Abstract
Purpose
Keeping happy and committed workers is an imperative goal for organisations in any field, including higher education. Institutions must, however, have a thorough understanding of the elements that influence various organisational commitment levels before they can develop human resource management guidelines and procedures that work. Hence, by using social exchange theory, this study aimed to investigate the connection between work–life balance (WLB), job satisfaction and organisational commitment among a sample of Zimbabwean higher education institutions. These factors have received relatively minimal attention in academic institutions, particularly in developing nations.
Design/methodology/approach
A cross-sectional survey was conducted, using convenience sampling, to examine 224 members of the teaching staff from two universities in western Zimbabwe. The collected data were analysed using partial least squares structural equation modelling.
Findings
The results revealed that WLB significantly predicted job satisfaction. Furthermore, the relationship between WLB and affective and normative commitment was found to be indirect and mediated by job satisfaction.
Research limitations/implications
The results of this study suggest that WLB and job satisfaction are crucial factors for higher education institutions that aim to secure their talented faculty's affective and normative commitment. Therefore, universities should implement firm policies and practices that encourage academic staff to maintain a healthy WLB and enhance job satisfaction.
Originality/value
The study's main contribution is the development of a conceptual model that contributes to the ongoing scholarly discourse on how to enhance organisational commitment among academic staff in under-resourced higher education institutions, as well as the concomitant implications for human resource policies within these institutions.
Keywords
Citation
Dube, N. and Ndofirepi, T.M. (2023), "Academic staff commitment in the face of a role (im)balance between work and personal life: can job satisfaction help?", European Journal of Management Studies , Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/EJMS-08-2022-0048
Publisher
:Emerald Publishing Limited
Copyright © 2023, Nomusa Dube and Takawira Munyaradzi Ndofirepi
License
Published in European Journal of Management Studies. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence maybe seen at http://creativecommons.org/licences/by/4.0/legalcode
Introduction
Skilled employees are crucial to the efficient functioning and strategic success of higher education institutions, providing a critical source of competitive advantage (Whitfield, 2019). However, retaining qualified individuals is a significant challenge, particularly in circumstances where unfavourable work conditions and compensation increase the likelihood of staff seeking employment elsewhere (Kipkebut, 2010; Theron et al., 2014; Bhebhe and Maphosa, 2016). Prior research has highlighted the already stressful nature of academic environments and the consequent impact on workplace behaviour and outcomes (Dorenkamp and Ruhle, 2019; Dorenkamp and Süß, 2017; Wilton and Ross, 2017). Academic staff, particularly new appointees and women, struggle to balance private life demands with excessive workloads (Dorenkamp and Ruhle, 2019; Lendák-Kabók, 2020). Höhle and Teichler (2013) note that academics must continue to qualify for an extended period after graduation before securing tenure, which exposes them to job-related pressures during a life stage when they should be focussing on their family roles (Brechelmacher et al., 2015). Consequently, universities' top management must find ways to enhance employee commitment to their organisations to reduce staff turnover.
Although the term “organisational commitment” is interpreted differently by scholars, Meyer and Allen's (1984) definition of the concept as a psychological bond that employees have with their employer is commonly used. Meyer and Allen (1997) proposed three sub-dimensions of organisational commitment: continuance commitment (the perceived cost of quitting), affective commitment (emotional bonding), and normative commitment (loyalty). Organisational commitment is a result of an employee's personal decision-making process, based on cognitive and relational factors (Kumar and Janakiram, 2017). Organisational commitment is relevant in higher education management because committed employees positively contribute to an organisation's competitiveness through their behaviour and identification with the organisation's values and goals (Meyer and Allen, 1997; Sait, 2017). Moreover, committed employees are less likely to leave an organisation at the slightest provocation (Mousa and Puhakka, 2019). In contrast, uncommitted employees are inclined towards unproductive tendencies, such as tardiness, absenteeism, and an eagerness to quit an organisation (Meyer and Allen, 1991; Zeidan, 2020).
Even though prior research has extensively examined the antecedents of employee commitment across economic sectors (Cohen, 2014; Haque et al., 2019; Hussain and Khayat, 2021; Singh and Onahring, 2019), a significant gap in the literature on higher education management identified by the authors, particularly in developing countries, is the dearth of systematic attempts to unravel how changeable psychosocial phenomena triggered by current environmental dynamics exert their influence on the sub-dimensions of organisational commitment.
An increasingly important psychosocial variable, WLB, describes an individual's ability to achieve harmony between the demands of paid work and private life activities (Dorenkamp and Süß, 2017). Recently, higher education management scholars have paid attention to this notion, in part due to the impact of the COVID-19 pandemic and the measures taken to contain it on workplace operations (Azevedo et al., 2020; Ashencaen et al., 2020; Hjálmsdóttir and Bjarnadóttir, 2021). As a result, many higher education institutions have had to indefinitely suspend face-to-face classes, close campuses, and abruptly shift to online learning, forcing employees to work from home where work and family demands intersect. The impact of this development on academics' commitment to their organisations is a topical research area (Dunn and McMinn, 2021; Sari and Seniati, 2020; Mwesigwa et al., 2020; Farid et al., 2015; Perez-Perez et al., 2017), more so at institutions in developing countries. According to Abendroth (2018), WLB perceptions tend to differ across institutional, cultural and economic settings. Thus, using social exchange theory as a frame of reference, the objective of this study is to contribute to bridging this knowledge gap by testing a conceptual model that connects WLB, job satisfaction, and organisational commitment using a sample of respondents from a developing country. Further research on the topic especially focussing on less studied locations and the unprecedented work and life circumstances created by the Covid-19 pandemic enhances scholars and university administrators' understanding of the antecedence to organisational commitment and inform policy and practices on staff retention. We analyse data collected from academic personnel at two state-funded higher education institutions in western Zimbabwe to address the following research questions:
How did the WLB of employees during the Covid-19 pandemic era affect their job satisfaction and organisational commitment?
The next section reviews relevant literature and suggests some research hypotheses. Then, the section on research design and methods is incorporated. Following that, a summary of the study's findings is provided. The paper ends with a discussion of the findings and their practical and theoretical significance.
Literature review and hypothesised relationships
This section summarises the literature on which this study is based. First, a discussion of the theory employed in this study is offered. Following that, an analysis of the empirical studies upon which the study hypotheses are based is conducted. The section closes with a depiction of the conceptual model of hypothesised relationships.
Underpinning theory
The theory of social exchange (TSE) posits that individuals engage in social relationships with others with the expectation that their efforts will be rewarded in a fair and equitable manner (Blau, 1964; Cherry, 2019). Thus, people engage in social interactions with the anticipation of receiving benefits that are commensurate with their contributions. This expectation of reciprocity and fairness in social exchanges creates a foundation for building and maintaining relationships over time. The TSE has been applied in various disciplines, including sociology, psychology, and organisational behaviour, to understand social interactions in different settings (Akarsu et al., 2020; Meira and Hancer, 2021; Kim et al., 2019).
In the context of the link between WLB, job satisfaction, and organisational commitment, the TSE can help researchers to explore the social exchange process between employees and their organisations. Employees who perceive that their organisations are meeting their WLB needs may reciprocate by demonstrating higher job satisfaction and organisational commitment. In this sense, the TSE can be used to explore how employees' perceptions of fairness and equity in social exchanges with their organisations influence their work attitudes and behaviours.
Empirical research has demonstrated the relevance of the TSE in exploring the link between WLB, job satisfaction, and organisational commitment (Hasan et al., 2021; Pradhan et al., 2016; Talukder, 2019). For example, researchers have used the TSE to investigate how perceptions of WLB can influence job satisfaction and organisational commitment among employees (Azeem and Akhtar, 2014). Other studies have examined the role of social exchange processes in predicting turnover intentions and job search behaviour among employees (Harden et al., 2018; Gould-Williams and Davies, 2005). Overall, the TSE provides a useful framework for understanding the complex relationships between individuals and their social environments, including the exchange of resources, mutual obligations, and interpersonal trust.
Work–life balance
The term “work–life balance” (WLB) is defined in a variety of ways throughout the literature. Abendroth (2018), for example, define WLB as the peaceful co-existence of distinct life domains. Dorenkamp and Süß (2017) depict it as the absence of friction between job and personal life. The concept of WLB has gained importance in discussions about organisational management practice because of the recognition that private and professional lives intrude on one another and can either complement or hamper one another depending on how they are managed (Kumar and Janakiram, 2017). Some scholars have noted that unbalanced work and personal life ultimately result in tension between the two spheres (Kelliher et al., 2019; Rothbard et al., 2021). This is because employees' time, physical, and emotional resources are repeatedly depleted as a result of persistent work–life tensions. It is argued that while employees may initially be able to bear the associated stress, their commitment to their professions gradually dwindles (Azeez et al., 2017). Employees who work in organisations that promote WLB often attain a combination of work and personal commitments, demonstrate a higher level of workplace engagement and hence boost their discretionary effort and productivity (Akter et al., 2020). Ultimately, negative outcomes such as emotional exhaustion and burnout are minimised. Vyas (2022) has underscored the significant impact of the COVID-19 pandemic on workplaces, with a particular focus on the remarkable changes that have occurred in working arrangements and environments. In addition, Rosa (2022) also highlights how the COVID-19 pandemic has triggered unprecedented challenges regarding WLB at universities. Luturlean et al. (2019) advance that an organisation's implementation of human resource management policies that encourage WLB is one method of increasing employees' contentment with their jobs. Such policies reflect the employers' understanding that their employees have lives apart from work and help ensure that one's home life does not interfere with one's professional life, and vice-versa (Xu, 2008).
Organisational commitment as an outcome of work–life balance
Although “organisational commitment” is defined in a variety of ways by scholars, in general, it relates to employees' level of identification with their employers and their readiness to leave (Radosavljevic et al., 2017). Organisational commitment is widely studied via the lens of Meyer and Allen's (1991) framework, which hypothesises three components of organisational commitment: affective, continuance, and normative commitment. Affective commitment relates to an employee's emotional attachment to an organisation, whereas continuance commitment speaks to the expenses associated with leaving a company, and normative commitment alludes to the obligation that employees feel to work with the organisation. When the three components are combined, it is believed that they increase a worker's tendency to remain with a given organisation (Giauque et al., 2010). The different sub-dimensions of organisational commitment, have varying implications for different workplace behaviours hence the need for management scholars and practitioners to understand them. For example, workers with a higher level of affective commitment are associated with more positive work attitudes and behaviours than those with a lower level; but, high levels of continuance commitment have not been shown to correlate with improved job performance (Meyer and Allen, 1997).
Although the antecedents to organisational commitment have been studied comprehensively and widely in organisational behaviour and human resources management over the years, the research theme remains relevant today because of the constantly evolving workplace environments which affects workers' attitudes and behaviours (Saravakos and Sirakoulis, 2014), especially in the aftermath of Covid-19 pandemic and its significant effects on work environments. In the current study, the focus is on the influence of WLB, a psycho-social factor that has gained prominence in organisational studies in recent years is relevant to the academic context where work and private life roles conflict is a burning issue (Abendroth, 2018). Given the high-pressure and stressful performance-based environments in which many universities staff work (Ismayilova and Klassen, 2019), such contexts are suitable for studying the outcomes of WLB. As Azevedo et al. (2020) underscore, WLB at university institutions is important for the recruitment and retention of high-quality faculty.
Previous research infers a positive relationship between respondents' perceptions of WLB and organisational commitment in general (Kim, 2014; Gulbahar et al., 2014; Hofmann and Stokburger-Sauer, 2017; Luturlean et al., 2019; Akar, 2018). However, other studies that sought to link WLB specifically to normative and continuance commitment have elicited mixed results. For instance, Onu et al. (2018) study of the effect of WLB on the normative commitment of employees in the banking sector of Nigeria revealed a significant positive relationship and recommended the prioritisation of leave policy incentives to strengthen employee commitment. Conversely, the study by Al Momani (2017) revealed a negative significant relationship between WLB and normative commitment in Jordanian working women. The preceding study also revealed a positive but insignificant relationship between WLB and continuance commitment. Against this background, using the present study we strive to contribute to the evidence base on the relationship between WLB and the sub-dimensions of organisational commitment. Thus, we hypothesise the following:
WLB is positively related to affective commitment.
WLB is positively related to continuance commitment.
WLB is positively related to normative commitment.
The role of job satisfaction
Job satisfaction relates to an employee's level of contentment with the job he or she performs (Parvin and Kabir, 2011). It is a multifaceted and complicated variable that reflects an employee's emotional condition regarding topics such as compensation, co-workers, promotion chances, the job itself, and relationship with supervisor(s) (Smith et al., 1969). Job satisfaction, according to Aziri (2011), entails a sense of accomplishment, a commitment to, and joy in one's work. It is contingent upon an individual's rational and subjective assessment of a variety of work-related variables, including pay and benefits, perceptions of fairness in promotion standards, working conditions, workplace relationships, and job characteristics (Parvin and Kabir, 2011), as well as the type of work, the required skill set, the amount of responsibility, the level of autonomy, and the work-relationship (Mishra, 2013). According to Ravari et al. (2012), job satisfaction is understood in the literature from four distinct perspectives: an emotional reaction, an attitude toward one's job, an expectation about one's employment, and a belief about one's job.
Previous studies have highlighted the importance of satisfied staff to the achievement of organisational outcomes at universities. For example, Ismayilova and Klassen (2019) note the stressful situations that university staff work in, and the increased likelihood of staff turnover and negative trickle-down effects when dissatisfaction with the work environment persists. This view is corroborated by Mwesigwa et al. (2020), whose study found a positive association between job satisfaction and organisational commitment among staff members at selected public universities in Uganda. Against this background, the following hypothesis is proposed:
WLB is positively related to job satisfaction.
Job satisfaction and organisational commitment have an ambiguous causal relationship in terms of which of the two influences the other (Saridakis et al., 2020). The literature, however, indicates an associative relative relationship between the two attitude variables. While there are relatively few studies linking job satisfaction to Allen and Meyer's subcategories of organisational commitment in higher education institutions contexts, the majority of them conclude that job satisfaction is a significant predictor of organisational commitment (Nehmeh, 2009) and a factor in organisations' efficiency and effectiveness (Aziri, 2011). Mabasa et al. (2016), for example, found a significant positive correlation between job satisfaction and affective commitment among employees at a sample of South African institutions of higher learning. Additionally, the same study revealed a favourable correlation between job satisfaction and commitment to continue working. This pattern of findings is corroborated by Akeke et al. (2015), who observed a positive relationship between job satisfaction, both affective and continuance commitment of non-academic staff at Nigerian universities, as well as Valaei and Rezaei (2016), who found a positive relationship between job satisfaction and both affective and continuing commitment among Malaysian information and communication technology-small and medium-sized enterprises (ICT-SMEs).
Several studies have examined the mediating role of job satisfaction in the relationship between work environments and outcomes. Hasan et al. (2021), for instance, investigated whether job satisfaction mediated the impact of person-job fit, WLB, and work conditions on organisational commitment in private firms in an emerging market context. Similarly, Azeem and Akhtar (2014) found that job satisfaction significantly mediated the relationship between WLB and organisational commitment among healthcare employees. Mwesigwa et al. (2020) found that job satisfaction partially mediated the relationship between leadership styles and organisational commitment among academic staff at public universities in Uganda. In another study, Talukder et al. (2019) demonstrated the mediating role of job satisfaction in the relationship between supervisor support and organisational commitment. Given that job satisfaction has previously been confirmed to be influenced by employees' perceptions of supportive measures at work and to have a positive association with organisational commitment, it is hypothesised that:
Job satisfaction mediates the relationship between WLB and affective commitment.
Job satisfaction mediates the relationship between WLB and continuance commitment.
Job satisfaction mediates the relationship between WLB and normative commitment.
The conceptual model of all hypothesised relationships is presented in Figure 1.
Methodological issues
The positivist paradigm formed the philosophical foundation for this study. In line with this, a quantitative cross-sectional survey was used to collect data about the study from a target population of academic staff at two public institutions of higher and tertiary education in western Zimbabwe. These institutions rely on government funding which is inadequate for their requirements and staff at the institutions often complain of heavy teaching load amidst a paucity of the required supporting resources (Mandibaya and Khan, 2020). There was no sampling frame, and the researchers used a convenience sample where the academic staff who volunteered to partake, and fully completed their questionnaires during the administration process were taken as the sample. The sampling process entailed identifying the target population and physical locations (their workplaces) to find them, approaching potential respondents in person at their workplaces and inviting them to participate in the study. The recruitment of respondents continued until a reasonable sample size for a quantitative study had been achieved. Thus, a total sample size of 224 respondents was obtained, out of a total of 271 potential respondents approached. Thus, the total response rate was 82.66%. Most of the respondents were female (n = 130; 58.03%), married (n = 142; 63.39%), aged between 30 and 39 years (n = 82; 36.61%), had served their employers for five to nine years (n = 88; 39.29%), and were master's degree holders (n = 144; 64.29%). Further details are provided in Table 1.
Data collection
Structured self-completion questionnaires with closed-end items were used to solicit data from the respondents between May and August 2020. The drop-off/pick-up method of questionnaire administration, where the researchers and three research assistance gave the questionnaires to the respondents at the various places of work and came to collect them on a different day, was used. This approach was deemed appropriate as reduces decline rates and non-response bias in surveys (Junod and Jacquet, 2023). Permission to conduct the research was sought from the institutions where the respondents worked. Voluntary consent to participate in the study was also verbally sought and obtained from the respondents. Respondents completed questionnaires anonymously during administration, and the researcher collected the questionnaires thereafter. No incentives were offered to the respondents, and the eligibility of the respondents depended on them being employed as academics at the two universities covered by the study. Respondents were assured of their right to withdraw from the study at any stage if they so wished as well as the confidentiality of their contributions.
The use of questionnaires was based on their flexibility in allowing respondents to answer in their own time. The data obtained through the use of a questionnaire is standardised and allows for easy comparison and analysis of it through descriptive and inferential statistics. The questionnaire elicited information on the respondents' demographic details, job satisfaction, WLB, affective commitment, continuance commitment, and normative commitment. Nine items adapted from Mensah (2014) were used to assess job satisfaction. These items were rated on afive-point Likert scale (5 being strongly agreed and 1 being strongly disagreed). WLB was determined using seven items also adapted from Mensah's work (2014). These items were rated on a five-point Likert scale (5 being strongly agreed and 1 being strongly disagreed). The 18-item organisational scale developed by Meyer and Allen (1997) was adapted to assess organisational commitment. It included three components of organisational commitment: “affective,” “continuance,” and “normative.” Each component was comprised of six items. These items were rated on a 5-point Likert scale (5 being strongly agreed and 1 being strongly disagreed). Table 2 summarises information about the reliability and validity of each of these scales.
The data gathered from the survey was cleaned, coded and entered into an Excel spreadsheet and exported to Smart PLS 3 data analysis computer software. Listwise deletion was used to deal with the problem of missing values. Thus, a case was only excluded from an analysis procedure where it did not have complete data, and included in other analyses where the data was complete. This approach was used because to avoid losing data given that the sample size was relatively small. No data outliers were detected. Partial least squares structural equation modelling (PLS-SEM) was used to test all the study's hypotheses. Computer software Smart PLS 4 was used for the purpose of conducting the analysis. The PLS-SEM was preferred to the covariance-based SEM because it is more tolerant of measurement error and missing data (Hair et al., 2019). In addition, it does not make stringent requirements regarding the sample size and data attributes.
Control variables
To examine the effect of demographic variables (age, gender, marital status, highest level of educational qualifications, and length of service to the university) on affective commitment, continuance commitment, and normative commitment, three sets of linear regression analyses were performed. However, the F-test results for each of the three models showed statistically non-significant results: F(16, 85) = 1.326, p = 0.201, R-square = 0.200; F(16, 85) = 0.954, p = 0.513, R-square = 0.152; and F(16, 85) = 1.775, p = 0.058, R-square = 0.250. This suggests that the demographic variables did not have a statistically significant effect on any of the three sub-dimensions of organisational commitment. Therefore, the demographic variables were not considered in further predictive tests.
Common method variance
Harman's single factor test was performed on the 34 measures of the five latent variables to examine the presence of common method bias. The 34 items were entered into principal factor analysis as one unrotated factor. Common method variance is typically assumed to be present when a single factor accounts for more than 50% of the total variance in the indicators (Podskoff et al., 2003). However, the total variance explained by the unrotated factor was 23%, which suggests a possible absence of common method bias.
Assessing the measurement model
The measurement model was assessed using three criteria namely Cronbach alpha, composite reliability, and average variance extracted (AVE). A value of at least 0.7 for the Cronbach alpha test and composite reliability indicates good reliability of the items measuring a particular construct. Similarly, AVE values of at least 0.5 suggest a good level of convergent validity for a variable. Thus, the results in Table 2 suggest that the five variables under study had acceptable levels of reliability and convergent validity.
The discriminant validity, which quantifies the degree to which different construct measures are unrelated, was determined using the heterotrait-monotrait ratio of correlations (HTMT). Discriminant validity is established when the HTMT ratios for pairs of variables are less than one. The results in Table 3 confirm the study's discriminant validity.
Results of hypotheses testing
The structural model was tested using path coefficients and coefficients of determination (R2). Whereas path coefficients demonstrate the statistical significance and strength of hypothesised relationships, the coefficient of determination (R2) measures the predictive capability of a proposed conceptual model.
Based on path coefficients observed, the following direct relationships were statistically significant: WLB → Job satisfaction r = 0.568, p = 0.000; Job satisfaction → Affective commitment r = 0.617, p = 0.000; and Job satisfaction - > Normative commitment r = 0.272, p = 0.042, therefore, disconfirming the null hypotheses. All other hypothesised direct relationships were not statistically significant, thus confirming the null hypotheses.
The following indirect relationships was statistically significant: WLB → Job satisfaction → Affective commitment (r = 0.351, p = 0.000) and WLB → Job satisfaction → Normative commitment (r = 0.154, p = 0.049, indicating the existence of mediated relationships. All other proposed indirect relationships were not statistically significant. Thus, H4, H5, and H7 were accepted. Further details relating to the correlation and predictive relationships between the variables are summarised in Tables 4 and 5 respectively.
The structural model test indicated the following coefficients of determination (r2) for the study's endogenous variables: affective commitment = 0.445, continuance commitment = 0.019, job satisfaction = 0.323, and normative commitment = 0.057. These are presented in Table 6. Thus, the structural model's predictors explained 44.5% of the variance in affective commitment, 1.9% of the variance in continuity commitment, 32.3% of the variance in work satisfaction, and 5.7% of the variance in normative commitment. There is no universally applicable rule of thumb for interpreting the coefficient of determination. Therefore, different research fields use different guidelines depending on the complexity of the model being tested. For instance, in marketing studies, coefficients of determination of 0.75, 0.50, or 0.25 for endogenous latent variables can be considered strong, moderate, or weak, respectively (Henseler et al., 2009).
In addition, the Stone-Geisser indicator (Q2) was used to assess the predictive relevance of the endogenous variables in the model. A Q2 value above 0 indicates that a model has predictive relevance, and higher Q2 values indicate greater predictive relevance (Hair et al., 2019). From Table 6, we can see that the affective and normative commitment, as well as job satisfaction variables had Q2 values greater than 0 but less than 0.25, indicating a small predictive relevance. Only one endogenous variable, continuance commitment, had a Q2 value less than 0, and therefore had no predictive relevance.
In terms of f-square, which measures the change in R-square when an exogenous variable is removed from the model, only the relationship between job satisfaction and affective commitment had a large effect size (f-square = 0.476; see Table 5). The effect sizes for the other direct relationships in the research model were non-significant, according to Cohen's (1988) criteria.
The outer variance inflation factors (VIF) in Table 7 which are all less than 5 suggest that multicollinearity was not a problem among the predictors.
Discussion
The purpose of this study was to explore the direct and indirect (via job satisfaction) effects of WLB on the organisational commitment of employees of selected universities in Zimbabwe.
Firstly, in contrast to previous findings, no statistically significant direct relationships between WLB and the three sub-dimensions of organisational commitment were discovered (H1, H2, and H3). This suggests that WLB may not be directly related to an employee's commitment to their organisation. This finding contradicted earlier studies from different contexts that established a direct relationship between WLB and organisational commitment (Kim, 2014; Sakthivel and Jayakrishnan, 2012; Nwagbara and Akanji, 2012; Shabir and Gani, 2020).
Secondly, the outcome of the PLS-SEM revealed that WLB had a significant positive relationship with job satisfaction (H4). This finding is relevant and noteworthy in the context of the perceptions and attitudes of employees during the COVID-19 era. It corroborates the conclusion by other studies that the COVID-19 pandemic era drastically changed the way people work (Rosa, 2022; Vyas, 2022) as remote working became the norm in many sectors, including academia. Arguably, the new work arrangements implemented during the pandemic blurred the boundaries between work and personal life, making WLB more challenging to achieve for many employees.
The positive relationship between WLB and job satisfaction can be interpreted as suggesting that organisations that prioritise WLB are more likely to have satisfied employees, which could have a positive impact on their overall performance. This interpretation is in line with the conclusions of Dorenkamp and Ruhle (2019) whose study among German academics revealed that work-to-life conflict acted as a stressor that reduced job satisfaction. It also corroborates findings from Mas-Machuca et al.’s (2016) study of employees of a Spanish pharmaceutical organisation which revealed that employee WLB enhanced job satisfaction.
Thirdly, the results also indicated that job satisfaction had positive predictive relationships with affective and normative commitment. The findings, thus, support, the idea that content employees feel bound psychologically to their employers and consequently identify with employers' goals and values. This finding corroborates previous research which links directly the facets of job satisfaction to affective and normative commitment (Valaei and Rezaei, 2016; Mabasa et al., 2016; Akeke et al., 2015).
Fourthly, the relationship between job satisfaction and continuance commitment, however, was not statistically significant. A possible explanation for this result is the nature of the continuance commitment construct, which is not always a reflection of an individual's satisfaction with the organisational environment, but rather the result of an individual's selfish rationalisation of the benefits of staying and the costs of leaving an organisation. Although these results differ from some published studies (Imam et al., 2013; Mabasa et al., 2016; Akeke et al., 2015), they are consistent with those of Sait (2017).
However, there was evidence of an indirect association between WLB and affective commitment (H5), as well as between WLB and normative commitment (H7), which was completely mediated by job satisfaction. This suggests that the respondents' perceptions of WLB had a significant bearing on certain aspects of organisational commitment which depended on whether they were content with their jobs or not. This finding regarding hypotheses 5 and 7 is consistent with the social exchange theory, which suggests that employees exchange their resources (e.g., time, effort, skills) with their organisation for rewards (e.g., salary, benefits, recognition). In this context, WLB can be seen as a resource that employees bring to the exchange. When employees can achieve a better WLB, they are likely to experience higher job satisfaction, which can lead to greater emotional attachment to an organisation and its values and norms. The finding, which is consistent with some earlier research (Van Saane et al., 2003; Hora et al., 2018; Mafini and Dlodlo, 2014), highlights the critical significance of job satisfaction as a buffer against potentially unpleasant job-related issues and how it acts against intents to leave an organisation.
Theoretical and practical implications
This study examined the mechanism by which academics' views of WLB are related to job satisfaction and organisational commitment at selected universities in a developing country. Thus, it contributes to the body of research aimed at determining the causes of organisational commitment in academic institutions. The findings of the study corroborated the social exchange theory, which suggests that when employees feel that their organisation cares about their well-being, they are more likely to reciprocate by putting in more effort at work, which could lead to better organisational outcomes. In this case, employees who are satisfied with their job are more likely to reciprocate by committing to the organisation, either because they have developed an emotional attachment to the organisation (affective commitment) or because they feel that they have an obligation to the organisation (normative commitment). The study also offered empirical evidence on that job satisfaction is a critical cog in the chain connecting working environment-related parameters to organisational commitment.
The findings of this study have some important practical implications. An important consideration is that higher education institutions that prioritise WLB are likely to attract and retain employees who value WLB. This can lead to a more engaged and productive workforce, which could have a positive impact on the organisations' overall performance. However, achieving WLB can be challenging, especially in the post-COVID-19 era, where remote work is still prevalent. Organisations may need to adopt flexible work arrangements, such as telecommuting or flexible schedules, to help employees achieve WLB.
The leadership and management of the institutions surveyed in this study should consider taking active processes to improve employee satisfaction, which results in employees developing an affective and normative commitment to their employer and profession. While increased compensation may not be an immediate option due to financial constraints, the multidimensional nature of job satisfaction allows for non-monetary sources of satisfaction such as promotions, a supportive work environment that prioritises employees' physical and mental well-being, and autonomy, among other measures. The finding that positive perceptions of WLB affect job satisfaction, affective commitment, and normative commitment mean that university administrators in Zimbabwe must incorporate measures that minimise conflict between work and family roles when designing and implementing staff motivation and retention measures. These strategies may include re-evaluating workloads, raising staffing levels, and implementing family-friendly flexible work arrangements. University top management should also develop support and mentoring programmes aimed mostly at young and female academics (because of their high susceptibility to role conflicts), to assist them in juggling family and career duties. Overall, the findings of this study suggests that organisations may need to focus on creating a work environment that fosters job satisfaction to promote employee commitment.
Limitations and future research areas
There are several limitations of using a cross-sectional research design in this work. Firstly, a cross-sectional design only provides a snapshot of data at a particular point in time. It does not allow for the examination of changes over time or the identification of causal relationships between variables. For example, in this study, it is unclear whether WLB leads to job satisfaction and organisational commitment, or whether employees who are already highly committed are more likely to have better WLB.
Secondly, a cross-sectional design relies on self-reported data, which can be subject to social desirability bias. This bias occurs when participants provide responses that they believe will be viewed favourably by the researcher or others, rather than their true beliefs or experiences. This could have affected the accuracy of the data collected in this study.
Thirdly, the sample size of this study was relatively small and limited to selected universities in Zimbabwe. This raises questions about the generalisability of the findings to other settings or populations. The results may not be applicable to employees in other types of organisations or in other countries.
Finally, cross-sectional designs are limited in their ability to control for confounding variables. In this study, there may be other factors that influence the relationship between WLB and organisational commitment, such as age, gender, and job tenure. Without controlling for these factors, it is difficult to draw definitive conclusions about the relationship between WLB and organisational commitment.
While a cross-sectional research design can provide valuable insights into the relationship between variables, it has several limitations that should be considered when interpreting the results. Future research could use longitudinal designs and control for confounding variables to provide a more comprehensive understanding of the relationship between WLB and organisational commitment.
Conclusion remarks
This paper aimed to explore the relationship between WLB and organisational commitment among teaching staff in selected universities in Zimbabwe. The findings indicate that WLB is positively related to job satisfaction, which in turn predicts affective and normative commitment. However, there was no direct relationship between WLB and the three sub-dimensions of organisational commitment, and the relationship between job satisfaction and continuance commitment was not statistically significant. These findings highlight the importance of considering the mediating role of job satisfaction in the relationship between WLB and organisational commitment, and the complexity of the relationship between these factors. The study contributes to the theoretical development of our understanding of WLB, job satisfaction, and organisational commitment, and provides practical insights for organisations seeking to promote employee well-being and commitment in the context of the COVID-19 pandemic.
Figures
Demographic profile of respondents
| Variables | Frequency | Percent (%) | |
|---|---|---|---|
| Gender | Male | 91 | 40.63 |
| Female | 130 | 58.03 | |
| Missing | 3 | 1.34 | |
| Total | 224 | 100 | |
| Age of respondents | Below 30 years | 40 | 17.86 |
| 30–39 | 82 | 36.61 | |
| 40–49 | 70 | 31.25 | |
| 50 years and above | 24 | 10.71 | |
| Missing | 8 | 3.57 | |
| Total | 224 | 100 | |
| Marital status | Single | 68 | 30.36 |
| Married | 142 | 63.39 | |
| Widowed | 3 | 0.01 | |
| Missing | 11 | 4.91 | |
| Total | 224 | 100 | |
| Service length | below 5 years | 56 | 2 |
| 5 to 9 | 88 | 39.29 | |
| 10 to 14 | 54 | 24.11 | |
| 15–19 | 12 | 5.36 | |
| 20 years and above | 8 | 3.57 | |
| Missing | 6 | 2.68 | |
| Total | 224 | 100 | |
| Education level | Bachelor's degree | 68 | 30.36 |
| Master's degree | 144 | 64.29 | |
| Doctorate | 12 | 5.36 | |
| Total | 224 | 100 |
Source(s): Table by authors
Reliability and construct validity
| Variable | Item | Factor loadings | Cronbach alpha | Average variance extracted | Composite reliability |
|---|---|---|---|---|---|
| Affective commitment | Affecom1 | 0.689 | 0.831 | 0.597 | 0.880 |
| Affecom2 | 0.667 | ||||
| Affecom3 | 0.747 | ||||
| Affecom4 | 0.879 | ||||
| Affecom5 | 0.857 | ||||
| Affecom6 | 0.656 | ||||
| Continuance commitment | Contcom1 | 0.994 | 0.748 | 0.621 | 0.747 |
| Contcom2 | 0.505 | ||||
| Contcom3 | 0.812 | ||||
| Contcom4 | 0.777 | ||||
| Contcom5 | 0.692 | ||||
| Contcom6 | 0.812 | ||||
| Job satisfaction | JobSat1 | 0.615 | 0.745 | 0.505 | 0.817 |
| JobSat2 | 0.769 | ||||
| JobSat3 | 0.31 | ||||
| JobSat4 | 0.52 | ||||
| JobSat5 | 0.806 | ||||
| JobSat6 | 0.701 | ||||
| JobSat7 | 0.596 | ||||
| JobSat8 | 0.642 | ||||
| Jobsat9 | 0.582 | ||||
| Normative commitment | NormCom1 | 0.882 | 0.696 | 0.613 | 0.823 |
| NormCom2 | 0.578 | ||||
| Normcom3 | 0.846 | ||||
| Normcom4 | 0.591 | ||||
| Normcom5 | 0.769 | ||||
| Normcom6 | 0.509 | ||||
| Work–life balance | WLBal1 | 0.613 | 0.731 | 0.590 | 0.814 |
| WLBal2 | 0.709 | ||||
| WLBal3 | 0.424 | ||||
| WLBal4 | 0.668 | ||||
| WLBal5 | 0.594 | ||||
| WLBal6 | 0.548 | ||||
| WLBal7 | 0.759 |
Source(s): Table by authors
Heterotrait-monotrait ratio (HTMT)
| Value | |
|---|---|
| Continuance commitment → affective commitment | 0.103 |
| Job satisfaction → affective commitment | 0.774 |
| Job satisfaction → continuance commitment | 0.220 |
| Normative commitment → affective commitment | 0.638 |
| Normative commitment → continuance commitment | 0.162 |
| Normative commitment → job satisfaction | 0.317 |
| Work–life balance → affective commitment | 0.511 |
| Work–life balance → continuance commitment | 0.159 |
| Work–life balance → job satisfaction | 0.735 |
| Work–life balance → normative commitment | 0.211 |
Source(s): Table by authors
Latent variables correlations
| Variable | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|
| 1. Affective commitment | – | ||||
| 2. Continuance commitment | 0.067 | – | |||
| 3. Normative continuance | 0.487*** | 0.115 | – | ||
| 4. Job satisfaction | 0.459*** | 0.017 | 0.082 | – | |
| 5. Work–life balance | 0.397*** | −0.008 | 0.064 | 0.467*** | – |
| Mean | 17.90 | 19.04 | 17.42 | 23.46 | 22.136 |
| Standard deviation | 5.23 | 6.88 | 5.76 | 6.936 | 6.69 |
Note(s): *p < 0.05, **p < 0.01, ***p < 0.001
Source(s): Table by authors
Hypotheses test results
| Relationship paths | Direct effects | f-squared | Indirect effects | Total effects | ||||
|---|---|---|---|---|---|---|---|---|
| Regression coefficients | p values | Regression coefficients | p values | Regression coefficients | p values | |||
| Job satisfaction → affective commitment | 0.617 | 0.000 | 0.466 | 0.617 | 0.000 | |||
| Job satisfaction → continuance commitment | −0.163 | 0.420 | 0.018 | −0.163 | 0.420 | |||
| Job satisfaction → normative commitment | 0.272 | 0.047 | 0.053 | 0.272 | 0.047 | |||
| Work–life balance → affective commitment | 0.082 | 0.322 | 0.008 | 0.433 | 0.000 | H1 Rejected | ||
| Work–life balance → continuance commitment | 0.061 | 0.704 | 0.003 | −0.031 | 0.803 | H2 Rejected | ||
| Work–life balance → job satisfaction | 0.568 | 0.000 | 0.476 | 0.568 | 0.000 | H4 Accepted | ||
| Work–life balance → normative commitment | −0.068 | 0.692 | 0.003 | 0.087 | 0.562 | H3 Rejected | ||
| Work–life balance → job satisfaction → affective commitment | 0.351 | 0.000 | H5 Accepted | |||||
| Work–life balance → job satisfaction → continuance commitment | −0.093 | 0.440 | H6 Rejected | |||||
| Work–life balance → job satisfaction → normative commitment | 0.154 | 0.049 | H7 Accepted | |||||
Source(s): Table by authors
Predictive quality of the model
| Variable | R2 | Adjusted R2 | Q2 |
|---|---|---|---|
| Affective commitment | 0.445 | 0.435 | 0.227 |
| Continuance commitment | 0.019 | 0.001 | −0.019 |
| Job satisfaction | 0.323 | 0.316 | 0.116 |
| Normative commitment | 0.057 | 0.040 | 0.015 |
Source(s): Table by authors
Outer VIF values
| Affective commitment | Continuance commitment | Job satisfaction | Normative commitment | |
|---|---|---|---|---|
| Affective commitment | ||||
| Continuance commitment | ||||
| Job satisfaction | 1 | 1 | 1 | |
| Normative commitment | ||||
| Work–life balance | 1 |
Source(s): Table by authors
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Further reading
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Rodrigo, R. (2022), “The trouble with ‘work–life balance’ in neoliberal academia: a systematic and critical review”, Journal of Gender Studies, Vol. 31 No. 1, pp. 55-73.
Virick, M., Lily, J.D. and Casper, W.J. (2007), “Doing more with less: an analysis of work life balance among layoff survivors”, Career Development International, Vol. 12 No. 5, pp. 463-480.