The first objective of this study was to identify the economic intelligence requirements of two organizations providing support to start-ups in Western Switzerland (Genilem and Fongit) and to define recommendations to address their key issues. The second objective was to identify needs common to the two institutions and to suggest a set of measures that could be used on a regional scale to rationalize the use of resources. Data were collected through about 20 interviews involving both start up managers and collaborators of the coaching companies. A questionnaire has been sent to most of the companies which had received support from these administrative bodies. As a result, 2 lists of about 15 guidelines were given to Genilem and Fongit. Furthermore, practical measures and a better task allocation have been suggested to the regional support partners. Ultimately, this research helped both Fongit and Genilem to improve their practices. It also served to provide a reflection on what should be considered as essential support for entrepreneurship in the cantons of Vaud and Geneva. In addition, the study offers an innovative methodology for the analysis of the need for economic intelligence.
This paper presents the important elements of doctoral research into archival science at the Université de Montréal – Ecole de bibliothéconomie et des sciences de information, about the definition and the measurement of the dimensions of quality applied to historical archives. It focuses mainly on three questions: first, what are intrinsic and extrinsic archival qualities; second, what conceptual framework can integrate and structure various dimensions of intrinsic and extrinsic qualities of archival documents; third, which indicators and variables should be tested to verify the measurability of these qualities. After developing a conceptual framework distinguishing four dimensions of quality of archives, a quantitative and descriptive study was conducted to confirm the measurability of fourteen variables of two of these four dimensions that were measured: the credible evidence as an intrinsic dimension example and the exploitability as an extrinsic dimension example.
The demand forecast is the most influential input into enterprise activities planning thus creating a challenging issue for Demand Planning experts in model selection. Models including quantitative, qualitative and hybrid forecasting methods have been developed and are widely used. The literature reveals the use of several case-dependent error measures to evaluate forecasting accuracy, however, these performance indicators may at times differentiate in results making it more difficult in determining the most appropriate forecasting model for the users’ needs. This paper presents the development of two hybrid multi-criteria decision making approaches, AHP-TOPSIS and ANP-TOPSIS, to evaluate and rank the relative performances based on error measures of alternate forecasting models. Validation is provided through an industrial application using empirical data from a plastic bag manufacturer based on five models
We propose a new method for input variable selection in nonlinear regression. The method is embedded into a kernel regression machine that can model general nonlinear functions, not being a priori limited to additive models. This is the first kernel-based variable selec- tion method applicable to large datasets. It sidesteps the typical poor scaling properties of kernel methods by mapping the inputs into a relatively low-dimensional space of random features. The algorithm discovers the variables relevant for the regression task together with learning the prediction model through learning the appropriate nonlinear random feature maps. We demonstrate the outstanding performance of our method on a set of large-scale synthetic and real datasets.
This paper studies the effects of estate recovery, estate taxation and long-term care (LTC) subsidies on the incentives both to buy LTC insurance and to transfer wealth by elderly parents and to provide informal care by children to their dependent elderly parents. We also investigate the effect of these three fiscal policies on public budgets allocated to finance LTC needs. Estate recovery is found to dominate the two other fiscal policies as it is more likely to incentivise both LTC insurance purchase and informal care supply while impacting positively government budget.
