REAL
Keystone sector methodology applied to Portugal
training programs, competition is being held among different local institutions and we
didn’t know if a significant pattern in this relational links already emerged.
We present the results for density in the 3 matrices15 in table 1.
Table 1 - Global Densities
N = 83
Social Network Concepts |
Formulas |
INF |
MON |
ORG |
Density V2 |
∑ V2ÿ / N*(N-1) |
0.156 |
0.007 |
0.057 |
Density in USA study |
0.240 |
0.100 |
0.155 |
It is worthy to note that global densities have low values compared with results
from US comparative study.
In table 2 potential densities refer to the 2nd and 3rd steps, which means we also
consider the mediation roles within the social network (direct and indirect links). We
ran the results considering the same matrices and it is possible to verify that
accumulated potential densities are significantly higher.
Table 2 - Accumulative densities
N = 83
Social Network Concepts |
Formulas |
Value |
Value |
Value |
2 - STEP PATH - V23 |
INF |
MON |
ORG | |
Density V23 |
∑V... / N*N |
0.51 |
0.098 |
0.506 |
3 - STEP PATH - V33 | ||||
Potential Density V3 3 |
∑V33/ N*N |
0.66 |
0.153 |
0.649 |
Accumulative potential density |
∑V33/ N*N - ∑ V3ij / N*N |
0.54 |
0.09 |
0.592 |
Looking at the results, the main conclusion will be that considering this one-
intermediary role, the network will potentially raise its density over the 51% and up to
66%, when the two-intermediary entities are considered (INF); 10 and 15% (MON) and
51 and 65% ( ORG ).
Following our theoretical argument it means that in TT there is plenty
opportunities to some entities in the network, so they can benefit from the existence of
structural holes and easily increase the network efficiency (INF and ORG). The extent
to which each node is directly connected to all other nodes and the extent to which a
node is directly connected only to those other nodes that are not connected to each
15 The complete tables with results are in Appendix.
13
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