The École de Management de Normandie (also known as EM Normandie) is a business school created in 1871. Incorporated as a Higher Education & Research non-profit association (under the 1901 Act) and operating under private law, it has campuses in Caen, Dublin, Le Havre, Oxford and Paris. It is one of the oldest business schools in France. It holds EPAS, EQUIS, and AACSB accreditations. In 2015, EM Normandie was selected to appear in the ranking of the Financial Times of the best masters in management in the world (69th).In January 2013, EM Normandie launched its new “Values & Performance” Strategic Plan, to guarantee further strategic consistency, to capitalize on its multi-campus experience, to apply active learning, and to serve the Normandy territory in partnership with its entire business community. This has brought new dimensions to the School's ambitions and reputation, thanks to the La SmartEcole® project and further partnerships with the University of Caen Normandy and the Grenoble School of Management.
PurposeThis paper aims to examine how digitalisation affects traditional supply chain risks in a French humanitarian organisation, focusing on the interplay between digital and conventional risk categories.Design/methodology/approachA case study at Banque Alimentaire Le Havre using FMEA, Risk Priority Numbers (RPNs), statistical and sensitivity analyses (correlation, partial least squares, analysis of variance) to evaluate how digitalisation reshapes risk profiles.Findings IS misfit strongly impacts supply and process risks. Social/human factors influence demand risk. Information systems (IS) usage affects environmental risks. Demand risk decreases significantly post-digitalisation. Overweighting RPN components amplify the effects of social/human issues while the effects of IS technical risks are more robust.Research limitations/implicationsThe single-case scope and direct impacts of IS risks based on standardised RPNs may limit generalisation. Future studies could explore these directions as well as cascading interdependencies.Practical implicationsThe study supports better digital risk governance, IS alignment and staff training for humanitarian supply chains undergoing digital transformation.Originality/valueThe paper offers a new hybrid framework integrating digital and traditional risks with empirical insights for researchers and humanitarian practitioners.
We propose a sequential monitoring scheme to detect changes in dynamic semiparametric risk models that capture Value-at-Risk (VaR) and Expected Shortfall (ES) jointly. The monitoring scheme is based on a gradient-based detector and a boundary function, and a change is detected when the detector crosses the boundary function. We derive the asymptotic limit of the stopping time of detection under the null hypothesis of no change. Monte Carlo simulations show that the proposed test has reasonable size control under the null hypothesis and high power under alternative hypotheses of various change point scenarios in finite samples. Empirical applications based on the S&P 500 index and the GBP/EUR exchange rate illustrate that our proposed test is able to detect change points in real-time.
This research note explores Minecraft as a methodological tool for collecting data from children in hospitality and tourism settings. While research involving children remains limited in these fields, Minecraft offers a playful, immersive, and participatory environment well suited to capturing their preferences and perceptions. The paper outlines a proposed methodological framework that details how Minecraft can be used to facilitate child-led exploration, construction, and interaction within virtual tourism spaces. Although promising, the method presents challenges related mainly to ethics and reliability, epitomised by the opposition covert and overt used of Minecraft.
Firms continue to rely on unsustainable practices and linear business models that push planetary boundaries to their limits. While the concept of the regenerative business model (RBM) has emerged to restore and enhance social-ecological systems, it remains conceptual and requires guidance on how to transform existing business models to prioritize planetary health and societal well-being. This study aims to develop a practical approach for firms to transform existing business models toward regeneration. Using a Design Science Research Methodology (DSRM), we designed and evaluated a three-step process template supported by transformative questions based on six design requirements (DRs) that guide a RBM transformation. Our findings show that regenerative transformation unfolds through three interconnected phases: re-grounding, re-wiring, and re-seizing business models. We advance theory by identifying the mechanisms of regenerative transformation, inform practice by offering a structured and actionable process, and contribute methodologically by demonstrating how design science can generate design knowledge for regeneration.
PurposeThis study aims to develop a structured decision-support framework to prioritize Industry 4.0 technologies (I4.0Ts) for reverse logistics operations in perishable-goods supply chains. These supply chains face unique challenges, including product perishability, unpredictable return flows, and the need for real-time monitoring and sustainability.Design/methodology/approachA mixed-method approach was adopted, combining a systematic literature review with expert validation to define relevant evaluation criteria based on the Technology-Organization-Environment (TOE) framework, which was extended to include scalability and social acceptance dimensions. The Fuzzy Analytic Hierarchy Process (FAHP) was used to weight five main and 14 sub-criteria, and the Fuzzy TOPSIS (FTOPSIS) was applied to rank four I4.0Ts: IoT, Blockchain, AGVs, and Big Data.FindingsThe results reveal that cost-effectiveness, scalability, and technological feasibility are the most influential criteria in technology selection. Among the evaluated alternatives, IoT and Blockchain emerged as the top-ranked technologies due to their strong alignment with the needs for traceability, monitoring, and operational responsiveness in perishable reverse logistics.Originality/valueThis study proposes a comprehensive, criteria-driven framework specifically for evaluating and prioritizing I4.0Ts in the context of reverse logistics for perishable goods. It contributes to the literature by integrating the TOE framework with fuzzy multi-criteria decision-making methods, providing actionable insights for technology selection in complex, time-sensitive supply chains.
