Emotional intelligence (EI) is highlighted by the literature as an important attribute that enables an individual to cope with changes and pressures in the work environment and subsequently yields consistent performance. However, some scholars debate the role of demographic diversities and their impact on levels of EI amongst individuals.
This study examined the influence of demographic variables on EI levels amongst early career academics (ECAs).
The study interrogates demographic variables and EI, two issues important in the 21st-century workforce setting. The relationship between the two may be of value to the debate surrounding the success of early career professionals in the higher education sector. The success of ECAs should be of importance to institutions of higher learning.
A quantitative approach was followed in conducting the study. Data were collected from a sample of 220 ECAs in a selected university in South Africa. A self-administered questionnaire was sent to the participants using SurveyMonkey online data collection tool. EI was measured using the Schutte Emotional Intelligence Scale.
Significant EI level differences were observed based on the participants’ ethnic background. However, no significant differences in EI levels could be found based on the respondents’ gender, age and work experience.
The findings may be relevant to career management and human resources forecasting.
The study adds to the literature on EI and career success of early career professionals.
Emotional intelligence (EI) is increasingly gaining empirical attention as a predictor of individual productivity and performance (Bande, Fernández-Ferrín, Varela, & Jaramillo,
Every profession has its challenges that may cause psychological stress and upset the professionals’ emotional balance (Oatley & Johnson-Laird,
The per-annum enrolment in institutions of higher learning has been on the rise for the past two decades (Coates et al.,
However, the individual’s level of EI may be influenced by several factors. According to Pooja and Kumar (
The demographic make-up of the workforce may be the basis for differences in terms of perceptions, values and attitudes amongst employees (Pooja & Kumar,
The article provides a literature review on EI, demographical variables and the relationship between the two. This is followed by an overview of the research design utilised to carry out the study. Findings of the study are also presented as well as recommendations for ECAs, management of institutions of higher learning and proposals for future research.
Kumar and Muniandy (
This study utilises the trait model of EI which according to Petrides, Pita and Kokkinaki (
Bar-On (
Studies exist that examined whether levels of EI vary across different demographic variables of individuals (e.g. Jorfi et al.,
According to Jorfi et al. (
In a study on retail employees by Shukla and Srivastava (
Age is believed to be associated with the level of social adaptability and awareness (Frank et al.,
The time that an individual spends in a certain field of profession is important for the individual to become exposed, acquainted and versed in the dynamics of the profession (Shukla & Srivastava,
Ethnicity background and/or nationality has been found in social studies to corroborate differences in beliefs, values and disturbance handling processes (Maduramente,
However, Hossein (
The study followed the quantitative nature in which data were collected from numerous respondents by means of a self-administered questionnaire and statistical tests were carried out to meet the main objective of the study, which was to examine the influence of demographical variables on the level of EI amongst ECAs.
The population of interest in this study was the ECAs at a rural South African campus in the Eastern Cape Province. The ECAs being referred to in this study were defined according to the following criteria:
All doctoral candidates helping with research supervision and facilitation of classes.
All postdoctoral fellows.
Research assistants, time-on-task lecturers.
Lecturers or researchers still within 8 years of their first academic appointment or research practice.
Using the criteria determined above, the population amounted to 401 participants. In collecting data, the researchers send the research instrument to those that were readily available and willing to take part in the study and a total of 220 responses were qualified for data analysis. This was satisfactory for the study because the number surpassed the predetermined Raosoft sample size of 158 at 5% margin of error and 50% expected response rate.
The study employed a self-administered questionnaire that had two sections. The first section had questions on the demographic aspects of respondents that included gender, age, faculty, position held, work experience and ethnical background. The second section consisted of the SEIS (Schutte et al.,
In this study, the Cronbach’s alpha for the 33 items on the SEIS is 0.797 (see
Cronbach’s reliability test.
Cronbach’s alpha | Number of items | Example item |
---|---|---|
0.797 | 33 | I present myself in a way that makes good impression on others |
In collecting the data, the researchers physically distributed the questionnaires and also utilised the online SurveyMonkey, whereby targeted respondents followed a link that was sent through to their personal emails. Follow-ups were made both in person and through the personal email. Respondents’ identity was kept confidential and so were the responses that were given which were treated with care to ensure anonymity and to prevent any damage to the person or the respondent. The researchers also ensured that the participants signed the consent form as evidence of their agreement to participate in the study.
The data collected were entered into the Statistical Package for Social Sciences version 22 software for analysis. Frequency distribution tables were utilised to summarise the demographic features of the data from the sample and measures. Analysis of variance (ANOVA), chi-square test and ordinal (proportional odds) regression analysis was conducted to test the hypotheses to the study.
The proposal and questionnaire of the study were reviewed by a research ethics committee and an ethical clearance certificate (REC-270710-028-RA level 1) was granted. Ethical clearance reference number: CHI191SMAR01.
The findings indicated that there were 95 (43.2%) men and 125 (56.8%) women. In terms of the participants’ age, 30.9% (
Based on
Descriptive statistics on the Schutte Emotional Intelligence Scale.
Emotional Intelligence | Mean | Median | Mode | Std. deviation | ||
---|---|---|---|---|---|---|
Valid | Missing | |||||
EI1 | 216 | 4 | 4.37 | 4.00 | 4 | 0.529 |
EI2 | 216 | 4 | 4.26 | 4.00 | 4 | 0.666 |
EI3 | 216 | 4 | 4.33 | 4.00 | 5 | 0.715 |
EI4 | 216 | 4 | 4.08 | 4.00 | 4 | 0.755 |
EI5 | 216 | 4 | 2.60 | 2.00 | 2 | 1.177 |
EI6 | 217 | 3 | 4.29 | 4.00 | 4 | 0.704 |
EI7 | 217 | 3 | 3.82 | 4.00 | 4 | 0.882 |
EI8 | 211 | 9 | 3.75 | 4.00 | 4 | 0.999 |
EI9 | 217 | 3 | 4.03 | 4.00 | 4 | 0.775 |
EI10 | 215 | 5 | 4.21 | 4.00 | 4 | 0.830 |
EI11 | 217 | 3 | 3.61 | 4.00 | 4 | 1.079 |
EI12 | 217 | 3 | 3.78 | 4.00 | 4 | 0.880 |
EI13 | 215 | 5 | 3.90 | 4.00 | 4 | 0.867 |
EI14 | 206 | 14 | 4.36 | 4.00 | 4 | 0.622 |
EI15 | 215 | 5 | 3.93 | 4.00 | 4 | 0.805 |
EI16 | 215 | 5 | 4.05 | 4.00 | 4 | 0.725 |
EI17 | 215 | 5 | 4.13 | 4.00 | 4 | 0.762 |
EI18 | 215 | 5 | 3.74 | 4.00 | 4 | 0.851 |
EI19 | 214 | 6 | 4.05 | 4.00 | 4 | 0.714 |
EI20 | 211 | 9 | 4.10 | 4.00 | 4 | 0.798 |
EI21 | 211 | 9 | 4.00 | 4.00 | 4 | 0.822 |
EI22 | 209 | 11 | 4.09 | 4.00 | 4 | 0.691 |
EI23 | 208 | 12 | 4.25 | 4.00 | 4 | 0.635 |
EI24 | 211 | 9 | 4.37 | 4.00 | 5 | 0.688 |
EI25 | 213 | 7 | 3.92 | 4.00 | 4 | 0.672 |
EI26 | 211 | 9 | 3.91 | 4.00 | 4 | 0.805 |
EI27 | 211 | 9 | 3.78 | 4.00 | 4 | 0.756 |
EI28 | 213 | 7 | 2.16 | 2.00 | 1 | 1.388 |
EI29 | 212 | 8 | 3.67 | 4.00 | 4 | 0.861 |
EI30 | 211 | 9 | 4.10 | 4.00 | 4 | 0.709 |
EI31 | 212 | 8 | 4.03 | 4.00 | 4 | 0.630 |
EI32 | 212 | 8 | 4.03 | 4.00 | 4 | 0.630 |
EI33 | 212 | 8 | 3.04 | 3.00 | 2 | 1.174 |
The proportional odds ordinal regression analysis was conducted on the data to test the hypothesis that the demographical variables (gender, age, working experience and nationality and ethnicity) significantly influence levels of EI amongst ECAs. Ordinal regression works well under the assumptions that there is non-multicollinearity amongst the independent variables and that each independent variable has an identical effect at each cumulative split of the ordinal-dependent variable. The multicollinearity diagnosis showed all the variance inflator factor values to be less than the threshold of three showing that there were no significant issues of multicollinearity amongst the independent variables. This meant that ordinal regression was applicable to the data.
In conducting the ordinal regression analysis, it was important to test whether the study model is better than the null model, which is without factors or covariates. A
Goodness of fit test.
Model | -2 Log likelihood | Chi-square | Sig. | |
---|---|---|---|---|
Intercept only | 100.483 | - | - | - |
Final | 72.378 | 28.105 | 6 | 0.031 |
Note: Link function, Logit.
Following the goodness of fit test is important. The assumed null hypothesis here is that the study model is adequately relative to a perfect model. In this regard, a good result is to fail to reject the null hypothesis. The study calculated the Pearson and deviance
Proportional odds chi-square test.
Variable | Chi-square | Sig. | |
---|---|---|---|
Pearson | 24.032 | 48 | 0.999 |
Deviance | 27.057 | 48 | 0.994 |
Note: Link function, Logit.
The test of parallel lines is also known as the test for proportional odds assumption. The null hypothesis under the assumption is that the slope coefficients in the model are the same across response categories (and lines of the same slope are parallel). The goal here was to fail to reject the null hypothesis because this would prove the study model to be good.
The
Test for parallel lines.
Model | -2 Log likelihood | Chi-square | Sig. | |
---|---|---|---|---|
Null hypothesis | 72.378 | - | - | - |
General | 70.610 | 1.768 | 6 | 0.940 |
Note: The null hypothesis states that the location parameters (slope coefficients) are the same across response categories. Link function, Logit.
Parameter estimates.
Variable | Estimate | Std. error | Wald | Sig. | 95% Confidence interval |
||
---|---|---|---|---|---|---|---|
Lower bound | Upper bound | ||||||
[Emot_Intel = 3] | −3.096 | 3.311 | 0.874 | 1 | 0.350 | −9.586 | 3.394 |
[Emot_Intel = 4] | 2.566 | 3.306 | 0.602 | 1 | 0.438 | −3.914 | 9.045 |
AGE | −0.241 | 0.300 | 0.644 | 1 | 0.422 | −0.829 | 0.347 |
The column ‘estimate’ gives information on the log odds of the independent variables. One unit increase in age (from a younger age group to the next older group) multiplies the odds of scoring high in EI by log (-0.241), which is 0.786 given that other variables are held constant. However, the
The working experience of respondents has an estimated beta of 0.153, which means that a unit increase in the number of years of experience multiplies the odds of scoring high levels of EI by 16.5% given that the other independent variables are held constant. This means that EI levels were rising by the length of work experience; however, the change is not significant as shown by the
The estimate for gender = 1 (male participants) is 0.241, which is above zero and this shows that keeping other independent variables constant, the male participants are 27.2% more likely to score high level of EI than their female counterparts. This is because the odds ratio is greater than 0. Despite the difference in the scoring of EI level for male and female participants as exhibited by the odds ratio, the
In terms of ethnicity of the participants, Africans had an estimated ratio of 0.292, which is greater than zero and this shows that the African participants had a cumulative ratio of 34% chance of scoring higher scores of EI than were the participants belonging to the ‘other’ race which was used as the reference group. The white participants had an odds ratio of 1.552 and when exponentiated meant that the magnitude of them scoring high on EI than the ‘other’ race was 4.723 times. The mixed race group had a beta or odds ratio of -1.816 and this is less than zero. This means that the mixed race group scored low on EI than the reference ‘other’ ethnicity group. In essence, the mixed race scored lower level of EI by a cumulative odds ratio of 0.163 times that of the ‘other’ race.
An exploratory factor analysis was conducted on the SEIS data and four factors had Eigen values greater than 1. These factors were interpreted as an expression of emotions, use of emotions, and a perception of emotion and regulation of emotion. Chi-square and ANOVA tests were performed in terms of gender and the other three factors, respectively. These tests were carried out in order to substantiate the findings from the proportional odds test.
Variable | ||||
---|---|---|---|---|
Gender (chi-square) | Age (one-way ANOVA) | Working experience (one-way ANOVA) | Ethnicity (one-way ANOVA) | |
Expression of emotions | 0.182 | 0.459 | 0.331 | 0.727 |
Use of emotions | 0.062 | 0.540 | 0.364 | 0.199 |
Perception of emotions | 0.906 | 0.383 | 0.428 | 0.018 |
Regulation of emotions | 0.528 | 0.656 | 0.521 | 0.191 |
ANOVA, analysis of variance.
The main objective of the study was to investigate the influence of demographic variables on the level of EI amongst ECAs at a selected institution. In this regard, there were some differences observed for the EI responses based on gender. Even though the differences were found to be insignificant, male participants were reported to be more likely to score low on EI than the female participants. The insignificant differences may be explained by the changing of gender roles and the exposition of similar work and family challenges for both the male and female participants. Even though the study observed some differences in the level of EI scores based on participants’ work experience, the differences were not significant. This may be explained by the fact that the participants were all ECAs and do face similar work and career challenges, and therefore, their EI levels may not significantly differ. The study observed an unexpected result as far as participants’ age was concerned. The older participants showed more probability to score low on EI than the younger participants. However, the difference observed was statistically deemed insignificant. This finding is opposed by Chen et al. (
In terms of the participants’ ethnicity, differences amongst groups were observed. The white participants scored higher on EI than all other groups. The African participants scored higher than the mixed race and the ‘other’ whilst the mixed race participants scored the least EI scores. It is possible that the mixed race and ‘other’ respondents scored the least as a result of the fact that they were significantly less represented than the black and white respondents. However, the differences were deemed insignificant as a result of the lack of statistical evidence. The responses on the perception of emotion factor were found to significantly differ with participants’ ethnic background. The difference may be explained in line with the effect of globalisation in which the workforce in an organisation is becoming significantly mixed as labour mobility across continents and nation increases (Hossein,
Importantly, in line with the main hypothesis of the study, the demographic variables studied did not collectively significantly influence the level of EI amongst ECAs even though differences were observed.
The respondents to the study indicated to belong to different groups or categories of varying demographic variables. This observation proves that the academic workforce demographics are increasingly becoming diversified and therefore inquiries into demographic dynamics are important (Ang et al.,
Because some differences between male and female levels of EI were observed, the human resource manager may need to continue to make efforts to reduce this difference as far as is possible to avoid sexism in making inferences concerning perspectives (Frank et al.,
The study also reported some differences in the level of EI based on the years of experience. Though the differences were proven insignificant, EI scores rose with the years of experience. This may imply that ECAs may need to endure their circumstances hoping that with more experience they become an effective manager of their own productivity and development. However, in order to gain experience, security of jobs is important. ECAs are mostly in non-permanent position (Matthews, Lodge, & Bosanquet,
In terms of the age of respondents, the study reported that the younger respondents scored higher EI scores than their older counterparts. This is contrary to the expectation that as people grow older, they become more experienced and mature to handle some circumstances that the younger generation struggle with (Chen et al.,
The presence of many factors affecting the personality, decisions and behaviours of individuals implies that change is imminent and therefore interval analysis of gaps and differences may be necessary.
This study was conducted under some limitations. External validity was compromised because the sample surveyed was selected through non-probability sampling procedure and also the data were collected from only one selected university. In this light, caution needs to be exercised in generalising findings to all the ECAs in the country or other institutions. Secondly, this study is part of a bigger project in which respondents had to answer questions pertaining to more than one variable on a self-administered instrument. This made the study risk to spurious variance as a result of the measurement instrument and not the constructs.
Despite the fact that the sample size used was sufficient for the purposes of this study, it must be noted that the sample did not sufficiently represent the characteristics of the population of interest. Lastly, EI is exhibited in theory as a personality trait or ability which is influenced by various factors. This study only included four demographic variables, which do not exhaustively represent all the factors that influence EI. Caution should also be taken in generalising the findings of this study. Regardless of the mentioned limitations to this study, the obtained findings may still be relevant to practice for ECAs, career counsellors and institutions of higher learning.
This study contributes to the literature of EI and ECAs. The findings of the study have implications on ECAs as they seek to personally grow and develop in their career, institutions of higher learning and their human resources functions and career counsellors. Differences in the levels of EI amongst ECAs were observed based on the various demographic variables. Even though the majority of these differences were statistically insignificant, it can be stated that the demographic variables may have a real impact on EI. The study suggests that further research needs be conducted in which comparisons can be made between early career professionals and those already established.
The researchers are indebted to the Govan Mbeki Research and Development Centre at the University of Fort Hare for the financial support and workshops which also became a point of contact with respondents.
The authors declare that there were no personal circumstances, relationships and financial gain that influenced them in data collection, analysis, interpretation and reporting.
M.M. was the principal researcher whilst W.T.C. was the supervisor (promoter) of the research. The researchers also declare that the views expressed in this study are their own and not the official position of any institution.