Moderating Role of Job Demands-Resources on Emotional Intelligence and Work Commitment Among Millennials in The Kenyan Telecommunication Sector

Moderating Role of Job Demands-Resources on Emotional Intelligence and Work Commitment Among Millennials in The Kenyan Telecommunication Sector

Joyce Wanjiru Thairu, (Ph.D Candidate); Domeniter Naomi Kathula, Ph.D; Peter Kithae, Ph.D

The Management University of Africa, Kenya

DOI: https://dx.doi.org/10.47772/IJRISS.2024.807067 

Received: 11 June 2024; Received: 26 June 2024; Accepted: 29 June 2024; Published: 02 August 2024

ABSTRACT

The influence of employee personal and organizational characteristics such as emotional intelligence and job demands-resources respectively on work commitment is crucial for organizational success. Most of these employees belong to the global millennial generational cohort in the telecommunication sector. This called for investigating the personal and organizational factors impacting their work commitment. The study investigated the impact of emotional intelligence and job demands-resources on work commitment among millennial employees in Kenya’s telecommunication sector. Employing a positivist research philosophy and a cross-sectional research design, the survey was conducted among 134 millennial employees aged between 23- 43 years from international gateway operators, a segment of telecommunication companies in Kenya. Participants completed an online survey measuring their emotional intelligence, job demands-resources, and work commitment. The associations between emotional intelligence and work commitment were examined using correlational analysis. The findings revealed a significant positive relationship between emotional intelligence and work commitment. Baron and Kenny’s step wise process was used to test the moderation effect of job demands-resources on the relationship between emotional intelligence and work commitment of millennial employees. Job demands-resources were found to moderate the relationship between emotional intelligence and millennial work commitment.

This study contributes to understanding millennials’ work commitment drivers and suggests implications for organizational practices and policy. The findings contribute to understanding the need for job analysis to determine the job demands and resources. The study also offers valuable insights into strategies organizations could adopt to bolster employee commitment, including fostering emotional intelligence and improving job demands- resources.

Keywords: Emotional intelligence, work commitment, job demands-resources, millennials, Telecommunications

INTRODUCTION

In today’s rapidly changing and competitive global business environment, organizations increasingly recognize the importance of understanding and enhancing employee work commitment. There are personal and organizational factors that influence work commitment including emotional intelligence and job demands-resources. In the telecommunications industry, work commitment is critical, given its dynamic nature and the need for engaged employees, many of whom belong to the millennial generation, to keep up with shifting customer needs and technological progress[1].

The telecommunication sector is one of the fastest-growing and most profitable sectors globally driven by increasing demand for communication services, advancements in technology, and the increasing reliance on communication networks. These technological advancements include the emergence of 5G networks, the Internet of Things (IoT), and artificial intelligence (AI) applications. In addition, the emergence of new players and disruptive technologies are challenging traditional ways of conducting business. These global trends have an immense impact on the telecommunication sector driving innovation, competition, market dynamics, and growth [2].

Regionally, within the African continent, the telecommunication sector has experienced significant growth and transformation characterized by unique trends and dynamics. These trends include market growth driven by a youthful population and urbanization that has created opportunities for increased mobile device penetration and digital service adoption. In addition, infrastructural development such as submarine cable projects and terrestrial fiber optic networks, aimed at expanding broadband connectivity has had a huge contribution to the growth of the sector[3].

Locally, the telecommunication sector in Kenya has played a pivotal role in driving economic development, connectivity, and innovation. The high mobile penetration rates coupled with the adoption of smartphones and mobile money services through M-pesa had contributed greatly to the growth of the sector[4], [5],[6].  It is against this backdrop of the global, regional, and local trends that this study sought to assess the role of emotional intelligence on work commitment among millennial workers who form the majority in the sector. In addition, the moderating role of job demands-resources on the relationship between emotional intelligence and work commitment was studied. Thus the objective of the study to determine the moderating effect of job demands-resources on the relationship between emotional intelligence and work commitment of millennial employees in the Kenyan telecommunication sector. Emotional intelligence which involves understanding of one’s emotions and those of others and managing them effectively, is a key individual characteristic that can impact work-related attitudes and behaviours[7]. Moreover, the Job Demands-Resources (JD-R) model has emerged as a theoretical framework to understand how job demands (such as workload and time pressure) and job resources (such as social support and autonomy) affect employee well-being and commitment[8].

LITERATURE REVIEW

Theoretical Framework

The origins of emotional intelligence theory can be tracked from the work of Thorn dike (1920) who posited that cognitive intelligence is insufficient in explaining human behaviour. He posited that human beings have different forms of intelligence including social intelligence. This view was upheld and advanced by Gadner (1983) who developed the theory of multiple intelligence published in his book Multiple Intelligences. In this theory, Gardner suggested that intelligence is not solely determined by cognitive abilities but also by other factors such as emotional and social skills. He thus introduced the concept of intrapersonal and interpersonal intelligence that formed the foundation for other models of EI[9].

Later, Salovey and Mayer introduced a concept of emotional intelligence which they defined as the ability to perceive, understand, manage, and use emotions effectively as a tool for guiding thinking and behaviour[10]. Goleman’s work (1995) popularized the construct of emotional intelligence in his research and publications in the field. Bradberry and Greaves (2009) advanced emotional intelligence theory in their work whose theme was to provide practical strategies for improving emotional intelligence in various aspects of life including the workplace. Boyatzis contributed to the theory of emotional intelligence and linked it to leadership. He emphasized the impact of emotional intelligence on effective leadership. In addition, he developed coaching methods to help leaders enhance their emotional intelligence [11]. Later Mckee collaborated with Boyatzis and Goleman in their work published in the book Primal Leadership: Realizing the Power of Emotional Intelligence. The work explored the impact of emotional intelligence on leadership effectiveness and organizational performance [12].

Job demands and resources theory (JD-R theory) is a framework that explains how job demands and resources affect employee well-being and job performance. The model developed by Bakker and Demerouti (2006) proposes that every job includes demands as well as resources that interact to affect employees’ engagement a component of work commitment, motivation and performance [13]. Job demands refer to physical, psychological, social, or organizational aspects of a job that require sustained effort and are therefore associated with certain physiological and psychological costs. These include workload, time pressure, emotional demands, physical demands, role ambiguity, work-family conflict, and job insecurity. These job demands can have a positive or negative effect on individual employee’s motivation depending on how they interplay with personal goals [14]. Job resources, on the other hand, are the physical, psychological, social, or organizational aspects of a job that help employees to achieve their work goals and reduce job demands. The job resources include autonomy, social support, feedback, skill variety, task significance, job control and career opportunities. It is worth noting that high job demands coupled with low resources can lead to negative work outcomes such as health complaints, while high job resources can motivate and enhance employee engagement thereby fostering positive organizational outcomes such as performance and commitment[8], [15],[16].

Empirical Review

Herr, Vianen, Bosle and Fischer (2021) conducted a study to examine the patterns of associations of job demands and resources with work engagement and mental health. The sample was drawn from the institute for Employment Establishment Panel using stratified sampling. The findings showed that job demands were negatively and job resources were positively correlated with work engagement and mental health[17].

Rai and Chawla (2022) conducted a study to explore the interrelationships among job resources, job demands, work and organization engagement of junior management grade 1 officers in 27 public sector banks in India. The findings showed that job demands moderated the relationship between job resources and work engagement. Work engagement was found to mediate the relationship between job resources and organization engagement [18]. Lambert, Qureshi, Holbrook, Frank and Hines (2022) conducted a study to examine the effect of workplace variables on organizational commitment using job demands-resources model. A sample of 163 correction officers from a prison in Haryana state in India participated in the study. The findings showed that job demands have no significant effect on organizational commitment. Conversely, the components of job resources considered in the study were found to be positively and significantly associated with organizational commitment[19].

Patience, De Braine and Dhanpat (2020) conducted a study to investigate the impact of job demands and job resources on work engagement of public and private sector nurses in Johannesburg, South Africa. A sample of 420 nurses were selected using purposeful sampling, majority of whom were females (88.8%) and from private sector (61.8%). The study utilized emotional labour scale, role conflict and ambiguity scale and exposure to workplace aggression to measure the job demands and job resources. In addition, work design questionnaire, organized career growth scale, leadership member exchange and Utrecht work engagement scale was used to measure work engagement. Regression analysis was used to determine which job demands and job resources could best predict the work engagement of nurses. The results showed that meaningful work contributed the largest variance in work engagement among nurses in both public and private sector. In addition, career advancement was associated with work engagement for both public and private sector nurses. While emotional demands imparted negatively on the engagement levels of public sector nurses, the study found that the nurses’ perceptions of meaningful work, leader-member exchange and career advancement enhanced their work engagement. The current study was conducted  in a different sector -the telecommunication sector – and a specific generational cohort -millennials- was considered [20].

METHODOLOGY

The present study is of cross sectional and descriptive-correlational design and utilized an online survey to collect data from millennials working in the International Gateway Operators (IGOs), a segment of Kenya’s telecommunication sector. The study’s target population comprised approximately 5234 individuals aged 23-43 years working in IGOs of Kenya’s telecommunication sector. The IGO sub-sector comprises organizations in the register of unified licensing framework licensees authorized to manage and operate infrastructure that connects Kenya’s telecommunication networks to the global telecommunications network. The IGO subsector of Kenya’s telecommunication sector was selected for the study because they comprise the top companies in the sector in terms of size and operations hence, they engage a sizeable number of millennial workers who form the unit of analysis for the study [21].

A sample of N=157 millennials were selected using random sampling technique.This sampling method was chosen to ensure the sample’s representativeness, reduce bias and enhance statistical validity of research findings. In addition, the technique enhances transparency, ease of implementation and generalizability of the study’s findings. Furthermore, employing simple random sampling enhanced the statistical validity of the research by facilitating the accurate application of various statistical techniques to analyze the data. Importantly, this sampling technique ensures transparency and fairness, affording every member of the population an equal opportunity to participate in the study[22], [23].

The research license was sought and obtained from the Government of Kenya and participants were expected to consent to participating in the study in order to proceed with the survey. A total of 157 online questionnaires were distributed to participants while 134 were received by the researcher yielding to a response rate of 85.4%. The questionnaire comprised of Schutte Self-Report Emotional Intelligence Test (SSEIT), Job Demand-Resources (JD-R) model and Morrow’s work commitment model to measure emotional intelligence, job demand and resources and work commitment respectively. The content validity of the questionnaire was approved by the supervisors and the reliability was confirmed using Cronbach alpha coefficient with the values α = 0.97, 0.93 and 0.97 for EI, JD-R and work commitment respectively showing that the instrument was reliable.

DATA ANALYSIS

To analyze data, descriptive tests and inferential statistics were carried out. The correlations between EI and work commitment were examined by Pearson’s correlation coefficient and an analysis of variance using IBM SPSS software (version 24). The Baron and Kenny process was used to test the moderation effect of JDR on the relationship between EI and work commitment.

RESULTS

In this study, a total of 134 millennials were involved. The demographics of the respondents are represented in table 1.

Table 1: Demographic Characteristics of the Study

The age of most of the participants was between 23-26 years old (41%) while the minority of the respondents age range was 35-38 years (7.5%) as shown in Table 1. In terms of educational level, the majority held bachelor’s degrees (74.6%) with 13.4% having master’s degrees, 6% having higher national diploma certifications and a minority of 1.5% each with a post-secondary certificate and doctorate degrees respectively. The results also indicated that most of the respondents were relatively new employees in their establishments between 0-3 years (64.2%) with the lowest having been engaged for between 4-6years (9.7%). As far as the employment terms are concerned, majority of the employees were engaged on permanent and pensionable terms (48.5%) followed closely by those on contractual terms (44.0%) with a minority (7.5%) engaged on casual terms.

The measures of emotional intelligence, job demands-resources and work commitment as determined by the study are represented in Table 2.

Table 2: Scores of Emotional Intelligence, Job Demands-Resources and Work Commitment (N=134)

The results from this research indicate that the mean EI score of the millennial employees was 4.01 and a standard deviation of 0.69 on a Likert scale of five levels showing an above average level of emotional intelligence of the participants. In addition, the job demands-resources indicated a mean of 3.47 and a standard deviation of 0.6 while work commitment showed a mean of 3.27 and a standard deviation of 0.8204. The results of the Pearson’s correlation coefficient also revealed that the age of the respondents is positively and weakly correlated with EI and JD-R at r=0.11 and 0.24 respectively and negatively correlated with work commitment r=-0.12. In addition, academic qualifications of the respondents were weakly correlated with EI and JD-R at r=0.11 and 0.17 respectively and negatively correlated with work commitment at r=-0.09.

The correlations among the three variables according to the findings of the study are represented in table 3.

Table 3: The Correlations Matrix

The results illustrated in Table 3 shows the relationships among the variables of the study- emotional intelligence, job demands-resources and work commitment- of millennials in Kenya’s telecommunication sector. The results show that individuals with higher levels of emotional intelligence tend to perceive higher job demands and resources (r=0.23, p< 0.05). Emotional intelligence was also positively correlated to work commitment, and statistically significant (r = 0.160, p < 0.05). Moreover, there is a statistically positive correlation between job demands-resources and work commitment (r = 0.493, p < 0.05). This reveals that individuals perceiving higher job demands-resources are more committed to their work.

The results of the moderating effect of job demands-resources on the relationship between emotional intelligence and work commitment of millennials in Kenya’s telecommunication sector are presented in table 4.

Table 4: Results of Regression Analysis for Moderating Effect of Job Demands-Resources on the Relationship between Emotional Intelligence and Work Commitment

1. Dependent Variable: Work Commitment
2. Predictors: (Constant), Emotional Intelligence
3. Predictors: (Constant), Emotional Intelligence, Job Demands-Resources
4. Predictors: (Constant), Emotional Intelligence, Job Demands-Resources, Interaction (EI*JDR)

Table 4 shows that the relationship among emotional intelligence, job demands-resources and work commitment is moderate (r=0.495). With the introduction of the interaction term, the Pearson correlation coefficient, r, increased from 0.495 to 0.499 and the F-ratio increased from 3.471 to 14.351. These findings imply that job demand-resources moderated the relationship between emotional intelligence and work commitment of millennial employees in Kenya’s telecommunication sector. The predictive model obtained from the results can be presented as follows:

Y=-1.345+0.539X1+1.267X2-0.137X1*X2+ε  where Y is work commitment, X1 is emotional intelligence, X2 is job demands-resources and ε is the error term.

DISCUSSIONS

The objective of the study was to determine the moderating effect of job demands-resources on the relationship between emotional intelligence and work commitment of millennial employees in Kenya’s telecommunication sector. The hypothesis of the studystated in the null form was that there is no significant moderating effect of job demands-resources on the relationship between emotional intelligence and work commitment of the millennial employees in the Kenyan telecommunication sector. Stepwise regression analysis was used to test the hypothesis. The moderating effect of job demands-resources on the relationship between emotional intelligence and work commitment was assessed, and results explained using coefficient of determination (R-Square), Analysis of Variance (ANOVA) and the regression coefficients. Hierarchical regression analysis was performed with an interaction term (a product of emotional intelligence and job demands-resources) introduced as an additional predictor.

Results indicated that the p value of the interaction term (EI * JD-R) was p = 0.000 <  0.05 and the R square increased from 2.6%, to 24.9% after the interaction term was included in the model and thus, job demands-resources moderates the relationship between emotional intelligence and work commitment of millennial employees in Kenya’s telecommunication sector. The study thus rejected the null hypothesis and adopted the alternative hypothesis that there is a significant moderating effect of job demands-resources on the relationship between emotional intelligence and work commitment of millennial employees in Kenya’s telecommunication sector.

The results of the study agreed with another study conducted by Herr, Vianen, Bosle and Fischer (2021) to examine the patterns of associations of job demands and resources with work engagement and mental health. The sample was drawn from the institute for Employment Establishment Panel using stratified sampling. The findings showed that job demands were negatively and job resources were positively correlated with work engagement and mental health[17]. Moreover, the study also agreed with another study conducted by Rai and Chawla (2022) to explore the interrelationships among job resources, job demands, work and organization engagement of junior management grade 1 officers in 27 public sector banks in India. The findings showed that job demands moderated the relationship between job resources and work engagement. Work engagement was found to mediate the relationship between job resources and organization engagement [18].

The results also agreed with the results of a study conducted by Lambert, Qureshi, Holbrook, Frank and Hines (2022) to examine the effect of workplace variables on organizational commitment using job demands-resources model. The findings showed that job demands have no significant effect on organizational commitment. Conversely, the components of job resources considered in the study were found to be positively and significantly associated with organizational commitment[19]. The study also agreed with the findings of research conducted by Patience, De Braine and Dhanpat (2020) to investigate the impact of job demands and job resources on work engagement of public and private sector nurses in Johannesburg, South Africa. The results showed that meaningful work contributed the largest variance in work engagement among nurses in both public and private sector. In addition, career advancement was associated with work engagement for both public and private sector nurses. While emotional demands imparted negatively on the engagement levels of public sector nurses, the study found that the nurses’ perceptions of meaningful work, leader-member exchange and career advancement enhanced their work engagement[20].

CONCLUSIONS

The study’s findings strongly supported the theoretical framework. The research investigated the interplay between emotional intelligence and job demands-resources, and their impact on the millennial work commitment within the context of Kenya’s telecommunication sector. Through a comprehensive analysis of survey data collected from employees in this sector, several key insights have been established that contribute to both theoretical understanding and practical implications. The findings of the study provided robust support for the hypothesized relationships. Firstly, it was established that emotional intelligence is a significant predictor of millennial work commitment. This highlights the importance of individuals’ ability to understand and regulate their own emotions as well as those of others in fostering commitment to their work roles. It is worth noting that emotional intelligence skills can be developed through training and practice. Secondly, the analysis revealed that job demands-resources have a moderating effect in shaping the relationship between emotional intelligence and work commitment among millennials. Precisely, favorable job demands, and adequate resources were found to enhance the positive impact of emotional intelligence on work commitment, emphasizing the importance of organizational support and conducive work environments. Organizational leadership ought to put emphasis on job analysis, systematically gathering information about a job by analyzing its tasks, duties, responsibilities, and requirements seek feedback from the employees with the aim of identifying the job demands and resources. The baseline of the job demands, and job resources established will offer the foundation for action.

RECOMMENDATONS FOR FURTHER RESEARCH

Further research in this field would be necessary in the following areas. A study to investigate how the relationships among emotional intelligence, job demands resources and work commitment vary across the different generational cohorts within the telecommunication sector in Kenya. This would help compare the attitudes and experiences of millennials with those of older generations (generation X and baby boomers) with the aim of understanding how generational differences influence work commitment and engagement. Studies may also be conducted to extend research in other sectors within Kenya and beyond to examine generalizability of findings beyond telecommunication sector. Lastly future research should also include factors such as economic conditions, organizational culture, or technological advancements that might also influence work commitment.

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