CHAPTER 5: RESEARCH FINDINGS
5.3 Data Collection Analysis
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Primary data for this thesis were collected from participants from different cultural backgrounds (Bhatti et al., 2019). A detailed survey questionnaire was created by the researcher prior to the start of the data collection procedure (Hall, Hume and Tazzyman, 2016). All the participants of this online survey work in public services across the United Arab Emirates. A simple random sampling method was considered as the sampling method to collect the primary raw data. The sample size of the population is 124, and each one of is the sample was made aware of the topic and the purpose of this research.
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Afthanorhan and Mamat, 2016). Results and graphs can be easily generated using this scale; at the same time, it can be said that this scale was much easier for the researcher to construct. On the other hand, there are a few drawbacks associated with the use of this scale as well; one of the prime drawbacks is that it judges a question on the basis of the total score obtained from every sample of the population.
5.3.1 Sample Size
It is defined as the term which indicates the number of subjects in a sample; the general population of a specific study can be understood in the first place using the sample size of the population. The number of individual samples in a survey is also termed as the sample size of the population in the thesis. The sample size of the population in this thesis is 124. Individuals come from a different cultural background; hence, the validity of this research will be very important in identifying the ways to manage the employees’ behaviour in multi-cultural organisation.
5.3.2 Gender
The orientation of the samples can be successfully understood from this demographic question. Out of the 124 individuals who took part in this data collection method, 80 of them are males and 28 of them are females, and the rest 16 of them have not stated their gender. Thus, of those who did, 64.5% are male and the rest (22.6%) are females. The valid percentage of females is 25.93% and the valid percentage of males is 74.07%. Thus, based on the above, it can be understood that most of the population of this sample are males. The gender biasedness of the survey is shown in the following diagram.
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Figure 5. 1: Gender of the participants
5.3.3 Education
This demographic question will be very significant to understand the highest educational achievement of the participants who have taken part in the online survey. Out of the total 124 participants, six of them do not have even a high school degree, nine of them only have a high school qualification, nine of them have their diploma certificate, 44 of them have a bachelor’s degree and 38 of them have successfully completed their master’s degree; however, 18 participants have not stated their educational qualification. Thus, it can be said that most of the sample are very well educated and have the minimum qualifications required to take part in this online survey. The following diagram is be very significant in understanding the distribution of the participants’ educational history.
Figure 5. 2: Education of the participants
139 5.3.4 Training to UG/PG level
This demographic question will be very useful to understand whether the survey participants have any IT-related qualification at any level. Out of the 124 participants, 57.94%
of them have IT-related educational qualifications, whilst 42.06% of them do not. Thus, this question was very useful to understand the fundamental IT knowledge of the participants who have been a part of this online data collection procedure. The distribution of these results is provided in the below figure.
Figure 5. 3: Qualification of the participants
5.3.5 IT-Related Training Courses
This demographic question will be very useful to understand the basic IT knowledge of the participants who have stated their opinion in the online survey. Out of the 124 respondents, 22.6 % of them have not gone through any type of IT-related training course, 18.69% of them have a minimum of one training course, 31.78% of them have been a part of two to five training courses and 20.36% of them have been through more than five training courses. Thus, out of the 124, 28 of them have not gone through any IT-related training courses and the rest have.
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Figure 5. 4: Attendance on IT-related training courses
5.3.6 Years Working in Current Position
This demographic question is very significant for the readers of this thesis to comprehend the experience of all the participants, who have worked for several years in their existing position. Out of the 124 participants, 20.19% of them have over 20 years of experience working in their current position, 23.08% of them have between 11- and 20-years’ experience, 25.96% of them have six to 10 years’ experience and the rest (30.77%) have one to five years of work experience in the current position. Thus, it can be identified that most of the sample population are very experienced in working in the same position over the years.
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Figure 5. 5: Years in current position
5.3.7 Position Held at Work
The designation of each survey participant can be understood in the first place using this demographic question. Out of the 124 participants, 19 skipped this question, 20% work as supporting staff or in the administrative units, 10.5% work as IT staff, 36.2% work as management staff, and 33.3% of the sample work in other positions. Thus, it can be understood that most of the survey participants work in a managerial role in their respective organisations.
The entire distribution of the participants’ designations can be successfully understood from the below pictorial presentation as well.
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Figure 5. 6: Position held at work
5.3.8 Nature of Task Performed in the Workplace
The nature of the work performed by each of the survey participants can be understood from this demographic question. Data gathered from the population help in understanding that 107 of the participants have stated the nature of their work whereas the other 17 have not stated this. Out of the 124 participants, 11.21% of them work as typing experts, 12.15% of them work as data entry operators, 10.28% of them work as data administrators, 8.41% of them work as communication experts, 3.74% of the population works in a general secretarial role, 6.54% of them work in computer maintenance, another 6.54% of the population works as system development experts or as software programmers, and the rest (41.12%) of the population work in a management role.
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Figure 5. 7: Nature of task
5.3.9 Common Method Variance (CMV)
All the variables of a research paper can be measured in accurate modus using CMV;
the biasedness of any data which might influence the research analysis is addressed using this measurement method. This thesis factor will make the most out of Harman’s single factor so that the total variance of one of the factors does not exceed 50%. Identifying the common method variance can be done with the help of Harman’s single factor as well, and the majority of the covariance among the factors can also be identified using Harman’s single factor. The relationship between the variables of this project can also be identified with the help of CMV.
The initial Eigenvalues are analysed using the CMV; based on the analysis of all the 124 components of this research, it can be concluded that the first component rotation extraction sum of squared loading is 42%, which is much less than 50%, which is the general standard to identify the biasedness of the instruments which are being used to analyse the collected data.
Hence, it can be stated that the instruments do not have any biasedness.
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Table 5. 1: Data total variances
Total Variance Explained
Component
Initial Eigenvalues
Extraction Sums of Squared Loadings
Rotation Sums of Squared Loadings
Total
% of Variance
Cumulative
% Total
% of Variance
Cumulative
% Total
% of Variance
Cumulative
% 1 52.430 42.282 42.282 52.430 42.282 42.282 36.595 29.512 29.512 2 16.435 13.254 55.536 16.435 13.254 55.536 23.925 19.294 48.807
3 4.218 3.401 58.938 4.218 3.401 58.938 4.916 3.965 52.771
4 3.113 2.510 61.448 3.113 2.510 61.448 4.130 3.330 56.102
5 2.752 2.219 63.667 2.752 2.219 63.667 3.546 2.860 58.961
6 2.310 1.863 65.530 2.310 1.863 65.530 3.033 2.446 61.407
7 2.053 1.656 67.186 2.053 1.656 67.186 2.873 2.317 63.724
8 1.935 1.561 68.747 1.935 1.561 68.747 2.660 2.145 65.870
9 1.793 1.446 70.193 1.793 1.446 70.193 2.229 1.798 67.668
10 1.705 1.375 71.568 1.705 1.375 71.568 2.187 1.764 69.431 11 1.673 1.349 72.917 1.673 1.349 72.917 1.923 1.551 70.982 12 1.523 1.228 74.146 1.523 1.228 74.146 1.650 1.331 72.313 13 1.468 1.184 75.330 1.468 1.184 75.330 1.565 1.262 73.575 14 1.362 1.098 76.428 1.362 1.098 76.428 1.560 1.258 74.833 15 1.319 1.064 77.492 1.319 1.064 77.492 1.548 1.249 76.082 16 1.248 1.006 78.498 1.248 1.006 78.498 1.516 1.223 77.304
17 1.205 .972 79.470 1.205 .972 79.470 1.515 1.222 78.526
18 1.113 .898 80.368 1.113 .898 80.368 1.502 1.211 79.737
19 1.064 .858 81.225 1.064 .858 81.225 1.481 1.194 80.931
20 1.010 .815 82.040 1.010 .815 82.040 1.375 1.109 82.040
21 .973 .784 82.825
22 .948 .764 83.589
23 .912 .735 84.324
24 .885 .714 85.038
25 .864 .697 85.735
Extraction Method: Principal Component Analysis.
The Eigenvalues of the extracted components can be comprehended from the below pictorial representation.
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Figure 5. 8: Screen plot for the eigenvalues