The influence of self-leadership strategies,psychological resources,and job embeddedness on work engagement in the banking industry

Abstract

This study used a model to determine the combined effect of psychological resources, self-leadership strategies, and job embeddedness on work engagement for employees in the banking sector. A descriptive quantitative research framework was adopted; data were collected from a sample of 303 banking sector employees. The results indicated that self-leadership strategies influence work engagement through psychological resources and job embeddedness. The three constructs combined explained 70.3% of variance in work engagement. Psychological resources have the strongest direct influence on work engagement, and self-leadership is a strong determinant of the psychological resources and moderate determinant of job embeddedness. The study concluded that implementing self-leadership strategies, encouraging the practice of psychological capital, and ensuring strong links and fit (job embeddedness) would aid in enhancing an engaged workforce. The results indicate that accumulating and expanding internal and job resources from psychological capital, self-leadership, and job embeddedness significantly influence work engagement and buffer the effects of job demands.

Keywords

Banks job embeddedness psychological resources self-leadership work engagement

Work engagement is associated with valuable business results across all types of organisations (Lee et al., 2016). It provides competitive advantage and has a direct influence on employee well-being and organisational performance (Kim et al., 2017). Despite its importance, most organisations still struggle to design and implement strategies to enhance work engagement. More than one third of workers in 17 of the world’s most important economies reported low levels of work engagement and another third are somewhere in the middle, but not driving better business results either (Hewitt, 2017). This significantly affects an organisations’ financial performance (Saks, 2017).

It is evident that work engagement plays an imperative role in ensuring the success of an organisation. Firms in the top decile of engagement outperform their peers by almost 147% in earnings per share, and have 90% better growth trend than their competitors have (Bakker, 2017). Thus, low levels of work engagement cost companies money, slow projects, and lower profits. An estimated $550 billion a year is lost due to loss of productivity caused by low levels of work engagement (Mann & Harter, 2016).

In South Africa, work engagement is listed as the third most important factor for organisations across all industries (Kotzé, 2018). However, the work engagement levels of employees in South Africa is quite depressing; more than 80% of employees feel disconnected from their work, whereas 43% consider exiting their current jobs (Rothmann, 2017). Although work engagement challenges are being experienced across all organisations, the finance and banking industry seems to suffer the most, as they are operating in a highly competitive environment (Sadlier, 2014). The financial meltdown, depreciation, and collapse of the South African currency (rand) have unquestionably tarnished the reputation of the banks and placed heavy demands on employees (Bersin, 2015). As a result, the financial services industry (FSI) workplace holds a great deal of general pessimism, lack of meaning, job insecurity, and a sense of hopelessness (Munyaka et al., 2017). This leads to apathy and detachment from one’s work and thus the general working environment is not engaging.

Attempts to address work engagement in the FSI concentrate on invalidated, unfocused annual surveys (Sadlier, 2014), yet basing work engagement strategies on surveys as the only solution has proved to be ineffective and unrealistic. It is just a repetitive pattern, focusing on engagement periodically and not acting upon results (Mann & Harter, 2016). These flawed approaches pose significant barriers to improving work engagement and achieving lasting change; therefore, many organisations are on the lookout for new strategies to engage employees (Bersin, 2015). The traditional methods of improving work engagement including coaching and mentoring, idea sharing, and workplace training have proved ineffective in certain environment; Saks (2017) and recent efforts have emphasised positive and proactive organisational behaviour as possible solutions (Albrecht et al., 2015; Bakker, 2017). Studies show that job and personal resources are the main predictors of work engagement and gain their salience in the context of high job demands, which characterise modern nature of work (Kim et al., 2017). Therefore, managers need to investigate ways in which internal coping resources can be generated from their workforce as a way to enhance engagement (Coetzee & De Villiers, 2010).

Work engagement is viewed as a positive, fulfilling, work-related state of mind characterised by vigour-related energy, mental resilience, and the ability to invest effort in one’s work, persisting even in difficult times (Schaufeli et al., 2002). Engagement is coupled with dedication, strong involvement in one’s work, and passion. Absorption relates to being fully concentrated and deeply engrossed in one’s work (Schaufeli & Bakker, 2004). A number of personal resources, which are self-efficacy, optimism, self-esteem, and resilience, have been identified as antecedents of work engagement (Kotzé, 2018). For the purpose of this study, personal resources will be limited to the dimensions of psychological capital (PsyCap) as noted in the Job Demands Resource model including resilience, hope, self-efficacy, and optimism. It should, however, be acknowledged that these resources do not constitute the whole of psychological resources. Recent studies have investigated the moderating effect of some of these psychological resources in the relationship between self-leadership and work engagement. Results indicated that increasing psychological resources can aid employees in overcoming setbacks and enhance work engagement (Chen & Lim, 2012; Kotzé, 2018; Tabaziba, 2015).

PsyCap is a multidimensional construct defined as the individual’s positive psychological state of development characterised by hope, optimism, resilience, and self-efficacy (Luthans et al., 2007). These psychological resources have a positive impact on work-related outcomes, such as work engagement and organisational commitment (Simons & Buitendach, 2013; Tabaziba, 2015). Consistent with the above, recent interventions to buffer the effects of high job demands clearly support the utility of psychological resources and positive retention as strategies to improve employees’ work environment and consequently enhance work engagement (de Waal & Pienaar, 2013).

Nielsen and Daniels (2012) noted that job embeddedness (JE) is part of the positive retention strategies and identified it as a possible way of securing work engagement. JE strengthens employee links with their supervisors and colleagues and ensures congruence between the job requirements and employee skills (de Waal & Pienaar, 2013). JE examines an individual’s links to other people, teams, and groups in the organisation. It also entails perceptions of the individual’s fit with the job, organisation, and community, and belief about what they would sacrifice if they leave their job (Holtom et al., 2006). Individuals with high levels of JE are involved with and tied to projects and people; they fit well in their jobs and believe they will sacrifice valued things if they quit their jobs (Zhao & Liu, 2010). Contrary, less embedded individuals spend most time strategising and pursuing possible job alternatives, failing to focus on their work, resulting in complete disengagement (Kilburn & Kilburn, 2008).

Self-leadership is also part of an iterative process of self-regulation in the positive behaviour change process that leads to an engaged workforce (Bandura, 2008). Through self-leadership, individuals regulate and control their behaviour, influencing and leading themselves by using specific sets of behavioural and cognitive strategies (Manz & Neck, 2008). Optimal work environments are characterised by high challenging demands, high job resources, and low hindrances (Bakker & Demerouti, 2014). Self-leading individuals have the ability to control and successfully manipulate the resources to suit their own needs (Breevaart et al., 2014). Thus, they can positively influence the resources of the work environment and contribute to their engagement (Bakker & Demerouti, 2014). With self-leadership strategies in place, an initial foundation for positive organisation is constructed, as personal resources of self-leadership facilitate higher psychological functioning, which in turn influences work engagement (Kotzé, 2018).

This study sought to examine the direct and indirect influence of psychological resources, self-leadership strategies, and JE dimensions on work engagement. The idea was to develop a model with a wide variety of both internal and external resources that sustain a continuous positive psychological state to counteract disengagement in the banking sector. Conservation of resource (COR) theory indicates that when confronted by threats to current and future resources, employees with more resources are better able to cope with immediate pressures and demands. Consequently, expanding the resources of employees can buffer the effects of job demands and workplace challenges. Expanding resources is thus a proactive way to deal with disengagement challenges before they escalate (Hobfoll & Freedy, 2002).

The following four propositions guided this exploratory study: (a) Self-leadership strategies, psychological resources, and JE have a direct influence on work engagement; (b) psychological resources mediate the relationship between self-leadership and work engagement; (c) JE mediates the relationship between self-leadership on work engagement; (d) both psychological resources and JE mediate the relationship between self-leadership and work engagement.

Method

This study adopted a quantitative research framework involving a systematic, scientific investigation of data and their relationships. The empirical aspect of the study utilised a cross-sectional survey design to collect quantitative primary data from the respondents using a self-report questionnaire to achieve the objectives of the study.

Participants

From a population of 524, a total of 303 employees from the banking industry participated. The age range extended from 19 to above 50 years, with the majority (30.7%) falling in the category 26 to 30, followed by 28.8% in the category 31 to 40. The gender distribution indicated that the majority (58.7%) of the participants were female and 39.3% male. The sample was made up of employees from various ethnicities: White (14.9%), Coloured (17.5%), Indian (9.9%), and African (57.1%). The distribution can be attributed to the affirmative action laws, advocating for the employment of previously disadvantaged groups.

Instruments

The survey had demographic questions and four scales.

Utrecht Work Engagement Scale

Work engagement was measured using the 17-item version of the Utrecht Work Engagement Scale (UWES-17), developed and validated by Schaufeli et al. (2002). Support for the three-dimensional structure of work engagement is evident when looking at the following goodness-of-fit statistics (Coetzer & Rothmann, 2007): χ² = 223.05, df = 85, root mean square error of approximation (RMSEA) = .07, and comparative fit index (CFI) = .94. It can, therefore, be assumed that the construct work engagement is represented by three latent subscales, which in turn are made up of 17 measured items. This study used five items to measure dedication, six items to measure vigour, and six items to measure absorption. This study found acceptable reliability estimates for each of the three sub-scales: dedication (α = .865), vigour (α = .855), and absorption (α = .861). Consistent with that, in previous studies in the South African context, the scale reported acceptable levels of construct validity and internal consistency: vigour (α = .78), dedication (α = .89), and absorption (α = .78; Storm & Rothmann, 2003). Similarly, Barkhuizen and Rothmann (2006) confirmed that the UWES-17 shows high internal consistency. In two South African studies (de Bruin et al., 2013; de Waal & Pienaar, 2013), it was found that work engagement can also be treated as a unidimensional construct, with reported reliabilities ranging between .88 and .89 for the unidimensional measure. This study reported a composite reliability of .967 for work engagement (see Table 1).

Table 1.

Quality criteria (outer model).

Variable	Composite reliability	AVE
WE	.967	.907
JE	.870	.692
PsyCap	.932	.775
SL	.920	.794

AVE: average variance extracted; WE: work engagement; JE: job embeddedness; PsyCap: psychological capital; SL: self-leadership.

Psychological Capital Questionnaire

Psychological resources were measured using the PsyCap scale (24-item Psychological Capital Questionnaire [PCQ-24]). The PCQ-24 was developed and validated by Luthans et al. (2007). These authors found empirical support for the four-dimensional structure of the PCQ-24, as evident from the following goodness-of-fit statistics: χ² = 422.7, df = 234, RMSEA = .046, and CFI = .934. This study, therefore, concludes that psychological resources are represented by four latent subscales, which in turn is made up of 24 items. This study used six items each to measure the following four latent subscales: hope, self-efficacy, resilience, and optimism. This study found acceptable reliability estimates for each of the four sub-scales: hope (α = .889), efficacy (α = .910), resilience (α = .810), and optimism (α = .772). A 5-point Likert-type scale was used. Within the South African context, previous research also reported acceptable internal consistency with alpha reliability coefficients ranging from .77 to .86 (Du Plessis & Barkhuizen, 2012). In another South African study (de Waal & Pienaar, 2013), it was found that PsyCap can be also be treated as a unidimensional construct, with reported reliabilities ranging between .63 and .69 for the unidimensional measure. This study obtained a composite reliability of .932 for PsyCap (see Table 1).

Self-leadership

Self-leadership strategies were measured using the Abbreviated Self-Leadership Questionnaire (ASLQ). Self-leadership is conceptualised as consisting of three dimensions/strategies: behaviour-focused strategies, cognitive thought pattern strategies, and natural reward strategies (Houghton et al., 2012; Houghton & Neck, 2002). Empirical support for the three-dimensional structure was found, as evident from the following goodness-of-fit statistics: χ² = 37.83, df = 23, RMSEA = .02, and CFI = .99 (Houghton et al., 2012). This study, therefore, treats self-leadership as being represented by three latent subscales, which in turn is measured using 16 items from both the ASLQ (Houghton et al., 2012) and the Revised Self-Leadership Questionnaire (Houghton & Neck, 2002): behaviour-focused strategies (eight items), cognitive thought pattern strategies (six items), and natural reward strategies (two items). This study found acceptable reliability estimates for each of the three subscales: behavioural strategies (α = .897), cognitive strategies (α = .886), and natural reward strategies (α = .739). A 5-point Likert-type scale was used. In the South African context, Nel and van Zyl (2015) found that self-leadership could be treated as a unidimensional construct, with an acceptable reliability (α = .89). This study obtained a composite reliability of .920 for self-leadership (see Table 1).

Job embeddedness

To assess JE, the Job Embeddedness Scale (JES) developed by Mitchell et al. (2001) was applied. Mitchell et al. (2001) conceptualised JE as consisting of three dimensions: fit to the organisation, links to the organisation, and organisation-related sacrifice. Exploratory factor analysis seems to support the three-dimensional nature of JE (Mitchell et al., 2001). This study treats JE as being represented by three latent subscales, which in turn is measured using 28 items: organisational fit (nine items), organisational sacrifice (10 items), and organisational links (nine items). Acceptable reliability estimates were found for each of the three subscale: organisational fit (α = .862), organisational sacrifice (α = .904), and organisational links (α = .890). A 5-point Likert-type scale was used. Consistent with that, acceptable internal consistency was yielded in a recent South African study reporting the following alphas, links .79, fit .81, and sacrifice .88 (Takawira, 2013). In addition to the subscales, the developers of the JES used a composite score as an indicator of overall JE (Mitchell et al., 2001). They reported an acceptable reliability when using all the items (α = .850). This study obtained a composite reliability of .870 for JE (see Table 1). Previous studies have also reported a good validity of the JES (Halbesleben & Wheeler, 2008; Holtom & O’Neill, 2004).

Procedure

Respondents were recruited from retail bank branches in the Free State Province in South Africa. Of 422 questionnaires distributed to the banking sector employees, 313 questionnaires were returned, of which 10 were incomplete and had to be excluded from the data. The 303 usable questionnaires gave a response rate of 71.8%.

Ethical considerations

Ethical clearance was received from the Ethics in Research Committee of the Faculty of Economic Management Sciences of the University of Free State (UFS-HSD2015/0579). The data collection process started in July 2016 and continued until February 2017. The participants signed a consent form that guaranteed confidentiality, anonymity, and publication only of aggregate data.

Data analysis

Variance-based structural equation modelling was employed to evaluate the different propositions. A two-step process was followed (Henseler et al., 2009). First, the outer model (i.e., measurement model) was evaluated in terms of relevant quality criteria. The purpose of the outer model is to determine whether the measurements used to operationalise each of the latent variables (i.e., constructs) are reliable and valid. The quality criteria associated with an acceptable outer model are as follows: (a) average variance extracted (AVE) of .5 and higher, (b) composite reliability estimates of .7 and higher, and (c) indicators (i.e., dimensions of constructs) with significant loadings on their respective constructs. In addition to significant loadings, the latter should also be .7 and higher.

Second, the inner model (i.e., structural model) was evaluated using the following guidelines: (a) the size of the path coefficients (beta values), (b) significance of the path coefficients, and (c) the amount of variance explained in the dependent variable by the proposed model. All the statistical analyses were conducted using SmartPLS version 3.2.7 (Ringle et al., 2015).

Results

It is evident that all the constructs met the quality criteria in terms of reliability and validity (see Table 1). More specifically, all the composite reliability estimates were above the recommended value of .7. In terms of validity, all the constructs have values above the recommended .5 related to the AVE.

Table 2 reports the loadings of each of the indicators in relation to the relevant theoretical construct. All the indicators have statistical significant loadings on their respective constructs, ranging between .706 (organisational fit) to .955 (vigour). It should be noted that all the loadings are above the recommended value of .7.

Table 2.

Indicator loadings (outer model).

Dimensions	WE	JE	PsyCap	SL
Absorption	.948
Behavioural strategies				.915
Cognitive strategies				.910
Dedication	.954
Hope			.901
Natural rewards				.847
Optimism			.896
Fit		.909
Links		.706
Sacrifice		.866
Resilience			.851
Self-efficacy			.872
Vigour	.955

WE: work engagement; JE: job embeddedness; PsyCap: psychological capital; SL: self-leadership.

The quality criteria (associated with the outer model), therefore, point to the fact that all the constructs used in the present theoretical model are reliable and valid. This enabled this study to continue evaluating the inner model, representing the four theoretical propositions.

From Table 3, it is evident that all the proposed paths in the theoretical model are statistically significant. All the variables in the theoretical model explain approximately 70% of the variance in work engagement (see Table 4). It is also clear that all the independent variables (JE: β = .118, p = .001; psychological resources: β = .621, p = .0001; and self-leadership: β = .172, p = .002) have significant relationships with work engagement. These results, therefore, provide support for Proposition 1.

Table 3.

Path coefficients (inner model).

	Original sample (O)	Standard deviation (SD)	t statistics (O/SD\|)	p values
JE ⩾ WE	.118	.035	3.325	.001
PsyCap ⩾ WE	.621	.051	12.173	.000
PsyCap ⩾ JE	.353	.097	3.648	.000
SL ⩾ WE	.172	.056	3.078	.002
SL ⩾ JE	.219	.093	2.367	.018
SL ⩾ PsyCap	.815	.021	39.322	.000

JE: job embeddedness; WE: work engagement; PsyCap: psychological capital; SL: self-leadership.

Table 4.

R² (inner model).

	R ²	R² adjusted
WE	.703	.700
JE	.299	.294
PsyCap	.664	.663

WE: work engagement; JE: job embeddedness; PsyCap: psychological capital.

To evaluate the remaining three propositions (relating to mediation), the indirect effects should be consulted (see Table 5). It is evident that PsyCap has a significant mediating effect (.507, p = .000) on the relationship between self-leadership and work engagement. The mediating effect of both PsyCap and JE is also statistically significant (.034, p = .029), but smaller than that of PsyCap alone (.034 vs. .507). Because the path coefficient between self-leadership and work engagement is statistically significant (β = .172, p = .002), the above two results provide evidence of partial mediation. Hence, the results of this study found partial support for Propositions 2 and 4.

Table 5.

Specific indirect effects (inner model).

	Original sample (O)	Standard deviation (SD)	t statistics (O/SD\|)	p values
SL ⩾ PsyCap ⩾ JE ⩾ WE	.034	.015	2.194	.029
SL ⩾ JE ⩾ WE	.026	.013	1.947	.052
SL ⩾ PsyCap ⩾ WE	.507	.045	11.282	.000

SL: self-leadership; PsyCap: psychological capital; JE: job embeddedness; WE: work engagement.

The results of this study found no support for Proposition 3, with JE having a non-significant mediating effect (.026, p = .052) on the relationship between self-leadership and work engagement.

Discussion

The study aimed at discovering the direct and indirect influence of psychological resources, self-leadership strategies, and JE on work engagement. It was proposed that the three constructs positively influence work engagement (directly and indirectly) and that self-leadership lays the foundation for both psychological resources and JE in their influence on work engagement. This was based on Bakker (2017), who noted that self-leadership strategies are used to expand psychological resources and assist with increasing personal resources like optimism and self-efficacy, which eventually transform to work engagement aspects (vigour, dedication, and absorption).

According to COR theory, employees have various resources (work and non-work) at their disposal to deal with the demands placed on them by their working environment. When employees invest in the development or use of resources, they combine different resources to build additional resources. When employees have an abundance of such resources, they create resource caravans (Hobfoll, 2001). It has also been suggested that the use and effectives of resources are context specific (Halbesleben, 2006). For example, work-related resources are better at predicting work outcomes than non-work resources. Hence, the resources should be related to the context of the outcomes. With the above as background, the outcomes of this study are discussed below.

All the three independent variables had significant relationships with work engagement. Self-leading individuals control and successfully manipulate their resources as they see fit (Breevaart et al., 2014). They can positively influence the resources of the work environment that may contribute to their engagement (Bakker & Demerouti, 2014). JE can be used to enhance levels of work engagement when employees strengthen links with their supervisors and colleagues ensuring congruence between the job requirements and employee skills (de Waal & Pienaar, 2013; Nielsen & Daniels, 2012). It has been suggested that employees with higher levels of PsyCap are more intrinsically motivated, have more psychological resources at their disposal therefore exhibiting higher levels of work engagement (Joo et al., 2016). Such individuals are also more likely to channel their psychological energy in their work, ultimately putting in more effort and becoming more engaged (Alessandri et al., 2018).

PsyCap (as a psychological resource) has a significant mediating effect on the relationship between self-leadership and work engagement. However, there is only evidence of partial mediation given that the relationship between self-leadership and work engagement is still statistically significant. This mediating effect is stronger (.507) than that of both PsyCap and JE combined (.034). Using the concept of a resource caravan, it can be argued that individuals use both self-leadership and PsyCap (both examples of personal resources) to create an abundance of personal resources at their disposal to enhance their levels of work engagement. Individuals who are able to self-manage themselves are in a better position to use various resources and strategies to structure their working environment, increase their levels of self-motivation, and exhibit behaviours that are likely to lead to higher performance. Self-managing individuals are able to identify which resources they need to mobilise to successfully perform their work (Breevaart et al., 2014).

Self-leadership strategies can, therefore, be used as building blocks for expanding personal resources (i.e., resource caravans), assisting individuals to identify self-defeating thinking patterns and replacing them with constructive beliefs (Kotzé, 2018). This process improves individuals’ use of personal resources, minimises dysfunctional thought processes, improves cognitive effectiveness, and creates hope. PsyCap explains the influence of self-leadership on dedication, and partly explains why self-leadership exerts both a direct and an indirect influence on vigour via PsyCap (Alessandri et al., 2018). The findings suggest that self-leadership strategies should be recognised as integral parts of the personal resources that facilitate positive behaviour that eventually translates to work engagement (Khandelwal & Khanum, 2017).

The results indicated that combined, self-leadership strategies, psychological resources, and JE have a statistically significant positive influence on work engagement. However, there was only evidence of partial mediation given that the relationship between self-leadership and work engagement was still statistically significant. A combination of the three variables and their dimensions expand personal and job resources, which may increase work engagement. In practice, based on the COR theory, accumulation of different job and personal resources benefit both individual and organisation through sustained engagement (Kotzé, 2018). Obtaining and retaining of a job and personal and psychological resources assist individuals in creating a sense that they are capable of meeting challenges and guarantee continuous engagement (Gawke et al., 2017; Sender et al., 2017). This is consistent with the findings of Kotzé (2018) and Tabaziba (2015), who identified several personal resources, including optimism, self-efficacy, and positive thinking, as antecedents of engagement. Individuals with numerous resources at their disposal experience resource abundance that ultimately influences their motivational levels at work (Hobfoll, 2001).

The mediating effect of JE was weaker (.037) than that of self-leadership and PsyCap (.507). One possible explanation is that individuals in this study had lower levels of JE (M = 3.408; SD = .658) compared with PsyCap (M = 4.101; SD = .796) and self-leadership (M = 3.709; SD = .750). Although they were not low on JE, they were lower compared with the self-leadership and psychological resources. It is therefore possible that they rather used their other personal resources (self-leadership and PsyCap), and to a lesser extent JE, to enhance their levels of work engagement. This reasoning may also provide a possible explanation as to why JE did not have a significant mediating effect (.026, p = .052) on the relationship between self-leadership and work engagement.

An alternative explanation comes from the dual-valence hypothesis (Hobfoll, 2001). The latter state that individuals can simultaneously use some of their resources (in this case self-leadership and PsyCap) while protecting (not using) other resources (in this case JE). In this study, personal resources are invested into enhancing work engagement while work-related resources (e.g., JE) are protected. In short, the personal resources (self-leadership and PsyCap) are used to enhance a personal outcome (work engagement) – as suggested previously that effectiveness of resources are context specific (Halbesleben, 2006).

Overall, considering that all three constructs render a number of personal and psychological resources that can possibly be used by organisations as well as individuals to facilitate work engagement and well-being, theory can be framed to integrate psychological capacities, self-leadership strategies, and JE dimensions as relevant job and personal resources within the banking industry to achieve an engaged workforce. The banking sector is operating in intricate and modest settings categorised by changing conditions and a highly impulsive economic climate; such environments require high levels of work engagement (Sadlier, 2014). Applying a wide range of personal resources identified in this study may yield positive results for both managers and employees. The banking sector has undergone rapid and striking changes due to globalisation, influx of technology, and increased competition and the global financial strain; in this whirlwind of changes, it is imperative for banks to foster high levels of work engagement to assist them to weather the storm of change (Munyaka et al., 2017).

One of the major limitations of the study is that only a limited number of constructs were explored in the model, yet literature indicates that there are more variables that can also influence work engagement. Future studies may consider including other variables such as emotional intelligence and mindfulness. This study focused mainly on the banking sector and used a convenience sampling procedure. This restricted generalisation, hence findings can only be carefully generalised in the banking industry. A further limitation of the study is the cross-sectional nature of the data, which does not provide a clear reflection of mediation. To get a broader understanding and to yield more insights regarding the interaction between these variables and mediation, future research should consider replicating the same study using longitudinal designs in a different setting.

Conclusion

This study concluded that work engagement could be promoted by expanding and stimulating psychological and personal resources. When individuals engage in self-leadership behaviour and are hopeful, optimistic, and self-efficacious, and when they fit well and have links in the organisation, they increase their psychological and personal resources, which in turn result in higher and more stable levels of work engagement over time. The study also discovered that enough evidence is available to establish a theory that integrates self-leadership strategies as interventions to facilitate positive behavioural change. The field of industrial psychology should, therefore, take a fresh look at self-leadership as a foundation to positivity at individual level. Self-leadership may form the basis of understanding how individuals identify, develop, and use various resources, both personal and social, to make the best of their work. The research yielded useful insights that explain how employees can optimise and sustain a positive working life by using psychological resources and self-leadership strategies, and expanding social links. This contributes to the field of organisational behavioural research by answering the call to increase positivity among employees.

Footnotes

Declaration of conflicting interests

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

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Martha Harunavamwe

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