Εργαστήριο Ηλεκτρονικού Εμπορίου και Ηλεκτρονικού Επιχειρείν
e-Business Research Center | ELTRUN

ELTRUN is the E-Business Research Center of the Athens University of Economics and Business (AUEB) and belongs to the Department of Management Science and Technology. The center was established by Prof. Doukidis in 1994 and currently consists of more than 40 researchers, including 6 members of the academic staff of AUEB and 15 Post-Doc and academic staff of other Institutions.

Through the years, ELTRUN has successfully managed to produce state-of-the-art research and to complete more than 40 international research projects some of them funded by the Information Society and Technologies Program of the European Commission.

 

The center is actively involved in commercial projects and executive education programs to solve difficult real-life problems with the support of ICTs, various activities that are intended to increase awareness in the fields of E-Business, Digital Transformation, Industry 4.0, Innovation and Entrepreneurship, eCommerce and Big Data. ELTRUN supports scientifically the Athens Center for Entrepreneurship and Innovation (ACEin) of AUEB.

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Research Projects

Research Groups

[AID] Artificial Intelligence and Digital Transformation

Scientific Coordinator

Professor George I. Doukidis

Co – Head

Dr. Anastasia Griva

RESEARCH STREAMS

 

  • Explainable AI (XAI) 
  • AI fairness and transparency
  • Generative AI (GAI)
  • Business value of AI
  • Responsible use, design and regulation of AI
  • AI and new business model creation
  • Digital Transformation for businesses
  • Digital Readiness and Small enteprises
  • Emerging Technologies, Projects and Digital Transformation
  • Intelligent Decision Making

RESEARCH OBJECTIVES

  • Examination of responsible use, design and regulation of AI with an emphasis on the role of explainable AI (XAI).
  • AI-driven value creation in contemporary organizations.
  • AI for business model innovation and transformation with an emphasis on identifying opportunities for disruptive AI-driven business strategies.
  • Identification of the factors influencing the adoption and scalability of AI solutions in businesses.
  • Generative AI (GAI) and its impact on organizations.
  • Investigation of techniques to control and guide the generation process in GAI systems in a user-defined manner.
  • Examination of digital transformation’s complex and varied aspects across different industries and business scales.
  • Digital transformation and emerging technologies.
  • Digital transformation frameworks for SMEs and Large organizations.
  • Integration of AI techniques in Decision Support Systems

[ADOPT] Advanced Manufacturing & Optimisation

ELTRUN Director &
Scientific Coordinator

Professor Yiannis Mourtos

Co – Head

Dr. Georgios Zois

RESEARCH STREAMS

  • Matchings and allocations under preferences, mostly focusing on stable b-matchings, Pareto b-matchings and Pareto-allocation
  • Applications of matchings under preferences to mechanism design especially in B2B settings
  • Polyhedral combinatorics and integer programming, mostly focusing on multi-index assignment problems and  multiple all-different predicates
  • Optimisation and digitisation of manufacturing, productivity analysis and performance evaluation
  • Production Planning and Scheduling under single or multiple objectives, including flow/job-shop and parallel machine scheduling environments.
  • Location and routing optimisation under various objectives in last-mile and middle mile transportation settings.

RESEARCH OBJECTIVES

  • Structural properties for key problems combinatorial optimisation, mainly but not exclusively in the form of polyhedral analysis.
  •  Design of optimisation methods for real-life combinatorial problems, focusing on: a) exact algorithms based on decomposition techniques, mostly focused on Benders Decomposition and its more recent variants, b) fast heuristics with proven performance guarantee, e.g., based on integer programming relaxation, which partly exploit the structural properties of the problem in hand, c) meta-heuristics for large-scale instances, including single-solution-, population- and RL-based techniques.
  • Development of optimisation software, normally problem-specific but with an emphasis on components that remain transferrable within broad problem classes.
  • Applying optimisation tools and services as part of Digital Twins in real-life settings for decision support, relying on well-structured user requirements while accompanying technologies for monitoring and data analytics.

[DIMER] DIgital Marketing and Electronic Retailing

Scientific Coordinator

Professor Adam Vrechopoulos 

Co – Head

Dr. Chris Lazaris 

RESEARCH STREAMS

  • Consumer-User Behaviour
  • Omnichannel Retailing
  • Integrated Marketing Communications
  • Digital Technologies and Marketing Research
  • Strategic Marketing in a Digital World
  • Customer Relationship Management (CRM)
  • Digital Technologies and Sales

RESEARCH OBJECTIVES

The research group conducts basic and applied research in the context of Digital Marketing and Electronic Retailing through an interdisciplinary approach (i.e., Marketing, Information Systems and Electronic Commerce).

[DAG] Data Analytics Group

Scientific Coordinator

Professor George Lekakos

Co – Head

Dr. Dimitris Papakyriakopoulos

RESEARCH STREAMS

  • Recommender Systems algorithms
  • Persuasive Systems
  • Big Data Analytics (BDA) and BDA Management for competitive advantage
  • FinTech applications design
  • User-centric Interaction and Interface design
  • E-commerce and e-government
  • IoT applications
  • Diagnostic and Predictive Analytics 
  • Augmented Analytics 
  • Text analytics and Natural Language Processing 
  • Latent models 
  • Data democratization
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RESEARCH OBJECTIVES

  • Design new hybridization techniques for personalization algorithms
  • Develop new models for building Competitive Advantage for the Data-Driven Enterprise
  • Design consumer services enhanced with intelligent features in support of consumer’s daily living
  • Design new types of personalized multimodal interfaces based on Artificial Companions Technology
  • Build omnichannel customer experience based on personalized recommendations through interactive tools in physical environment (eg smart mirrors in physical retail stores) and online (eg chatbots, personal assistants)
  • Develop persuasive models and persuasive messages based on communication and information theories
  • Application of Deep Neural Networks in recommendation architectures achieving high recommendation quality and aiming at better customer satisfaction.
  • Implementation of persuasive technologies in recommendation systems based on user-centric characteristics
  • Developing models for real-time recommendation engines
  • Utilization of data sources to enhance business value
 

[INTENT] Innovation and Entrepreneurship Group

Scientific Coordinator

Professor Katerina Pramatari

Co – Head

Dr. Angeliki Karagiannaki

RESEARCH STREAMS

  • Innovation and Technology Entrepreneurship
  • Technology Transfer
  • Entrepreneurial Innovation Ecosystems
  • Entrepreneurship Education and the Entrepreneurial University
  • Open Innovation
  • Information Systems and Technology Entrepreneurship
  • Innovation for Environmental and Social Impact
  • Electronic Services and User Engagement
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RESEARCH OBJECTIVES

  • Assessing the business value of innovative technologies and technology entrepreneurship
  • Fostering entrepreneurial skills and the role of universities in nurturing entrepreneurship
  • Development of entrepreneurial innovation ecosystems
  • Research commercialization, with a specific focus on understanding the impact of Proof-of-Concept initiatives in transforming research outcomes into practical applications and marketable products.
  • Investigating the Dynamics and Impact of Open Innovation through Industry-University Collaboration
  • Understanding the drivers and barriers in facilitating the successful transfer of technology from research to practical applications
  • Exploring Impact-Driven Entrepreneurship and Assessment to measure and analyse the multifaceted impacts generated by entrepreneurial endeavors
  • Analysing Digital Entrepreneurship with a focus on the development of electronic services 

ISTLab - Information Systems Technology Laboratory

(Affiliated DMST Lab)

Scientific Coordinator

Professor Nancy Pouloudi

ISTLab Director &
Scientific Coordinator

Professor Angeliki Poulymenakou

RESEARCH STREAMS

  • Social, organizational and political aspects of ICTs: virtual communities, electronic collaboration, inter-organizational networks, and e-goverment
  • Information systems: analysis, development and adoption
  • Design, management and evaluation of enterprise technolgies: e-Learning, knowledge management, and enterprise resource planning systems
  • Mobile, Wireless, and Sensor-based Computing: Applications and Services, Business Models
  • Pervasive and Ubiquitous Information Systems: Design, Analysis, and Technology Acceptance

RESEARCH OBJECTIVES

  • Assessing the organizational and societal impact of ICTs
  • Use of mixed-methods in the study of information systems
  • Information systems and work-life balance
  • Personal and organizational impact of cloud computing adoption
  • Consumerized IT devices
  • Impact of ICT use in the public sector
  • Digital transformation and IT-enabled change

ELTRUN at a glance