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Évaluation des aides à la décarbonation du plan France Relance
No full textCe projet documente et analyse l’impact des aides à la décarbonation sur trois volets : le ciblage et le recours aux aides du plan France Relance, les effets économiques et environnementaux des précédentes vagues d’aides à la décarbonation et en particulier du Fonds Chaleur administré par l’Ademe, et les premiers effets rétrospectifs des impacts économiques des aides à la décarbonation du plan France Relance
What can be learnt from failures in the sports media business? A case study of the Mediapro crash in football media rights in France
No full textInternational audienc
Follow the money! Why dividends overreact to flat-tax reforms
No full textWe estimate behavioral responses to dividend taxation using recent French reforms: a rate hike followed, five years later, by a cut. Exploiting household and firm tax data as well as data linking firms and shareholders, we find very large dividend tax elasticities to both reforms. Individuals who control firms adjust dividend receipts instantaneously, accounting for most of the aggregate dividend reaction. Investment is insensitive to dividend taxation. Dividend adjustments are instead driven by corporate saving, as owner-managers treat firms as low-tax saving vehicles. Our results fit the ‘new view’ of dividend taxation, provided an additional low-tax yet costly payout option is available that offers a tax arbitrage opportunity to entrepreneurs in control of their firms
A Novel Integer Linear Programming Approach for Global L0 Minimization
No full textInternational audienceGiven a vector y ∈ R n and a matrix H ∈ R n×m , the sparse approximation problem P 0/p asks for a point x such that ∥y-Hx∥ p ≤ α, for a given scalar α, minimizing the size of the support ∥x∥ 0 := #{j | x j ̸ = 0}. Existing convex mixed-integer programming formulations for P 0/p are of a kind referred to as "big-M ", meaning that they involve the use of a bound M on the values of x. When a proper value for M is not known beforehand, these formulations are not exact, in the sense that they may fail to recover the wanted global minimizer. In this work, we study the polytopes arising from these formulations and derive valid inequalities for them. We first use these inequalities to design a branch-and-cut algorithm for these models. Additionally, we prove that these inequalities are sufficient to describe the set of feasible supports for P 0/p. Based on this result, we introduce a new (and the first to our knowledge) M-independent integer linear programming formulation for P 0/p , which guarantees the recovery of the global minimizer. We propose a practical approach to tackle this formulation, which has exponentially many constraints. The proposed methods are then compared in computational experimentation to test their potential practical contribution
Unraveling the foundations and the evolution of conceptual modeling—Intellectual structure, current themes, and trajectories
No full textInternational audienceThe field of conceptual modeling has now been in existence for over five decades. To understand how this field has evolved and should continue to evolve, it is useful to examine the contributions made over time and the themes that have emerged. In this research, we apply bibliometric analysis to a corpus of over 4700 research papers spanning from 1976 to 2023. We successively apply co-citation, bibliographic coupling, and main path analysis. Co-citation and citation networks are produced that surface the intellectual structure of the field, the main themes, and the relationships among major and influential research papers over time. We identify four areas in the intellectual structure of the field: conceptual modeling and databases; grammars and guidelines for conceptual modeling; requirements engineering and information systems design methodologies; and ontology constructs for conceptual modeling. Between 2017 and 2023, we distinguish nine research themes, including domain-specific conceptual modeling and applications, ontologies and applications, genomics, and datastores and multi-model data. The main path analysis identifies several trajectories among the major and most influential papers. This leads to insights into the lineage of key, influential papers in conceptual modeling research. The primordial nature of the main paths identified encompasses two important aspects. The first revolves around refining and complementing the entity-relationship model. The second identifies the contribution of ontologies for conceptual modeling to make the models more robust. Based on the findings from this bibliometric analysis, we propose several directions for future conceptual modeling research
La gestion de l’activité de prise en charge des patients peut-elle devenir visible ?
No full textInternational audienceDespite the substantial resources invested in the healthcare system, problems related to dissatisfaction among health professionals persist. The hypothesis put forward in this article is that many issues lie at the level of real activity and the on-the-ground experiences of healthcare professionals. Drawing on an analysis of the administrative burdens, hospital hierarchies, and the coordination of patient pathways, and taking inspiration from pragmatist thinking, an overall diagnosis emerges: healthcare professionals on the ground are developing effective solutions, but these efforts often go unnoticed because they differ from the official reform initiatives in place.Malgré les ressources injectées dans le système, le malaise des professions de santé persiste. L’hypothèse avancée est qu’une grande partie des problèmes se situe au niveau de l’activité réelle. À partir d’une analyse sur le fardeau administratif, les hiérarchies hospitalières, et la coordination du parcours du patient, et en s’inspirant de la pensée pragmatiste, un diagnostic d’ensemble ressort : menée par des professionnels qui agissent sur le terrain, des solutions adaptées se bâtissent, mais restent assez invisibles, car éloignées de la mise en place des réformes officielles
From knowledge to skills: training for transition jobs. Interview with Alain Grandjean
No full textInternational audienceAlain Grandjean is an economist and author specializing on green finance. He is also cofounder and partner of Carbone 4, a consultancy firm focusing on energy transition and adaptation to climate change. The interview first revolves around the academic content Alain Grandjean considers as the bare necessities to be taught in higher education, no matter the curriculum. This should take the form of a basic synthetic training which takes into account the major environmental issues without too much technicality as well as lessons in accounting and economics, which he considers essential. The interview also looks more specifically at engineering and business schools. Then Alain Grandjean shares his views on the effectiveness of different ways to engage for the transition -like radical individual lifestyle transformations and civil disobiedience. He also evokes the roles that trade unions as well as NGOS can play and he talks about collapsology
Bayes meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes
No full textInternational audienceBernstein's condition is a key assumption that guarantees fast rates in machine learning. For example, under this condition, the Gibbs posterior with prior has an excess risk in , as opposed to in the general case, where denotes the number of observations and is a complexity parameter which depends on the prior . In this paper, we examine the Gibbs posterior in the context of meta-learning, i.e., when learning the prior from previous tasks. Our main result is that Bernstein's condition always holds at the meta level, regardless of its validity at the observation level. This implies that the additional cost to learn the Gibbs prior , which will reduce the term across tasks, is in , instead of the expected . We further illustrate how this result improves on the standard rates in three different settings: discrete priors, Gaussian priors and mixture of Gaussian priors
A Novel Instance Generator for Simulating Middle-Mile Logistics Networks
No full textInternational audienceTo tackle the challenge of optimizing middle-mile logistics, the crucial link between warehouses and final deliveries, we introduce a novel instance generator that aims to create a rich and adaptable dataset of diverse instances to empower researchers and developers. The instance defines a logistics network with hubs, vehicles, routes, lines, and rotations. Additionally, it specifies a list of shipments that need to be transported through this network. To customize the instance, the user can adjust various parameters, such as the number of hubs, density of the space graphs, distribution of shipment weights, or the maximum number of vehicles.The generator reflects real-world complexities through variations in network size and structure. We developed a random graph generator to mimic real-world middle mile networks, by generating space graphs for hubs. Subsequently, lines and routes are randomly constructed on the generated space graphs, while adhering to user-defined constraints.The tool is in the form of an optimized C++ library that enables the generation of instances with a large number of hubs and shipments. It offers the immense potential for advancing middle-mile logistics optimization by providing a comprehensive and adaptable dataset for benchmarking optimization approaches, training machine learning models, and analyzing the impact of network configurations and shipments characteristics on overall efficiency