The career choice is one of the most important and sensitive matter in the life of the individual, because this choice will result in building the entire professional future of the individual. The influence of career choice has a lasting impact on an individual. It serves to be a predictor and determinant of their prospective level of income, nature of work and consequently leaves a mark on the personality, behaviour and outlook of an individual. Any wrong decisions regarding career can change the fate of an individual. An apt career decision and individual action in this regard is manifested on a larger scale in the economic prosperity of a nation. Individuals who are misfits in their workplace tend to be less productive and efficient and therefore are unable to achieve their goals. The concept has been explained by Onyejiakuas [1] cited in Jones and Larke [2], who defines occupation as a means of living, which has the power to change personalities, determine social status, predict expected earnings, determine social groups etc. Thus its importance cannot be undermined. Given its complexity, it is then a point to ponder upon as to how career decisions are made. The factors affecting the career choice are grouped under four heads for the purpose of this study. The past studies focused on few determinant factors affecting career choice. Therefore, the grouping is done considering the research gaps identified on review of the related literature. The variables are grouped into demographic, environmental, opportunity and personality factors. The study investigates how these factors are related to and what impact it has on the career path choice of students in higher education institutions. 

Significance of the Study

The influence of career path choice has a significant and lasting impact on an individual. Wrong choice of career path can change the fate of an individual and can have adverse impact on his/her life. In every country, young people face challenges in deciding their career path and starting their professional lives, regularly while business environment keeps changing [3]. In Oman, few studies were made in order to explain how job seekers plan their career path. The Oman National Centre for Statistics and Information (NCSI) 2017 announced that, one in five Omani job seekers admitted that the government or civil service industry is the most attractive for the local talent. The NCSI, also indicated that as of December 2017, there were 238688 Omanis employed in the private sector, compared to 200174 Omanis working in the public sector for the same period. This shows that 54% of the Omani citizens’ work in the private sector and 46% in the public sector. It is very important to understand and realize the potential factors that can shape the career path decision of undergraduates in the Sultanate of Oman. This will provide useful insights to the Oman government to control the rate of unemployment. It will help the government to keep up to date of current career needs, requirements and demand of the job-seekers. Moreover, the study will help university students to be aware and get ready to make informed decisions regarding their career path choice. In the light of these facts the study is highly relevant and significant.

Objectives of the Study

• To investigate the influence of demographic variables on students’ career choice

• To identify the influence of environment factors on students’ career choice 

• To determine the influence of opportunity factors on students’ career choice

• To investigate the influence of personality factors on students’ career choice

To analyze which among these factors have significant impact on the students’ career choice.

Literature Review

Agarwala [4] explored the influence of a range of factors on the career choice of management students in India. The importance of different individuals in the family and at work in making career choices among these students was explored. The results show that "Skills, competencies and abilities" was the most important factor and "father" was the most significant individual influencing the career choice of Indian management students. The predominant cultural value was collectivism, although the students demonstrated individualist tendencies in some contexts. A protean orientation guided the career orientation of these students. Asma and Abeeda [5] investigated the influence of parental education, profession and income on the career decisions of 432 students from two public sector universities in Lahore city. The results show the parents influence as most significant, followed by influence from peers, gender, print media, financial reasons, interest and others. According to Bandura et al. [6], an individual’s environment, talents, skills and academic achievement exert an influence on career choice. Research shows homes, schools and the social setup influence an individual’s career choice. According to Brenda et al. [7], choosing a senior high school career or tracks to pursue is one of the most challenging decision any junior high school student may undertake. The objectives were to investigate junior high school student's career preferences for senior high school studies, as well as the determinants that may influence their career selection. Only the peer component was shown to be statistically insignificant. Among the career selection determinants, the variable interest was found to have the strongest influence on students' course preferences. Diverse career selection factors have statistically significant effects on students' senior high school career choices. A study conducted in Florida reports 99% females opted for cosmetology fields and 100% males chose to be plumbers [8]. Research reports that females traditionally avoid male-dominated fields. However, recent studies show that women are adopting professions which are conventionally male-oriented. Brock and Cammish [9] interviewed school children from six countries, viz. India Bangladesh, Jamaica, Cameroon, Sierra Vanuatu and Leone, asked them to share their opinion on gender factor which acts as a barrier for women education. Access to school was reported as a common factor for females. Literature reports that parents’ educational level is the most important factor in students’ career decision [10,11]. The results uphold that parents are a child’s first teacher and thus they have the role of a guide, advisor and counsellor in their lives. Nyarko-Sampson [12] explained that parents exert emotional pressure on their wards regarding the choice of careers. They make independent consultations regarding the career they think is most suitable for their children. The child’s preferences are never a matter of concern for them. Schools role is to provide accurate guidance and also encourage students to continue with education and not drop out a study by Mickelson and Velasco [13] shows that mothers have a stronger influence on their children as compared to their fathers. Decisions which involve the choice of elective subjects, courses of specializations and subsequent careers are equally stressful and trying for girls and boys completing schooling and proceeding to college [14]. Ghuangpeng Siriwan [15] investigated factors that drive the career decision-making of Thai and Australian tourism and hospitality students. It also sought to understand the way these factors impacted on Thai and Australians’ career decision-making and how their cultural interpretations influenced their decision-making. Several factors of particular importance were gender, the feedback students received during work-placement, family obligations and career opportunities in the industry that appeared to be interrelated and could have a positive or negative impact on students’ decision to seek a career in the industry. Jeofrey [16] investigated factors that influence the choice of career pathways among high school students in Midlands Province of Zimbabwe to establishing a career guidance model that would assist career guidance teachers in high schools in their endeavours to help students make career choice from a well-informed perspective. Family members, career guidance in schools, the geographical location of schools, peers through peer advice and encouragement had an influence on students’ choice of careers. The influence of gender was lowly rated. The study recommended the training of parents, peers and teachers to enhance students’ choice of careers. It was also recommended that only trained career guidance teachers be allowed to teach career guidance. Omar et al. [17] aimed to study the factors that influence students’ career choices. Among the variables included are personality, parents or guardians, peer groups, career guidance counsellors, environment, opportunity and economic considerations. Only five variables significantly influence students: personality, parents or guardians, peer groups, career guidance counsellors and environment while economic consideration factors were not significant. Peer groups showed a negative relationship with students’ career choices.

Research Gaps

There are many studies on factors influencing the career choice of students conducted in various countries. But those studies focused on any of the few determinant factors affecting career choice. Moreover, research studies in Oman is limited. Thus this study addresses these issues by covering all the relevant factors affecting career choice of students, viz. demographic factors, environment factors, opportunity factors and personality factors.

The study is analytical in nature. A cross- sectional research design is used. The data is collected from a sample of 248 students [18] from a population of 692 Advanced Diploma and Bachelor students registered in the University during the academic year 2021-22. Stratified random sampling method was used and the sample was drawn proportionately from the strata consisting of three departments viz; Business 75, Information Technology 48 and Engineering 125 respectively. The data collection method is primary wherein a structured questionnaire is distributed to sample selected for the study. The 27-item questionnaire consists of four subscales namely demographic factors, environmental factors, opportunity factors and personality factors and it is scored on a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly Agree).The Cronbach’s Alpha test is used to measure the internal consistency of items in the subscales. The Cronbach’s Alpha of 0.88 is obtained which proves that the instrument used is internally consistent and reliable. The response rate obtained for primary data collection is 64%, consisting of responses from 158 advanced diploma and bachelor students. Secondary data was obtained from the findings stated in books, published documents and literature related to the research. The period of the study is from September 2021 to December 2021. Descriptive statistics are used to describe the characteristics of the sample such as the variables’ mean, standard deviation and frequency. Correlation and regression statistical methods are used to analyse the collected data. SPSS version 21 is used to extract the relevant statistical tools.

The correlation analysis helped to determine the relationship between the demographic factors (independent variable) and the dependent variable (career choice). The Pearson’s correlation coefficient is used to show the direction, strength and significance of the relationship. The p-value was based on a 95% confidence interval, meaning that if the p-value is lower than 0.05 (p<0.05), it is regarded as statistically significant, vice versa [19]. 

Demographic Factors and Career Choice

Hypothesis Testing

• H0: Career choice is not influenced by demographic variables

• H1: Career choice tends to be influenced by demographic variables

Based on the results in Table 1 above, there is a weak positive relationship between each of the demographic factors viz; family income, parents education background and CGPA with the dependent variable, career choice. The r-values are 0.120, 0.067 and 0.180 for family income, parents’ education background and the CGPA of the students. There is significant relation between career choice and CGPA as the p value (0.012) is less than 0.05.

Regression analysis was performed to determine whether the independent variables (demographic factors like family income, parents’ education background and CGPA) predict the dependent variable (career choice). In addition, multiple linear regression analysis was used to determine which amongst the three demographic factors contribute most to the variation of the dependent variable (career choice).

Table 2 shows that the correlation of demographic factors (independent variables) on career choice is 0.183. The model summary illustrates the (R square) value, which helps in explaining variance in the dependent variable (career choice). The R square value (0.034) represents the coefficient of determination. This means that the demographic variables (family income, parents’ education background and CGPA) predict the dependent variable (career choice) by 3.4% only thus, leaving out 96.6% unexplained. This means that there are other extra independent variables which are not considered in the study that is significant in explaining variation in career choice of students. 

The ANOVA was performed to test the statistical significance of the regression model on whether it is a good descriptor for the relationship between the predictor variables (demographic variables) and the dependent variable (career choice) (Table 3). There is no significant effect of demographic factors (independent variables) such as family income, parents’ education background and CGPA on the students’ career choice (F = 1.788; p = 0.152.

Table 1: Correlations

Table 2: Model Summary

a. Predictors: (Constant), CGPA, Parents education background, Family income, b. Dependent Variable: Career Choice

Table 3: ANOVA

a. Dependent Variable: Career choice, b. Predictors: (Constant), CGPA, Parents education background, Family income

The p value is greater than alpha (0.05). This means there is no statistical significance between the demographic factors and career choice. Therefore, the null hypothesis (H0) is accepted. 

The coefficients Table 4 helped the researcher to compare which of the three demographic variables contribute the most to the variation of career choice. Therefore, to make the comparison, the Beta standardized coefficients were used. The results indicate that none of the demographic factors contribute to the variation in career choice decisions. (Family income – β = 0.045, p = 0.649, Parents education background – β = -0.017, p = 0.855 and CGPA β = 0.164, p = 0.083) are insignificant predictors of career choice. This shows that the three demographic variables, having weak positive correlation to dependent variable (career choice), have insignificant impact on career choice. H0 is accepted and H1 is rejected proving that there is no significant influence between demographic factors and career choice.

Environment Factors and Career Choice

Hypothesis Testing

• H0: Career choice is not influenced by environment factors

• H2: Career choice tends to be influenced by environment factors

Table 5 shows that there is a positive relationship between each of the environmental factors viz; colleges in locality, support from parents, success of family business, advice of teachers, counselling in the University, alumni and work environment with the dependent variable, career choice. The r-values are 0.149, 0.190, 0.078, 0.166, 0.152, 0.196 and 0.250 respectively. It can be seen that there is a weak uphill (positive) linear relationship between these variables and the career choice of the students. Except success of family business all the other environmental factors are significantly correlated with the career choice.

Table 6 shows that the correlation of environmental factors (independent variables) on career choice is 0.284. The R square value is 0.081. This means that the environmental variables (colleges in locality, support from parents, success of family business advice of teachers, counselling in the University, alumni and work environment) predict the dependent variable (career choice) by 8.1% thus, leaving out 91.9% unexplained which means that there are other extra independent variables that is significant in explaining variation in career choice of students.

The ANOVA reveals that there is no significant effect of environmental factors (independent variables) such as colleges in locality, support from parents, success of family business, advice of teachers, counselling in the university, alumni and work environment on the students’ career choice (F = 1.881; p = 0.076. The p value is greater than Alpha (0.05). This means there is no statistical significance between the demographic factors and career choice. Therefore, the null hypothesis (H0) is accepted proving that there is no significant relationship between environmental factors and career choice.

The coefficients Table 8 helps to compare which of the seven environmental factors studied contribute the most to the variation of career choice. The results indicate that none of the demographic factors contribute to the variation in career choice decisions. (Colleges in locality – β = 0.034, p = 0.725, Support from parents – β = 0.078, p = 0.462, Success of family business β = -0.156, p = 0.154, Advice of teachers – β = 0.055,p = 0.642, Counselling in the university β = 0.028, p= 0.781, Alumni – β = 0.031, p = 0.796, Work environment β = 0.214, p = 0. .068) are insignificant predictors of career choice. This shows that the seven environmental variables studied, having weak positive correlation to dependent variable (career choice), have insignificant impact on career choice. H0 is accepted and H1 is rejected proving that Career choice is not influenced by environment factors.

Opportunity Factors and Career Choice

Hypothesis Testing

• H0: Career choice is not influenced by opportunity factors

• H3: Career choice tends to be influenced by opportunity factors

Table 4: Coefficients

a. Dependent Variable: Career Choice

Table 5: Correlations

Table 6: Model Summary

a. Predictors: (Constant), Work environment, Colleges in locality, Counselling in the University, Success of family business, Support from parents, Advice of teachers, Alumni, b. Dependent Variable: Career choice

Table 7: ANOVA

a. Dependent Variable: Career choice, b. Predictors: (Constant), Work environment, Colleges in locality, Counselling in the university, Success of family business, Support from parents, Advice of teachers, Alumni

Table 8: Coefficients

a. Dependent Variable: Career Choice

Based on the results in Table 9 above, there is a positive relationship between each of the opportunity factors viz; University mentoring opportunities, High paid jobs, Part time jobs, On the Job Training (OJT), Labour market structure and demand with the dependent variable, career choice. The r-values for University mentoring opportunities, High paid jobs, Part time jobs, On the Job Training (OJT), labour market structure and demand are 0.157, 0.215, 0.085, 0.152 and 0.143 respectively. It can be seen that there is a weak uphill (positive) linear relationship between these variables and the career choice of the students. Except part time jobs, all the opportunity variables are significantly correlated with career choice.

Table 10 shows that the correlation of opportunity factors (independent variables) on career choice is 0.281. The R square value is 0.079. This means that the opportunity variables (University mentoring opportunities, High paid jobs, Part time jobs, On the Job Training (OJT), Labour market structure and demand) predict the dependent variable (career choice) by 7.9% thus, leaving out 92.1% unexplained showing that there are other extraneous variables which are not considered in the study that is significant in explaining variation in career choice of students.

The ANOVA shows that the model is a good descriptor of the relationship between independent variables (opportunity factors) and the dependent variable (career choice). The F-ratio in the ANOVA tests whether the overall regression model is a good fit for the data. The table shows that the independent variables statistically significantly predict the dependent variable, F (5, 152) = 2.604, p = 0.027). 

Table 9: Correlations

Table 10: Model Summary

a. Predictors: (Constant), Labour market structure and demand, University mentoring opportunities, OJT, High paid jobs, Part time jobs, b. Dependent Variable: Career choice

The p value is less than alpha (0.05). i.e., the regression model is a good fit of the data. The ANOVA Table 11, proves that the overall correlation 0.281 is significant. Hence the model is significant.

The coefficients Table 12 helped to compare which of the five opportunity variables contribute the most to the variation of career choice. The results indicate that two of the opportunity factors viz; Opportunity of high paid jobs and part time jobs contribute to the variation in career choice decisions. (High paid jobs – β = 0.320, p = 0.016, Part time jobs- β = -0.296, p = 0.041. The rest three factors viz; (University mentoring opportunities – β = 0.111, p = 0.211, OJT- β = 0.065, p = 0.564, labour market structure and demand β = 0.053, p = 0.671) are insignificant predictors of career choice. This means that the explanatory variables like University mentoring opportunities, OJT and labour market structure and demand are no more useful in the model, when the other two variables are already in the model. In other words, with the high paid jobs and part time jobs in the model the other three opportunity variables no more add a substantial contribution to explaining career choice of students. This shows that two of the opportunity variables, have significant impact on dependent variable, career choice. Opportunities for high paid jobs and part time jobs has significant impact on the career choice decisions of the students. Hence, H1 is accepted proving that the opportunity factors like knowledge of high paid jobs and opportunities for part time jobs have significant impact on the career choice decisions of students. Therefore, the regression equation is developed as follows:

Y = a + bX1 + cX2 + dX3 + ϵ

The model equation based on the analysis is given below:

Y = 4.060 + 0.210(X1) + -0.203 (X2) 

Where:

X1: Represents high paid jobs 

X2: Part time jobs)

Personality Factors and Career Choice

Hypothesis Testing

• H0: Career choice is not influenced by personality factors

• H4: Career choice tends to be influenced by personality factors

Table 13 shows that there is a positive relationship between each of the personality factors viz; Match personality, Personal interest, Emotions and Social skills with the dependent variable, career choice. The r-values for these independent variables are 0.110, 0.206, 0.055 and 0.233 respectively. It can be seen that there is a weak uphill (positive) linear relationship between these variables and the career choice of the students. Personal interest and social skills are significantly correlated with career choice as the p values are less than 0.05.

Table 14 shows that the correlation of personality factors (independent variables) on career choice is 0.290. The model summary that the R square value is 0.084. In other words, personality factors (Match personality, Personal interest, Emotions and Social skills) explain about 8.4% of variability of career choice decision of students leaving out 91.6% unexplained which means that there are other extra independent variables that is significant in explaining variation in career choice of students.

The ANOVA results show that the model is a good descriptor of the relationship between independent variables (personality factors) and the dependent variable (career choice) (F = 3.520; p = 0.009). The p value is less than alpha (0.05). i.e., the regression model is a good fit of the data). The ANOVA table, proves that the overall correlation 0.281 is significant. Hence the model is significant.

The coefficients Table 16 shows that only one personality variable viz; social skills contribute to the variation in career choice decisions. (Social skills – β = 0.229; p = 0.024). The rest three factors viz; (Match personality- β = -0.018 p = 0.866, Personal interest β = 0.212 p = 0.062, Emotions- β = -0.199 p = 0.073) are insignificant predictors of career choice. This means that the explanatory variables like match personality, personal interest and emotions are no more useful in the model, when social skills variable is already in the model. In other words, with social skills variable in the model, the other three personality variables no more add a substantial contribution to explaining career choice of students. This shows that social skills variable has a significant impact on dependent variable, career choice. Hence H1 is accepted proving that social skills have significant impact on the career choice decisions of the students. 

Table 11: ANOVA

a. Dependent Variable: Career choice, b. Predictors: (Constant), Labour market structure and demand, University mentoring opportunities, OJT, High paid jobs, Part time jobs

Table 12: Coefficients

a. Dependent Variable: Career Choice

Table 13: Correlations

Table 14: Model Summary

a. Predictors: (Constant), Social skills, Match personality, Emotions, Personal interest, b. Dependent Variable: Career choice

Table 15: ANOVA

a. Dependent Variable: Career choice, b. Predictors: (Constant), Social skills, Match personality, Emotions, Personal interest

Table 16: Coefficients

a. Dependent Variable: Career Choice

The model equation based on the analysis is given below:

Y = 4.012+ 0.151(X1), (where X1 represents Social skills)

Hence, it is concluded that the career choice of students is affected by opportunities of high paid jobs, part time jobs and social skills. Any change in these variables will directly affect the career choice of students.

Lastly, based on the results and discussion, it is proved that among the opportunity factors studied, knowledge of high paid jobs and opportunities for part time jobs are the most contributing variables towards the variation of career choice decisions. The results match with Asma and Abeeda [5] study which investigated the influence of parental education, profession and income on the career decisions of 432 students from two public sector universities in Lahore city wherein the results reveal that along with few other factors analyzed, financial reasons had significant influence on the career choice decisions of students.

The study concludes that among the personality factors, the social skills possessed by students have significant influence on their career path choice. This agrees with Agarwala [4], which concluded that "Skills, competencies and abilities" were the most important factor influencing the career choice of Indian management students.

Findings of the Study

There is a weak positive relationship between demographic factors like family income, parent’s education background and the student CGPA on the career choice and it has insignificant impact on career choice of students.

There is a weak positive relationship between environmental factors like access to colleges in the locality, support from parents and friends, success of family business, advice of teachers/advisors, assistance of counselling department in the university, alumni and the work environment on the career choice but, it has insignificant impact on the student’s career choice.

There is a weak positive relationship between the opportunity factors like the mentoring opportunities in the University, knowledge of high paid jobs and opportunities for part time jobs, the university on the job training and the structure and demand of the labour market and the career choice. Among the five opportunity variables studied, the knowledge of high paid jobs and opportunities for part time jobs have significant impact on career choice of the students.

There is a weak positive relationship between personality factors like matching the student personality with personalities of people in the same career, personal interest, emotions and the social skills and the career choice. Among the four personality variables studied only the social skills of the students have significant impact on career choice of the students.

The significance value of high paid jobs, part time jobs and social skills of the students are 0.016, 0.041 and 0.024 respectively. This means that there is significant impact of these independent variables on the students’ career choice decisions. Thus it is statistically proved that among all independent variables, knowledge about high paid jobs, opportunities for part time jobs (opportunity factors) and the social skills (personality factor) of the students have significant impact on students’ career choice decisions.

Based on the result of analysis, it is evident that except the opportunity factors like knowledge about high paying jobs and opportunities for part time employment and secondly the personality factor like social skills, the other variables are having insignificant impact on the students’ career choice. Hence there is still more that needs to be done by the institution in terms of assisting the students in career guidance. The correlation results showed that the independent variables analyzed have weak correlation with the career choice. The students are not career focused when they lack the knowledge about the new and emerging careers and the factors around that could influence their career choice decisions. Proper career guidance can help to lead the students to the right career path choice. Lastly, based on the regression results, the study concludes that among the variables studied, knowledge of high payed jobs, opportunities for part time jobs and the social skills possessed by the students are the most contributing variables towards the variation of career choice decisions. 

Recommendations

Career choice is one of the most crucial factor that has effect on the life of the students. The findings reveal that the support from the counselling department has no significant impact on the students’ career choice decisions. Lack of knowledge regarding the scope of the new and emerging careers and the existing common preferences that students generally make actually pose a challenge in making good career choice decisions. The study reveals that the role of the student counsellors are minimal when it comes to making informed career choices. The University Counselling Department may focus on assisting the students with professional counselling services so that the student is encouraged to have a careful analysis so as to evaluate if their choice is the right one. 

The University On the Job Training (OJT) department in association with the counselling department could work on matching the student training requirements and provide suitable training to the students so as to improve their employability skills which can help them to make a right career path choice after graduation.

The study reveals that there is lack of mentoring opportunities that could provide guidance, advice and continuing support that will help the students in their learning and development process. This can be taken care of by the specialization committee that can ideally work towards educating the students with respect to the career opportunities and growth related to each specialization. Establishing an active career guidance cell in the university that can provide relevant academic and career information to enable students to make informed decisions along the way, can also improve the career focus of the students. 

Personality development programs and public speaking training can be arranged for the students. Proper training and workshop sessions to this effect can help the students to identify and nurture their social skills which can have a positive impact on students’ career choice decisions. 

Recommendations for Future Research

The study also suggests that further studies should be conducted on other independent variables that were not put into consideration in this study that is significant in explaining the variation in career choice of students. Since the study was done in a selected higher education institution, future studies in larger samples covering more universities in the Sultanate can be carried out. Furthermore, since the study only focused on the quantitative measure, future works are encouraged in several areas in both quantitative and qualitative measure.

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