Step by Step of Mediating Effect Testing Baron and Kenny’s (1986) procedure is adopted to test the mediating effects. This method is very useful to test the mediating effects by using hierarchical regression analysis (Mathieu, Maynard, Taylor, Gilson, & Ruddy, 2007; Mathieu & Taylor, 2007). There are 4 conditions to test the mediating effects. First, independent variable (X) must relate significantly to dependent variable (Y). Second, independent variable (X) must relate significantly to mediating variable (M). Third, mediating variable (M) must relate to significantly to dependent variable (Y). Finally, if independent variable (X) fail to account for significant dependent variable (Y) after mediating variable (M) has been controlled, then the evidence is considered as a full mediation. Alternatively, if independent variable (X) and mediating variable (M) account for significant dependent variable (Y), the evidence is considered to be a partial mediation. In our group homework assignment, Hypotheses H11 and H12 need to be tested by hierarchical regression. We will only practice H11. The following instructions are to show you how to get the results of mediating effects. 1. Compute mean score of independent, mediating, and dependent variables. 2. Above 4 conditions need to apply to produce the results of mediating effects. 3. Let see step by step of mediating effects. Analyze >> Regression >> Linear >> Select a factor of Dependent variables from the left panel to “Dependent” >> Select all the factors of independent variables from the left panel to “Independent” >> Click on “Statistics” >> Select “R squared change”, “Collinearity Diagnostics”, “Durbin-Watson”, and “Covariance Matrix” >> Click on “Continue.” For “Method”, you may need to select “Stepwise” >> Click on “OK” As recommended above, you need to conduct the mediating effects with 4 steps of regression analysis. a. SC (X)TI (Y) b. SC (X)CU (M) c. CU (M) TI (Y) d. [SC (X) + CU (M)]TI (Y) Note: SC = Social capital; CU = Competence upgrading; TI = Technology innovation. X = Independent variable; M = Mediating variable; Y = Dependent variable.