CHAPTER 5: DISCUSSION, CONCLUSION AND IMPLICATIONS
5.1 Discussion of Major Findings
This section investigated the effects of four independent variables (IV) on graduate unemployment in Malaysia. A total of 387 target respondents answered the disseminated questionnaire on their employability skills (ES), quality of education (QE), job expectations (JE), and market demand (MD) for graduate unemployment (GU). The relationship between the four IVs and DV (graduate unemployment) is examined using Multiple Linear Regression models. The main conclusion was that all of the predictive components, such as employability skills, quality of education, job expectations, and market demand, were shown to be clearly and strongly connected with graduate unemployment at various points.
Table 5.1:
Hypothesis Statement Acceptance
Hypothesis (H) Statement Result
H1 There is a significant negative relationship between employability skills and the unemployment of Malaysian graduates.
Do not reject
H2 There is a significant negative relationship between the quality of education and the unemployment of Malaysian graduates.
Do not reject
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H3 There is a significant positive relationship between job expectations and the unemployment of Malaysian graduates.
Do not reject
H4 There is a significant negative relationship between market demand and the unemployment of Malaysian graduates.
Do not reject
5.1.1 Hypothesis 1: Employability Skills
The employability skills correlation coefficient value is -0.578. The negative value in correlation coefficient reveal that employability skills and graduate unemployment are moderately negatively connected. On the other hand, the p-value for employability skills (0.0000) is smaller compare to the alpha value of 0.01, indicate that employability skills and graduate unemployment are significantly related.
In our study, the employability skills are basically formed by 5 soft skills which are communication skill, adaptability skill, problem-solving skill, English language skill and leadership qualities. In analysis, the majority of the respondents agrees that employability skills are important for graduates to get employed where 35% of respondents agree with it and 57.62% of respondents strongly agree with that. In terms of communication skills, 34.11% of respondents disagree that they are lacking in communication skills, while 39.02% of respondents agree that they are lacking in communication skills. There is a slightly higher percentage that shows graduates in Malaysia are unconfident in their communication skills. Moreover, a higher percentage of respondents (43.15%) feels that they have no problem adapting to a new environment and new knowledge in a short period while 38.24% of them agree that they are lacking in adaptability skills.
Besides, a slightly higher portion of respondents (41.86%) thinks that they are not lacking in problem solving skills, 50.90% of respondents disagree that they are lacking in English communication skills, 46.77% disagree that they are lacking in leadership qualities. It reflects that
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majority of the respondents think that they are good in their employability skills since the findings also shows that the majority of the people are having stable jobs currently. However, communication skills seem like a challenge to current graduates in Malaysia since a bigger portion of respondents agree that they are weak in communication skills. Besides, it is also worth notice that a larger percentage of respondents agree that they are lacking relevant working skills in their field of study, which amounted to 43.15% (refers to Appendix 4.3).
We can observe that the parameter estimate of employability skills is -1.698 using Multiple Linear Regressions for employability skills. This means that if employability skills increase by 1, graduate unemployment will decrease by 12.417 including the intercept. The variation of employability skills has contributed 39.50% of the variation of dependent variable using R-Square of Multiple Linear Analysis.
5.1.2 Hypothesis 2: Quality of Education
The correlation coefficient for quality of education is -0.449. The negative correlation coefficient value reveals that quality of education and graduate unemployment are moderately negatively connected. On the other hand, the p-value for quality of education (0.0000) is smaller than the alpha value of 0.01, indicating that quality of education and graduate unemployment are significantly related.
In our study, the quality of education is primarily affected by five factors: the administrative support system, the syllabus, the knowledge delivered by lecturers, the competency of lecturers, and the teaching method of lecturers. According to the study, 43.67% of respondents agree and 31.27% strongly agree that the administrative support system determines student quality. The administrative support system includes the university library, health care centre, sports facilities, and faculty offices. Graduates can substantially improve their quality of education by studying in an environment with a strong administrative support system. The majority of respondents disagree that the syllabus I studied is unrelated to the job industry, with 23% disagree and 21.71% strongly disagree, indicating that the majority of graduates are content with their field of study. Furthermore,
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42.12% of respondents agree, and 34.88% strongly agree that they can receive knowledge presented by lecturers. Additionally, many respondents agree that the competency of lecturers is important, with 288 persons in the agree category, of which 35.14% agree and 39.28% strongly agree. Finally, many respondents agree that the lecturers' teaching methods are important, with 298 persons in the agree category, 37.47% agree, and 39.53% strongly agree. (Refers to Appendix 4.3)
We can observe that the parameter estimate of quality of education is -0.643 using Multiple Linear Regressions for quality of education. When quality of education rise by 1 unit, graduate unemployment will also rise by 13.472 with the inclusion of intercept. The quality of education contributed as one of the independent variable to interpret 39.50% of the variation of graduate unemployment using R-Square of Multiple Linear Analysis.
5.1.3 Hypothesis 3: Job Expectations
The correlation coefficient value for job expectations is 0.487. The values of the positive correlation coefficient reveal that job expectations and graduate unemployment are moderately positively connected. On the other hand, Job expectations have a p-value of less than 0.0000, which is lower than the alpha value of 0.01, showing that they are significantly related to graduate unemployment.
In our study, job expectations are mostly determined by seven factors which are salary, preferred location, working environment, medical benefits, job position, bonus, and work-life balance.
According to the study, the majority of respondents agree that expecting a high-income amount to accept an offer with 37.21% agree and 28.17% strongly agree. As a result, one of the reasons most graduates are jobless or unable to find work is the expectation of high pay or salary. Furthermore, the majority of respondents agree on location as a preference for finding a job, with 38.50% agree and 33.85% strongly agree. Some graduates will prefer to work at a company nearby to their home or in a location with accessible transportation, however this often results in many graduates losing a lot of employment opportunities when they can't find their preferred area to work. According to
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the data analysis, the majority of respondents agree or strongly agree on a good working environment, medical benefits, job position, bonus, and work-life balance. According to these data, more than 50% of respondents agreed or strongly agreed with the statement. Since the respondents are all recent graduates, people all have higher expectations for their future jobs, willing to work in a well-paying and comfortable environment. However, expectations are frequently excessively high, which has the opposite impact, as our study found that the higher the job expectations, the higher the graduate unemployment. (Refers to Appendix 4.3)
The parameter estimate value is shown 0.673 using Multiple Linear Regressions for job expectations. It indicates that if job expectations increase by 1, graduate unemployment will grow by 14.788 involving the intercept. The job expectations contributed as one of the independent variable interpreting 39.50% of the variation of graduate unemployment using R-Square of Multiple Linear Analysis.
5.1.4 Hypothesis 4: Market Demand
The value of the market demand correlation coefficient is -0.519. The negative value reveals that market demand and graduate unemployment are moderate negatively connected. On the other hand, the p-value for market demand is less than 0.0000, which is less than the alpha value of 0.01, indicating that market demand and graduate unemployment are significantly related.
In our study, the market demand is defined as the demand of graduates in the labour market whether during the inflation or recession. According to the findings, the majority of respondents believe that market demand is strongly influencing their unemployment rate. Since we assume that COVID-19 leads Malaysia’s economy to a recession stage, a high percentage of respondents agree that they take more time and effort to find a job during recession up to 89.15% . Besides, a high portion of 71.58% respondents thinks that jobs available in their studied industry have been affected during the recession; while 67.44% of respondents agree that high-skilled job-available have reduced during the time.
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In addition, a slightly higher number of respondents (58.40%) stand the point that there is an imbalance between job demand and supply in the labour market. From their own view, 62.27% of respondents stated that most of the companies reduce the number of job positions available in their field of study. According to the data analysis, the economy and labour market are influencing the unemployment rate of graduates as they coincidently face the recession when finding a job after graduation. Thus, this also proved the hypothesis that the lower the market demand, the higher the graduate unemployment. (Refers to Appendix 4.3)
We can observe from Multiple Linear Regressions that market demand has -0.839 of parameter estimate value. It indicates that when market demand grows by 1, graduate unemployment will increase by 13.276 involving the intercept. Besides, market demand also contributed as one of the independent variable interpreting 39.50% of the variation of graduate unemployment using R- Square of Multiple Linear Analysis.