3 resultados para case study method

em Corvinus Research Archive - The institutional repository for the Corvinus University of Budapest


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Today’s business leaders must constantly review and develop their firm’s abilities to adapt to and benefit from external changes. Dynamic capabilities are the capacity of an organization to purposefully create, extend or modify its resource base. They enable it to exploit business, technological and market opportunities and adapt to market changes, an ability more often observed in highly dynamic industries, such as consumer electronics or telecommunications. Using the case study method, this article identifies dynamic capabilities in traditional, less dynamic industries when faced with a sudden drop of revenue. Four distinct routines emerge, namely structure and practices enduring time-sensitive strategic decision-making by the tice, and a culture encouraging learning and coevolving. Seemingly strategic paradox objectives encourage the management team to question the status quo and, when managed well, transform the tensions between old and new into an ability to advance superior ideas faster.

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Stylization is a common method of ornamental plant use that imitates nature and evokes the scenery. This paper discloses a not yet proposed aspect of stylization, since the method offers the possibility of preserving the physiognomy of those habitats that seem to vanish due to future climate change. In addition, novelty of the method is founded also on that vulnerability of the Hungarian habitats has been examined by the researchers only from the botanical and ecological point of view so far and not in terms of its landscape design value. In Hungary, acidofrequent mixed forests appear to be highly sensitive to climate change according to ecological models. We are going to discuss the methodology of stylization of climate sensitive habitats and briefly refer to acidofrequent mixed forests as a case study. Those coniferous and deciduous tree species of the studied habitat that are water demanding are proposed to be substituted by drought tolerant ones with similar characteristics, and an optionally expandable list of these taxa is presented. Based on this the authors suggest experimental investigations of those of the proposed taxa for which the higher drought tolerance is based on observations only.

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Regional climate models (RCMs) provide reliable climatic predictions for the next 90 years with high horizontal and temporal resolution. In the 21st century northward latitudinal and upward altitudinal shift of the distribution of plant species and phytogeographical units is expected. It is discussed how the modeling of phytogeographical unit can be reduced to modeling plant distributions. Predicted shift of the Moesz line is studied as case study (with three different modeling approaches) using 36 parameters of REMO regional climate data-set, ArcGIS geographic information software, and periods of 1961-1990 (reference period), 2011-2040, and 2041-2070. The disadvantages of this relatively simple climate envelope modeling (CEM) approach are then discussed and several ways of model improvement are suggested. Some statistical and artificial intelligence (AI) methods (logistic regression, cluster analysis and other clustering methods, decision tree, evolutionary algorithm, artificial neural network) are able to provide development of the model. Among them artificial neural networks (ANN) seems to be the most suitable algorithm for this purpose, which provides a black box method for distribution modeling.