What happened to entrepreneurial economies after the financial crisis? An empirical study of OECD countries

The aim of this paper is to analyze entrepreneurial activity in OECD countries over the period 1999-2012 in order to make a distinction between economies that are more or less entrepreneurial. A combined use of multidimensional and evolutive data analysis methods is used with variables pertaining to entrepreneurial activity and growth. It allows us to distinguish several types of development. Furthermore, three main periods are found, before, during and after the crisis. The pre-crisis period, from 1999 to 2008, was a period of growth favorable to entrepreneurship while the sub-period 2010-2012 is less favorable. The effects of the financial crisis are noticeable after a delay in 2009. We show that in 2009, the agricultural economies have best withstood the financial crisis. Secondly, during the period 2010-2012 after the crisis, economies widely dependent on the financial sector were most impacted by the financial crisis. Because of the financial crisis, the entrepreneurial dynamics vary greatly across countries over the period 1999-2012, however we were able to establish common trajectories for a number of the

Exploring digitalisation in the agri-food sector and its paradoxes: Evidence from a comparative study with small French companies

This paper discusses the results of a study on the digitalisation of the agri-food sector in a French region characterised by small- and medium-sized farms. Our results, which rely on a survey comparing digital practices in the agri-food sector with other sectors, reveal a paradox. While digitalisation is mostly perceived as a panacea capable of increasing agricultural pro- ductivity while respecting the planet, it is not widespread in the agri-food sector and even less than in other sectors of the same size. At the same time, the perceived impact of digitalisation is also lower than in other sectors. To increase the digitalisation of this sector, two elements emerge from our results: both the implementation of a global digital transformation strategy and membership of a professional association are required. Here, we refer to a broad definition of digitalisation, which includes organisational and social aspects, and does not only address technological dimensions. Our study challenges the technocen- tric and productive vision of digitalisation. It suggests that farmers’ institutional environments and policies need to take a more holistic view of digitalisation to provide increased sense and generate engagement

Glioma Through the Looking GLASS: Molecular Evolution of Diffuse Gliomas and the Glioma Longitudinal AnalySiS Consortium

Adult diffuse gliomas are a diverse group of brain neoplasms that inflict a high emotional toll on patients and their families. The Cancer Genome Atlas (TCGA) and similar projects have provided a comprehensive understanding of the somatic alterations and molecular subtypes of glioma at diagnosis. However, gliomas undergo significant cellular and molecular evolution during disease progression. We review the current knowledge on the genomic and epigenetic abnormalities in primary tumors and after disease recurrence, highlight the gaps in the literature, and elaborate on the need for a new multi-institutional effort to bridge these knowledge gaps and how the Glioma Longitudinal AnalySiS Consortium (GLASS) aims to systemically catalog the longitudinal changes in gliomas. The GLASS initiative will provide essential insights into the evolution of glioma toward a lethal phenotype, with the potential to reveal targetable vulnerabilities, and ultimately, improved outcomes for a patient population in need

Cas pédagogique (AQS0925-1) : Mesurer et expliquer l'intention d'usage d'une nouvelle technologie

Objectifs pédagogiquesa. Connaître des fondamentaux statistiques utiles en gestion, en appliquant des concepts vus en cours dans un contexte concret ;b. Gérer une base de données originale ;c. Mettre en pratique les outils mathématiques et statistiques d'analyse, tels que les tableaux et les graphiques, les mesures de tendance centrale ou de dispersion, les coefficients d'association et de corrélation ;d. Interpréter les résultats afin de caractériser correctement une population, les liens entre différentes variables et tirer des conclusions pertinentes ;e. Mettre en place une étude quantitative complète, de la formulation d'hypothèses jusqu'à l'interprétation des résultats en passant par de la conception du questionnaire.Le cas contribue également au développement de compétences transversales, telles que :a. Capacité d'analyse et de synthèse d'une situation complexe, en reliant les concepts théoriques aux données collectées ;b. Capacité de travail en équipe, en organisant et coordonnant les différentes étapes de l'étude statistique ;c. Capacité de communication et de restitution, en présentant les résultats et recommandations de manière claire et argumentée lors de la soutenance.Ce cas propose aux étudiant·e·s de mesurer et d'expliquer l'intention d'utiliser une nouvelle technologie à partir d'un questionnaire basé sur la littérature académique et la Théorie UTAUT (Venkatesh et al., 2003). Étude « fil rouge » intégrée au cours de statistiques descriptives, elle permet d'appliquer progressivement les concepts et méthodes vus en classe.Les étudiant·e·s suivent la démarche statistique complète : choix de l'objet, population, échantillonnage, collecte et codage des données, analyses descriptives, formulation et vérification d'hypothèses. L'utilisation d'Excel (tableaux, graphiques, corrélations) leur permet d'acquérir une méthodologie quantitative, de la conception du questionnaire à l'interprétation des résultats

Les politiques publiques face aux plateformes digitales : Exemple de la Normandie

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Digital plateforms: new intermediations, new proximities to rethink the territorial development

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L’éducation entrepreneuriale au collège : développer un état d’esprit d’entreprendre

International audienceThe French association Entreprendre Pour Apprendre (EPA), which aims to “foster the entrepreneurial spirit ofyoung people,” announced in 2016 that it had supported only 27,000 young people out of nearly 13 millionstudents and apprentices in the French school system. Thus, despite political recommendations, it appearsthat entrepreneurship education remains restricted to those enrolled in higher education.Based on an example of a mini-enterprise in a collège (secondary school), this article proposes to explore thestudents’ representations and experiences of the project. The objective is to observe how an entrepreneurialexperience leads to the mobilization of different resources, the development of skills, and, more generally,the creation of an entrepreneurial spirit among students. This work allows us to enrich the reflection on therole that entrepreneurial education should have in collèges, as well as the conditions of its deployment.L’association Entreprendre Pour Apprendre (EPA), dont l’objectif est de « favoriser l’esprit d’entreprendre desjeunes » annonçait en 2016 avoir accompagné seulement 27 000 jeunes sur près de 13 000 000 d’élèves etapprentis scolarisés. Ainsi, malgré les préconisations politiques, il semble que l’éducation entrepreneurialereste restreinte à l’enseignement supérieur.Cet article propose, à partir d’un exemple de mini-entreprise au collège, d’explorer les représentations descollégiens et la manière dont ils ont vécu le projet. L’objectif est d’observer comment le dispositif conduit àmobiliser différentes ressources, développer des compétences et, de manière plus générale, l’esprit d’entreprendredes élèves. Ce travail nous permet d’enrichir la réflexion sur la place à donner à l’éducation entrepreneurialeau collège ainsi que les conditions de son déploiement

Diversify Approaches to Better Understand the Compatibility of Artificial Intelligence and Sustainability: “I Love You… Me Neither”

International audienceThe aim of this article is twofold: 1. Suggest an overview of current knowledge and understanding of both concepts and 2. Present the six contributionsand their positioning in relation to current the literature linked to artificial intelligence and sustainability. For that, we use different but complementary sources. First, we ask artificial intelligence to reveal the mainstream view. Then we call on human intelligence to provide a critical perspective.Finally, we carry out a bibliometric analysis using the SCOPUS database and two different statistical analyses (the CCA – co-citation analysis, theBCA – bibliographic coupling analysis). The diversity of the sources used, and their complementarity allow us to propose a holistic vision of the subject,highlighting the concerns that surround it and identifying future avenues of research for academics. The articles selected in this special issue fill some ofthe gaps raised and call for further research