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Cost analysis of pig slaughtering: A Hungarian case study
121-129Views:245The scale of Hungarian slaughterhouses is small in international comparison and the cost of slaughter and cutting a pig of average live weight is relatively high at 16.1-19.4 EUR on average. The aim of this study is to evaluate the cost of pig slaughter and cutting through the case study of a medium-scale plant in Hungary. Based on data from the enterprise, a calculation was performed in relation to the “output” quantity of pig slaughter and cutting, as well as its value and the cost and cost structure of processing. The capacity of the examined plant and its utilisation were analysed and cost reductions were estimated for various increases of output. In 2015, the direct cost of slaughter and cutting was 18.9 EUR per pig for the medium-scale plant which processed 100 thousand pigs. When the purchase cost of pigs is excluded, labour costs accounted for the highest share (30%) of costs, followed by services (29%) and energy costs (21%). For this reason, the level of wages and employer’s contributions has a rather high significance. Analysis showed that significant increases in Hungarian minimum wage and guaranteed living wage in 2017 resulted in an estimated 7% increase in the cost of slaughter and cutting compared to 2015, despite the decrease of contributions. The capacity utilisation of the plant was a low 28% when compared to a single 8-hour shift considered full capacity. The cost of slaughter and cutting was estimated to be reduced to 14.2-17.0 EUR per pig if the plant operated at full capacity. This may be considered a lower bound estimate of cost because there are numerous restricting factors on optimising capacity utilisation, such as: 1) number of live animals available for purchase and related logistics; 2) cooling capacity availability; 3) labour availability; 4) market position of the enterprise and potential for marketing additional pig meat products. Enterprises of this scale are recommended to consider producing more value-added products and, accordingly, investing in product development.
JEL Classification: Q13, Q19
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Analysis of the influential factors on gross value added in the Hungarian sheep sector
107-112Views:143The competitiveness of the Hungarian sheep sector has been in steady decline for some time now. Crucial has been the problem that the value added in the sector is not generated in Hungary, as most of the produced lambs in Hungary leave the country with an average weight of 21 kilograms, with slaughtering happening abroad.A model has been constructed for our investigations, which introduces the connections between the product cycle phases for mutton in Hungary. This model allows us to calculate the volume of gross value added generated within specific product cycle phases. We used Monte Carlo simulation for our examination, for which the Crystall ball software package was utilized, namely the OptQuest module, for optimization. First, we conducted an optimization of an experiment number of 500,000 for “Gross value added” in the case of the slaughterhouse. During the optimization, Easter, Christmas and August lamb ratio and ewe number, as well as progeny, were set as decision variables and examined as values of gross value added, the decision variables of which contribute to obtaining the best results. The gained decision variables were set in the model and a Monte Carlo simulation was run with an experiment number of 500,000, where only the values of the conditions were changed along the pre-set dispersion; the values of the decision variables were fixed. The most significant aim of our investigation was to identify the volume of gross value added generated during processing in various phases of the product chain and the change of which inputs affected this volume the most. The findings proved that, in the case of capital uniformity, the output of processing was most influenced by sheep progeny on the bottom level of the mutton product chain. This factor is followed by that of weight gain in the source material producing and fattening sub-modules, as well as the gross wage in starter lamb feed and meadow hay in the source material producing sub-modules. Contour plots helped to describe the connections between these factors. By using contour plots, the volume of gross value added might be forecast for various combinations of factors.