Work-life balance, job satisfaction and turnover intention amongst information technology employees

Abstract

Talent retention is of particular concern in the information technology
(IT) sector owing to globalisation, the skills shortage and rapidly
advancing technology. Employee turnover has signifi cant costs and
negative consequences for organisations. The objective of this study
was to explore the association between employees’ experiences of
work-life balance (as measured by the Survey Work-Home Interaction-
Nijmegen), job satisfaction (as measured by the Minnesota Satisfaction
Questionnaire) and their turnover intention (as measured by the Turnover
Intention Scale). A random sample of 79 permanently employed salaried
employees in a South African IT company participated in the study. The
participants were represented by predominantly white and married
people between the ages of 26 and 45 and people with more than 10
years’ tenure. Regression analysis showed that experiences of negative
work-home interaction and positive work-home interaction signifi cantly
predicted job satisfaction and turnover intention. Job satisfaction also
signifi cantly predicted turnover intention. However, no interaction effect
was observed between overall work-life balance and job satisfaction in
predicting turnover intention. White employees had signifi cantly stronger
experiences of job satisfaction and negative home-work interface,
while black employees had signifi cantly stronger positive experiences
of home-work interface and lower levels of job satisfaction. White and
black employees, marital status and tenure groups differed signifi cantly
regarding their job satisfaction. Talent retention strategies should
consider the relationships between work-life balance, job satisfaction and
turnover intention.

Full text

446 iSouthern African Business Review Volume 20 2016
Work-life balance, job satisfaction and turnover
intention amongst information technology employees
R.M. Oosthuizen, M. Coetzee & Z. Munro
10ABSTRACT
20Talent retention is of particular concern in the information technology
(IT) sector owing to globalisation, the skills shortage and rapidly
advancing technology. Employee turnover has signifi cant costs and
negative consequences for organisations. The objective of this study
was to explore the association between employees’ experiences of
work-life balance (as measured by the Survey Work-Home Interaction-
Nijmegen), job satisfaction (as measured by the Minnesota Satisfaction
Questionnaire) and their turnover intention (as measured by the Turnover
Intention Scale). A random sample of 79 permanently employed salaried
employees in a South African IT company participated in the study. The
participants were represented by predominantly white and married
people between the ages of 26 and 45 and people with more than 10
years’ tenure. Regression analysis showed that experiences of negative
work-home interaction and positive work-home interaction signifi cantly
predicted job satisfaction and turnover intention. Job satisfaction also
signifi cantly predicted turnover intention. However, no interaction effect
was observed between overall work-life balance and job satisfaction in
predicting turnover intention. White employees had signifi cantly stronger
experiences of job satisfaction and negative home-work interface,
while black employees had signifi cantly stronger positive experiences
of home-work interface and lower levels of job satisfaction. White and
black employees, marital status and tenure groups differed signifi cantly
regarding their job satisfaction. Talent retention strategies should
consider the relationships between work-life balance, job satisfaction and
turnover intention.
21Key words: Knowledge workers, IT employees, work-life balance, job satisfaction, turnover
intention, talent management, talent retention
Prof. R.M. Oosthuizen and Prof. M. Coet zee are i n the Departm ent of Ind ustri al and Organis ational Psychology a nd Mrs Z .
Munro is a s tudent in the Department of In dustr ial and O rganisational Psych ology, University of South Africa. E-mail:
oosthrm@unisa.ac.za

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Work-life balance, job satisfaction and turnover intention amongst information technology
Introduction
1Against the background of globalisation, the skills shortage and the “talent war”,
it is evident that talent retention is a strategic issue for an organisation’s survival,
adaptation and competitive advantage (Martins & Coetzee 2007; Munro 2015;
Takawira, Coetzee & Schreuder 2014; Van Dyk & Coetzee 2012). The knowledge
economy has led to increased competition for those employees with scarce and
desirable skills, knowledge and experience. In the knowledge economy, the skills
and knowledge (human and intellectual capital) of employees are often the main
enablers for organisations to leverage a competitive advantage (Botha, Bussin & De
Swardt 2011; Van Staden & Du Toit 2011). An organisation’s success depends on
the mental ability of a relatively small number of highly skilled knowledge workers
(Ramsey & Barkhuizen 2011). When knowledge workers leave, the organisation loses
the knowledge they take with them and cannot sustain its competitive advantage
(Ramsey & Barkhuizen 2011). The challenge for organisations in the knowledge
economy is to optimise, create, transfer, assemble, protect and exploit knowledge
assets that underpin organisational competencies, which in turn underscore their
products and services (Ramsey & Barkhuizen 2011).
Talent retention in the IT sector is of particular concern because the global labour
market provides increased career opportunities for IT professionals who have strong
tendencies to leave their organisations (Munro 2015; Van Dyk & Coetzee 2012). IT
professionals are regarded as key knowledge workers (Lumley, Coetzee, Tladinyane
& Ferreira 2011) who have specialised knowledge and skills that are difficult to
replace (McKnight, Philips & Hardgrave 2009). The increasing demand for skilled
IT professionals has forced organisations to start devising retention strategies aimed
at retaining IT employees with critical skills and experience (Mohlala, Goldman &
Goosen 2012). The retention of IT employees is critical to an organisation, as they
hold tacit knowledge about the interface between systems and key business processes
(McKnight et al. 2009). Employee turnover has significant costs and negative
consequences for any organisation (Bothma 2011; Du Plooy & Roodt 2010; 2013;
Takawira et al. 2014) including impaired organisational functioning, service delivery
and administration (Bothma & Roodt 2012; 2013).
Objectives of the study
1Research has shown that the experiences of work-life balance and job satisfaction
and their turnover intention are important to consider in the retention of knowledge
workers (Döckel, Basson & Coetzee 2006; Van Dyk & Coetzee 2012). The retention
of highly skilled professional employees such as IT staff becomes more complex

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448
when considering the multi-culturally diverse workplace represented by South
African organisations (Munro 2015). The aim of this study was therefore to explore
the association between a sample of IT staff ’s experiences of work-life balance, job
satisfaction and turnover intention, and whether individuals from different age,
gender, ethnicity, marital status and tenure groups differed significantly in relation to
these variables. Knowledge of the association between employees’ work-life balance,
job satisfaction and turnover intentions and how diverse groups of IT employees
differ in relation to these variables, could potentially help to inform strategies aimed
at improving employee (“talent”) retention in the IT sector.
Work-life balance
1The concept of work-life balance has been growing in interest amongst academics
and practitioners and is at the core of issues central to human resource development
(Sturges & Guest 2004). Work-life balance is defined as the degree to which an
individual is engaged in and equally satisfied with his or her work role and family
role consisting of the following three dimensions of work-family balance: time
balance, involvement balance and satisfaction balance (Greenhaus, Collins & Shaw
2003). Time balance involves devoting equal time to work and family. Involvement
balance entails equal involvement in work and family (Greenhaus et al. 2003).
Satisfaction balance means equal satisfaction with work and family (Greenhaus et
al. 2003; Chimote & Srivastava 2013).
Sturges and Guest (2004) posit that work-life balance denotes a balance not only
between work and family, but also between work and the rest of one’s life activities.
According to Koekemoer and Mostert (2010), various researchers in the work-family
literature have classified previously researched antecedents of work-life balance into
the following three main categories: demographic and personal characteristics, family
or non-work characteristics and work- or job-related characteristics. Demographic
and personal characteristics include gender, age, family status, negative affectivity
and personality (Koekemoer & Mostert 2010). Family or non-work characteristics
include social support, parental stressors, family role ambiguity and family stressors
(Koekemoer & Mostert 2010). Work- or job-related characteristics include work
stressors, work demands, hours spent at work, job stress, job support and flexibility at
work (Koekemoer & Mostert 2010).
The literature suggests many positive implications of experiences of work-life
balance, including the following: Work-home interaction (WHI) functions as an
important intervening pathway between potential stressors in the work and home
domains and psychological health (Geurts, Rutte & Peeters 1999); WHI mediates

449
the impact of workload on workers’ well-being (Geurts et al. 2003); work experiences
and family experiences can have additive effects on well-being (Voydanoff 2001);
and participating in multiple roles can have beneficial effects on both physical and
psychological well-being (Barnett & Hyde 2001; Demerouti & Geurts 2004; Geurts
et al. 1999; Geurts & Demerouti 2003; Voydanoff 2001). Furthermore, participating
in multiple roles protects individuals from the effects of negative experiences in any
one role (Barnett & Hyde 2001). In addition, work-family balance is considered to
promote well-being (Greenhaus et al. 2003). However, the findings of Frone, Russell
and Cooper (1997) suggest that both time- and strain-based WHI may compromise
opportunities to recover from work demands, which in turn increases the chances
that the demands of work will erode affective well-being and subjective health.
The South African socio-economic, political and societal circumstances influence
employees’ experiences of work-life balance differently in comparison with other
countries. This is because of employment equity, where previously disadvantaged
individuals become part of the workforce and are influenced by Westernisation that
could potentially transform traditional, culture-specific family roles (Brink & De la
Rey 2001). Little is known about how different resource characteristics such as race
and culture shape the work-family experience (Potgieter & Barnard 2010). Mostert and
Oldfield (2009) found significant differences in the work-home interaction amongst
different socio-demographic groups (including ethnicity) and recommended further
research of work-life balance differences in different socio-demographic groups.
An employee’s age has an influence on his or her attitude to work, as job
involvement becomes more stable with an employee’s age, mainly because of job
conditions becoming more stable (Lorence & Mortimer 1985). Sturges and Guest
(2004) suggest that the relationship between work and non-work is more important
to young employees than it is to other groups of workers, as young employees wish
to develop and manage their own careers on their own terms, with a key focus being
the achievement of balance between the work and non-work aspects of their lives.
Job satisfaction
1Job satisfaction refers to the intrinsic-extrinsic definition of job satisfaction of
Weiss, Dawis, England and Lofquist (1967). Intrinsic satisfaction is derived from
performing work and consequently experiencing the feelings of accomplishment,
self-actualisation and identity with the work (Martin & Roodt 2008). Extrinsic
satisfaction results from satisfaction with the work environment (Weiss et al. 1967)
and is derived from the rewards the individual receives from peers, managers or the
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organisation, which can take the form of advancement compensation or recognition
(Martin & Roodt 2008).
The satisfaction level of employees plays a critical role in retaining employees,
particularly those regarded as core employees or knowledge workers (Döckel et al
2006; Martins & Coetzee 2007). Organisations are attempting to understand why
people leave and what strategies can be implemented to retain those employees
(Martins & Coetzee 2007). The optimal functioning of an organisation depends in
part on the level of job satisfaction of employees, as their full potential is needed at all
levels of the organisation (Rothmann & Coetzer 2002). Employees seek congruence
with the organisation, which can be described in terms of employees fulfilling the
requirements of the organisation and the organisation fulfilling the requirements of
its employees (Rothmann & Coetzer 2002). Employees will experience job satisfaction
if they perceive that their capacities, experience and values can be utilised at work and
that their work offers them opportunities and rewards (Rothmann & Coetzer 2002).
Information on job satisfaction is valuable to an organisation, as satisfied employees
experience physical and psychological well-being, while dissatisfied employees
are more likely to be associated with absenteeism, psychological withdrawal and
employee turnover (Rothmann & Coetzer 2002).
Job satisfaction involves employees’ affective or emotional feelings and has major
consequences for their lives (Sempane, Rieger & Roodt 2002). Information on the job
satisfaction of employees is valuable to organisations (Rothmann & Coetzer 2002).
Numerous research studies have been conducted to assess the effects of job satisfaction
on employee productivity, absenteeism and turnover (Robbins 2001). Roznowski and
Hulin (1992) found that job dissatisfaction is related to absenteeism, trade union
activities and psychological withdrawal. If an organisation does not create conditions
for minimal levels of job satisfaction, this may result in deterioration in productivity,
increased employee turnover and absenteeism and a decline in morale (McKenna
2000).
Job satisfaction tends to be associated with a number of individual and
organisational variables that include gender, age, education, hours of work and
the size of the establishment (Blyton & Jenkins 2007). Research has shown that
demographic factors such as gender, age, tenure and race are associated with job
satisfaction (Ghazzawi 2008; Martin & Roodt 2008; Spector 1997). Research indicates
an inconsistency in results comparing gender (Ghazzawi 2008; Spector 1997; 2008)
and racial groups (Martin & Roodt 2008). Also, a positive linear relationship has
been reported between employee age and job satisfaction, showing that employees
become more satisfied with their job as their chronological age progresses (Martin
& Roodt 2008). According to Bretz and Judge (1994), job tenure is the most basic

451
indicator of person-environment fit. An employee will remain in an environment he
or she prefers (satisfaction), while the environment too finds the person acceptable
(satisfactoriness). Employees seek to achieve and maintain correspondence with their
environment (Weiss et al. 1967).
Turnover intention
1Turnover intention is defined as “the conscious and deliberate wilfulness to leave
the organisation” (Tett & Meyer 1993: 262). In other words, it is the extent to which
an employee plans to leave or stay with the organisation (Bothma & Roodt 2013;
Jacobs & Roodt 2011). According to Tett and Meyer (1993), the intention to leave the
organisation is the final step in a series of withdrawal cognitions leading to actual
turnover. Job satisfaction and turnover intentions were found to be precursors in the
withdrawal process which predict voluntary employee turnover (Du Plooy & Roodt
2010).
Employee turnover has significant costs and negative consequences for any
organisation (Bothma 2011). The loss of highly skilled employees may have disruptive
implications, which may include impaired organisational functioning, service delivery
and administration (Bothma & Roodt 2012; 2013). Additionally, the loss of highly
skilled employees may carry increased costs of rehiring and retraining employees
(Bothma & Roodt 2012; 2013). These consequences provide a sound rationale for
the study of turnover intention. Jacobs’ (2005) turnover intention model proposes
that positive or negative perceptions of organisational culture (predictors) are related
to turnover intentions (criterion). Variables such as job satisfaction, organisational
citizenship behaviour, organisational commitment and knowledge sharing mediate
this relationship (Bothma & Roodt 2013). Research by Igbaria, Meredith and Smith
(1994) found that organisational commitment and job satisfaction are the most
immediate predictors of intention to stay with the organisation.
According to Kennedy (2006), although there is no single identifiable variable
that can be identified as the primary cause of turnover intention, it has been
positively correlated with age, years of employment, education, caseload complexity,
self-esteem, organisational culture and job satisfaction. Research by Quan and Cha
(2010) concluded that past turnover behaviour is a strong predictor of future turnover
intentions, and that age, education, work experience, salary, past turnover behaviour
and work hours are functional in formulating turnover intentions.
According to Ding and Lin (2006), career satisfaction and job satisfaction have
the most significant effects on turnover intentions, with organisational commitment
mediating the relationship. Research by Pienaar, Sieberhagen and Mostert (2007)
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indicates that job satisfaction is the most significant predictor of turnover intention
and is significantly and negatively correlated with turnover intention. Tian-Foreman
(2009) found strong support for the hypothesised negative relationship between
employee turnover intention and job satisfaction. Wheeler, Gallagher, Brouer and
Sablynski’s (2007) research, however, revealed statistical support for the fact that
person-organisation misfit and job dissatisfaction do not necessarily lead to turnover
intention.
Identifying the key factors that may be related to turnover intention could enable
organisations and researchers to proactively identify the key determinants of turnover
and develop and manage strategies to reduce voluntary turnover (Mitchell, Holtom &
Lee 2001; Pienaar et al. 2007). Employee turnover has significant costs and negative
consequences for any organisation (Bothma 2011; Du Plooy & Roodt 2010, 2013;
Takawira et al. 2014), which may have disruptive implications, including impaired
organisational functioning, service delivery and administration and increased costs
of rehiring and retraining employees (Bothma & Roodt 2012; 2013). Research on
turnover intention can be used to manage the turnover process and help develop
strategies or interventions aimed at reducing employee turnover and its associated
costs (Du Plooy & Roodt 2010; Tuzun & Kalemci 2012).
Various research studies have found no significant relationship between gender
and turnover intention (Joseph, Ng, Koh & Ang 2007; Martin & Roodt 2008). Race
is a poor and inconsistent variable when used as a predictor of turnover intention
(Martin & Roodt 2008). However, Du Plooy and Roodt (2013) found that race
moderates the prediction of turnover intention. Research indicates a significant
relationship between the age of an employee and his or her turnover intention, with
turnover intentions decreasing as age increases (Chawla & Sondhi 2011; Ferres,
Travaglione & Firns 2003; Martin & Roodt 2008). Du Plooy and Roodt (2013) found
that age moderates the prediction of turnover intention. A significant relationship
exists between job tenure and turnover intention (Mkavga & Onyishi 2012).
Empirical research has shown positive associations between work-life balance
and job satisfaction (Virick, Lily & Casper 2007). An Australian study by Fox and
Fallon (2003) suggested that positive experiences of work-life balance significantly
increased levels of job satisfaction and decreased turnover intentions. It appears from
their study that turnover intention could be reduced by improving employees’ job
satisfaction through successful work-life balance. Noor (2011) also found significant
associations between employees’ work-life balance, job satisfaction and intentions to
leave the organisation. However, the nature of the association between these three
constructs and the way in which various biographical groups (age, gender, ethnicity,
marital status and tenure) differ regarding these constructs in the South African IT

453
environment are not well known. In the light of increasing concerns about retaining
valuable South African IT staff, the present study is deemed to be timely and
important. More specifically, the study aimed to answer the following three research
questions:
• What is the magnitude and direction of the association between individuals’ age,
gender, ethnicity, marital status, tenure, work-life balance, job satisfaction and
turnover intention?
• Do individuals’ experiences of work-life balance have an interaction (moderating)
effect with their job satisfaction in predicting their turnover intention?
• Do individuals from various age, gender, ethnicity, marital status and tenure
groups differ significantly regarding their experiences of work-life balance, job
satisfaction and turnover intention?
Method
Participants and procedure
1A quantitative cross-sectional survey-based research design was applied in this
study. The population for this empirical research comprised all the employees of an
IT organisation in South Africa with IT skills and experience (N = 440). A stratified
random sample of 260 (n = 260) was invited to participate voluntarily. A final
sample of 79 respondents (n = 79) completed the surveys, yielding a response rate
of 30.38%. The participants were represented by predominantly white (68%) and
black (African, coloured and Indian: 32%) people. Married (66%) and unmarried
(single and divorced: 34%) people between the ages of 26 and 45 (46%), and people
with more than 10 years’ tenure (62%) were representative of the sample.
Measuring instruments
1A biographical questionnaire was compiled and used in order to gather information
pertaining to the participants’ age, gender, ethnicity, marital status and tenure. The
Survey Work-Home Interaction-Nijmegen (SWING) instrument was used to
measure work-life balance (Geurts, Taris, Kompier, Dikkers, Van Hooff & Kinnunen
2005). This instrument distinguishes between four types of home-work-interaction,
namely negative home-work-interaction (NHWI); positive home-work-interaction
(PHWI); negative work-home-interaction (NWHI); and positive work-home-
interaction (PWHI) (Geurts et al. 2005; Marais, Mostert, Geurts & Taris 2009).
The items were answered on a four-response format varying from 0 (never) to 3
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R.M. Oosthuizen, M. Coetzee & Z. Munro
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(always). The following reliabilities have been found in South Africa: NWHI 0.85
– 0.90; PWHI 0.67 – 0.79; NHWI 0.78 – 0.79; PHWI 0.77 – 0.79 (Marais et al.
2009). In the present study, the Cronbach alpha coefficients for the SWING and its
sub-dimensions were greater or equal to 0.74 (high internal consistency reliability).
The Minnesota Satisfaction Questionnaire (MSQ20) (Weiss et al. 1967) was used
to measure job satisfaction. The MSQ measures both the intrinsic and extrinsic
dimensions of job satisfaction (Foxcroft & Roodt 2010). This study used the short
form of the MSQ, namely the MSQ20. The MSQ20 consists of 20 items and uses
a five-point Likert-type response format. Reliabilities in the South African context
have been reported, with alphas ranging from 0.79 to 0.85 (Buitendach & Rothmann
2009). In the present study, the Cronbach alpha coefficients for the MSQ20 and its
sub-dimensions were greater or equal to 0.89 (high internal consistency reliability).
Turnover intentions were measured with a six-item Turnover Intention Scale
(TIS-6) (Bothma & Roodt 2013). The response scale was scored on a five-item Likert
scale, varying between poles of intensity with 1 (never) to 5 (always) (Du Plooy &
Roodt 2010). A Cronbach alpha reliability coefficient of 0.80 has been reported for the
TIS-6 (Bothma & Roodt 2013). For the current study, the Cronbach alpha coefficient
for the TIS-6 was 0.88, indicating high internal consistency reliability.
Procedure and ethical considerations
1Ethical clearance to conduct the study was obtained from the Research Ethics
Committee of the institution, while permission to conduct the research was
obtained in writing from the directors of the organisation. All the participants
received in electronic format an information leaflet from the researcher informing
them of the nature of, reason for, confidentiality, ethical procedures and voluntary
nature of the study, together with a letter from the managing director of the
organisation informing participants of the benefits and value of the study for the
organisation, and encouraging their participation. The electronic leaflet provided
each participant with a URL link which directed him or her to the survey. Owing
to the possible sensitive nature of the study, participants were requested to complete
the survey anonymously. The data was collected over a two-week period. The
researcher maintained confidentiality, respected the participants’ privacy and kept
the completed questionnaires secure. No harm was done to the participants during
the study.
Statistical analysis
1The SPSS (Statistical Package for the Social Sciences Version 23 1989; 2015) and
the SAS (Statistical Analysis System Version 9.4 2002; 2012) programs were used

455
to analyse the data. Descriptive statistics summarised the means, deviations and
Cronbach alphas. Correlation coefficients were calculated to indicate the correlations
between the different biographical groups and between the variables. It was decided
to set the significance value at a 95% confidence interval level (p ≤ 0.05), in order
to counter the probability of a Type I error (Tredoux & Durrheim 2009). For the
purposes of this study, r values larger than 0.30 (medium effect) were regarded as
practically significant (Cohen 1992). Regression analysis was conducted to assess
whether the biographical variables and the work-life balance and job satisfaction
variables significantly predicted turnover intention and whether work-life balance
had a significant interaction effect with job satisfaction in predicting turnover
intention. The value of the adjusted R² was used to interpret the results, as a number
of independent variables had to be considered, with R² values larger than 0.13
(medium effect) regarded as practically significant (Cohen 1992). The significance
value for interpreting the results was set at Fp ≤ .05.
Independent samples T-tests determined whether there were significant mean
differences between the various biographical groups in relation to the respective
variables. Levene’s test for equality of variances was performed to determine variances
between the biographical groups. The significance value for interpreting the results
was set at p ≤ .05. One-sample Kolmogorov-Smirnov tests were conducted to test for
normality and determine whether the data was normally or non-normally distributed.
The results revealed a normal distribution of the data. Harman’s factor analysis was
conducted in order to measure common bias variance and determine whether the
majority of the variance could be explained by a single factor. No evidence of common
method bias was identified.
Results
1Table 1 indicates that the total mean average score of overall work-life balance was
(M = 2.21; SD = 0.37), indicating a relatively low level of work-life balance. The
participants obtained the highest mean score on the positive home-work interaction
(PHWI) sub-scale (M = 2.60; SD = 0.72), indicating above-average levels of
positive influence from home to work, while the lowest mean score was for negative
home-work interaction (NHWI) (M = 1.58; SD = .49), indicating very low levels
of negative influence from home to work. Furthermore, the total mean average
score of overall job satisfaction was (M = 3.65; SD = 0.72), indicating a relatively
high level of job satisfaction. The total mean average score of turnover intention was
(M = 2.86; SD = 1.08), indicating moderate levels of turnover intentions.
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1Research question 1: What is the magnitude and direction of the association between
individuals’ age, gender, ethnicity, marital status, tenure, work-life balance, job
satisfaction and turnover intention?
1Table 1 shows that negative work-home interaction (NWHI) had a significant
negative association with job satisfaction (r = -.39; p ≤ .001; moderate practical
effect size) and a positive association with turnover intention (r = .51; p ≤ .001;
large practical effect size). On the opposite scale, positive work-home interaction
(PWHI) had a significant positive association with job satisfaction (r = .48; p
≤ .001; moderate practical effect size) and a negative association with turnover
intention (r = -.43; p ≤ .001; moderate practical effect size). Overall job satisfaction
had a significant negative association with turnover intention (r = -.77; p ≤ .001;
large practical effect size). The r values were below the concerns for possible multi-
collinearity (r ≤.80).
In terms of the biographical variables, negative work-home interaction (NWHI)
had a negative correlation with age (r = -.25: p ≤ .03; small practical effect size)
indicating that NWHI decreased with age. Positive work-home interaction (PWHI)
had a positive correlation with age (r = .31: p ≤ .01; medium practical effect size)
and a positive correlation with tenure (r = .24: p ≤ .03; small practical effect
size), indicating that PWHI increased with age and tenure. Negative home-work
interaction (NHWI) had a positive correlation with ethnicity (r = .31: p ≤ .01;
medium practical effect size), while positive home-work interaction (PHWI) had a
negative correlation with ethnicity (r = -.29: p ≤ .01; small practical effect size).
Job satisfaction had a positive significant correlation with age (r = .40: p ≤ .05;
medium practical effect size), tenure (r = .41: p ≤ .05; medium practical effect size)
and ethnicity (r = .23: p ≤ .04; small practical effect size), but a negative correlation
with marital status (r = -.22: p ≤ .05; small practical effect size). Turnover intention
had a negative correlation with age (r = -.43: p ≤ .05; medium practical effect size),
indicating that an increase in age would lead to a decrease in turnover intention.
Turnover intention also had a negative correlation with tenure (r = -.29: p ≤ .01;
small practical effect size).
1Research question 2: Do individuals’ experiences of work-life balance have an interaction
(moderating) effect with their job satisfaction in predicting their turnover
intention?
1Two regression models were computed to explore (1) whether the biographical
variables and the work-life balance variables significantly predict overall job
satisfaction, and (2) the main effects of the biographical variables, the work-life
balance variables and overall job satisfaction in predicting turnover intention and

457
the interaction (moderating) effect between overall work-life balance and job
satisfaction in predicting turnover intention. Dummy variables were created for the
biographical variables: age: < 35 years = 0; > 36 years = 1; gender: male = 0;
female = 1; marital status: single/divorced = 0; married = 1; tenure: < 10 years =
0; > 10 years = 1.
Table 2 shows that in terms of job satisfaction, the regression model was significant
(job satisfaction as the dependent variable; F = 6.78; p ≤ .0001). The model explained
40% (R² = .40; large practical effect) of the variance in job satisfaction. Ethnicity
(ß = .26; p ≤ .05; sr² = .04; moderate practical effect in terms of incremental variance
explained) and positive work-home interaction (PWHI: ß = .42; p ≤ .01; sr² = .08;
moderate practical effect in terms of incremental variance explained) contributed
positively and significantly in explaining the variance in job satisfaction, while
negative work-home interaction (NWHI: ß = -.24; p ≤ .05; sr² = .04; moderate
practical effect in terms of incremental variance explained) contributed significantly
and negatively in explaining the variance in job satisfaction. The semi-partial values
showed that positive work-home interaction contributed the most in terms of the
incremental variance explained in job satisfaction.
In terms of turnover intention, Table 2 shows that the regression model was
significant (turnover intention as the dependent variable; F = 13.75; p ≤ .0001). The
model explained 65% (R² = .65; large practical effect) of the variance in turnover
intention. Gender (ß = .16; p ≤ .05; sr² = .02; moderate practical effect in terms of
incremental variance explained) and negative work-home interaction (NWHI: ß =
.32; p ≤ .001; sr² = .06; moderate practical effect in terms of incremental variance
explained) contributed positively and significantly in explaining the variance in
turnover intention. Job satisfaction had a major and negative significant effect in
predicting turnover intention ( ß = -.65; p ≤ .001; sr² = .22; large practical effect in
terms of incremental variance explained). The semi-partial values showed that job
satisfaction contributed the most in terms of the incremental variance explained in
turnover intention. No significant interaction effect between work-life balance and
job satisfaction in predicting turnover intention was observed.
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Table 1: Descriptive statistics: Means, standard deviations, internal consistency reliability coe cients and correlation coe cients between
the biographical and construct variables
mmmcxxvVariables mmmcxxviMean mmmcxxviiSD mmmcxxviiiαmmmcxxix1mmmcxxx2mmmcxxxi3mmmcxxxii4mmmcxxxiii5mmmcxxxiv6mmmcxxxv7mmmcxxxvi8mmmcxxxvii9mmmcxxxviii10 mmmcxxxix11 mmmcxl12
mmmcxli1mmmcxliiAge mmmcxliii–mmmcxliv–mmmcxlv–mmmcxlvi–mmmcxlvii–mmmcxlviii–mmmcxlix–mmmcl–
mmmcli2mmmcliiGender mmmcliii–mmmcliv–mmmclv–mmmclvi–mmmclvii–mmmclviii–mmmclix–mmmclx–
mmmclxi3mmmclxiiEthnicity mmmclxiii–mmmclxiv–mmmclxv–mmmclxvi–mmmclxvii–mmmclxviii–mmmclxix–mmmclxx–
mmmclxxi4mmmclxxiiMarital status mmmclxxiii–mmmclxxiv–mmmclxxv–mmmclxxvi–mmmclxxvii–mmmclxxviii–mmmclxxix–mmmclxxx–
mmmclxxxi5mmmclxxxiiTenure mmmclxxxiii–mmmclxxxiv–mmmclxxxv–mmmclxxxvi–mmmclxxxvii–mmmclxxxviii–mmmclxxxix–mmmcxc–
mmmcxci6mmmcxciiNWHI mmmcxciii2.12 mmmcxciv.61 mmmcxcv.89 mmmcxcvi-.25* mmmcxcvii.11 mmmcxcviii-.05 mmmcxcix-.05 mmmcc-.09 mmmcci–
mmmccii7mmmcciiiPWHI mmmcciv2.35 mmmccv.65 mmmccvi.74 mmmccvii.31** mmmccviii-.06 mmmccix.04 mmmccx-.21 mmmccxi.24 mmmccxii-.21 mmmccxiii–
mmmccxiv8mmmccxvNHWI mmmccxvi1.58 mmmccxvii.49 mmmccxviii.85 mmmccxix-.03 mmmccxx-.08 mmmccxxi.31** mmmccxxii-.09 mmmccxxiii-.01 mmmccxxiv.30** mmmccxxv.13 mmmccxxvi–
mmmccxxvii9mmmccxxviiiPHWI mmmccxxix2.60 mmmccxxx.72 mmmccxxxi.74 mmmccxxxii.18 mmmccxxxiii-.09 mmmccxxxiv-.28** mmmccxxxv.01 mmmccxxxvi-.01 mmmccxxxvii.03 mmmccxxxviii.62*** mmmccxxxix.00 mmmccxl–
mmmccxli10 mmmccxliiOverall work-
life balance
mmmccxliii2.21 mmmccxliv.37 mmmccxlv.80 mmmccxlvi.11 mmmccxlvii-.05 mmmccxlviii-.12 mmmccxlix-.12 mmmccl.08 mmmccli.60*** mmmcclii.58*** mmmccliii.46*** mmmccliv.71*** mmmcclv–
mmmcclvi11 mmmcclviiOverall job
satisfaction
mmmcclviii3.65 mmmcclix.72 mmmcclx.94 mmmcclxi.40*** mmmcclxii.10 mmmcclxiii.23* mmmcclxiv-.22* mmmcclxv.41*** mmmcclxvi-.39*** mmmcclxvii.48*** mmmcclxviii-.08 mmmcclxix.15 mmmcclxx.00 mmmcclxxi–
mmmcclxxii12 mmmcclxxiiiTurnover
intention
mmmcclxxiv2.86 mmmcclxxv1.08 mmmcclxxvi.88 mmmcclxxvii-.43*** mmmcclxxviii-.18 mmmcclxxix-.11 mmmcclxxx.16 mmmcclxxxi-.28** mmmcclxxxii.51*** mmmcclxxxiii-.43*** mmmcclxxxiv.06 mmmcclxxxv-.11 mmmcclxxxvi.10 mmmcclxxxvii-.77*** mmmcclxxxviii–
1Notes: N = 79. *** p ≤ .001; ** p ≤ .01; * p ≤ .05 (two-tailed). NWHI: negative work-home interaction; PWHI: positive work-home interaction; NHWI: negative home-
work interaction; PHWI: positive home-work interaction

459
Table 2: Regression analysis results
mmmcclxxxixPredictor mmmccxcJob satisfaction mmmccxciTurnover intention
mmmccxciißmmmccxciiitmmmccxcivsr²mmmccxcvßmmmccxcvitmmmccxcviisr²
mmmccxcviiiAge mmmccxcix.03 mmmccc- -.33 mmmccci-.10 mmmcccii-1.30
mmmccciiiGender mmmccciv-.13 mmmcccv-1.35 mmmcccvi.16 mmmcccvii-2.06* mmmcccviii.02
mmmcccixEthnicity mmmcccx.26 mmmcccxi-2.38* mmmcccxii.04 mmmcccxiii.06 mmmcccxiv - .67
mmmcccxvMarital status mmmcccxvi.13 mmmcccxvii-1.34 mmmcccxviii-.01 mmmcccxix - -.16
mmmcccxxTenure mmmcccxxi.11 mmmcccxxii-1.002 mmmcccxxiii.09 mmmcccxxiv-1.10
mmmcccxxvNWHI mmmcccxxvi-.24 mmmcccxxvii-2.35* mmmcccxxviii.04 mmmcccxxix.32 mmmcccxxx-3.78*** mmmcccxxxi.06
mmmcccxxxiiPWHI mmmcccxxxiii.42 mmmcccxxxiv-3.19** mmmcccxxxv.08 mmmcccxxxvi-.71 mmmcccxxxvii- -.48
mmmcccxxxviiiNHWI mmmcccxxxix-.14 mmmcccxl-1.35 mmmcccxli.12 mmmcccxlii-1.42
mmmcccxliiiPHWI mmmcccxliv-.01 mmmcccxlv - -.05 mmmcccxlvi.01 mmmcccxlvii -- .13
mmmcccxlviiiOverall work-life
balance
mmmcccxlix-.002 mmmcccl- -.02 mmmcccli.100 mmmccclii- -.87
mmmcccliiiOverall job satisfaction mmmcccliv-.65 mmmccclv-6.97*** mmmccclvi.22
mmmccclviiOverall job satisfaction
x Overall work-life
balance
mmmccclviii.10 mmmccclix-1.35
mmmccclxModel
mmmccclxiFp mmmccclxii6.78*** mmmccclxiii13.75***
mmmccclxivAdjusted R² mmmccclxv.40 mmmccclxvi.65
1Notes: N = 79. *** p ≤ .001; ** p ≤ .01; * p ≤ .05. NWHI: negative work-home interaction; PWHI: positive work-home
interaction; NHWI: negative home-work interaction; PHWI: positive home-work interaction.
1Research question 3: Do individuals from various age, gender, ethnicity, marital status
and tenure groups differ significantly regarding their experiences of work-life
balance, job satisfaction and turnover intention?
1Table 3 summarises only the significant differences that were observed for the
biographical groups in terms of their work-life balance, job satisfaction and turnover
intention levels. In terms of work-life balance, the white participants had significantly
stronger experiences (mean: 1.68 vs 1.37; p ≤ .01; d = .69, moderate practical effect)
of negative home-work interaction (NHWI) and overall job satisfaction (mean: 3.77
vs 3.38; p ≤ .01; d = .52, moderate practical effect) than their black counterparts.
The black participants had significantly stronger experiences (mean: 2.99 vs 2.41; p
≤ .001; d = .86, large practical effect) of positive home-work interaction (PHWI)
than their white counterparts.
Work-life balance, job satisfaction and turnover intention amongst information technology

R.M. Oosthuizen, M. Coetzee & Z. Munro
460
The married participants had significantly higher levels of job satisfaction (mean:
3.80 vs 3.36; p ≤ .01; d = .61, moderate practical effect) than their unmarried
counterparts. Participants with less than 10 years’ tenure had significantly lower
levels of job satisfaction (mean: 3.32 vs 3.85; p ≤ .001; d = .78, moderate practical
effect) and higher turnover intention (mean: 3.18 vs 2.66; p ≤ .05; d = .50, moderate
practical effect) than those with more than 10 years’ tenure.
Table 3: Independent samples t-tests for signi cant mean di erences
mmmccclxviiLevene’s
test for
equality of
variance
mmmccclxviiiT-test for
equality of
means
mmmccclxixCohen d
mmmccclxxVariable mmmccclxxiBiographical group mmmccclxxiiNmmmccclxxiiiMean mmmccclxxivSD mmmccclxxvFp mmmccclxxvitmmmccclxxviidf
mmmccclxxviiiNHWI mmmccclxxixEthnicity mmmccclxxxWhite mmmccclxxxi54 mmmccclxxxii1.68 mmmccclxxxiii.49 mmmccclxxxiv1.87*mmmccclxxxv-2.70** mmmccclxxxvi77 mmmccclxxxvii.69
mmmccclxxxviiiBlack (African,
coloured,
Indian)
mmmccclxxxix25 mmmcccxc1.37 mmmcccxci.40
mmmcccxciiPHWI mmmcccxciiiEthnicity mmmcccxcivWhite mmmcccxcv54 mmmcccxcvi2.41 mmmcccxcvii.68 mmmcccxcviii.06*mmmcccxcix-3.55*** mmmcd77 mmmcdi.86
mmmcdiiBlack (African,
coloured,
Indian)
mmmcdiii25 mmmcdiv2.99 mmmcdv.67
mmmcdviOverall job
satisfaction
mmmcdviiEthnicity mmmcdviiiWhite mmmcdix54 mmmcdx3.77 mmmcdxi.62 mmmcdxii3.97* mmmcdxiii-2.29* mmmcdxiv77 mmmcdxv.52
mmmcdxviBlack (African,
coloured,
Indian)
mmmcdxvii25 mmmcdxviii3.38 mmmcdxix.86
mmmcdxxOverall job
satisfaction
mmmcdxxiMarital
status
mmmcdxxiiMarried mmmcdxxiii52 mmmcdxxiv3.80 mmmcdxxv.64 mmmcdxxvi1.01*mmmcdxxvii-2.65** mmmcdxxviii77 mmmcdxxix.61
mmmcdxxxOther (single/
divorced)
mmmcdxxxi27 mmmcdxxxii3.36 mmmcdxxxiii.79
mmmcdxxxivOverall job
satisfaction
mmmcdxxxvTenure mmmcdxxxvi<10 years mmmcdxxxvii30 mmmcdxxxviii3.32 mmmcdxxxix.68 mmmcdxl.01*mmmcdxli-3.38*** mmmcdxlii77 mmmcdxliii.78
mmmcdxliv>10 years mmmcdxlv49 mmmcdxlvi3.85 mmmcdxlvii.68
mmmcdxlviiiTurnover
intention
mmmcdxlixTenure mmmcdl<10 years mmmcdli30 mmmcdlii3.18 mmmcdliii.95 mmmcdliv2.35*mmmcdlv-2.15* mmmcdlvi77 mmmcdlvii.50
mmmcdlviii>10 years mmmcdlix49 mmmcdlx2.66 mmmcdlxi1.11
1Notes: N = 79. Signi cant di erences only are reported. *** p ≤ .001; ** p ≤ .01; * p≤ .05. NWHI: negative work-home
interaction; PWHI: positive work-home interaction; NHWI: negative home-work interaction; PHWI: positive home-
work interaction
Discussion
1Overall, the results corroborated research indicating significant associations
between individuals’ work-life balance, job satisfaction and turnover intention (Fox
& Fallon 2003; Noor 2011). In agreement with previous research, low levels of job
satisfaction significantly predicted high levels of turnover intention (Fox & Fallon

461
2003; Martin & Roodt 2008; Tian-Foreman 2009). Similar to research by Virick et
al. (2007), work-life balance was positively associated with job satisfaction. More
specifically, the present study suggested that experiences of positive work-home
interface (i.e. balance) may be associated with higher levels of job satisfaction and
experiences of negative work-home interface (imbalance) with lower levels of job
satisfaction. In line with this, it appears from the results that high levels of negative
work-home interaction are likely to result in higher levels of turnover intention. Fox
and Fallon (2003) also found that achieving work-life balance resulted in increased
levels of job satisfaction and decreased turnover intention. According to Downes
and Koekemoer (2011), organisations that invest heavily in work-life balance report
lower employee turnover. Muteswa and Ortlepp (2011) also recommended that
organisations create an environment conducive to maintaining work-life balance
in an attempt to retain staff. Organisations that fail to create conditions for minimal
levels of job satisfaction may suffer increased employee turnover (McKenna 2000).
However, no interaction effect was observed between overall work-life balance
and job satisfaction in predicting turnover intention. According to Pienaar et al.
(2007), job satisfaction generally tends to be the most significant predictor of turnover
intention. The results pertaining to tenure support Martin and Roodt’s (2008) findings
that, overall, job satisfaction increases as an employee’s years of experience increase
(Martin & Roodt 2008). The results of the present study further showed that the
same principle applied in terms of turnover intention, confirming the link between
high levels of job satisfaction and lower turnover intention. In terms of ethnicity, the
study corroborates the findings of previous studies indicating that white participants
tend to report higher levels of job satisfaction than black participants (Davis 1985;
O’Reilly & Roberts 1973; Tuch & Martin 1991). White employees had significantly
stronger experiences of job satisfaction and negative home-work interface, while black
employees had significantly stronger positive experiences of home-work interface and
lower levels of job satisfaction. Married people also appeared to experience higher
levels of job satisfaction than their counterparts.
Overall, it can be concluded that managers and human resources practitioners
should consider the ways in which work-life balance and job satisfaction relate to
the turnover intentions of IT employees as part of their talent retention strategies.
In addition, ethnicity significantly explains and predicts the variance in the job
satisfaction of IT employees, while gender explains the variance in the turnover
intentions of IT employees. The results indicated job satisfaction as a significant
predictor of turnover intention, suggesting that IT employees who are satisfied with
their jobs are less likely to have intentions to leave their organisations. Managers
and human resource practitioners should consider work-life balance initiatives aimed
Work-life balance, job satisfaction and turnover intention amongst information technology

R.M. Oosthuizen, M. Coetzee & Z. Munro
462
at improving the work-home interaction and job satisfaction of IT employees, thus
reducing their turnover intentions.
Limitations of the study and future research
1Considering the relatively small sample size, the results might not truly reflect the
demographics of South African IT organisations, and researchers should beware
of generalising the findings as being representative of all IT employees. Future
research with larger populations is recommended in order to generalise the findings
of this study. Since the current study was restricted to participants employed in
the IT sector, the findings cannot be generalised to other occupational contexts.
Furthermore, despite the use of a stratified sampling technique, the sample was not
entirely representative of the demographics of the organisation, as well as that of
the South African population, owing to the high response rate of white respondents
compared to that of black and Indian respondents. This limits the ability to draw
inferences from this study to the greater South African population as well as the IT
sector. Despite these limitations, the results of this empirical study indicated a linear
relationship between job satisfaction and turnover intention. In addition, the study
indicated relationships between various sub-dimensions of work-life balance and
job satisfaction amongst IT employees that could be explored in future research.
This study could be used as a basis for future research seeking to understand these
relationships in order to inform the talent retention strategies in the IT sector. It is
recommended that future research be conducted to examine the impact of talent
retention strategies and practices on the work-life balance, job satisfaction and
turnover intentions of IT employees over a period of time using a longitudinal study.
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