Research Center
Artificial Intelligence and Decision Making

Mission of the Research Center


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

Events
Regular seminar series, held monthly, featuring guest speakers from Information Systems, Operations Management, Marketing, and Finance.

Events
International Society of Inventory Research (ISIR) summer school, with a specific emphasis on AI in Supply Chain Management.

Events
Regular internal seminar series, held every two weeks.

Research Center
Artificial Intelligence and Decision Making

Our people


Director:

Yacine Rekik, Information & Operations Management (Paris)

Yacine Rekik
Information & Operations Management(Paris)

Permanent Faculty:

Researchers:

  • Thu-Quynh Mai
    PhD(Paris)
Research Center
Artificial Intelligence and Decision Making

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 (Lidl, REI, Aldi, Tesco, Auchan, Iceberg, MegaImage, Sainsburys, Primark) 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.
Research Center
Artificial Intelligence and Decision Making

Our Publications


Machine Learning Methodology for Business Studies
Kahalé. N.

2023

Unbiased time-average estimators for Markov chains. Mathematics of Operations Research.

Published Online

Zhong, H., Chen, Y., Liu, C. and Benson, H.

2023

Decision Aggregation with Reliability Propagation

Decision Support Systems

Kahalé. N.

2022

On the effective dimension and multilevel Monte Carlo.

Operations Research Letters, vol 50, 415-421

Maliar, L., Maliar, S. and Winant, P.

2022

Deep Learning for Solving Dynamic Economic Models

vol 122, 76-101

Kahalé. N.

2020

Randomized Dimension Reduction for Monte Carlo Simulations.

Management Science, vol 66, 1421-1439

Kahalé. N.

2020

General multilevel Monte Carlo methods for pricing discretely monitored Asian options.

European Journal of Operational Research, vol 287, 739-748

Kahalé, N.

2019

Efficient simulation of high dimensional Gaussian vectors

Mathematics of Operations Research, vol 44, 58-73

Zhong, H., Liu, C., Zhong, J. and Xiong, H.

2018

Which Startup to Invest in: A Personalized Portfolio Strategy

Annals of Operations Research

Applications of Language Model in Organization
Bick, M., Breaugh, J., Dong, C., Pina, G., and Waldner, C.

2023

AI and the future of academic writing: Insights from the ESCP Business School Prompt-o-thon workshop in Berlin.

ESCP Impact paper.

Dong, C., Saxena, A., Bick, M. and Sabia, A.

2023

On the Journey to AI Maturity: Understanding the Role of Enterprise Artificial Intelligence Service.

AIS Transactions on Enterprise Systems, vol 6.

Liang, Y., Liu, Wl, Li, K., Dong, C., and Lim, M.

2023

A co-opetitive game analysis of platform compatibility strategies under add-on services.

Production and Operations Management, forthcoming.

Dong, C., Bharambe, S. and Bick, M.

2022

Why Do People Not Install Corona-Warn-App? Evidence from Social Media. In: Themistocleous, M., Papadaki, M. (eds) Information Systems. EMCIS 2021.

Lecture Notes in Business Information Processing, vol 437. Springer, Cham

Analytics for Better Business Decision Making
Vafainia, S., Rooderkerk, R. Breugelmans, E., & Bijmolt, T.

2024

Decision support system development for store flyer space allocation: Leveraging own- and cross-category flyer space effects.

International Journal of Marketing Research

Tran M.T., Rekik, Y. and Hadj-Hamou, K.

2024

Optimal pricing for dual-channel retailing with stochastic attraction demand model, vol 268, 109127

International Journal of Production Economics

Fathizadeh, F., Savinien, J. and Rekik, Y.

2024

Fuzzy Gaussian mixture optimisation of the newsvendor problem: mixing fuzzy perception and randomness of customer demand.

International Journal of Production Research, vol 61 (10), 3459-3480

Ren, X., Gong, Y., Rekik, Y. and Xu, X.

2023

Anticipatory shipping versus emergency shipment: data-driven optimal inventory models for online retailers

International Journal of Production Research, 2548-2565

Yang, B., Xu, X., Gong, Y. and Rekik, Y.

2023

Data-driven optimization models for inventory and financing decisions in online retailing platforms.

Annals of Operations Research, 1-24

Rekik, Y., Glock, Ch., and Syntetos, A.

2023

Grow sales by 4-8% by improving Inventory record accuracy, ECR white paper.

ECR Shrink Group (ecrloss.com)

Innovation and Management of Disruptive Technologies
Li, Q., Rekik, Y. and Hadj-Hamou, K.

2024

Agricultural production optimization: the impacts of agricultural cooperative and blockchain-based information sharing.

24ème Congrès annuel de la Société Française de Recherche Opérationnelle

Li, Q., Hadj-Hamou, K., and Rekik, Y.

2024

The formation of cooperatives with the implications of information sharing and contract farming.

International Journal of Production Research

Pelé, P., Schulze, J., Piramuthu, S. and Zhou, W.

2023

IoT and blockchain based framework for logistics in food supply chains.

Information Systems Frontiers 25 (5), 1743-1756

Li, L., Tang, O., Zhou, W. and Fan, T.

2023

Backroom effect on perishable inventory management with IoT information.

International Journal of Production Research 61 (12), 4157-4179

F Pan, S Pan, W Zhou, T Fan

2022

Perishable product bundling with logistics uncertainty: Solution based on physical internet.

International Journal of Production Economics 244, 108386

Research Center
Artificial Intelligence and Decision Making

Our Contributions To Debates


Impact Papers
Bick, M., Breaugh, J., Dong, C., Pina, G., & Waldner, C.

2023

AI and the future of academic writing: Insights from the ESCP Business School Prompt-o-thon workshop in Berlin

ESCP Impact paper

Benyayer L.D., & Zhong H.

2023

Embracing AI-human collaboration: The key to unlocking new sources of competitive advantages

ESCP Impact paper

Vafainia, S.

2023

Deep learning: a game changer for marketing analytics. Or is it?

ESCP Impact paper

Press(recent contributions)
Benyayer L.D., & Zhong H.

2023

AI-human collaboration can unlock new sources of competitive advantage

LSE Business Review

Zhong H.

2023

Generative artificial intelligence: how do we mitigate the extreme risks?

The Choice by ESCP

Zhong H.

2023

Intelligence artificielle : qui sortira vainqueur de la bataille géopolitique ?

Les Echos

Desmichel, P., Maggioni, I., Vafainia S.

How companies can turn NFTs into useful tools

LSE REVIEW

Vidéos & Podcasts