The objective of this research is to investigate the perception of owner – managers and

their employees regarding entrepreneurial leadership. To develop the research, two questions

are raised related to the similarities or differences of the perceptions of both groups

with what is established in the literature and between the self – evaluation of the owner –

managers and their employees on whether the former perform as an entrepreneurial leader.

As a research method, both groups are asked to perform, first individual evaluations and

then to match certain behaviours and the levels at which they should appear at certain levels

of entrepreneurial leadership capacity. The data gathered during the investigation were

processed using the Categorical Principal Components Analysis and revealed the similarities

and differences between the perceptions of the owner-managers and their employees on

entrepreneurial leadership. In spite of not finding significant differences between what is established

in the literature and among the perceptions of the groups under study, interesting

nuances stand out that, if not identified and understood, could have a negative effect on

the performance of SMEs. The results of the research demonstrated the importance of the

approach of behaviour and perception in the study of entrepreneurial leadership.

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.