Préparation des PME familiales belges à la transmission et impact sur la performance

Une large littérature conceptuelle met en évidence les difficultés éprouvées lors de la transmission des entreprises familiales à la génération suivante. Ces développements théoriques ont été validés par de nombreuses études empiriques, même s’il subsiste des débats contradictoires. Les objectifs de cette recherche sont de déterminer si la préparation de la transmission a une influence sur la performance des PME familiales et si ces PME se heurtent à moins de problèmes. Une enquête, réalisée auprès de 2 000 PME, a permis de relever 159 transmissions et de collecter les informations concernant la transmission. Cet article utilise la méthodologie du pairage statistique de manière à comparer les performances de PME familiales préparées à la transmission à celles d’homologues non préparées. Les résultats obtenus ne permettent pas de montrer que les PME familiales préparées sont significativement plus performantes. Les résultats montrent néanmoins une évolution des performances des PME non familiales après la transmission (observée sur trois ans) encore plus négative en cas de non-préparation.A large part of the literature shows the difficulty for family firms to operate their transmission to the following generation. These theoretical developments were validated by many empirical studies, even if they remain debatable. The aim of this research is to determine if the preparation of succession has an influence on the performance of family SMEs, and to detect the principal succession problems of Belgian family SMEs. We therefore conducted a large inquiry in order to identify Belgian family SMEs and their main succession characteristics. This paper uses paired samples methodology to compare the performance of family SMEs prepared for succession with that of non-prepared family SMEs. The results do not show that the prepared family SMEs are significantly more competitive. The results show however an evolution in the performances of non-family SMEs after succession (over three years) that are even more negative if they are not prepared.Una amplia literatura conceptual subraya las dificultades encontradas en el momento de la transmisión de las empresas familiares a la generación siguiente. A pesar de que estos desarrollos teóricos fueran validados por numerosos estudios empíricos, aún permanecen en los debates. Los objetivos de esta investigación es determinar si la preparación de la sucesión tiene una influencia sobre el resultado de las PyMEs familiares y si estas PyMEs encuentran menos problemas. Una encuesta, realizada ante 2 000 PyMEs, permitió identificar 159 transmisiones y recoger la información relativa a la transmisión. Este artículo utiliza la metodología de los pares estadísticos para comparar el resultado de PyMEs familiares preparadas a la transmisión con las de homólogas no preparadas. Los resultados obtenidos no permiten demostrar que las PyMEs familiares preparadas son significativamente más competitivas. Los resultados demuestran sin embargo una evolución, todavía más negativa en caso de no preparación, del resultado de las PyMEs no familiares después de la transmisión (observada durante tres años)Die Schwierigkeiten von Nachfolgeregelungen in Familienunternehmen sind in der Literatur vor allem durch konzeptionelle Beiträge eingehend publiziert worden. Die darin dargelegten theoretischen Konzepte sind auch durch zahlreiche empirische Studien validiert worden, wobei Widersprüche weiterhin im Raum bestehen bleiben. Die vorliegende Studie versucht die Fragen zu beantworten, ob die Vorbereitung zur Nachfolge Einfluss auf die Leistung des Familienunternehmens hat und inwiefern diese Unternehmen mit weniger Problemen konfrontiert werden. Durch eine Umfrage bei 2000 KMU konnten 159 Betriebe identifiziert werden, die im Nachfolgeprozess. Der statistische Vergleich der Leistungen von vorbereiteten und unvorbereiteten Familien-KMU erbrachte keinen signifikanten Unterschied. Jedoch fällt die negative Leistungsentwicklung von Nicht-Familien-KMU (beobachtet über drei Jahre) auf, die sich nicht auf den Übergangsprozess vorbereitet haben

" La combinaison d'indicateurs comptables et de caractéristiques de propriété et de gestion permet-elle d'expliquer l'endettement financier des PME familiales ? "

International audienceL'étude économétrique présentée se concentre sur l'analyse des déterminants de l'endettement financier des PME. L'originalité de cet apport consiste à expliquer ce niveau d'endettement sur base de variables comptables, financières ainsi que de variables propres aux PME en terme de propriété et de gestion et à constater si le caractère familial d'une PME influence ce niveau d'endettement financier

SPOCC: Scalable POssibilistic Classifier Combination -- toward robust aggregation of classifiers

We investigate a problem in which each member of a group of learners is trained separately to solve the same classification task. Each learner has access to a training dataset (possibly with overlap across learners) but each trained classifier can be evaluated on a validation dataset. We propose a new approach to aggregate the learner predictions in the possibility theory framework. For each classifier prediction, we build a possibility distribution assessing how likely the classifier prediction is correct using frequentist probabilities estimated on the validation set. The possibility distributions are aggregated using an adaptive t-norm that can accommodate dependency and poor accuracy of the classifier predictions. We prove that the proposed approach possesses a number of desirable classifier combination robustness properties

Quantification des images couleur par un algorithme de classification crédibiliste

Nous proposons un algorithme de quantification des images couleur fondé sur la théorie de l'évidence. Dans ce cadre, le problème de quantification est vu comme un problème de classification non supervisée dans l'espace couleur. Partant d'un nombre de classes égal au nombre de couleurs de l'image originale, l'algorithme de classification crédibiliste estime itérativement de nouvelles partitions crédales. L'originalité du travail présenté repose sur la définition d'un nouveau critère contrôlant la convergence de l'algorithme permettant ainsi d'obtenir le nombre de classes désiré. La nouvelle palette couleur est calculée à partir de la partition crédale obtenue à la convergence de l'algorithme. Cette approche de quantification couleur par une méthode de classification non supervisée présente l'intérêt d'être complètement indépendante de toute initialisation. La méthode de quantification proposée, comparée à des méthodes de quantification existantes a montré son efficacité. En particulier, les résultats en terme de distorsion vis-à-vis de l'image originale sont meilleurs que ceux obtenus avec les autres méthodes testées

Extensive Natural Epigenetic Variation At A De Novo Originated Gene.

Epigenetic variation, such as heritable changes of DNA methylation, can affect gene expression and thus phenotypes, but examples of natural epimutations are few and little is known about their stability and frequency in nature. Here, we report that the gene Qua-Quine Starch (QQS) of Arabidopsis thaliana, which is involved in starch metabolism and that originated de novo recently, is subject to frequent epigenetic variation in nature. Specifically, we show that expression of this gene varies considerably among natural accessions as well as within populations directly sampled from the wild, and we demonstrate that this variation correlates negatively with the DNA methylation level of repeated sequences located within the 5'end of the gene. Furthermore, we provide extensive evidence that DNA methylation and expression variants can be inherited for several generations and are not linked to DNA sequence changes. Taken together, these observations provide a first indication that de novo originated genes might be particularly prone to epigenetic variation in their initial stages of formation.9e100343

Highly dynamic and sex-specific expression of microRNAs during early ES cell differentiation.

International audienceEmbryonic stem (ES) cells are pluripotent cells derived from the inner cell mass of the mammalian blastocyst. Cellular differentiation entails loss of pluripotency and gain of lineage-specific characteristics. However, the molecular controls that govern the differentiation process remain poorly understood. We have characterized small RNA expression profiles in differentiating ES cells as a model for early mammalian development. High-throughput 454 pyro-sequencing was performed on 19-30 nt RNAs isolated from undifferentiated male and female ES cells, as well as day 2 and 5 differentiating derivatives. A discrete subset of microRNAs (miRNAs) largely dominated the small RNA repertoire, and the dynamics of their accumulation could be readily used to discriminate pluripotency from early differentiation events. Unsupervised partitioning around meloids (PAM) analysis revealed that differentiating ES cell miRNAs can be divided into three expression clusters with highly contrasted accumulation patterns. PAM analysis afforded an unprecedented level of definition in the temporal fluctuations of individual members of several miRNA genomic clusters. Notably, this unravelled highly complex post-transcriptional regulations of the key pluripotency miR-290 locus, and helped identify miR-293 as a clear outlier within this cluster. Accordingly, the miR-293 seed sequence and its predicted cellular targets differed drastically from those of the other abundant cluster members, suggesting that previous conclusions drawn from whole miR-290 over-expression need to be reconsidered. Our analysis in ES cells also uncovered a striking male-specific enrichment of the miR-302 family, which share the same seed sequence with most miR-290 family members. Accordingly, a miR-302 representative was strongly enriched in embryonic germ cells derived from primordial germ cells of male but not female mouse embryos. Identifying the chromatin remodelling and E2F-dependent transcription repressors Ari4a and Arid4b as additional targets of miR-302 and miR-290 supports and possibly expands a model integrating possible overlapping functions of the two miRNA families in mouse cell totipotency during early development. This study demonstrates that small RNA sampling throughout early ES cell differentiation enables the definition of statistically significant expression patterns for most cellular miRNAs. We have further shown that the transience of some of these miRNA patterns provides highly discriminative markers of particular ES cell states during their differentiation, an approach that might be broadly applicable to the study of early mammalian development

ncPRO-seq: a tool for annotation and profiling of ncRNAs in sRNA-seq data

Summary: Non-coding RNA (ncRNA) PROfiling in small RNA (sRNA)-seq (ncPRO-seq) is a stand-alone, comprehensive and flexible ncRNA analysis pipeline. It can interrogate and perform detailed profiling analysis on sRNAs derived from annotated non-coding regions in miRBase, Rfam and RepeatMasker, as well as specific regions defined by users. The ncPRO-seq pipeline performs both gene-based and family-based analyses of sRNAs. It also has a module to identify regions significantly enriched with short reads, which cannot be classified under known ncRNA families, thus enabling the discovery of previously unknown ncRNA- or small interfering RNA (siRNA)-producing regions. The ncPRO-seq pipeline supports input read sequences in fastq, fasta and color space format, as well as alignment results in BAM format, meaning that sRNA raw data from the three current major platforms (Roche-454, Illumina-Solexa and Life technologies-SOLiD) can be analyzed with this pipeline. The ncPRO-seq pipeline can be used to analyze read and alignment data, based on any sequenced genome, including mammals and plants. Availability: Source code, annotation files, manual and online version are available at http://ncpro.curie.fr/. Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin