As the heading implied, this chapter highlighted the results of the conducted study and a detail discussion regarding the results were also presented.
Descriptive Statistics
The descriptive statistics covered the demographic information of this study. This particular information was gathered from one hundred and twelve (112) faculty staff from the various schools in University of The Gambia (UTG). A total of four (4) questions were used for descriptive statistics. These questions covered gender, age, level of education and number of years working. Detail information regarding the frequency and percentage of the demographic data are shown in the table 4.1 below.
42 Table 4.1.
Demographic Data of Respondents
Item Frequency Percentage 1. Gender
Male 73 65.2 Femae 39 34.8 Total 112 100 2. Age
20-30 40 35.7 31-40 53 47.3
41-50 19 17 Total 112 100
3. Education
Diploma 2 1.8 Bachelor’s 65 58.0 Master’s & 42 37.5 Doctorate
Total 112 100 4. Work Experience
< 1 year 27 24 1-5 years 58 51.8 6-10 years 20 17.9 11-15 years 7 6.3 Total 112 100
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Gender
A greater percentage of the respondents of this study were male. Out of the 112 respondents, they constituted for 65.2%. In the context of numeracy it referred to 73 males out of the 112. On the other hand, females accounted for 34.8% which constituted for a total of 39 females.
Age
The respondents’ age ranged from 20 years to above 50 years. However, the most frequent age ranged fell between 31 and 40, followed by 20 and 30. The percentage for these two age ranges accounted for 47.3% and 35.7% respectively.
Education
The level of education of most of these respondents was bachelor’s degree. This group accounted for 58% which amounted to 65 respondents out of the total of 112. On the other hand, 37.5% of the respondents representing 42 of people, were Master’s degree holders. Meaning this accounted for the second highest. The remaining 4.5% represented the doctorate and Diploma holders of 2.7% and 1.8% respectively.
Number of Years Working (Work Experience)
Experience basically referred to the number of years that the respondents spent in the University of The Gambia. In other words, their tenure. The descriptive statistics on this aspect therefore revealed that the work experience of the 112 respondents ranged from less than a year to more than 15 years. The most frequent one fell under the range of 1 to 5 years (51.8%, 58 respondents).
Discussion
With reference to the above table (4.1) showing the descriptive statistics, it was obvious that the largest number of the respondents were males and for age wise, the most frequent range was from 31 to 40. In addition, the tenure of most of the respondents was from 1 to 5 years.
Furthermore, the age range is a manifestation that University of The Gambia is a young university compared to most of the universities in the sub region. Unlike most of the faculty staff in most universities in the sub region, UTG’ faculty staff is dominated by a youthful population.
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Pearson Correlations Analysis
The Pearson correlations analysis was conducted so as to determine the relationships between the various variables. It covered the mean, standard deviation and correlations.
Table 4.2.
Mean, Standard Deviation and Correlations
Mean SD 1 2 3 4 5 6 7 8 9
1. KS 3.79 .59 (.871)
2. RW 2.92 .46 .194* (.706)
3. T 3.56 .50 .320** .385* (.758)
4. ICT 2.53 .80 -0.056 -0.09 .189* (.751)
5. LS 2.34 .67 .213* .413 .524** .484** (.916) 6. Gender 1.34 .47 -0.053 -0.074 -0.053 .230* 0.006
7. Age 2.86 .82 -0.021 -0.166 -0.006 .211* 0.151 -.201*
8. Level of
Education 3.41 .57 -0.05 -217* -0.073 .201* 0.137 -0.098 .534**
9. Tenure 2.08 .89 -0.134 -.340** -.222* 0.141 -0.092 0.116 .469** .346**
Note. 1. The Cronbach’s Alpha Values are the ones represented in the parenthesis;
2. *p<0.05. **p<0.01. ***p<0.001.
3. Gender, Age, Level of Education & Tenure were the demographics
4. KS= Knowledge Sharing, RW= Rewards, T= Trust, ICT= Information & Communication Technology, LS= Leadership
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Discussion
Table 4.2. is a table that showed a correlation between independent variables and the dependent variable as well as among the demographics. The correlation results highlighted how three out of the four independent variables were correlated with that of the dependent variable.
The independent variables that correlated with the dependent variable of Knowledge Sharing were:
Rewards, Trust and Leadership. On the other hand, the one variable out of the four independent variables that had no correlation with Knowledge Sharing was Information and Communication Technology. Detail descriptions of the information on the correlation table are discussed further.
To begin with, Rewards as the first independent variable, had positive correlation with Knowledge Sharing (r=.194, p<.05). This implied that when employees are considerably rewarded either through remuneration or recognition of their efforts towards Knowledge Sharing, they will be enthusiastically willing and ready to share their knowledge. Therefore, rewards of whatever nature is a rudiment for organizational knowledge sharing. Similarly, Trust (r=.320, p<.01). The correlation between the second independent variable of Trust and Knowledge Sharing, was greater than that of the correlation between the first independent variable of Rewards and Knowledge Sharing. Rewards and Knowledge Sharing were significant at .05 which represented one star whereas Trust and Knowledge Sharing were significant at .01, meaning it had two stars. In addition, the third independent variable that correlated with Knowledge Sharing was Leadership. This independent variable (Leadership) too had a weaker correlation with Knowledge Sharing compared with that of Trust with Knowledge Sharing. Leadership (r=.213, p<.05). As stated earlier, this implied that Leadership had correlations with Knowledge Sharing. Meaning if the leadership of any organization provides the necessary and needed support to its staff, it will pave the way for broader organizational knowledge sharing.
On the other hand, Information and Communication Technology (ICT) had no correlation with Knowledge Sharing in University of The Gambia. Similarly, none of the demographic variables was correlated with that of the predictor variable. This implied that gender, age, level of education and work experience or tenure had no correlation on Knowledge Sharing in University of The Gambia.
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Relationships between the Independent Variables and the Dependent Variable
Hierarchical linear regression was used conducted to test the four hypothesis of this study.
Each of the individual independent variables were separately entered under the heading of independent variable against the dependent variable under the heading of dependent variable.
Firstly, the first independent variable of Reward (RW) was entered under the heading of independent variable against the dependent variable of Knowledge Sharing (KS) under the dependent variable heading. Secondly, Trust as the second independent variable was put under its appropriate heading of independent variable against the dependent variable of KS under the dependent variable. In the third step, Information and Communication Technology (ICT) as an independent variable was also put under the heading of independent variable and ran against that of KS under dependent variable. Finally, the last hypothesis relating to Leadership (LS) also followed the same process and procedure as the previous independent variables.
A detail information on the results of the hypothesis testing for each independent variable in its relation to the dependent variable are shown in the tables below.
Table 4.3.
Relationship between Reward and Knowledge Sharing
Independent
Variables
Model 1 β Reward .194*
R² .038 Adjusted R² .029
ΔR² .038 F .040*
Note. *p<0.05. **p <0.01. ***p<0.00.
The table above sowed the relationship between the independent variable Reward and that of the dependent variable Knowledge Sharing.
47 Table 4.4.
Relationship between Trust and Knowledge Sharing
Independent
Variable
Model 2 β Trust .320**
R² .320
Adjusted R² .094 ΔR² .320 F .001**
Note. *p<0.05. **p<0.01. ***p<0.00.
Table 4.4 above showed a result about the relationship between Trust as an independent variable and Knowledge Sharing as the dependent variable.
Table 4.5.
Relationship Between ICT & Knowledge Sharing
Independent
Variable
Model 3
β Information &
Communication
Technology .056
R² .003 Adjusted R² .006 ΔR² .006 F .554
Note. *p<0.05. **p<0.01. ***p<0.001.
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The regression results presented in table 4.5. is about Information and Communication Technology’s (ICT) relations with Knowledge Sharing. The results indicated that ICT has no significant effect on Knowledge Sharing.
Table 4.6.
Relationship between Leadership and Knowledge Sharing Independent
Variable
Model 4 β Leadership .213*
R² .046 Adjusted R² .037 ΔR² .037 F .024*
Note. *p<0.05. **p<0.01. ***p<0.001.
The above table presented results about the extent of the effect of Leadership as an independent variable on Knowledge Sharing as a dependent variable.
Furthermore, the four tables (4.3., 4.4., 4.5., and 4.6.) that were highlighted earlier, individually represented the results for the four independent variables of this study in relation to the dependent variable of Knowledge Sharing. On the other hand, the table below (4.7.) gave a summary of these individual results.
49 Table 4.7.
Relationships between the Four Independent Variables and the Dependent Variable (N=112)
Independent tables above, the results indicated that out of these four hypothesis, all were supported except one.
The rejected hypothesis was hypothesis 3. The said hypothesis read, Information and Communication Technology has positive influence on Knowledge Sharing. It turned out that information and communication Technology which contained the dimensions of internet availability and accessibility had no significant effect on Knowledge Sharing at University of The Gambia. This however, did not concord with some other previous researches in the literature that highlighted that information and communication technology facilitated and had significant influence on knowledge sharing. These authors include: Lin (2007), Syed-Ikhsan and Rowland (2004) and Brink (2003). These authors indicated that for knowledge sharing to thrive in any institution of any type and size, Information and Communication Technology should not be ignored. Other authors such as Huysman and Wulf (2006) also explained that Information and Communication Technology aids the search, access, retrieval and dissemination of knowledge.
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As stated above, the rejected hypothesis on Information and Communication Technology (ICT) came as a surprise to the researcher. As highlighted above in the citations, ICT indeed plays a pivotal role in organizational knowledge sharing process. However, this is not the case in the University of The Gambia as this study results indicated. This could be due to the fact that the dominant method of knowledge sharing is through face to face which might require little or no ICT utilization. Also, University of The Gambia is a young university and might not have the needed and sufficient equipment and facilities that enhance internet availability and accessibility, or it could be that it lacked the needed ICT infrastructure and therefore does not bother on knowledge sharing, hence its insignificance.
On the other hand, Reward as the first independent variable with (β= .194, p<0.05) indicated a significant effect on knowledge sharing in University of The Gambia. Therefore, this results is in line with some other previous researches conducted by Davenport and Prusak (2000);
Gupta and Govindarajan (2000). They indicated that reward both in terms of incentive or recognition, truly enhances and promote organizational knowledge sharing. In addition, Bock et al. (2005) conducted a research on organizational knowledge sharing where the focus was on its relations with rewards (motivational theory). They acknowledged that reward was a source of motivation and significantly contribute to knowledge sharing.
Moreover, the research result also registered that Trust has significant impact on knowledge sharing. In fact its strength on knowledge sharing in UTG is stronger than that of Reward. This findings has also got strong literature support. Hislop (2000) believed that the stronger the bond of trust among employees in an organization, the greater the degree of knowledge sharing among them. In addition, Sharrat and Usoro (2003) explained that if organizations are determined and ready to adhere to reciprocal mutuality, commitment, as well as reliability and honesty as values that are trustworthy, then they are rest assured of an increase organizational knowledge sharing. As such, there is a strong bond of significant relationship between trust and knowledge sharing.
In addition, the last independent variable that this research result indicated had a significant relationship with knowledge sharing is Leadership. In their study, Connelly and Kelloway (2003) buttressed the idea that leadership readiness and support are rudiments for an increased organizational knowledge sharing. They stated that if the top management pave by depicting positive attitude towards knowledge sharing and they rendered every support to its course, then
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employees will ever be ready to share their knowledge whenever, wherever, and however it is needed. Similarly, Cabrera, Collins and Salgado (2006) highlighted that top management’s attitude and support towards knowledge sharing practice in an organization, can in fact positively influence employee’s perception in relation to knowledge sharing. In short, leadership support has a positive and significant impact on knowledge sharing.
Finally, the results of this study bring into limelight that a provision of Rewards, establishment of Trust among faculty staff at University of The Gambia as well as positive Leadership attitude and support greatly influence and promote Knowledge Sharing.
Based on the results of this research on determining the influence of the factors highlighted earlier, the table below shows how the established hypothesis were supported or otherwise (rejected).
Table 4.8.
Results of Summarisation of Hypothesis Testing
Hypothesis Results H1 Rewards has positive influence on Knowledge Sharing Supported H2 Trust has positive influence on Knowledge Sharing Supported H3 Information & Communication Technology has positive
Influence on Knowledge Sharing Rejected H4 Leadership has positive influence on Knowledge Sharing Supported
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Discussions
Table 4.8. above is a representation of the four hypothesis that were developed for this study based on the four independent variables. All of the four hypothesis were supported except one. The first hypothesis stated that rewards has positive influence on knowledge sharing. This hypothesis was supported. Meaning if there is appropriate and sufficient provision of rewards then the process of knowledge sharing will increase. The rewards covered both remuneration and recognition. That is, when the staff are well paid and their efforts in terms of their contributions towards knowledge sharing are always recognise, then they will always be eager and will to promote knowledge sharing. Similarly, the second hypothesis that was built on Trust was also supported. This implied that when staff have trust in the management and among themselves, the magnitude of knowledge sharing will undoubtedly increase. If the staff feel that they are secure and there will be confidentiality when they contribute by sharing their knowledge then they will whole heartedly do that.
On the other hand, it was hypothesised that Information and Communication Technology has positive influence on knowledge sharing. This hypothesis was however rejected. This is interpreted by saying that Information and Communication Technology has no significance influence on knowledge sharing. Meaning weather there is sufficient internet provision and well equipped internet infrastructure it does not matter because it does not have a toll on knowledge sharing. Finally, the last hypothesis stated that Leadership has a positive influence on knowledge sharing. Like the previous two hypothesis on rewards and trust, this hypothesis too was supported.
This implied that when the behaviour of the leadership towards knowledge sharing is positive and encouraging, then the rest of the staff will follow suit. Again, when the leadership provides the necessary support by availing the required equipment and resources that are necessary and do facilitate knowledge sharing then knowledge sharing is bound to thrive.
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