FNEGE MEDIAS

Épisodes du podcast

Antony, together with his colleagues from NEOMA, presents research conducted with the University of Bristol on how international companies choose countries for sourcing. The concept of "country risk," once focused on economic conditions and political stability, now includes three major sociopolitical factors: populism, which creates regulatory uncertainty; state fragility, which affects suppliers’ ability to deliver; and checks and balances, which can limit but not always prevent political drift. The study, covering 1,300 U.S. companies and their suppliers in 90 countries, shows that these factors directly influence sourcing decisions. Examples like Samsung and H&M illustrate this shift toward countries perceived as more stable. In conclusion, companies must strengthen their geopolitical monitoring to anticipate risks and secure their supply chains.
PAULRAJ Antony - NEOMA Business School |
Our research investigates how management interventions can facilitate user adaptation to new information technology across implementation stages and usage contexts. Drawing on the Coping Model of User Adaptation, we propose a 2×2 coping framework, showing that tailored interventions—such as training, user participation, feedback handling, and change fairness—differently shape users’ beliefs (perceived usefulness and ease of use) and coping mechanisms. Empirical studies in both mandatory (police officers) and voluntary (university students) settings confirm that communal coping dominates in mandatory contexts while individual coping prevails in voluntary ones. Pre-implementation beliefs strongly influence post-implementation perceptions, and deep usage significantly enhances user performance and satisfaction. The study offers theoretical insights into adaptive processes and practical guidance for managers aiming to improve IT implementation success.
YU Nadia-Yin - NEOMA Business School |
Robotic warehouses have transformed logistics, prioritizing speed and efficiency. However, traditional static priority systems often leave low-priority customers facing excessive delays, raising concerns about fairness. This research, based on Invia, a robotic warehouse company, proposes a dynamic priority allocation model to balance efficiency and fairness. By adjusting order priorities over time, this approach ensures that both high-priority and long-waiting low-priority orders receive timely fulfillment. Through stochastic modeling and simulations, we demonstrate that dynamic prioritization reduces delays compared to static and first-come, first-served (FCFS) models. Case studies in e-commerce and healthcare logistics illustrate the broader impact of fairness in automation. As industries increasingly rely on AI-driven decision-making, the balance between efficiency and equity becomes critical. This research challenges the assumption that robotic warehouses should optimize for speed alone and advocates for a future where fairness plays a central role in automated commerce.
YUAN Zhe - EMLV |
Dans un contexte économique sans précédent marqué par une pandémie mondiale, l’entrelacement complexe du discours sur le greenwashing à l’ère des fake news s'est intégré au tissu de la durabilité d’entreprise, remodelant les perceptions des managers et mettant à l’épreuve leur attitude face aux décisions durables. À travers une étude qualitative en deux phases, cette recherche examine l’impact du discours sur le greenwashing sur les perceptions et attitudes des managers vis-à-vis de la durabilité en France après la pandémie. Les résultats révèlent une déconnexion entre le discours externe sur le greenwashing et l’état d’esprit des managers, ces derniers associant souvent les accusations de greenwashing aux « fake news ». De plus, l’étude montre que la pandémie a déplacé l’attention vers les préoccupations financières, reléguant la durabilité au second plan dans la prise de décision stratégique et modifiant ainsi le paysage de la responsabilité d’entreprise. En allant au-delà du cadre habituel centré sur les consommateurs et les clients, cette étude vise à combler un vide critique dans la recherche sur le greenwashing en examinant son impact sur différents acteurs. À travers cette analyse, nous cherchons à contribuer aux recherches sur le discours du greenwashing en offrant une compréhension plus approfondie des complexités et des nuances entourant les perceptions managériales de ce discours et des initiatives de durabilité dans une époque marquée par des défis sans précédent.
KADDOURI Ouiam - EMLV |
The benefit of gender diversity on the corporate boards of family firms (FFs) continues to receive growing interest. In this paper, we examine the goals of women who hold a position on the board of directors at FFs. Goal setting has been used to identify what they want to accomplish here. How do they make a difference? This question is answered through the theoretical lens of socio- emotional wealth (SEW) and goal setting. We contribute to the literature supporting gender-diverse board composition, emphasizing the goals associated with women on FF boards, and highlighting their role in family business succession. Drawing on SEW and goal setting theory, this study examines how women’s goals influence succession. Driven by the research question, our data bring together three categories of goals pursued by women in the boardroom.
EL HAYEK SFEIR Soumaya - Excelia Business School |
An Initial Coin Offering (ICO) is a modern fundraising method for start-ups, similar to crowdfunding but using digital tokens instead of traditional cash or rewards. Investors purchase these tokens, which they can later use to buy the product or resell for potential profit. ICOs provide entrepreneurs with a global financing opportunity while offering investors early access to innovative projects. Overall, ICOs connect entrepreneurship, finance, and blockchain technology, making them a revolutionary tool for start-up funding.
DELL’ERA Michele - EDC Business School |
The goal of this study is to examine how environmental taxes influence the comparative advantage in environmental products and carbon emissions within emerging economies. To gain a better understanding, we examine whether this impact changes depending on the level of government integrity. The results indicate that increased environmental taxes mitigate the comparative advantage in environmental goods for emerging markets. However, for countries with high levels of government integrity, higher environmental taxes enhance their competitive edge in environmental goods. Additionally, our findings show that although a rise in environmental taxes is associated with higher carbon emissions, raising such taxes results in a reduction in carbon emissions for emerging economies with solid government integrity. These findings suggest that robust political institutions are crucial in promoting the comparative advantage of emerging markets in environmental goods and mitigating climate change. In the absence of substantial confidence in political or governmental institutions, the efficient implementation of climate taxes poses considerable challenges. Furthermore, we observe that an increase in the comparative advantage of environmental goods results in a decrease in carbon emissions.
KOCAARSLAN Baris - EDC Business School |
This study explores the influence of legal uncertainties on the process of innovating human resources (HR) practices in developing countries. Through a case study focused on introducing remote work within Kazakhstan’s Technical Gas Industry during a healthcare crisis, we examine the multifaceted challenges and opportunities that emerge when navigating a complex legal landscape. Our findings reveal that legal uncertainties, stemming from inadequacies in legislation and the tightness of norms, significantly impede the ability to adapt and modernize HR practices during crises. Furthermore, the criticality of the company’s position within the industry, combined with a low degree of legal enforcement, underscores the concept of ‘responsibilization’ among HR professionals. This phenomenon compels HR practitioners to assume greater responsibility and make strategic decisions that occasionally push the boundaries of existing laws and regulations. In this context, we propose a novel conceptualization of responsibilization, distinct from empowerment, as it involves embracing negative legal consequences associated with proactive decision-making during crises. This study contributes significantly to our understanding of how legal uncertainties influence the process of HR innovation in developing countries, highlighting the intricate interplay between regulatory frameworks, crisis management, and organizational transformation.
NAVAZHYLAVA Kseniya - EMLV |
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 |