Mission of the Research Centre

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.

Our Publications

Our Contributions To Debates