Leadership Practices and Work Engagement in Higher Education: The Mediating Role of Job Demands-Resources

Abstract

There has been extensive research on leadership and work engagement, but little is known concerning leadership practices and work engagement levels in higher education in Namibia. This study examines leadership practices and work engagement in higher education, as well as the mediating role of job demands and job resources in the link. A quantitative approach was adopted following an explanatory research design to explain the mediating roles of job demands and resources in the interplay between leadership practices and work engagement. A combination of sampling strategies (stratified, convenience, and purposive sampling) was adopted to draw a sample of 450 respondents from different groups of employees within the target population of the study. The primary data was collected through an online survey, which was formatted using the Likert-type rating scale. Quantitative data was analyzed using structural equation modelling via SmartPLS Version 3.3.9. Leadership practices have significant relationships with both job demands and resources. On the other hand, job demands have a significant positive relationship with work engagement, but job resources exert no significant effect on work engagement levels. Therefore, the relationship between leadership practices and work engagement was fully mediated by job demands in higher education.

Keywords

higher education job demands job resources leadership work engagement

Introduction

Leadership, especially on the executive level, is an important ingredient of organizational sustainability in a highly dynamic and unpredictable global business environment (Hsieh & Wang, 2015). Particularly, positive leadership has been linked to important indicators of employee wellbeing such as employee engagement (Decuypere & Schaufeli, 2020; Hsieh & Wang, 2015) in various domains such as vigor, dedication, absorption, and health (Bakker & Leiter, 2017). In fact, leadership is viewed as “one of the single biggest factors contributing to employee work engagement” (Hsieh & Wang, 2015, p. 2332). In a modern society punctuated by globalization, high employee mobility, and industrial volatility, it is unsurprising that concerns around the influence of leadership on employee engagement continue to pervade scholarly discourse. As a result, there has been widespread interest from practitioners and scholars in the interrelationship between leadership and employee work engagement.

Work engagement is becoming more important due to its effect on employees and organizational performance. Work engagement can be described as a person’s feeling of purpose and focused energy that is demonstrated by their personal initiative, flexibility, effort, and persistence in the direction of organizational goals (Schaufeli, 2013). An engaged employee is deeply ingrained and has an innate sense of dedication, pride, and loyalty that is difficult to alter (Decuypere & Schaufeli, 2020; Macey et al., 2011; Marciano, 2010). Such employees cultivate positive working relationships in the organization by providing excellent services for customer satisfaction, offering suggestions to enhance performance, being devoted to the strategic goals, and acting as brand ambassadors (Bakker, 2011; Lavigna & Basso, 2020). Employees who are engaged are more likely to do well in their jobs, help their co-workers, and showcase their commitment to the organization.

Despite extensive research on leadership (Lee et al., 2019; Mansoor et al., 2021; Mehmood et al., 2016; Posner, 2016; Tims et al., 2011; Tuckey et al., 2012) and work engagement (Bhuvanaiah & Raya, 2014; Breevaart et al., 2014; Schaufeli, 2013; Swarnalatha & Prasanna, 2013), little is known concerning the mediating role of job demands on the relationship between leadership practices and work engagement levels in higher education. This vacuity in the body of knowledge is even more pronounced in the developing world, with the bulk of the extant literature originating from the Global North. This is despite the fact that leadership and its associated behaviors are culture-bound, and Global North and Global South cultural orientations differ (Akanji et al., 2020). For example, empirical studies conducted in the Global North reveal that leadership effectiveness exerts a significant positive influence on work engagement through affective, behavioral, and cognitive pathways (Decuypere & Schaufeli, 2020; Kahn, 1990; Shaughnessy et al., 2018). While there is a dearth of empirical studies establishing the relationship between leadership practices and work engagement in higher education institutions in developing countries. This empirical gap should be addressed since context and realities matter in social and management science research. Therefore, this study examines leadership practices and work engagement in higher education in Namibia, as well as the mediating role of job demands and job resources in the link.

The following sections of this paper focus on theoretical perspectives, a literature review on leadership practices, job demands, job resources, and work engagement. The subsequent section unpacks the research method, data collection, and data analysis procedures adopted for the study. Thereafter, we present the results and provide a discussion of findings, pointing out the theoretical and practical implications of the study. In the last section, we point out the limitations of the study and propose further research directions, as well as the conclusion.

Background Theory

The theories explicating variables under investigation are behavioral leadership theory (Blake & McCanse, 1991; Cartwright & Zander, 1970; Hemphill & Coons, 1957), job demands-resources (JD-R) theory (Bakker & Demerouti, 2014), and work engagement theory (Kahn, 1990). Behavioral leadership theory argues that the success of a leader is based on actions and behaviors exhibited to influence subordinates and ensure organizational behavior effectiveness rather than personal attributes (De Jong & Den Hartog, 2007). The behavioral theory holds that leaders can exhibit leadership behaviors to influence their followers toward the accomplishment of common goals. The implication is that different leadership behaviors or styles can be inculcated through executive development interventions for leadership effectiveness. Thus, leadership practices (Kouzes & Posner, 2012; Posner, 2016) such as modelling the way, inspiring a shared vision, challenging the process, enabling others to act and encouraging the heart of excellent service delivery in higher education can be explained by behavioral leadership theory.

The JD-R model is an established theory in industrial psychology (Bakker & Demerouti, 2014; Stander et al., 2015). According to the model, all job roles are comprised of a set of demands and resources (Bakker & Demerouti, 2014; Bakker et al., 2011; Schaufeli & Bakker, 2004). Job demands constitute job elements that require psychological, physical, social, or organizational strain (Stander et al., 2015). Job resources, on the other end, include capitals that assist individuals to effectively accomplish tasks and be more active in their job roles (Bakker & Demerouti, 2007, 2014; Stander et al., 2015). Job resources can effectively mitigate against the effects of job demands and include physical, social, or organizational elements of a job role that allow the incumbent to achieve the desired personal and organizational outcomes (Bakker & Demerouti, 2007; Bakker et al., 2020). Therefore, the JD-R model is the theoretical framework underpinning the use of job demands and resources as mediators in the model, explaining the relationship between leadership practices and work engagement in higher education.

Kahn opines that human behaviors may showcase combinations of personal engagement and disengagement. Personal engagement is the concurrent employment and manifestation of a person’s (preferred self) in job behaviors that provide support for work and interpersonal relationships in the world of work, as well as one’s physical, cognitive, and emotional presence to enhance performance (Huang et al., 2022; Kahn, 1990; Schaufeli, 2013). Personal disengagement on the other hand, has to do with a concurrent withdrawal and defense of one’s preferred self through actions that encourage the absence of interpersonal relationships in the workplace, as well as one’s physical, cognitive, and emotional absence or passive involvement in organizational activities (Huang et al., 2022; Kahn, 1990). Consequently, we believe that work engagement theory provides the required insights to examine the influence of leadership practices on employee work engagement levels in higher education institutions in Namibia. The mediating roles of job demands and resources were observed in the interplay between leadership practices and work engagement in higher education using variance-based structural equation modeling.

Leadership Practices

Leadership is about creating a way for people to contribute to making something extraordinary happen (Kouzes & Posner, 2012; Posner, 2016). After many years of research, Kouzes and Posner, identified five leadership characteristics through best-practice leadership experiences. The research was based on the experiences of world-known leaders and their trials and tribulations to get employees to believe in their organizations again. After observing the staff's lack of motivation and perceived low work engagement levels, the leaders adopted new sets of practices to address the organizational problems. The practices followed by these leaders have led to remarkable changes in staff attitudes toward achieving more than expected. The five exemplary leadership practices from previous studies are analyzed below.

Model the Way

This practice implies that the leader should model the way for teams to act, follow, perceive, and perform. Vito et al. (2014) advise that leaders should find their voice by clarifying their own values because those values influence how leaders respond to their followers’ needs for engagement. Expressing genuine values should seek to empower and motivate followers to accomplish common goals. It further shows the competence of the leaders by demonstrating their ability to act in alignment with their expressed values. This practice sets an example for followers and helps build confidence and consensus among them (Decuypere & Schaufeli, 2020). Leaders can also strengthen values through sharing stories and bringing values to life.

Inspire a Shared Vision

This practice implies that in order to bring the said vision to life, the leader can create exciting and enabling opportunities for the subordinates (Kouzes & Posner, 2012; Posner, 2016). This requires that leaders bring their vision to life by appealing to the shared aspirations of their followers, and not just the visions and missions that management has come up with. In the case of higher education in Namibia, this can be cascaded down to the departmental levels, where a leader should demonstrate active listening skills to ascertain the aspirations of subordinates and inspire them to align their aspirations with the broader organizational vision.

Challenge the Process

The third practice states that, if the followers believe in the shared vision, the leader will be able to take any initiative and improve the organization with the followers’ active participation (Kouzes & Posner, 2012). Leaders embracing this practice seek inventive ways to alter, grow, and improve subordinates’ creativity (Vito et al., 2014). Leaders push their followers to try new things and sponsor their courage to take chances and seek out opportunities for change (Posner, 2016). If the followers believe in the shared goal, the leader can take advantage of the opportunity to improve the organization with the followers’ active participation. Leaders embracing this practice can encourage their followers to challenge the status-quo, explore more creative ways of doing things, and take calculated risks to raise more change agents.

Enable Others to Act

Leaders who enable others to act have faith in their subordinates’ ability to execute duties efficiently (Kouzes & Posner, 2012). They do not desire power or status, and they understand that followers must feel compelled to act or perform their responsibilities based on their work ethics as professionals (Posner, 2016). Leaders encourage collaboration by building organizational trust and joint goals. They motivate their followers to solve their own problems, resulting in the development of transactional and transformational leadership skills.

Encourage the Heart

Effective leaders must encourage with their hearts, and when the team or followers grow disheartened, the leader should be able to do something personal for subordinates to encourage them (Kouzes & Posner, 2012). Taking the time to ask how your team is doing or if they have any issues is an example of such an act. Occupying a leadership position does not necessarily mean such a person possesses the qualities of an exemplary leader. Outstanding leaders are developed over time through hard work and experience, and they should also receive support and encouragement through leadership development interventions. Another point raised by Kouzes and Posner is that every decision is a test of character, in which what you say must match with what people observe (Kouzes & Posner, 2012; Posner, 2016). This is what makes a person occupying such a position an authentic leader.

The practices analyzed in this section apply not only to leaders but to any member of the work group who wants to make a difference in the workplace. To be successful in today’s workplace, doing things the same way is unlikely to yield any significantly improved results. To the best of our knowledge, the literature on leadership and its influence on employee work engagement is non-existent in Namibia. Changes in the global business environment should push leaders in various workplaces to innovate and adjust with the times, or they risk being left behind and lacking sustainability. Consequently, this necessitates research to keep up with the changes in the highly dynamic contemporary environment, which is subject to various environmental influences.

Leadership Practices and Work Engagement

Various recent studies showcase a positive relationship between leadership and employee work engagement (Decuypere & Schaufeli, 2020; Nikolova et al., 2019; Shaughnessy et al., 2018). Effective leadership exerts a positive influence on work engagement through affective, behavioral, and cognitive pathways (Decuypere & Schaufeli, 2020; Kahn, 1990). A study conducted by Shaughnessy et al. (2018) also found a positive relationship between leadership practices and work engagement. The study indicated that the leaders surveyed fell short in inspiring a shared vision and were risk-averse, thus leading to low levels of work engagement, especially in the areas of vigor and absorption. An exemplary leader should be able to assess the psychosocial aspects of work to improve employee well-being (X. Li et al., 2022), drive productivity (Bhuvanaiah & Raya, 2014), and provide a competitive advantage (Swarnalatha & Prasanna, 2013). Hence, employee work engagement is essential in order to drive organizational performance.

Work engagement can be influenced by leaders not just by improving work conditions, but also by inspiring, connecting, and receiving support from their colleagues (Nikolova et al., 2019). Work engagement is linked to employee health and turnover intentions, organizational commitment, personal initiative, and willingness to go the extra mile for the company, as well as employee performance (Schaufeli & Bakker, 2010). Furthermore, longitudinal studies have connected a variety of positive leadership styles to employee work engagement (Biggs et al., 2014; Chughtai, 2014; A. N. Li & Liao, 2014; Mehmood et al., 2016). For example, transformational leadership has proven to have the most positive effect on employee engagement (Al-Amin, 2017; Tims et al., 2011). The reason is that transformational leaders influence employee work engagement by modeling the way, inspiring a shared vision, challenging the process, and enabling others to act with an encouraging heart (Carasco-Saul et al., 2015). Transformational leaders raise their followers’ optimism, accountability, meaningfulness, and innovative activity to achieve strategic objectives. Moreover, positive leadership styles enhance employees’ engagement directly and indirectly by increasing job resources and reducing job demands (Schaufeli, 2015; Schaufeli & Bakker, 2004).

Job Demands

Job demands refer to any work-related stresses and expectations or duties that are required of an employee. Job demands can be defined as “those physical, social, or organizational aspects of the job that require sustained physical or mental effort and are therefore associated with certain physiological and psychological costs” (Demerouti et al., 2001, p. 501). This could include factors like deadlines, workload, and emotional pressure. Such work pressures have a negative influence on employees’ work-life balance (Balogun & Afolabi, 2019). Job demands, as well as job and personal resources, activate separate processes, according to JD-R theory (Demerouti et al., 2001). Moreover, job demands such as high work pressure, emotional demands, and position ambiguity can cause sleep issues, tiredness, and poor health (Bakker & Demerouti, 2007). The implication is that if job demands are not properly managed, it could lead to stress and burnout. While Bakker et al. (2005) examined the effect of job resources as a buffer to reduce the impact of job demands on burnout in higher education, this study examines the mediating role of job demands on the relationship between leadership practices and work engagement in higher education.

Job Resources

Job resources are beneficial to employees in achieving their professional goals, encouraging their personal growth and development, and improving their overall well-being (Bakker, 2010). Contrary to job demands, resources can serve as a motivating process, having a lot of job resources can lead to higher motivation and better work engagement (Bakker & Demerouti, 2014). Despite extensive work on JD-R theory (Bakker & Demerouti, 2007, 2014; Bakker et al., 2005, 2011; Demerouti et al., 2001), engaging leadership in the JD-R model (Decuypere & Schaufeli, 2020; Nikolova et al., 2019; Schaufeli, 2015; Shaughnessy et al., 2018; Tuckey et al., 2012), and work engagement (Kahn, 1990; Schaufeli & Bakker, 2010; Schaufeli et al., 2002; Shaughnessy et al., 2018), there is a paucity of research examining the mediating role of job resources on the relationship between leadership practices and work engagement in higher education in Namibia. These relationships should be investigated in the African context to extend the body of knowledge regarding the mediating influence of job resources on the interplay between leadership practices and work engagement in the higher education system. To address this gap, we examined the mediating role of job resources in the relationship between leadership practices and work engagement in higher education.

Research Model and Hypotheses Development

The research model examines the mediating roles of job demands and resources on the relationship between leadership practices and work engagement levels in higher education in Namibia. As indicated in Figure 1, leadership practices (model, inspire, enable, encourage, and challenge) are exogenous latent variables investigated in higher education in Namibia. Job demands (stress levels and emotional demands) and resources (support at work and the company’s commitment) are the mediating variables investigated in this study. Work engagement (vigor, dedication, and absorption) on the other hand, is the endogenous latent variable.

Figure 1.

Leadership practices and work engagement in higher education.

Based on an extensive literature review and the research model presented in Figure 1, we hypothesized as follows:

H1 Leadership practices have a significant effect on job demands in higher education in Namibia.

H2 Leadership practices have a significant effect on job resources in higher education in Namibia.

H3 Job demands have a significant effect on work engagement in higher education in Namibia.

H4 Job resources have a significant effect on work engagement in higher education in Namibia.

H5 Leadership practices affect work engagement levels in higher education in Namibia.

H6 Job demands mediate the relationship between leadership practices and work engagement in higher education in Namibia.

H7 Job resources mediate the relationship between leadership practices and work engagement in higher education in Namibia.

Methodology

A post-positivist research paradigm was adopted using a quantitative approach to test the hypotheses developed in this study. An explanatory research design was adopted following a cross-sectional survey to gather relevant information from the respondents (participants occupying leadership positions and their subordinates) in higher education in Namibia.

Research Procedure and Participants

The population for this study were executives and their subordinates in the academic, technical, and administrative staff categories in higher education institutions in Namibia. The estimated number of employees in the participating higher education was 1008. A stratified convenience sampling technique was adopted in accordance with the ethical guidelines in social science research involving humans. The stratified convenience sampling strategy is instrumental in ensuring that only respondents who were interested in participating in the study from each stratum were provided the survey link to complete the survey. The participants in different staff categories were contacted via email from the Human Resources (HR) departments. The survey introduction letter included informed consent. A polite reminder at regular intervals was sent from the HR department to reach an acceptable response rate. A total of 450 respondents completed the online survey in 3 months. The 450 responses were collected from staff members who were working on-site and remotely (the hybrid category). The reason is that higher education institutions in Namibia have realized the positive influence of such flexible work arrangements on employees’ engagement and productivity during the pandemic (Atiku et al., 2020). Items concerning the demographic details of respondents were excluded from the questionnaire to protect the anonymity and confidentiality of our respondents.

Questionnaire Design and Measures

Leadership practices in higher education were measured using the Leadership Inventory Practices questionnaire (LPI) (Kouzes & Posner, 1987), developed by Kouzes and Posner. The LPI contains 30 items that measure the five practices of exemplary leadership (model, inspire, enable, encourage, and challenge), and respondents were asked to rate their supervisors on a 10-point (“almost never” to “almost always”) scale using a Likert-type rating scale. Job demands and job resources in higher education were measured using the Copenhagen Psychosocial Questionnaire (COPSOQ 1), which was developed in 1997 (Pejtersen et al., 2010). The scale contains 43 items measuring job demands and resources using a five-point (“0–never” to “4–always”) Likert-type rating scale. Work engagement in higher education was measured using the Utrecht Work Engagement Survey (UWES), developed by Schaufeli and Bakker (2004). The survey contained 17 items measuring the three dimensions of work engagement (vigor, dedication, and absorption) using a seven-point (“0–never” to “6–always”) Likert-type rating scale. The scale was adapted in this study using 11 items, of which four measured vigor, the other four were instrumental in measuring dedication, and the remaining three items measured absorption among staff members in higher education in Namibia.

Data Analysis

The quantitative data collected in this study was analyzed using descriptive and inferential statistics. The data was downloaded and saved as a CSV (comma-delimited) file. The CSV file was imported into SmartPLS version 3.3.9 (Hair et al., 2012; Ringle et al., 2015) for descriptive statistical analyses using the mean scores and standard deviation. The psychometric property of the research instrument was established using the Cronbach’s alpha coefficient, average variance extracted (AVE), square root of AVE, and Fornell–Larcker criterion, as well as heterotrait-Monotrait (HTMT) ratio of correlations to establish the reliability and validity of the research instrument. The inferential statistics such as variance-based structural equation modeling (Hair et al., 2021) was used to examine the mediating role of job demands and resources on the association between leadership practices and work engagement levels in higher education in Namibia.

Results

The measurement scales adapted for measuring all the constructs investigated in this study are sub-dimensional, which suggests the need to perform second-order confirmatory factor analysis (Milfont & Duckitt, 2004). The following factors and items were removed from the measurement model during second-order confirmatory factor analysis due to the low factor loadings for convergent and discriminant validity. According to the rule of thumb, the AVE value should be greater than 0.5 to establish the convergent validity of each construct (Hair et al., 2021). The items measuring work demands were removed from the model. Hence, job demands were assessed using items measuring emotional demands and stress levels. An item was deleted from stress levels (SL3), as well as support at work (SW5). The factor loadings and AVE values for all latent variables investigated are provided in Table 1.

Table 1.

Reliability and Convergent Validity of the Reflective Latent Variables.

Second-order CFA	Variables	Indicators	Loadings	Mean	SD	CA	CR	AVE
Leadership practices	Model	M1	0.843	0.842	0.030	.989	0.989	0.757
		M2	0.831	0.830	0.033
		M3	0.856	0.854	0.028
		M4	0.847	0.848	0.037
		M5	0.920	0.920	0.021
		M6	0.957	0.957	0.012
	Inspire	I1	0.929	0.928	0.021
		I2	0.953	0.952	0.017
		I3	0.921	0.920	0.019
		I4	0.941	0.941	0.013
		I5	0.944	0.944	0.012
		I6	0.953	0.953	0.011
	Enable	E1	0.917	0.916	0.020
		E2	0.917	0.916	0.021
		E3	0.844	0.843	0.033
		E4	0.921	0.921	0.020
		E5	0.847	0.846	0.031
		E6	0.924	0.923	0.022
	Encourage	EH1	0.882	0.881	0.023
		EH2	0.867	0.865	0.029
		EH3	0.963	0.962	0.015
		EH4	0.975	0.975	0.011
		EH5	0.943	0.943	0.015
		EH6	0.946	0.945	0.017
	Challenge	C1	0.896	0.894	0.025
		C2	0.922	0.921	0.018
		C3	0.926	0.925	0.018
		C4	0.943	0.942	0.015
		C5	0.934	0.934	0.015
		C6	0.943	0.942	0.016
Job demands	Stress levels	SL1	0.839	0.836	0.038	.849	0.911	0.633
		SL2	0.886	0.883	0.029
		SL4	0.874	0.874	0.029
	Emotional demands	ED1	0.717	0.712	0.067
		ED2	0.731	0.728	0.074
		ED3	0.705	0.705	0.074
Job resources	Support at work	SW1	0.755	0.746	0.064	.942	0.948	0.550
		SW2	0.783	0.778	0.057
		SW3	0.841	0.834	0.042
		SW4	0.667	0.658	0.075
		SW6	0.803	0.799	0.040
		SW7	0.812	0.808	0.035
		SW8	0.676	0.669	0.062
		SW9	0.714	0.708	0.053
	Company commitment	CC1	0.640	0.640	0.052
		CC2	0.710	0.713	0.057
		CC3	0.587	0.594	0.079
		CC4	0.755	0.757	0.037
		CC5	0.782	0.772	0.052
		CC6	0.803	0.794	0.049
		CC7	0.751	0.741	0.055
Work engagement	Vigor	V2	0.845	0.844	0.043	.927	0.929	0.543
		V3	0.866	0.867	0.034
		V4	0.786	0.786	0.050
		V1	0.732	0.730	0.054
	Dedication	D1	0.876	0.875	0.033
		D2	0.861	0.860	0.034
		D3	0.919	0.918	0.024
		D4	0.903	0.901	0.024
	Absorption	A1	0.780	0.775	0.049
		A2	0.657	0.649	0.076
		A3	0.751	0.748	0.067

Note. CA = Cronbach’s alpha; CR = composite reliability; AVE = average variance extracted.

The factor loadings for reflective latent variables reported in Table 1 ranged from 0.640 to 0.953. There is no gainsaying that all factors loaded considerably well, which also accounted for the AVE values greater than 0.5. The AVE values in Table 1 ranged from 0.543 to 0.757. The value of AVE must be greater than 0.5 to establish convergent validity (Hair et al., 2021). Since the AVE values reported in this study are greater than the threshold of 0.5, the convergent validity of the key constructs investigated in this study was established. The composite reliability coefficients of the key latent variable ranged from 0.911 to 0.989. The Cronbach’s alpha coefficients of the latent variables ranged from 0.849 to 0.989, which ascertained the internal consistency of the measurement scales used in this study. Discriminant validity for the reflective latent variables is reported in Table 2.

Table 2.

Discriminant Validity of Latent Variables and Collinearity Evaluation.

Discriminant validity of latent variables by Fornell–Larcker’s criterion
Latent variable	JD	JR	LP	WE
Job demands (JD)	0.796
Job resources (JR)	0.797	0.742
Leadership practices (LP)	0.528	0.641	0.870
Work engagement (WE)	0.596	0.436	0.366	0.737
Note: Diagonals are the square roots of AVE.
Discriminant validity evaluation for the reflective variables by HTMT criterion
Latent variable	JD	JR	LP	WE
Job resources (JR)	0.804
Leadership practices (LP)	0.529	0.638
Work engagement (WE)	0.597	0.442	0.363
Collinearity evaluation between the predictor constructs by inner VIF values
Latent variable	JD	JR	WE
Leadership practices (LP)	1.000	1.000	1.699
Job demands (JD)			2.739
Job resources (JR)			3.353

Note. Diagonal elements in bold are the square roots of the Average Variance Extracted (AVE).

As shown in Table 2, the discriminant validity of the latent variables was statistically verified using Fornell–Larcker’s criterion (Fornell & Larcker, 1981; Hair et al., 2021) and HTMT ratios (Henseler et al., 2015). In line with guidelines provided by Fornell and Larcker, the square roots of AVE values are greater than the inter-construct correlations, which is an indication that discriminate validity was established in this study. The HTMT ratio is another criterion used in ascertaining discriminate validity by observing the similarity between predictor variables, which means that if the ratio is less than one, discriminant validity is established in the study (Henseler et al., 2015). The HTMT ratios reported in Table 2 are less than the cut-off value of one. Therefore, the discriminant validity of the key constructs investigated in this study was established. The multi-collinearity evaluation of predictor variables was examined using variance inflation factor (VIF) scores for all construct combinations reported in Table 2. The VIF values ranged from 1.000 to 3.353, which indicated that no multi-collinearity issues were found among predictor variables since the VIF values were less than 5 (Becker et al., 2015). The fitness of the measurement and structural models were ascertained in this study using the Standardised Root Mean Square Residual (SRMR) and Normed Fit Index (NFI). The SRMR value (0.06) of the estimated model was less than the threshold of 0.08 (Henseler et al., 2016), which is an indication of a good fit. Statistically, the NFI value (0.94) was also greater than 0.9, which represents an acceptable fit (Bentler, 1990; Ramayah et al., 2017). The results of path analyses conducted in this study using variance-based Structural Equation Modelling (SEM) are depicted in Figure 2.

Figure 2.

Structural model for leadership practices and work engagement in higher education.

As illustrated in Figure 2, the structural model revealed that leadership practices exert a significant direct effect on job demands (β = .528, p < .001, n = 450). Therefore, the research hypothesis one was supported in this study since the p value is less than .05. The implication of this result is that leadership practices have a significant positive influence on job demands in higher education. The results revealed that leadership practices exert a significant direct effect on job resources (β = .641, p < .001, n = 450). The research hypothesis two was also supported since the p value is less than .05. The implication of this result is that leadership practices have a significant positive influence on job resources in higher education.

The third research hypothesis was formulated to test the effect of job demands on work engagement levels in higher education. The results showed that job demands have a significant effect on work engagement (β = .675, p < .01, n = 450) levels in higher education. Hypothesis three was supported considering the p value reported. The implication is that job demands have a significant effect on work engagement levels in higher education. Job resources, on the other hand, exert no significant influence on work engagement (β = −.183, p > .05, n = 450) levels in higher education. Based on our findings, research hypothesis four (4) was not supported. Hence, the job resources offered by leadership in higher education exert no significant effect on employees’ work engagement levels. Statistically, the results revealed that leadership practices exert no significant direct effects on work engagement (β = .128, p > .05, n = 450) in higher education. Therefore, hypothesis five was not supported since leadership practices exert no significant direct effect on work engagement levels in higher education. The mediating role of job demands was established in this study using the specific indirect effects reported in Table 3.

Table 3.

Direct and Indirect Effects of Reflective Latent Variables.

Hypo	Directs	M	SD	Coeff.	T Stat	p Value	Decision
H1	Leadership practices → Job demands	0.528	0.072	0.528	7.321	.000	Supported
H2	Leadership practices → Job resources	0.649	0.081	0.641	7.899	.000	Supported
H3	Job demands → Work engagement	0.659	0.197	0.675	3.431	.001	Supported
H4	Job resources → Work engagement	−0.138	0.278	−0.183	0.658	.511	Not supported
H5	Leadership practices → Work engagement	0.096	0.130	0.128	0.979	.328	Not supported
Specific indirect effects
H6	Leadership practices → Job demands → Work engagement	0.346	0.111	0.356	3.211	.001	Supported
H7	Leadership practices → Job resources → Work engagement	−0.078	0.175	−0.117	0.670	.503	Not supported

Source. Emerged from statistical analysis.

The empirical evidence indicated in Table 3 revealed that job demands mediate the relationship between leadership practices and work engagement (β = .356, p < .01, n = 450). Hence, the hypothesis six was supported since job demands mediate the relationship between leadership practices and work engagement levels in higher education. The implication of our findings is that the relationship between leadership practices and employee work engagement was fully mediated by job demands in higher education. Conversely, the empirical evidence showed that job resources exert no significant indirect effects on employee work engagement (β = −.177, p > .05, n = 450). levels in higher education. The research hypothesis seven was not supported since job resources do not mediate the relationship between leadership practices and work engagement levels of employees in higher education.

Discussion and Implications

Despite numerous studies establishing the link between leadership practices, job demands-resources and work engagement (Bakker, 2011; Bakker & Leiter, 2017; Cheung et al., 2021; Giusino et al., 2022; Lovelace et al., 2007; Sandhåland et al., 2017; Seljemo et al., 2020; Tims et al., 2011), such studies have overlooked the mediating role of job demands and resources on the link between leadership practices and work engagement levels in higher education. The theoretical implication of this study is based on the fact that job demands mediate the relationship between leadership practices and work engagement in higher education. This study suggests that leadership practices (Posner, 2016; Schaufeli, 2015), the job demands and resources model (Bakker & Demerouti, 2014), and the evidence-based model of work engagement (Bakker, 2011) can be unified based on the empirical evidence reported in Figure 2. For example, job demands-resources theory (Bakker & Demerouti, 2017) can be extended by incorporating leadership practices and work engagement in the model to examine the mediating role of job demands and job resources on the link.

A significant positive relationship was established between leadership practices and job demands in higher education. This result corresponds to previous studies establishing the link between leadership practices and job demands (Sandhåland et al., 2017; Seljemo et al., 2020). While the study conducted by Sandhåland et al. (2017) focused on leadership practices and job demands among workers on offshore vessels, the current study established the link between leadership and job demands in higher education. The study conducted by Seljemo et al. (2020) on the link between the constructs was based on data collected from health care professionals. Conversely, Schaufeli (2015) found a significant negative relationship between leadership and job demands based on a survey of a Dutch workforce. Our findings contextualizing leadership practices and job demands in the Namibian higher education system revealed a significant positive relationship. Bakker et al. (2005) only examined the effect of job resources as a buffer to reduce the impact of job demands on burnout in higher education. This study is unique in showcasing the mediating influence of job demands on the relationship between leadership practices and work engagement in higher education. The results showed that job demands mediate the relationship between leadership practices and employee work engagement in higher education.

Statistically, a positive relationship was found between leadership practices and job resources in higher education. This research coroborates the findings of a study (Balwant et al., 2019) conducted in the Trinidad and Tobago’s service industry that established a significant positive relationship between transformational leadership and job resources. The study (Balwant et al., 2019) found a significant relationship between job resources and work engagement, and established the moderating role of job resources in the relationship between transformational leadership and work engagement. Our findings in the service sector (higher education) differ because no significant positive relationship was found between job resources and employee work engagement levels. Whilst, previous studies (Balwant et al., 2019; Hawkes et al., 2017) found a significant relationship between transformational leadership and work engagement, our findings did not support a significant postive relationship between leadership practices and work engagement in higher eduction. One of the reasons why leadership practices exert no direct influence on work engagement could be attributed to the prominent role of job demands of staff members in higher education institutions. This is explained by the mediating influence of job demands on the interplay between leadership practices and work engagement levels in higher education institutions. However, the implication of this result is that leadership practices exert an indirect influence on wok engagement of staff members in higher education, through job demands.

In terms of the mediating role of job resources in the relationship between leadership practices and work engagement, no significant indirect effect of job resources was established on the link in this study. The implication of this result is that job resources exert no significant mediating influence on the relationship between leadership practices and work engagenment levels in the Namibian higher education system. This result differs from the empirical evidence reported by Hawkes et al. (2017) that job resources moderate the relationship between leadership practices and work engagement. The current study examines the mediating inluence of job demands on the association between leadership and work engagement, which shows that job demands significantly mediate the relationship, whereas job demands was not measures or examined in the structural model reported by Hawkes et al. (2017). However, job resourses did not mediate the rationship between leadership practices and work engagement in the context of higher education institutions in Namibia. While a negative relationship was found between job resources and work enagement, the value reported on the link does not suggest a significant negative relationship between these variables in higher education.

Practical Implications

The results reported in this study offer managerial implications for leadership practices and employee work engagement levels in higher education. The structural model (see Figure 2) revealed that leaders, through their practices, are directly involved in regulating and/or managing their subordinates’ job demands. In practice, this would mean that leaders can manage job demands to avoid employee disengagement due to burnout, by having control over their work stressors (working hours, a fair workload, and ensuring a work-life balance). Offering job resources, which are supports to help employees accomplish their responsibilities more effectively (Lee et al., 2019). Job resources could be provided in forms of job autonomy (having control over your work), emotional support, technical tools (internet and computer or tools), feedback, rewards, job control, participation, job security, and supervisory support. Job resources are instrumental in buffering the impact of job demands on employee burnout in higher education (Bakker et al., 2005). For example, job demands and job resources are important predictors of employee well-being and organizational performance (Kaiser et al., 2020). The implication is that the quantity of job demands and resources offered by a leader have an impact on employee well-being in higher education. Whilst no significant direct effect was found on the link between leadership practices and employee work engagement, this could mean that concerted effort is required from those in leadership positions in higher education. The efforts should be geared toward effective job resources to enhance subordinates’ psychological well-being in higher education. Employees’ psychological well-being in higher education can be improved through specific investments in mental health coverage, provision of on-site psychological therapy, creating a center for social engagement and mentoring through community of practice. Furthermore, psychological well-being in higher education can be promoted by encouraging staff members to focus on their own self-care alongside their professional activities.

Limitations and Future Research

One of the limitations of the current study is the use of variance-based SEM (SmartPLS). Future studies should consider the use of covariance-based SEM (e.g., AMOS), which is more appropriate for goodness of fit and theoretical confirmation. Furthermore, future studies should consider the use of a qualitative approach or mixed methods approach to gather in-depth information from those in leadership positions, as well as subordinates across the different sectors of the economy. Such research will provide a comprehensive analysis of non-numerical data from leaders and their subordinates to establish the leadership practices and it influence on job resources and employee work engagement levels in Namibia. Moreover, future studies should include job performance as an endogenous variable in the model to establish the influence of leadership practices on job performance, as well as the effect of work engagement on job performance in the African context. Future studies may also focus on different industrial sectors, such as government, or the private sector, which may be relatively more demanding than the higher education sector.

Conclusion

The main objective of this study was to examine the relationship between leadership practices and work engagement in higher education, as well as the mediating role of job demands and resources. We measured five leadership practices influencing job demands, job resources, and employee job engagement levels in higher education. These leadership practices are to model the way, inspire a shared vision, challenge the process, enable others to act, and encourage the heart for excellent service delivery in higher education. The study found that leadership practices have a significant positive influence on job demands and job resources in higher education. While the relationship between leadership practices and employee work engagement in higher education was mediated by job demands. Empirically, job resources exert no significant mediating influence on the relationship between leadership practices and work engagement levels in higher education. Therefore, efforts should be geared toward offering effective job resources to enhance subordinates’ psychological well-being and work engagement levels in higher education.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Sulaiman Olusegun Atiku

Data Availability Statement

The data generated during and/or analysed during the study are available from the corresponding author on reasonable request.

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