Du capitalisme familial au capitalisme financier? : le cas de l'industrie suisse des machines, de l'électrotechnique et de la métallurgie au 20e siècle

L'objectif principal de cette thèse consiste à mettre en évidence la persistance du capitalisme familial en Suisse au cours du 20e siècle, et sa résistance aux capitalismes managérial et financier qui sont censés lui avoir succédé. Pour ce faire, nous avons retenu vingt-deux grandes entreprises du secteur des machines, de l'électrotechnique et de la métallurgie - principale branche de l'industrie suisse pour la période considérée -, pour lesquelles ont été recensés les membres des conseils d'administration et les principaux dirigeants exécutifs pour cinq dates- repère couvrant le siècle (1910, 1937, 1957, 1980 et 2000). Cette thèse s'inscrit dans une démarche pluridisciplinaire qui relève à la fois de l'histoire d'entreprise et de la sociologie des dirigeants, et fait appel à différentes méthodes telles que l'analyse de réseau et l'analyse prosopographique. Elle s'articule autour de trois axes de recherche principaux : le premier vise à mettre en évidence l'évolution des modes de gouvernance dans notre groupe d'entreprises, le second investit la question de la coordination patronale et le troisième a pour but de dresser un portrait collectif des élites à la tête de nos vingt-deux firmes. Nos résultats montrent que durant la majeure partie du siècle, la plupart de nos entreprises sont contrôlées par des familles et fonctionnent sur un mode de coordination hors marché qui repose notamment sur un réseau dense de liens interfirmes, le profil des dirigeants restant dans l'ensemble stable. Si la fin du siècle est marquée par plusieurs changements qui confirment l'avènement d'un capitalisme dit financier ou actionnarial et la mise en place de pratiques plus concurrentielles parmi les firmes et les élites industrielles, le maintien du contrôle familial dans plusieurs entreprises et la persistance de certains anciens mécanismes de coopération nous incitent cependant à nuancer ce constat. - The main objective of this research is to highlight the persistence of family capitalism in Switzerland during the 20th century and its resistance to managerial and financial capitalisms that succeeded. For this purpose, we focus on twenty- two big companies of the machine, electrotechnical and metallurgy sector - the main branch of the Swiss industry for the considered period - whose boards of directors and executive managers have been identified for five benchmarks across the century (1910, 1937, 1957, 1980 and 2000). This thesis relates to business history and elites sociology, and uses different methods such as network analysis and prosopography. It is articulated around three main parts. The aim of the first one is to identify the evolution of corporate governance in our twenty-two enterprises, the second part concentrates on interfirms coordination and the objective of the last one is to highlight the profile of the corporate elite leading our firms. Our results show that during the main part of the century, most of the companies were controlled by families and were characterized by non-market mechanisms of coordination such as interlocking directorates ; moreover, the profile of the corporate elite remained very stable. Although some major changes that took place by the end of the century confirmed a transition towards financial capitalism and more competitive interaction among firms and the corporate elite, the persistence of family control in several companies and the maintaining of some former mechanisms of coordination allow us to put this evolution into perspective.

On exiting after voting

We consider the problem of a society whose members must choose from a finite set of alternatives. After knowing the chosen alternative, members may reconsider their membership in the society by either staying or exiting. In turn, and as a consequence of the exit of some of its members, other members might now find undersirable to belong to the society as well. We analyze the voting behavior of members who take into account the effect of their votes not only on the chosen alternative, but also on the final composition of the society

Modelling ecological niches with support vector machines

1. The ecological niche is a fundamental biological concept. Modelling species' niches is central to numerous ecological applications, including predicting species invasions, identifying reservoirs for disease, nature reserve design and forecasting the effects of anthropogenic and natural climate change on species' ranges. 2. A computational analogue of Hutchinson's ecological niche concept (the multidimensional hyperspace of species' environmental requirements) is the support of the distribution of environments in which the species persist. Recently developed machine-learning algorithms can estimate the support of such high-dimensional distributions. We show how support vector machines can be used to map ecological niches using only observations of species presence to train distribution models for 106 species of woody plants and trees in a montane environment using up to nine environmental covariates. 3. We compared the accuracy of three methods that differ in their approaches to reducing model complexity. We tested models with independent observations of both species presence and species absence. We found that the simplest procedure, which uses all available variables and no pre-processing to reduce correlation, was best overall. Ecological niche models based on support vector machines are theoretically superior to models that rely on simulating pseudo-absence data and are comparable in empirical tests. 4. Synthesis and applications. Accurate species distribution models are crucial for effective environmental planning, management and conservation, and for unravelling the role of the environment in human health and welfare. Models based on distribution estimation rather than classification overcome theoretical and practical obstacles that pervade species distribution modelling. In particular, ecological niche models based on machine-learning algorithms for estimating the support of a statistical distribution provide a promising new approach to identifying species' potential distributions and to project changes in these distributions as a result of climate change, land use and landscape alteration.

Classification of very high spatial resolution imagery using mathematical morphology and support vector machines

We investigate the relevance of morphological operators for the classification of land use in urban scenes using submetric panchromatic imagery. A support vector machine is used for the classification. Six types of filters have been employed: opening and closing, opening and closing by reconstruction, and opening and closing top hat. The type and scale of the filters are discussed, and a feature selection algorithm called recursive feature elimination is applied to decrease the dimensionality of the input data. The analysis performed on two QuickBird panchromatic images showed that simple opening and closing operators are the most relevant for classification at such a high spatial resolution. Moreover, mixed sets combining simple and reconstruction filters provided the best performance. Tests performed on both images, having areas characterized by different architectural styles, yielded similar results for both feature selection and classification accuracy, suggesting the generalization of the feature sets highlighted.

Nouveau manuel complet du tisserand, ou Description des procédés et machines employés pour les divers tissages des matières organiques filamenteuses ; suivi d'une Histoire de la filature et du tissage, depuis les temps les plus reculés jusqu'à nos jours / par E. Lorentz et C.-E. Jullien,...

Collection : Manuels Roret

On the Condition Monitoring of Induction machines

The research of condition monitoring of electric motors has been wide for several decades. The research and development at universities and in industry has provided means for the predictive condition monitoring. Many different devices and systems are developed and are widely used in industry, transportation and in civil engineering. In addition, many methods are developed and reported in scientific arenas in order to improve existing methods for the automatic analysis of faults. The methods, however, are not widely used as a part of condition monitoring systems. The main reasons are, firstly, that many methods are presented in scientific papers but their performance in different conditions is not evaluated, secondly, the methods include parameters that are so case specific that the implementation of a systemusing such methods would be far from straightforward. In this thesis, some of these methods are evaluated theoretically and tested with simulations and with a drive in a laboratory. A new automatic analysis method for the bearing fault detection is introduced. In the first part of this work the generation of the bearing fault originating signal is explained and its influence into the stator current is concerned with qualitative and quantitative estimation. The verification of the feasibility of the stator current measurement as a bearing fault indicatoris experimentally tested with the running 15 kW induction motor. The second part of this work concentrates on the bearing fault analysis using the vibration measurement signal. The performance of the micromachined silicon accelerometer chip in conjunction with the envelope spectrum analysis of the cyclic bearing faultis experimentally tested. Furthermore, different methods for the creation of feature extractors for the bearing fault classification are researched and an automatic fault classifier using multivariate statistical discrimination and fuzzy logic is introduced. It is often important that the on-line condition monitoring system is integrated with the industrial communications infrastructure. Two types of a sensor solutions are tested in the thesis: the first one is a sensor withcalculation capacity for example for the production of the envelope spectra; the other one can collect the measurement data in memory and another device can read the data via field bus. The data communications requirements highly depend onthe type of the sensor solution selected. If the data is already analysed in the sensor the data communications are needed only for the results but in the other case, all measurement data need to be transferred. The complexity of the classification method can be great if the data is analysed at the management level computer, but if the analysis is made in sensor itself, the analyses must be simple due to the restricted calculation and memory capacity.