Full Text Available Car-building industry territorial reconfiguration in Europe is the result of several rounds of company delocations from origin countries to emergent countries. Such rounds have been limited by the gradual opening of the national countries, as well as by changes in East European ideology and politics. Hence, about the end of the 90’s, European car-building industry shows considerable disparity, East to West. In the car-building companies’ vision, East-European car-building development potential is basically sustained by both the car low penetration rate, and the low labor cost. On the long term run, gradual valorizing of the East-european trading, with increasing labor costs, may read as a wearing thin of the competitive advantage in car-building industries, as well as problem issues of novel territory attractiveness needing permanent boosting. Country-to-country comparative analysis indicates that competitive advantage of car-building has not gone down in all of the West-European States. Competitive advantage of the West-European car-building industry increases, which can be explained, in part, by adequate strategies, as both labor costs, and cars penetration rate, go up.
Full Text Available Revival of the Russian economy and the forecast of demand for rail transportation shows, that it is necessary to update park of freight cars which has undergone significant ageing for the lack of regular updating. In the given aspect the special role is got with strategic planning activity of the large car-building enterprise of the Ural federal district – Federal state unitary enterprise "Production association "Ural Carriage-Building Plant". Authors offer strategy of economic development of the given enterprise which contains the following directions: commodity and price strategy, bases of a marketing policy, increase of personnel potential of the enterprise, development of investment process, a Directions of research and developmental activity. The predicted estimation of results of development and introduction of offered strategy of economic development of the enterprise in 2007 − 2010 is made. Spillovers and the results expected from introduction of strategy at a microlevel and a macrolevel, in social and economic sphere and budgetary sphere are submitted.
Ramos, Daniel; Zadora, Grzegorz
Highlights: → A selection of the best features for multivariate forensic glass classification using SEM-EDX was performed. → The feature selection process was carried out by means of an exhaustive search, with an Empirical Cross-Entropy objective function. → Results show remarkable accuracy of the best variables selected following the proposed procedure for the task of classifying glass fragments into windows or containers. - Abstract: In this work, a selection of the best features for multivariate forensic glass classification using Scanning Electron Microscopy coupled with an Energy Dispersive X-ray spectrometer (SEM-EDX) has been performed. This has been motivated by the fact that the databases available for forensic glass classification are sparse nowadays, and the acquisition of SEM-EDX data is both costly and time-consuming for forensic laboratories. The database used for this work consists of 278 glass objects for which 7 variables, based on their elemental compositions obtained with SEM-EDX, are available. Two categories are considered for the classification task, namely containers and car/building windows, both of them typical in forensic casework. A multivariate model is proposed for the computation of the likelihood ratios. The feature selection process is carried out by means of an exhaustive search, with an Empirical Cross-Entropy (ECE) objective function. The ECE metric takes into account not only the discriminating power of the model in use, but also its calibration, which indicates whether or not the likelihood ratios are interpretable in a probabilistic way. Thus, the proposed model is applied to all the 63 possible univariate, bivariate and trivariate combinations taken from the 7 variables in the database, and its performance is ranked by its ECE. Results show remarkable accuracy of the best variables selected following the proposed procedure for the task of classifying glass fragments into windows (from cars or buildings) or containers