Grants
March 15th 2024 to March 14th 2027
L'émergence du virus COVID-19 a entraîné une pandémie avec plus de 6,9 millions de décès estimés dans le monde. La gestion de l'épidémie en Europe, y compris en France, a permis de réduire la charge de morbidité attendue. Cet objectif a été atteint en particulier grâce à la combinaison d'une réduction initiale de la transmission par des politiques de confinement plus ou moins strictes et, un an plus tard, d'une forte incitation à l'utilisation des vaccins contre le virus Covid-19 au sein de la population adulte, en utilisant des vaccins dont l'efficacité contre les formes sévères de la maladie est élevée et bien établie. Cette période a été marquée par un débat scientifique, sociétal et politique sur l'efficacité, la sécurité, la faisabilité, la légitimité, la parcimonie et l'équité d'une variété de contre-mesures préventives (PCM) et de politiques connexes. Ce débat a illustré les défis à relever pour contrôler les maladies infectieuses émergentes tout en maintenant la confiance parmi et entre les parties prenantes et en limitant les inégalités sociales. Si l'on peut affirmer que l'innovation biomédicale rapide associée à des incitations fortes permettra de contrôler avec succès les futures maladies infectieuses émergentes, d'autres s'interrogent sur les coûts sociétaux élevés de cette approche, notamment au détriment de la confiance et de l'équité sociales.
Un nombre considérable de données probantes en sciences sociales et en santé publique ont décrit la nécessité de renforcer la confiance des individus dans les décisions et les actions, et de s'attaquer aux inégalités sociales pendant la réponse aux épidémies, et que les recommandations basées sur les préférences, l'organisation au niveau local, y compris les travailleurs de la santé, peuvent aider à répondre à ces exigences. Cependant, on sait peu de choses sur la façon dont ces preuves peuvent être mises en œuvre et traduites dans la pratique de la santé publique pendant les situations d'épidémie et, pour y parvenir, des cadres méthodologiques sont nécessaires.
Le projet ACME a pour objectif de contribuer au développement et à la mise en œuvre de PCM efficaces, acceptables et accessibles, y compris la vaccination, spécifiquement pour une utilisation pendant les épidémies de maladies infectieuses (ré)émergentes en France. L'objectif est d'identifier et de préparer, lors des activités de préparation aux épidémies, des stratégies et des programmes de confiance et d'inclusion. Le projet ACME répond au cadre PEPR en construisant un consortium de recherche multidisciplinaire d'institutions académiques en France qui utiliseront les sciences sociales et les méthodes de santé publique pour se préparer aux futures épidémies de maladies infectieuses émergentes. Notre projet correspond à l'axe 2 (Connaissance, expertise, communication), car il vise à mieux comprendre les facteurs clés qui influencent l'acceptation et l'accessibilité physique et psychologique des différents PCM dans les situations d'épidémie, et recommandera des approches pour la traduction de ces preuves en actions de santé publique. Bien que l'élaboration et la mise en œuvre des programmes relèvent de la compétence des États membres, on peut s'attendre à ce que les recommandations en matière de GCP soient de plus en plus guidées par des entités supranationales européennes, une dimension qui sera prise en compte dans le projet ACME grâce à l'implication des parties prenantes européennes dans des étapes spécifiques.
Les objectifs généraux du projet ACME sont les suivants
1. Évaluer les déterminants, les facilitateurs et les barrières de l'adoption/adhésion, de la confiance et de l'équité sociale concernant les PCM dans les situations épidémiques en France, et identifier des approches pour surveiller ces facteurs pour la préparation aux épidémies qui devraient être mises en œuvre dans les périodes non-épidémiques (WP1).
2. Développer des scénarios potentiels de maladies épidémiques et de GCP pertinents, et évaluer les préférences autour des stratégies et programmes correspondants parmi la population générale, les travailleurs de la santé et d'autres sous-groupes pertinents (WP2).
3. Préparer une recherche interventionnelle sur les programmes de GCP inclusifs et de renforcement de la confiance dans les situations épidémiques, en identifiant les expériences rapportées en France et ailleurs (études de cas) et évaluer leur transférabilité dans un contexte épidémique en France (WP3).
4. Développer des recommandations et des feuilles de route vers des stratégies et des programmes qui assurent l'acceptabilité et l'accessibilité des PCM pendant les situations épidémiques en France et en Europe, élaborer des pré-protocoles (blueprints) pour une mise en œuvre rapide de la recherche interventionnelle dans les futures situations d'urgence, et préparer leur transfert et leur mise en œuvre dans la recherche et l'action de santé publique pour la préparation aux épidémies (WP4).
The COVID-19 emergence has led to a pandemic with over 6.9 million estimated deaths worldwide [1]. The epidemic management in Europe including France has allowed reducing the expected burden of disease. This was achieved in particular by a combination of initial reduction of transmission via containment policies of variable stringency and, one year later, strongly incentivised high uptake of Covid-19 vaccines among the adult population, using vaccines with high and well-persisting effectiveness against severe forms of the disease. This period was marked by scientific, societal and political debate about the effectiveness, safety, feasibility, legitimacy, parsimony and fairness of a variety of preventive countermeasures (PCMs) and related policies. This illustrated the challenges to control emerging infectious diseases while maintaining trust among and between stakeholders and limiting social inequalities. While it can be argued that rapid biomedical innovation combined with strong incentives will successfully control future emerging infectious disease events, others question the high societal costs of this approach, in particular at the expenses of societal trust and equity.
A considerable body of social sciences and public health evidence has described the need to foster individuals’ confidence in decisions and actions, and to address social inequalities during epidemic response, and that preference-based recommendation, organisation at the local level including healthcare workers (HCWs) can help achieving these requirements. However, less is known about how this evidence can be operationalised and translated into public health practice during epidemic situations and, to achieve this, methodological frames are needed.
The ACME project aims to contribute to the development and implementation of effective, acceptable and accessible PCMs, including vaccination, specifically for use during epidemics of (re-)emerging infectious diseases in France. The vision is to identify and prepare, during epidemic preparedness activities, confidence-building and inclusive strategies and programmes. The ACME project responds to the PEPR frame by constructing a multidisciplinary research consortium of academic institutions in France who will use social sciences and public health methods to prepare for future emerging infectious disease epidemics. Our project corresponds to the Axis 2 (Knowledge, expertise, communication), as it aims at a better understanding of key factors that impact the acceptance and the physical and psychological accessibility of various PCMs in epidemic situations, and will recommend approaches for the translation of this evidence into public health action. Although programme development and implementation are member state competencies, PCM recommendations can be expected to be increasingly guided by European supranational entities, a dimension that will be taken into account in the ACME project through involvement of European stakeholders in specific steps.
The general objectives of the ACME project are to:
1. Assess determinants, facilitators and barriers of uptake/adherence, confidence and social equity regarding PCMs in epidemic situations in France, and identify approaches to monitor these factors for epidemic preparedness that should be implemented in non-epidemic periods (WP1).
2. Develop potential scenarios of epidemic diseases and relevant PCMs, and evaluate preferences around corresponding strategies and programmes among the general population, HCWs and other relevant subgroups (WP2).
3. Prepare interventional research on confidence-building and inclusive PCM programmes in epidemic situations, by identifying experiences reported in France and elsewhere (case studies) and evaluate their transferability to an epidemic context in France (WP3).
4. Develop recommendations and roadmaps towards strategies and programmes that assure acceptability and accessibility of PCMs during epidemic situations in France and Europe, elaborate pre-protocols (blueprints) for rapid implementation of interventional research in future emergencies, and prepare their transfer and implementation into research and public health action for epidemic preparedness (WP4).
Confiance, équité sociale, préférences, recherche interventionnelle, transfert
Uptake, confidence, social equity,preferences, interventional research, transfer
ANRS
Bruno Ventelou (bruno.ventelou@univ-amu.fr)
January 01st 2021 to December 31st 2025
Les institutions contribuent à la stabilité économique et sociale. Par conséquent, leur remise en cause est souvent à l'origine d'un accroissement notable de l'incertitude économique. L'un des exemples les récents est le Brexit: voté en juin 2016 et toujours en cours de négociations 3 ans après. Cette période de confusion pèse sur les décisions des agents et est à l'origine de fragilités économiques.
Partant de ce constat, ce projet s'intéresse au comportement des entreprises et des gouvernements lorsqu'ils évoluent dans un environnement incertain. Son objectif est d'évaluer la manière dont ces agents réagissent à l'incertitude et dans quelle mesure leurs décisions peuvent elles-mêmes être source d'incertitude.
Ce projet propose d'améliorer la compréhension: (1) du comportement des entreprises en univers incertain à travers leurs décisions d'emploi et d'investissement, (2) du lien entre les décisions des entreprises et l'incertitude engendrée par politiques gouvernementales.
Institutions contribute to social and economic stability. Therefore, increasing institutional weaknesses may be a source of deep economic uncertainty. One striking example is the Brexit: the referendum took place in 2016 and negotiations are still ongoing 3 years after. This period of doubtless alters agents' decisions and might generate economic fragilities.
Based on this fact, this project focuses on firms' and governments' behavior in an uncertain environment. It seeks to assess how those agents react to uncertainty and whether their decisions can by themselves be a source of uncertainty.
This project proposes to provide a better understanding of (1) firms' labor and investment decisions when they face uncertainty, (2) the link between firms' behavior and economic policy uncertainty.
Incertitude macroéconomique, données micro, décisions de firmes
Macroeconomics; monetary economics; economic growth
ANR
Céline Poilly (celine.poilly@univ-amu.fr)
October 01st 2023 to September 30th 2029
Les économistes ont établi l’impact des migrations et des comportements familiaux, pris séparément, sur la croissance économique. Ils n’ont en revanche pas encore pleinement étudié comment l’interaction entre formation familiale et migration a influencé le développement économique européen. Nous contribuerons à cette analyse en construisant une base de données nouvelle qui combinera les données de grands sites généalogiques (Geni et Geneanet) avec d’autres sources tel que les recensements de la population. Nous entendons répondre à trois questions : (Q1) Aux différents stades de leur formation, comment les familles et leurs membres décident-elles de migrer vers de meilleures opportunités économiques? (Q2) Comment ces décisions sont-elles influencées par les transformations économiques et sociales traversées par l’Europe depuis le milieu du 17ème siècle? (Q3) Comment les décisions familiales et migratoires ont-elles contribué à la croissance économique en Europe de l’Ouest ? La première étape de notre projet consistera à construire et traiter les biais de notre base de données qui suivra le parcours migratoire et familial d’environ 700 millions d’Européens de leur naissance à leur mort entre 1640 et 1940. Ces données nous permettront d’abord d’analyser comment les décisions de fécondité et de migration ont interagi au cours du temps et influencé les retombées économiques de la migration ainsi que la mobilité sociale. Nous explorerons la dimension de genre de ces questions, les normes de genre étant un déterminant important des comportements familiaux et le résultat des dynamiques de population. Les résultats de ces analyses au niveau individuel serviront à répondre aux questions Q1 et Q2. Nous utiliserons alors les méthodes d’estimations structurelles afin de comprendre comment les migrations familiales ont nourri la croissance économique de long terme aux niveaux local et national, répondant par cela la question Q3.
The roles played by migration and family formation for economic growth have been well studied by economists. Yet these aspects have tended to be examined separately, without considering the interaction between family formation and migration. This project seeks to understand the extent of this interaction and how it shaped economic development in Western Europe. To address this question we intend to build and explore a new dataset combining data from online genealogical websites (Geni and Geneanet) with other sources, notably censuses. We aim at answering three questions: (Q1) How does family members' decision to migrate in search of better economic opportunities depend on the stage of family formation? (Q2) How were these decisions shaped by the major economic and social transformations that Europe experienced since the mid-17th century? (Q3) How did family formation and migration decisions contribute to economic growth in Western Europe? The first stage in the project will tackle an ambitious collection of data to build (and de-bias) our novel dataset. The latter will allow us to follow around 700 million Europeans over the period 1640 to 1940, providing rich information from their birth to their death that will identify both family dynamics and migration patterns. The data will first be used to analyze how fertility and migration decisions shaped each other, with a particular focus on the economic returns to migration and the implications for social mobility. The project will also consider the gender dimension of these questions, as gender norms are both an important determinant of family outcomes and a result of population dynamics and location choices. Results from these individual-level analyses will allow us to answer Q1 and Q2. We will then use structural estimations to understand how family migration affects long-run economic growth both at the local and aggregate levels, in order to answer our third research question, Q3.
Families, Migration and Long-run economic growth in Europe
Gender, Genealogical data, Economic Growth, Migration
ANR
Cécilia Garcia-Penalosa (cecilia.garcia-penalosa@univ-amu.fr)
February 01st 2022 to January 31st 2026
Les inégalités économiques augmentent et vont s’aggraver avec la crise du Covid19 dans la zone euro. Nous supposons que la fragmentation financière et bancaire crée des opportunités de financement et de revenus différentes entre les pays, les ménages et les entreprises, et donc contribue à cette dynamique. Notre objectif est d'évaluer les effets redistributifs des secteurs bancaires et financiers face à la dispersion des revenus et des richesses dans la zone euro. Nous considèrerons d’abord l’impact de l’intermédiation bancaire sur les inégalités, via les distorsions dans l’accès au crédit qu’induit la fragmentation. Nous nous interrogeons alors sur la stratégie optimale de la BCE permettant une croissance plus inclusive. Nous étudions ensuite les principaux déterminants d'un cercle vertueux entre les financements de marchés et la réduction des inégalités. Nous souhaitons montrer qu’une intégration financière et bancaire régionale complète peut contribuer à une Europe plus juste.
Economic inequalities rise and are accentuated by the Covid19 crisis in the Eurozone. We assume that financial and banking fragmentation implies different financing and income opportunities between countries, households and firms and thus fuels this dynamic. Our purpose is to assess the redistributive effects of financial markets and the banking sector considering income and wealth dispersion in the Eurozone. We first focus on the impact of banking intermediation on inequalities, via the distortions in the access to credit that the fragmentation induces. We therefore question the optimal ECB strategy for a more inclusive growth. We then study the main determinants of a virtuous circle between market financing and the reduction of inequalities. Our aim is to show that full regional financial and banking integration can contribute to a fairer Europe.
fragmentation financière, dispersion des revenus, union monétaire
financial fragmentation, income dispersion, monetary union
ANR
Céline GIMET (celine.gimet[at]sciencespo-aix.fr)
December 01st 2021 to November 30th 2024
Neurodegenerative diseases represent one of the main public health issues in our western societies and one of the greatest challenges in drug development. Prevention policies have become essential to address these issues: primary prevention to prevent disease onset by acting on actionable risk factors, or secondary prevention to slow disease progression with very early therapeutic interventions, ideally at pre-symptomatic stages. Key to the implementation of such prevention measures is the identification of at-risk patients, at the point of care, and preferably long before disease onset.
Our project, LeMeReND, proposes to use electronic health records (EHR) to identify biomedical risk factors through studying previous diagnoses (preclinical comorbidities), drug prescription, clinical care usage, and biological test results. This analysis will use longitudinal data in EHR registries including millions of patients who have been followed for at least 10 years before diagnosis in 4 different healthcare systems: Australia, France, the UK and Sweden and across 4 therapeutic areas: Alzheimer’s disease, Parkinson’s disease, dementia with Lewy bodies and motor neuron diseases. We will identify the biomedical risk factors that are common to these diseases and the ones differentiating them.
We will stratify patients based on the progression profile of their exposure to the set of risk factors, in order to design tailored primary prevention measures. We will also design a screening tool which will give each patient a propensity score to develop one of these neurodegenerative diseases.
Such a tool could be deployed at the point of care to prioritise at-risk individuals for further inclusion in secondary prevention trials. We will evaluate the economic and social benefits of this new generation of precision prevention measures. We will study the public acceptability of a secondary-prevention effort, among the French population, and the feasibility of its implementation in primary care practices in France, Australia, and Sweden. Eventually, we will progress our understanding of the genetic and imaging markers of the disorders by studying the identified prodromal biomedical factors, using the UK BioBank and GWAS summary statistics. This will progress our understanding of the pathological processes which result in an increased risk to develop a specific neurodegenerative disease.
LeMeReND gathers a multidisciplinary research group with a leading expertise in epidemiology, statistics and machine learning, in particular for the analysis of longitudinal EHR data. Partners have demonstrated a strong track record on neurodegenerative diseases (Sweden, France, Australia), analyses of large-scale data including neuroimaging (France), genetics (Australia), longitudinal modelling (Sweden, France), and machine learning (Australia, France). An expert team in health economics and health policy complements the consortium.
LeMeReND will therefore provide invaluable insights to inform health policies and highlight possible new therapeutic targets. It will provide unique screening tools to facilitate the large-scale recruitment of patients in secondary prevention trials.
Neurodegenerative diseases represent one of the main public health issues in our western societies and one of the greatest challenges in drug development. Prevention policies have become essential to address these issues: primary prevention to prevent disease onset by acting on actionable risk factors, or secondary prevention to slow disease progression with very early therapeutic interventions, ideally at pre-symptomatic stages. Key to the implementation of such prevention measures is the identification of at-risk patients, at the point of care, and preferably long before disease onset.
Our project, LeMeReND, proposes to use electronic health records (EHR) to identify biomedical risk factors through studying previous diagnoses (preclinical comorbidities), drug prescription, clinical care usage, and biological test results. This analysis will use longitudinal data in EHR registries including millions of patients who have been followed for at least 10 years before diagnosis in 4 different healthcare systems: Australia, France, the UK and Sweden and across 4 therapeutic areas: Alzheimer’s disease, Parkinson’s disease, dementia with Lewy bodies and motor neuron diseases. We will identify the biomedical risk factors that are common to these diseases and the ones differentiating them.
We will stratify patients based on the progression profile of their exposure to the set of risk factors, in order to design tailored primary prevention measures. We will also design a screening tool which will give each patient a propensity score to develop one of these neurodegenerative diseases.
Such a tool could be deployed at the point of care to prioritise at-risk individuals for further inclusion in secondary prevention trials. We will evaluate the economic and social benefits of this new generation of precision prevention measures. We will study the public acceptability of a secondary-prevention effort, among the French population, and the feasibility of its implementation in primary care practices in France, Australia, and Sweden. Eventually, we will progress our understanding of the genetic and imaging markers of the disorders by studying the identified prodromal biomedical factors, using the UK BioBank and GWAS summary statistics. This will progress our understanding of the pathological processes which result in an increased risk to develop a specific neurodegenerative disease.
LeMeReND gathers a multidisciplinary research group with a leading expertise in epidemiology, statistics and machine learning, in particular for the analysis of longitudinal EHR data. Partners have demonstrated a strong track record on neurodegenerative diseases (Sweden, France, Australia), analyses of large-scale data including neuroimaging (France), genetics (Australia), longitudinal modelling (Sweden, France), and machine learning (Australia, France). An expert team in health economics and health policy complements the consortium.
LeMeReND will therefore provide invaluable insights to inform health policies and highlight possible new therapeutic targets. It will provide unique screening tools to facilitate the large-scale recruitment of patients in secondary prevention trials.
ANR JPcofuND 2 - IP
Bruno Ventelou (bruno.ventelou[at]univ-amu.fr)
October 01st 2024 to March 31st 2028
La technologie Sea Water Air Conditioning (SWAC) utilisant l’eau de mer profonde à basse température reste très peu utilisée dans le monde car encore mal connue et nécessite de très gros investissements. Cependant, elle permet de climatiser des bâtiments et des quartiers de façon très efficace, en divisant par dix la consommation, la puissance appelée et les émissions de C02 par rapport à l’existant. Dans le contexte de changement climatique et d’épisodes successifs de canicule, la demande en équipements pour le rafraîchissement actif des bâtiments va vraisemblablement exploser au-delà des prévisions faites par l’agence internationale de l’énergie en 2018 dans son rapport « future of cooling ». Le présent projet propose une approche multidisciplinaire destinée à identifier et lever tous les verrous pouvant freiner ou limite le recours à la technologie de climatisation par eau de mer profonde (SWAC) avec pour objectifs opérationnels :
• D’identifier et anticiper les freins et verrous environnementaux, sociaux et sociétaux.
• D’étudier le potentiel de valorisation industrielle agronomique des rejets d’eau de mer en sortie de process SWAC
• D’étudier les possibilités d’exploitation de la ressource pour la cogénération froid/électricité
• Définir les stratégies d’intégration de ces technologies pour des bâtiments et quartiers plus durables
• De procédé à une optimisation multifactorielle tenant compte de l’intégralité des problématiques
Le projet apportera des connaissances et des outils nouveaux pour la conception des futurs installations SWAC et permettra des améliorations SWAC sur le fonctionnement des installations existantes. Grace à l’approche multidisciplinaire, il permettra de d’anticiper les potentiels freins à l’implantation de la technologie SWAC dans tous les territoires disposant d’eau froide à proximité des côtes et apportera toute les réponses d’ordre énergétique, environnemental, sociétal et économique attendues par les concepteurs et donneurs d’ordre.
The Sea Water Air Conditioning (SWAC) technology, using deep-sea cold water, remains widely underutilized worldwide due to its limited understanding and requiring substantial investments. However, it efficiently air conditions existing buildings and districts and reduces consumption, power demand, and CO2 emissions by a factor of ten. In the context of climate change and successive heatwaves, the demand for active cooling equipment in buildings is expected to surge beyond the predictions made by the International Energy Agency in its 2018 'Future of Cooling' report.
This project proposes a multidisciplinary approach to identify and overcome any barriers that may hinder or limit the adoption of deep-sea water air conditioning (SWAC) technology, with the following operational objectives:
• Identify and anticipate environmental, social, and societal barriers and obstacles.
• Study the potential industrial and agricultural valorization of seawater discharges from the SWAC process.
• Explore opportunities for utilizing the resource for cold/electricity co-generation.
• Define integration strategies for these technologies in more sustainable buildings and districts.
• Carry out multifactorial optimization, taking into account all relevant issues.
The project will provide new knowledge and tools for designing future SWAC installations and will highlight improvements for existing SWAC facilities. Through a multidisciplinary approach, it will enable the anticipation of potential barriers to the implementation of SWAC technology in all regions with cold water near the coasts. It will provide answers to energy, environmental, societal, and economic issues expected by designers and decision-makers. The MAEVA project will thus promote SWAC as a sustainable and resilient air conditioning technology."
Energie durable, propre, sûre et efficace
Sustainable, clean, safe and efficient energy
ANR
Frédéric Rychen (frederic.rychen@univ-amu.fr)
December 01st 2021 to May 31st 2025
The growing use of artificial intelligence and Machine Learning (ML) by banks and Fintech companies is one of the most significant changes in technology being integrated in the financial industry over past decades. In a recent report (ACPR, 2018), the French Prudential Supervision and Resolution Authority evaluates the disruptive potential of ML and concludes that it raises subject to mixed judgements. On the one hand, this set of new techniques holds great promise for the future of financial services. On the other hand, its practical applications still face many unresolved challenges. Within this context, the MLEforRisk project aims to provide better understanding of the usefulness of the combination of ML and econometrics for financial risk measurement. MLEforRisk is a multi-disciplinary project in the fields of finance and financial econometrics, which brings together senior and junior researchers in business, economics, and applied mathematics.
The growing use of artificial intelligence and Machine Learning (ML) by banks and Fintech companies is one of the most significant changes in technology being integrated in the financial industry over past decades. In a recent report (ACPR, 2018), the French Prudential Supervision and Resolution Authority evaluates the disruptive potential of ML and concludes that it raises subject to mixed judgements. On the one hand, this set of new techniques holds great promise for the future of financial services. On the other hand, its practical applications still face many unresolved challenges. Within this context, the MLEforRisk project aims to provide better understanding of the usefulness of the combination of ML and econometrics for financial risk measurement. MLEforRisk is a multi-disciplinary project in the fields of finance and financial econometrics, which brings together senior and junior researchers in business, economics, and applied mathematics.
ANR
Sébastien LAURENT (sebastien.laurent[at]univ-amu.fr)
March 01st 2021 to October 31st 2025
Dans un contexte d’économie circulaire, le projet RECALL propose d’extraire les métaux de valeur (fer et métaux critiques) dans un déchet minier : les résidus de bauxite. Du fait de l’importance économique des métaux critiques (ils sont présents dans de nombreuses applications émergentes) et leur fort risque d’approvisionnement, la production de ces métaux à partir de sources secondaires apparaît comme une voie inévitable pour de pérenniser ces nouvelles filières économiques. Ainsi, ce projet propose de développer des procédés "doux" d’extraction (procédés physico-chimique et bio-inspiré) en se basant sur une caractérisation fine des déchets et de la spéciation des métaux et sur une analyse socio-économique. Ce projet sera un tremplin pour cette thématique identifiée comme stratégique par le CEREGE et permettra d’initier des collaborations internationales (Horizon Europe). Ce projet d’intérêt scientifique, économique et sociétal est soutenu par l’institut de l’économie circulaire.
In the context of a circular economy, the RECALL project aims at extracting valuable metals in mining waste: bauxite residues. Due to the economic importance of critical metals (they are present in many emerging applications) and their high supply risk, production from secondary resources appears to be inevitable in order to sustain these new economic sectors. Thus, this project proposes to develop environmentally sustainable extraction processes (soft physico-chemical and bio-inspired processes) to recover these metals, with thorough characterization of the waste and metal speciation and the evaluation of social welfare associated with the process being developed. This research project will be a springboard for this research topic identified as strategic by the CEREGE lab and for initiating collaborative project (EU calls, Horizon Europe). This project, not only of scientific interest, but also of economic and societal interest, is supported by the French Institute of Circular Economy.
ANR
Dominique Ami (dominique.ami[at]univ-amu.fr)
December 01st 2021 to June 29th 2026
Le comportement prosocial est motivé non seulement par les incitations formelles, mais aussi par des préoccupations d'image, image de soi et image sociale. Alors qu'il existe une littérature sur préoccupations d'image et comportement éthique, les interactions entre l'image de soi et l'image sociale n'ont pas encore été étudiées. Dans SOSELF, nous proposons de combler cette lacune en utilisant une combinaison de théorie, d'expériences de laboratoire et de méthodes empiriques. Nous explorerons comment l’image sociale et l'image de soi sont liées par un principe de cohérence et comment leurs interactions entraînent des réponses comportementales à l'environnement. Nous étudierons ensuite l’effet de l'une des principales interventions utilisées pour promouvoir un comportement prosocial, les rappels moraux. SOSELF peut éclairer les politiques publiques dans un large éventail de domaines, et nous étudierons en particulier l'impact d'interventions comportementales sur la culture d’entreprise.
Prosocial behavior is driven, not only by formal incentives, but also by image concerns, both self- and social image. While there is a growing literature on the consequences of image concerns on ethical behavior, the interactions between self-and social-image have not been studied yet. In SOSELF, we propose a comprehensive approach to fill this gap. Our project will use a combination of theory, laboratory experiments and empirical methods relying on an interdisciplinary team. We will explore how social and self-image are tied together by a principle of coherence and how their interactions drive behavioral responses to the environment. Building on these results, we will study the optimal design of one of the main interventions used to promote prosocial behavior: moral reminders. SOSELF can inform policy in a wide range of domains, from fighting the circulation of fake news to fighting against corruption. We will in particular focus on how behavioral interventions modify firm culture
ANR
Stéphane Luchini (stephane.luchini[at]univ-amu.fr)
April 01st 2022 to March 31st 2026
Digitalization is the sociotechnical phenomenon of adopting information and communication technologies. Beyond wages and employment, this can have important effects on non-pecuniary (NP) working conditions, job satisfaction and wellbeing at work. Our objective is to understand how digitalization affects these dimensions of work, as well as how it affects the way individuals tradeoff wages and NP work conditions. The nature of social distancing during the COVID pandemic and the reliance of telecommuting on digital technologies have pushed these issues into the limelight. Therefore, we will also study the effects of digitalization in the context of the pandemic.
We ask whether and how digitalization impacts various dimensions of working conditions – hours, flexibility, mobility, physical effort, autonomy, team work, etc. – and thus job satisfaction and occupational choices. Taking into account non-pecuniary aspects of job quality is important because both wages and NP work conditions are considered by workers deciding on labor supply – and by employers deciding on labor demand – and there is reason to believe that they have not evolved in lockstep. One of the goals of project WRKCOV19 is to deepen our understanding of how new digital technologies (DTs) affect the joint evolution of wage and working conditions. The importance of this issue has recently been magnified by the COVID-19 crisis, as many employers and workers have dramatically increased their use of DTs in order to promote remote work and limit human contact in the workplace. Little is known about the impact of this radical re-organization on working conditions and wellbeing at work. And while vaccination campaigns will gradually remove many such barriers, much of the working conditions landscape will not return to the status quo ante.
Digitalization is the sociotechnical phenomenon of adopting information and communication technologies. Beyond wages and employment, this can have important effects on non-pecuniary (NP) working conditions, job satisfaction and wellbeing at work. Our objective is to understand how digitalization affects these dimensions of work, as well as how it affects the way individuals tradeoff wages and NP work conditions. The nature of social distancing during the COVID pandemic and the reliance of telecommuting on digital technologies have pushed these issues into the limelight. Therefore, we will also study the effects of digitalization in the context of the pandemic.
We ask whether and how digitalization impacts various dimensions of working conditions – hours, flexibility, mobility, physical effort, autonomy, team work, etc. – and thus job satisfaction and occupational choices. Taking into account non-pecuniary aspects of job quality is important because both wages and NP work conditions are considered by workers deciding on labor supply – and by employers deciding on labor demand – and there is reason to believe that they have not evolved in lockstep. One of the goals of project WRKCOV19 is to deepen our understanding of how new digital technologies (DTs) affect the joint evolution of wage and working conditions. The importance of this issue has recently been magnified by the COVID-19 crisis, as many employers and workers have dramatically increased their use of DTs in order to promote remote work and limit human contact in the workplace. Little is known about the impact of this radical re-organization on working conditions and wellbeing at work. And while vaccination campaigns will gradually remove many such barriers, much of the working conditions landscape will not return to the status quo ante.
ANR
Eva Moreno-Galbis (eva.moreno-galbis[at]univ-amu.fr)
