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.