Table 5

Results of the analysis of the multiple linear regression model

Regression model 4Regression model 5Regression model 6
Market shareDifferentiationCost reduction
BSigVIFBSigVIFBSigVIF
B01.776**0.015 1.645**0.000 1.3630.087 
TC0.0960.1271.180.0920.0681.180.0490.5951.18
CI0.241**0.0221.250.0020.9781.250.0860.3761.25
Size0.0020.1011.330.0060.002**1.330.0000.9451.33
Age−0.0010.8861.27−0.0010.7281.27−0.0040.3861.27
SE10.0410.7071.530.1660.1001.53−0.1250.2361.53
SE20.1810.1981.460.1100.5611.46−0.0370.8251.46
SE3−0.0570.7261.140.0400.7541.14−0.0190.5541.14
SE40.2070.2381.30.1950.1221.30.0320.7401.3
SE50.0940.438 0.0530.6451.38−0.0980.2811.38
Model test
F(12,130)2.3411.094.57
Sig0.0100.0000.000
R20.20160.23680.1422
Lagrange multiplier (LM)χ2 (1) = 10.04, Sig. = 0.002**χ2(1)=40.34,Sig.=0.0000**χ2(1)=25.05,Sig.=0.0000**
Durbin Watson1.902.1531.973
Kolmogorov–Smirnov test (KS)Test-statistic = 0.83, Sig. = 0.000Test-statistic = 0.201, Sig. = 0.000Test-statistic = 0.210, Sig. = 0.000

Note(s): **Statistically significant at 5% significance level, TC: Target cost, CI: Continuous improvement

Source(s): Author’s work based on Rogers (1993) 

or Create an Account

Close Modal
Close Modal