Abstract: Emotional intelligence plays a vital role in organizational performance. Literature suggests that emotional intelligence can be a tool for controlling job stress and enhance job satisfaction, which leads to reduction in attrition. The study is an earnest attempt to unfold the results in the best possible way of a meta analysis to ascertain if there indeed exists an empirical evidence to support the relationship between emotional intelligence and different variables viz., demographic profile, job stress, job satisfaction and turnover intention. The results obtained from a meta analysis of scientific articles related to emotional intelligence, demographic characteristics (age, education, income and gender), job stress, job satisfaction and turnover intention variables are highlighted through the study. Eighty five studies were reviewed for a possible analysis with 41 studies meeting the criteria for inclusion. The findings of the present study reveal that there is a relationship between emotional intelligence and the aforesaid variables. Emotional intelligence and demographic variables (age, gender, education and income) have a significant positive relationship. Job stress was found to have a negative relationship with emotional intelligence. Job satisfaction is positively related to emotional intelligence, whereas turnover intention found no relationship (random model) with emotional intelligence. The study concludes that there is a moderately strong relationship between emotional intelligence and demographic characteristics (age, gender, education and income) and job stress, job satisfaction. Therefore, in Indian workplace, EI awareness will be an effective measure to control job stress and turnover intention. Theoretical implication and future study on it are discussed during the course of the study.
INTRODUCTION
Today in this competitive world, the economy, technology and cultures are rapidly changing. The 21st century is a time of globalization, information revolution and speed (Cascio, 2001). Everybody is struggling for survival in this changing world. The only factor that appears to be constant in today’s organizations is change (Mossholder et al., 2000). Organizations are making changes to cope with the environmental change, market strategies and technologies (Langley, 2000). Indeed, the organization’s ability to deal with change provides a competitive advantage (Skinner et al., 2002). Employees are the functional part of the organization and make an effort towards their own survival and for that of the organization as well. The progress and achievement of organizations is undoubtedly dependent on human force (Monfared et al., 2010). Employees of the organization are adjusting to the change and ability. Every organization will expect from their employees to deal with economic changes through constant up gradation of skills. This changing environment becomes a challenge for human resource managers and their roles also change according to time (Shukla, 2009). To sustain in the changing era, employees need an excellent Intelligence Quotient (IQ). However, according to some scientist, IQ by itself is not a good predictor of job performance (Singh, 2006). Best IQ accounts for job performance is about 25% of the variance (Hunter and Hunter, 1984). Some of the studies pointed out that job performance vary and that 10% may be a more realistic estimate (Sternberg, 1996). Some studies have suggested that emotional intelligence has different, even opposite, features from intellectual intelligence (Halicinarli and Bender, 2006; Stein and Book, 2003). In today’s rapidly evolving world, a person’s EI or "Emotional Quotient" (EQ) is the most important predictor of success (Goleman, 1998). This term got popularized when Goleman (1995) claimed that people who have high competencies of emotional intelligence skills are more likely to have happier and successful lives.
Although, the importance of emotion’s research in organizations has been ignored, research into the impact of emotions on organizational behavior is increasing (Ashkanasy et al., 2000). Over the recent years, the use of emotional intelligence increased with respect to organizational behavior (Mayer et al., 2000). Emotional intelligence significantly contributed to understand the different relationship in the organizational settings (Mayer et al., 2000; Jordan and Troth, 2002). Several studies and articles have contributed to the literature in relation to stress and depression in the past 15 years (Kessler, 1997; Mazure, 1998; Monroe and Hadjiyannakis, 2002; Paykel, 2003; Tennant, 2002). A severe level of stress at home or at work was associated with an increased risk of suicide (Feskanich et al., 2002). It was found that coworker support, work-life balance and role expectation conflicts are the new determinants responsible for job stress in India (Shukla and Srivastava, 2016a).
Emotional intelligence is one of the important abilities (Colman, 2009), other than Intelligent Quotient (IQ), which can control the job stress variable, job satisfaction variable and turnover intention. According to Richards and Pryce (2006), EI is linked to reduce stress, improve performance and reduce turnover. It is found that an employee who is emotionally intelligent would be more optimistic, happy and have the competency to change, adapt and manage the stressful situations of the organization and strong emotions without falling apart a bit by actively coping with stress (Carmeli, 2003). Higher EI showed better health (Schutte et al., 2007).
The motivation of this study manifested itself in the problem faced by the organizations today in India with respect to job satisfaction, job stress and turnover intention. As far as job stress is concerned in India, Mike (2012) showed that due to demanding schedules and high level of stress, nearly 78% of corporate employees in India sleep less than 6 h a day, leading to severe sleep disorders. The survey pointed out that 21% of the people in the sample suffered from depression. Increase in job stress will affect job satisfaction. According to Mike (2012), India is ranked as the 3rd most job-dissatisfied country in the world.
Given the ongoing problem, it was found from the literature that the EI competencies are very effective to prevent stress among employees (Salovey et al., 2002; Ciarrochi et al., 2002). Ciarrochi et al. (2002) discovered that emotional intelligence could effectively regulate the relationship between stress and psychological health. In other words, people with high emotional intelligence tend to keep thinking positively when experiencing a positive mood (consistent with the maintenance of a self-emotion) and tend to return to normal when experiencing a negative mood (consistent with emotional restoration). In other words, positive mood guided by emotional intelligence prevents the occurrence of stress and melancholy. The current study provides an analysis of the claimed role of emotional intelligence in the workplace. Following a brief overview of the importance of EI, consideration is given to an emerging literature that promotes the assessment, training and the individual’s utilization of emotional intelligence in the Indian workplace. To review the relationship between emotional intelligence, job stress, job satisfaction and turnover intention; the incorporation of a meta analysis might provide a more robust method. Meta analysis suggests the empirical work done in the respective domain.
Meta analysis has been performed in the area of EI and leadership (Mills, 2009; Harms and Crede, 2010), EI and health (Schutte et al., 2007), EI and job performance (O’Boyle et al., 2011). However, a meta analysis has not yet been performed in the area of EI and demographic profile, job stress, job satisfaction and turnover intention. This procedure addresses the questions of sufficiency and stability in a specific area. Firstly it indicates whether a certain phenomenon is already established or needs additional studies and secondly it indicates whether new studies would change the existing findings. This would give researchers the notion that more investigation is required in order to test the relationship between EI and various respective variables (demographic, job stress, job satisfaction and turnover intention). One valuable way to put together disperse results from different studies is using meta-analysis. A rigorous quantitative approach which refers to the statistical integration of the results of independent studies, leading to conclusions that are more precise and more reliable than can be derived in any one primary study or in a narrative review (Johnson et al., 1995; Rosenthal and DiMatteo, 2001), meta analysis thus gives a more rounded view of the researched field. Using meta analysis statistical methodology with a comprehensive review of the literature using electronic methods not available to earlier researchers and an extensive search for "Grey literature" and unpublished reports, this study reports the finding of an exhaustive systematic review/meta analysis of the available research examining the relationship between emotional intelligence, demographic profile, job stress, job satisfaction and turnover intention.
MATERIALS AND METHODS
A review of the documentary corpus made it possible to select, describe and analyze research studies by the use of meta analysis with respect to emotional intelligence, demographic characteristics (age, education, gender and income), job stress, job satisfaction and turnover intention. To this end, an exploratory search was conducted using Scholar Google (http://scholar.google.com), simple Google search and EbescoHost database, wherein the search criterion is on the basis of variables in the titles of research papers published. By using meta analysis on individual studies, an attempt has been made to analyze the findings of work done in the respective areas.
Meta analytic procedure: Correlation meta analysis was performed on different individual studies with reference to different variables. The data are analyzed using comprehensive meta analysis software 2.0. This meta analysis is based on Hedges and Olkin (1985) and Hedges and Vevea (1998). Present study used correlation coefficient (r) and sample size (n) as an input measure for calculating effect size. Briefly, the procedure entails of converting study outcomes to standard normal metrics (Zs associated with one-tailed probabilities for significance levels and Fisher’s r-to-Z transformation for effect sizes), combining them to produce weighted means and examining them in diffuse and focused comparisons. There are two statistical models for undertaking statistical meta analysis: Fixed model and random model. A fixed effect meta analysis assumes that individual study is trying to estimate the same true effect size. The differences are due to larger sample size in the different studies given more weight. Random effects meta analysis assumes that each study has a different true effect that will be estimated for each study. Differences are expected and have been incorporated into the study giving more weight to smaller studies than in fixed effect meta analysis. This study showed graphically fixed and random model for correlation meta analysis along with the relative weights of fixed model and random model of individual studies. Random model effect has been applied for results due to different sample size.
Inclusion criteria: A rule has been created about which study to include in the analysis. Firstly, the study should be empirical and quantitative. No prerequisite has been made on nationality, date of publication, sample size and test scales. Secondly, the study should be on emotional intelligence in relation to demographic profile, job stress, job satisfaction and turnover intention. Present study incorporates past studies done extensively with Pearson correlation coefficient and sample size. Through these measures, effect size has been calculated. For assessing relationship of emotional intelligence on demographic profile, the factors included were age, income, gender and education. The unpublished studies were also taken into account since works done on the variables of published studies were not found to be adequate.
Emotional intelligence: Emotional intelligence is a term popularized in past 10 years (Davies et al., 1998). Emotional Intelligence (EI) is defined as "The ability to perceive and express emotion, assimilate emotion in thought, understand and reason with emotion and regulate emotion in self and others" (Mayer and Salovey, 1997). Goleman (1995) popularized the emotional intelligence term after publication of the book emotional intelligence: "Why it can matter more than IQ". Emotional intelligence is one of the personality characteristics (Mayer et al., 2000).
Research development in emotions originated when first known study published and states that emotional expression is essential for survival and adaptation (Darwin, 1872). Thorndike (1920) defined emotional intelligence as a type of social intelligence that was related to managing and understanding others. In Wechsler (1943) described the impact of non-cognitive factors on intelligent behavior. Building on emotional strength is important for human being (Maslow, 1950). Emotional intelligence reflects not a single trait or ability but a composite of distinct emotional abilities, i.e., perceiving, understanding and regulating emotions (Mayer and Salovey, 1997). Emotional intelligence originated from the theory of multiple intelligence. The theory has proposed two types of intelligence, i.e., interpersonal intelligence and intrapersonal intelligence (Gardner, 1983). The term emotional intelligence got introduced in the doctoral dissertation entitled "A study of emotion: Developing emotional intelligence (Payne, 1985). Emotional intelligence as a concept is gaining a great deal of attention because the emotions of employees are recognized as an integral part of workplace (Bay and McKeage, 2006).
Emotional intelligence with demographic profile: There are studies conducted in the past which have firmly established a significant relationship between emotional intelligence and demographic profile.
Data analysis revealed that there were no significant differences in the overall level of emotional intelligence of respondents based on gender and age. Khalili (2011) conducted a study involving 112 employees of small and medium enterprises (SME) in the private sector in Malaysia for assessment of gender differences in emotional intelligence. Significant differences were not found in overall emotional intelligence in gender. Katyal and Awasthi (2005) in their study involved 150 students of class 10th from different government schools in Chandigarh for assessment of gender differences in emotional intelligence. Girls were found to have higher emotional intelligence as compared to boys. Harrod and Scheer (2005) in their study explored adolescent emotional intelligence relative to demographic characteristics (age, sex and household income, parent’s level of education and location of residence) on a sample of 200 high school students of Midwestern states, USA. The significant relationship was not found among emotional intelligence and age or location of residence. Females were found to have higher emotional intelligence than males. Interestingly recent study has found out a positive relation between emotional intelligence and mother’s education and emotional intelligence and household income. Ahmad et al. (2009) investigated emotional intelligence among 80 males (n = 80) and 80 females (n = 80) from North West Frontier Province (NWFP) of Pakistan and concluded that males had a higher emotional intelligence as compared to females. Nandwana and Joshi (2010) in their study assessed emotional intelligence and the impact of gender on emotional intelligence of 60 tribal adolescents in Udaipur. They concluded that social isolation, lower socio-economic status, family type and educational backwardness might be some of the factors accounting for lower emotional intelligence of tribal adolescents. However, gender differences were not reported with respect to emotional intelligence. Min (2010) conducted a study in Taipei city to explore the relationships of demographic variables (e.g., gender, age and work variables) on a sample of 380 tour guides. Findings showed that females had a higher emotional intelligence as compared to males. Significant correlation was not found between age and emotional intelligence. The findings also revealed a positive association between emotional intelligence and work experience. Waddar and Aminabhavi (2010) investigated whether postgraduate (PG) students staying at home and hostel differ significantly from each other in some of the important personality variables such as self-efficacy and emotional intelligence. The study was conducted on a sample of 200 PG students from different Departments of Karnataka University. The results revealed that PG students staying at home had significantly higher self-efficacy and emotional intelligence as compared to students staying in hostels. The findings also revealed that demographic variables such as age, gender, order of birth and caste significantly contributed to the self-efficacy and emotional intelligence of PG students.
Hopkins and Bilimoria (2008) in their study found that there were no significant differences between male and female leaders with reference to emotional and social intelligence competencies. Cavallo and Brienza (2001) found that most studies on emotional intelligence did not find differences in terms of gender. Celik and Deniz (2008) found that Turkish scouts have emotional intelligence higher than other contemporary scouts. Gender has no significant effect on emotional intelligence and age has no significant effect on emotional intelligence. Bar-On (1997) favored this result by reporting that men and women hold similar scores (Singh, 2001; Titrek et al., 2007).
Emotional intelligence with job stress: Stress is a common problem in all industries worldwide (Taylor et al., 1997). There are several studies which have investigated the impact of Emotional Intelligence on stress.
Vembar (2001) concluded that emotional intelligence has a moderating effect on hardiness and physical health. Findings also reveal that emotional intelligence accounted for 24.3% of the variance in physical health. Emotional intelligence is a significant moderator of the relationship between occupational stress and well-being (Ciarrochi et al., 2001; Mikolajczak and Luminet, 2008; Shukla and Srivastava, 2016b). Salami (2010) found in his study that people with high levels of emotional intelligence might experience less stress. Spector and Goh (2001) found the positive relationship between emotional intelligence competencies and stress. Darolia and Darolia (2005) studied the role of emotional intelligence is coping with stress and emotional control behavior. The study clearly stated that the persons who are emotionally intelligent are able to understand and recognize their emotions and manage themselves appropriately. They can control impulsiveness and aggression in a stress situation. Gohm et al. (2005) led an investigation among 158 freshmen to find an association between emotional intelligence and stress and considered personality as a moderating variable. The results suggested that emotional intelligence is potentially helpful in reducing stress for some individuals but irrelevant for others. Oginska-Bulik (2005) investigated the relationship between emotional intelligence and perceived stress in the workplace and studied health related consequences in human service workers. The results confirmed that employees having higher emotional intelligence perceived a lower organizational stress and suffered less from negative health consequences. The study also revealed that emotional intelligence plays a moderating role in preventing executives/employees from negative health outcomes especially from depression symptoms. Singh and Singh (2008) investigated the impact of emotional intelligence on to the perception of role stress of medical professionals. The study was conducted on a sample size of 312 medical professionals consisting of 174 male and 138 female doctors working in a privately managed professional hospital. The findings of the study indicated no significant difference in the level of emotional intelligence and perceived role stress between gender and having significant negative relationships of emotional intelligence with organizational role stress for both the genders and medical professionals.
Emotional intelligence with job satisfaction: Goleman (1998) investigated that individuals having a high level of emotional intelligence tend to experience more positive moods and emotions in contrast to those with a lower overall emotional intelligence. Santhapparaj and Alam (2005) and Ngah et al. (2009) studied the relationship between emotional intelligence and work attitude of university staff in Malaysia. The results indicated that emotional intelligence is positively related to work attitude and appraisal. Expressions of emotions (dimension of emotional intelligence) is moderately correlated with job performance and job satisfaction. Ssesanga and Garrett (2005) studied the relationship between emotional intelligence and job satisfaction among university professionals in Uganda and found evidence of job satisfaction among university employees and antecedent variables of emotional intelligence. The results suggested that academics with high emotional intelligence would perceive high satisfaction and tend to feel more emotionally attached to their organizations. Chiva and Alegre (2008) found that emotional intelligence is one of the most important factors that theoretically related to organizational performance and individual variables such as job satisfaction. Sy et al. (2006) found a positive correlation between emotional intelligence and job satisfaction among food service employees. The study concluded that employees with high emotional intelligence have higher job satisfaction, which was supported by the finding of Wong and Law (2002). Bar-On (2004) conducted a study to examine the relationship between emotional quotient competencies and job satisfaction from a heterogeneous group of professionals. The results concluded that there was a positive relationship between EQ scores and job performance satisfaction. Carmeli (2003), Kafetsios and Loumakou (2007), Vakola et al. (2004) studies have observed weak to modest relationships between trait emotional intelligence and job satisfaction. Psilopanagioti et al. (2012) found emotional intelligence (use of emotion dimension) was significantly and positively correlated with job satisfaction (r = 0.42, p<0.001) and it was found negatively correlated between surface acting and job satisfaction (r = -0.39, p<0.001). Ealias and George (2012) revealed that there is a very high positive relationship between emotional intelligence and job satisfaction. The study also shows that the designation of the employee does not have relationship with job satisfaction and emotional intelligence. However, it found that experience and marital status have a significant relationship with emotional intelligence and job satisfaction.
Emotional intelligence with turnover intention: Studies found that higher emotional intelligence is negatively correlated to turnover intentions (Wong and Law, 2002; Goleman, 1998; Kooker et al., 2007; Carmeli, 2003; Lee and Liu, 2007; Falkenburg and Schyns, 2007; Firth et al., 2004). Bhatnagar (2013) result shows there is no linear relationship between emotional intelligence and turnover intention. The scale tends to experience turnover intentions in a high magnitude. The finding resembles the findings of Action Society Trust (1996), which reported that no significant correlations were found between withdrawal intentions from the organization and emotional intelligence. Jeswani and Dave (2012) found after the empirical investigation that emotional intelligence has a significant impact on turnover intention of faculty members. The result shows that general mood has an inverse significant relationship with turnover intention.
RESULTS
Table 1-4 represents the correlation coefficient of different studies with varying sample sizes, which have been included for meta analysis. Table 5 shows the meta analysis of the relationship between EI with demographic profile, job stress, job satisfaction and turnover intention. A correlation meta analysis was performed to analyze the individual study with reference to modeled variable. Table 1 shows the meta analysis of relationship between EI and demographic profile. It was analyzed 9 studies (k = 9) included age, gender, income and education with a total sample size of 2775. Correlation meta analysis performed with fixed model and random model. Table 5 shows the result of emotional intelligence with demographic variable has a significant positive relationship (for random model Fisher’s Z = 0. 112, p<0.001, for fixed model Fisher’s Z = 0. 110, p<0.001). The results of the different studies (with Fishers Z and 95% CI) are shown in a forest plot (Fig. 1).
Emotional intelligence with job stress: Table 6 shows the correlation coefficient matrix of the relationship between EI and job stress. There are 15 studies (k = 15) on which meta analysis has been conducted. Figure 2 shows the result of meta analysis, including a forest plot of fisher’s Z transformation and 95% confidence interval. Results show that EI with Job stress having a significant negative relationship (for random model Fisher’s Z = -0.315, p<0.001, for Fixed model Fisher’s Z = -0.344, p<0.001).
| Table 1: | Correlation coefficient matrix of the relationship between EI and demographic profile |
n: Sample size, r: Correlation coefficient, A: Sample age, I: Sample income, E: Sample education, G: Gender (Male and female), 1: Included in the study 0: Not included in the study and k (studies): 9 | |
| Table 2: | Correlation coefficient matrix of the relationship between EI and job stress |
| n: Sample size, r: Correlation coefficient and k: (studies): 15 | |
| Fig. 1: | Forest plot included individual studies with respect to age, gender, income and education |
| Fig. 2: | Forest plot of the relationship between EI and job stress |
| Table 3: | Correlation coefficient matrix of the relationship between EI and Job satisfaction |
| n: Sample size, r: Correlation coefficient and k (Studies): 14 | |
| Table 4: | Correlation coefficient matrix of the relationship between EI and turnover intention |
| n: Sample size, r: Correlation coefficient and k (Studies): 3 | |
Emotional intelligence with job satisfaction: Table 7 shows the correlation coefficient matrix of the relationship between EI and job satisfaction. For k = 14, including unpublished studies, are used for meta analysis. Figure 3 shows the result of meta analysis conducted for the relationship between EI and job satisfaction. Result is displayed with forest plot and relative weights used for meta analysis for the fixed and random model. Meta analysis was conducted and found that EI has a significant positive relationship (for random model Fisher’s Z = 0. 564, p<0.001, for fixed model Fisher’s Z = 0. 468, p<0.001).
Emotional intelligence with turnover intention: Table 8 shows correlation statistics for EI and turnover intention. There are very few studies done with our inclusion criterion. For k = 3, Table 8 indicates that there are different results for fixed model and random model due to fewer studies found and unpublished studies included which increases the probability of publication bias. By using fixed and random model effect result shows significant negative relationship of EI with turnover intention with CI = -0.343 to 0.041 (Fisher’s Z = -0.151, p = 0. 124). Forest plot (Fig. 4) showed that there is negative relationship found between emotional intelligence and turnover intention.
Publication bias: Our focus of the study is to provide accurate results from the meta analysis. It is important to note that our findings are only as good as the studies used to derive these meta- analytic estimates. Therefore, it is important to ensure that the study must be a fair representation of the population and not bias by any systematic factor. One of such bias is publication bias.
Publication bias is the term used whenever the research that appears in the published literature is systematically unrepresentative of the population of completed studies. Publication bias occurs when findings of individual studies are not statistically significant or the finding is different from the hypothesis of the study.
| Fig. 3: | Forest plot of the relationship between EI and job satisfaction |
| Table 5: | Studies included in the meta analysis of the relationship between EI and demographic profile |
| Table 6: | Studies included in the meta analysis of the relationship between EI and job stress |
Generally, published studies are more significant as compared to unpublished studies but due to less work done with reference to these variables according to our inclusion criterion; unpublished studies have also been taken into account. Therefore, it is important to find the publication bias in our meta analysis.
Funnel plots by plotting effect size on x-axis and standard error on y-axis examine the publication bias and examine the distribution of the studies on the plot. Funnel plot of the studies is interpreted as: If publication bias did exist, it would be to the lower left of the mean. The studies which are negative in funnel plot are conducted on less sample size.
| Fig. 4: | Forest plot of the relationship between EI and Turnover Intention |
| Fig. 5(a-d): | Publication bias results: (a) EI with demographic profile (no bias), (b) EI with job stress (no bias indicated), (c) EI with job satisfaction (some studies found biased) and (d) EI with turnover intention (no bias indicated) |
| Table 7: | Studies included in the meta analysis of the relationship between EI and job satisfaction |
All the studies have included according to the inclusion criterion of the meta analysis.
The results of the funnel plot for the publication bias are shown in Fig. 5a-d. Comprehensive meta analysis 2.0 (Hopewell et al., 2005) was effected to conduct the publication bias test.
| Table 8: | Studies included in the meta analysis the relationship between EI and turnover intention |
The result of the publication bias indicates no or minimal bias for the EI relationship with different variables. As the result shown in Fig. 5a, b and d indicates no evidence of bias exists to the left of the mean. For EI with job satisfaction was found to have minimal bias as it is not symmetric and showing certain studie s in the bottom of the funnel plot as shown in Fig. 5c. As study included unpublished data also, it may include publication bias in meta analysis. Nevertheless it is expected that emotional intelligence research enriched with literature, accurate and precise findings will result in enhanced research content in future.
DISCUSSION
By identifying these results of a meta analysis on emotional intelligence and different variables, this result makes an important contribution to the literature methodologically and theoretically. The results have important implications for how emotional intelligence is applied in an organization. Methodologically, this study examines how emotional intelligence is related to different variables (demographic profile, job stress, job satisfaction and turnover intention) by using meta analysis. In terms of theoretical contribution, the results of this study confirmed that emotional intelligence has significant relationship with respect to different variables used in the study. It indicates that the ability of employees to properly manage their emotions and other employee emotions can increase their capabilities to cope with psychological stress in the job. As a result, it may lead to higher job satisfaction in the organizations. This result is consistent with the studies of Guleryuz et al. (2008), Kafetsios and Zampetakis (2008) and Quoidbach and Hansenne (2009).
Emotional intelligence and demographic variable (Age, gender and education and income) has a significant positive relationship (Fariselli et al., 2006) (for random model Fisher’s Z = 0. 112, p<0.001, for fixed model Fisher’s Z = 0. 110, p<0.001).
Results showed that EI with Job stress is having a significant inverse relationship (for Random model Fisher’s Z = -0.315, p<0.001, for Fixed model Fisher’s Z = -0.344, p<0.001). The studies conducted by Oginska-Bulik (2005), Matthews et al. (2002), Montes-Berges and Augusto (2007), Naidoo and Pau (2008), Slaski and Cartwright (2002) also reveals similar results.
The result from meta analysis showed that EI is having a significant positive relationship with job satisfaction (for random model Fisher’s Z = 0. 564, p<0.001, for fixed model Fisher’s Z = 0. 468, p<0.001). This study resulting from different studies of various countries showed that EI competencies always increase in job satisfaction. This result is also consistent with Caruso and Salovey (2004), Sy et al. (2006) who found that employee’s emotional intelligence was positively associated with job satisfaction and performance. In keeping with recent studies (Lopes et al., 2006; Sy et al., 2006), the results demonstrated convincingly that EI is an important personality-level predictor of work affectivity and job satisfaction.
The result of meta analysis favored the past studies, turnover intention has negative relationship with EI (Wong and Law, 2002; Goleman, 1998; Kooker et al., 2007; Carmeli, 2003; Lee and Liu, 2007; Falkenburg and Schyns, 2007; Firth et al., 2004). Particularly Wong and Law (2002) have supported this argument and through their study, they have highlighted the fact that the higher the emotional labor in a particular job, the stronger EI is negatively related to turnover intention.
In terms of practical contributions, the findings of this study can be used as a guideline by the management to overcome job stress problems in organizations. In other words, EI competency is a better tool to prevent job stress. Therefore, EI should be used in recruitment, selection, training programs, appraisals, promotions and employee development programs. Employees with higher levels of emotional intelligence are associated with organizational performance. Considering the findings of this meta analysis study from a practical perspective, the identification of emotional intelligence as a moderator in the job stress process might have a significant potential as a stress management technique. Today, every organization has been putting all efforts to be in competition. This has effectively meant that the organization is compromising heavily on three important variables i.e., job stress, job satisfaction and turnover intention. Overall, it now depends on individual personality’s composite emotional abilities (Mayer and Salovey, 1997) for reducing job stress, increase job satisfaction and suppressing the feeling of not quitting the organization. Our meta analysis results indicated that emotional intelligence plays an important role in relation to almost all the variables considered in the study. Indian organizations are highest in attrition rate due to low job satisfaction and high job stress (ASSOCHAM., 2011). This study revealed that how emotional intelligence is related to different variables through different studies, which are from different countries including India. Indian selection system of employees currently emphasizes cognitive ability and specific subject knowledge. Emotional abilities are not formally included in the selection system of Indian organization. In the light of current approach being too narrow, our results reveal that how emotional intelligence can significantly contribute to handle job stress among the employees, which increases the job satisfaction (Hollingworth et al., 1988; Abdel-Halim, 1982; Keller, 1975; Leigh et al., 1988) and decreases the turnover intention. Furthermore based on the meta analysis, EI will be an important variable in real business environment, where good employee’s emotional quotient will help employees to handle job stress and at the same time, it can suppress the feeling of not to quit the organization. Thereby organizations can reduce the attrition rate, which gives an economic advantage.
Finally, this study has significant implications for finding the correlation relationship of emotional intelligence with respective variables (demographic profile, job stress, job satisfaction and turnover intention). Loss of employees or employee turnover due to major factors discussed such as job stress can cause psychological and physiological distress, which in turn would reduce productivity, service quality and increase recruitment cost (Powell and York, 1992; Achoui and Mansour, 2007). Emotional intelligence as a concept has to be recognized as an integral part of workplace (Bay and McKeage, 2006).
CONCLUSION AND FUTURE RECOMMENDATION
Our meta analysis suggests some important conclusion about the emotional intelligence and some propositions for future study. The aim of the meta analysis study was to investigate the relationship between emotional intelligence and demographic profile, job satisfaction, job stress and turnover intention. Results found that emotional intelligence is playing a vital role to influence and control the different variables. Meta analysis shows that emotional intelligence has a significant relationship with demographic profile, job stress and job satisfaction. Results also found negative results for emotional intelligence and turnover intention. Using random model effect with Z-value -1.539, standard error 0.099, it was found inversely related and by using fixed model effect with Z-value -2.785, standard error 0.023 it was found negatively significant. Some studies showed mixed results. The study found that women’s emotional intelligence level is higher than men’s EI. Some studies found no significant relation between gender and EI. Age found a significant positive relationship with emotional intelligence. Majorly job stress found a negative relationship with emotional intelligence. Job satisfaction was found positively related to emotional intelligence, whereas turnover intention found no relationship (random model) with emotional intelligence. The study suggests moderately strong relationship between emotional intelligence and demographic profile, job stress and job satisfaction. The study will contribute in the theory to understand the relationship between emotional intelligence, job stress, job satisfaction and turnover intention. The current study contributes to the organizations in terms of the job stress coping and decrease the attrition in the organizations, which is associated with cost and increases the job satisfaction to make employees loyal. Although, many studies have suggested the same finding, however, the same are mixed which cannot be generalized. This study attempted to combine all the findings of the different studies and found conclusive results, which can be treated as generalized results. This study suggests the theoretical implication for future research, which needs a quantitative study conducted in order to demonstrate the utility of the variables. In terms of practical implication, this pioneering study suggests that EI has a strong relationship with demographic variable, job stress, job satisfaction and turnover intention. In workplace, EI awareness will be an effective measure to control job stress and turnover intention. Secondly, EI training will be effective in organizations to control job stress, which will decrease the turnover intention and increase the job satisfaction. The EI will be an important tool to overcome the stress and can be treated as a stress coping strategy. The available empirical related to these variables are less and the same can be one of the limitations of this study. Finally, future study is required to determine what types of training are most efficient for improving emotional competency and dealing with emotional labor that affects well-being and job-stress.