Analyzing the Mediating Role of Work Engagement and Organizational Justice in the Relationship between Emotional Intelligence and Job Satisfaction among Employees in Kenya ()
1. Introduction
In an ever-changing work environment, job satisfaction continues to be a crucial element of the workplace (Bentley et al., 2013). Job satisfaction is important, because most employees spend a significant portion of their lives working. Hence, its impact on their general life as a highly satisfied employee improves their overall well-being fostering productivity (Doest et al., 2006). Emotional intelligence partly defined by the social cognitive theory of organizational management as those who regulate their emotions, has a substantial impact on one’s perception of fairness inside an organization (Ouyang et al., 2015), an important factor that could predict work-related outcomes such as job satisfaction.
Extensive literature has shown that work engagement is a mediator between personality and various organizational outcomes such as job performance and career satisfaction (Bakker et al., 2012; Jawahar & Liu, 2017; Ngo & Hui, 2018). An important organizational factor that affects job satisfaction is organizational justice (OJ) (Ouyang et al., 2015). Creating a healthy organization has become crucial in improving employee health and well-being (Schaufeli et al., 2002; Schaufeli & Bakker, 2004). Work engagement, according to (Demerouti & Bakker, 2011; Simpson, 2009; Orgambídez-Ramos & de Almeida, 2017), is related to job attitudes such as job satisfaction and organizational commitment. (Orgambídez-Ramos & de Almeida, 2017) noted that engaged employees believe that their work has sense and meaning. They perform tasks better, value the duties they perform, and report higher levels of satisfaction. Researchers have shown a positive relationship between work engagement and job satisfaction (Shahpouri et al., 2016; Van Bogaert et al., 2013). Hence, this study focuses on two mediating variables organizational justice and work engagement.
1.1. Motivation
Meisler (2013) study in Israel found that perceived organization justice mediates the relationship between emotional intelligence (EI) and turnover intentions, suggesting future research on EI and job satisfaction to understand their impact. Vratskikh et al. (2016) study at the University of Jordan found emotional intelligence predicts job satisfaction, suggesting cross-cultural research to understand EI’s impact on work outcomes. Several studies have explored the relationship between emotional intelligence (EI) and work-related outcomes (Schlaegel et al., 2022), but limited research has been conducted on EI’s impact in different national contexts (Kjeldsen & Andersen, 2013), particularly in developing economies (Chordiya et al., 2019) like sub-Saharan Africa, which differs significantly from Western cultures. This study aims to analyze job satisfaction and emotional intelligence in the Kenyan context, a sub-Saharan African country with a unique cultural context and lower-middle-income status, thereby filling a knowledge gap in developing countries, and enhancing the understanding of these dynamics.
1.2. Background
Job satisfaction has been a key focus for researchers for 45 years (Cantarelli et al., 2016), as it is a crucial human development resource in organizations (Wangechi et al., 2018). It involves employee contentment with tasks, work conditions, compensation, career advancement opportunities, and relationships (Lee, 2018). The World Bank report emphasizes the importance of boosting job satisfaction to improve workforce productivity, as it is vital for modern society. Sub-Saharan Africa’s productivity levels are low, with Africa and Kenya lagging in human capital development (Wangechi et al., 2018). Job satisfaction is linked to performance indicators, with satisfied workers reporting punctuality, increased productivity, happier lives, and better health (Cantarelli et al., 2016), while dissatisfied workers arrive late, quit, and engage in counterproductive behavior (Vigan & Giauque, 2018).
Job satisfaction in Kenya is a significant concern, impacting public security and education sectors. Brighter Monday Launches Kenya Employee Satisfaction Report, 2021 report highlights the importance of prioritizing employee satisfaction for higher retention and productivity. The unemployment rate in 2023 was 5.6%, a decline from 2021. Performance concerns within the Kenya National Police Service affect job satisfaction among police officers (Chemos et al., 2016). According to the Brighter Monday Launches Kenya Employee Satisfaction Report, 2021 reveals that 90% of Kenyans believe job satisfaction increases productivity, but less than half are satisfied with their current employer. The COVID-19 pandemic has significantly impacted job satisfaction among healthcare workers, with over one-third dissatisfied (Afulani Patience, 2021). High levels of stress and burnout are associated with lower job satisfaction. The pandemic has also led to a 16% decrease in private-sector employment, with the hospitality sector experiencing the most severe impact (Kenya Economic Update, 2021). Based on this background, job satisfaction is a crucial aspect of the workplace in Kenya.
Gilbert et al. (2016) pointed out that job satisfaction was one of the most studied concepts in organizational behavior owing to its contribution to organizational outcomes. Kenya is not exempted from this as indicated by the following studies. Firstly Ligare et al. (2020) study about job promotion and employee performance among the Administration Police staff in Bungoma County, noted that job satisfaction will enable individuals to be more innovative and hardworking. Secondly, Odisa et al. (2021) noted that job satisfaction was found to lead to better student learning, improved overall wellness of the institution, and student behavior among teachers in public secondary schools in Nairobi County. Moreover, Odisa et al. (2021) noted that job satisfaction also helps to improve retention rates in learning institutions. Moreover, 48% of employees’ commitment to remain with an organization was highly dependent on HR management initiatives and job satisfaction (Kadiresan et al., 2015; Matuga & Bula, 2021). Lastly, Korir and Ndegwa (2020) study on Finlays Kenya Limited in Kericho County concluded that job satisfaction is a crucial element for employees.
Emotional intelligence (EI) has been found to have a positive correlation with job satisfaction in Kenya, particularly among teachers (Sambu, 2019). EI can help teachers manage stress levels, leading to better mental health and overall well-being (Sambu, 2019). In the banking industry, Omondi (2016) noted that strengthening EI can improve job satisfaction, especially in the Kenya Post Office Savings Bank (KPOSB), which faces challenges such as falling profitability and pressure on staff to meet targets. Wangari et al. (2019) studied the influence of EI on organizational performance among insurance companies in Kenya, and found that self-awareness, self-management, social awareness, and management of interpersonal relationships significantly impact organizational performance. Understanding and managing emotions can improve decision-making and motivation, leading to better organizational performance.
Diana (2022) found a positive relationship between emotional intelligence (EI) and job satisfaction among call center workers in Nairobi County. However, there is limited research on EI in Kenya; however, it is becoming a trend for researchers recently. Organizational justice is crucial for job attitudes, stress indicators, and behaviors (Dai & Xie, 2016). However, in competitive business environments, management often pressures employees to improve performance, leading to unrealistic expectations (Muchemi, 2019) and harsh consequences such as salary cuts and suspensions (Dai & Xie, 2016). This pressure raises concerns about the erosion of organizational justice principles; hence, managers must understand employee emotions to effectively manage justice perceptions (Muchemi, 2019). Research has shown that organizational justice plays a crucial role in fostering positive employee attitudes and behaviors in various Kenyan industries (Onyango et al., 2022). Employees’ perception of fairness and honesty can lead to more extra-role conduct, which is beneficial for the organization’s development (Demirkiran et al., 2016). Research has explored the impacts of organizational justice within various Kenyan industries. For example, a study examining employee engagement in the hospitality industry in the North Rift region found that organizational justice played a crucial role in fostering positive employee attitudes and behaviors (Onyango et al., 2022). However, unjust treatment can lead to negative behaviors such as theft, withdrawal, resistance, vandalism, sabotage, and reduced positive behavior (Lilly, 2017). Another study found that contract breaches among Kenyan workers had a significant negative impact on their mental health (Cachón-Alonso & Elovainio, 2022), highlighting the importance of distributive justice in preventing organizational toxicity and poor performance.
1.3. Research Gap and Novelty
Previous researchers have found evidence that individual factors such as Emotional intelligence, and work engagement, and organizational factors such as perceptions about organizational justice in an organization significantly influence Job Satisfaction. However, I could not find research that has studied these factors simultaneously Kenyan context. This study provides new insights into the relationship between how EI affects work attitudes Petrides et al. (2016), the role of organization justice Mustafa et al. (2023), and work engagement. To fill in the knowledge gap of better understanding the relationship between emotional intelligence and job satisfaction, this research aims to assess the role of work engagement and organization justice as a mediator variable in the relationship between emotional intelligence and job satisfaction in a sample of employees in Kenya. The main research question is whether work engagement and organization justice mediate the relationship between emotional intelligence and job satisfaction, such that employees with high levels of emotional intelligence would achieve higher levels of job satisfaction in the presence of high work engagement and high perception of organizational justice.
1.4. Problem Statement and Research Objectives
Poor management resulting from a lack of emotional intelligence is a key factor in affecting employee performance in organizations. The survival and success of organizations used to be relatively predictable, but now, with the focus on employee performance for growth and sustainability, it’s crucial to measure such performance to assess organizational success (Maloba & Wamwayi, 2021), hence the need to maintain and promote job satisfaction of its employees. The modern work environment, driven by globalization, necessitates employee training to improve emotional intelligence and mental agility (Kumar, 2012). Job satisfaction is crucial for organizational success, but low levels are observed in higher education institutions (Yassin Sheikh Ali et al., 2014). This research aims to address the limited understanding of how emotional intelligence affects job satisfaction in Kenya, and how organizational and individual factors mediate this relationship (Maloba & Wamwayi, 2021). The study aims to address the gap in empirical data and contribute to optimizing workplace dynamics in the Kenyan context. The study examines the relationship between emotional intelligence, organizational justice, work engagement, and job satisfaction among Kenyan employees, examining the mediating role of organizational justice and work engagement.
2. Literature Review
2.1. Job Satisfaction
Job satisfaction is related to individual and organizational behaviors including absenteeism, turnover, job performance, and organizational citizenship behavior. Locke (1976) and Lee (2018) described job satisfaction as a positive emotional state that emanates from an individual’s subjective experience in their job. Also, Wolf (1970) and Liu et al. (2016) considered job satisfaction within the workplace as the fulfillment, or lack thereof, of employees’ physical and psychological needs by the job. In terms of attitude, job satisfaction is seen as the feelings individuals have about their jobs, which emerge from their perceptions of the jobs and the extent to which there is a good fit between the individual and the organization (George & K.A., 2015; Ivancevich & Matteson, 1980). George and K.A. (2015) and Lawler and Ledford (1992) further defined job satisfaction as the feelings people have about the rewards they receive on the job, indicating a focus on the tangible returns of work.
Vroom (1962) defined job satisfaction relating to the role of employees in the workplace, as affective orientations on the part of individuals towards work roles. (Meier & Spector, 2015), defined job satisfaction as the overall feeling people have about their jobs and the various aspects, it may be favorable leading to satisfaction, or unfavorable leading to dissatisfaction. This implies that the concept of job satisfaction is a multidimensional concept that is assessed from various perspectives, since individuals have different expectations and ways of assessing their jobs, a person might experience satisfaction in one aspect of their job while feeling indifferent or dissatisfied about other aspects (Locke, 1976; Schmidt, 2007; Benevene et al., 2018). Chandra and Priyono (2015) and Lee (2018) noted that psychological factors, such as work goals and recognition, also contribute to job satisfaction. Recent studies have shifted focus from occupational characteristics to individual factors of job satisfaction (Ouyang et al., 2015; Zhang et al., 2014). Fostering job satisfaction is crucial for improving performance, reducing turnover, increasing profitability, enhancing customer satisfaction, and promoting employee health (Kollmann et al., 2020; Thielgen et al., 2015). Bailey et al. (2016), Macdonald and Macintyre (1997) noted that job satisfaction is specific to a single individual and their particular job situation, reflecting an individual’s feelings and attitudes towards their role and work environment.
2.2. Emotional Intelligence
Emotional intelligence is the social ability of an individual to understand their own emotions, and the emotions of others and use them to form favorable relationships with others or to guide thinking and behavior (Salovey & Mayer, 1990), which is important for organizations today, right from the staff to top management. (Mayer et al., 2016) also defined it as a psychological resource made up of a set of abilities related to processing emotion-relevant information and possibly contributing to positive job attitudes and behaviors specifically job satisfaction. Also, according to Zhu et al. (2015), emotional intelligence is a psychological resource that can be used to predict employee performance. Emotional intelligence has become popular in the last decade and has been adopted in social and behavioral sciences to predict organizational commitment Salovey and Mayer (1990), leadership, Jain and Duggal (2018), and how people cope with stress (Boyatzis, 2018).
The study uses (Law et al., 2004) four dimensions of emotional intelligence (EI) 1) Self-emotion appraisal (SEA) involves a person’s awareness of their emotions and their ability to express them naturally, which is better understanding recognizing, and acknowledging their emotions (Mayer & Salovey, 1997), 2) Others’ emotion appraisal (OEA) is the capacity to perceive and comprehend the emotions of others, enabling individuals to predict their reactions with high sensitivity (Shah, 2022), 3) Regulation of emotion (ROE) involves a person’s ability to monitor, control, and modify emotions to recover from psychological distress, resulting in improved emotional control and reduced stress and lastly 4) use of emotion (UOE) involves using emotions for constructive activities or personal performance improvement, with individuals with high ROE abilities likely to encourage continuous improvement Law et al. (2004) and Acosta-Prado et al. (2022).
2.3. Organization Justice
Pan et al. (2018) defined organization justice as an employee’s perception of fairness. This subjective element makes organizational justice prone to influences stemming from individual biases, that is, it is not just about the elements in the situation but rather aspects of the perceiver (Johnston et al., 2016). High levels of justice enhance employees’ sense of belonging and organization identification, while negative perceptions can lead to irrationality (Zhu et al., 2015). This study will adopt Elovainio et al. (2010), dimensions of organizational justice that is procedural, distributive, and interpersonal justice.
According to Lavelle et al. (2007), procedural justice involves people’s perception that they have a say during the decision-making process and that the procedures used by the organization to make the decision are fair and free of bias (Cohen-Charash & Spector, 2001; Gluschkoff et al., 2021; Leventhal, 1980). Procedural justice is important because it encourages incident reporting, as individuals feel valued and respected in the workplace (Blader & Tyler, 2003). Positive emotions and engagement are associated with procedural justice, but workplace bullying can impair this process. Distributive justice is the equitable allocation of resources and rewards within an organization Pereira et al. (2017), rooted in fairness and equality. According to Correia and Almeida (2020), distributive justice refers to the belief that resources allocated are deserved, and based on equitable principles, such as contribution, need, or equality. This view implies that there is an inherent expectation of a balance between input and output, where the rewards one receives are directly proportional to their contribution to the organization (Strom et al., 2014). Colquitt et al. (2013) further, extend this understanding by defining it as the fairness of decision outcomes, which are crucial for individuals’ perceptions of justice. However, the concept of justice is subjective, with emotions playing a significant role in personal interpretation. (Bala Subramanian et al., 2022) argue that employees in organizations actively evaluate the fairness of resource and reward distribution, considering factors such as job development opportunities and career advancement prospects. This broad concept of distributive justice encompasses a wide range of factors that contribute to an employee’s overall sense of value and recognition within the organization (Bala Subramanian et al., 2022).
According to Colquitt et al. (2001), interpersonal justice refers to the fairness of treatment individuals receive in organizations, focusing on the respect and dignity they get from decision-makers. It involves how employees perceive the treatment during resource allocation and rewards, such as respect, honesty, and politeness. Improper and unfair treatment can reduce motivation and job satisfaction among subordinates. The Affective Events Theory (AET) is crucial in understanding interpersonal justice, as it suggests that individuals’ perceptions and reactions are influenced by their emotional responses to treatment, which are interpersonal events that elicit emotional reactions (Boulter & Boddy, 2020).
2.4. Work Engagement
Work engagement is defined as a positive psychological state characterized by vigor, dedication, and absorption into one’s work tasks (Schaufeli et al., 2002; Schaufeli & Bakker, 2004). Vigor refers to higher levels of energy mental resilience investment of effort while working, and persistence in the face of difficult situations, dedication refers to being intensely involved in work tasks and experiencing an associated sense of meaningfulness and enthusiasm, inspiration, and pride while working and absorption refer to a state of full concentration on work and deeply engrossment in it, and not easily distracted (Knight et al., 2017; Schaufeli et al., 2002; Eldor & Vigoda-Gadot, 2017; Bakker, 2017).
According to Du Plessis and Boshoff (2018), disengaged employees will manifest a physical appearance of withdrawal and defensiveness, resulting in behaviors that lead to low productivity. Employees who fully engage physically, emotionally, and cognitively in their work roles derive a sense of purpose and reward from their performance and will feel psychologically secure, and trusting in their workplace’s environment, and perceive themselves as having the necessary physical and psychological resources required for their tasks a positive, fulfilling (Bakker & Demerouti, 2008; Knight et al., 2017). Mazzetti et al. (2023) noted that high levels of work engagement increase their feelings of commitment and involvement in work roles contributing to overall job satisfaction. Engaged employees are enthusiastic about their duties and go above and beyond to ensure that the organization achieves its objectives (Bakker & Demerouti, 2008; Greenier et al., 2021).
2.5. Affective Events Theory
Affective events theory emphasizes how specific events result in attitudes and behaviors through the process of cognitive and affective reactions (Weiss & Cropanzano, 1996). It explains the link between affective events at the workplace, the emotional reactions they trigger, and the resulting attitudes or behaviors (Kelly & Barsade, 2001; Zhu et al., 2023). Affective events can be positive or negative such as anger, fear, joy, love, and sadness, and can stem from various sources in an organization or the external environment (Boulter & Boddy, 2020). An event is considered as a change, a shift in circumstances, or a modification in one’s current experience (Weiss & Cropanzano, 1996). The AET proposes that positive events such as transformational leadership (Ding and Lin, 2021), team flexibility (Wang et al., 2022), or leader-member exchange (Cropanzano et al., 2017) can illicit positive attitudes such as entrepreneurial passion, job satisfaction, organizational trust, and affective commitment and thus favorably influence workplace behaviors (Ghasemy et al., 2021). On the other hand, a negative affective workplace event such as unfair treatment (Judge et al., 2006) and abusive supervision, or bullying (Glasø et al., 2011), Boulter and Boddy (2020) can illicit negative attitudes and outcomes.
A study conducted by Extremera et al. (2018), on the mediating role of work engagement on how EI makes one feel at work. The evidence showed that affective dispositions over organizational characteristics played an important role in predicting job satisfaction. According to the theory Weiss and Cropanzano (1996), the emotional experiences accumulated in the work environment, along with other factors (including personality), shape employees’ work attitudes. Furthermore, in Affective Event Theory Weiss and Cropanzano (1996) suggested that the emotional state at work is a crucial conduit for the influence of personality and organization on job satisfaction and performance. EI can cast a “rosy glow” over workplace events, allowing employees to interpret them more positively, thus promoting positive effects and diminishing negative effects, as discussed by Miao et al. (2017). This positive interpretation can lead employees to infer higher job satisfaction from their positive moods and workplace environment.
2.6. Hypothesis Development
According to Extremera et al. (2018) and Kafetsios and Zampetakis (2008), there are several reasons for employees with higher EI experience higher job satisfaction. Kafetsios and Zampetakis (2008) concluded that EI significantly affected job satisfaction among teachers. Khan et al. (2017) assessed the relationship between emotional intelligence and job satisfaction among academic librarians and noted that workers experience high job satisfaction when the level of emotional intelligence is high. Tagoe and Quarshie (2017) studied the relationship between emotional intelligence and job satisfaction among nurses and found a significant positive correlation. Emotional Intelligence (EI) enhances work engagement because it involves managing and regulating one’s emotions and those of others this sustained emotional experience becomes the fuel to achieve tasks (Green et al., 2017). EI can lead to positive work outcomes such as work engagement (Masa’deh et al., 2019). Levitats and Vigoda-Gadot (2020) noted that Emotional Intelligence positively influences civil servants’ dedication to their community, commitment to their organization, and willingness to go above and beyond for others in the workplace. The ability to control their own emotions and thoughts, Di Fabio (2017) emotionally intelligent employees may be less likely to ruminate over a negative or unfair decision Petrides et al. (2016) and henceforth better at deciphering whether they are being treated with honesty, politeness, and respect by the organization (Meisler, 2013; Mustafa et al., 2023). According to Ouyang et al. (2015) individuals with high EI can manage and make good use of their and others’ emotions to promote their perception and understanding of factors related to the organization and better understand organizational justice factors; by contrast, those with low EI easily form a sense of organizational injustice. Based on the above literature, we can hypothesize that
H1: Emotional intelligence has a positive effect on Job satisfaction.
H2: Emotional intelligence has a positive effect on Work Engagement.
H3: Emotional intelligence has a positive effect on Organizational justice.
Several studies have linked perceived organizational justice to job satisfaction (Pan et al., 2018). When employees feel they are being treated equally within the organization, their job satisfaction increases (García-Izquierdo et al., 2012). Abdul Rauf (2014) conducted a study to investigate the impact of perceived organizational justice on job satisfaction and noted that organizational justice was a strong predictor of job satisfaction. When employees perceive fair processes and procedures in decision-making processes, this leads to increased work engagement (Antonio De Castro et al., 2023). Accordingly, the more employees have a favorable view of the organization, the more engaged in their work (Antonio De Castro et al., 2023; Eisenberger et al., 1986). Based on the social exchange theory and equity theory, employees are likely to develop positive attitudes and reciprocate with positive emotions and behaviors when they perceive fair treatment by their organization, similarly, when they trust that their contributions are met with equitable outcomes, they are inclined to respond with positive attitudes, emotions, and behaviors (Enoksen, 2015; Wan et al., 2018). According to Karanika-Murray et al. (2015) employees who are highly engaged in their work exhibit energy and dedication to their work and, consequently satisfied with their jobs. Orgambídez-Ramos et al. (2014) noted the importance of employee engagement in the organization, since high levels of employee engagement lead to high levels of job satisfaction. Based on this literature, the hypothesis states that
H4: Organizational justice has a positive effect on Job satisfaction.
H5: Organizational justice has a positive effect on Work Engagement.
H6: Work Engagement has a positive effect on Job Satisfaction.
Based on the Job-Demands research model, Emotional intelligence is a personal resource and an antecedent of work engagement (Bakker & Demerouti, 2014; Schaufeli et al., 2002). Studies by Bakker et al. (2012), Jawahar and Liu (2017), and Ngo and Hui (2018) have shown work engagement as a mediator between personal resources and organizational outcomes such as job performance, career satisfaction, and job satisfaction. Moura et al. (2014) studied the antecedents of job satisfaction and found work engagement was one. Fairness perceptions are subjective and therefore determined by a person’s emotional state (Ouyang et al., 2015). Similarly, Ouyang et al. (2015) provided evidence that organizational justice mediates the impact of emotional intelligence (EI) on job satisfaction, suggesting that high EI individuals, adept at managing emotions, more positively perceive workplace fairness, leading to greater job satisfaction. When employees view the organization as just, they tend to develop a stronger sense of trust and loyalty in their relationship with their employer (Ouyang et al., 2015). Hence, the hypothesize states that
H7: Work engagement mediates the relationship between emotional intelligence and Job satisfaction.
H8: Organizational justice mediates the relationship between emotional intelligence and Job satisfaction.
3. Methodology
3.1. Sample
The study will use quantitative research methods, as described by Bilal et al. (2021), to analyze relationships between variables and a cross-sectional study, a one-shot approach, will provide an overview of the general situation, assessing variables one point in time. This study focuses on employed Kenyans, analyzing individual employees from various organizations, sectors, age groups, and management levels across Kenya. The sample size is determined using the “10-times rule” in PLS-SEM, which requires a sample size of 10 times the maximum number of indicators pointing to the latent variable (Hair et al., 2011, Hair et al., 2014). The study employed a non-probability convenience sampling approach, distributing questionnaires through friends and acquaintances who shared them with other potential respondents. Data will be collected using a self-administered closed-ended questionnaire through Google Forms, with a response rate of 55% (n = 237).
3.2. Measurement
Job Satisfaction is measured using the item Generic Job Satisfaction Scale (Macdonald & Macintyre, 1997), consisting of 10 items. Sample questions include “I receive recognition for a job well done”. Responses were rated using a 5-point Likert scale (1-Strongly Disagree to 5-Strongly Agree). Work Engagement was measured using the shorter version of the Utrecht Work Engagement Scale UWES-9 composed of 9 items (Balducci et al., 2010) derived from the original UWES 17 (Schaufeli et al., 2006). Sample questions include “At my work, I feel bursting with energy”. Responses were rated using 5 point Likert scale (1-Never to 5-Always). Emotional Intelligence was measured using the Wong and Law (2004) Emotional Intelligence scale (WLEIS). The scale consists of 16 items, with 4 dimensions of Emotional intelligence (Self-Emotions Appraisal, Others Emotional Appraisal, Regulation of Emotions and Use of Emotion). Self-report measures are commonly used to measure emotional intelligence. A global EI score is calculated, a higher score indicates greater Emotional intelligence (Extremera et al., 2018). Responses were rated using a 5-point Likert scale (1-Totally Disagree to 5-Totally Agree). Sample questions include “I have a good understanding of my own emotions”. Organizational justice is measured using (Elovainio et al., 2010) shortened version items developed by Colquitt 2001, comprising distributive justice (2 items), procedural justice (4 items), and interpersonal justice (4 items). Sample questions include “Have those procedures been applied consistently?” Responses were rated using a 5-point Likert scale (1-Totally Disagree to 5-Totally Agree) (Figure 1).
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Figure 1. Research model.
3.3. Analysis
The results are analyzed using Partial Least Square (PLS) that measures the hypothesis and effects among variables (Hair et al., 2020). The first step is conducting an outer model test to measure the validity and reliability test of the instrument. Validity is done using factor loading, where the outer loading value of 0.5 is considered reliable (Hair et al., 2019). Reliability test using Cronbach’s Alpha value of 0.6 and higher (Hair et al., 2019) indicates that the instruments are reliable. In addition, AVE measures convergent validity using AVE values higher than 0.6 (Hair et al., 2016). Thus, the variables are considered valid and reliable when they meet this criterion. The second step is an inner model analysis using the f-square to measure the significance of the impact of independent variables on dependent variables and the R-square to measure the proportion of the variance in the dependent variable that is explained by the independent. The third step is hypothesis testing using the path coefficient and p-value.
The research uses data from 237 respondents as shown in Table 1. There are more male respondents (n = 125) than female respondents (n = 112). The majority are Gen Z (n = 103), followed by Gen Y (n = 100), and lastly Gen X (n = 34). Most respondents are single (n = 134) and married (103). In terms of education, the majority hold a Bachelor’s degree (134), followed by College Education (64), Master’s degree (18), Secondary Education (16), and Doctoral degree (5). Tenure is distributed with the highest number having more than 5 years (90), 3 - 5 years (52), 1 - 2 years (39), and less than one year (56). Position-wise, staff members dominate (101), with middle management (77), lower management (46), and top management (13). Employment status reveals a significant portion of contract workers (112), permanent workers (99), and outsourced workers (26). The size of organizations varies, with medium-sized firms (100 - 1000 employees) being the most common (96), followed by small (less than 100 employees) (98) and large organizations (more than 1000 employees) (43). Sector analysis indicates a notable presence in Education (50), ICT and Manufacturing (38 each), Health (25), and Wholesale and Retail (24), among others, with smaller representations in areas like Accounting, Consultancy, and the Justice System.
Table 1. Respondents profile.
Classification |
Description |
Total |
Gender |
Female |
112 |
|
Male |
125 |
Age Group |
Gen X (44 - 58 yrs) |
34 |
|
Gen Y/Millenials (30 - 43 yrs) |
100 |
|
Gen Z (18 - 29 yrs) |
103 |
Marital Status |
Married |
103 |
|
Single |
134 |
Education |
Bachelor’s Education |
134 |
|
College Education |
64 |
|
Doctoral Education |
5 |
|
Masters Education |
18 |
|
Secondary Education |
16 |
Tenure |
1 - 2 years |
39 |
|
3 - 5 years |
52 |
|
Less than one year |
56 |
|
More than 5 years |
90 |
Position |
Lower Management |
46 |
|
Middle Management |
77 |
|
Staff |
101 |
|
Top Management |
13 |
Employment Status |
Contract worker |
112 |
|
Outsourced worker |
26 |
|
Permanent worker |
99 |
Size of Organization |
Large (more than 1000 employees) |
43 |
|
Medium (100 to 1000 employees) |
96 |
|
Small (less than 100 employees) |
98 |
Sector |
Accounting |
1 |
|
Agricultural |
10 |
|
Building and Construction |
5 |
|
Consultancy |
1 |
|
Education |
50 |
|
Electrical |
1 |
|
Energy |
1 |
|
Environmental |
1 |
|
Finance |
9 |
|
Health |
25 |
|
Information and Communication
Technology (ICT) |
38 |
|
Justice System |
1 |
|
Manufacturing |
38 |
|
NGO |
2 |
|
Public Sector |
2 |
|
Security |
2 |
|
Tourism and Hospitality |
20 |
|
Transport and Infrastructure |
5 |
|
Water |
1 |
|
Wholesale and Retail |
24 |
The first step is testing the indicator’s reliability using outer loading as shown in Figure 2, all the indicators have values higher than 0.5 indicating a strong relationship between the indicators and latent variables except for two indicators (AB3 = 0.323, SEAI = 0.468). This decision to retain indicators, even with lower loadings, was made based on their influence on Average Variance Extracted (AVE). That is indicators with lower loading values were retained when their removal did not lead to an improvement in the Average Variance Extracted (AVE) value as shown in Table 2, which is in line with the recommendations by (Hair et al., 2014).
Figure 2. Reliability results using outer loadings.
The next step is to measure the validity and reliability using Cronbach’s alpha, composite reliability, and AVE values. The output results indicate that all variables have Cronbach’s alpha values and Composite values greater than 0.6 and 0.7, indicating high levels of internal consistency as shown in Table 2. Therefore, it can be concluded that all the measuring indicators for each variable from the questionnaire are reliable. The AVE values as shown in Table 2 for the 4 variables surpassed the threshold of 0.5, indicating that the measures used in this study are related and hence have met the criteria for convergent validity.
Table 2. Validity and reliability results.
|
Cronbach’s alpha |
Composite
reliability (rho_a) |
Composite
reliability (rho_c) |
Average variance extracted (AVE) |
EI |
0.940 |
0.943 |
0.947 |
0.531 |
JS |
0.904 |
0.910 |
0.921 |
0.539 |
OJ |
0.894 |
0.897 |
0.915 |
0.576 |
WE |
0.899 |
0.921 |
0.921 |
0.574 |
In cross-loadings, each indicator’s loading on its assigned latent variable should exceed its loading on any other latent variable, ensuring clear differentiation between constructs. The output results of cross loading resented in Table 3, indicate that indicators AB1, AB2, AB3, DE1, DE2, DE3, V1, V2, and V3 are more strongly associated with the construct they are intended to measure which is Work Engagement, rather than with other constructs. The same can be seen about the rest of the indicators, hence valid.
Table 3. Discriminant validity results using cross-loading matrix.
|
EI |
JS |
OJ |
WE |
AB1 |
0.481 |
0.608 |
0.474 |
0.818 |
AB2 |
0.405 |
0.446 |
0.34 |
0.637 |
AB3 |
0.267 |
0.244 |
0.214 |
0.323 |
DE1 |
0.493 |
0.692 |
0.513 |
0.867 |
DE2 |
0.477 |
0.701 |
0.492 |
0.864 |
DE3 |
0.536 |
0.641 |
0.497 |
0.806 |
V1 |
0.396 |
0.644 |
0.454 |
0.729 |
V2 |
0.447 |
0.728 |
0.543 |
0.835 |
V3 |
0.39 |
0.654 |
0.501 |
0.784 |
DJ1 |
0.403 |
0.501 |
0.691 |
0.439 |
DJ2 |
0.341 |
0.437 |
0.708 |
0.394 |
IJ1 |
0.408 |
0.606 |
0.785 |
0.494 |
IJ2 |
0.408 |
0.569 |
0.788 |
0.501 |
IJ3 |
0.382 |
0.52 |
0.789 |
0.417 |
PJ1 |
0.503 |
0.585 |
0.756 |
0.504 |
PJ2 |
0.398 |
0.484 |
0.787 |
0.459 |
PJ3 |
0.312 |
0.499 |
0.757 |
0.44 |
JS1 |
0.42 |
0.718 |
0.532 |
0.522 |
JS10 |
0.469 |
0.851 |
0.601 |
0.732 |
JS2 |
0.438 |
0.675 |
0.402 |
0.505 |
JS3 |
0.494 |
0.806 |
0.543 |
0.681 |
JS4 |
0.377 |
0.696 |
0.445 |
0.494 |
JS5 |
0.449 |
0.790 |
0.497 |
0.612 |
JS6 |
0.42 |
0.698 |
0.515 |
0.588 |
JS7 |
0.245 |
0.638 |
0.476 |
0.529 |
JS8 |
0.398 |
0.713 |
0.497 |
0.595 |
JS9 |
0.483 |
0.727 |
0.582 |
0.622 |
OEA1 |
0.674 |
0.398 |
0.41 |
0.397 |
OEA2 |
0.690 |
0.362 |
0.334 |
0.375 |
OEA3 |
0.719 |
0.379 |
0.338 |
0.392 |
OEA4 |
0.742 |
0.465 |
0.369 |
0.462 |
ROE1 |
0.781 |
0.418 |
0.411 |
0.403 |
ROE2 |
0.754 |
0.44 |
0.413 |
0.439 |
ROE3 |
0.735 |
0.409 |
0.402 |
0.373 |
ROE4 |
0.772 |
0.419 |
0.415 |
0.44 |
SEA1 |
0.468 |
0.306 |
0.24 |
0.298 |
SEA2 |
0.726 |
0.466 |
0.335 |
0.489 |
SEA3 |
0.716 |
0.429 |
0.378 |
0.486 |
SEA4 |
0.717 |
0.373 |
0.317 |
0.4 |
UOE1 |
0.713 |
0.479 |
0.453 |
0.445 |
UOE2 |
0.769 |
0.445 |
0.396 |
0.403 |
UOE3 |
0.815 |
0.441 |
0.42 |
0.444 |
UOE4 |
0.806 |
0.433 |
0.437 |
0.419 |
In Table 4, the R-square for Job Satisfaction is 0.727, indicating that organizational justice, work engagement, and emotional intelligence together explain 72.7% of the variance in Job Satisfaction, showing a strong model fit. Organizational Justice has an R-square of 0.276, meaning emotional intelligence explains 27.6% of its variance, suggesting a weaker relationship or missing variables. Work Engagement’s R-square is 0.458, with emotional intelligence and organizational justice explaining 45.8% of its variance, indicating a moderate model fit. Thus, Job Satisfaction has the best fit, followed by Work Engagement, with Organizational Justice having the weakest fit.
Table 4. R-square matrix.
|
R-square |
R-square adjusted |
JS |
0.727 |
0.724 |
OJ |
0.276 |
0.272 |
WE |
0.458 |
0.453 |
The final step is to test the hypotheses. The results as shown in Table 5 show that in all cases except for EI -> JS, the p-values are lower than 0.05, suggesting that the relationships are statistically significant and the null hypothesis can be rejected. This means there is strong evidence to support the hypothesized relationships between these constructs. However, for EI -> JS, since the p-value is higher than 0.05, the evidence is not strong enough to reject the null hypothesis, and thus the relationship is not considered statistically significant. From the path coefficient matrix, we can see that EI has a direct effect on OJ and WE, as indicated by the supported decision with significant P values (p < 0.05).
Table 5. Path coefficient matrix.
|
Original sample (O) |
Sample mean (M) |
Standard deviation (STDEV) |
T statistics (|O/STDEV|) |
P values |
EI -> JS |
0.083 |
0.082 |
0.064 |
1.302 |
0.193 |
EI -> OJ |
0.525 |
0.530 |
0.066 |
7.971 |
0.000 |
EI -> WE |
0.356 |
0.357 |
0.072 |
4.966 |
0.000 |
OJ -> JS |
0.306 |
0.307 |
0.055 |
5.531 |
0.000 |
OJ -> WE |
0.418 |
0.420 |
0.061 |
6.871 |
0.000 |
WE -> JS |
0.576 |
0.577 |
0.066 |
8.681 |
0.000 |
In mediation analysis, the total effects of an independent variable on a dependent variable include both direct effects and indirect effects. Table 6 shows the total effect of EI on JS as significant, with a coefficient value of 0.575 and, a p-value of 0.000 < 0.05. The direct effect of EI on JS is 0.083, p-value 0.193 > 0.05 insignificant suggesting that the direct influence of EI on JS is not statistically supported. The indirect effects of the EI on JS through the mediators WE and OJ are both statistically significant, with coefficients of 0.205 and 0.161, respectively with p values 0.000 < 0.005. Based on the mediation results in Table 6, this indicates that the mediators play a significant role in the relationship between the independent and dependent variables.
Table 6. Mediation analysis results.
Total effects EI-JS |
Direct effects EI-JS |
Indirect effects of EI on JS |
Coefficients |
P-value |
Coefficients |
P-value |
Hypotheses |
Coefficients |
P-value |
0.575 |
0.000 |
0.083 |
0.193 |
EI-WE-JS |
0.205 |
0.000 |
|
|
|
|
EI-OJ-JS |
0.161 |
0.000 |
4. Results and Discussion
The analysis highlights the relationships between emotional intelligence, organizational justice, work engagement, and job satisfaction among employees in Kenya. Emotional intelligence shows a positive but insignificant effect on job satisfaction (0.083, p = 0.193), suggesting other factors in the Kenyan workplace might influence satisfaction more. This finding is intriguing, as it contrasts with some existing literature (Naz et al., 2019; Ouyang et al., 2015; Wen et al., 2019) that reports a significant positive relationship. A possible reason for this is the culture and socioeconomic status of Kenya. In Kenya, job satisfaction might be more influenced by external factors such as economic stability, job security, and work-life balance rather than internal factors like emotional intelligence. Also, Kenya has a more collectivist culture, where group harmony and relationships might overshadow individual emotional traits. In such environments, organizational justice and work engagement might be more critical determinants of job satisfaction than EI alone. The Job Demands-Resources (JD-R) Model also provides a deeper understanding of this alternative observed phenomenon. The JD-R model posits that job satisfaction is influenced by the balance between job demands and job resources. Emotional intelligence can be seen as a personal resource that helps employees manage job demands. In the Kenyan context, job resources like organizational justice and work engagement might be more critical than personal resources (EI) in determining job satisfaction. The relative availability and importance of these resources could explain the non-significant direct effect of EI. However, emotional intelligence significantly enhances organizational justice (0.525, p = 0.000) and work engagement (0.356, p = 0.000), indicating that emotionally intelligent individuals perceive greater fairness and are more committed to their work. Organizational justice significantly impacts job satisfaction (0.306, p = 0.000), suggesting that employees who perceive their environment as fair are more likely to be satisfied with their jobs This study aligns with findings by Gichira et al., 2016 and Ouyang et al., 2015 which found a positive relationship between OJ and JS. OJ significantly and work engagement (0.418, p = 0.000), underscoring the importance of perceived fairness in fostering both satisfaction and engagement. Furthermore, work engagement strongly affects job satisfaction (0.576, p = 0.000) showing that in Kenyan organizations, higher work engagement (WE) significantly increases job satisfaction (JS) due to the energy, focus, and dedication it brings to employees. Engaging work environments and supportive structures enhance job fulfillment. The findings back up the findings by (Gong et al., 2020; Riyanto et al., 2021; Topchyan & Woehler, 2021) who found a positive relationship between WE and JS. Work engagement mediates the relationship between emotional intelligence and job satisfaction (0.205, p = 0.000), showing that engagement is a significant link. These findings are in line with the studies by (Extremera et al., 2018; Orgambídez-Ramos et al., 2014; Topchyan & Woehler, 2021) which show that EI’s ability to build relationships and regulate emotions enhances work engagement, which subsequently increases job satisfaction. Organizational justice also mediates this relationship (0.161, p = 0.000), these findings are in line with the findings of (Ouyang et al., 2015) and (Mustafa et al., 2023). Employees with high EI foster a fair culture leading to greater job satisfaction, while those with low EI may perceive increased injustice, reducing satisfaction. The effect is less strongly than WE, indicating that while fair treatment contributes to satisfaction, the primary driver is the work engagement fostered by emotional intelligence. Overall, these findings emphasize the central roles of work engagement and organizational justice in enhancing job satisfaction.
Affective Events Theory (AET) posits that workplace events trigger emotional reactions, which in turn influence attitudes and performance (Weiss & Cropanzano, 1996). The current findings extend AET by highlighting the critical role of emotional intelligence in shaping how events are interpreted and the emotional responses that follow. Emotionally intelligent individuals may be more likely to perceive workplace events in a positive light, recognize the emotions triggered, and adaptively manage those feelings. This suggests that emotional intelligence can influence the entire affective events process, from initial perception to ultimate impact on attitudes like job satisfaction. Organizations can apply AET to promote job satisfaction and well-being by developing emotional intelligence, fostering a sense of organizational justice, and creating conditions that encourage work engagement as key strategies. Organizations can do this by providing training in emotional skills, ensuring fair and transparent decision-making processes, recognizing and rewarding contributions, providing opportunities for growth and development, and fostering a positive and supportive work environment. AET emphasizes the direct impact of affective events on job satisfaction. However, the current findings highlight the critical mediating roles of work engagement and organizational justice. This suggests that the emotional responses triggered by workplace events may primarily influence job satisfaction indirectly, by shaping levels of engagement and perceptions of fairness. Emotionally intelligent individuals may experience more positive affective events, leading to greater engagement and perceptions of justice, which in turn enhance job satisfaction. This extends AET by emphasizing the complex pathways through which workplace events ultimately influence well-being. While AET provides a general framework for understanding how workplace events influence well-being, the current findings underscore the importance of cultural and contextual factors in shaping these dynamics. The study’s focus on Kenyan employees highlights that the specific events that trigger emotional responses, and the pathways through which those responses influence attitudes, may vary across different cultural and organizational contexts. Future research should explore how AET plays out in diverse settings, considering how cultural norms, organizational practices, and individual differences influence the affective events process. By doing so, researchers can provide a more nuanced understanding of how to promote positive well-being and performance across different contexts.
5. Conclusion
The study provides new insights into the complex relationships between emotional intelligence, organizational justice, work engagement, and job satisfaction among employees in Kenya. Emotional intelligence was found to have indirect effects on job satisfaction, primarily through work engagement and organizational justice. This highlights the nuanced ways in which emotional intelligence operates in the workplace, suggesting that emotionally intelligent individuals create a work context that enhances their well-being by promoting fairness and engagement. The focus on Kenyan employees underscores the importance of considering cultural and organizational contexts in understanding the effects of emotional intelligence, emphasizing the need for culturally sensitive theories and interventions. Organizational justice emerged as a central factor, fostering both work engagement and job satisfaction. The importance of justice may be particularly high in collectivist cultures like Kenya, which emphasize community and collaboration. Work engagement was identified as a critical mediator highlighting the importance of fostering engagement as a way to leverage the benefits of emotional intelligence and fairness for promoting well-being. Job satisfaction was found to be influenced by a complex interplay of individual differences (emotional intelligence), organizational factors (justice), and work experiences (engagement), emphasizing the need for multifaceted approaches to promoting satisfaction. The importance of considering cultural and organizational contexts in understanding the determinants of job satisfaction was underscored, as what fosters satisfaction can vary across different contexts. The impact of emotional intelligence on satisfaction may primarily be indirect, through shaping engagement and justice perceptions, providing a more nuanced understanding of how individual differences influence satisfaction.
The study’s sample, was restricted to specific sectors in Kenya, while sufficient for the analysis, not all sectors were represented. This limitation significantly reduces the generalizability of the results, as the findings may not reflect the broader Kenyan workforce. To address this, future research should replicate the study with a larger and more diverse sample encompassing various sectors. Additionally, the study identified work engagement and organizational justice as mediators in the relationship between emotional intelligence (EI) and job satisfaction. However, this focus is somewhat narrow as it did not explore other potential moderating and mediating factors. Important pathways and mechanisms may have been overlooked, limiting the depth of the analysis. Future research should investigate other potential moderators and mediators to provide a more holistic view of how EI influences job satisfaction. The cultural specificity of the study presents another limitation. Conducted within a Kenyan context, the results may not apply to other cultural settings. Cultural differences can significantly impact the dynamics between EI, work engagement, organizational justice, and job satisfaction. Conducting similar studies in different countries and cultural contexts would help determine how these relationships vary across cultures, thereby enhancing the external validity of the findings. Moreover, the study’s cross-sectional design restricts its ability to draw causal conclusions. This design captures a snapshot in time, which limits understanding of the directionality of the relationships between the variables. A longitudinal design, which tracks employees over time, would provide stronger evidence for the causal relationships between EI, work engagement, organizational justice, and job satisfaction. Such a design would offer insights into how these variables interact and influence each other over the long term.