Emotional intelligence on job performance: A study on Malaysian employees

Abstract

BACKGROUND:

The COVID-19 pandemic has affected the emotional intelligence of employees through the negative effects on their mental health, and led to poor workplace performance.

OBJECTIVE:

The purpose of this research is to examine the level of EI of Malaysian employees in various sectors affecting their job performance through the mediating influence of psychological capital by using the Schutte Self-Report Emotional Test (SSEIT), 24-item Psychological Capital Questionnaire (PCQ-24) and Role-Based Performance Scale (RBPS) theories.

METHOD:

A quantitative study was conducted. 350 sets of questionnaires were given out to Malaysian employees, of which 311 were returned. Data were analysed through regression analysis.

RESULTS:

The results showed that all emotional intelligence subscales, except for utilising emotions, have a significant relationship with job performance through the effect of psychological capital.

CONCLUSION:

This study offers valuable and insightful implications by combining the SSEIT, PCQ-24, and RBPS models to investigate the effect of emotional intelligence on job performance in Malaysia, which is an unusual combination model to analyse employees’ job performance. It helps Malaysian companies, managers, employers, and other related parties to recognise the processes and elements that influence employees’ work performance. This research also successfully developed an extended SSEIT model together with PCQ-24 and RBPS and verified their applicability on workplace performance.

Keywords

Psychological distress emotional disturbance employee performance emotional aspects

1 Introduction

The coronavirus 2019 (COVID-19) pandemic made enterprises unable to support themselves. The pandemic contributed to the intensification of people’s tight pace of work and life, resulting in people’s emotional and psychological stress and affecting their performance in the workplace [1]. The COVID-19 pandemic has caused ASEAN countries to suffer from low GDP development and a high unemployment rate by bringing negative effects on the employee’s mental health, most notably [2]: absenteeism, resignation, increased relational clashes, and difficulty with shared participation; decreased eagerness, inventiveness, effectiveness and execution of work; and increased executive costs in human asset [3]. In addition, employees nowadays often fail to realise their level of emotional intelligence (EI) and this may lead them to irreparable consequences, such as miss out on career promotion opportunities, as leaders are not willing to have an emotionally unstable subordinate under their guidance. It may also jeopardize their career prospects and the company’s future development due to their inability to manage negative emotions. Consequently, it may lead them to engage in inappropriate behaviour that is detrimental to the organization and many others.

2 Problem statement

The COVID-19 pandemic has turned employees down, resulting them to have a hard time processing and maintaining their emotions or to stay positive; to improve their mind-set and conducts at work [4]. EI and intelligence quotient (IQ) have complementary effects on each other [5]. However, society has undervalued the importance of EI without noticing that EI is the primary factor that influences employees’ high-quality performances in organizations.

3 Research questions

The general research question of this study is: What are the factors of EI that affect employees’ job performance (JP) through their psychological capital (PsyCap)? The specific research questions are:

What is the relationship between Malaysian employees’ EP and PsyCap?

What is the relationship between Malaysian employees’ ability of UE and PsyCap?

What is the relationship between Malaysian employees’ ability of MSE and PsyCap?

What is the relationship between Malaysian employees’ SS and PsyCap?

What is the relationship between Malaysian employees’ ability of MOE and PsyCap?

What is the relationship between Malaysian employees’ PsyCap and their JP?

4 Research objectives

EI is the ability to recognise, manage emotions and communicate feelings, absorb feelings in ideas, comprehend and reason with feelings, and manage feelings in oneself and others [6]. Based on the research questions, the general aim of this study is to understand the factors of EI that affect employees’ JP through their PsyCap. The specific aims of carrying out this study are:

To investigate the association between Malaysian employees’ EP and PsyCap.

To examine the connection between Malaysian employees’ ability of UE and PsyCap.

To find the association between Malaysian employees’ ability of MSE and PsyCap.

To explore the relationship between Malaysian employees’ SS and PsyCap.

To assess the relationship between Malaysian employees’ ability of MOE and PsyCap.

To decide the association between Malaysian employees’ PsyCap and their JP.

5 Literature review

5.1 Theoretical support: SSEIT, PCQ-24, RBPS models

The Schutte Self-Report Emotional Test (SSEIT) was established by Schutte et al. [7] to test on EI sub-scales to predict an employee’s JP overall composite scale. Empirical studies demonstrate that the SSEIT model provides a dependable and effective trait EI assessment. It has strong internal and test-retest reliabilities, and cluster differences in score and associations with other measures are consistent with theoretical expectations [8, 9]. The SSEIT model is a better version of many traditional metrics [10]. So, SSEIT looks to be a valid theory and a model that can be employed to assess global trait EI in a shorttime.

PsyCap is a theory which emphasises on raising a person to his/her full potential with the aim of increasing the performance and welfare in organisations [11]. The 24-item Psychological Capital Questionnaire (PCQ-24) was established by Luthans et al. [12] to measure human’s level of PsyCap, which has become the most extensively used self-report measure. PCQ-24 was adopted in this study due to its reliability as its validity has been examined by numerous researchers across different countries, such as Cid et al. [13], Lupşa and Vîrgă [14], and Sapyaprapa [15].

Role-Based Performance Scale (RBPS) ratings was employed to observe employees’ behaviour that is related to the organisation’s goal [16]. This model was used to supplement the findings from the SSEIT measurements from respondents to determine whether EI sub-scales have significant association with their overall JP.

SSEIT, PCQ-24, and RBPS were adopted in this research to evaluate the impacts of employees’ level of EI on their respective JP. PsyCap is also combined into the theoretical model to propose a clear understanding of the process of EI’s impact on each employee’s working performance.

5.2 Relationship between emotional perception (EP) and PsyCap

EP includes four distinct characteristics, which are affective, a component of their overall impressions; motivation that motivates people to act in certain ways; a presentation that leads humans to learn about the emotional components of perception through experience; and relational, a recognition of how people emotionally react to an object [17]. Fulkerson believes that employees with the ability to perceive emotions are more likely to avoid conflicts or negative situations, which explains their behaviour of developing positive psychological competencies. Therefore, employees with the ability to perceive emotions are proposed to have better PsyCap in the workplace.

H1. Emotional perception has a significant impact on Malaysian employees’ psychological capital.

5.3 Relationship between utilising emotions (UE) and PsyCap

Using emotions indicates the capability of a person to access and/or generate feelings while also promoting thoughts [18]. Employees that are good at using emotions in thinking and reasoning are less likely to suffer emotional exhaustion that may bring a minor level of life satisfaction and low quality of JP [19]. This can be interpreted as employees with a high ability to utilise their emotions properly are likely to obtain motivation to succeed and have confidence to overcome difficult challenges. Therefore, the ability to utilise emotions is proposed to have a significant impact on employees’ PsyCap, which influences their working performance respectively [18, 20].

H2. Utilising emotions has a significant impact on Malaysian employees’ psychological capital.

5.4 Relationship between managing self-relevant rmotions (MSE) and PsyCap

People’s reactions to their own emotions at work could affect their performance [21]. Such self-focused emotional skills are significant for caring professionals since they can help employees’ well-being by reducing their job stress [22]. Consequently, the literature has recommended various strategies such as directly regulating their own emotions and mobilising one’s social job resources which are the possible approaches that can help professionals to manage their own emotions effectively and improve their work-home balance [23]. The capability to control and cope up one’s self-emotions can significantly affect his/her behaviour through the effect of self-efficacy, resilience, and others that determines his/her performance at the workplace.

H3. Managing self-relevant emotions has a significant impact on Malaysian employees’ psychological capital.

5.5 Relationship between social skills (SS) and PsyCap

SS consist of six main characteristics, which are goal-directed, socially skilled behaviours, the person’s behaviour can be broken down into discrete pieces, behaviours that can be learned by imitating, social abilities, and an individual’s cognitive control to learn when and how to apply certain social behaviours [24]. So, people with SS can build relationships and do things well that maintain friendships with people in their surroundings [25]. A socially skilled person that has a good relationship with others is more likely to have no issues in communicating and solving issues with others [26]. Therefore, socially skilled person may be easier to get jobs and get promoted in their workplace due to their enrichment in social abilities [27].

H4. Social skills have a significant impact on Malaysian employees’ psychological capital.

5.6 Relationship between managing others’ emotions (MOE) and PsyCap

MOE started with an individual’s awareness of others’ emotions [21]. Recognising others’ emotions led to the organisation of emotions, and adds to human’s active learning [28]. Responding to others’ emotions has a significant contribution to the interaction with others or the helpfulness of patient treatment [29]. Trainees will most likely learn and communicate with their patients in a better way for their treatment skills development when they are more experience in managing patients’ emotions. Such process is a part of active learning that enhances one’s behaviour and performance through dealing with others in a good manner that reduce errors in the workplace [30].

H5. Managing others’ emotions has a significant impact on Malaysian employees’ psychological capital.

5.7 Relationship between PsyCap and JP

EI has a considerable relationship with PsyCap [31]. EI can lead to stronger psychological resources and have a major impact on employees’ proactive attitudes toward change in the workplace [32]; and PsyCap has significant mediating and moderating effects of emotional labour methods on job burnout, which can impact the JP of an employee [33]. Therefore, PsyCap played an important role in predicting subjective well-being and employee’s career commitment, which could affect JP.

H6. Psychological capital has a significant impact on Malaysian employees’ job performance.

The research framework of this research is given in Fig. 1.

Fig. 1

Proposed research framework. Adopted from Schutte et al.’s [7] SSEIT, Luthans et al.’s [12] PCQ-24 and Welbourne et al.’s [16] RBPS model.

6 Research methodology

6.1 Data collection

Primary data was collected using a self-report questionnaire that was adapted from the SSEIT and PCQ-24, and data about the employees’ performance at work was adapted from the RBPS.

6.2 Population

The population of this study is the total number of employees in Malaysia. According to official Malaysian government data, Malaysia’s total workforce is expected to reach 16.07 million in 2021 [34]. From this group, a sample of several hundred people who are currently employed in any sector was selected.

6.3 Sampling frame

This study does not have a sampling frame as all Malaysian citizens’ details are kept private, and it is difficult to gather information on every employee in Malaysia. According to the Department of Statistics Malaysia, 2021, Malaysia’s total workforce of 16.07 million demonstrated the labour force participation rate is reaching 68.3% of the total working-age population (age range: 15 to 64 years). Hence, the sampling locations are selected based on the percentage of the workforce in each Malaysian State.

6.4 Sampling technique

As a sampling frame was not accessible for this research, non-probability sampling is used. Judgmental sampling is used for three reasons: respondents can provide the rationale researchers need to establish broad generalisations from the facts they are analysing, whether those generalisations are theoretical, analytic, or logical; it provides the researchers access to a varied range of non-probability sampling strategies and allows researchers to directly collect data from the respondents, extract data information to summarise the significant implications of their findings for the general public[35].

Self-administration questionnaires were sent out via email and social media platform for data collection. By doing so, researchers can get quick and immediate responses, however, these tools are frequently misinterpreted for junk mail [36]. Only employees with Malaysian citizenship were chosen as this study’s respondents since they are from the most important contributors to organisational success; and are more involved in JP, which fitted this study’s purpose.

6.5 Sampling size

The sample size for the data analyses is four to ten times the number of items in the questionnaire [37]. The questionnaire in this study contains 32 items and therefore, a sample size of 128 to 320 respondents is regarded sufficient and appropriate for data analysis. Three hundred instances in a sample are a decent number [38]. Thus, a sample size between 300–320 is considered appropriate for this study.

6.6 Research instrument

A self-report questionnaire which includes four sections has been used to gather data as it is easier to collect information from a huge number of people in a short period [39]. Section A has the respondent’s demographic profile, Section B the items for the five independent variables, Section C the items in the mediating variable, and Section D the items in the dependent variable.

6.7 Pilot test

It is common to do a pilot test with a sample size of 10 to 20 percent of the final sample size [40]. The pilot study in this study had 31 participants. As a general rule, Cronbach’s Alpha values between 0.6 and 0.7 are moderate but acceptable. Cronbach’s Alpha values of 0.8 or greater are considered excellent, but values higher than 0.95 might be an indication of redundancy [41]. A Cronbach Alpha score of larger than 0.6 is regarded as excellent dependability and an acceptable index [42]. On the contrary, Cronbach’s Alpha less than 0.6 is regarded as low [43]. Table 1 shows the outcome of the pilot test. The Cronbach Alpha of all the variables is adequate as the values are all higher than 0.6 [44, 45].

Table 1
Reliability statistics of the pilot test

Variables Cronbach’s Alpha Number of items

Emotional perception 0.731 4

Utilising emotions 0.725 4

Managing self-relevant emotions 0.803 5

Social skills 0.682 4

Managing others’ emotions 0.837 4

Psychological capital 0.890 6

Job performance 0.893 5

Variables	Cronbach’s Alpha	Number of items
Emotional perception	0.731	4
Utilising emotions	0.725	4
Managing self-relevant emotions	0.803	5
Social skills	0.682	4
Managing others’ emotions	0.837	4
Psychological capital	0.890	6
Job performance	0.893	5

7 Results and discussion

7.1 Demographic profile of respondents

350 survey questionnaires were disseminated and 311 replies were received and used. The 311 respondents included 140 males (45%) and 171 females (55%). The majority of the respondents were working in other sectors (43.4%) that were not studied in this study, followed by retail service (13.8%), education (11.9%), advertising and marketing (9.6%), banking and finance (7.7%), manufacturing (7.1%), health care (4.5%), and accounting and audit (1.9%). Most respondents (49.5%) worked for less than a year, followed by 1 to 2 years (21.2%), 7 years or above (15.4%), 3 to 4 years (9%), and 5 to 6 years (4.8%).

7.2 Reliability test of full data

The outcome of the reliability test of the full data is shown in Table 2 which depicts that the Cronbach’s Alpha for all variables is more than 0.6; therefore, the questionnaire’s questions are dependable ad internally valid [44, 45].

Table 2
Reliability statistics of full data

Variables Cronbach’s Alpha Number of items

Emotional perception 0.751 4

Utilising emotions 0.736 4

Managing self-relevant emotions 0.814 5

Social skills 0.659 4

Managing others’ emotions 0.792 4

Psychological capital 0.878 6

Job performance 0.899 5

Variables	Cronbach’s Alpha	Number of items
Emotional perception	0.751	4
Utilising emotions	0.736	4
Managing self-relevant emotions	0.814	5
Social skills	0.659	4
Managing others’ emotions	0.792	4
Psychological capital	0.878	6
Job performance	0.899	5

7.3 Normality test

Then, a normality test was conducted, and it has been noticed that since all the skewness and kurtosis values fell within the suggested values of ±3 and ±10 respectively, all the constructs are considered normally distributed [46].

7.4 Pearson’s correlation coefficient analysis

From Table 3, it can be seen that the correlation among the variables was less than 0.9; thus there is no multicollinearity problem among the variables [44].

Table 3
Pearson’s correlation coefficients

EP UE MSE SS MOE PsyCap JP

Emotional perception (EP) 1 0.514^ 0.432^ 0.416^ 0.454^ 0.445^ 0.485^

0.000 0.000 0.000 0.000 0.000 0.000

Utilising emotions (UE) 1 0.512^ 0.361^ 0.496^ 0.415^ 0.480^

0.000 0.000 0.000 0.000 0.000

Managing self-relevant emotions (MSE) 1 0.483^ 0.517^ 0.544^ 0.451^

0.000 0.000 0.000 0.000

Social skills (SS) 1 0.499^ 0.447^ 0.442^

0.000 0.000 0.000

Managing others’ emotions (MOE) 1 0.525^ 0.473^

0.000 0.000

Psychological capital (PsyCap) 1 0.623^**

0.000

Job performance (JP) 1

	EP	UE	MSE	SS	MOE	PsyCap	JP
Emotional perception (EP)	1	0.514^**	0.432^**	0.416^**	0.454^**	0.445^**	0.485^**
		0.000	0.000	0.000	0.000	0.000	0.000
Utilising emotions (UE)		1	0.512^**	0.361^**	0.496^**	0.415^**	0.480^**
			0.000	0.000	0.000	0.000	0.000
Managing self-relevant emotions (MSE)			1	0.483^**	0.517^**	0.544^**	0.451^**
				0.000	0.000	0.000	0.000
Social skills (SS)				1	0.499^**	0.447^**	0.442^**
					0.000	0.000	0.000
Managing others’ emotions (MOE)					1	0.525^**	0.473^**
						0.000	0.000
Psychological capital (PsyCap)						1	0.623^**
							0.000
Job performance (JP)							1

7.5 Inferential analysis

This is divided into two parts. The first part is a multiple linear regression which observes the relationship between the independent variables (EP, UE, MSE, SS, and MOE) and the mediating variable (PsyCap), in which PsyCap has been deliberated as the dependent variable. The second part is a simple linear regression which observes the relationship between mediating variable (PsyCap) and dependent variable (JP), in which PsyCap has been deliberated the independent variable.

7.6 Multiple linear regression (MLR)

Table 4 shows the R² value of 0.411 which conveys that 41.1% of the variation in the PsyCap can be described by EP, UE, MSE, SS, and MOE, and the balance 58.9% is explained by other factors which are not deliberated in this study.

Table 4
Model summary^b

Model R R² Adjusted R² Standard error of estimate R² change Change statistics

F changes df1 df2 Sig. F change

1 0.641^a 0.411 0.401 0.72696 0.411 42.564 5 305 0.000

Model	R	R²	Adjusted R²	Standard error of estimate	R² change	Change statistics
1	0.641^a	0.411	0.401	0.72696	0.411	42.564	5	305	0.000

a. Predictors: (Constant), EP, UE, MSE, SS, MOE; b. Dependent variable: PsyCap.

Table 5 shows the F-value of 42.564, which is significant as the p-value is less than 0.05. EP, UE, MSE, SS, and MOE, therefore, have a substantial relationship with PsyCap, with a good model fit.

Table 5

ANOVA^a

Model		Sum of squared	df	Mean square	F	Sig. (p-value)
1	Regression	112.469	5	22.494	42.564	0.000^b
	Residual	161.185	305	0.528
	Total	273.654	310

a. Dependent variable: PsyCap; b. Predictors: (Constant), EP, UE, MSE, SS, MOE.

Table 6 shows that EP, MSE, SS, and MOE have a p-value lower than 0.05. These four variables have a substantial and positive impact on the mediating variable (PsyCap). H1, H3, H4, and H5 are supported. However, UE (p = 0.557) is found to be insignificantly associated with PsyCap as its p-value is more than 0.05. Thus, H2 is not statistically supported.

Table 6

Multiple linear regression coefficients^a

Model		Unstandardised B	Coefficients standard error	Std. coefficients beta	t	Sig. (p-value)	Collinearity statistics
							Tolerance	VIF
1	(Constant)	–0.375	0.319	–	–1.174	0.241	–	–
	EP	0.233	0.085	0.150	2.745	0.006	0.648	1.542
	UE	0.047	0.081	0.033	0.588	0.557	0.599	1.669
	MSE	0.400	0.080	0.284	4.981	0.000	0.593	1.687
	SS	0.161	0.073	0.119	2.197	0.029	0.659	1.517
	MOE	0.333	0.082	0.234	4.069	0.000	0.586	1.707

a. Dependent variable: PsyCap.

Consequently, the MLR equation is expressed as below:

PsyCap = –0.375 + 0.233EP + 0.047UE + 0.4MSE + 0.161SS+ 0.333MOE.

7.7 Simple linear regression (SLR)

Table 7 shows the R² value of 0.389 which describes that 38.9% of the variation in the JP can be described by PsyCap, and the balance 61.1% is described by other factors which are not considered in this study.

Table 7
Model summary^b

Model R R² Adjusted R² Standard error of estimate R² change Change statistics

F changes df1 df2 Sig. F change

1 0.623^a 0.389 0.387 0.67046 0.389 196.504 1 309 0.000

Model	R	R²	Adjusted R²	Standard error of estimate	R² change	Change statistics
1	0.623^a	0.389	0.387	0.67046	0.389	196.504	1	309	0.000

a. Predictors: (Constant), PsyCap; b. Dependent variable: JP.

Table 8 depicts the F-value of 196.504, which is significant as the p-value is less than 0.05. PsyCap, therefore, has a substantial relationship with JP, with a good model fit.

Table 8

ANOVA^a

Model		Sum of squared	df	Mean square	F	Sig. (p-value)
1	Regression	88.332	1	88.332	196.504	0.000^b
	Residual	138.902	309	0.450
	Total	227.234	310

a. Dependent variable: JP; b. Predictors: (Constant), PsyCap.

Table 9 indicates that PsyCap has a p-value lower than 0.05. PsyCap has a substantial and positive impact on the dependent variable (JP), as shown by this. Thus, H6 is supported. Therefore, the SLR equation is expressed as below:

Table 9

Simple linear regression coefficients^a

Model	Unstandardised B	Coefficients standard error	Std. coefficients beta	t	Sig. (p-value)	Collinearity statistics
							Tolerance	VIF
1	(Constant)	1.154	0.168	–	6.851	0.000	–	–
	PsyCap	0.568	0.041	0.623	14.018	0.000	1.000	1.000

a. Dependent variable: JP.

JP = 1.154 + 0.568PsyCap.

Table 10 shows the summary of the hypotheses testing.

Table 10

Summary of hypotheses testing

Hypotheses	Linear regression		Result
	p-value	β
H1: Emotional perception has a significant impact on Malaysian employees’ psychological capital.	0.006	0.233	Significant
H2: Utilising emotions has a significant impact on Malaysian employees’ psychological capital.	0.557	0.047	Not Significant
H3: Managing self-relevant emotions has a significant impact on Malaysian employees’ psychological capital.	0.000	0.400	Significant
H4: Social skills have a significant impact on Malaysian Employees’ psychological capital.	0.029	0.161	Significant
H5: Managing others’ emotions has a significant impact on Malaysian employees’ psychological capital.	0.000	0.333	Significant
H6: Psychological capital has a significant impact on Malaysian employees’ job performance.	0.000	0.568	Significant

8 Discussion

The outcomes demonstrate that EP has a significant impact on Malaysian employees’ PsyCap (p < 0.05). This result shows that emotion does have an impact on peoples’ thoughts, actions, and their behaviour in making decision and processing information [47, 48], which confirms that persons who can properly understand their emotions can avoid job burnout [33].

The results also show that utilising emotions has no significant impact on Malaysian employees’ PsyCap (p > 0.05). Possible reasons for this insignificant result could be that the respondents could not fully understand the revised questionnaire’s construct and its related items, or could not tell them apart, and thus could not manage or facilitate their emotions without a proper understanding of the emotion they were experiencing [49]. Respondents’ preferences, talents, and a predisposition to exaggerate or underestimate their actual ability to use their emotions could all be factors that contributed to the EI construct yielding a non-significant result [50]. Besides, in Western culture, the EI notion was created, tested, and validated. When the same thing is done in another culture, it is worth considering the cultural differences in terms of vocabulary, experience, and ethos[51 –53].

It can be seen that MOE has a significant impact on Malaysian employees’ PsyCap (p < 0.05). So, employees with a high ability to manage their self-emotions will have a high level of self-efficacy that enables employees to confront stressful situations and resilience, by controlling their own emotions when performing their job due to individuals that focus on their emotional skills and control their own emotions properly are able to gain confidence in mobilising their motivation, and courses of actions to achieve high levels of performance [54, 55].

This result was also supported by another study which concluded that psychological support included emotional, stress coping, counselling, and knowledge [56].

The results show that SS got a substantial impact on Malaysian employees’ PsyCap (p < 0.05). This result suggests that, by expressing both good and negative thoughts in an inter-personal context without losing social reinforcement, employees can improve their hope and optimism. Therefore, individuals’ level of PsyCap is influenced by their SS [57].

MOE has a significant impact on Malaysian employees’ PsyCap (p < 0.05). It is confirmed that emotionally knowledgeable individuals can regulate not only their own emotions, but also the sentiments of others, are psychologically stable [58, 59]. So, employees’ ability to manage others’ emotions has an impact on their PsyCap when they work well with others, which improves their self-efficacy, level of optimism, hope, and resiliency in the workplace, allowing them to perform well at work.

PsyCap was found to have a substantial impact on Malaysian employees’ JP (p < 0.05). PsyCap has a direct impact on worker behaviour because it is a collection of positive psychological capacities, such as self-efficacy, that are significant in the learning process [60, 61]; optimism, which is a personality attribute that influences one’s mood and behaviour [62]; hope, in which individuals might use hope to defend themselves from feelings of weakness and incapacity to manage their emotions [63]; resilience, which allows workers to keep working as they have a lot of flexibility that enables them to rarely lose their jobs when experiencing big setbacks [64]. These four dimensions that make up PsyCap proved that PsyCap promotes worker behaviours and strengthen the workforce [65]. It has also been found that PsyCap has significant mediating and moderating effects of emotional labour methods on job burnout, which can impact an employee’s JP [66]. Also, the findings by another researcher showed that PsyCap has positive relationships with job satisfaction and JP [67]. Another study established that PsyCap provided significant personal resources to help employees cope with demanding career-related activities; while employees engaged in career advancement activities, they also improved their performance [68].

9 Comparison with other related studies

This study demonstrated a significant relationship between EP and Malaysian employees’ PsyCap. This outcome confirmed the findings of other researchers [33 , 48]. This study showed an insignificant relationship between Utilising Emotion and PsyCap, which is contrary to the findings of the studies by [51 –53]. The reason could be the cultural differences between Western culture and Asian culture. Again, this study demonstrated a significant relationship between Managing Self-relevant Emotion and Malaysian employees’ PsyCap. This outcome is in line with the findings of the studies by [54, 55]. Similarly, SS and MOE have an impact on the PsyCap; these results are similar to the findings of the studies by [57 –59]. Finally, PsyCap was found to have a substantive impact on JP, which has also been confirmed by previous studies [60 –65].

10 Theoretical significance

This study is important academically as it researches and analyses Malaysian employees’ EI and JP in the workplace. The SSEIT was used to investigate employees’ EI levels, but the factors in the SSEIT were unable to provide a clear knowledge of how EI affects employees’ JP. As a result, PsyCap was introduced as an extra mediating variable in this study to conduct the entire process of EI affecting work performance because it is regarded to be the primary driver of employees’ ability to execute well behaviours in a company. This further explained the entire process, this study provided a more complete understanding of the process of EI affecting employees’ working behaviour.

11 Practical significance

Nowadays, organisations are increasingly paying close attention to their employees’ EI and their capacity to cope with stress, emotional weariness, and other issues while on the job. This study’s findings are critical because the proposed scale might be utilised for recruiting, career counselling, and the evolution of the individual [69, 70]. Employers looking for employees who can identify, adjust, and manage their mentality, form appropriate relationships with others in the organisation, and conduct themselves in a way that allows them to perform well at work may find this study useful. Moreover, this study helps firms determine which SSEIT variables are the underlying determinant that can boost JP among Malaysian employees working in a variety of fields, as these EI factors are important in influencing their psychological state and way of thinking as well as interpreting in the workplace.

12 Limitations of the study

EI was first tested in this study utilising a self-report questionnaire. Self-report assessments have the disadvantage that self-report bias may have masked the study’s findings because survey replies may not necessarily represent respondents’ real behaviour. People tend to react to circumstances on the spur of the moment, with few choices which may lead to inaccurate reaction during the assessment [71, 72]. Secondly, the SSEIT scale may not be appropriate for usage in those who opt to project a socially desirable image. Answers to SSEIT questions may appear more socially desirable to respondents who regard themselves to be socially acceptable [7]. It may be difficult to determine this quality in individuals recruited from one’s research population.

Respondents between the ages of 18 and 30 made up the largest percentage of those who completed the questionnaires, followed by those between the ages of 40 to 49, 31 to 39, 50 to 59, and over 60. Due to the age imbalance, there will be differences in their thinking and perception about their level of EI and PsyCap when performing in the workplace.

13 Recommendations for future research

Forthcoming studies are suggested to utilise longitudinal study approach as it allows for long-term analysis of changes in target respondents [73]. Future researchers may look into whether employees’ EI levels differ before and after they begin their research. Furthermore, forthcoming research should pay attention to qualitatively investigating the concept of EI, as studies have shown that EI is difficult to measure quantitatively [74]. Exploring EI, PsyCap, and JP from a new perspective may benefit the area of research on EI. Besides, future academics are encouraged to do comparative studies on the subject that include other Southeast Asian countries that have similar cultural roots in Malaysia. Researchers could incorporate factors from the PCQ-24 model into their research models, and combine them with other constructs through different models to further verify the individual qualities of different respondents.

Finally, since the questionnaire was not distributed in the respondents’ native languages, future SSEIT studies in Malaysia should consider translating the instrument into Malay, Chinese, and Tamil versions all at the same time to enable respondents of all ages can fully understand and participate in the survey. Furthermore, future studies should focus on gathering data from Malaysian employees over 40 years old to observe and gain a better understanding of the part of EI in the JP of employees of all ages.

14 Conclusion

This study provides researchers, managers, human resource administrators, employers, and organisations with a deep understanding of Malaysian employees’ EI and PsyCap in affecting their JP in various industries. In conclusion, the modified SSEIT, PCQ-24, and RBPS can be considered a fit model in this study, and are capable of predicting employees’ EI, PsyCap, and JP from different cultural backgrounds in the workplace in Malaysia. The objective of this study is to find out the relationship between EP, UE, MSE and SS with PsyCap and to examine the relationship between PsyCap and JP. Accordingly, all aims were achieved with significant relationships as hypothesised, except for Utilising Emotions, due to difference between Western and Asian cultures.

Ethics statement

The participants were clearly informed that their involvement in the study is voluntary. This research was approved by the Thesis committee of Xiamen University Malaysia (IBU1904097/Sep 2021).

Footnotes

Acknowledgments

The authors would like to thank all respondents for their responses.

Funding

No funding was obtained from any source for this study.

Conflict of interest

None to report.

References

, Park

, Hyun

. Impacts of the COVID-19 pandemic on employees’ work stress, well-being, mental health, organisational citizenship behaviour, and employee-customer identification. Journal of Hospitality Marketing & Management. 2021;30(5):529–48.

Chong

TTL

, Li

, Yip

. The impact of COVID-19 on ASEAN. Economic and Political Studies. 2021;9(2):166–85.

Ruiz-Aranda

, Castillo

, Salguero

, Cabello

, Fernández-Berrocal

, Balluerka

. Short- and midterm effects of emotional intelligence training on adolescent mental health. Journal of Adolescent Health. 2012;51(5):462–67.

Kniffin

, Narayanan

, Anseel

, Antonakis

, Ashford

, Bakker

, Bamberger

, Bapuji

, Bhave

, Choi

, Creary

, Demerouti

, Flynn F

, Gelfand

, Greer

, Johns

, Kesebir

, Klein

, Lee

, Vugt

. COVID-19 and the workplace: Implications, issues, and insights for future research and action. American Psychologist. 2021;76(1):63–77.

Kabir

, Nahar

, Sengar

, Kabir

. Wealth code unlocked: The combined effct of emotional intelligence and intelligence quotient. Preprints. https://doi.org/10.20944/preprints202107.0283.v1

Cherniss

. Emotional intelligence: Toward clarification of a concept. Industrial and Organisational Psychology. 2010;3(2):110–26.

Schutte

, Malouff

, Hall

, Haggerty

, Cooper

, Golden

, Dornheim

. Development and validation of a measure of emotional intelligence. Personality and Individual Differences. 1998;25(2):167–77.

Petrides

, Furnham

. On the dimensional structure of emotional intelligence. Personality and Individual Differences. 2000;29(2):313–20.

Saklofske

, Austin

, Minski

. Factor structure and validity of a trait emotional intelligence measure. Personality and Individual Differences. 2003;34(4):707–21.

10.

Ciarrochi

, Deane

, Anderson

. Emotional intelligence moderates the relationship between stress and mental health. Faculty of Health and Behavioural Sciences - Papers (Archive). 2002:197–209.

11.

Luthans

, Luthans

. Positive psychological capital: Beyond human and social capital. Business Horizons. 2004;47(1):45–50.

12.

Luthans

, Avolio

, Avey

, Norman

. Positive psychological capital: Measurement and relationship with performance and satisfaction. Personnel Psychology. 2007;60(3):541–72.

13.

Cid

, Martins Mdo

, Dias

, Fidelis

ACF

. Psychological Capital Questionnaire (PCQ-24): Preliminary evidence of psychometric validity of the brazilian version. Psico-USF. 2020;25(1):63–74.

14.

Lupşa

, Vîrgă

. Psychological Capital Questionnaire (PCQ): Analysis of the romanian adaptation and validation. Psihologia Resurselor Umane. 2018;16:27–39.

15.

Sapyaprapa

. Validation of psychological capital questionnaire in thai employees. The Asian Conference on Psychology & the Behavioural Science. 2013;394–99.

16.

Welbourne

, Johnson

, Erez

. The role-based performance scale: Validity analysis of a theory-based measure. Academy of Management Journal. 1998;41(5):540–55.

17.

Fulkerson

. Emotional perception. Australasian Journal of Philosophy. 2020;98(1):16–30.

18.

Alston

DBA

. Emotional intelligence and transformational leadership to foster sustainability. 2016;7(5):9–20.

19.

Moon

, Hur

. Emotional intelligence, emotional exhaustion, and job performance. Social Behaviour and Personality: An International Journal. 2011;39(8):1087–96.

20.

Hambrook

, Brown

, Tchanturia

. Emotional intelligence in anorexia nervosa: Is anxiety a missing piece of the puzzle? Psychiatry Research. 2012;200(1):12–19.

21.

Pekaar

, Bakker

, van der Linden

, Born

MPh

, Sirén

. Managing own and others’ emotions: A weekly diary study on the enactment of emotional intelligence. Journal of Vocational Behaviour. 2018;109:137–51.

22.

Satterfield

, Hughes

. Emotion skills training for medical students: A systematic review. Medical Education. 2007;41(10):935–41.

23.

De Boer

, Lok

, Van’t Verlaat

, Duivenvoorden

, Bakker

, Smit

. Work-related critical incidents in hospital-based health care providers and the risk of post-traumatic stress symptoms, anxiety, and depression: A meta-analysis. Social Science & Medicine. 2011;73(2):316–26.

24.

Hargie

, Saunders

, Dickson

. Social Skills in Interpersonal Communication, 3rd ed., Routledge, London, 1994. https://www.amazon.com/Social-Skills-Interpersonal-Communication-Third/dp/0415081378

25.

Warnes

, Sheridan

, Geske

, Warnes

. A contextual approach to the assessment of social skills: Identifying meaningful behaviours for social competence. Psychology in the Schools. 2002;42(2):173–87.

26.

Bryan

, Freer

, Furlong

. Language and communication difficulties in juvenile offenders. (Doctoral dissertation, University of York St John.). 2007. Retrieved from https://sci-hub.yncjkj.com/10.1080/13682820601053977

27.

Denham

, Mason

, Caverly

, Schmidt

, Hackney

, Caswell

, Demulder

. Preschoolers at play: Co-socialisers of emotional and social competence. International Journal of Behavioural Development. 2001;25(4):290–301.

28.

Niven

, Totterdell

, Holman

. A classification of controlled interpersonal affect regulation strategies. Emotion (Washington, D.C.). 2009;9(4):498–509.

29.

Dubé

, Bélanger

, Trudeau

. The role of emotions in health care satisfaction. Positive feelings have the expected effect, but negative ones do not always result in dissatisfaction. Journal of Health Care Marketing. 1996;16(2):45–51.

30.

Bakker

, Demerouti

, Brummelhuis

. Work engagement, performance, and active learning: The role of conscientiousness. Journal of Vocational Behaviour. 2012;80(2):555–64.

31.

Jafari

, Seyyed Khorasani

. The prediction of academic procrastination based on emotional intelligence with mediating role of psychological capital in medical sciences students. Education Strategies in Medical Sciences. 2018;11(2):39–47.

32.

Malik

, Masood

. Emotional intelligence and resistance to change: Mediating role of psychological capital in telecom sector of Pakistan. Pakistan Journal of Commerce and Social Sciences. 2015;9(2):485–502.

33.

Peng

, Jiang

, Zhang

, Xiao

, Song

, Feng

, Zhang

, Miao

. The impact of psychological capital on job burnout of chinese nurses: The mediator role of organisational commitment. PLOS ONE. 2013;8(12):e84193.

34.

Department of Statistics Malaysia Official Portal. 2021. Available from: https://www.dosm.gov.my/v1/index.php?r=column/cthemeByCat&cat=155&bul_id=ZjJOSnpJR21sQWVUcUp6ODRudm5JZz09&menu_id=L0pheU43NWJwRWVSZklWdzQ4TlhUUT09

35.

Sharma

. Pros and cons of different sampling techniques. International Journal of Applied Research. 2017;3(7):749–52.

36.

Hargittai

. Potential biases in big data: Omitted voices on social media. Social Science Computer Review. 2020;38(1):10–24.

37.

Hinkin

. A brief tutorial on the development of measures for use in survey questionnaires. Organisational Research Methods. 1998;1(1):104–21.

38.

Deshpande

, Rademacher

, Vempala

, Wang

. Matrix approximation and projective clustering via volume sampling. Proceedings of the Seventeenth Annual ACM-SIAM Symposium on Discrete Algorithm - SODA. 2006;2:225–47.

39.

Zald

. The power and functions of boards of directors: A theoretical synthesis. American Journal of Sociology. 1969;75(1):97–111.

40.

Hazzi

, Maldaon

. A pilot study: Vital methodological issues. Business: Theory and Practice / Verslas: Teorija Ir Praktika. 2015;16(1):53–62.

41.

Ursachi

, Horodnic

, Zait

. How reliable are measurement scales? External factors with indirect influence on reliability estimators. Procedia Economics and Finance. 2015;20:679–86.

42.

Pallant

. SPSS survival manual: A step by step guide to data analysis using IBM SPSS. Australian and New Zealand Journal of Public Health. 2001;37(6):597–98.

43.

Thorndike

. Book Review: Psychometric Theory (3rd ed.) by Jum Nunnally and Ira Bernstein New York: McGraw-Hill, 1994, xxiv + 752 pp. Applied Psychological Measurement. 1995;19(3):303–5.

44.

Hair

, Black

, Babin

, Anderson

. Multivariate data analysis: A global perspective (7th ed.), 2011.

45.

Daud

KAM

, Khidzir

, Ismail

, Abdullah

. Validity and reliability of instrument to measure social media skills among small and medium entrepreneurs at Pengkalan Datu River. International Journal of Development and Sustainability.. 2018;7(3):1026–37.

46.

Kline

. Principles and practice of structural equation modeling (2nd ed.). Guilford Press, 2005.

47.

Brief

, Weiss

. Organisational behavior: Affect in the workplace. Annual Review of Psychology. 2002;53(1):279–307.

48.

Loewenstein , Lerner

. Handbook of Affective Science. Oxford University Press, 2003, pp. 619–42.

49.

Chan

. So Why Ask Me? Are Self-Report Data Really That Bad? In Statistical and Methodological Myths and Urban Legends. Routledge, 2008.

50.

Schulze

, Roberts

. Emotional Intelligence: An International Handbook. Hogrefe Publishing, 2005.

51.

Gökçen

, Furnham

, Mavroveli

, Petrides

. A cross-cultural investigation of trait emotional intelligence in Hong Kong and the UK. Personality and Individual Differences. 2014;65:30–5.

52.

Lin

, Chen

, Song

. Does your intelligence help to survive in a foreign jungle? The effects of cultural intelligence and emotional intelligence on cross-cultural adjustment. International Journal of Intercultural Relations. 2012;36(4):541–52.

53.

Shipper

, Kincaid

, Rotondo

, Hoffman

. A cross-cultural exploratory study of the linkage between emotional intelligence and managerial effectiveness. The International Journal of Organisational Analysis. 2003;11(2):171–91.

54.

Rahimnia

, Karimi Mazidi

, Mohammadzadeh

. Emotional mediators of psychological capital on well-being: The role of stress, anxiety, and depression. Management Science Letters. 2013;3:913–26.

55.

Mellão

. The relation between emotional intelligence and psychological capital of employees. International Journal of Developmental and Educational Psychology. 2013;2(1):545–50.

56.

Kobayashi

, Sezai

, Ishikawa

, Masujima

. Psychological and educational support for cancer patients who return to work: A scoping review. WORK. 2022;73(1):291–300.

57.

Hersen

, Miller

. Michel hersen and the development of social skills training: Historical perspective of an academic scholar and pioneer. Behavior Modification. 2012;36(4):444–53.

58.

Staw

, Sutton

, Pelled

. Employee positive emotion and favorable outcomes at the workplace. Organisation Science. 1994;5(1):51–71.

59.

Eljadi

. Exploring the relationship between emotional intelligence and organisational citizenship behaviour, and the potential moderator effect of job control in service companies (Unpublished Doctorial Dissertation). Universiti Sains Malaysia. Kuala Lumpur, Malaysia, 2007.

60.

Baron

, Morin

. The impact of executive coaching on self-efficacy related to management soft-skills. Leadership & Organisation Development Journal. 2010;31(1):18–38.

61.

Avey

, Reichard

, Luthans

, Mhatre

. Meta-analysis of the impact of positive psychological capital on employee attitudes, behaviours, and performance. Human Resource Development Quarterly. 2011;22(2):127–52.

62.

Lounsbury

, Steel

, Loveland

, Gibson

. An investigation of personality traits in relation to adolescent school absenteeism. Journal of Youth and Adolescence. 2004;33(5):457–66.

63.

Enzi

, Ibrahim

. Positive psychological capital (PSYCAP) (conceptual perspective in core basics and requirements for building and preparing. Journal of Economic and Administrative Sciences. 2012;18(65):1–31.

64.

Maddi

. On hardiness and other pathways to resilience. American psychologist. 2005;60(3):261–62.

65.

Harms

, Luthans

. Measuring implicit psychological constructs in organisational behaviour: An example using psychological capital: IMPLICIT MEASURE OF PSYCAP. Journal of Organisational Behaviour. 2012;33(4):589–94.

66.

Peng

, He

, Deng

, Zheng

, Chang

, Liu

. Emotional labor strategies and job burnout in preschool teachers: Psychological capital as a mediator and moderator. Work. 2019;63(3):335–45.

67.

NGO

. Impact of psychological capital on job performance and job satisfaction: A case study in vietnam. The Journal of Asian Finance, Economics and Business [Internet]. 2021;8(5):495–503.

68.

Daswati

, Hillman

, Syahruddin

, Rudi

, Ahmad

. The effect of psychological capital on performance through the role of career engagement: Evidence from Indonesian public organizations. Cogent Social Sciences. 2022;8:1.

69.

Bar-On

. The Bar-On Emotional Quotient Inventory (EQ-i): Rationale, description and summary of psychometric properties. In Measuring emotional intelligence: Common ground and controversy, Nova Science Publishers, 2004, pp. 115–45.

70.

Bar-On

. The bar-on model of emotional-social intelligence. Psicothema. 2006;18(Suppl):13–25.

71.

McClelland

. Testing for competence rather than for “intelligence”. The American Psychologist. 1973;28:1–14.

72.

Hughes

. SAGE Internet Research Methods. SAGE Publications Ltd, 2012.

73.

Keeves

. Longitudinal Research Methods. In Psacharopoulos

, (Ed.), Economics of Education, Pergamon, 1987, pp. 369–382.

74.

Dulewicz

, Higgs

. Emotional intelligence – A review and evaluation study. Journal of Managerial Psychology. 2000;15(4):341–72.

Emotional intelligence on job performance: A study on Malaysian employees

Abstract

BACKGROUND:

OBJECTIVE:

METHOD:

RESULTS:

CONCLUSION:

Keywords

1 Introduction

2 Problem statement

3 Research questions

4 Research objectives

5 Literature review

5.1 Theoretical support: SSEIT, PCQ-24, RBPS models

5.2 Relationship between emotional perception (EP) and PsyCap

5.3 Relationship between utilising emotions (UE) and PsyCap

5.4 Relationship between managing self-relevant rmotions (MSE) and PsyCap

5.5 Relationship between social skills (SS) and PsyCap

5.6 Relationship between managing others’ emotions (MOE) and PsyCap

5.7 Relationship between PsyCap and JP

6.1 Data collection

6.2 Population

6.3 Sampling frame

6.4 Sampling technique

6.5 Sampling size

6.6 Research instrument

6.7 Pilot test

7.1 Demographic profile of respondents

7.2 Reliability test of full data

Table 2 Reliability statistics of full data Variables Cronbach’s Alpha Number of items Emotional perception 0.751 4 Utilising emotions 0.736 4 Managing self-relevant emotions 0.814 5 Social skills 0.659 4 Managing others’ emotions 0.792 4 Psychological capital 0.878 6 Job performance 0.899 5

7.4 Pearson’s correlation coefficient analysis

7.6 Multiple linear regression (MLR)

Table 4 Model summaryb Model R R2 Adjusted R2 Standard error of estimate R2 change Change statistics F changes df1 df2 Sig. F change 1 0.641a 0.411 0.401 0.72696 0.411 42.564 5 305 0.000

Table 7 Model summaryb Model R R2 Adjusted R2 Standard error of estimate R2 change Change statistics F changes df1 df2 Sig. F change 1 0.623a 0.389 0.387 0.67046 0.389 196.504 1 309 0.000

9 Comparison with other related studies

10 Theoretical significance

11 Practical significance

12 Limitations of the study

13 Recommendations for future research

14 Conclusion

Ethics statement

Footnotes

Acknowledgments

Funding

Conflict of interest

References

Table 4
Model summary^b

Model R R² Adjusted R² Standard error of estimate R² change Change statistics

F changes df1 df2 Sig. F change

1 0.641^a 0.411 0.401 0.72696 0.411 42.564 5 305 0.000

Table 7
Model summary^b

Model R R² Adjusted R² Standard error of estimate R² change Change statistics

F changes df1 df2 Sig. F change

1 0.623^a 0.389 0.387 0.67046 0.389 196.504 1 309 0.000