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Beyond Theory – Embedding Practice into KM Research�How a Unique Professor-Practitioner Alliance Led to Breakthrough Publications

Who are we?

The Research-Practice Gap

Results

Challenges

Needs

Example

Outcome

Lessons learned

Call to action

Ginetta

Luna

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Ginetta Gueli�Short Bio

  • Seasoned Program & Project Manager focused on Knowledge Management, Digital Transformation and Learning.
  • International experience across business & NGO sectors – from SMEs to corporates (BCG, IOM/UN, ITA Airways (ex Alitalia,etc.).
  • Guest Lecturer – Knowledge Management Foundations course, Tor Vergata University (Rome, Italy).
  • KM Lobby Show - Executive Producer & Podcaster @ PKS.
  • Member of key knowledge-sharing communities – KM4Dev, SIKM Leaders, Dutch CoP.
  • Motto: "Being educated does not mean remembering all the concepts, but knowing where to look for them” - Umberto Eco

​

Senior Program and Project Manager &

Knowledge Manager

Beyond Theory – Embedding Practice into KM Research | Gueli-Leoni

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Luna Leoni�Short Bio

  • Associate Professor in Management – Tor Vergata University of Rome - Italy
  • Vice Coordinator of the Master in Economics and Management of Tourist and Cultural Activities – MEMATIC
  • Courses: Management of Creative Firms & Knowledge Management Foundations
  • Board Member of RESER – European Association for Research on Services

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The Research-Practice Gap:�how to «solve» it

    • Challenge: Scholars are often disconnected from practical realities.
    • Need: Stronger integration between universities and KM practitioners.
    • Example: Ginetta & Luna (i.e., how we met and how we continued our collaboration over the years)

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Results

    • Goals: Exploration of the reasons for integrating AI into KM processes and its potential opportunities/challenges
    • Outputs: Publication of articles in scientific and professional journals
    • Contributions: Pushing the frontier of KM by showing how AI-infused KM processes can reshape how knowledge is created, shared, and leveraged in organizations
    • Implications of Research–Practice Integration: i) cutting-edge research can feed directly into practical decision support systems, narrowing the gap between academic insights and enterprise deployment; ii) providing actionable levers for managers through which interventions translate into outcomes; iii) encouraging a two-way dialogue where practice problems refine research questions and research findings guide operational improvements.

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    • Enhancing Interpersonal Skills: Mutual trust, empathy, and open communication became the foundation of effective collaboration.
    • Synthesising Research and Practice: Combining theoretical rigor with practical relevance created richer, evidence-based knowledge.
    • Communicating Scientific Knowledge: We refined how to make complex KM concepts accessible to practitioners and decision-makers.
    • Bridging Policy and Science: We learned to translate academic insights into actionable strategies supporting organizational and policy decisions.

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  • Collaborate: Build bridges between academia, industry, and communities.
  • Apply Research: Transform insights into tangible KM practices.
  • Empower Groups: Encourage collective learning and co-creation.
  • Enhance Impact: Use evidence to drive smarter, knowledge-based decisions.

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AI statement and References

An artificial intelligence tool (i.e., ChatGPT) was used to create some of the illustrative images included in this presentation. The use of AI was limited to visual generation, while all conceptualization, analysis, and interpretation were carried out by the authors.

    • Leoni L., Gueli G. (2025), AI-empowered knowledge management (KM) processes: what effects on decision-making?, RealKM Magazine, https://realkm.com/2025/01/08/ai-empowered-knowledge-management-km-processes-what-effects-on-decision-making/
    • Leoni, L., Gueli, G., Ardolino, M., Panizzon, M., & Gupta, S. (2024). AI-empowered KM processes for decision-making: empirical evidence from worldwide organisations. Journal of Knowledge Management, 28(11), 320-347.
    • Ardolino, M., Bacchetti A., Leoni L., Gueli G. (2023). Il knowledge management a supporto dell’AI per migliorare le performance delle aziende manifatturiere, AI4Business – Digital360. Disponibile al link: https://www.ai4business.it/intelligenza-artificiale/il-knowledge-management-a-supporto-dellai-per-migliorare-le-performance-delle-aziende-manifatturiere/
    • Leoni, L., Ardolino, M., El Baz, J., Gueli, G., & Bacchetti, A. (2022). The mediating role of knowledge management processes in the effective use of artificial intelligence in manufacturing firms. International Journal of Operations & Production Management, 42(13), 411-437.
    • Leoni L., Ginetta G. (2022), Interested in AI to improve your manufacturers’ performance and resilience? KM processes are what you need!, RealKM Magazine. Disponibile al link: https://realkm.com/2022/12/03/interested-in-ai-to-improve-your-manufacturers-performance-and-resilience-km-processes-are-what-you-need/
    • Leoni L., Gueli, G. (2021), The impact of digital transformation on knowledge management processes, Proceedings of the 31st RESER Conference “The disruptive role of AI, data and ecosystems in services”, Heilbro (Germany, virtual), Fraunhofer IAO press, 14-15 October 2021. Doi: 10.24406/publica-fhg-412936

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Thank you!

Profilo Linkedin: https://www.linkedin.com/in/ginetta-gueli-7800306/

Profilo Linkedin: https://www.linkedin.com/in/lunaleoni/