Archive ouverte de l'ESSEC Business School
Not a member yet
1344 research outputs found
Sort by
A two-sector model of healthcare provision with directed search
No full textForthcoming in Theory and Decision (2025)In France, specialist physicians providing outpatient care work either in sector 1, where fees are regulated, or sector 2, where they set their own fees freely. Patients choose their physician based on fees, perceived quality of service and the likelihood of obtaining an appointment, directing their search toward either sector 1 or sector 2 providers. In equilibrium, significant patient and physician mobility across sectors means that policies affecting one sector have spillover effects on the other. We use comparative statics to analyze the consequences of various policies, such as increasing regulated fees or expanding private insurance coverage for sector 2 consultations. Both entail a positive response of the unregulated fee in sector 2. Some effects are counterintuitive and result from the reallocation of patients and physicians across sectors, which can deteriorate the effectiveness of the search process
Matrix CUSUM statistic, July 23 -August 22, 2012
No full textStructural changes occur in dynamic networks quite frequently and its detection is an important question in many situations such as fraud detection or cybersecurity. Real-life networks are often incompletely observed due to individual non-response or network size. In the present paper we consider the problem of change-point detection at a temporal sequence of partially observed networks. The goal is to test whether there is a change in the network parameters. Our approach is based on the Matrix CUSUM test statistic and allows growing size of networks. We show that the proposed test is minimax optimal and robust to missing links. We also demonstrate the good behavior of our approach in practice through simulation study and a real-data application
Adoption de la cryptomonnaie : une analyse sous le prisme de la Valeur Unifiée Perçue
No full textInternational audienceThe development of Fintechs is disrupting the financial industry, with rapid adoption of cryptocurrencies, especially among millennials. However, current literature highlights various factors influencing this adoption but presents a gap by not accounting for ethical and anticipated values, nor the absence of a unified theoretical framework. To address these shortcomings, the study proposes the concept of Perceived Unified Value, encompassing utilitarian, epistemic, individual, dynamic, emotional, ethical, and anticipated dimensions. By integrating this concept into an innovative adoption model, the research provides financial institutions with tools to better anticipate market perceptions and adapt their strategies. This approach would optimize investments in innovations while meeting consumer needs in a competitive environment. Finally, research avenues are suggested to deepen the understanding of this unified value and its influence on trust and satisfaction among cryptocurrency users
Macroeconomic Consequences of the War in Ukraine on Central and Eastern European Economies: A SVAR Analysis
No full textThis paper investigates the macroeconomic effects from the Russian invasion of Ukraine in February 2022 on the economies of Bulgaria, Czechia, Hungary, Poland and Romania, using a SVAR model based on a similar analytical framework as that described in Bruhin et al. (2023)[3]. The exogenous shock is captured by the geopolitical risk index developed by Caldara and Iacoviello (2022) [4]. Simulations show that, by the end of 2022, the war contributed to a rise in inflation by 0.45-0.85 percentage points and a drop in GDP by 0.79-1.55 percentage points compared to the counterfactual "no-war" scenario. Our findings suggest a generally larger impact on economic activity in CEE countries compared to Western European economies, a result that can be attributed to the structural weaknesses of these economies, and to the geographic proximity to the conflict area, which led to a higher volatility of the series in the CEE region. Regarding inflation, the uncertainty bands suggest that the war's impact could have been larger, potentially reaching up to 3 percentage points
Low-Rank Graphon Estimation: Theory and Applications to Graphon Games
No full textThis paper tackles the challenge of estimating a low-rank graphon from sampled network data, employing a singular value thresholding (SVT) estimator to create a piecewise-constant graphon based on the network's adjacency matrix. Under certain assumptions about the graphon's structural properties, we establish bounds on the operator norm distance between the true graphon and its estimator, as well as on the rank of the estimated graphon. In the second part of the paper, we apply our estimator to graphon games. We derive bounds on the suboptimality of interventions in the social welfare problem in graphon games when the intervention is based on the estimated graphon. These bounds are expressed in terms of the operator norm of the difference between the true and estimated graphons. We also emphasize the computational benefits of using the low-rank estimated graphon to solve these problems
Minimax optimality of deep neural networks on dependent data via PAC-Bayes bounds
No full textIn a groundbreaking work, [34] proved the minimax optimality of deep neural networks with ReLu activation for least-square regression estimation over a large class of functions defined by composition. In this paper, we extend these results in many directions. First, we remove the i.i.d. assumption on the observations, to allow some time dependence. The observations are assumed to be a Markov chain with a non-null pseudospectral gap. Then, we study a more general class of machine learning problems, which includes least-square and logistic regression as special cases. Leveraging on PAC-Bayes oracle inequalities and a version of Bernstein inequality due to [31], we derive upper bounds on the estimation risk for a generalized Bayesian estimator. In the case of least-square regression, this bound matches (up to a logarithmic factor) the lower bound in [34].We establish a similar lower bound for classification with the logistic loss, and prove that the proposed DNN estimator is optimal in the minimax sense. </p
A Branch-Price-and-Cut algorithm for the Multi-Commodity two-echelon Distribution Problem
No full textInternational audienceIn the Multi-Commodity two-echelon Distribution Problem (MC2DP), multiple commodities are distributed in a two-echelon distribution system involving suppliers, distribution centres and customers. Each supplier may provide different commodities and each customer may request several commodities as well. In the first echelon, capacitated vehicles perform direct trips to transport the commodities from the suppliers to the distribution centres for consolidation purposes. In the second echelon, each distribution centre owns a fleet of capacitated vehicles to deliver the commodities to the customers through multi-stop routes. Commodities are compatible, i.e., they can be mixed in the vehicles. Finally, customer requests can be split by commodities, that is, a customer can be visited by several vehicles, but the total amount of each commodity has to be delivered by a single vehicle. The aim of the MC2DP is to minimise the total transportation cost to satisfy customer demands. We propose a set covering formulation for the MC2DP where the exponential number of variables relates to the routes in the delivery echelon. We develop a Branch-Price-and-Cut algorithm (BPC) to solve the problem. The pricing problem results in solving an Elementary Shortest Path Problem with Resource Constraints (ESPPRC) per distribution centre. We tackle the ESPPRC with a label setting dynamic programming algorithm which incorporates ng-path relaxation and a bidirectional labelling search. Pricing heuristics are invoked to speed up the procedure. In addition, the formulation is strengthened by integrating capacity cuts and two families of valid inequalities specific for the multiple commodities aspect of the problem.Our approach solves to optimality 439 over the 736 benchmark instances from the literature. The optimality gap of the unsolved instances is 2.1%, on average.</p
SOME RECOMMENDATIONS ON ESG CRITERIA TO PRIORITIZE IN THE EXECUTIVE DIRECTORS' COMPENSATION POLICY
No full textViviane de Beaufort, Hichâm Ben Chaïb. Quelques recommandations sur les critères ESG à prioriser dans la politique de rémunération des dirigeants mandataires sociaux. 2024. ⟨hal-04680027⟩The inclusion of ESG (environmental, social, and governance) criteria in executive remuneration policies is now well-established, yet it remains uneven across companies and often applied too discretionarily. The choice among various criteria is not always the most relevant to the business and can sometimes be "easy" to achieve, ensuring the additional remuneration is awarded. Defining a set of standard ESG criteria applicable to all companies is a challenge. On this point, we find the conclusions developed by Dell' Erba and Ferrarini (2024).It is thus pertinent to develop a personalised approach, tailored to the specificities of each economic entity and its non-financial challenges. We propose, therefore, to promote a philosophy of extra-financial performance in executive remuneration, guided by a set of principles to direct remuneration committees in the selection, evaluation, and measurement of ESG criteria.In this perspective, it is essential to place ESG criteria within the context of their deployment to justify executive remuneration policies. Integrating ESG criteria into remuneration packages should be seen as a legitimate objective, equivalent to financial criteria. By encouraging executives to aim for extra-financial performance, the goal is to align the objectives of sustainable value creation with those of executive remuneration.Research shows a positive correlation between ESG scores and the adoption of remuneration policies based on sustainable performance. Companies with strong ESG profiles are more likely to adopt such policies. However, it remains crucial to demonstrate that linking executive remuneration to ESG criteria effectively contributes to overall extra-financial performance. Furthermore, the European directive on corporate sustainability reporting (CSRD) now imposes a normative framework aimed at encouraging companies to disclose information on the nonfinancial impacts of their activities, which should progressively clarify matters. Such a harmonised framework at the European level represents a step forward towards greater transparency and accountability of companies regarding ESG criteria. Companies would do well to adopt this framework as quickly as possible, even if it seems complex
INCERTITUDE ORDINAIRERésilience organisationnelle en situation de crise
No full textNational audienceConflits militaires, tensions géopolitiques, pandémies, réchauffement climatique, crise de sens, mouvements sociaux et inflation sont autant d’éléments qui contraignent et constituent des phénomènes de crise qu’il est nécessaire d’appréhender et solutionner.Le titre Incertitude ordinaire signifie que les situations de crise sont devenues le quotidien et que nos hypothèses de travail ne doivent plus être construites sur un monde stable mais en crise permanente. À partir de la description et de l’analyse de situations de crise, il s’agit de s’interroger sur les bons fonctionnements et un management adapté aux situations que l’on pourrait qualifier de crises, d’extrêmes, d’imprévus, etc.Cet ouvrage a pour ambition de s’interroger sur les mécanismes en situations imprévues et d’en déduire des manières d’agir adaptées et performantes au regard de l’urgence de la situation elle-même.La notion de la résilience organisationnelle sera définie à partir des travaux de Karl Weick sur le sujet avec le fait que les décisions verticales et centralisées ont peu d’efficacité sur le fonctionnement des équipes qui vivent la situation. La notion de micro-solutions et micro-décisions en mode essai-erreur sera privilégiée par rapport à la planification.Les auteurs de cet ouvrage constituent une équipe d’académiques et d’experts qui ont eu à gérer des situations extrêmes
Media Mergers in Nested Markets
No full textNational audienceWe analyze the effect of media mergers in a model that stresses, on the one hand, the fact that media are two-sided platforms willing to attract advertisers and viewers and, on the other hand, that strong competitors have emerged to challenge traditional media on both sides. We show that a merger has two conflicting effects on traditional media's incentives to invest in quality programs and to exploit their market power. When competition is primarily between traditional media, a Business-Stealing Effect dominates, and the merger is detrimental to advertisers and viewers. When the competition is mainly between the traditional media and their new competitors, an Ecosystem Effect dominates, and the merger benefits advertisers and viewers. We extend this setting to discuss the role of financial constraints that might limit investments in the quality of programs and show that the same effects are at play