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DEVELOPING A MODEL EMPLOYMENT ARRANGEMENT USING A TAXONOMIC APPROACH AND A SIMILARITY MEASURE BASED ON MINING COMPANIES
Abstract
This article aims at developing a method to establish a model employment arrangement based on mining companies using a taxonomic approach and a similarity measure as well as potential practical applications of the presented studies. In order to establish the model employment arrangement, the author uses the production parameters of mining companies significantly affecting the number of employees. As a result, the following algorithm has been proposed: arranging mines into typologically homogeneous groups using the stochastic taxonomy method; establishing a ranking list within the groups and selecting leaders based on the lowest unit cost of production; adopting the employment arrangement represented by the leader as a model for a given group of typologically similar mines. This grouping method allows the leader, with similar production parameters, to obtain the lowest unit cost of production within the group. Accordingly, it is assumed that both the status and arrangement of its employment can cause it to become a model to follow for the remaining mines in each group. The division into typologically similar groups allows the author to obtain groups of objects that are homogeneous with regard to the applied criteria. When comparing the size and structure of employment of any mine with the model-leader, it can be easily noted where the areas of either excess or shortage of employment are, and thus corrective actions can be implemented. This method helps to optimize the number of employees necessary for the implementation of production processes in hard coal mines, including production costs. The study procedure described above is universal and allows for the qualitative and quantitative establishment of employment arrangement in any enterprise with the only difference being that other variables, typical of an analyzed enterprise, should be applied for calculation. In addition, this method helps to set a benchmark for comparing the studied size and structure of employment in a given organization with potentially better solutions in this area. The created model can be used to determine any areas of optimizing the number of employees, and data obtained can also be an invaluable source of information necessary in the process of human resource management.
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