Abstract
This literature review explores how C-level education connects to corporate sustainability and executive well-being. Drawing on upper echelons and human capital perspectives, prior literature links higher education to stronger corporate social responsibility (CSR) engagement and green innovation. The well-being implications, however, are less consistent. Education can support self-efficacy and a sense of purpose, but it can also intensify role overload and moral strain when organisational priorities conflict with sustainability values. We conclude by outlining key gaps and directions for future research. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2027.

Abstract
This study assesses physicians’ and dentists’ self-reported management control (MC) literacy in the Portuguese private healthcare sector. Understanding MC literacy among clinicians without formal managerial positions is important because they increasingly contribute to patient-centred care and service coordination. Using a quantitative survey (n = 48 valid responses out of 65), we examine reported familiarity with and use of MC-related information and practices. MC literacy is captured through self-reported familiarity with and use of MC-related information and practices, including information systems, financial information, non-financial information, and horizontal control. The findings indicate generally low levels of MC familiarity and tool use, with physicians displaying slightly higher levels than dentists. Respondents with management education exhibited a higher MC familiarity and more frequent use of MC-related tools. Additionally, those in managerial roles also report more frequent use of information systems and financial and non-financial information, as well as higher horizontal control, with modest associations. Our findings point to opportunities for competency development through curricular and continuing education initiatives in the private healthcare sector. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2027.

Abstract
Collaborative Online International Learning (COIL) projects offer accessible opportunities for internationalization “at home”, enabling students and teachers to engage in global learning environments while fostering individual and collective knowledge construction through intercultural collaboration. This study examines students’ perceptions of the educational benefits and learning outcomes associated with participation in a COIL project conducted between two higher education institutions during the spring semester of 2024–2025. Data were collected through an online survey and analyzed using statistical methods. The findings indicate that participation in the COIL project significantly supports the development of a range of competencies, including communication and digital skills, problem solving, multidisciplinary teamwork, intercultural awareness, leadership, time management, self-confidence, and the ability to share and critically discuss diverse perspectives. The results also emphasize the importance of fostering a sense of community, which emerged as a central factor in promoting student engagement in collaborative online learning. Additionally, the effective use of digital tools linking global classrooms was identified as a key enabler of remote international collaboration, facilitating interaction, discussion, and collective knowledge exchange. Overall, the study demonstrates that online collaborative networks generate substantial educational and professional benefits by enhancing communication, engagement, communities of practice, inclusion and innovation, while also offering directions for future research in COIL-based learning initiatives. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2027.

Abstract
Generative AI is already reshaping higher education. It can automate parts of writing, support feedback, and help students work across languages, but it also raises difficult questions about integrity, transparency, privacy, bias, and unequal access. This review brings together research published between 2021 and 2025 to map how students are using these tools, what ethical risks are most frequently reported, and how universities are responding. Across studies, academic integrity remains the dominant concern, especially as conventional detection tools struggle to keep pace. The literature also points to a continuing governance gap and to the growing vulnerability of traditional assessment formats. Building on these findings, we outline an ethical-pedagogical framework aimed at helping regulators and institutions translate broad principles into concrete guidance for staff and students. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2027.

Abstract
This bibliometric study analyzes 2,280 Scopus documents (2016–2025) to map the global evolution of digital technology, innovation, and well-being in higher education following the United Nations’ (UN) adoption of the Sustainable Development Goals (SDGs) in 2015. Output surged post-2020, driven by pandemic-accelerated digital adoption and institutional student mental health priorities. The United States, China, and India dominate production, supported by large-scale funding and national online learning ecosystems, with Sustainability (Switzerland) as the leading outlet. Dominant author keywords (resilience, mental health, and machine learning) reflect a core agenda of artificial intelligence (AI)-powered predictive analytics for emotional support and adaptive pedagogies. Prolific authors like Gupta, S. and Zekhnini, K. anchor learning analytics for stress detection, while mid-tier contributors advance inclusive design and sustainable edtech. The corpus illustrates a mature, interdisciplinary field transitioning from reactive responses to proactive, human-centered digital transformation. Limitations include Scopus-only coverage and post-search subject filtering. Future research should prioritize longitudinal validation of AI well-being tools, cross-national scalability, and sustainability metrics for digital learning infrastructure. This replicable analysis provides a data-driven foundation for SDG-aligned, technology-enhanced higher education. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2027.

Abstract
In this study, we compared different survival models using machine learning (ML) techniques to assess the impact of enriching survival models with features extracted from topological data analysis (TDA). Using a clinical dataset on lung transplantation, we compared the Cox model, random survival forests (RSF), and the DeepSurv deep neural network, along with their TDA-enriched versions. TDA uses persistent homology and generates descriptors that capture the global and multiscale structures present in the data that do not appear in Euclidean spaces. The results show that integrating these descriptors improves predictive performance, increasing the C-index and enhancing risk discrimination. Thus, the integration of TDA and ML emerges as a promising alternative for modeling survival in complex biomedical data. © IFIP International Federation for Information Processing 2027.