In this paper, we examine the efficiency of the sort done by the Swiss lower secondary school tracking system, looking at students’ outcomes in dual vocational education and training (VET)—the most common education type at the upper secondary level in the country. We discuss a simple Ricardian model about the process of school tracking based on the absolute advantage (i.e., the ability) of students in abstract learning, as opposed to contextualised learning which is more decisive in dual VET. The mismatch created by the tracking system for certain types of students is key to explain the relative track effect on outcomes in dual VET. Using administrative panel data for the Canton of Geneva, we estimate a series of zero inflated models. All results support the assumption of a miss-allocation of students to lower secondary school tracks. We thus conclude that the efficiency of the sort related to the tracking system could be improved, were students sorted on the basis of their comparative and not absolute advantage in each form of learning.
L’article se focalise sur les pratiques actuelles d’évaluation, en Suisse et en France, dans le contexte des offres publiques d’achat. Les auteurs exposent successivement leur méthodologie, leurs principaux résultats et quelques enjeux pratiques et académiques.
We introduce a unified modeling and solution framework for various classes of rich vehicle and inventory routing problems as well as other probability-based routing problems with a time-horizon dimension. Demand is assumed to be stochastic and non-stationary, and is forecast using any forecasting model that provides expected demands over the planning horizon, with error terms from any empirical distribution. We discuss possible applications to various problems from the literature and practice: from health care, waste collection, and maritime inventory routing, to routing problems based on event probabilities, such as facility maintenance where the breakdown probability of a facility increases with time. We provide a detailed discussion on the effects of the stochastic dimension on modeling and the solution methodology. We develop a mixed integer non-linear model, provide examples of how it can be reduced and adapted to specific problem classes, and demonstrate that probability-based routing problems over a planning horizon can be seen through the lens of inventory routing. The optimization methodology is heuristic, based on Adaptive Large Neighborhood Search. The case study is based on waste collection and facility maintenance instances derived from real data. We analyze the cost benefits of open tours and the availability of better forecasting methodologies. We demonstrate that relaxing the distributional assumptions on the error terms and calculating probabilities using simulation information has only a minor impact on computation time. Simulating the error terms on the final solution further allows us to verify the low level of occurrence of undesirable events, such as stock-outs, overflows or breakdowns, with a moderate impact on the routing cost compared to alternative realistic policies. What is more, simulating the objective of the final solution shows that it is an excellent representation of the real cost.
The increasing interdependence of firms and individuals throughout the world facilitates the development of the crowdlending market. Crowdlending is an emerging source of financing involving open calls to the public, generally via internet, to finance with loans individuals or companies (Meyer, 2007). The major role of crowdlending activities has been to bring new energy to a global economy that is unable to catch its breath following the recent financial crises (Berger, 2009). North America leads the world in crowdlending volumes, representing 58% of the world's market. But the global strong growth is due, in part, to the rise of Asia as a major crowdlending player with 21% of the world's market, putting the region slightly ahead of Europe (Pignon. 2015). As of today, Switzerland has not adopted specific regulation governing the practice of crowdlending, but the regulator has issued a fact sheet on this topic, informing the stakeholders of the crowdlending industry that some of their activities may be subject to banking regulation (Dietrich, 2015). In this context, this article get a general overview of the regulations adopted abroad, in particular in the USA and in the European Union, where countries such as the UK or France chose to adopt a more detailed regulation, some with financial limits applicable to crowdlending campaigns or with specific requirements regarding who would be authorized to invest in crowdlending campaigns or soft regulation in the form of Best Practices.
Il suffit parfois d’un détail pour qu’une organisation échoue à atteindre ses objectifs, alors même que la stratégie a été longuement réfléchie, que les compétences sont présentes, tout comme les volontés individuelles. Mais lequel? Tenter de répondre à cette question, c’est interroger la culture de l’entreprise. Le manager de terrain n’est parfois ni un expert, ni un stratège, et bien qu’il soit l’un des maillons essentiels de la mise en application de la stratégie choisie, certains principes en vigueur peuvent l’empêcher d'exploiter son plein potentiel. Si les techniques issues du management scientifique peuvent apporter une solution partielle, elles doivent également être accompagnées d’une approche moins cartésienne. L’efficience de la pratique managériale ne réside pas uniquement dans l’application de méthodes simples et ordinaires. Encore faut-il que celles-ci s’intègrent au système complexe dans lequel évolue le manager. C’est afin de procurer aux futurs gestionnaires d’entreprise une vue pratique et synthétique des méthodes d’organisation du travail que cet ouvrage a été conçu. Il retrace les principales évolutions de cette discipline et expose les bases essentielles du management scientifique, tout comme celles du management moderne, sous un angle socio-psychologique. Ce livre se destine principalement aux étudiants débutant un cursus en gestion d’entreprise, mais il sera également précieux pour tous les managers de terrain désireux de revisiter les fondamentaux de leur fonction ou la pertinence de leur pratique.
This paper presents a new Moodle activity called “e-voting”. This activity brings wider interaction inside large face-to-face classes. The paper presents how interactions can be supported and enhanced by engaging students, and also by enabling professors to work on initial concepts in a flipped-class or distance learning contexts. This paper describes the three different pedagogical models, proposes scenarios to be used. It presents the e-voting activity on Moodle, its advantages, its functioning and availability for the Moodle community.
Research in the health-care domain requires the collection of important and exhaustive datasets, in order to validate a scientific hypothesis, or to assess the effectiveness of a treatment, technology, medicine, or procedure. The data acquisition phase for this type of work requires an often under-estimated amount of time and effort, while needing to keep high quality standards for the entire process. Many of the tasks associated with data acquisition are often carried out manually, resulting in error-prone procedures, hand-transcription, inaccuracy, and time delays to produce a resulting usable dataset. This paper presents MedRed (Medical Research Data Acquisition Platform ), a platform and a service designed to facilitate the data acquisition process for researchers in the health-care do-main, using the REDCap software for data capture. This service is available in a first stage, for all scientists of the HES-SO (University of Applied Sciences and Arts Western Switzerland) schools in Switzerland, and partially supported by the SwissUniversities CUS-P2 program.
We present texture operators encoding class-specific local organizations of image directions (LOIDs) in a rotation-invariant fashion. The LOIDs are key for visual understanding, and are at the origin of the success of the popular approaches, such as local binary patterns (LBPs) and the scale-invariant feature transform (SIFT). Whereas, LBPs and SIFT yield hand-crafted image representations, we propose to learn data-specific representations of the LOIDs in a rotation-invariant fashion. The image operators are based on steerable circular harmonic wavelets (CHWs), offering a rich and yet compact initial representation for characterizing natural textures. The joint location and orientation required to encode the LOIDs is preserved by using moving frames (MFs) texture representations built from locally-steered image gradients that are invariant to rigid motions. In a second step, we use support vector machines to learn a multi-class shaping matrix for the initial CHW representation, yielding data-driven MFs called steerable wavelet machines (SWMs). The SWM forward function is composed of linear operations (i.e., convolution and weighted combinations) interleaved with non-linear steermax operations. We experimentally demonstrate the effectiveness of the proposed operators for classifying natural textures. Our scheme outperforms recent approaches on several test suites of the Outex and the CUReT databases.
The introduction of new products is often seen as an attractive strategy that improves firm performance. However, because novelty can endanger local traditions and decrease attachment to existing stakeholders, launching new products can result in an arduous enterprise, in particular, in industries that value tradition. This paper elaborates on the resources and strategies upon which firms can rely to introduce novelty in traditional industries. In particular, family firms enjoy unique identity advantages over non-family firms that allows them to introduce new products in a legitimate way. This advantage can be better materialized when family firms make use of naming strategies by referring to their traditions in their product labels and serving geographically disconnected consumers. I test these predictions using data about more than 300 breweries in Franconia, a geographical cluster in Northern Bavaria (Germany) and one of the most traditional industries in Europe. The results of this study confirm that family firms are more likely to engage in the introduction of new beer types, especially those that are named using words that recall the traditional identity of the firm. Moreover, we also find support for the idea that these strategies are more common when firms serve geographically distant portions of the market.
