Upper Echelons Theory - Hambrick & Mason, 1984 Various studies show that organizations are a reflection of its top managers (Finkelstein and Hambrick) 1996 Carpenter et al (2004) also repeats the composition of the TMT, in terms of diversity of the upper echelons theory due to the duties of internal and external management.

1. International
Conference
on
Business
&
Banking
and
Corporate
Social
Responsibility,
University
Network
(ICBB
and
CSR-­‐UN)
23
–
24
February
2010
Surabaya
Joy
Elly
Tulung
1-­‐1

2. • Upper
Echelons
Theory
-­‐
Hambrick
&
Mason,
1984
• Various
studies
show
that
organizations
are
a
reTlection
of
its
top
managers
(Finkelstein
and
Hambrick)
1996
• Carpenter
et
al
(2004)
also
repeats
the
composition
of
the
TMT,
in
terms
of
diversity
of
the
upper
echelons
theory
due
to
the
duties
of
internal
and
external
management.
1-­‐2

3. † Tihanyi
et
al
(2000),
126
companies
in
the
electronics
industry
† Kilduff
et
al
(2000),
data
from
35
Tirms
and
159
managers
† Herrmann
and
Datta
(2005),
based
on
a
sample
of
112
manufacturing
Tirms
in
the
United
States
† Staples
(2005)
whereas
conducted
a
study
of
the
largest
TNC
80,
and
found
that
60/80
or
75%
of
these
companies
had
at
least
one
foreigner
in
their
councils.
1-­‐3

4. † Glunk
et
al
(2001)
who
study
and
explore
the
TMT
differences
and
similarities
in
England,
Dutch
and
Denmark
† Heijltjes
et
al
(2003)
in
their
study
look
at
the
national
scale
TMT
diversity
in
two
countries
in
Europe,
i.e.
Netherlands
and
Sweden,
† Hendriks
(2004)
conducted
research
on
TMT
diversity
and
Tirm
performance
in
IT
companies
of
small
and
medium
sizes
in
the
Netherlands
and
Belgium.
† van
Veen
and
Marsman
(2008)
n
their
study
explain
the
diversity
of
nationalities
in
15
countries
in
Europe
1-­‐4

5. † Ping
(2007)
who
conducted
an
empirical
study
of
data
from
2001-­‐2002
of
356
Chinese
companies
† Julian
et
al
(2003),
International
Joint
Venture
team
in
Thailand
† Kusumastuti
et
al
(2007),
48
manufacturing
companies
registered
in
Jakarta
Stock
Exchange
in
2005
1-­‐5

6. Does
the
composition
of
the
Top
Management
Team
in
the
industry
affect
the
banks
performance
in
Indonesia?
1-­‐6

7. Age
• Pegels
and
Yang
(2000:697)
state
that
older
managers
tend
to
avoid
risk
(Vroom
and
Pahl,
1971)
while
the
young
one
tend
to
pursue
more
risky
and
innovative
growth
strategies.
Gender
• Glunk
et
al
(2001)
found
that
gender
distribution
is
very
different
in
three
countries:
there
are
few
women
executives
in
the
30
countries,
with
the
exception
of
the
UK,
Denmark
and
Dutch
1-­‐7

8. Educational
Level
and
Educational
Backgroud
• Dahlin
et
al
(2005)
found
that
the
education
diversity
in
TMT
affects
the
range
and
depth
of
the
use
of
positive
information,
and
may
negatively
affect
the
combination
of
information.
• Herrmann
and
Datta,
2005;
Hambrick
and
Mason,
1984,
explained
also
in
the
previous
subsection
should
be
a
complementary.
1-­‐8

9. AGE
GENDER
ROA
EDUCATIONAL
LEVEL
EDUCATIONAL
BACKGROUND
1-­‐9

10. † Deductive
† 9
banks
listed
in
Indeks
kompas
100
† Annual
Report
2008
† 134
top
executives
1-­‐10

11. Age
of
TMT s
50
–
7.5%
The
rest
73,8%
54
–
51
–
6.0%
6,7%
52
–
6.0%
1-­‐11

12. 1-­‐12

13. 1-­‐13

14. 1-­‐14

15. Age
Gender
0.51
0.020
ROA
Educational
Educational
Level
Background
-­‐0.265
0.022
1-­‐15

16. Normal P-P Plot of Regression Standardized Residual
† Normality
Dependent Variable: ROA
Expected Cum Prob
1.0
0.8
0.6
0.4
0.2
0.0
0.0 0.2 0.4 0.6 0.8 1.0
Observed Cum Prob 1-­‐16

17. Scatterplot
Regression Standardized Residual
† Heterogeneity
Dependent Variable: ROA
2
1
0
-1
-2
-2 -1 0 1 2 3
Regression Standardized Predicted Value
1-­‐17

18. † CoefIicient
Coefficientsa
Unstandardized Standardized
Coefficie nts Coefficie nts Correla tions Collinearity Statistics
Model B Std. Error Beta t Sig. Zero-order Partial Part Tolerance VIF
1 (Constant) .014 .007 2.088 .039
Age 9.27E-005 .000 .089 .906 .367 .082 .092 .088 .970 1.031
Gender .002 .003 .077 .778 .439 .022 .079 .076 .956 1.046
Educatio nal level -.003 .001 -.277 -2.810 .006 -.266 -.274 -.273 .976 1.025
Content of education -9.48E-007 .000 -.001 -.009 .993 .001 -.001 -.001 .987 1.013
a. Dependent Variable: ROA
† Equation
Y
=
0.014
+
0.0000927
X1
+
0.002
X2
-­‐
0.003
X3
-­‐
0.000000948
X4
1-­‐18

19. † Every
one
point
increase
in
X1,
Y
will
increase
as
much
as
0.0000927
in
which
other
variables
are
considered
constant
† Every
one
point
increase
in
X2,
Y
will
increase
as
much
as
0.002
where
the
other
variables
are
considered
constant
† Every
one
point
increase
in
X3,
Y
will
be
reduced
by
0.003
when
other
variables
are
considered
constant
† Every
one
point
increase
in
X4,
Y
will
be
reduced
by
0.000000948
when
other
variables
are
considered
constant
1-­‐19

20. † ANOVA
(b)
Sum of
Model Squares df Mean Square F Sig.
1 Regression
.000 4 .000 2.183 .077(a)
Residual
.004 97 .000
Total
.005 101
† a
Predictors:
(Constant),
Educational
Background,
Educational
level,
Age
,
Gender
† b
Dependent
Variable:
ROA
1-­‐20

21. † Partial
Test
† Age
(X1)
† From
the
coefTicient
table
the
signiTicant
value
=
0.367>α
show
that
the
null
hypothesis
was
not
rejected.
The
conclusion
of
this
is
that
the
independent
variable
X1
(Age)
does
not
affect
the
dependent
variables
(ROA)
† Gender
(X2)
† From
the
coefTicient
table,
the
signiTicant
value
=
0.439>α,
show
that
the
null
hypothesis
was
not
rejected.
The
conclusion
from
this
is
that
the
independent
variable
X2
(Gender)
did
not
affect
the
dependent
variables
(ROA)
1-­‐21

22. † Educational
Level(X3)
† From
the
coefTicient
table,
the
signiTicant
value
=
0.006<α,
which
shows
the
null
hypothesis
was
rejected,
with
the
conclusion
being
that
the
independent
variable
X3
(Education
Level)
affect
the
dependent
variable
(ROA)
† Educational
Background
(X4)
† From
the
coefTicient
table,
the
signiTicant
value
=
0.993>α,
the
null
hypothesis
was
not
rejected.
The
conclusion
is
that
the
independent
variable
X4
(Education
Sector)
does
not
affect
the
dependent
variable
(ROA).
1-­‐22

23. † The
conclusion
was
that
the
independent
variables
simultaneously
does
not
affect
the
dependent
variables,
so
top
management
team
composition
does
not
affect
the
company
performance.
† Also
only
the
educational
level
of
the
top
management
team
had
an
inTluence
on
the
performance
of
banking
companies
in
Indonesia,
with
age,
gender
and
educational
background
having
no
effect
on
the
company
performance
in
Indonesia.
1-­‐23

24. † Limited
sample
† Just
9
banks
1-­‐24