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Due to the decline of the Western European textile industry in the 1960s and international economic turbulences in the 1970s, the chemical fibre industry in Western Europe ran into trouble. The ten largest manufacturers of polyester fibres therefore applied for a structural crisis cartel in 1972. Even though the European Commission rejected the request, the question of a cartel agreement remained a topic of discussion at the European level for more than ten years. In June 1978, eleven European manufacturers of chemical fibres signed a cartel agreement in Brussels, but it was not compatible with the Treaty of the European Economic Community. It was not until 1980 that the companies submitted a new contract to the European Commission which was in accordance with antitrust law and renewed in 1982. The article analyses the course of negotiations as well as the driving forces and different aims of political and industrial players on the national and the European level. [ABSTRACT FROM AUTHOR]

The identification of outliers in measurement data is hindered if they are present in leverage points as well as in rest of the data. A promising method for their identification is the Monte Carlo estimation (MCE), which is subject of the present investigation. In MCE the data are searched for data subsamples without leverage outliers and with few (or no) non-leverage outliers by a random generation of subsamples. The required number of subsamples by which several of such subsamples are generated with a given probability is derived. Each generated subsample is rated based on the residuals resulting from an adjustment. By means of a simulation it is shown that a least squares adjustment is suitable. For the rating of the subsamples, the sum of squared residuals is used as a measure of the fit. It is argued that this (unweighted) sum is also appropriate if data have unequal weights. An investigation of the robustness of a final Bayes estimation with the result of the Monte Carlo search as prior information reveals its inappropriateness. Furthermore, the case of an unknown variance factor is considered. A simulation for different scale estimators for the variance factor shows their impracticalness. A new resistant scale estimator is introduced which is based on a generalisation of the median absolut deviation. Taking into account the results of the investigations, a new procedure for MCE considering a scale estimation is proposed. Finally, this method is tested by simulation. MCE turns out to be more reliable in the identification of outliers than a conventional resistant estimation method. [ABSTRACT FROM AUTHOR]

The question about how companies solved their existing information and knowledge problems is rarely examined for companies of the 19th and 20th century. Therefore the following contribution takes a closer look at the methods used by Gutehoffnungshütte in this period for obtaining the relevant information and how it ensured that the information would reach the particularly targeted employee. This case study of one of the most important pioneers of the German industrialization shows that the company's management used different methods (bureaucratisation, reports, meetings etc.) which developed only slowly in an evolutionary and implicit way because knowledge basically remained bound to certain persons until 1914. After the First World War, the company grew enormously under the leadership of the new chairman of the executive board Paul Reusch, who created a management-by-letter system that provided him with a lot of information and a monopoly on power until his dismissal during the Second World War. [ABSTRACT FROM AUTHOR]

With the increase in energy consumption during the boom years the composition of energy sources in West Germany changed fundamentally. West German chemical companies followed the international trend towards petrochemicals and converted their production and energy generation systems to oil. But the unrestricted use of fossil fuels soon provoked concerns. As a consequence, nuclear power appeared as an attractive alternative to power generation by coal and oil. The examples of the large West German companies Hoechst, Bayer and BASF show the connections between the chemical and nuclear industry under the conditions of increasing international competition. The Hoechst management discussed not only the question of own nuclear power stations, but also considered nuclear chemistry as a potential business. In the case of BASF, the plans for an own nuclear power station were more advanced than at Hoechst. The proposed location on BASF's factory premises, however, represented a distinct rejection of the current safety philosophy that could not be ignored by policymakers. [ABSTRACT FROM AUTHOR]

The L1-norm estimation is a resistant estimation method and therefore used for the detection of gross errors in geodetic measurement data. Alternatively, other Lp-norms have been suggested in literature for resistant parameter estimation. A common numerical solution method for Lp-norm estimation is the method of iteratively reweighted least squares. Procedural manners for a successful application of this method are considered. A modification of the method is given, which reduces the number of iterations significantly. By means of a simulation the applicability of the mentioned methods and the success of different Lp-norms in the detection of gross errors are tested. It shows that solving the L1-norm numerically may be unsuccessful and that instead a resistant Lp-norm is to be recommended, which is comparably successful in the detection of gross errors and can successfully be solved numerically by the presented modification of iteratively reweighted least squares. [ABSTRACT FROM AUTHOR]