Artificial Intelligence and Decision Making – AI&DM
Mission of the Research Centre
The mission of our research center is the creation and dissemination of research on Artificial Intelligence and data-driven decision making for improving the productivity, sustainability, and security of organizations, and gaining strategic advantage in today’s digital economy and data-driven world. This includes both methodological and applied research in a broad scope of business management disciplines, such as Operations Management, Finance, Marketing, and Information Systems. Currently, the research center comprises four research groups:
- Machine Learning Methodology for Business Studies
- Applications of Language Model in Organization
- Analytics for Better Business Decision Making
- Innovation and Management of Disruptive Technologies
Our People
Director
Yacine Rekik
Director ESCP of The Future of European Multinationals (FEM)
Yacine Rekik is a Full Professor of Decision Sciences at ESCP Business School (Paris campus). Prof. Rekik's research focuses on developing models that provide both qualitative and quantitative insights into the digital transformation of supply chains. His work explores topics such as the impact of RFID technology on supply chain performance, examining how it drives cost reduction and enhances service levels. He also investigates omnichannel supply chain strategies and data-driven flow management, leveraging advanced analytics and machine learning to address complex challenges. As an active member of the Efficient Consumer Response (ECR) community, Prof. Rekik is deeply involved in research on Inventory Record Inaccuracy (IRI). He develops algorithmic and data-driven solutions, including machine learning techniques, to tackle this critical issue and optimize supply chain efficiency.
Permanent Faculty
Wei Zhou
Professor
Paris
wzhou@escp.eu
Nabil Kahale
Associate Professor
Paris
nkahale@escp.eu
Yacine Rekik
Professor
Paris
yrekik@escp.eu
Pablo Winant
Professor
Paris
pwinant@escp.eu
Julien Fouquau
Professor
Paris
jfouquau@escp.eu
Chuanwen Dong
Professor
Berlin
cdong@escp.eu
Saeid Vafainia
Assistant Professor
Paris
svafainia@escp.eu
Hao Zhong
Associate Professor
Paris
hzhong@escp.eu
Yuting Gao
Assistant Professor
Madrid
ygao@escp.eu
Mostafa Rezaei
Assistant Professor
Paris
mrezaei@escp.eu
Researchers (PhD students):
- Thu-Quynh Mai, Paris
Our Research Activities
- Machine Learning Methodology for Business Studies
The goal of this research group is to develop new machine learning (ML) methodologies, specifically aimed at supporting business decision-making. Ongoing research projects on this research theme:- L. Maliar, S.Maliar, P.Winant, 2022, Deep Learning for Solving Dynamic Economic Models
- Zhong, H., Yuan Z., Zhang D., Jiang Y., Zhang S. & Xiong H., Unboxing Causation: A Design Instantiation of Causation Theory using Reinforcement Learning on VC Decision-making Processes
- Zhang S., Zhong H., Yong G. & Xiong H., Bring Me a Good One: Seeking High-potential Startups using Heterogeneous Venture Information Networks
- Kahale N., Efficient Monte Carlo methods for Machine Learning
- Applications of Language Model in Organization
This group explores the practical applications of large language models in organizational contexts, with a primary emphasis on enhancing productivity and ensuring safety through adoption, identification of use cases, and alignment methodologies. Ongoing research projects on this research theme:- Mimra, W, Winant P., The risk and social preferences of large language models
- Gao, Y., Hahn, J., The Impact of ChatGPT on People’s Engagement With Online Advice Communities
- Weis, M., Dong, C., and Bick, M. , Firms’ AI Adoption: Challenges and First Remedies
- Analytics for Better Business Decision Making
This research group conducts applied research to explore how AI and ML technologies can improve various facets of business operations, including financial forecasting, demand forecasting, inventory management, marketing strategies, and responses to natural disasters, and security measures. Ongoing research projects on this research theme:- Rezaei, M., Lee, I., & Beverly, J., The effect of wildfire suppression resources: Targeting fire groups with enhanced treatment effect
- Rezaei, M., & Ingolfsson, A., Forecasting to support EMS tactical planning: What is important and what is not
- Rekik, Y.., Application of AI in retailing to cope with inventory inaccuracy, ECR funded project with the implication of 9 major retailers Category | Ecr Shrink Group (ecrloss.com)
- Rekik, Y., Machine learning based models for the omnichannel supply chain
- Mai, T.Q., Zhou, W., Dong, C. and Rekik, Y., Analytical and data-driven models to cope with food waste and loss in supply chains (PhD project of Thu Quynh Mai)
- Fouquau J. & Schoder, A., Impact of environmental news on finance
- Dong, C., Decarbonizing last-mile logistics
- Dong, C., and D., Li., Achieving Economic and Environmental Sustainability with Supply Chain Contracts
- Innovation and Management of Disruptive Technologies
The goal of this research group is to investigate technologies within the realm of business innovation and management that can significantly alter or revolutionize existing markets and industries, such as IoT, blockchain, RFID, sensor network systems, digital twins, and the physical internet. Ongoing research projects on this theme:- Zhou, W., IoT and blockchain based framework for logistics.
- Zhou, W., physical internet to manage perishable product bundling.
- Rekik, Y., use of blockchain technology in the agriculture supply chain.