Factors Influencing Communication Effectiveness of Employees of Central Food Retail Company Limited (Head Office)
Keywords:
Communication Patterns, Communication Components, Communication Effectiveness, Multiple Regression Analysis, Central Food Retail Company LimitedAbstract
The objectives of this study were: (1) to examine the level of opinions regarding communication patterns and communication components; (2) to examine the level of opinions regarding communication effectiveness; and (3) to investigate the influence of communication patterns and communication components on employees’ communication effectiveness. The population employed in this study consisted of 907 employees of Central Food Retail Company Limited (Head Office). The sample size was determined using Taro Yamane’s formula with a 95% confidence level, resulting in a total of 389 samples collected. The research instrument used for data collection was a questionnaire. The statistics used for data analysis included percentage, frequency, mean, standard deviation, One-way Analysis of Variance, and multiple regression analysis. The research findings revealed that the overall opinion level regarding communication pattern factors among employees was at a high level (= 4.20), the overall opinion level regarding communication component factors was at the highest level (
= 4.26), and the overall opinion level regarding communication effectiveness was at the highest level (
= 4.22). The multiple regression analysis revealed that communication patterns had a statistically significant influence on communication effectiveness within the organization at the 0.05 level. The multiple correlation coefficient was high (R = 0.853), with a predictive power of 72.4 percent (Adjusted R² = 0.724). Among the dimensions, top-down communication (β = 0.303) exerted the greatest influence. In addition, the components of communication were found to significantly affect communication effectiveness in the organization at the 0.05 level. The multiple correlation coefficient was high (R = 0.902), with a predictive power of 81.2 percent (Adjusted R² = 0.812). Among these components, the receiver dimension had the strongest influence (β = 0.463).
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