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Innovating Manufacturing Business Models Through Digital and AI-Driven Transformation: Insights from the Modapto Project

From June 24th to 28th, the 30th ICE/IEEE ITMC Conference in Madeira, Portugal served as an exceptional platform for showcasing state-of-the-art research as part of the Madeira Digital Transformation Week. This event brought together five major events: the 30th ICE/IEEE ITMC Conference, the 2nd edition of the Madeira Digital Transformation Summit, the EIT Health Transformation Talks, the CyberSecPro Summer School, and the NITIM Graduate School.  

Among the many influential presentations was the paper titled “Innovation in Manufacturing Business Models Enabled by Digital and AI-Driven Transformation,” presented by Timoleon Farmakis, a researcher at ELTRUN, The E-Business Research Center of the Athens University of Economics and Business (AUEB) partner in the MODAPTO project. 

This research explores the transformative potential of digital and AI-driven technologies in manufacturing business models, proposing a conceptual framework that assists manufacturers in innovating their business models.  

Key Highlights of the Research:

  1. Transformative Potential: The research explores how digital and AI-driven technologies can impact manufacturing business models, making them more efficient and innovative.
  2. Operational Efficiency: It highlights the ways these technologies can streamline operations, reduce costs, and increase productivity.
  3. Support for Digital Transformation: It examines the role of these technologies in supporting broader digital transformation initiatives, crucial for maintaining competitive advantage in today’s fast-paced industrial landscape.

Co-Authors of the Research:

  • Stavros Lounis (ELTRUN, AUEB, Greece)
  • Ioanna Georgoutsou (ELTRUN, AUEB, Greece)
  • Anastasios Koukopoulos (ELTRUN, AUEB, Greece)
  • Yiannis Mourtos (ELTRUN, AUEB, Greece)

This publication forms a part of the MODAPTO project’s business and exploitation tasks, informing the industrial strategies implemented in relevant tasks.

For more detailed information on this research and to access the full paper upon publishing, please contact Timoleon Farmakis at timoleonfarmakis@aueb.gr or Stavros Lounis at slounis@aueb.gr.

Stay tuned for more updates and insights from the MODAPTO Project!