Subordinates' perceptions of the need- supportive, need-thwarting, and need- indifferent behaviors used by their supervisors: A person-centered investigation

International audienceAdopting a recent tripartite operationalization of subordinates’ perceptions of their supervisors’ behaviors, anchored in Self-Determination Theory (SDT), this person-centered study considers the co-existence of subordinates’ perceptions of their supervisors’ need-supportive, -thwarting, and -indifferent behaviors. Moreover, we also consider how these various combinations (or profiles) of perceived supervisor behaviors relate to subordinates’ levels of work motivation, well-being, attitudes, behaviors, and work-home functioning. A sample of 596 French employees (Mage = 31.22; 73.5% women) participated in this study. Our results revealed six profiles of subordinates characterized by distinct configurations of perceived need-related behaviors from supervisors (Globally Unfavorable; Globally Favorable and Supportive; Moderate-Indifferent; Moderately Favorable and Involved; Moderately Unfavorable; Moderately Favorable). These profiles displayed well-differentiated patterns of associations, consistent with our expectations, with all of the outcomes considered in this study. These findings underscored the key role of subordinates’ specific perceptions of need-supportive, -thwarting, and -indifferent behaviors, over and above their global perceptions of their supervisors’ behaviors, in determining how beneficial or harmful supervisory profiles are. In particular, our results also highlighted the critical role played by need-indifferent behaviors, which prove to be a very important, and yet typically neglected, component of subordinates’ perceptions of their supervisors’ behaviors

Digital Transformation for DIY Business Sustainability and Growth in Emerging Markets

International audienc

Lexical aspect: the case of prefixes in Old French

International audienc

Réussir à innover en matière de prévention des risques : de la recherche-action collaborative à la mise en retrait des chercheurs

National audienc

Benefits of a group-based running session on feelings of energy and fatigue: No augmenting effect of green exercise during the defoliation season

International audienc

Identifying Critical Commuters: A Machine Learning Approach to Flexible Work Hours and Urban Congestion

International audienceCongestion remains one of the most prevalent transport problems in major cities. Recent approaches to managing demand aim to make working hours flexible to reduce congestion during peak periods. However, these approaches must also address synchronization needs at the employer, household, and individual levels. This study presents a framework to identify critical commuters who can adjust their arrival times, benefiting individual motivations, and managing arrival time demands. We explore multiple machine learning approaches to model and predict an individual's ability to shift their workplace arrival times. Ultimately, we choose gradient boosting due to its superior performance. Utilizing this ensemble approach on an employee survey data from Rennes Metropole in France, we analyze the factors that influence individual's flexibility in their arrival times. Key determinants identified include regular school drop-offs, theoretical arrival time contract with employer, and, to a lesser extent, age and income. Our findings demonstrate the need for a bi-level framework that incorporates both arrival time demand management and social justice analyses to ensure effective and equitable outcomes

Large-Scale Evacuation with Vehicular Communication: Navigating Through Dark Zones

International audienceIn times of disaster, ensuring the safe evacuation of affected populations is crucial for saving lives and mitigating community risks. This research presents a Dynamic Population Evacuation (DPE) approach, which combines strategic planning and real-time management aided by vehicular communication technology. By addressing the impact of disasters on transportation and communication systems, the DPE framework utilizes dynamic shelter allocation and simulation-based traffic assignment techniques to enhance planning accuracy. It incorporates a trip-based traffic simulator to account for the effects of disasters on transportation networks and a Vehicular Ad Hoc Network (VANET) simulator to manage communication dark zones. To manage dark zones, The proposed framework continuously updates the evacuation plan in real time to manage road blockages and the disabling of VANET resources. Accounting for the temporal evolution of areas with communication dark zones improves evacuation efficiency regarding clearance time. A sensitivity analysis is conducted on the compliance rate of evacuees to instructions provided by the vehicular communication management system. Furthermore, the framework's effectiveness is evaluated by simulating the real test case of the 2018 Camp Fire wildfire in Paradise, California, where roads and communication were severely disrupted. Additionally, by comparing the architectures of cloud computing and fog computing while accounting for blocked roads, the framework shows more than a 12% improvement in network clearance time compared to fog computing and a 19% improvement compared to traditional evacuation planning

Compte-rendu de A. Marzano, Plants, politic and Empire in Ancient Rome, Cambridge, 2022

International audienc

Coupling cubic equations of state with the concept of entropy scaling to model the viscosity of ionic liquids

International audienceThis short paper investigates the applicability of our previously developed entropy scaling model to pure ionic liquids and concludes that it can be used without any modification and leads to very satisfactory results when coupled with the Peng-Robinson or Soave-Redlich-Kwong cubic equations of state. For the considered ionic liquids, the average deviations between calculated and experimental viscosities were found to be around 4.6 and 5.8% for the two cubic equations of state, respectively