Strategy Communication Model

Identification of the Model

From a communication perspective, it is hypothesized that strategy communication has a positive impact on organizational performance. The main variables of interest for this study are (BSC) strategy communication as the independent and organizational performance as the dependent variable. On one hand, strategy communication refers to a selective and planned program of communication intervention in the form of employee training on BSC concepts and principles and subsequent involvement in the actual scorecard development and implementation process (Beryl, 2015). Strategy Communication will be operationalized using three factors: valid messages; support of organizational culture; and, knowledge sharing as described

y7 = is the factor Process improvement of the Organizational Performance construct; y8 = is the factor Sustainability of strategic management of the Organizational Performance construct;

w1 = is the factor Age of the Employee Demographic construct; w2 = is the factor Gender of the Employee Demographic construct; w3 = is the factor Educational Attainment of the Employee Demographic construct; w4 = is the factor Length of Service of the Employee Demographic construct;

z1 = is the factor Relative performance evaluation of the Employee Motivation construct; z2 = is the factor Meaningful reward/penalty of the Employee Motivation construct; z3 = is the factor Appropriate benchmark of the Employee Motivation construct;

X->Y = is the regression coefficient between Strategy Communication (X) and Organizational Performance (Y);

W->Y = is the regression coefficient between Employee Demographic (W) and Organizational Performance (Y);

Z->Y = is the regression coefficient between Employee Motivation (Z) and Organizational Performance (Y);

X->Z = is the regression coefficient between Strategy Communication (X) and Employee Motivation (Z);

X->x1 … X->x3 = are the loading factors of the three components (x1 … x3) of the construct Strategy Communication

In closing, the SEM model described above represents a single integrated view of the variables of interest in the proposed research and the fact that this is rendered in a computer-based SEM modelling and simulation tool would allow testing of the various hypotheses based on actual data obtained from