This report presents the updated Targeted Skills Framework (TSF v1.1) developed as part of the DIGI-ME project, which aims to enhance business master’s programs with relevant digital competencies and skills. It responds to the increasing need for business education to evolve in light of digital transformation and shifting labour market expectations.
The report identifies the core challenges business programs face in adapting to these changes and outlines the rationale for integrating digital elements into their curricula. A revised methodology for developing the TSF v1.1 is presented, combining empirical data from multi-stakeholder workshops, a systematic literature review, and needs analysis. This methodological refinement supports the development of TSF v1.1. The framework includes four interlinked components: managerial competencies, digital competencies, proficiency levels, and emerging technologies. Each is grounded in evidence and supported by extensive data included in the annexes.
TSF v1.1 serves as a robust foundation for building digital capability within business education and provides practical guidance for educators, program designers, and institutional leaders.
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Authors: Valentina Beretta, Enrico Cotta Ramusino, Maria Chiara Demartini, Emanuel Bagna
DOI: https://doi.org/10.1016/j.irfa.2025.104375
Abstract: This study adopts a bibliometric and content analysis to investigate extant literature on the link between sustainability and M&A. Findings from the analysis of 96 papers show that the extant literature is fragmented and interdisciplinary, with many authors from Chinese and Australian institutions analysing primarily Chinese and US firms. Preferred outlets either are in the field of general management or specialized in finance. From a methodological perspective, quantitative studies represent by far the majority of the analysed sample. Several avenues for further research are addressed.
Keywords: M&A, Sustainability, Bibliometric, Performance analysis, Science mapping
Link to the article: https://www.sciencedirect.com/science/article/pii/S1057521925004624
Authors: Valentina Beretta, Maria Chiara Demartini, Eugenia Parodi, Francesco Sotti
DOI: https://doi.org/10.1016/j.ribaf.2026.103644
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Link to the article: https://www.sciencedirect.com/science/article/pii/S0275531926003740.
Authors:
Maria Chiara Demartini, Daniela Quintanilla Segovia, Eugenia Parodi, Elisa Maccagni, Dmitrii Gribovskii, Sniazhana Diduc, Rumy Narayan, Adam Smale, Claire Stead, Federico Pigni
DOI: 10.1109/ICIR70631.2026.11628115
Abstract: As Artificial Intelligence (AI) and digital technologies rapidly transform organizations and education, aligning university curricula with future workforce needs has become increasingly urgent. This study examines which digital and managerial competencies professionals will need, how emerging technologies will shape those demands, and how well current higher education programs respond to them. Using a qualitative workshop approach with academic and industry participants. Preliminary results suggest that soft skills such as leadership, communication, adaptability, and continuous learning, remain central, while technologies like AI, digital twins, and quantum computing will significantly reshape professional roles. The analysis reveals that while existing programs show strengths in digital management, notable gaps persist in soft skills, experiential learning, and advanced AI-related competencies. This analysis aims to offer a practical framework to help institutions redesign curricula in line with evolving labour market expectations and needs.
Keywords: digital competencies, managerial competencies, curriculum design, higher education institutions, emerging technologies
Link to the article: https://ieeexplore.ieee.org/document/11628115
Authors: Mohamed Amir Omezzine, Federico Pigni, Lucia Billeci
DOI:10.1109/ICIR70631.2026.11628346
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Artificial intelligence, immersive XR/VR environments, and wearable sensing technologies are increasingly converging in education. However, most adaptive learning systems still rely on behavioral and performance indicators such as correctness, completion, response time, and help-seeking. These indicators are useful but often too coarse to capture the cognitive and affective conditions under which learning unfolds. This paper develops a design-oriented framework for a State-Aware Digital Twin (SADT), defined as an instrumented XR/VR task environment in which adaptive decisions are conditioned on confidence-scored evidence about learner state. Grounded in Information Systems research, Flow Theory, Cognitive Load Theory, and NeuroIS, the framework specifies a five-layer architecture linking XR task telemetry, behavioral traces, wearable sensing, a state engine, and a bounded-action orchestrator. The paper contributes a conservative-adaptation principle, a reference architecture, and a staged validation protocol for testing when multimodal sensing adds intervention value beyond behavioral logs and XR telemetry.
Keywords: Learning (artificial intelligence), Printing, Extended reality, Timing, Fluid flow, Loading, Design methodology, Cognitive load, Architecture, Artificial intelligence
Link to the article: https://ieeexplore.ieee.org/document/11628346
Authors: Rumy Narayan, Sniazhana Diduc
DOI:10.1109/ICIR70631.2026.11628234
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Business schools confront a compounding crisis of formation. Curricula anchored in bounded-firm ontologies produce graduates who are analytically competent yet structurally unprepared for the architectural complexity of platform-mediated digital ecosystems. Compounding this, the integration of artificial intelligence as an ambient reasoning partner produces conditions for cognitive surrender, the uncritical adoption of AI outputs accompanied by inflated confidence and reduced metacognitive monitoring. We sharpen the construct of cognitive surrender against the related but distinct phenomena of automation bias and algorithm aversion, and we identify its proximate mechanism in what cognitive linguists have recently theorized as the deferential hazards of generative AI design. We argue that the ontological and cognitive crises share a single epistemological root in management education's treatment of knowledge as the stable possession of bounded agents. Drawing on the DIGI-ME Targeted Skills Framework (TSF), built on the DigComp 2.2 architecture, we propose that competencies of reflective trust, hybrid agency, and ethical situatedness constitute foundational preconditions for leadership formation, and we translate these competencies into concrete curricular instruments. We close with limitations and an empirical research agenda anchored in the DIGI-ME consortium.
Keywords: management education, cognitive surrender, digital competence, leadership formation, algorithmic agency, DigComp, deferential hazards
Link to the article: https://ieeexplore.ieee.org/document/11628234
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DOI:10.1109/ICIR70631.2026.11628234
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The increasing digitalization of labour markets and organizational environments requires higher education institutions to strengthen students' digital competencies through innovative pedagogical approaches. This study examines how different instructional environments, traditional learning formats and immersive virtual reality-based experiences, may influence digital competency development among students and alumni of the Master in International Business and Entrepreneurship (MIBE) at the University of Pavia. An exploratory quasi-experimental single-group pre-test/post-test design was adopted, in which participants sequentially experienced a traditional face-to-face job interview with human resource professionals and an immersive virtual reality interview supported by AI-mediated feedback and reflective coaching. Digital competencies were assessed through the seven dimensions of the Targeted Skills Framework (TSF). Descriptive findings suggest overall improvements in self-perceived digital competencies, particularly in digital self-development and reflective practice, digital content creation, information and data literacy, problem solving, and emerging technology integration, while communication and collaboration remained relatively stable. The findings indicate that traditional and immersive instructional environments may contribute to digital competency development in complementary ways within management education. The study contributes to the literature by adopting a competence-oriented and comparative approach to examine digital competency development in higher education and provides preliminary evidence supporting the pedagogical value of immersive and AI-mediated learning experiences.
Keywords: Digital competences, Higher education, Immersive learning, Virtual reality, Competence development, Management education
Link to the article: https://ieeexplore.ieee.org/document/11628437
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Abstract: The rapid pace of digital transformation demands that higher education institutions (HEIs) equip business graduates with targeted, relevant, and adaptable digital competencies and skills. Yet curricula in many business programs remain too static, homogeneous, and insufficiently informed by a structured understanding of which digital skills truly matter. This paper presents the methodology developed by the EU co-funded project – DIGI-ME project to identify and classify targeted digital competencies and skills for business master's students, and introduced the first iteration of the Targeted Skills Framework (TSF v1.1). Drawing on a multi-stage process that combines systematic literature review, expert interviews, and participatory design, the TSF articulates a taxonomy of digital competencies and skills mapped to program-level learning outcomes. We position this work within critical debates on AI and education, arguing that personalized, evidence-based skill identification is a necessary counterweight to the reductive logics that currently dominate educational discourse. The TSF is designed to be institutionally agnostic, portable across European HEIs, and compatible with lifelong learning certification pathways.
Keywords: Artificial intelligence, Technology, Business, Modeling, Programming, Design methodology, Learning (artificial intelligence), Printing, Tools, Conferences
Link to the article: https://ieeexplore.ieee.org/document/11628132
Authors:
Abstract: Intelligent Tutoring Systems are widely recognized as key tools for supporting personalized learning; however, their effective integration in school settings largely depends on teachers' acceptance and adoption. This paper presents an evaluation of ATLAS platform, an adaptive ITS designed to support competence-based learning and higher-order skills such as critical thinking. Using a mixed-methods approach, the study combines quantitative measures of usability, perceived usefulness, and intention to use with qualitative analyses of teachers' comments collected after a training experience with the system. Results showed an overall positive evaluation of ATLAS across all measured dimensions, indicating that teachers perceive the system as usable and having pedagogical potential for instructional practice. Qualitative findings further highlight adaptive mechanisms, scaffolding, and automatic exercise generation as key strengths, while also identifying challenges related to interface clarity, accessibility, and classroom integration. Building on these results, the paper discusses design implications for the development and adoption of ITSs in school contexts, emphasizing the importance of teacher-centered design, transparency of adaptive features, and alignment with instructional practices when targeting complex competencies.
Keywords: Intelligent Tutoring Systems, Personalized Learning, Teacher-Centered Design, Critical Thinking
Link to the article: https://ieeexplore.ieee.org/document/11628132
Authors:
Abstract: AI tools and wearable devices are a widely explored topic in educational context. These tools can be combined to propose a personalized educational pathway for students. The DIGI-ME project aims to profile the students from a multimodal perspective to provide them a personalized educational offer. An online platform was developed to assess students' psychological profile, job ambition, and digital skills proficiency through validated psychological questionnaires and external online tools. Moreover, an in-person measurement session was conducted, in which the students were subjected to two stressful tasks: the Montreal Imaging Task System (MIST) and a public speaking session. During the sessions, wearable sensors were used to collect physiological signals. A greedy algorithm computed the affinity between students and mentors and assigned a mentor to each student. Cosine similarity and Word Movers' Distance (WMD) were used to compare students and course descriptions. Finally, we used the Large Language Model (LLM) Mistral to generate customized explanations for the student-course affinity. The preliminary results showed the feasibility of providing personalized suggestions for students. A future step will be the evaluation of the effect of personalization on learning and psychophysiological wellbeing.
Keywords: education, biometrics,artificial intelligence,personalization,LLMs
Link to the article: https://ieeexplore.ieee.org/document/11628122
