- •Evaluation of managerial competences: risk aversion and successful decision making in basic education principals m. Navarro Rodriguez1, r. Edel Navarro2, y. Soto Ruiz3
- •1 Universidad Pedagógica de Durango (mexico) 2 Universidad Veracruzana (mexico) 3 Ministery of Education, Durango State. (mexico)
- •Abstract
- •1Introduction
- •1.1Management skills in educational institutions and decision-making
- •1.2. Successful decisions and risk aversion
- •1.3. Objectives
- •3Results
- •3.1Analysis of significant differences between two groups, t test for one sample
- •1.4. Research hypotheses
- •2Methodology
- •3.2. Correlations between successful management decisions and risk aversion level.
- •Effects of risk aversion on successful decisions: a linear regression model
- •4. Conclusions
3.2. Correlations between successful management decisions and risk aversion level.
In order to establish the probable relationships between the items of successful management decisions and items that measure the level of risk aversion, a bivariate Pearson correlation test was established; Table 2 shows the correlations found with a significance of .05 (*) and .001 (**)
Table No. 2 Pearson's Correlations: Successful directive decisions and Risk Aversion
Ítems: successful management decisions |
Correlations found with items of risk aversion |
Their successful decisions demonstrate effectiveness and results |
.28* |
Their successful decisions meet institutional and user needs |
.27*, .27*, .26* |
Your successful decisions generate real recognition |
.53**, .31**, 52**, 48**, 42**, 47**, 44** |
Their successful decisions are taken as example |
.45**. .41**, .31*, .50**, .53**, .47**, 47**, 52**, 47** |
Their successful decisions have transformed the institutional context |
.25*
|
Their successful decisions have made a positive difference in the lives of users |
.36**, .26*, .38**, .47**, .42**, .61**, .48** |
Has made successful decisions even with absence of information anticipating future events |
.52**, .50**, .39**, .43**, .58**,.44**, .58**, .36** |
Has made successful decisions even with absence of information anticipating future events |
.51**, .51**, .35**, .57**, .49**, .46**, .60**, .49**, .33** |
Has made successful decisions even in situations of ambiguity, applying different strategies |
.63**, .51**, .50**, .50**, .58**, .57**, .52**, .55**, .42** |
As can be seen in Table 2, when the successful decision describes a managerial skill that responds to how to decide in uncertainty conditions, the number of correlations increases in the items related to risk aversion, in this way; successful decisions, changing situations maintains 9 significant strong correlations, followed by successful decisions in ambiguous situations with 9 strong significant correlations, followed by successful decisions, absence of information with 8 significantly strong correlations, successful decisions, positive difference in users with 7 correlations, 4 strongs and 3 of an average type. Other strong correlations are established between successful decisions, taken as an example, with 9 strong correlations and successful decisions generate real recognition, with 6 strong correlations and a mean correlation.
This indicates that the more the item is associated with risk aversion, the less approval status the successful decision item will have and the more strong and multiples correlations will have Ho withholding.
It can be established that the successful decisions with the lowest correlation to risk aversion items are: successful decisions, effectiveness results with only a mean correlation and successful decisions transform the institutional context with also only a correlation, it means that in these items, the associating between the decision with conditions of uncertainty and risk aversion is not presented.
If we make a successful decision representative of what it is to be successful in terms of a community of practitioners, we can take the item: successful decisions are take them as an example, this item is quite representative of a successful decision, we can obtain a linear regression model for that item, establishing its predictor variables and / or effects on said variable, as described below.
