Labor absenteeism is a factor that affects the good performance of organizations in any

part of the world, from the instability that is generated in the functioning of the system.

This is evident in the effects on quality, productivity, reaction time, among other aspects.

The direct causes by which it occurs are generally known and with greater reinforcement

the diseases are located, without distinguishing possible classifications. However, behind

these or other causes can be found other possible factors of incidence, such as age or sex.

This research seeks to explore, through the application of neural networks, the possible

relationship between different variables and their incidence in the levels of absenteeism. To

this end, a neural networks model is constructed from the use of a population of more than

12,000 employees, representative of various classification categories. The study allowed the

characterization of the influence of the different variables studied, supported in addition to

the performance of an ANOVA analysis that allowed to corroborate and clarify the results

of the neural network analysis.

In recent years, the outsourcing of a variety of different activities has been more commonly observed in the coal mining industry. This is connected with employing workers by external companies. These practices are not necessarily perceived as good ones by mines’ employees because they may influence their remuneration directly or indirectly. Firstly, as external employees treat work in mining company as a source of a quick income. Therefore, external companies often calculate their employees compensation not based on working time (i.e. hours) but on the basis of a specific, accomplished task. Such employment is called piecework, whereas the workers employed in this kind of system are called output workers/piece workers. Therefore, to receive higher wages in these companies, employees carry out their tasks faster and more efficiently. This, in turn, can affect the standards of workers employed by the mining company. In addition, outsourced workers are often retired miners, so the costs incurred by employers are significantly lower. In addition, in order to not to lose the retirement benefit, they work for a much lower rate. On the other hand, outsourced work can be done in a hurry (on a piece rate), which is not conducive to compliance with safety regulations, therefore mine employees may feel unsafe. This article aims to present how mine employees assess outsourcing underground works. In order to achieve this aim, a survey was carried out among employees of one of the coal mine companies in Silesia. Participants of the survey were randomly chosen among underground miners employed at one mine company. The survey was anonymous which obviously might have influenced respondents’ honesty in answering. The survey was carried out in several mines of the chosen company. In some of them the survey was carried out online and in the remaining ones it was filled out on paper. Analyzing the survey results allowed for a better understanding of the reasons of the disapproval of outsourcing underground works. This, in turn, may be used for better human resources management including, in particular, planning an incentive based pay system.