Factors Affecting Job Placement on the Job Mismatch among Omanis in the Sultanate of Oman: Analytical Perspective

This paper examines the intricate terrain of job mismatch among recent graduates in the Sultanate of Oman, seeking to unravel the complex array of factors that contribute to this phenomenon. The primary objectives of the study are: firstly, to scrutinize the factors shaping job mismatch; secondly, to assess the impact of varied job search strategies on the occurrence of job mismatch among fresh graduates; and finally, to analyse the role of employability skills specifically, technical skills, soft skills, and social mobility skills in influencing job mismatch outcomes. The research employs a comprehensive framework with independent variables including technical skills, soft skills, social mobility skills, and job search strategies, while the dependent variable is job mismatch. The findings reveal that there is a significant relationship with job mismatch, emphasizing their pivotal role in shaping graduates' alignment with their chosen careers. Notably, any deficiency or weakness in these independent variables can precipitate the occurrence of job mismatch. This paper contributes valuable insights to the field of career development by shedding light on the nuanced interplay between various factors that influence job mismatch in the unique context of Sultanate of Oman. By understanding the intricacies of this phenomenon, policymakers, educators, and employers can collaboratively work towards enhancing the employability and career satisfaction of new graduates, thereby fostering a more harmonious alignment between workforce skills and industry demands.


Introduction
Education is the process where an individual acquires or imparts basic knowledge to another (Hossain et al., 2023).It is also where a person develops skills essential to daily living, learns social norms, develops judgment and reasoning, and learns how to discern right from wrong.The ultimate goal of education is to help an individual navigate life and contribute to society once they become older (Hossain et al., 2018a;Hossain et al., 2018b).There are various types of education but typically, traditional schooling dictates the way one's education success is Vol 14, Issue 1, (2024) E-ISSN: 2222-6990 measured.People who attended school and attained a higher level of education are considered more employable and likely to earn more.In developing, low-income countries, for example, there is a projected 10 per cent increase in a person's future income for every additional year of education.Education helps eradicate poverty and hunger, giving people the chance at better lives.This is one of the biggest reasons why parents strive to make their kids attend school as long as possible.It is also why nations work toward promoting easier access to education for both children and adults.Education is typically divided into three categories: formal education, informal education, and non-formal education.Formal education Formal education is the type that is typically conducted in a classroom setting in an academic institution.This is where students are taught basic skills such as reading and writing, as well as more advanced academic lessons.Also known as 'formal learning', it usually begins in elementary school and culminates in post-secondary education.It is provided by qualified teachers or professors and follows a curriculum.

Informal Education
Informal education, on the other hand, is the type that is done outside the premises of an academic institution.Often, this is when a person learns skills or acquires knowledge from home, when visiting libraries, or browsing educational websites through a device.Learning from the elders in one's community can also be an important form of informal education.Such education is often not planned or deliberate, nor does it follow a regimented timetable or a specific curriculum.It is spontaneous and may also be described as a natural form of education.

Non-formal education
Non-formal education has qualities similar to both formal and informal education.It follows a timetable and is systemically implemented but not necessarily conducted within a school system.It is flexible in terms of time and curriculum and normally does not have an age limit.The most common examples of non-formal education include community-based courses, vocational training or short programs that are not facilitated by professional instructors.If all students in low-income countries acquired basic reading skills before leaving school, entire societies could change dramatically.According to UNESCO, nearly 60 million people could escape poverty if all adults had just two more years of schooling.If all adults completed secondary education, 420 million could be lifted out of poverty.But education isn't just about living above the poverty line (UN Report, 2021) Education is a human right, a powerful driver of development, and one of the strongest instruments for reducing poverty and improving health, gender equality, peace, and stability (Hossain et al., 2018c).It delivers large, consistent returns in terms of income, and is the most important factor to ensure equity and inclusion.For individuals, education promotes employment, earnings, health, and poverty reduction.Globally, there is a 9% increase in hourly earnings for every extra year of schooling.For societies, it drives long-term economic growth, spurs innovation, strengthens institutions, and fosters social cohesion.Developing countries have made tremendous progress in getting children into the classroom and more children worldwide are now in school.But learning is not guaranteed, as the 2018 World Development Report (WDR) stressed.Making smart and effective investments in people's education is critical for developing the human capital that will end extreme poverty.
At the core of this strategy is the need to tackle the learning crisis, put an end to Learning Poverty, and help youth acquire the advanced cognitive, socioemotional, technical and digital skills they need to succeed in today's world.Youth have also suffered a loss in human capital in terms of both skills and jobs.High learning poverty hinders more advanced skill development, and youth enter the workforce lacking the skills needed to be productive, resilient, and adaptable.An estimated two-thirds of the world's youth fail to achieve the equivalent of PISA minimum proficiency in language and math skills.Youth who suffer from high learning poverty achieve even worse rates of basic skills proficiency at the secondary level, which often prevents them from acquiring the higherorder, technical, and digital skills needed for the workplace, especially non-routine cognitive tasks that complement technology.Young men often further face underachievement in skills acquisition and young women face barriers to translating their skills into economic opportunities.Unemployment is a serious problem in countries across the world (Hossain et al., 2018a;Saleh et al., 2023).More than 5 million people will become unemployed by the end of next two years, making the existing unemployment situation worst due to slowing down of global economy.The International Labor Organization has warned that the unemployment will rise by about 3.5 million in 2017 to 204.9 million and that 1.5 million would be added to the global rate in 2018 to become more than 206 million.The level of employment and unemployment rate are highly influenced by the level of economic growth in any country (Al Qalhati et al., 2020a;Al Qalhati et al., 2020b).A country which is having higher rate of economic growth, unemployment rate is reduced due to creation of more jobs offering higher employment opportunities to educated youth.As a result of economic growth, there is higher level of demand for educated youth.Countries with higher economic growths are required to ensure corresponding growth in generating educated youth to fulfil the market demand for qualified persons.Under this context, it is the primary responsibility of the government of a country to ensure that an appropriate education and training systems are in place so as to cater to the demanding needs of the industrial sector so that the country is able to achieve sustainable growth of the economy.

Problem Statement
Employment is one of the main goals of every individual, which forms the basis of winning bread and other basic needs of the individual and the concerned family.In recent times the consciousness of mismatching a job is undertaken with respect to the education of concerned employee, is found to yield underperforming and non-conforming results which in later stages leads to employee turnover.This problem is found to be magnified in multiple folds in the region Sultanate of Oman, declining its status of economic operations.Further, the factors playing a pivotal role are technological advancements, economic slowdown, and socio-cultural changes that are evolving due to globalization.
In terms of addressing this perceived skills mismatch, 44 per cent of Omanis believed that companies should provide training opportunities to employees, 38 per cent believed that educational institutions and governments should work together to predict future skills needs, and 38 per cent believed that companies and educational institutions should work together to provide students with the skills they need to enter the job market (Bayt, 2016).

Limitations
The factors influencing job placement and causing job mismatch among Omanis in Oman include inadequate educational alignment with market needs, a dearth of relevant skills, limited vocational training opportunities, and mismatched expectations between employers and job seekers.Additionally, regional disparities in economic development and job availability contribute to placement challenges.Social and cultural factors may also play a role, such as gender norms impacting career choices.Overcoming these limitations requires targeted educational reforms, enhanced vocational training programs, and a better understanding of local labor market dynamics to bridge the gap between job supply and demand in Oman.Collection on the data was yet another important challenge as many employers did not wanted to disclose the information termed as confidential.

Literature Review
The government of Oman is actively diversifying its economy away from dependence on oil, aiming to nurture a competitive private sector.This involves enhancing the skills of the national workforce and boosting productivity in the private sector while maintaining the supply of skilled foreign workers crucial for competitiveness.In 2020, foreign workers constituted 77% of the total workforce, with Omanis dominating the public sector and foreign workers being more prevalent in the private sector (International Labour Organization, 2022).Nationalization policies have led to increased Omani employment in the private sector compared to the public sector over the past decade.The COVID-19 pandemic presented an opportunity for Oman to further integrate Omanis into the private sector, with their share rising from 15% to 24% in 2021 (International Labour Organization, 2022).To support diversification efforts, the Omani Chamber of Commerce and Industry (OCCI) is actively involved in assessing and monitoring the country's skills needs, identifying potential obstacles to diversification.The survey of 106 firms in Oman conducted between May and June 2022, along with desk research, provides valuable insights for businesses, policymakers, workers' organizations, and employers to assess policy options, especially concerning skills development for nationals and skills-based international recruitment.
The study revealed that lower-skilled nationals typically occupy white-collar clerical and support roles, while low-skilled foreign workers are more prevalent in elementary occupations.At the high-skilled professional level, foreign workers outnumber nationals, indicating Oman's reliance on importing technical skills.However, at the mid-level technician and associate professional positions, the numbers of nationals and foreigners are comparable, suggesting an increasing presence of nationals in technical fields (International Labour Organization, 2022).During the pandemic, firms faced challenges hiring nationals for high-skilled occupations due to wage and work condition expectations and a perceived lack of skills and experience.Foreign worker recruitment also encountered difficulties, mainly due to visa and immigration restrictions.Looking ahead, surveyed firms expressed plans to hire new workers, particularly in higher-skilled positions, but expressed concerns about the availability of nationals with the required technical, behavioral, and soft skills (International Labour Organization, 2022).Additional findings indicate that while most firms have human resources development staff, only a fraction have health and safety representatives, training budgets, or joint workers committees.Approximately half of the surveyed firms have policies promoting nationalization, ensuring workplace safety, and resolving employment disputes, but fewer have policies related to subcontractor employment standards and gender dimensions at work (International Labour Organization, 2022).In 2019, the primary sectors of employment for Omani nationals in the private sector were construction (22%), real estate (19%), wholesale and retail (15%), and manufacturing and mining and quarrying (12%).Foreign workers, on the other hand, were predominantly engaged in construction (30%), domestic work (14%), wholesale and retail trade (14%), and manufacturing (12%) (International Labour Organization, 2022).By 2021, these leading economic sectors persisted, with an increase in health and social workers among Omanis, as well as in transportation, storage, and communication, while community and social services experienced a significant decline.In terms of skill levels, Omanis in the private sector were categorized into occupational labor (32%) and limited skill labor (27%) in 2019.Foreign workers were largely classified as limited skill labor (46%) and occupational labor (23%).Notably, there were gender variations in occupational categories, (International Labour Organization, 2022) with female nationals primarily falling into mid-level occupational workers (48%) and high-skilled specialists (25%), while male nationals were more distributed among limited skilled (27%), occupational workers (26%), and skilled workers (23%).The factors affecting job mismatch and job placement among Omanis in the Sultanate of Oman are diverse and can be influenced by various economic, educational, and societal elements.A mismatch may occur when the skills acquired through education do not align with the requirements of available jobs.The education system needs to be attuned to the demands of the labor market.Disparities in the quality of education and the skills acquired may lead to a gap between what is taught in educational institutions and what is required in the job market The economic structure of Oman, which has traditionally been reliant on oil, may contribute to mismatches as the labor market evolves with economic diversification efforts.The overall demand for jobs and the specific industries that are growing or contracting can impact job placement and mismatches.Mismatches can arise when there is a lack of alignment between the technical skills possessed by job seekers and those sought by employers.
In addition to technical skills, soft skills such as communication, teamwork, and problemsolving may also contribute to job placement challenges (Javed et al., 2020).Government policies aimed at increasing the employment of Omani nationals, such as Omanization, may influence job placement and mismatch by prioritizing the hiring of local talent.Labor market regulations and policies can impact the ease with which individuals find suitable employment.Job seekers may face challenges due to their limited work experience and specific expectations, contributing to mismatches.Gender-related factors and societal expectations can influence job placement and the types of jobs that individuals pursue.Societal attitudes towards certain occupations may influence job choices, leading to mismatches based on perceptions of the prestige associated with specific jobs.

Research Objective
To study the factors that influence job mismatch of new graduates in Oman

Research Question
What are the factors that influence job mismatch of new graduates in Oman?

Research Methodology
The study aims to investigate the factors that influence the job mismatch in Oman.The quantitative research approach is selected to provide a deeper understanding of the intricacies of entrepreneurial leadership in this unique context.

Research Design
Quantitative Approach: This study employs a quantitative research design, as it allows for an in-depth study of the factors affecting job mismatch.Data was collected through survey questionnaire through google using a 5-point likert scale based closed ended questions.Close-ended online questionnaire allowed the participants to provide in-depth survey feedback to the survey.Quantitative methods are well-suited for understanding the complexities of such mismatch factors of graduate's employability issues.Explanatory Research: Given the evolving nature of the study this research follows an explanatory approach to study and gain insights into entrepreneurial leadership within this context.

Data Collection
Sampling: Stratified sampling was used to select a cluster group of participants with varying experiences, representing different geographical areas and sectors.Data Sources: In addition to surveys, documents such as business reports, publications, and news articles were analysed to complement the interview data and provide context.

Data Analysis
The collected data was analysed through statistical analysis.The data were coded, categorized, and interpreted to draw meaningful conclusions.

Ethical Considerations
Informed Consent: Participants were provided with clear information about the study's purpose, procedures, and potential risks.Informed consent was obtained before data collection.
Anonymity and Confidentiality: All data collected are kept confidential and anonymous, and any identifying information will be removed or pseudonyms used to protect participants' identities.Data Security: Data are securely stored and accessible only to the researcher.The above table 2 shows the total male sample respondents were 273 and the total female sample respondents were 112.The sample size comprised of both male and female in public and private sector of Oman and the following table shows the sample distribution of the same.The above table 3 shows the sample respondents from public sector ( 183) and the private sector ( 202) and the total number of respondents is 385.The number of male respondents and female respondents of public sector are 130, 53 respectively.The number of male respondents and female respondents of private sector are 143, 59 respectively.Hence, the total male sample respondents were 273 and the total female sample respondents were 112.
To evaluate the normality graphically, researcher use the Histogram, Q-Q Plots and boxplots of the variables.The data is usually distributed as the data points are similar to the diagonal line.If the data points stray from the line in an apparent non-linear way the data is not usually distributed.As can be seen from the below Histogram, Q-Q Plots and boxplots of the variables that the data is not normally distributed.A Q Q plot compares two different distributions.If the two sets of data came from the same distribution, the points will fall on a 45-degree reference line.To use this type of graph for the assumption of normality, compare your data to data from a distribution with known normality.

Technical skills (TS)
Factor analysis is a statistical method used to identify and interpret underlying latent factors that contribute to the observed correlations or patterns in a set of variables.It is commonly employed in various fields, including psychology, sociology, marketing, and finance, to understand the structure of relationships among variables.Hair et al. ( 2019) defines factor analysis as "an interdependent technique whose purpose is to define the underlying structure among the variables in the analysis".Factor analysis can be used for data reduction or data summarization.KMO and Bartlett's Test of Sphericity was conducted as an additional measure to confirm the statistical significance of the correlation among the variables.

KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy: This measure varies between 0 and 1, and high values generally indicate that factor analysis may be useful with the data.If the value is less than 0.5, the results of the factor analysis probably won't be very useful.Here in the table 4 KMO measure of sampling adequacy is 0.890 which is more than 0.5.So, the amount of data is sufficient to measure the job mismatch and adequate for the factor analysis..000 Bartlett's Test of Sphericity: This is used to test the null hypothesis that the variables are uncorrelated, or the correlation matrix is an identity matrix.If the variables are uncorrelated then the appropriateness of factor analysis must be questioned.Values less than 0.05 of the significance level indicate that the variables reject the null hypothesis and factor analysis may be useful with the data.Here approximate chi-square statistic is16672.414and 0.000 significant level which is less than 0.05.So, we can say that the variables reject the null hypothesis.They are correlated and factor analysis will be useful.This study asked some questions from the respondents about their demographic information so as to set the context for addressing the research questions.In the following subsection, the summaries of demographic variables of respondents are presented.These summaries include gender, age, CGPA, family income, discipline.This information was gathered from the first section (Demographics) of the survey questionnaire.Although answering all questions/statements of the survey questionnaire was completely voluntary, the majority of respondents answered the whole questionnaire.Missing responses were limited to the question regarding gender.The correlation coefficient is a statistical measure that quantifies the strength and direction of the linear relationship between two variables.It provides a numerical value that indicates how closely related or associated the variables are.The most commonly used correlation coefficient is Pearson's correlation coefficient (often denoted by "r"), but other types include Spearman's rank correlation coefficient and Kendall's tau.
A correlation coefficient would be significant if the p-value is more than the correlated significance level.When negative coefficients are obtained, this indicates that both variables analyzed are having a negative relationship.This means that when a variable increase, the other variable decreases.In contrast, if two variables are having positive relationship whereby when the former variable increases, the latter also increases,  The Pearson Correlation Coefficient for most of the variables is between± 0.01 to ± 0.7 this illustrates that all of the independent variable has relationship with the dependent variable.All the independent variables which are TS impact (.317), SS (.419), SMS (.414), and JSS (.417) has moderate but definite relationship with the dependent variable of JM.

Regression Analysis
Regression analysis is a kind of analysis method used to determine the relation between the dependent variable and one or more independent variable.Regression analysis is a statistical method used to examine the relationship between one dependent variable and one or more independent variables.The goal of regression analysis is to model and understand the nature of this relationship and make predictions based on the observed data.The most common type of regression analysis is linear regression, but there are other variations, including multiple regression, polynomial regression, logistic regression, and more.Two types of regression analysis can be performed, that is, univariate and multivariate.A multiple regression is run by using the Statistical Package for the Social Sciences (SPSS).For running the regression job mismatch is considered as dependent variables and technical skills, soft skills, social mobility skills, job search strategies are considered as independent variables.is a statistical measure that represents the proportion of the variance for a dependent variable that's explained by an independent variable or variables in a regression model.When R 2 is larger than the correlations between the dependent and independent variables are high.Here the adjusted R square is 19.4%, that means technical skills, soft skills, social mobility skills, job search strategies can explain 19.4% of the total variance of job mismatch with the standard error of 47.2%.

Analysis of Variance (ANOVA)
Analysis of variance (abbreviated as ANOVA) is an extremely useful technique concerning researches in the fields of economics, biology, education, psychology, sociology, business/industry and in researches of several other disciplines.This technique is used when multiple sample cases are involved.As stated earlier, the significance of the difference between the means of two samples can be judged through either z-test or the t-test, but the difficulty arises when they happen to examine the significance of the difference amongst more than two sample means at the same time.The ANOVA technique enables us to perform this simultaneous test and as such is considered to be an important tool of analysis in the hands of a researcher.Using this technique, one can draw inferences about whether the samples have been drawn from populations having the same mean.The ANOVA technique is important in the context of all those situations where they want to compare more than two populations such as in comparing the yield of crop from several varieties of seeds, the gasoline mileage of four automobiles, the smoking habits of five groups of university students and so on.In such circumstances one generally does not want to consider all possible combinations of two populations at a time for that would require a great number of tests before they would be able to arrive at a decision.This would also consume lot of time and money, and even then, certain relationships may be left unidentified (particularly the interaction effects).Therefore, one quite often utilizes the ANOVA technique and through it investigates the differences among the means of all the populations simultaneously.Predictors: (Constant), JSS, TS, SMS, SS Since the P-value is smaller compared to the alpha level (0.05), then we can conclude that the group of independent variables reliably predict the DV (Job mismatch) and the model is significant.
this will be indicated by a negative Pearson correlation coefficient.The rules of thumb regarding the range of coefficient and the strength of association proposed by Hair et al., in 2012 is shown in Table below.

Table 2
Sample size of the respondents of diversified job mismatch

Table 3
Sample size of the respondents of diversified job mismatch

Table 5
CorrelationAll of the independent variables' correlations with dependent variable of the study are discussed below.Pearson correlation is used for determining the correlation between dependent and independent variables of this study.

Table 8
Rules of Thumb about Pearson Correlation CoefficientCorrelation is significant at the 0.01 level (2-tailed).