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I nform at ion Funct ions to degree of adopt ion is significant as well, where p is less than 0.05. As shown in table 4.5a, correlation between degree of adoption and
Continuous I m provem ent has the largest correlation, where value r is equal t o 0.70.
Variable EW
CI ZD
JIT PULL
MTF DEC
IF VIF
DOA 0.68 0.70 0.60 0.49 0.57 0.53 0.57 0.48
0.34
Pr e dict or va r ia ble
EW - 0.64 0.52 0.20
0.44 0.47 0.29 0.21
- 0.01 CI
- 0.38 0.42 0.29 0.45 0.43 0.07
0.20
ZD - 0.27 0.41
0.39 0.11 0.12 - 0.01 JIT
- 0.50
0.55 0.33
0.13 0.06
PULL -
0.50 0.31
0.07 - 0.17
MTF -
0.32 0.04
0.07
DEC -
0.43 0.44
IF -
0.53
VIF -
p .05; p .01
Table 4. “ I nter- correlation for DOA and predictors variables N= 40 ” .
Table 5 indicates the correlation between the predictor variables and m anagem ent com m itm ent to 5’s General Visual Managem ent . Qualit y Leadership was t he only
variable which significant ly correlat ed to the m anagem ent com m itm ent, where r is equal to 0.359 with p less t han 0.05. All predict or variables positively correlated to
the m anagem ent com m itm ent.
Variable WEMP
TRAIN GROUP
QLEAD 5’s and General Visual Management
0.225 0.198 0.242 0.359
Pr e dict or va r ia ble WEMP
- 0.255 0.380 0.604
TRAIN -
0.514 0.45
GROUP -
0.748
QLEAD -
p 0.05; p 0.01
Table 5. “ I nter- correlation for m anagem ent com m itm ent and predictors variables N= 40 ” .
4.3 Regression
The regression analyses are com puted to determ ine the strength of the relationship between independent variables and dependent variables Boyer, 1996 . Moreover,
in regression analyses, an equat ion can be creat ed. This regression equat ion allows prediction of values of the dependent from given values of the independent
Bower, 2000 .
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Sim ult aneous m ult iple regression was conduct ed t o invest igat e t he best predict ors of degree of adoption. I n sim ultaneous m odel, all independent variables ent er t he
regression equation at once to exam ine t he relat ionship bet ween the whole set of predictors and the dependent variable Coakes, 2005 . This is because all the nine
independent variables are significantly related to dependent variable. The beta coefficient s are present ed in the Table 6. Note t hat all nine variables significantly
predict the degree of adoption when they are included. The adj usted R squares value was 0.993. This indicates t hat 99.3 of the variance in degree of adoption
was explained by all nine variables. The regression equation for this m odel to predict the degree of leanness of the
com pany is st at ed in Equat ion 1. The equat ion also can be used t o est im at e t he degree of adoption for other sam ple size.
Degree of adopt ion = 0.014 EW + 0.020 CI + 0.015 ZD + 0.013 JI T + 0.017 PULL + 0.013 MFT + 0.013 DEC + 0.016 I F
+ 0.014 VI F + 0.062
Equation 1. “ Degree of adoption”
Where, EW
= Elim inat ion of wast e m ean value
CI =
Continuous I m provem ent m ean value ZD
= Zero Defects m ean value
JI T =
Just- in- Tim e m ean value PULL
= Pull I nstead of Push m ean value
MFT =
Mult ifunct ional Team s m ean value DEC = Decentralized
Responsibilities m ean value I F
= I ntegrated Functions m ean value
VI F =
Vertical I nform ation Functions m ean value
I n stepwise regression, the num ber of independent variables entered and the order of entry are determ ined by statistical criteria generated by stepwise procedure
Coakes, 2005 . Since not all independent variables significantly related to m anagerial com m itm ent, therefore stepwise regression would be appropriate to
analyses the com bined effect of predictor variables on dependent variable. I n this case t he m anagem ent com m it m ent t o 5’s and General Visual Managem ent will be
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P. Puvanasvar an; H. Megat ; T. S. Hong; M. M. Razali
the dependent variables. The independent variables are the supporting m anufacturing infrastructure. The result s of stepwise regression are given in table
7. The only variable select ed t o ent er t he m odel is Qualit y Leadership, which accounts for 39.4 of the variance in the dependent variable, and is significant at
p is less t han 0.01.
Variable B
SEB β
EW 0.014 0.002 0.173
CI 0.020 0.002 0.246
ZD 0.015 0.001 0.180
JIT 0.013 0.002 0.144
PULL 0.017 0.002 0.195
MFT 0.013 0.002 0.157
DEC 0.013 0.002 0.127
IF 0.016 0.001 0.222
VIF 0.014 0.002 0.180
Constant
0.062 0.006 Not e. R
2
= 0.993; p .01, p .001
Table 6. “ Sim ultaneous Multiple Regression Analyses Sum m ary for EW, CI , ZD, JI T, PULL, MFT, DEC, I F, and VI F N= 40 ” .
The other variables are excluded from the m odel. These are true with the result of correlat ion analyses, where Qualit y Leadership is t he only relat ed variables and
contribute to the 5’s and General Visual Managem ent. The regression equation for t his m odel t o predict t he m anagerial com m it m ent of the com pany is st at ed in
Equation 2. The equation also can be used to estim ate m anagerial com m itm ent for other sam ple size.
Managerial Com m it m ent = 0.494 QLEAD + 1.642
Equation 2. “ Managerial Com m itm ent” .
Where, QLEAD
= Qualit y Leadership m ean value
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The roles of com m unication process for an effect ive lean m anufacturing im plem entat ion 145
P. Puvanasvar an; H. Megat ; T. S. Hong; M. M. Razali
Independent variables B
SEB R
2
F QLEAD
0.494 0.187 0.394 6.964
Constant
1.642 0.660 p 0.05
Table 7. “ Stepwise regression for Managem ent com m itm ent to 5’s and General Visual Managem ent with SMI N= 40 ” .
4.4 Degree of Leanness and Degree of Management Commitment
