1-­‐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-­‐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-­‐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-­‐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-­‐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-­‐6  

Does  the  composition  of  the  Top  Management  Team  in  the  industry  affect  the  banks’  

performance  in  Indonesia?    

1-­‐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-­‐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-­‐9  

AGE  

GENDER  

EDUCATIONAL  LEVEL  

EDUCATIONAL  BACKGROUND  

ROA  

1-­‐10  

�  Deductive  �  9  banks  listed  in  Indeks  kompas  100  �  Annual  Report  2008  �  134  top  executives    

1-­‐11  

Age  of  TMT’s  

50  –  7.5%  

51  –  6,7%  

52  –  6.0%  

54  –  6.0%  

The  rest  73,8%  

1-­‐12  

1-­‐13  

1-­‐14  

1-­‐15  

Age      0.51  

Gender    0.020  

Educational  Level      -­‐0.265  

Educational  Background      0.022  

ROA  

1-­‐16  

�  Normality  

Observed Cum Prob1.00.80.60.40.20.0

Exp

ecte

d C

um

Pro

b

1.0

0.8

0.6

0.4

0.2

0.0

Normal P-P Plot of Regression Standardized Residual

Dependent Variable: ROA

1-­‐17  

�  Heterogeneity  

Regression Standardized Predicted Value3210-1-2

Reg

ressio

n S

tan

dard

ized

Resid

ual

2

1

0

-1

-2

Scatterplot

Dependent Variable: ROA

1-­‐18  

�  CoefIicient  

�  Equation      Y  =  0.014  +  0.0000927  X1  +  0.002  X2  -­‐  0.003  X3  -­‐  0.000000948  X4    

Coefficientsa

.014 .007 2.088 .0399.27E-005 .000 .089 .906 .367 .082 .092 .088 .970 1.031

.002 .003 .077 .778 .439 .022 .079 .076 .956 1.046-.003 .001 -.277 -2.810 .006 -.266 -.274 -.273 .976 1.025

-9.48E-007 .000 -.001 -.009 .993 .001 -.001 -.001 .987 1.013

(Constant)AgeGenderEducational levelContent of education

Model1

B Std. Error

UnstandardizedCoefficients

Beta

StandardizedCoefficients

t Sig. Zero-order Partial PartCorrelations

Tolerance VIFCollinearity Statistics

Dependent Variable: ROAa.

1-­‐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-­‐20  

�  ANOVA  (b)  

�  a    Predictors:  (Constant),  Educational  Background,  Educational  level,  Age  ,  Gender  

�  b    Dependent  Variable:  ROA  

Model Sum of

Squares df Mean Square F Sig. 1 Regression .000 4 .000 2.183 .077(a)

Residual   .004 97 .000

Total   .005 101

1-­‐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-­‐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-­‐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-­‐24  

�  Limited  sample    �  Just  9  banks