According to results, 39.1% and 60.9% of the studied cases are male and female, respectively. In addition, 12.4%, 46.7%, 30.7% and 10.2% of the cases were 20–30, 30–40,40–50 and > 50 years old, respectively. Regarding education, 2.9%, 66.2% and 30.9% of the cases have over-diploma, B.S and M.S and above degree, respectively. Furthermore, 11.2%, 22.4%, 38.4%, 17.7% and 10.3% of the cases has < 5, 5–10, 10–15, 15–20 and > 20 years of job experience. Of the studied cases, 13.6% were non-experts, 76.3% were experts, 7.1% were experts in charge and 3% were managers. Regarding the travel time from home to university, 32.6%, 42% and 25.4% of the cases was travelling the distance in less than half an hour, 0.5-1 hour and > 1hour, shows in Table 1.
Table 1
Demographic Characteristics of Research Sample.
Variable | Frequency | % |
Sex | Male | 66 | 39.1 |
Female | 103 | 60.9 |
Age | 20–30 | 21 | 12.4 |
30–40 | 79 | 46.7 |
40–50 | 52 | 30.7 |
> 50 | 17 | 10.2 |
Education | Over diploma | 5 | 2.9 |
BS | 112 | 66.2 |
MS and above | 52 | 30.9 |
Job experience | < 5 | 19 | 11..2 |
5–10 | 38 | 22.4 |
10–15 | 65 | 38.4 |
15–20 | 30 | 17.7 |
> 20 | 17 | 10.3 |
Position | Non-specialist | 23 | 13.6 |
Specialist | 129 | 76.3 |
Responsible specialist | 12 | 7.1 |
Manager | 5 | 0.3 |
travel home-university distance | < half an hour | 55 | 32.6 |
0.5-1 hour | 71 | 42 |
> 1 hour | 43 | 25.4 |
The T-test results also revealed the positive and significant relationship of gender with the communication skills (P = 0.04).The ANOVA results revealed the positive and significant relationship of age group, level of education and travel home-university distance with the communication skills affected the productivity of employees (P ≤ 0.05).
The results of Pearson correlation analysis revealed a positive significant relationship between the dimensions of communication skills and human resource productivity (p = 0.000). On the other hand, the coefficient of correlation is R = 0.814 which has a positive sign and is a high value. Therefore, this relationship is direct and strong in the meaning that as communication skills increase, human resource productivity. The results of Pearson correlation analysis showed a significant positive relationship between the dimensions of communication skills and human resource productivity where effectiveness (r = 0.812, p = 0.000), listening (r = 0.706, p = 0.000) and verbal (r = 0.624, p = 0.000) dimensions have the highest correlation with human resource productivity, respectively shows in Table 2.
Table 2
The Coefficient of the Correlation of Communication Skill Dimensions with Human Resource Productivity of Research Sample.
Variable | Coefficient of correlation | Sig. level | number |
Communication skill dimensions | verbal → HR productivity | 0.624 | 0.000 | 169 |
listening → HR productivity | 0.706 | 0.000 | 169 |
Effectiveness→HR productivity | 0.812 | 0.000 | 169 |
The regression implementation stages of communication skills with standard and non-standard coefficients, standard deviation, and t-test with their significance levels, show in Table 3. Therefore, it can be stated that there is a significant linear relationship between communication skills and human resource productivity. T-test for regression coefficient also shows the significance of this coefficient (sig = 0.000). In other words, communication skills has a positive significant effect on human resource productivity as indicated by the positive sign of B-factor, shows in Table 3.
Table 3
Regression model coefficients.
Model | Non-standard coefficient | Standard coefficient | t | Sig. level |
B | Std. Error | Beta |
Constant | 0.512 | 0.163 | - | 3.140 | 0.000 |
Communication skills | 0.831 | 0.046 | 0.814 | 18.100 | 0.000 |
The effect and explanatory role of each communication skills dimension on human resource productivity were determined by entering method regression analysis. Study data indicate that the correlation of the effectiveness dimension, which was introduced to the regression model to explain the variance of human resource productivity, is 0.812 and it explains 66% of changes to human resource productivity. Listening skill was introduced to the model too with the coefficient of correlation of 0.706 and the coefficient of determination of 49%. Moreover, the correlation between verbal skills and human resource productivity was 0.624 and verbal skills explained 38% of changes to human resource productivity, shows in Table 4.
Table 4
The Effect and Role of Each Communication Skill Dimensions on Human Resource Productivity of Research Sample.
Regression results | R | R² | Adjusted R² | F | Sig. | STD | Durbin-Watson |
Verbal skill | 0.624 | 0.389 | 0.385 | 106.214 | 0.000 | 0.49037 | 1.74 |
Listening skill | 0.706 | 0.498 | 0.495 | 165.598 | 0.000 | 0.44444 | 1.92 |
Effectiveness skill | 0.812 | 0.660 | 0.658 | 323.690 | 0.000 | 36.591 | 1.52 |
Multiple regression models showed that increased verbal skill, listening skill and effectiveness skill increased human resource productivity. Among all factors influencing human resource productivity based on β coefficient, effectiveness skill the most impact on human resource productivity, shows in Table 5.
Table 5
The Coefficient of the Correlation of Communication Skill Dimensions with Human Resource Productivity of Research Sample.
Model | Non-standard coefficient | Standard coefficient | t | Sig. level |
B | Std. Error | Beta |
Dimensions of communication skills | Constant | 1.274 | 0.212 | - | 6.016 | 0.000 |
Verbal skill | 0.602 | 0.058 | 0.324 | 10.306 | 0.000 |
constant | 1.313 | 0.167 | - | 7.848 | 0.000 |
Listening skill | 0.609 | 0.047 | 0.706 | 12.869 | 0.000 |
Constant | 0.953 | 0.140 | - | 6.806 | 0.000 |
Effectiveness skill | 0.711 | 0.040 | 0.812 | 17.991 | 0.000 |