About the Author(s)

Nhamo Mashavira symbol
Department of Human Resource Management, Julius Nyerere School of Social Sciences, Great Zimbabwe University, Masvingo, Zimbabwe

Nyasha D. Nyoni symbol
Department of Human Resource Management, Julius Nyerere School of Social Sciences, Great Zimbabwe University, Masvingo, Zimbabwe

Motshedisi S. Mathibe Email symbol
Gordon Institute of Business Science Business School, Faculty of Economic and Management Sciences, University of Pretoria, Johannesburg, South Africa

Lister Chada symbol
Department of Human Resource Management, Julius Nyerere School of Social Sciences, Great Zimbabwe University, Masvingo, Zimbabwe


Mashavira, N., Nyoni, N.D., Mathibe, M.S. & Chada, L., 2023, ‘Work-life balance in the Zimbabwe Retail Sector: Testing a job-engagement and job-satisfaction model’, Acta Commercii 23(1), a1139. https://doi.org/10.4102/ac.v23i1.1139

Original Research

Work-life balance in the Zimbabwe Retail Sector: Testing a job-engagement and job-satisfaction model

Nhamo Mashavira, Nyasha D. Nyoni, Motshedisi S. Mathibe, Lister Chada

Received: 09 Mar. 2023; Accepted: 12 June 2023; Published: 21 Aug. 2023

Copyright: © 2023. The Author(s). Licensee: AOSIS.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Orientation: This study focuses on the relationship between work-life balance (WLB), job engagement, and job satisfaction (JS) among employees in the retail sector in Bulawayo urban Province, Zimbabwe.

Research purpose: The purpose of this study was to validate the relationship between WLB, job engagement and JS.

Motivation for the study: The motivation for the research stemmed from the dearth of studies from the global south that examined the causal relationship between three aforementioned variables within the retail sector.

Research design, approach and method: A descriptive survey design was employed in a study that involved 108 employees from the retail sector in Bulawayo province. Adapted standardised closed questionnaires were used for data collection. The study was developed and tested, using structural equation modelling, a model that can be used to explain the effect of the three variables on each other.

Main findings: The study established a statistically significant relationship between WLB and job engagement. It was also found that WLB plays a major role in facilitating positive JS outcomes. However, a weak association was established between JS and dedication – a dimension of job engagement.

Practical/managerial implications: Striking a balance between employees’ career and personal life directly impacts their JS and job engagement levels.

Contribution/value-add: This study’s findings shed light on the complex dynamics between the three variables that are helpful for organisations seeking to enhance employee well-being and optimise performance of their workforce.

Keywords: work–life balance; job engagement; job satisfaction; Bulawayo; Zimbabwe.


In the last two decades, researchers have been working to provide a more consolidated perspective of the work–family interface. Work–life balance (WLB) has emerged as a dominant concept in this view (Brough et al. 2020). However, the term WLB is commonly used without a clear theoretical development (Bello & Ibrahim 2020). There is no consensus in the literature on how to describe the construct and the themes that inform its conceptualisation vary (Brough et al. 2020). Most definitions of WLB are situational and subjective (Gunawan et al. 2020) as the balance between life and work activities changes from one person to another depending on their satisfaction with either domain (Sen & Hooja 2018). According to the absolutist approach of defining WLB, one must give equal time to every domain and find balance in order to manage responsibilities in both work and non-work domains (Gunawan et al. 2020).

Regarding the provision of work, the retail sector in Zimbabwe, dominated by OK Zimbabwe, TM and Spar Supermarkets, is one of the largest employers in the country (IPC 2019). Despite a declining economic situation, Zimbabwe’s retail sector is growing and could become a significant hub for businesses. However, the sector is characterised by demands and pressure, inadequate WLB, long working hours, fewer off days on public holidays and being short-staffed (IPC 2019). These challenges have led to job dissatisfaction and employee disengagement (IPC 2019).

Demirtas et al. (2017) conceptualised job engagement as a positive mindset characterised by liveliness, higher levels of vigour (VI), self-fulfilment, determination and dedication (DE) shown by feelings of pride, enthusiasm, inspiration and job meaningfulness. Higher levels of job engagement are associated with greater chances of generating higher shareholder value, return on assets and profitability and are related to citizenship behaviour, job satisfaction (JS), commitment and both contextual and job performance (Kangas et al. 2017). Job engagement itself is a positive state that is both affective and cognitive and is characterised by DE, VI and absorption (AB) (Kangas et al. 2017). Vigour refers to high levels of mental resilience, energy and willingness to put effort into one’s work while persevering through difficulties (Boikanyo & Heyns 2019). Dedication implies a strong work commitment that is considered useful, meaningful, inspiring, challenging and that invokes feelings of enthusiasm and pride (Boikanyo & Heyns 2019). Absorption is marked by full concentration on one’s work in a pleasant way.

Interestingly, JS has received attention in research because of its importance in enhancing corporate effectiveness (Lee 2017). It refers to extrinsic and intrinsic job elements that address employees’ desires in achieving their tasks (Casper et al. 2018). The belief that JS can reduce turnover and absenteeism and increase organisational commitment, effectiveness and engagement has driven organisations to understand it better (Yousef 2017). Dissatisfied employees are counterproductive, so it is essential for management to promote WLB practices that enhance JS. A lack of WLB has a tendency to compromise employee engagement and reduce JS (Saks 2006). Issues such as long working hours, erratic shifts, under staffing, a lack of off days, the demands and pressures associated with the retail sector and ineffective WLB policies may negatively impact employee engagement and satisfaction (Aruna Shantha 2019; Žnidaršič, Vukovič & Marič 2020).

Corporations have a mandate to uphold employees’ rights to balance their work and life. A physically and mentally healthy worker is more productive with higher levels of engagement effectiveness (Kashyap, Joseph & Deshmukh 2016). With only 20% of global employees reported as being engaged at work, costs associated with disengagement include miserable work experiences poor management of employees (Clifton & Harter 2021). An unhealthy workforce is costly because of high absenteeism rates, low productivity, job dissatisfaction behaviour patterns and lower quality goods and services offered (Kashyap et al. 2016). The retail culture of serving customers during festivals and holidays has the potential to disturb employees’ WLB. Although employees are recruited on shift basis, unexpected shift timings and the obligation to work during such periods is likely to leave less time for family (Agarwal 2012). This can be challenging for women in particular as they have to fulfil both their professional and domestic responsibilities.

This study is one among the few (if any) that considered the three variables in the context of Zimbabwe’s retail sector. Some studies limited themselves to JS and job engagement, others to WLB and job engagement, while others focused on WLB and JS only. Although some studies attempted to explore the association between the three variables, no known study attempted the same in Zimbabwe. This study begins by providing literature on the three variables, followed by the methodology, findings and the discussion. The study concludes by pointing out its limitations and then proffers recommendations for further inquiry.

Literature review

Work–life balance

Work–life balance has grown to be a major concern in today’s organisations. The dynamism of the business environment continues to accentuate a greater difficulty in the balance between professional roles and personal responsibilities (Shankar & Bhatnagar 2010). Dating back to the 19th century, the construct of WLB was seen as more inclined to women as it became prominent at a time when women entered the labour market. However, Aruna Shantha (2019) notes the differences in the global communities, which reflect a different picture whereby all employees regardless of gender also want flexibility and control over their work and personal life. Today’s generation has many responsibilities, work obligations and family responsibilities owing to the complexity brought about by globalisation and technology, hence employers should craft effective and efficient family friendly policies and practices supportive of WLB.

According to Brough et al. (2020), WLB is a multifaceted concept that encompasses various elements that include equity across multiple roles, perceived control between multiple roles, a satisfaction between multiple roles and the fulfilment of role salience between multiple roles. There is a strong need for retailers to build pillars of support both at work and home. Every employee deserves work opportunities that strike a balance between their career and personal life in order to nurture their well-being (Sen & Hooja 2018).

Work–family conflict

Although an enormous amount of literature deals with the issue of work–family conflict and family–work conflict, a full review of this literature goes beyond the purview of this study. Work–family conflict occurs when an incompatibility between the pressures of work and family happens to an employee (Akkas, Hossain & Rhaman 2015). Work–family conflict can be experienced when an employee has to perform the multiple roles of spouse, parent and worker (Akkas et al. 2015). In order to be executed effectively, each of the aforementioned roles demand energy, time and commitment. However, demands from work and family roles are often mutually incompatible – participation in one role makes participation in the other role more difficult. Work–family conflict has become more ubiquitous than family–work conflict (where family interferes with work) although both can occur (Akkas et al. 2015). However, irrespective of the direction of causation, when one realm gets acrimonious with the other realm, the result is usually conflict and escalating stress on the employee.

Family-related factors

A research study conducted by Murphy, Duxbury and Higgins (2007) revealed that high levels of work–family conflict were experienced by people with a lot of care-needing dependents who include the elderly and children. The research shows that employees with a lot of care-needing dependents fail to strike a balance between job demands and family responsibilities, thus work–family conflict results. Working mothers with children below the age of three were found to experience high levels of work–family conflict because of child care needs. Moreover, families with strong bonds and who were fully immersed in their family traditions and values experienced a lot of family–work interferences (Murphy, Duxbury & Higgins 2007). Most family-related factors are bound to a lot of care giving. This, however, has a negative bearing on the level of commitment, motivation and engagement to one’s work (Murphy, Duxbury & Higgins 2007).

Individual-related factors

People have different values and beliefs that may interfere with the balance between work and family. Individual needs and values can contribute to work–family conflict (Marolt, Zimmermann & Žnidaršič 2020). According to (Kossek & Lee 2017) importance, priority and centrality help to explain the individual factors that influence work–life conflict. The value that an individual places on a role determines its importance and how it is prioritised (Kossek & Lee 2017). Importance is the value expression that an individual uses to determine the gravity and urgency of a role (Gonçalves, Curado & Martsenyuk 2023).

Types of conflict

According to Žnidaršič and Marič (2020), literature, identifies two types of conflicts, namely time and strain conflict. On one hand, time conflict occurs when the time allocated to work roles interferes with the fulfilment and functioning of duties of the family and vice versa. This type of conflict is a result of people failing to equally distribute their time among different roles (Cui & Li 2021). A good example of time-based conflict is when an individual chooses to work overtime while missing a family function or commitment (Cui & Li 2021). Higher levels of work–family conflict are likely to have a negative bearing on employee well-being and performance (Fay & Hüttges 2017).

On the other hand, strain conflict occurs when stress from work (or family) hinders family (or work) duties. Netemeyer, Boles and McMurrian (1996), refer to a case where work-related anxiety and irritability deter the accomplishment of family (or work) roles and vice versa. For instance, marital problems at home could influence one to behave poorly at work or miss deadlines at work. Employees in the retail sector are more likely to be vulnerable to strain-based conflict because of the excessive stress levels associated with the industry (Vutete & Vutete 2015).

Hypotheses development
Work–life balance versus job engagement

Work–life balance is a concept that facilitates a highly engaged workforce that is purposefully driven and aligned to business strategy (Burke et al. 2018). Proper prioritising both work and lifestyle sets the stage for employee engagement. If workers feel there is a balance between their work and personal life they tend to exert more effort beyond the call of duty (Margaretha, Lestari & Efendi 2020). In situations where employees are constrained of taking adequate care of responsibilities outside the office, presenteeism (a condition where the employee is physically available but mentally depleted) may thrive. The key dimensions to an engaged workforce are VI, DE and AB (Schaufeli, Bakker & Salanova 2006) and these may not come from people who are mentally, physically and emotionally depleted because of WLB deficits. Based on the aforementioned, three hypotheses relating WLB to each of the dimensions of job engagement by Schaufeli et al. (2006) were proposed. Hypotheses 1, 4 and 6 of this study were thus crafted:

H1: Work–life balance is positively associated with job VI.

H4: Work–life balance is positively associated with job DE.

H6: Work–life balance is positively associated with job AB.

Work–life balance versus job satisfaction

Work–life balance is said to have a unidirectional relationship with JS because if employees can afford a better life, they can do a better job (Kasbuntoro et al. 2020). The general idea is that when employers support their workers in managing work and family roles, employees are likely to feel cared for and this may generate positive feelings towards work, thereby influencing their JS levels. Brough et al. (2014) suggest that employees experiencing WLB are satisfied with their jobs and lives. The most critical domains of human life are job and family, hence a balance of the two is highly likely to bring satisfaction (Wahda et al. 2021). A study by Kasbuntoro et al. (2020) revealed that WLB had a positive but significant effect on JS in the banking industry in Jakarta. It was noticed that people experiencing WLB are more satisfied with their lives and report an improved mental and physical well-being. Adikaram (2018) also carried out a research on the impact of WLB on JS using a sample of 150 employees from a commercial bank in the private sector of Sri Lanka. Factors that were considered in the research included work pressure, nature of the job, working hours, WLB programmes, working conditions and turnover intentions. The results indicated that WLB had a major impact on JS. A related study by Walga (2018) revealed that JS and WLB share a significant positive relationship. Based on the above mentioned, it can be hypothesised as follows:

H3: Work–life balance is positively associated with job satisfaction.

Job engagement versus job satisfaction

Although often treated as one, job engagement and JS are two distinct constructs that are somehow related. According to Garg, Kiwelekar, Netak and Ghodake (2021), JS is an important driver of job engagement. The highest level of employee engagement is expressed when employees feel satisfied with their organisation and its working environment. In such a scenario, employees tend to portray pro-organisational behaviours such as high level of loyalty, high commitment, low turnover intentions and good citizenship behaviours. Kim-Soon and Manikayasagam (2015) established a positive correlation between job engagement and JS. Vorina, Simonič and Vlasova (2018) also identified job engagement to be an antecedent of JS. Furthermore, Bellani, Ramadhani and Tamar (2018) examined the extent to which JS contributed to the engagement of employees at a private company in Indonesia. A multiple regression revealed that JS significantly predicted the engagement of employees. The study established that enhancing JS can possibly leverage workforce engagement. Although the study by (Shuck, Kim & Chai 2021) also presents a case of reverse causality, its findings were significant in the sense that it reinforced the fact that an association exists between the two variables. Based on the given reviewed literature, the following hypotheses pertaining to the relationship between three dimensions of job engagement and JS were proffered:

H2: Vigour is positively associated with job satisfaction.

H5: Dedication is positively associated with job satisfaction.

H7: Absorption is positively associated with job satisfaction.

Research methods and design

Research participants

The employees in the Bulawayo Urban retail sector were the target population of the research study (Cooper & Schindler 2006). The study used the convenience sampling technique, which allowed researchers to get more less costly samples and in a short period.

Research instruments

A structured questionnaire with closed items was used for this study because it allows for minimal researcher involvement and influence on respondents (Khothari & Garg 2014). The researchers adapted standardised items for all the three variables under study. Customised items from the Self-Assessment WLB scale by Hayman (2005), the job engagement scale by Schaufeli et al. (2002) and the JS Rating scale by Warr, Cook and Wall (1979) was used.

Structure of the questionnaire

Section A focussed on demographic data. Sections B to D used a five point Likert scale. Participants were expected to choose their responses from: ‘strongly disagree’ – 1 point, ‘disagree’ – 2 points, ‘neutral’ – 3 points, ‘agree’ – 4 points and ‘strongly agree’ – 5 points.

Section A

Section A focused on extracting personal data. Personal data are defined as information that helps in identifying a person (Bryman 2012). Personal data requested included the age, sex, level of education, marital status and the duration of employment of respondents.

Section B

Section B measured the ability of employees to balance their work, family obligations and commitments. The section was mainly focused on measuring the existence of WLB in the sector. The Hayman (2005) Self-Assessment WLB standardised scale with a reliability level of 0.8–0.9 and validity level above 0.90 was adopted (Agha et al. 2017). An example of one of the items that were used to measure the ability of employees to balance work–family obligations and commitments:

  • My job makes my personal life difficult.
Section C

This section measured employees’ levels of job engagement. The researchers adapted a standardised scale formulated by Schaufeli et al. (2002) with a reliability level of 0.70. The standardised scale consists of 19 items, but the researchers used 11 items measuring VI, DE and AB. An example of one of the items used to measure respondents’ job engagement levels:

  • It is difficult to detach myself from my job.
Section D

Section D measured respondents’ JS levels. The study employed a JS Rating scale formulated by Warr, Cook and Wall (1979) whose reliability score is 0.80. An example of one of the items that were used to measure respondents’ JS levels:

  • I am satisfied with the opportunity to use my abilities.
Research procedure

The researchers sought for ethical clearance first before questionnaires were physically distributed with strict adherence to coronavirus disease 2019 (COVID-19) safety protocols. After seeking respondents’ informed consent and assuring them of anonymity, respondents were given 3 days to complete the questionnaire. Of the 120 delivered questionnaires, 108 were completed and returned.

Statistical analysis

The researchers employed structural equation modelling (SEM) because it offers clear statistical analysis that can be testable in conducting further analysis (Hair et al. 2014). Some evidence support that some SEM models could be tested meaningfully even with a small sample size of 100 to 150, which is regarded as the minimum size of a sample for conducting SEM (Tabachnick, Linda & Fidell 2001). In view of this, this study used a sample size of 108 respondents

Ethical considerations

Ethical clearance to conduct this study was obtained from the Great Zimbabwe University Julius Nyerere School of Social Sciences Research Ethics Committee.


Descriptive statistics

To do SEM there are certain things such as discriminant validity and reliability tests that have to be met. The Cronbach’s alpha test (CA) that tests internal consistency, the composite reliability (CR) and even the average extracted variance (AVE) were calculated, and the results are summarised in Table 1. The considered variables were WLB, VI, JS, DE and AB.

TABLE 1: Descriptive statistics for construct variables.

The results shown in Table 1 indicate that the CA values do range from 0.757 to 0.878, suggesting internal consistency of the measurement constructs. All the CR values exceeded 0.7, a recommended threshold value by Hair et al. (2014). In addition, all the AVE values exceeded the 0.5 threshold value. These results imply that the measurement constructs were reliable, hence better results may be attained.

The structure and cross-loadings of the variables were calculated to determine convergent validity of the factors with the results being summarised in Table 2.

TABLE 2: Structure and cross-loadings.

It can be noticed, from the Table 2, that all the cross-loading values exceeded 0.6, showing that convergent validity existed on the measurement constructs. All variables with factor values (loadings) below 0.6 were removed from the model. Inter-construct correlations helped to examine discriminant validity. Inter-constructs correlations are presented in Table 3.

TABLE 3: Inter-construct correlations.

According to the findings displayed in Table 3, discriminant validity existed in all the measurement items, as shown by the square root of the AVE values (diagonal values) for the factors, which exceeded the corresponding correlation coefficient values of other factors. As reliability tests and discriminant validity were confirmed, a structural equation model can be fitted (see Figure 1).

FIGURE 1: Structural equation model.

From the SEM displayed in Figure 1, the following hypotheses were derived and tested:

H1: Work–life balance is positively associated with VI.

H2: Vigour is positively associated with JS.

H3: Work–life balance is positively associated with JS.

H4: Work–life balance is positively associated with DE.

H5: Dedication is positively associated with JS.

H6: Work–life balance is positively associated with AB.

H7: Absorption is positively associated with JS.

The partial least squares (PLS) approach was employed in analysing the data through the use of SmartPLS software. The SEM results from the analysis are presented in Table 2.

The first hypothesis examined the relationship between WLB and VI. A coefficient value of 0.704 shown on the table above, shows that WLB has a positive effect on VI. The association between WLB and VI is statistically significant at 1% level because the probability value is less than 0.001. This suggests the acceptance of H1, which says WLB is positively associated with VI. This means that as WLB improves, VI will also improve.

The second hypothesis examined the relationship between VI and JS. It can be noticed, from the above table, that VI positively affects JS because of the coefficient value of 0.238. Furthermore, there is a statistically significant relationship at 5% level because the probability value of 0.028 is less than 0.05. The results suggest the acceptance of the H2, which states that VI is positively associated with JS. This implies that improvements in VI will result in JS improvement.

The relationship between WLB and JS formed the third hypothesis of the study. According to the given results, WLB had a positive effect on JS as indicated by a positive coefficient value of 0.304. Work–life balance and JS have a statistically significant relationship at 5% level because of the probability value of 0.046, which is below 0.05. From these results, hypothesis H3 is accepted. This means that the improvements in WLB will be reflected by the improvement of JS.

The fourth hypothesis attempted to examine the relationship between WLB and DE. The given results suggest that WLB had a positive effect on DE, as supported by a positive coefficient value of 0.912. A statistically significant relationship exists at 1% level because the probability value is less than 0.001. These results suggest the acceptance of H4, which says WLB is positively associated with DE. These results suggest that as WLB improves, DE improves as well.

The fifth hypothesis investigated the association between DE and JS. The results displayed in the table suggest that DE positively affects JS, as indicated by the positive coefficient value of 0.077. However, the relationship lacks statistical significance, as evidenced by a probability value of 0.635, which lies above the 0.05 threshold value. These results suggest the rejection of H5.

The sixth hypothesis was meant to examine the relationship between WLB and AB. According to the results displayed in the table above, WLB had a positive effect on AB because of the positive coefficient value of 0.709. Furthermore, the relationship becomes statistically significant at 1% level because the probability value is less than 0.01. These results suggest the acceptance of H6, which states that WLB is positively associated with AB. The result implies that the improvements in AB will be influenced by improvements in WLB.

The seventh hypothesis examined the relationship between AB and JS. According to the results in Table 4, AB had a positive effect on JS because of the coefficient value of 0.246. The relationship between AB and JS is statistically significant at 5% level because the probability value of 0.025 is below the threshold value of 0.05. These results suggest the acceptance of H7, which says AB is positively associated with JS. This means that as AB improves, JS improves as well. The results in Table 4 suggest that H1, H2, H3, H4 and H6 are supported, while H5 is not supported.

TABLE 4: Structural equation modelling results.

The next section presents a summary of the fitted model containing coefficients and factor loadings.

Goodness of fit of the model

Brioness Penalver et al. (2017) observed that R² and Q² are helpful in deciding the goodness of fit of a model and showed that the values have to be above zero. Both the R2 (R2 = 0.609) and Q² (Q² = 0.290) exceed the zero threshold value. Hair et al. (2016) postulate that a Q² value above 0 for an endogenous latent variable depicts the path model’s predictive relevance for a certain dependent construct. According Figure 2, 60.9% (R2 = 0.609) total variability in JS was being explained in the model by the independent variables (VI, DE, AB and WLB). Henseler, Ringle and Sinkovics (2009) and Hair, Ringle and Sarstedt (2011) suggest that the R² for the fitted model implies good levels of predictive accuracy of the model. Table 5 shows some of the goodness of fit results.

FIGURE 2: Relationships.

TABLE 5: Goodness of fit results.

Table 5 indicates that, the standardised root mean square residual (SRMR) value for the fitted model is 0.077, which lies below the threshold value of 0.1, suggesting acceptance of the model. Furthermore, the normed fit index (NFI) value of 0.91 for the model, which is slightly above the recommended threshold value of 0.9, suggests that the fitted model is a good.


Work–life balance versus job engagement

Structural equation modelling was employed to assess how WLB and job engagement relate. Job engagement was characterised by DE, VI and AB (Schaufeli et al. 2002). The first hypothesis presented by the SEM examined the relationship between WLB and VI. The SEM results revealed that WLB had a positive effect on VI, DE and AB, with coefficient values of 0.704, 0.912 and 0.709, respectively. These indicated a strong positive correlation between WLB and the three variables measuring job engagement. The p-values of 0.001 and less for the three variables at 1% level of significance suggest the acceptance of the alternative three hypotheses H1, H4 and H6, which imply a statistically significant relationship between WLB and the three variables measuring job engagement, viz VI, DE and AB

The aforementioned findings are supported by studies carried out by (Li, McCauley & Shaffer 2021) and Vance (2017), who observed that the resources offered by a job have significant and motivational influence in increasing job engagement. Furthermore, other studies (Dhas 2018; Presa 2018) indicated a positive correlation between WLB and job engagement. Ibrahim et al. (2020) argued that poor WLB practices such as long working hours, erratic work schedules, poor communication, a lack of autonomy among other factors have a negative impact on employee engagement levels. The issue of WLB poses some challenges in various degrees and with different outcomes to employees despite their occupation, gender and age. It is therefore the duty of management to ensure that effective and efficient WLB practices are in place (Presa 2018). The major concern is that organisations and regulatory boards do revise unfavourable laws, policies and practices to further support the concept of WLB thereby enhancing workforce engagement and corporate effectiveness (Dhas 2018). Job engagement and WLB are catalysts that have incredible potential in unleashing continuous corporate growth. The retail sector characterised by long working hours, busy schedules, fast movement of goods and services, requires that management do exercise effective WLB practices to enhance employee job engagement (Chikweche 2017).

Work–life balance versus job satisfaction

The hypothesis examining the relationship between WLB and JS was again tested using SEM. The SEM results revealed that WLB had a positive but weak effect on JS. This was evidenced by a positive coefficient value of 0.304, which was indicative of a weak positive correlation between WLB and JS. In addition, a probability value of 0.046, which is below 0.05 proved that the relationship between WLB and JS was statistically significant at 5% level. The results suggest acceptance of the alternative hypothesis H3, which implies a positive association between WLB and JS. The research findings support those from a related study by Aruna Shantha (2019) that found a statistically significant and positive correlation between WLB and JS. Žnidaršič et al. (2020) and Casper et al. (2018) also assert that striking a balance between work and family commitments enhances JS. Kashyap et al. (2016) however observes how challenging it is for organisations to achieve WLB in the retail sector, especially in a developing country such as Zimbabwe characterised by a high rate of inflation, political instability, unstable currency and high unemployment.

Interestingly, Adikaram (2018) seems to realise that managerial employees can tailor-make their own schedules to balance their family and work commitments, whereas lower-level employees have little to say on how their work schedules are crafted. This could explain why levels of JS could differ among employees in the same organisation. It therefore implies that job autonomy, being one of the significant elements of WLB shares a positive relationship with JS (Adikaram 2018). As a result, the greater autonomy one has, the more power they wield in deciding flexible working arrangements and the greater the likelihood of satisfaction outcomes (Adikaram 2018).

Job engagement versus job satisfaction

Hypotheses 2, 5 and 7 presented by the SEM examined the relationship between the three variables of job engagement (VI, DE and AB) and JS. A coefficient value of 0.238 was indicative of a weak positive correlation between VI and JS. The relationship was, however, statistically significant at 5% level, with a probability value of 0.028, which is less than 0.05. This led to the acceptance of the alternative hypothesis H2, which proposes that VI is positively associated with JS. The fifth objective investigated the association between DE and JS. The results displayed in the table suggest that DE weakly but positively affects JS, as indicated by a positive coefficient value of 0.077. However, the relationship was not statistically significant, as evidenced by a probability value of 0.635, which is above the threshold value of 0.05. These results suggest the rejection of the alternative hypothesis, which suggests a statistically significant relationship between DE and JS. Finally, the seventh hypothesis presented on the SEM examined the relationship between AB and JS. A coefficient value of 0.246 indicated a weak positive correlation between the two. The relationship between AB and JS was statistically significant at 5% level because of a probability value of 0.025, which was below the threshold value of 0.05. The results therefore suggest the acceptance of the alternative hypothesis that suggests a positive association between AB and JS.

The aforementioned results suggest a weak positive correlation between job engagement (as measured by all the three variables) and JS, while statistically significant relationships existed between only two variables measuring job engagement (i.e. VI and AB) and JS. This means that as employee job engagement improves, their JS would weakly improve as well. Job engagement was therefore instrumental in influencing JS. These research findings concur with Harini, Luddin and Hamidah (2019) who established that the level of commitment and satisfaction one has towards his or her job is derived from the level of engagement they have towards the job. Individuals who are highly engaged to their work are very persistent in achieving their tasks even in the face of extreme challenges, all because of the satisfaction derived. Extant literature (Aziri 2019; Bellani et al. 2018; McIlveen et al. 2021) also confirm the positive relationship between job engagement and JS Effective employee engagement practices such as valuing the opinions of employees, getting them involved in crafting policies and practices, autonomy, among others, enhance outcomes of JS to a greater extent. Furthermore, Maryati and Astuti (2022) assert that effective job engagement practices create communication channels between the workforce and its management facilitating outcomes of JS, motivation and commitment.

It can however be highlighted that the lack of a statistically significant relationship between DE and JS, although confounding, has been explained by Vance (2017). Employees may be dedicated to their jobs and lack satisfaction from it or vice versa because of various reasons such as employment opportunity, ineffective collective bargaining in terms of the value of salaries, recognition, working conditions, leadership, style of management and the job itself (Vance 2017). Although previous studies (Abu Khalaf, Hmoud & Obeidat 2019; Aziri 2019; Bellani et al. 2018; Casper et al. 2018; Harini et al. 2019; Jaiswal et al. 2017; Lee 2017; McIlveen et al. 2021; Abu Khalaf, Hmoud, & Obeidat 2019) indicate a positive relationship between job engagement and JS, this study indicated that the DE of employees to their work had no influence on JS. Therefore, investing in employee engagement, specifically regarding DE, will not enhance outcomes of JS as previously anticipated. However, the contrasting results could be attributed to the unique external environment under which the study was conducted. This study was conducted in a country in the global south, characterised by hyperinflation, an unstable currency, regressive laws, political instability, dilapidating economy and a high rate of unemployment among many other depressive characteristics (Chikweche 2017).

Conclusion and recommendations

The study established a statistically significant relationship between WLB and job engagement. When organisations strike a balance between work and employees’ personal life, employees are likely to become engaged in their work. It was also found that WLB plays a major role in facilitating positive JS outcomes. Retail shops that prioritise WLB promote a highly satisfied workforce that is purposefully driven and aligned to the organisation’s goals. However, a weak association was established between JS and DE (a dimension of job engagement), yet a significant relationship was established with the other two dimensions of job engagement, viz VI and AB. The DE of employees does not entail satisfaction with their jobs. Drawing from the given conclusions it is recommended that employers or their proxies should make serious engagements with employees or their representatives in their quest to craft meaningful family-friendly policies to ensure a balance between work and family commitments. This is more likely to facilitate positive job outcomes.

Limitations and directions for future studies

While this study examined the relationship between WLB, job engagement and JS among employees in the retail sector in Bulawayo Urban province in Zimbabwe, future studies may consider other variables such as intention to quit, employee creativity, employee commitment and so on, that are equally relevant in understanding the nuances of the employment relationship. Future studies may also consider carrying out a mixed methods inquiry at regional or national levels involving bigger samples in order to either validate the findings of this study or tap into the lived experiences of employees.

Contributions of the study

Notwithstanding the importance of WLB, job engagement and JS in contemporary organisations, very few studies have validated the relationship between the three variables in one study. Furthermore, this study is one of the few studies conducted on the relationship between the three aforementioned variables in the retail sector of a country in the global south. In view of the aforementioned, this study was able to extend the frontiers of knowledge with regard to the relationship between the aforesaid variables in a country in the global south whose context and peculiarities are worlds apart from her counterparts in the global north, where most of the related studies have been carried out.


Competing interests

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

Authors’ contributions

D.N.N. did problem formulation, data collection and review of the literature. N.M. assisted in data analysis and helped in results and discussions sections. M.M. and L.C. did the overall proofreading, editing and alignment of issues.

Funding information

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

Data availability

Data sharing applies to this article as new data were created or analysed in this study.


The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors.


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