CHAPTER 1: INTRODUCTION 1.0 Chapter Overview - DSpace@UM

1986; Johnson et al., 1994; Huang, 2001) where adoption of succession plan improvedorganizational performance. Based on the regression coefficients findings from model 1in Table 4.19, the regression line for this model was derived as follows:-Y = 1.882 + 0.546X 1 + εHowever, prior research by Huang (2001) had failed to support the argument of Pattan(1986) as the relationship between adoption of succession planning program and HumanResource outcomes was statistically insignificant.4.9.2 Model 2 - Regression Analysis Between Organizational Outcomes AndDemographic Variables (Control Variables)In regression Model 2 of Table 4.19, it was found that except for industrial sector, theother 5 demographic/control variables are linearly related to the dependent variables. Theregression results indicated that the model was significant (R 2 = 0.347, F-value = 8.930, p= 0.000). The firm age (beta = 0.207, p < 0.05), firm size (beta = 0.209, p < 0.05) , andfirm type/ownership (beta = 0.175, p < 0.05) were positively and significantly related toorganizational outcomes/performance. Whereas, firm listing (beta = -0.251, p < 0.05) ,and staff turnover rate (beta = -0.420, p < 0.05) were negatively and significantly relatedto organizational outcomes/performance. Interestingly, though, the industrial sector wasnot significantly related (p > 0.05) to organizational outcomes. The adjusted R 2 of 0.308indicated that 30.8% of the variance in the organizational outcomes was explained by theindependent variables i.e. firm age, firm size, industrial sector, firm type, firm listing andstaff turnover rate. The highest value of variance inflation factor (VIF = 1.591) suggested85