TABLE 3.

Polynomial regression with response surface analysis.

Variables	Coefficients	SE
Constant (b0)	4.118***	0.588
Age	–0.070	0.105
Education	–0.089	0.103
Employee	0.286*	0.186
Asset	–0.108	0.050
Loss orientation coping (LOC) (b1)	0.053	0.085
Restoration orientation coping (ROC) (b2)	0.159	0.096
LOC squared (b3)	0.186**	0.063
LOC × ROC (b4)	–0.038	0.085
ROC squared (b5)	0.087	0.090
a1	0.212*	0.102
a2	0.235*	0.096
a3	–0.106	0.150
a4	0.311*	0.145

Dependent variable: innovation ambidexterity; significance level: *p < 0.05; **p < 0.01; ***p < 0.001 (two-tail tests, sample size = 106); a₁ = b₁ + b₂, a₂ = b₃ + b₄ + b₅, a₃ = b₁ – b₂, and a₄ = b₃ – b₄ + b₅, where b₁ is the coefficient for LOC, b₂ is the coefficient for ROC, b₃ is the coefficient for LOC squared, b₄ is the coefficient for LOC × ROC, b₅ is the coefficient for LOC squared.