EM Normandie

Founded in 1871 as one of the first major French business schools, EM Normandie is a member of the Conférence des Grandes Écoles and stands out in the very closed circle, worldwide, of the 1% of institutions doubly accredited by EQUIS and AACSB. It is also in the Top 80 of the Financial Times and QS international rankings.

It is located on six campuses (Caen, Le Havre, Paris, Dublin, Oxford and, from September 2022, Dubai) and brings together a community of 5,800 students and 21,500 members of its Alumni EM Normandie association.

Through a wide portfolio of training courses (Grande Ecole Program, Bachelor International Management, BBA, MS, MSc), it offers an enhanced learning experience to help the generations of yesterday, today and tomorrow to become actors of a sustainable world, free to think, free to learn and free to create.

The academic and applied research activities of EM Normandie are grouped together within the Laboratoire Métis.

Vidéos récentes de cette institution

03:57
Virtual influencers are 100% Computer Generated Influencers created by AI and 3D artists. These virtual influences can model, sing, and even interact with fans—without ever existing in real life. Despite the risks of virtual influencers (e.g., lack of authenticity, ethical and transparency concerns, etc.), they represent enormous opportunities for brands.
ZAMAN Mustafeed - EM Normandie |
03:47
Recently, ensemble-based machine learning models have been widely adopted and have demonstrated their effectiveness in bankruptcy prediction. However, these algorithms often function as black boxes, making it difficult to understand how they generate forecasts. This lack of transparency has led to growing interest in interpretability methods within artificial intelligence research. In this paper, we assess the predictive performance of Random Forest, LightGBM, XGBoost, and NGBoost (Natural Gradient Boosting for probabilistic prediction) on French firms across various industries, with a forecasting horizon of one to five years. We then apply Shapley Additive Explanations (SHAP), a model-agnostic interpretability technique, to explain XGBoost, one of the best-performing models in our study. SHAP highlights the contribution of each feature to the model’s predictions, enabling a clearer understanding of how financial and macroeconomic factors influence bankruptcy risk. Moreover, it allows for the explanation of individual predictions, making black-box models more applicable in credit risk management.
NGUYEN Hoang Hiep - EM Normandie |
03:48
This research explores Corporate Environmental Responsibility (CER) in emerging economies, focusing on Peru and Chile. Climate change is reshaping businesses, but these economies face unique challenges. The study used fuzzy-set qualitative comparative analysis to examine 500+ companies and their motivation to invest in CER.
RUBINOS Cathy - EM Normandie |
03:06
Drawing from women's testimonials in The Guardian and from contributions of feminist writers, Virginia Woolf, Julia Kristeva, and Margaret Mead, we start a conversation on the positive and energizing aspects of menopause in the workplace. We propose a social interpretation of menopause that challenges a pervasive perspective of medical decline: A theorization of “the dialectic of zest,” as inspired by the writings of Margaret Mead. By problematizing the experiences of women going through this transition in the workplace, we reveal how well-intentioned awareness campaigns can lead to further stigmatization. We thus encourage organizations to not only favor an approach of “education for all” but also extend their social imaginaries beyond medicalized perspectives and coping views.
QUENTAL Camilla - EM Normandie |

Podcasts récents de cette institution

Virtual influencers are 100% Computer Generated Influencers created by AI and 3D artists. These virtual influences can model, sing, and even interact with fans—without ever existing in real life. Despite the risks of virtual influencers (e.g., lack of authenticity, ethical and transparency concerns, etc.), they represent enormous opportunities for brands.
ZAMAN Mustafeed - EM Normandie |
Recently, ensemble-based machine learning models have been widely adopted and have demonstrated their effectiveness in bankruptcy prediction. However, these algorithms often function as black boxes, making it difficult to understand how they generate forecasts. This lack of transparency has led to growing interest in interpretability methods within artificial intelligence research. In this paper, we assess the predictive performance of Random Forest, LightGBM, XGBoost, and NGBoost (Natural Gradient Boosting for probabilistic prediction) on French firms across various industries, with a forecasting horizon of one to five years. We then apply Shapley Additive Explanations (SHAP), a model-agnostic interpretability technique, to explain XGBoost, one of the best-performing models in our study. SHAP highlights the contribution of each feature to the model’s predictions, enabling a clearer understanding of how financial and macroeconomic factors influence bankruptcy risk. Moreover, it allows for the explanation of individual predictions, making black-box models more applicable in credit risk management.
NGUYEN Hoang Hiep - EM Normandie |
This research explores Corporate Environmental Responsibility (CER) in emerging economies, focusing on Peru and Chile. Climate change is reshaping businesses, but these economies face unique challenges. The study used fuzzy-set qualitative comparative analysis to examine 500+ companies and their motivation to invest in CER.
RUBINOS Cathy - EM Normandie |
Drawing from women's testimonials in The Guardian and from contributions of feminist writers, Virginia Woolf, Julia Kristeva, and Margaret Mead, we start a conversation on the positive and energizing aspects of menopause in the workplace. We propose a social interpretation of menopause that challenges a pervasive perspective of medical decline: A theorization of “the dialectic of zest,” as inspired by the writings of Margaret Mead. By problematizing the experiences of women going through this transition in the workplace, we reveal how well-intentioned awareness campaigns can lead to further stigmatization. We thus encourage organizations to not only favor an approach of “education for all” but also extend their social imaginaries beyond medicalized perspectives and coping views.
QUENTAL Camilla - EM Normandie |

Plus de vidéos / podcasts de

Auteurs de cette institution