically examines how these digitally mediated systems are reshaping destination visibility, competitiveness and governance. Moreover, prospective contributions can provide insights into how stakeholders can avail themselves of these smart technologies to ensure sustainable, inclusive and strategically coordinated destination development. Thu, 01 Jan 2026 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/149670 2026-01-01T00:00:00Z