This chapter will feature three categories of this study. First, it illustrates the results obtained from the pilot study. However, a comprehensive report of the pilot study is displayed on Appendix C on page 93. Secondly, the main study analysis is given beginning with sample characteristics of participants. It also presents the descriptive statistics analysis of the constructs of the main study based on the mean and standard deviation for each individual item used in this study; PLS software was used for this analysis. Finally, it presents the results of the reliability and validity test, the structural equation model test and other salient analysis which were computed courtesy of PLS.
PLS Result for Pilot Study
A pilot study was initially carried out to determine the reliability and validity of the scale and the instrument. The pilot test was with the aim to evaluate and identify the items which have low outer loadings. Therefore, may determine if necessary to drop or not. And also, to examining if the outer loadings of the measurements correspond with the constructs. As results reveals, majority of the indicators had outer loadings above 0.70, which means the items were related to the constructs they are designed to measurement. In the same vain the pilot study outcomes indicate that the Cronbach’s alpha for all the constructs has values above 0.70. This explains the degree of reliability of the items as revealed. The items for the construct of intrinsic motivation has 16 items with Cronbach’s alpha of (0.917); extrinsic motivation 16 items (0.939); knowledge sharing 12 items has (0.628); knowledge creation process has 12 items (0.891); innovation 12 items (0.935); and organizational performance 12 items (0.872). Table 4.1. below illustrates this result.
47 Table 4.1.
Cronbach’s Alpha Results for Pilot Study (N=53)
Code Construct Number of Items Cronbach’s Alpha Value
IM Intrinsic Motivation 16 0.917
EM Extrinsic Motivation 16 0.939
KS Knowledge Sharing 12 0.628
KCP Knowledge Creation Process 12 0.891
INNO Innovation 12 0.935
OP Organizational Performance 12 0.872
Note. EM= Extrinsic Motivation; IM= Intrinsic Motivation; INNO= Innovation; KCP= Knowledge Creation Process; KS=
Knowledge Sharing; OP= Organizational Performance
Table 4.2. below highlights the factor loadings for each individual item. To confirm the correlation of items and constructs, explanatory factor analysis (EFA) was conducted to measure if each item owns its factor loading and that it is higher than .40 or not, otherwise, according to Kerlinger (1986), the item will be regarded as not belonging to the variable. Hence majority of the items have a factor loading of above .40, indicating that the items could be used in the main investigation and analysis of this study.
48 Table 4.2.
Factor Loadings of All Items via PLS Pilot Study (N=53)
Coding Loadings Coding Loadings
EHO_1
Note: EHO= Enjoyment in Helping Others; KSE= Knowledge Self-Efficacy; AUTO= Autonomy; COMP= Competency;
RWC= Relationship with Co-workers; EOR= Expected Organization Reward; WE= Work environment; JS= Job Security; L=
Leadership; T= Trust; O= Opportunity; S= Socialization; C= Combination; I= Internalization; E= Externalization; PI= Process Innovation; TI= Technology Innovation; OI= Organization Innovation; CS= Customer Satisfaction; MS= Market Share; FP=
Financial Performance
49
This section illustrates the pilot test data analysis using PLS to calculate path analysis. In order to compute for the t-value and test the significance of the path coefficients a bootstrapping technique was used.
As the results depicts, there is a weak positive and significant influence of intrinsic motivation on knowledge sharing (β=0.099, t=.556, p < .01). In this case, hypothesis 1 was accepted. Second, extrinsic motivation also has a weak positive and significant effect on knowledge sharing (β=0.141, t=0.632, p < .01). Hypothesis 2 also accepted. Knowledge creation has a kind of weak positive and significant effect on knowledge sharing (β=.391, t=1.346, p < .01). Knowledge sharing, however, has a positive and significant effect on innovation (β=0.434, t=3.604, p < .001). Finally, innovation has a positive and significant influence on organizational performance (β=0.551, t=6.407, p < .001). Therefore, the null hypotheses 1, 2 and 3 were accepted while 4 and 5 were rejected.
Table 4.3.
Path Analysis Result via PLS Pilot Study (N=53)
Path Hypothesis β-path Adj. t-value Sig. Direction Null Hypotheses
IM->KS H1 0.099 0.556 + Accepted
EM->KS H2 0.141 0.632 + Accepted
KCP->KS H3 0.391 1.346 + Accepted
KS->INNO H4 0.434 3.604 + Rejected
INNO->OP H5 0.551 6.407 + Rejected
Note. EM= Extrinsic Motivation; IM= Intrinsic Motivation; INNO= Innovation; KCP= Knowledge Creation Process; KS=
Knowledge Sharing; OP= Organizational Performance p < .01, p < .05, p < .001
PLS Results for Main Study Sample Characteristics
In this study, a total of 300 questionnaires were distributed online via email. From the lot, 206 valid questionnaires were obtained constituting an overall response rate of 68.6%. The process was strictly confidential and anonymous by employees of both (Gamtel/Gamcel).
Table 4.4. provides the sample characteristics of participants in this study. The software SPSS was used to analysed this data. Four categories were used in this study, and participants responded according to their status. The four categories included were, gender, age, Level of education and work duration.
Gender: According to the results, a large number of participants in this study were male. Out of the 206 respondents, 129 constituted for males with 62.6% respondent rate. On the contrary,
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the female participants registered 37.4% of respondent rate which presents 77 out of the total 206 participants.
Age: In this section, the respondents’ age ranged from less than 20 years to above 50 years. As illustrated in the table, 20 to 30 years and 31 to 40 years has the most frequency ratings. The percentage for the two age ranges added for 23.8% and 44.2% respectively. What this explains, therefore, is that majority of the company employees are young peoples.
Level of Education: According to the results, majority of the participants in this study attained diploma level of education. This group accounted for 50.5% of respondent ratings and constituted 104 out of the total 206 participants. 32.5% accounted for bachelor degree, 11.7%
for certificate and 5.3 for master degree holders.
Work Duration: Basically, duration referred to the number of years the participants served in the company. In this category, the participants work duration with highest frequency and percentage are between 1 to 5 years and 6 to 10 years accounting 49 and 92 frequency, and 23.8% and 44.7% respectively. However, a more noticeable range also appeared to have participants serving the company long, that is, 11 to 15 years. This range registered 18.4%
which is considerable high bearing in mind the frequency value of 38 it accounted for.
51 Table 4.4.
Sample Characteristics Based on Demographic Variables (N=206)
Variable Frequency Percentage (%)
Gender Male Level of Education Certificate
Diploma Work Duration Less than 1 year
1 to 5 years
Descriptive Statistics Analysis of Questionnaire items
This section highlights the respondents’ rating of the items in relation to the variables used in the study. It provides each construct’s mean and standard deviation which also explains the strength of the mean to represent the data. The statistical software PLS 3.0 was used to compute these results. A 5-point Likert scale measurement was used ranging from “strongly disagree” to “strongly agree”. It is important to note that, only those items that were not dropped from the analysis are the items to be included here.
Findings: Intrinsic Motivation (IM)
Table 4.5. illustrates the statistical outcome of the items used to measure the construct
“intrinsic motivation” in this study. It mainly featured the mean and standard deviation of the items. A total of 16 items were used to measure this construct. The item EHO_4 (M=4.11) has accounted for the highest mean value, indicating that the respondents showed a level of agreement to the item, which corresponds to “I enjoy helping colleagues in providing assistance in difficult situations”. The lowest item mean is COMP_1 (M=3.52) representing “I have the feeling that I can even accomplish the most difficult tasks at work.” that participants answered fairly “agree” or still “neutral”. The standard deviation for AUTO_1 (SD=.88) and COMP_1
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(M=.85) and COMP_2 (SD=.85) has scored the highest values, which may explain employees resolute to keeping low profile in judging their own abilities as a result not to show off. The results imply that employees in this company have the willingness to help colleagues yet do not display superiority complex against colleagues at work.
Table 4.5.
Intrinsic Motivation via a 5-point Likert Scale (N=206)
Coding Item Mean Std. Deviation
EHO_1 I enjoy helping my colleagues in problem solving.
3.88 .67 EHO_2 It feels good to help someone accomplish a task. 3.54 .80 EHO-3 It feels pleasurable working in teams to achieve
a particular objective.
KSE_1 I have the expertise required to provide valuable knowledge for my organization.
KSE_3 It does not make any difference whether I share my knowledge with colleagues.
3.83 .67 KSE_4 Most other employees can provide more
valuable knowledge than I can.
3.97 .70
Total Average 3.86
AUTO_1 I control the content of my job. 3.69 .88
AUTO_2 I have a lot of freedom to decide how I perform assigned tasks.
3.89 .74 AUTO_3 I set my own schedule for completing assigned
tasks.
3.69 .64 AUTO_4 I have the authority to initiate projects at my job. 3.74 .72
Total average 3.88
COMP_1 I have the feeling that I can even accomplish the most difficult tasks at work.
3.52 .85
Note: EHO = Enjoyment in Helping Others; KSE = Knowledge Self-Efficacy; AUTO = Autonomy; COMP = Competency
53
Findings: Extrinsic Motivation (EM)
Extrinsic motivation has four dimensions or variables that were measured by using 16-items including, relationship with co-workers, expected organization rewards, work environment and job security. Table 4.6. highlights respondents’ perception on extrinsic motivation as denoted by its mean and standard deviation. In this regard, RWC_1 (M=4.02),
“My co-workers are supportive of my goals and values” and RWC_4 (M=3.85) which relates to “Help is available from my co-workers when I have a problem” has higher mean scores and relatively low standard deviations. This implies that employees in this company show high regards for each other and help is always available whenever needed, especially when the task is in line with company goals. And also, there shows consistency in response variation due to low score in standard deviations.
Table 4.6.
Extrinsic Motivation via a 5-point Likert Scale (N=206)
Coding Item Mean Std. Deviation
RWC_1 My co-workers are supportive of my goals and values.
4.02 .67 RWC_2 My co-workers really care about my well-being. 3.53 .92 RWC_3 My co-workers are willing to offer assistance to me
perform my job to best of my ability.
3.60 .80 RWC_4 Help is available from my co-workers when I have
a problem.
3.85 .78
Total average 3.88
EOR_1 Considering all my efforts and achievements, my job promotion prospects are adequate.
3.47 .77 EOR_2 Considering all my efforts and achievements, I
receive the respect and prestige I deserve at work.
3.82 .73 EOR_3 Considering all my efforts and achievements, my
salary/income is adequate.
3.58 .64 EOR_4 I always look forward to higher bonus for helping
others gain valuable knowledge.
3.70 .67
Total Average 3.70
WE_1 Overall, my work area is appropriate for my work. 3.60 .75 WE_2 The variety of work environments needed for my
job is available to me.
3.55 .72 WE_3 I like the style/quality of my furniture. 3.67 .69
WE_4 My work environment is too noisy. 3.62 .73
Total Average 3.70
JS_1 How likely do you think it is that you will lose your job or be laid off in the next year?
3.94 .82
54
JS_2 How satisfied are you with the amount of job security you have?
4.10 .68 JS_3 I have experienced or I expect to experience an
undesirable change in my work situation.
4.13 .70
JS_4 My job security is poor. 3.88 .77
Total Average 4.07
Note: RWC = Relationship with Co-workers; EOR = Expected Organization Reward; WE = Work Environment; JS = Job
Security (Continued)
Findings: Knowledge Creation Process (KCP)
Table 4.7. depicts the mean and standard deviation for the construct knowledge creation process. This construct has four variables that measures its effect and a total of 12 items were used in the process. As illustrated in Table 4.7., it could be realized that S_3, “My company stresses creating a work environment that allows peers to understand the craftsmanship and expertise.” C_1, “My company stresses the use of deductive and inductive thinking.” has the highest means. From this one could deduce that employees have support from management in employee quest creation new ideas through vibrant interaction via conducive environment provided. The items under (I_1, I_2 and 1_3) all have high standard deviation scores compared to the others. Implying respondents’ inconsistency in respond behaviour which kind of show their disagreement to the items under study.
Table 4.7.
Knowledge Creation Process via a 5-point Likert Scale (N=206)
Coding Item Mean Std. Deviation
S_1 My company stresses sharing experience with employees and customers.
3.72 .78 S_2 My company stresses finding new strategies and
market opportunities by wandering inside the firm.
3.87 .71 S_3 My company stresses creating a work environment
that allows peers to understand the craftsmanship and expertise. C_3 My company stresses the use of metaphors in dialogue
for concept creation.
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I_2 My company stresses building up materials by gathering management figures and technical information.
3.90 .98
I_3 My company stresses creating manuals and documents on product and services.
3.57 .81
Total Average 3.82
E_1 My company stresses forming teams as a model, conducting experiments, and sharing results with entire departments.
Knowledge sharing has two variables which constitute the construct, it includes leadership and opportunity. A total of 12 items were used to measure this construct using a 5-point Likert scale ranging from “strongly disagree” to “strongly agree”. From table 4.5, O_3,
“I am satisfied with the job-related training my organisation offers” and O_4, “I am satisfied that I have the opportunities to apply my talents and expertise” has highest standard deviations.
This explains the inconsistency of participants respond behaviours and also indicates that employees in this company are not very much satisfied with the training offered by the company. Also, there is little room for one to apply the talents and expertise acquired.
Table 4.8.
Knowledge Sharing via a 5-point Likert Scale (N=206)
Coding Item Mean Std. Deviation
L_1 The leadership thinks that encouraging knowledge sharing with colleagues is beneficial.
3.34 .71 L_2 I believe leaders in my company make cooperative
and team decision.
3.24 .66 L_3 The management is keen to see that the staffs are
happy to share their knowledge with colleagues.
3.45 .67 L_4 I sometimes feel senior staff are unwilling to learn
from junior staff because they think they have a higher position, more experience and/or authority in the company.
3.38 .75
Total Average 3.50
O_1 My Company provide training programes, structured team work, coloquial, etc. to facilitate knowledge sharing.
3.81 .70
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O_2 Company’s infrastructure enables employees to access the shared knowledge effectively.
3.60 .84 O_3 I am satisfied with the job-related training my
organisation offers.
3.91 1.01 O_4 I am satisfied that I have the opportunities to apply my
talents and expertise.
3.20 1.00
Total Average 3.88
T_1 I always have this believe that my colleagues would give me a helping hand if I encounter difficulties.
3.46 .78 T_2 I sometimes feel uncertain to share information with
colleagues if I feel there is no confidentiality.
3.39 .99
In this section, the construct innovation has three variables including, process innovation, technology innovation and organization innovation. To measure this construct, a total of 12 items were used and the table below shows the mean and standard deviation of each individual item. Items TI_1 (M=3.90), “There is rapid change in technology in our company” and TI_2 (M=3.96), “The changes in technology has provided huge opportunities in our company” have the highest mean score. The results reveal that the company is aware of the growing changes in technology and thus, employees accepts the changing trend as it provides them with opportunities that they can utilize. This could also mean the changes in technology might be an opportunity for employee career development path.
Table 4.9.
Innovation via a Likert Scale (N=206)
Coding Item Mean Std. Deviation
PI_1 Company has clear and specific process of innovation development.
3.43 .89 PI_2 In our company, service process approach changes
at a great speed in comparison with our competitors.
3.45 .76
PI_3 The nature of delivery process in our company is always different compared with that of our main competitors.
3.77 .81
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PI_4 Company encourages using process innovation to understand the information of customers, suppliers and competitors. TI_3 The technological breakthrough in our company
has made a big changes in the processing of information.
3.87 .81
TI_4 Company can fast its’ service to customers because of company’s technology innovation.
3.82 .82
Total Average 3.94
OI_1 Company improves internal communication efficiency because company’s organizational innovation.
3.50 .78
OI_2 Company cross-cultural communications ability is good for keeping ahead of market.
3.66 .69 OI_3 Company continues to import new way of
management and knowledge to keep flexibility.
3.72 .68
In relation to organizational performance, 12 items were used to measure the mean and standard deviation of the three variables, that is, customer satisfaction, market share and financial performance. For this construct, CS_1 (M=3.84), “Our competitive advantage is based on understanding our customers' needs” has the highest mean. These showed that (Gamtel/Gamcel) employees agree and understands the needs of their customers, thus edge over their competitors in providing better and quality products plus a decent service delivery.
Hence company keeps on continuous improvement of brand and services provided to customers. Furthermore, MS_2 (M=3.86), “Comparing to company’s competitors, the products of company’s brand is popular”, has the second highest mean. This implies that the company attaches significant important to product branding. Thus, endeavour rigorously to initiate products that would not only quality but stands unique in the market. All other items also showed considerable high means, explaining the agreeability and consistency of employees’
responses to items, this with regards relatively low standard deviation scores.
(continued)
58 Table 4.10.
Organizational Performance via a 5-point Likert Scale (N=206)
Coding Item Mean Std. Deviation
CS-1 Our competitive advantage is based on understanding our customers' needs.
3.84 .71 CS_2 We regularly monitor and assess our commitment to
customer satisfaction.
MS_1 Comparing to company’s competitors, company’s market development is good.
3.10 .83 MS_2 Comparing to company’s competitors, company’s
market share is high.
3.21 .90 MS_3 Comparing to company’s competitors, company’s
Sales growth is satisfying.
3.35 .80 MS_4 Comparing to company’s competitors, the products
of company’s brand is popular.
3.86 .64
Total Average 3.52
FP_1 Comparing to company’s competitors, company’s profitability is satisfying.
3.52 .76 FP_2 Comparing to company’s competitors, company’s
Cost control is good.
3.53 .74 FP_3 Comparing to company’s competitors, company’s
Cash flow from operations is satisfying.
3.60 .73 FP_4 Comparing to company’s competitors, company’s
return on investment is good.
3.50 .72
Total Average 3.61
Note: CS = Customer Satisfaction; MS = Market Sharing; FP = Financial Performance
Correlation Analysis
A correlation matrix was obtained after conducting a correlation analysis using PLS. The aim of this findings or analysis is to obtain a correlation results that could be used to observe if multicollinearity exists in the model. The concept of multicollinearity is an important feature in research and this study also uphold it’s significant. Thus, multicollinearity should exists in the correlation analysis if two variables are closely correlated to one another having values above .75. If the correlation value between two variables exceeds .75, then multicollinearity does exist and this could be problematic according to Kennedy, (1989). In this study, therefore,
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the issue of multicollinearity does not exist as all the values in the matrix are below .75. Table 4.11. displays correlation among the constructs in this study.
Even though there might exist collinearity among the constructs in this study that does not weaken the strength of prediction or the model reliability as depicted in Table 4.12 below.
Table 4.11.
Correlation among All the Constructs via PLS (N=206)
EM IM INNO KCP KS OP
EM IM
INNO 1
KCP 1
KS -0.318 1
OP -0.115 0.083 1
Note. EM= Extrinsic Motivation; IM= Intrinsic Motivation; INNO= Innovation; KCP= Knowledge Creation Process; KS=
Knowledge Sharing; OP= Organizational Performance
Table 4.12.
Collinearity Statistic (VIF) among All the Construct via PLS (N=206)
EM IM INNO KCP KS OP
EM 2.332
IM 3.241
INNO 1.000
KCP 2.495
KS 1.000
OP
Note. EM= Extrinsic Motivation; IM= Intrinsic Motivation; INNO= Innovation; KCP= Knowledge Creation Process; KS=
Knowledge Sharing; OP= Organizational Performance
60 Table 4.13.
Correlation Analysis for Main Study via PLS (N=206)
EHO KSE AUTO COMP RWC EOR WE JS L O T S C I E PI TI OI CS MS FP
EHO 1
KSE .508 1
AUTO .490 .653 1
COMP .565 .393 .499 1
RWC .448 .493 .494 .694 1
EOR .295 .271 .408 .446 .458 1
WE .416 .518 .577 .648 .580 .502 1
JS .349 .376 .432 .389 .527 .323 .483 1
L .348 .236 .235 .414 .362 .376 .353 .155 1
O .264 .224 .187 .341 .301 .232 .338 .319 .336 1
T .167 .171 .072 .140 .206 .018 .102 .113 .090 .071 1
S .504 .523 .496 .572 .551 .337 .441 .232 .251 .215 .152 1
C .444 .650 .651 .411 .545 .251 .540 .401 .220 .220 .185 .682 1
I .462 .500 .373 .454 .388 .344 .429 .341 .438 .116 .215 .493 .539 1
E .417 .410 .566 .516 .500 .377 .477 .273 .337 .106 .027 .480 .527 .422 1
PI .435 .253 .364 .616 .499 .434 .561 .408 .403 .455 .069 .424 .410 .507 .452 1
TI .525 .363 .468 .529 .432 .428 .398 .442 .429 .443 .100 .491 .407 .521 .427 .653 1
OI .446 .372 .530 .574 .638 .401 .427 .455 .348 .356 .119 .653 .570 .494 .509 .669 .662 1
CS .407 .182 .496 .480 .442 .388 .392 .350 .341 .277 .036 .309 .343 .291 .559 .436 .539 .554 1
MS .338 .281 .204 .140 .244 .193 .209 .344 .224 284 .187 .301 .371 .250 .108 .216 .315 .342 .184 1
FP .348 .206 .365 .263 .307 .301 .327 .236 .335 .210 .122 .262 .196 .227 .289 .354 .348 .329 .278 .452 1
61
Note. EHO=Enjoyment in Helping Others; KSE=Knowledge Self-Efficacy; AUTO=Autonomy; COMP=Competence; RWC=Relationship with Co-workers; EOR=Expected Organizational Reward; WE=Work Environment; JS=Job Security;
Note. EHO=Enjoyment in Helping Others; KSE=Knowledge Self-Efficacy; AUTO=Autonomy; COMP=Competence; RWC=Relationship with Co-workers; EOR=Expected Organizational Reward; WE=Work Environment; JS=Job Security;