research paper on emotional intelligence and job performance

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A Meta-Analysis of the Relationships Between Emotional Intelligence and Employee Outcomes

Çaǧlar doǧru.

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Edited by: Osman Titrek, Sakarya University, Turkey

Reviewed by: Ajay K. Jain, Management Development Institute, India; Catherine S. Daus, Southern Illinois University Edwardsville, United States

*Correspondence: Çaǧlar Doǧru [email protected]

This article was submitted to Organizational Psychology, a section of the journal Frontiers in Psychology

Received 2020 Sep 28; Accepted 2022 Feb 28; Collection date 2022.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Emotional intelligence is an emerging field since the 1990s due to its important outcomes for employees. This study is a psychometric meta-analysis examining the links between emotional intelligence and organizational commitment, organizational citizenship behavior, job satisfaction, job performance, and job stress of employees. In this meta-analysis, carefully selected studies on emotional intelligence since the origin of the concept in 1990 were included along with studies examining its outcomes. For this analysis, three streams of emotional intelligence, consistent with previous meta-analyses, were considered: ability, self-report, and mixed emotional intelligence. This meta-analysis is an attempt to add to the literature by analyzing the relationships between emotional intelligence and selected employee outcomes over a period of time beginning in 1990. The three streams of emotional intelligence were separately analyzed to examine their relationship with employee outcomes. These outcomes were included in the study based on select research studies. Our study results showed that emotional intelligence and its three streams were positively related to organizational commitment, organizational citizenship behavior, job satisfaction, and job performance and negatively related to job stress.

Keywords: emotional intelligence (EI), organizational commitment, organizational citizen behavior (OCB), job satisfaction, job performance, job stress, meta-analysis

Introduction

Since the 1990s, the study of emotional intelligence has gained importance in disciplines such as psychology (Salovey et al., 2009 ), management (Prentice et al., 2020 ), organizational behavior (Minbashian et al., 2018 ), leadership (Goleman et al., 2013 ), education (Titrek, 2009 ), and marketing (Kidwell et al., 2011 ). This is due to the increasing value of emotional intelligence in employees. It is argued that a business that effectively manages emotions within its organization results in better performance and higher rates of return than companies that ignore emotions (Parmar, 2016 ). Emotions can be effectively managed in an organization by understanding employees (Pick et al., 2015 ), cultivating empathy (Petrovici and Dobrescu, 2014 ), giving them a chance to understand each other and creating a unique organizational emotional climate (Härtel et al., 2008 ). All these abilities, in addition to the capacity of the employees to monitor their own and others' emotions, were defined as emotional intelligence by Salovey and Mayer ( 1990 ). They viewed emotional intelligence as a subgroup of social intelligence, and following their continued research, they revised it and propounded the four-branch model of emotional intelligence, which included perception and expression of emotion, assimilating emotion in thought, understanding and analyzing emotion, reflective regulation of emotion (Mayer and Salovey, 1997 ). In their studies, they projected emotional intelligence as an ability, and recent research has added weight to the ability and the integrative model approaches in this field (Mayer et al., 2008 ).

In this study, the primary goal is to update the prior meta-analyses on the relationships between emotional intelligence in organizations and employee outcomes. Scholars have already linked particular employee outcomes with emotional intelligence. These include performance (Gong et al., 2019 ), job satisfaction (Feyerabend et al., 2018 ), organizational commitment (Baba, 2017 ), burnout (Hong and Lee, 2016 ), stress (Sarrionandia et al., 2018 ), leadership (Mullen et al., 2019 ), motivation, organizational justice, and counterproductive work behavior (Tziner et al., 2020 ). In this research, we have attempted to articulate the consequences of emotional intelligence in organizations by conducting a meta-analysis. Various useful meta-analyses on emotional intelligence already exist. For example, Joseph and Newman ( 2010 ) conducted an integrative meta-analysis linking emotion perception, understanding, and regulation with performance. Harms and Credé ( 2010 ) found a positive correlation between emotional intelligence and transformational and transactional leadership. O'Boyle et al. ( 2011 ) added to the literature through their three-stream approach for emotional intelligence and the relationship between the approach with job performance. Miao et al. ( 2017a ) also used the three-stream approach to explore the connections between emotional intelligence and job satisfaction, organizational commitment, and turnover intentions. Building on previous theoretical and methodological contributions of various scholars, in this study, it was decided to explore the relationships between emotional intelligence and certain employee outcomes using a meta-analysis covering a period of 30 years. The employee outcomes that were selected for this analysis are organizational commitment, organizational citizenship behavior, job performance, job satisfaction, and job stress. These employee outcomes were selected for two reasons. First, according to the literature survey, they are the most correlated employee outcomes with emotional intelligence. Second, the three streams of emotional intelligence and the selected employee outcomes form part of future research suggestions in studies undertaken by Ashkanasy and Daus ( 2005 ), Joseph and Newman ( 2010 ), and Mattingly and Kraiger ( 2019 ).

This study also aims to add to the existing literature on emotional intelligence. First, this study includes a vast array of studies on emotional intelligence since the origin of this concept in 1990. Second, this study explores the relationship between emotional intelligence and a wide range of selected employee outcomes, namely, organizational commitment, organizational citizenship behavior, job performance, job satisfaction and job stress. These employee outcomes were carefully selected through a literature review. Third, this study adopts the three-stream classification of emotional intelligence as highlighted by Ashkanasy and Daus ( 2005 ). This study has the following structure – a detailed theoretical review followed by the hypothesis, the research methodology, the overall analysis, and finally, the results of the study. A comprehensive discussion on the results will be presented at the end of the study.

Theoretical Background and Hypothesis Development

Emotional intelligence.

Salovey and Mayer ( 1990 ) were the first to assess emotional intelligence (EI) as an ability of an individual to effectively manage their own and others' emotions. According to Van Rooy and Viswesvaran ( 2004 ), it included all verbal and non-verbal abilities to understand and evaluate emotions. Additionally, there are previous studies that debate whether emotional intelligence is a trait or an ability. Some scholars argue that EI is a competence (e.g., Salovey and Mayer, 1990 ; Austin, 2010 ), and some others refer to it as a trait (e.g., Bar-On, 1997 ; Petrides and Furnham, 2000 ; Petrides et al., 2007 ).

Based on the different approaches for emotional intelligence, different measures have been adopted to assess them. For instance, Harms and Credé ( 2010 ) and O'Boyle et al. ( 2011 ), in their studies, discussed the Bar-On Emotional Quotient Inventory (EQ-i) (1997) and the Emotional and Social Competency Inventory (Boyatzis et al., 2011 ) for measuring emotional intelligence as a trait. Mayer and Salovey ( 1997 ) developed and transformed EI into a four-branch model. In 2002, the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) was developed (Mayer et al., 2002 ) and, after a year, the 141-item scale MSCEIT V2.0 was developed (Mayer et al., 2003 ).

Throughout this study, the three-streams approach of emotional intelligence is used. According to Ashkanasy and Daus ( 2005 ), the first stream is ability-based, the second is self-report, and the third is mixed-model. The purpose of the study is to include as many studies as possible using the three different streams and to measure emotional intelligence.

Organizational Commitment

Organizational commitment as a concept has been very popular among organizational behavior scholars since the 1970s. It has been associated with many important employee attitudes and behaviors like employee turnover (Marsh and Mannari, 1977 ; Kang et al., 2015 ), job satisfaction (Bartol, 1979 ; Culibrk et al., 2018 ), absenteeism (Cohen and Golan, 2007 ), job performance (Supriyanto, 2013 ), role stress (Han et al., 2015 ), and knowledge sharing (Curado and Vieira, 2019 ).

Organizational commitment is indicative of the employee's recognition and acceptance of organizational circumstances (Steers, 1977 ). The essential characteristics of organizational commitment include approval of organizational rules, approval of objectives and values, and behaving in favor of the organization (Porter et al., 1974 ). Given the multidimensional structure of organizational commitment, Meyer and Allen ( 1991 ) classified the concept into affective, normative, and continuance commitment. Affective commitment is defined as the sentimental attachment employees have for their organization, and normative commitment is built on the moral obligation they feel to stay back in an organization. Continuance commitment is when the employee prefers to remain in the organization for fear of facing a negative outcome associated with leaving the organization (Allen and Meyer, 1990 ).

Employees with higher emotional intelligence are believed to direct their own emotions, and therefore, they might be more committed to their organizations. These kinds of employees are more resistant to emotional surges. For this reason, their intent to leave their organizations is lower when compared to employees with a lower level of emotional intelligence (Lee and Woo, 2015 ). Another reason is that emotionally intelligent employees are more successful in building strong social relationships in the workplace (Schutte et al., 2001 ). Managers, who are recognized as the agents of the organization, provide social support that increases the level of organizational commitment (Panaccio and Vandenberghe, 2009 ). As evidenced from the literature by Miao et al. ( 2017a ), and Baba ( 2017 ), there is a positive correlation between EI and organizational commitment, which is our first hypothesis.

Hypothesis 1 (H1): EI has a positive relationship with organizational commitment of employees .

Organizational Citizenship Behavior

Organizational citizenship behaviors (OCB) of employees are generally related to the social and psychological aspects within organizations (Organ, 1997 ). These behaviors mostly go beyond the formal job description in the workplace. Among these behaviors are accepting extra responsibilities and duties, working longer hours, accepting and obeying organizational rules and procedures, and helping colleagues when they need (Organ et al., 2006 ). These types of activities are usually not listed in the formal reward system of an organization (Organ and Lingl, 1995 ).

Organ ( 1988 ) classified organizational citizenship behavior into altruism, conscientiousness, sportsmanship, courtesy, and civic virtue and used each classification to define a particular behavior exerted by the employee in an organization. For example, it is altruism when employees tend to help colleagues when they need anything. Conscientiousness is related to obeying organizational rules like working hours, for instance. When employees employ constructive approaches to issues in the organization and refrain from complaining of any inconvenience, it is sportsmanship . It is courtesy when employees stop from abusing the rights of others in the organization. Lastly, civic virtue refers to activities that are undertaken to serve the interests of the organization, such as being a member of various committees.

Emotional intelligence is understood to reinforce the organizational citizenship behaviors of employees in an organization. This may be deducted from the results of studies that have found that employees who are good at managing their emotions are more eager to demonstrate positive behaviors in their organizations (e.g., Miao et al., 2017c ; Kim and Park, 2020 ). Additionally, employees with high emotional intelligence tend to volunteer helping others in the workplace. Previous studies demonstrate the positive link between EI and OCB (e.g., Turnipseed and Vandewaa, 2012 ; Pradhan et al., 2016 ; Miao et al., 2018 ), which is the second hypothesis.

Hypothesis 2 (H2): A positive relationship exists between EI and organizational citizenship behavior .

Job Satisfaction

Job satisfaction has emerged as a very popular behavioral outcome among scholars who have been trying to locate behavioral outcomes since the beginning of 1930s (e.g., Hoppock, 1935 ). Job satisfaction is an attitude that signals “a positive or negative evaluative judgment toward an employee's job.” (Weiss, 2002 ). Ever since the introduction of the concept of job satisfaction in this field, its various impacts on employees have been examined. Among them are job performance (Li et al., 2018 ), turnover intentions (Lu et al., 2016 ), job burnout (Zhang and Feng, 2011 ), organizational commitment (Valaei and Rezaei, 2016 ), and organizational citizenship behavior (Singh and Singh, 2019 ). According to these studies, there are positive links between job performance, organizational commitment and organizational citizenship behavior, and job satisfaction. On the contrary, job satisfaction has negative effects on turnover intentions and burnout since it is an important element that steers an individual's happiness and enthusiasm to perform in the workplace (Piccolo et al., 2005 ).

Emotional intelligence is a vital input for employees feeling job satisfaction. For example, Anari ( 2012 ), in his study on high-school teachers, established positive links between emotional intelligence and job satisfaction. Similarly, Brunetto et al. ( 2012 ) found that EI was the main indicator for predicting job satisfaction in a study among 193 police officers in Australia. Furthermore, in their meta-analysis, Miao et al. ( 2017b ) revealed that job satisfaction was positively affected by emotional intelligence regardless of gender, age, or tenure, which is the basis of our third hypothesis.

Hypothesis 3 (H3): EI has a positive link with job satisfaction .

Job Performance

Job performance, in general, can be defined as the employee's activities and behaviors that directly or indirectly contribute to the organizational goals (Borman and Motowidlo, 1993 ). From this perspective, the level of job performance is a valuable indicator for many human resource management decisions (e.g., training and development, compensation, and promotion).

Most studies categorize job performance as a task or a contextual performance (e.g., Borman and Motowidlo, 1997 ; Van Scotter, 2000 ). Task performance includes the degree to which employees meet the standards of core and technical tasks and duties. Alternatively, contextual performance measures the degree of employees' behaviors that promote the social and psychological environment in the organization, such as helping others, taking extra responsibilities in the workplace, and obeying organizational rules and procedures (Motowidlo and Van Scotter, 1994 ). There are many studies that substantively establish that emotional intelligence is a meaningful precursor for performance. For example, Farh et al. ( 2012 ) found in their study on 212 professionals from different organizations that overall emotional intelligence led to more effective teamwork and higher job performance. Similarly, Li et al. ( 2018 ) found a positive correlation between trait emotional intelligence and performance among 881 teachers and 37 principals from primary schools in China. Also, O'Boyle et al. ( 2011 ) found positive correlations between all the three streams of emotional intelligence and job performance in their meta-analysis, which is our fourth hypothesis.

Hypothesis 4 (H4): EI is positively related to job performance .

Job stress is a deviation from the ordinary psychological state of an employee due to job-related factors (Schuler, 1980 ). Job stress is mostly associated with poor job performance (Siu, 2003 ), low motivation (Luo, 1999 ), low job satisfaction (Parker and DeCotiis, 1983 ), high emotional exhaustion (Griffin et al., 2010 ), and high turnover intentions (Mullen et al., 2018 ). In general, building strong social relationships, having role clarity, providing organizational support, and encouraging knowledge sharing help employees decrease their stress levels.

In addition to environmental and organizational factors, the employees' personality, perceptions, and emotions are significant factors contributing to job stress among them (Spector and Goh, 2001 ; Sur and Ng, 2014 ). It is evident that employees who are good at managing their emotions experience lower job stress (Mann, 2004 ). However, it is important to note the link between emotional intelligence and job stress. Lee ( 2010 ) found a negative relationship between emotional intelligence and job stress among 152 nurses from 4 hospitals in Korea. Similarly, Shukla and Srivastava ( 2016 ) found a negative relationship between trait emotional intelligence and job stress among 564 retail employees, which is our fifth hypothesis.

Hypothesis 5 (H5): EI is negatively related to job stress .

Meta-Analytical Research Methodology

Literature review.

Since the aim of this study was to include all the relevant research so far, 1990 was chosen as the beginning year, given that it was in 1990 that Salovey and Mayer conceptualized EI. The time period for this analysis was from 1990 to 2019. However, to expand the scope of this study, studies that were published in the early months of the 2020 were also included. To increase the likelihood of identifying relevant studies, both published and unpublished research works in English were included in the analysis. Keywords such as emotional intelligence, emotional ability, emotional competency, emotional stability, organizational commitment, organizational citizenship behavior, job satisfaction, job performance, job stress, and occupational stress were used in this analysis.

To expand the scope of this study, several research techniques were adopted which were similar to those adopted in previous meta-analytic studies that were part of the literature review. First, the main electronic databases such as ABI/INFORM Global, APA PsycInfo, EBSCOhost, Google Scholar, JSTOR, ProQuest, ProQuest Dissertation and Theses, ScienceDirect, and Web of Science were scanned. Second, a further scanning was carried out by searching the archives of leading journals such as the Academy of Management Annals, the Academy of Management Journal, the Academy of Management Review, Administrative Science Quarterly, the Journal of Applied Psychology, the Journal of Management, the Journal of Organizational Behavior, the Journal of Occupational and Organizational Psychology, Leadership Quarterly, Personnel Psychology, and Personality and Individual Differences. Third, proceedings of leading conferences on Management and Psychology were also scanned (e.g., Annual Meeting of Academy of Management, European Academy of Management Conference, and the Society for Industrial and Organizational Psychology Annual Conference). This broad scanning resulted in identifying 287 articles and 118 unpublished dissertations and conference papers for examining the links between EI and organizational commitment, organizational citizenship behavior, job satisfaction, job performance and job stress. For the articles to be useful for this analysis, some inclusion criteria were determined.

Inclusion Criteria

In order to be included in this meta-analysis, the identified studies needed to meet some rules and standards. The first criterion for any study to be included in this analysis was that it should be a quantitative empirical study providing at least correlation coefficients in its variables. The second criterion was that it should have been published between 1990 and 2020 (the first 2 months). The third criterion was that English should be the article's language. The fourth criterion was related to the sample – only studies that used unique samples when studying more than one sample were included in the analysis. This inclusion criterion was developed to prevent duplication in samples. Drawing on the recommendations from Ashkanasy and Daus ( 2005 ) and meta-analysis by O'Boyle et al. ( 2011 ), emotional intelligence was coded based on three streams (ability EI, self-report EI, and mixed EI). After screening the identified articles using the inclusion criteria, the final total sample for this meta-analysis consisted of 253 effect sizes representing data from 78,159 participants.

Visualization of the Inclusion and Exclusion Process

After carefully screening the existing literature on emotional intelligence and its possible outcomes in the workplace and checking the identified studies against the inclusion criteria, some studies were excluded from the analysis. In order to demonstrate the screening and the selection processes, a widely used visualization technique in meta-analyses, PRISMA Flow Diagram for new Systematic Reviews (Page et al., 2021 ), was employed throughout this meta-analysis and it is shown in Figure 1 .

PRISMA flow diagram for new systematic reviews. Source: Page et al. ( 2021 ).

Descriptive Statistics for the Sample

To understand the profile of the participants in the studies and to provide more information about the sample, some of the descriptive statistics were categorized on the basis of participants' gender, age, and job positions (managerial or non-managerial) as well as the publication details (year and country) of the studies. The descriptive statistics are presented in Table 1 .

Descriptive statistics of the samples included in the analysis.

There is no gender or age information of the participants .

When there is no information about the job position of participant employees, they are assumed to have non-managerial positions .

For this study, the psychometric meta-analysis method was used. The strength of this method is that it provides a basis for estimating the variance of sampling error and gives an opportunity to estimate reliability for studies in which no reliability had been reported (Hunter and Schmidt, 2004 ). This method has been used in previous meta-analyses (e.g., Harms and Credé, 2010 ; O'Boyle et al., 2011 ). One of the reasons for choosing this technique is that it helps to forecast the variance associated with sampling error and artifacts. To generate artifact distributions, reliability estimates were employed to fill the gaps stemming from the absence of reliability data in some of the studies. Hunter and Schmidt ( 1990 ) suggested that the distributions of correlations were corrected in this study. Further, r obs and SD obs were corrected to help understand the artefactual biases and moderators, as done previously by Harms and Credé ( 2010 ). Using the technique proposed by Hunter and Schmidt ( 1990 ) and successfully applied by their successors (Ones et al., 1993 ), several sets of artifact distributions along with their descriptive details are presented in Table 2 . Next, to indicate the significance of effect sizes, the confidence interval was chosen as 95% (corrected). Finally, within this scope, the sample sizes and uncorrected coefficients were converted into corrected correlation coefficients.

Descriptive statistics of artifact distributions for correcting validities.

SD, standard deviation .

The ratio of the standard deviation of the selected group to the standard deviation of the referent group .

As seen in Table 2 , the overall mean of the predictor reliability for artifact distribution is 0.83 and the standard deviation value is 0.09. The mean of the square roots of predictor reliabilities is 0.91 and the standard deviation of the square roots is 0.05. The overall mean of the criterion reliabilities is 0.87 with a standard deviation value of 0.13. The mean of the square roots of criterion reliabilities is 0.93 and the standard deviation of the square roots of reliability is 0.07. Finally, the mean value of the range restriction value is 0.80 with a standard deviation value of 0.15.

After conducting the psychometric meta-analysis (Hunter and Schmidt, 2004 ), the results obtained from the analysis were listed separately. Beginning with the relationship between EI and organizational commitment, the results are presented in Table 3 .

Meta-analytic results of the relationship between EI and organizational commitment.

EI, emotional intelligence; k, number of independent samples; n, sample size; r ¯ , uncorrected sample size weighted mean correlation; ρ, corrected correlation; SD ρ , standard deviation of corrected correlation; CI, confidence interval .

As evident from Table 3 , according to 37 independent overall EI samples, EI is positively and significantly correlated with organizational commitment (ρ = 0.26, p < 0.001). Therefore, according to the result, H 1 is supported. Additionally, all three streams of EI are also positively correlated with organizational commitment. Although there is a slight difference in magnitude, the most powerful positive relationship exists between self-report emotional intelligence and organizational commitment (ρ = 0.28, p < 0.001). The weakest relationship is between ability emotional intelligence and organizational commitment (ρ = 0.22, p < 0.001). The results of the relation between EI and organizational citizenship behavior are presented in Table 4 .

Meta-analytic results of the relationship between EI and OCB.

EI, emotional intelligence; OCB, organizational citizenship behavior; k, number of independent samples; n, sample size; r ¯ , uncorrected sample size weighted mean correlation; ρ, corrected correlation; SD ρ , standard deviation of corrected correlation; CI, confidence interval .

Based on the results obtained from 43 samples, it is evident that emotional intelligence has a positive relationship with organizational citizenship behavior (ρ = 0.36, p < 0.001). For this reason, H 2 is supported. As with organizational commitment, self-report emotional intelligence has a strong positive relationship with organizational citizenship behavior (ρ = 0.37, p < 0.001). Also, as found in previous studies, the important relationship between emotional intelligence and job satisfaction was reaffirmed. Table 5 provides the correlations and additional statistical results.

Meta-analytic results of the relationship between EI and job satisfaction.

According to 74 independent samples, emotional intelligence is positively related to job satisfaction (ρ = 0.29, p < 0.001). This indicates that H 3 is also supported. The three streams of EI are also positively correlated with job satisfaction. This reaffirms another important relationship between emotional intelligence and job performance that this analysis sought to verify. The results are presented in Table 6 .

Meta-analytic results of the relationship between EI and job performance.

As seen in Table 6 , for measuring overall EI, 68 samples were used. Again, both overall emotional intelligence (ρ = 0.29, p < 0.001) and the three streams of EI were positively related to job performance. Therefore, H 4 is also supported. Finally, the relationship between emotional intelligence and job stress is presented in Table 7 .

Meta-analytic results of the relationship between EI and job stress.

It is evident in Table 7 that based on the results obtained from 31 samples, a negative relationship exists between emotional intelligence and job stress (ρ = −0.43, p < 0.001). This significant and negative relationship is marginally stronger than the other relationships in this study. Therefore, H 5 is also supported. Yet again, all three types of EI were significantly related to job stress. It can be inferred that emotional intelligence is an important source for overcoming job stress in the workplace.

Effects of Possible Moderators

The results obtained from the analysis of this meta-analysis suggested conducting a moderator analysis. To understand the effects of the substantive moderators, the moderating effects of different emotional intelligence types, managerial and non-managerial positions and publication types were analyzed by conducting separate meta-analyses.

Effects of Types of Emotional Intelligence

As previously stated, the potential moderating effects of ability emotional intelligence, self-report emotional intelligence, and mixed emotional intelligence were further studied by conducting separate meta-analyses. The separate results are indicated in Tables 3 – 7 . According to the results, Ability EI, Self-report EI , and Mixed EI have similar positive and statistically meaningful effects on organizational commitment, organizational citizenship behavior, job satisfaction, and job performance but have negative effects on job stress (i.e., ρ AbilityEI = 0.22; ρ Self−report EI = 0.28; ρ Mixed EI = 0.27 for organizational commitment; ρ AbilityEI = 0.29; ρ Self−report EI = 0.37; ρ Mixed EI = 0.35 for organizational citizenship behavior; ρ AbilityEI = 0.24; ρ Self−report EI = 0.31; ρ Mixed EI = 0.30 for job satisfaction; ρ AbilityEI = 0.28; ρ Self−report EI = 0.33; ρ Mixed EI = 0.31 for job performance; and ρ AbilityEI = −0.42; ρ Self−report EI = −0.45; ρ Mixed EI = −0.37 for job stress).

Effects of Managerial/Non-Managerial Positions

Few of the studies included in this meta-analysis had further categorized the employees as holding either managerial or non-managerial positions in their organizations. Employees such as branch managers, coaches, supervisors, and chief officers were categorized under managerial staff, while frontline employees and subordinates were categorized under non-managerial staff. To examine the moderating effects of managerial and non-managerial positions on employee outcomes, separate meta-analyses were conducted. According to the results of the meta-analyses, a higher correlation exists between emotional intelligence and organizational commitment when employees held managerial positions (ρ managerial : 0.32 > ρ non −managerial : 0.24), as shown in Table 3 . On the other hand, as indicated in Table 4 , the correlation between emotional intelligence and organizational citizenship behavior was lower among managers (ρ managerial : 0.27 < ρ non −managerial : 0.38). Table 5 shows the lower levels of correlation between emotional intelligence and job satisfaction among managers (ρ managerial : 0.21 < ρ non −managerial : 0.33). The same is applicable for the managers' relationship between emotional intelligence and job performance, as evident in Table 6 (ρ managerial : 0.33 < ρ non −managerial : 0.40). Finally, in Table 7 , the negative correlation between emotional intelligence and job stress is established; however, it is stronger among employees in non-managerial positions (ρ managerial : −0.30 < ρ non −managerial : −0.47).

Effects of Publication Type

To examine the moderating effects of publication types included in this meta-analysis, both published and unpublished studies were included in separate analyses. This was done to overcome the “file drawer problem” (Harms and Credé, 2010 ), given that most of the results in this analysis were derived from published studies. According to the results, the correlations between the variables differ based on whether a study is published or unpublished. For example, in Tables 3 – 7 , the corrected correlation between emotional intelligence and organizational commitment in published studies is higher than the one in unpublished studies (ρ published : 0.31 > ρ unpublished : 0.21). Similarly, between emotional intelligence and job satisfaction (ρ published : 0.35 > ρ unpublished : 0.24) and between emotional intelligence and job stress (ρ published : −0.48 > ρ unpublished : −0.38), the same correlation exists. However, the corrected correlation between emotional intelligence and organizational citizenship behavior in published studies is lower than the one in unpublished studies (ρ published : 0.32 < ρ unpublished : 0.40). Similarly, the correlation between emotional intelligence and job performance is lower in published studies (ρ published : 0.25 < ρ unpublished : 0.34).

Findings and Theoretical Contributions

With the help of this analysis, the relationships between EI and selected employee outcomes in organizations are presented herewith. According to the results obtained in this study, emotional intelligence and its three streams are positively related to organizational commitment, organizational citizenship behavior, job satisfaction, and job performance; however, they are negatively related to job stress. If the relationship between the different streams of EI and organizational commitment is analyzed, it is noticed that self-report EI is slightly stronger than mixed EI and ability EI (ρ Self−report EI: 0.28 > ρ Mixed EI : 0.27 >ρ Ability EI : 0.22). Similarly, the relationship between the different streams of EI and organizational citizenship behavior shows that self-report EI is slightly stronger than ability EI and mixed EI (ρ Self−report EI: 0.37 > ρ Mixed EI : 0.35 >ρ Ability EI : 0.29). Additionally, self-report EI is slightly stronger than ability EI and mixed EI when there exists a relationship between the different streams of EI and job satisfaction (ρ Self−report EI: 0.31 > ρ Mixed EI : 0.30 >ρ Ability EI : 0.24). In the relationship between EI streams and job performance, self-report EI is still stronger than mixed EI, and ability EI is the weakest (ρ Self−report EI: 0.33 > ρ Mixed EI : 0.31 >ρ Ability EI : 0.28). However, when samples of job stress is analyzed, although self-report EI has the strongest negative correlation, ability EI emerges second (ρ Self−report EI: −0.45 > ρ Ability EI : −0.42 > ρ Mixed EI : −0.37). These results can be used to explain the ranking within the three streams of emotional intelligence. In general, except for the relationships between the EI streams and job stress, it is evident that self-report EI is the most influential among all three EI streams. Although it is useful to note that the differences in their magnitudes are quite slim, in the relationships between the EI streams and job stress alone, ability EI ranked second while mixed EI ranked third.

When the results of this meta-analysis are compared with the previous meta-analyses, it is evident that the findings of the relationships between EI and organizational commitment are consistent with surveyed literature. Miao et al. ( 2017a ) also found a positive correlation between self-report EI and organizational commitment, which is slightly stronger (ρ = 0.43) than the result obtained in this study (ρ = 0.28). Their result on mixed emotional intelligence is also higher (ρ = 0.43) than the one in this study (ρ = 0.27). Previous meta-analyses also found a positive correlation between EI and organizational citizenship behavior. For example, Miao et al. ( 2017c ) obtained positive correlations between the three streams and organizational citizenship behavior. The corrected correlation coefficients in this analysis are marginally lower than their results. There are also similarities between this research and the analysis of Miao et al. ( 2017a ) on the link between emotional intelligence and job satisfaction. Furthermore, the results obtained from this meta-analysis indicate a positive link between EI and job performance; these results are consistent with the previous meta-analysis of O'Boyle et al. ( 2011 ). The last relationship examined in this meta-analysis was between EI and job stress. The negative relationship between them was already identified in the studies that were included in this study. Since there was no meta-analysis in the literature that examined this relationship, the results of this study were consistent with the results of separate studies (e.g., Mikolajczak et al., 2007 ; Karimi et al., 2014 ).

Finally, it is important to flag the effects of managerial and non-managerial positions of the employees on the relationships between emotional intelligence and employee outcomes. As reported in the results shared above, it is evident that, when employees hold managerial positions, their emotional intelligence positively influences their level of organizational commitment and a stronger correlation is obtained (ρ managerial : 0.32 > ρ non −managerial : 0.24). However, correlations between emotional intelligence and organizational citizenship behavior (ρ managerial : 0.27 < ρ non −managerial : 0.38), job satisfaction (ρ managerial : 0.21 < ρ non −managerial : 0.33), job performance (ρ managerial : 0.33 < ρ non −managerial : 0.40), and job stress (ρ managerial : −0.30 < ρ non −managerial : −0.47) was weaker in those employees holding managerial positions. From this perspective, although there are positive relationships between emotional intelligence and organizational citizenship behavior, job satisfaction, and job performance, it is evident that those employees who hold non-managerial positions exhibit stronger positive correlations to these outcomes. A similar trend is observed in the negative relationship between emotional intelligence and job stress among non-managers in the workplace.

In this study, an attempt was made to add to the existing literature on emotional intelligence by determining the nature of relationships between emotional intelligence and selected employee outcomes such as organizational commitment, organizational citizenship behavior, job satisfaction, job performance, and job stress. These relationships were distinguished by ability EI, self-report EI, and mixed EI. This helped us to see the consequences of emotional intelligence on employees in a more detailed way. Lastly, the categorization of managerial and non-managerial roles in the samples provided valuable insights into the relationships between emotional intelligence and employee outcomes.

Limitations and Future Research Suggestions

One of the limitations was the methodology used in the studies. Some studies used self-reports for organizational citizenship behavior and job performance. Though these studies were few, their inclusion in this analysis is a limitation for more accurate results. Another limitation is the inclusion of unpublished studies such as dissertations in the analysis. Yet again, though there were few dissertations compared to other published resources, it is important enough to be flagged as a limitation for this analysis. The third limitation was that only English sources were included in the analysis. Finally, moderators and contextual factors were not included to retain the focus on the aim of the research.

The limitations listed in this meta-analysis provide a basis for future research in this area. Researchers should also consider including more moderators and contextual factors while assessing the outcomes of emotional intelligence in their future studies. Future research should also examine the effects of emotional intelligence on other factors like leadership, occupational stress, role stress, innovative behavior and social relations. Another potential variable that has been largely underemphasized is the correlation between emotional intelligence and digital transformation in the workplace (e.g., Kaur and Sharma, 2021 ). Thus, researchers should investigate the role of emotional intelligence on the future of work and employees' perceptions of digitalization in the workplace (e.g., Stubbemann, 2021 ).

Practical Implications

Emotional intelligence gains importance day by day for human resource managers and line managers. In general, human resource managers are more eager to select and place candidates with higher emotional intelligence (Chia, 2005 ). Similarly, line managers are satisfied with the performance of employees with higher emotional intelligence (Gong et al., 2019 ). This is because these employees can manage their own emotions as well as their colleagues' emotions. With the help of emotional intelligence, employees' satisfaction from job (Soleimani and Einolahzadeh, 2017 ), organizational commitment (Jain and Duggal, 2018 ), and job performance (Joseph et al., 2015 ) is set to increase. For these reasons, human resource departments should plan strategies for increasing the emotional intelligence of their employees. They could design training and development programs to increase ability EI, self-report EI, and mixed EI. Human resources managers could also set rules and standards for rewarding employees with favorable behaviors in the workplace. In addition, line managers could demonstrate effective leadership by promoting employee outcomes based on emotional intelligence.

This meta-analysis was an attempt to explore the consequences of emotional intelligence on employee outcomes with the help of previous studies within a time frame of the last 30 years. From this perspective, this study has tried to add an important brick on the wall of emotional intelligence literature. Consistent with the previous meta-analyses, the three-stream approach for emotional intelligence was adopted for this study as well. After carefully examining the studies, it has been observed that all streams of EI are positively related to organizational commitment, organizational citizenship behavior, and job satisfaction whereas they are negatively related to job stress. According to the results of this meta-analysis, the magnitudes of the correlations were higher in self-report emotional intelligence compared to ability emotional intelligence; however, the differences were not very large.

From this comprehensive meta-analysis, it can be inferred that employees who are good at managing their own emotions and their colleagues' emotions are more committed to their organizations and are more eager to show organizational citizenship behavior, evince job satisfaction, and evince better job performance, and their level of job stress tends to decrease. Since these are all favorable employee outcomes, managers should design development programs for increasing the capacity of emotional intelligence among employees in the organization. In addition to other job-specific competencies, they should select and place employees with high emotional intelligence.

By including all three streams of emotional intelligence to examine their links with employee outcomes, this holistic meta-analysis is a first step for future studies exploring important relationships and developing research models on emotional intelligence. Although there are comprehensive studies in the literature, more studies are still needed for the future.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

Author Contributions

The author confirms being the sole contributor of this work and has approved it for publication.

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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ORIGINAL RESEARCH article

The influence of emotional intelligence on job burnout and job performance: mediating effect of psychological capital.

• Department of Psychology, Normal College, Qingdao University, Qingdao, China

How does emotional intelligence (EI) affect job performance and job burnout? Direct or indirect? What role does psychological capital play? This study surveyed 450 employees of various enterprises through questionnaires. Results are as follows: (1) Employees’ EI has a positive predictive effect on psychological capital and job performance, and it is negatively correlated with job burnout; (2) psychological capital has a negative predictive effect on job burnout and a positive predictive effect on job performance; and (3) psychological capital plays a mediating role in the relationship between EI and job burnout/performance. Results of this study may contribute to develop EI theories in organizational behavior field. As for enterprises, improving the EI of employees will help to improve their psychological capital, and high psychological capital will lead to positive job performance and less job burnout.

Introduction

In contemporary society, the economy is developing rapidly, competition tends to grow, and organizational performance is one of the most important indicators of how to develop ever better in the face of global competition. As a profit-making organization, improving organizational performance is the most important mission of enterprises. Present-day companies want to recruit or train potential employees who are willing to go beyond their established roles to improve performance ( Adams et al., 2002 ). However, when enhancing the organizational performance of enterprises, the workload and work pressure of employees will also be increased. Therefore, job burnout, which can easily occur in a high-pressure environment, is a common problem in enterprises or organizations. The problem of job burnout will affect the job performance and cause it to decline, leading to more serious burnout, forming a vicious circle, and ultimately affecting the organizational performance. Earlier findings documented the fact that job burnout could have many negative effects on employees, which could not only reduce job performance and job satisfaction but also increase absenteeism/separation rate, etc. ( Maslach et al., 2001 ). In addition, the results of a study showed that “Job burnout can easily lead to apathy toward others, have a negative impact on the individual, and have a negative impact on the organization” ( Sharma and Sharma, 2015 ). In this context, a key to the development of enterprises is reducing employees’ job burnout and improving their job performance.

Many organizations have realized that, to stand out in today’s competitive business world, they need not only academic skills but also emotional intelligence (EI) ( O’Boyle et al., 2011 ). EI has a long process of development; Salovey and Mayer formally put forward the concept of “EI” in 1990. In 1995, the concept of EI received much attention all over the world due to the publication of Goleman’ s book Emotional intelligence: Why it can matter more than IQ . Since then, an important research subject has arisen in the fields of industrial and organizational psychology: the relationship between EI and job performance. Researchers have associated job performance with EI, arguing that it was not only the ability to manage one’s own feelings but also the ability to understand others within the organization ( Mayer et al., 2003 ). According to Bandura’s theory of self-efficacy, EI can effectively regulate individual’s emotion and then promote the formation of self-efficacy. In practice, to enable employees to adapt to new work environment faster and create better job performance, the manager also begins to pay attention to the relationship between EI and work performance in recruitment and training. If a manager improves the EI of employees, they can effectively reduce their job burnout, improve job performance, and solve the problem of poor enterprise efficiency.

Although some studies have proven the effect of EI on job performance and job burnout, the related research on how EI affects job performance and job burnout has not been fully certified and is still waiting for investigation. Pradhan confirmed the hypothesis that “EI plays a regulatory role between psychological capital and organizational citizenship behavior” ( Pradhan et al., 2016 ). Moreover, EI and psychological capital can predict job performance and job burnout. On this basis, the purpose of this paper is to explore the role of psychological capital, which played a mediating role in the relationship between EI and job burnout. This study summarizes the four structures, gives the hypothesis, and explains the research methods. Finally, it discusses the contribution to the theoretical development and the possible implications for organization by the results.

Theory and Hypothesis

Emotional intelligence.

Emotional intelligence is “the ability to control emotions of oneself and others, to distinguish them from each other and to apply this information to guide one’s own thinking and action” ( Salovey and Mayer, 1990 ). Goleman, in his book in 1995, described how to help students build up EI; his study of more than 500 organizations from the Hay Group showed that more than 85% of senior leaders owe their outstanding performance to EI rather than intelligence ( Goleman, 1995 ). Bar-On proposed the following definition: “EI is a series of non-cognitive, competent, and skills that affect the ability of individuals to successfully respond to environmental needs and pressures” ( Bar-On, 1997 ). In 1998, Goleman presented the concept of emotional competence, defined as follows: “On the basis of EI, people have made good achievements at work and demonstrated the ability to form through acquisition;” to distinguish emotional competence from EI, he thinks that EI is essentially a potential, and emotional competence is a kind of acquired ability based on EI, which reflects people’s ability to learn and master skills and apply this intelligence to specific situations ( Goleman, 1998 ). Cooper noted that “if IQ is the driving force in business in the 20th century, the driving force in business in the 21st century will be EI ( Cooper and Sawaf, 1998 ).” In 2000, Bar-On further noted that EI is a social capability that affects a range of emotional capabilities and had an effect on environmental requirements. Bar-On also made a distinction between EI and social intelligence; he regards EI as an individual’s ability to manage one’s own actions, such as impulse control, and regards social intelligence as a relational skill ( Bar-On and Parker, 2000 ). Meanwhile, Salovey and Mayer improved and enriched the view of EI as a cognitive emotion used to enhance cognitive activities, as well as the ability to solve problems and difficulties through the use of knowledge ( Mayer et al., 2000 ). EI includes four aspects: (1) the ability to accurately perceive, assess, and express emotions; (2) the ability to promote thinking using emotion; (3) the ability to understand emotion and emotional knowledge; and (4) the ability to regulate and manage emotions.

Influence of Emotional Intelligence on Job Burnout and Job Performance

The concept of job burnout was proposed by Freudenberger (1974) , after he put forward the concept; the problem of job burnout began to be explored by a large number of scholars. This study used Maslach’ s definition of job burnout. According to Maslach and Jackson (1981) , job burnout includes emotional exhaustion, depersonalization, and personal accomplishment. Among them, exhaustion is the central quality of burnout; depersonalization is an attempt to distance yourself from the service recipient by actively neglecting the qualities that make it unique. The relationship between personal accomplishment and the other two dimensions of job burnout is more complex. It is difficult to gain a sense of accomplishment when feeling exhausted or when helping people toward whom one is indifferent ( Maslach et al., 2001 ). Much research has been conducted to explore the antecedent variable to determine the relevant factors that prevent or reduce this negative performance.

Performance can be defined in many ways, but the more precise definition came from Campbell et al. (1993) , who defined performance as “the goal relevant actions of an employee.” In other words, whether the behavior of employees matches the goals of the organization and whether it can achieve the desired results of the organization. As one of the types of performance, job performance reflects how effectively a person is using influence opportunities ( Chen and Schaubroeck, 2002 ), that is whether the work done by the employees are effective or whether they can show good talent.

Durán et al. (2004) have shown that individuals who have a clear emotional expression ability and emotional repair ability can significantly contribute to individual success. Indeed, emotion not only affects the way people think and act but also signals about judgement and information processing ( Averill et al., 1994 ; Brief and Weiss, 2002 ; Loewenstein and Lerner, 2003 ); employees with higher EI can find suitable solutions more smoothly at work and apply emotional resources reasonably and can often quickly access social support in communication and interaction with people, thus reducing the possibility of failure and the depersonalization brought about by failure. Employees can manage emotions by adjusting their perception of the work environment and the emotional stimuli from the environment; they can accomplish what they want to achieve by strengthening, weakening, prolonging, or shortening certain emotional experiences ( Wong and Law, 2002 ). All of these can effectively reduce employees’ sense of burnout at work. There is also a significant negative correlation between emotional evaluation and emotional exhaustion and a significant negative correlation between emotional control and failure ( Chan, 2006 ). In addition, the study of Platsidou (2010) showed that there is a high correlation between EI and burnout. The optimization of EI is a key factor in the relief of job burnout. Likewise, according to a systematic review of EI and teacher burnout, EI is negatively correlated with teacher burnout ( Mérida-López and Natalio, 2017 ).

Through, these results support the hypothesis of the relationship between EI and job burnout. On the basis of the existing related theory and research summarized, we derive the following hypothesis:

H1 : Employees’ EI has a significant negative correlation with job burnout.

H2 : Employees’ EI has a significant positive correlation with their job performance.

Psychological Capital

In recent years, with the hot research subject of positive psychology and its application in the fields of organizational behavior and management, a new theoretical concept, psychological capital, has been put forward. Luthans defined the concept of psychological capital as a general, positive core psychological element of the individual, including the psychological state that conforms to the standard of positive organizational behavior, which is mainly composed of four dimensions. The four positive psychological abilities of self-efficacy, hope, optimism, and tenacity are the core psychological elements that transcend economic capital, social capital, and human capital. These four dimensions are measurable and developed mental states, allowing individuals to achieve more effective performance ( Youssef and Luthans, 2007 ). Since the positive psychological state contained in psychological capital can promote the positive attitude and behavior of the individual, empirical studies have become increasingly focused on psychological capital.

The Influence of Psychological Capital on Job Burnout and Job Performance

The interpretation of the concept of job performance refers to a set of performance activities produced by employees in the work environment. Peterson and Luthans, through the study of enterprises, found that psychological capital, self-efficacy, optimism, hope, and tenacity can have a positive impact on job performance and attitude ( Peterson and Luthans, 2003 ). The more “hope” employees have, the higher their performance is, in general. An empirical study on psychological capital and job performance of employees in Chinese enterprises by Luthans ( Luthans et al., 2005 ) drew the following conclusions. First, Chinese employees’ hope, optimism, and tenacity all play a positive role in predicting their job performance. Second, the overall psychological capital, which is composed of optimism, hope, and tenacity, plays a more important role in the positive prediction of job performance. Therefore, according to the above results, the psychological capital of employees has a positive predictive effect on their job performance.

The conservation of resource (COR) theory showed that people are encouraged to acquire, protect, and promote the basic principle of acquiring what they cherish—their resources ( Hobfoll, 1988 ). From the COR theory, people are facing the threat of losing resources in three situations. When resources are threatened (e.g., lose self-esteem because of poor grades), wasted (e.g., affect academic performance because of part-time work), and the investment in resources has no income (e.g., take time to study, but there is no increase in GPA) ( Alarcon et al., 2011 ). Research by Cozzarelli (1993) and Rini et al. (1999) supported the view that the possession of a major resource in COR theory is usually linked with the possession of other resources. It is the desire to defend and promote acquisition of these valued resources which motivates human behavior in the face of stress ( Holmgreen et al., 2017 ). The cross-domain relevance of COR theory makes it widely used in the study of internal pressure in organizations ( Grandey and Cropanzano, 1999 ; Brotheridge and Lee, 2002 ). This is a multitiered theory designed to understand individuals nested within different environments, such as the family, the community, and the culture ( Hobfoll, 2001 ). More importantly, it has been confirmed by many empirical studies that it is an important determinant of job burnout ( Hobfoll and Shirom, 2001 ; Shirom et al., 2013 ). According to the COR theory, psychological capital can be used as an individual resource to help individuals regulate their job stress, thus alleviating their job burnout. Similarly, the meta-analysis of Lee and Ashforth (1996) showed that resource-related factors can be used to resolve emotional exhaustion and cynical negative emotions, thus effectively controlling the occurrence of low job self-efficacy situations. Avey et al. (2006) studied the correlation between psychological capital and absenteeism through an empirical study of 105 high-level engineering staff. According to the results of the study, first, optimism and hope regulated and predicted voluntary and involuntary absenteeism, and the overall psychological capital (composed of the four dimensions of optimism, hope, resilience, and self-efficacy) is more effective and accurate in predicting voluntary absenteeism than hope, optimism, resilience, and self-efficacy considered separately. Second, the results showed that there is a significant negative correlation between the overall psychological capital and involuntary absenteeism. In addition, Rehman’ s study on teachers’ job burnout showed that teachers’ positive psychological capital has a significant impact on eliminating job burnout and improving job performance ( Rehman et al., 2017 ).

Taken together, in the theoretical support of the above research results, we can assume that employees’ psychological capital will have a negative predictive effect on their job burnout and a positive predictive effect on their job performance. Thus, the following hypotheses can be claimed:

H3 : There is a significant negative correlation between employees’ psychological capital and job burnout.

H4 : The psychological capital of employees has a significant positive correlation with their job performance.

The Mediating Effect of Psychological Capital in Emotional Intelligence, Job Performance, and Job Burnout

Some studies have shown that there is a significant positive correlation between EI and psychological capital; psychological capital played a mediating role in employees’ EI and resistance to change ( Malik and Masood, 2015 ). Meanwhile, EI is significantly related to psychological capital; in addition, employees can improve their psychological capital by motivating themselves to form self-motivation and developing the ability to control their emotions in various situations ( Mellão and dos Santos Mendes Mónico, 2013 ).

Bandura found that the mental state is an important factor of self-efficacy ( Bandura, 1978 ). Medium-intensity emotions contribute to the formation of self-efficacy, while overintense emotion weakens self-efficacy. EI can allow individuals to effectively regulate their emotions and promote the formation of self-efficacy. In addition, some scholars have shown that positive psychological orientation can help individuals develop better EI to maintain healthy interpersonal relationships and achieve the best organizational performance ( Pradhan et al., 2016 ). In a recent study, it was also shown that the EI of managers plays an important role in obtaining psychological capital ( Sarwar et al., 2017 ).

Therefore, it can be speculated that people with high EI will also have higher psychological capital. Previous studies have shown that psychological capital has a full mediating effect between servant leadership and employees’ intention to stay, sales ambidexterity, and service-oriented organizational citizenship behaviors ( Tsaur et al., 2019 ). As a result, psychological capital, as a mediating role, has been applied in a large number of studies in the field of organizational psychology. Accordingly, the following hypothesis is suggested:

H5 : Psychological capital plays a mediating role in the relationship between EI and job burnout/performance.

Materials and Methods

Participants and procedure.

This study sent out questionnaires to enterprises, organizations, or employees in advance by means of questionnaire survey. The subjects were employees of a number of private enterprises, state-owned enterprises, and public institutions in Qingdao area, Shandong Province, China, including two sales private enterprises, one IT state-owned enterprise, and one junior middle school. Participants include salespeople in the enterprise, human resources directors, and middle school mathematics teachers. To test the heterogeneity of samples, we carried out one-way ANOVA. The results showed that there was no significant difference in job performance and job burnout among different occupations ( p > 0.05). A total of 450 questionnaires were distributed, among which 347 valid questionnaires were recovered, and the recovery rate of valid questionnaires was 77%. The basic information of the questionnaire respondents is as follows: (1) the number of male participants was 208, accounting for 59.9% of the total participants, and the number of female participants was 139, accounting for 40.1% of the total participants; (2) the number of persons with a college education or below was 166, or 47.8% of the total participants, the number of participants with undergraduate education was 174, accounting for 50.1% of the total participants, and the number of participants with a master’s degree or above was 7, accounting for 2.1% of the total participants. All the investigations were approved by the Institutional Review Board of Normal College of Qingdao University, and each participant signed informed written consent.

We used the Psychological Capital Questionnaires developed by Luthans et al. (2007) to measure this variable. The scale is based on the published, widely accepted, standardized scale for all four elements to be measured, and the reliability and validity of the measurement are well validated in the context of Chinese enterprises ( Luthans et al., 2008 ). The scale consists of four dimensions: hope, toughness, optimism, and self-efficacy. We use the six-item Likert scale to allow the participants to express opinions or attitudes from “strongly disagree” to “strongly agree.” Sample items include “since I have been through many hardships before, I am able to survive the difficult times at work now;” “I’m optimistic about what’s going to happen to my job;” “in my current job, things have never been the way I wanted them to be;” and “at work, I always believe that behind the darkness is the light; there is no need to be pessimistic.” The confirmatory factor analysis (CFA) results showed that the data are in accordance with the model of four factors and a higher-order factor [χ 2 /df = 3.63, root mean square error of approximation (RMSEA) = 0.07, comparative fit index (CFI) = 0.89, normed fit index (NFI) = 0.85, Tucker–Lewis index (TLI) = 0.88]. Using a past study as a reference, we used the total average of the four dimensions as the final measurement for the variable.

We used the Emotional Intelligence Scale (EIS) developed by Wong and Law (2002) . The instruction is revised to form a Chinese version of the EIS, which consists of 16 items ( Law et al., 2004 ) and is a self-report test. Its four dimensions are as follows: evaluation and expression of one’s own emotions; evaluation and identification of the emotions of others; monitoring of one’s own emotions; and using emotional self-motivation. The scale was scored on a seven-point scale, where “1” stands for “strongly disagree.” Sample items include “when I’m in trouble, I can control my temper and solve problems rationally;” “I can control my emotions;” “when I am angry, I usually calm down in a very short time;” and “I have good control over my emotions.” The CFA results showed that the data are in accordance with the model of four factors and a higher-order factor (χ 2 /df = 2.67, RMSEA = 0.07, CFI = 0.97, NFI = 0.96).

Job Burnout

We used the most authoritative and most commonly used scale in the study of job burnout—the Maslach Burnout Inventory—General Survey ( Maslach et al., 1986 ). Li Zhaoping was authorized by Professor Michael Leiter, the developer of the questionnaire in 2002, to revise the Maslach Burnout Inventory—General Survey in the environment of China. The revised scale has good reliability and validity in China. The scale consists of three dimensions, namely, emotional exhaustion, work attitude, and sense of accomplishment. The seven-point Likert scale is used for evaluation in this study, where “zero” to “six” denote from “never” to “everyday.” Sample items include “I am confident that I can do all the work effectively;” “I’ve done much valuable work;” “I was very happy when I finished something on the job;” “in my opinion, I’m good at my job;” and “I feel like I’m making a useful contribution to the company.” The results of CFA showed that the data accord with the model of three factors and one higher-order factor (χ 2 /df = 4.63, RMSEA = 0.11, CFI = 0.93, NFI = 0.92, TLI = 0.92). According to previous studies, we take the weighted mean of the three dimensions as the final measurement of the variable.

Job Performance

We used the scale developed by Heilman et al. (1992) to measure employees’ performance. The scale mainly evaluates job performance through self-evaluation, including “generally speaking, very talented,” “overall, effective work” and “overall, excellent performance.” A five-point Likert scale was used for evaluation, where values from “1” to “5” range from “strongly inconsistent” to “strongly consistent.”

Controlled Variables

There are many empirical studies to explore the impact of demographic variables on psychological capital, job burnout, job performance, and EI. The empirical study of Gnilka and Novakovic (2017) . showed that women tend to score higher in tests of emotional skills than men, Salavera also explores the gender differences in self-efficacy and EI ( Salavera et al., 2017 ), FakhrEldin’s (2017) study on EI in innovation explores the influence of age differences. In addition, the difference in educational experience is also discussed as an influencing factor in an empirical study on employees’ EI and job satisfaction ( Huang et al., 2019 ). On this basis, this study controlled individual traits that might have an impact on employees’ psychological capital, job burnout, job performance, and EI, including their sex, age, and educational experience. In this study, except for sex, which is classified as a variable (“one” for male and “two” for female), the other two variables are continuous. Therefore, we take an exploratory approach to the three variables.

Data Analytic Strategy

In this study, SPSS16.0 and AMOS 23.0 software were used for data analysis. The statistical analysis items included the following: (1) descriptive statistics, correlation analysis, and diversity test of demographics and research variables; (2) reliability and validity of the questionnaire were tested by reliability analysis and CFA; and (3) the asymmetric confidence interval method (bootstrapping) was used to verify the relationship between EI, psychological capital, and job burnout/performance.

Internal Consistency Reliability Test Results of Each Questionnaire

Reliability mainly showed whether the measurement results have good internal consistency and stability, and the higher the consistency is, the better the reliability of the scale is. The reliability analysis results are shown in Table 1 . The Cronbach’s alpha reliability coefficient of each scale reached a good level above 0.8, and the reliability coefficient of each dimension of each scale exceeded 0.7, which indicates an acceptable level of reliability.

Table 1. Internal consistency reliability results of each questionnaire ( n = 347).

Confirmatory Factor Analysis Results of Each Research Variable

The theoretical framework of this study is based on previous theories, and the assumptions put forward are based on previous research conclusions. The research tools used in this study were revised according to previous studies; therefore, this study used AMOS23.0 to carry out the CFA of the scale. Because the job performance scale in this study has no subscales, in the CFA of this study, we do not yet analyze the research variables of job performance. Referring to the relevant research on the evaluation of structural equation model by Shook et al. (2004) the results are reported.

In this study, we used the χ 2 /df, RFI, TLI, NFI, IFI, CFI, RMSEA, and SRMSR indexes as model indicators, and the fitting criteria for determining each index are as follows: χ 2 /df ≤ 7; RFI, TLI, NFI, IFI, and CFI ≥ 0.80, where the closer the value is to 1, the better is the fit; RMSE ≤ 0.1, where the closer the value is to 0, the better is the fit; SRMSR ≦ 0.05, where the closer the value is to 0, the better is the fit.

As reported in Table 2 , the results are as follows: for the chi-square test of the psychological capital scale model, χ 2 /df = 2.97 < 4; for the chi-square test of the job burnout scale model, χ 2 /df = 2.49 < 5; and the χ 2 /df of the two-scale models is <6; therefore, the fitting degree of the model is good. For the chi-square test of the EIS model, χ 2 /df = 3.94 < 7, and the fitting degree is good. The TLI, NFI, IFI, and CFI index of the psychological capital scale model is above 0.8 (TCL = 0.838, RFI = 0.774, NFI = 0.815, IFI = 0.869, CFI = 0.867); RMSEA = 0.07 < 0.08, where it reaches the level of fair fitting, therefore the degree of fitting of the psychological capital scale model to the data. The TLI, IFI, CFI, and NFI indexes of the job burnout scale model were above 0.9 (TCL = 0.956, RFI = 0.928, NFI = 0.948, IFI = 0.968, CFI = 0.968), and RMSEA = 0.06 < 0.1, it reaches the level of fair fitting; thus, the job burnout scale model has a good degree of fitting to the data. Moreover, the TLI, NFI, IFI, CFI, and RFI indexes of the EIS model were all ∼0.9 (TCL = 0.911, RFI = 0.885, NFI = 0.917, IFI = 0.937, CFI = 0.936), and RMSEA = 0.09 < 0.1, which reached the mediocre fitting level; therefore, the EIS model fits the data well. In summary, the analysis concluded that the models of the three scales well fit the data, so the above three scales all have good validity.

Table 2. Confirmatory factor analysis results of the scale ( n = 347).

Confirmatory Test of Discriminant Validity of Variables

For the validation of test interpretation and the establishment of construct validity, discriminant validation is required ( Campbell and Fiske, 1959 ). In the formal sample survey, the discriminant validity of variables was tested by CFA. According to the method of Netemeyer et al., the items of EI job burnout and psychological capital were averaged to each dimension, and each dimension was regarded as the latent variable index, while the job performance was analyzed directly by item. According to the suggestions of Fornell and Larcker (1981) , we further used the average variance extracted (AVE) to test the discriminant validity of variables. The AVE of each dimension was above 0.36, in which EI (AVE = 0.54), job burnout (AVE = 0.74), and job performance (AVE = 0.73) reached a good level, and psychological capital (AVE = 0.46) was acceptable. Based on the results of CFA and the above analysis, it can be proved that the variables have good discriminant validity, so the next structural equation analysis can be carried out.

As shown in Table 3 , the four-factor model (model 11) (χ 2 /df = 2.31, CFI = 0.958, RMSEA = 0.061, TLI = 0.947, RFI = 0.910, SRMSR = 0.041) is better than other nested models and has a good matching index. This means that the four-factor model can better represent the measured factor structure in this study and verify the discriminant validity of the variables.

Table 3. Confirmatory factor analysis results of measurement model.

Descriptive Statistics and Correlation Analysis of the Research Variable

Descriptive statistics of each variable are shown in Table 4 . The correlation analysis showed that there is a significant positive correlation between psychological capital and EI, a significant negative correlation between psychological capital and job burnout, a significant positive correlation between psychological capital and job performance, a significant negative correlation between EI and job burnout, and a significant positive correlation between EI and job performance. The results of these analyses are consistent with the theoretical expectations.

Table 4. Descriptive statistics of main variables.

The Diversity Test of Scores of Each Scale and Demographic Variables

As mentioned above, we analyzed three demographic variables from an exploratory point of view. Through the one-way ANOVA and independent t test, the variables of each scale were tested for significant differences under different levels of demographic variables to explore the influence of each demographic variable, including gender differences, age differences, and differences in educational experience.

Gender Differences

Independent t test was made with sex as categorical variable and psychological capital, job burnout, job performance, and EI as dependent variables ( Table 5 ). The men’s scores in psychological capital, job performance, and EI were slightly higher than the women’s scores, and the men’s scores of job burnout were lower than the women’s scores, but the overall difference was not significant. Gender differences did not reach a significant level in all four variables.

Table 5. t test on gender of each scale.

Age Differences

A one-way ANOVA was made with the age difference as an independent variable and psychological capital, job burnout, job performance, and EI as dependent variables ( Table 6 ). There are significant differences in job burnout and job performance among different age groups; age difference is not significant for psychological capital and EI. The results showed that, at different ages, the social experience of employees gradually matures, and they become more skilled at work; in addition, repeated work will lead to burnout and boredom, so there will be a trend of rising and falling in both job burnout and job performance.

Table 6. One-way ANOVA analysis of all scales in age.

Educational Experience Difference

A one-way ANOVA with educational experience as an independent variable and psychological capital, job burnout, job performance, and EI as dependent variables ( Table 7 ) showed that job burnout ( F = 5.09, p < 0.01) and job performance ( F = 8.94, p < 0.001) have significant differences by educational experience; there is no significant difference between psychological capital and educational experience. Similarly, there is no significant difference between EI and educational experience.

Table 7. One-way ANOVA analysis of all scales in educational experience.

Research Hypothesis Test

To verify the theoretical hypothesis of this study, we used bias-corrected bootstrapping to examine the mediation effect. In the original data, we used the random sampling method to extract 2,000 bootstrap samples to produce approximate sampling distribution and used the 2.5% percentile and the 97.5% percentile to estimate the 95% CI of the intermediary effect. The confidence interval of the total effect does not include 0, which indicates that the mediation effect is statistically meaningful. First, we examined the role of psychological capital, which played a mediating role in the relationship between EI and job burnout ( Table 8 ). The results showed that the confidence interval of the indirect effect is −0.133 to −0.004, which showed that a mediating role exists. The confidence interval of the direct effect is −0.182 to 0.025, which showed that psychological capital has a complete mediating role between EI and job burnout ( Figure 1 ).

Table 8. Test the mediating effect of psychological capital in the influence of emotional intelligence on job burnout.

Figure 1. Schematic diagram of the mediating effect of psychological capital in the influence of emotional intelligence on job burnout.

Second, we examined the role of psychological capital, which played a mediating role in the relationship between EI and job performance ( Table 9 ). The results showed that the confidence interval of the indirect effect is −0.133 to −0.004, which showed that a mediating role exists. The confidence interval of the direct effect is −0.182 to 0.025, which showed that psychological capital is a complete mediating role between EI and job burnout ( Figure 2 ).

Table 9. Test the mediating effect of psychological capital in the influence of emotional intelligence on job performance.

Figure 2. Schematic diagram of the mediating effect of psychological capital in the influence of emotional intelligence on job performance.

In this study, we use two frameworks shown in Figures 1 , 2 to present the relationship between EI and job burnout/performance and find that psychological capital plays a mediating role in the relationship between EI and job burnout/performance. Most of previous studies focus on simple effect of EI on job performance ( Wen et al., 2019 ), without in-depth research on mechanism behind it; therefore, this study is necessary for further exploration.

Findings and Theoretical Contributions

First, the results of this study show that employees’ EI plays a significant positive role in predicting their job performance. In other words, in enterprises or organizations, the higher the level of EI employees have, the better they perform. It can also be speculated that employees with higher levels of EI will perform better than those with lower levels of it. Employees with high level of EI perform well and have higher satisfaction with their jobs; what is more, they also build a good social support system for their partner ( Miao et al., 2017 ). Thus, EI plays an important role in improving enterprises’ competitive advantage. In addition, this study supports previous studies, emphasizing the correlation between EI and job burnout ( Schoeps et al., 2019 ) and confirming that the higher employees’ EI level, the better their job performance and the lower the EI of employees, the higher their job burnout. It implies that employees’ EI levels negatively predict job burnout. The results can provide a breakthrough point for managers of enterprises or organizations to reduce employees’ job burnout. They can use different emotions to produce the best way to solve daily problems and offset dissatisfaction in work ( Nǎstasǎ and Fǎrcaş, 2015 ). As the results prove, efforts to improve employees’ EI level will effectively slow down or eliminate employees’ job burnout. A more important finding in the results is that, adopting the role of a mediation, psychological capital can provide a theoretical basis for enterprises or organizations to improve employees’ job performance and reduce their job burnout. In fact, the experience of achievement at work will improve the psychological capital level of employees ( Madrid et al., 2018 ). Therefore, in daily management, enterprises or organizations should pay attention to not only the job performance of employees but also the development of their psychological capital to achieve common progress of management and performance.

In sum, this study discusses the influence of EI by introducing the concept of psychological capital. It is of great innovative value to this study of organizational behavior and the construction of a healthy organization. In addition, in recent years, EI has become the leading area of academic research. In the field of business, it has also become an important part. Therefore, EI occupies the position of hot research field in the world.

Building on previous studies, this study expands the relevant theories and adds strength to the development of EI theory. The level of EI affects the ability of employees to express their personal feelings and communicate with others ( Siahaan, 2018 ), and it will affect their handling of emotions with customer, which is related to not only the work attitude of employees but also job performance to a certain extent.

Limitations and Future Directions

There are still some limitations to this study. First, the research variable of job performance is measured by employees’ self-report; this may entail the influence of some social expectations and tendencies in employees’ evaluation of their behavior ( Podsakoff et al., 2012 ). However, self-report may lack objectivity, which does not conform to the real situation of employees, so there may be some deviation in the overall research. Therefore, future researchers can use the combination of self-evaluation and other evaluation to increase the objectivity of the results. Second, for sampling convenience, the samples of this study are from various enterprises or organizations in certain areas of China, which limits the generalization of the results of this study. Whether the results can be applied to other regions or industries with other cultural backgrounds needs to be further tested. To overstep this limitation of this study, future research can expand the scope of research, repeat research in different cultural areas, and can be used as a comparative study to explore the differences between the cultural background of the East and the West.

Practical Implications

Based on these findings, we put forward some practical suggestions on the recruitment of employees and the improvement of organizational performance. First of all, when interviewing, interviewers should pay attention to the personal quality of applicants. HR managers should look for applicants who have positive attitude and genuine care ( Choi et al., 2019 ). As for measurement method, the EIS developed by Wong and Law (2002) can be used to measure the EI of applicants in recruitment. Second, introduce regular training programs (e.g., PsyCap short training interventions) to improve employees’ EI and psychological capital ( Avey et al., 2009 ). Third, in addition to improving the overall EI and psychological capital level of employees, the prevention of job burnout is also an important part. Enterprises need to carefully consider workload and work hours of staff and draw up appropriate work plans, which lead to well job performance and less job burnout.

Conclusively, enterprises can improve their organizational performance and development by improving the EI and psychological capital of their employees. The results of this study can be applied not only to enterprises but also to other organizations, such as schools or hospitals. Thus, this study can also provide a relevant theoretical basis for the development of multilevel and multifaceted organizations and groups.

This study explores the role of psychological capital, which played a mediating role in the relationship between EI and job performance/burnout. The results showed that (1) EI is negatively correlated with job burnout, (2) EI has a significant positive correlation with job performance, (3) EI has a significant positive correlation with psychological capital, (4) psychological capital has a significant negative correlation with job burnout, (5) psychological capital has a significant positive correlation with job performance, (6) psychological capital played a mediating role in the relationship between EI and job burnout, and (7) psychological capital played a mediating role in the relationship between EI and job performance.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher.

Ethics Statement

The studies involving human participants were reviewed and approved by the Institutional Review Board, Normal College, Qingdao University. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

ZG and YC designed, performed, and analyzed the research. ZG, YC, and YW wrote the manuscript. YW critically reviewed and edited the manuscript.

This work was supported by grants from the National Social Science Fund of China under Grant No. 14CGL073 awarded to ZG.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords : psychological capital, emotional intelligence, job performance, job burnout, intermediary effect

Citation: Gong Z, Chen Y and Wang Y (2019) The Influence of Emotional Intelligence on Job Burnout and Job Performance: Mediating Effect of Psychological Capital. Front. Psychol. 10:2707. doi: 10.3389/fpsyg.2019.02707

Received: 31 July 2019; Accepted: 15 November 2019; Published: 10 December 2019.

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*Correspondence: Yayu Wang, cHN5d2FuZ3lheXVAMTYzLmNvbQ==

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