A resource-based perspective on work–family conflict: meta-analytical findings

Eko Yi Liao (Department of Management, The Hang Seng University of Hong Kong, Shatin, Hong Kong)
Victor P. Lau (Department of Management, The Hang Seng University of Hong Kong, Shatin, Hong Kong)
Ray Tak-yin Hui (Lee Shau Kee School of Business and Administration, Open University of Hong Kong, Kowloon, Hong Kong)
Kaylee Hao Kong (Department of Management, The Hang Seng University of Hong Kong, Shatin, Hong Kong)

Career Development International

ISSN: 1362-0436

Article publication date: 15 January 2019

Issue publication date: 31 January 2019

Abstract

Purpose

The purpose of this paper is to provide an updated and theory-driven meta-analysis of work–family conflict (WFC). The authors quantitatively review the relationships between WFC and three pairs of antecedents and several consequences.

Design/methodology/approach

A meta-analysis was conducted to investigate the research model. Specifically, the authors adopt a resource-based perspective (i.e. conservation of resources (COR) theory) to investigate the relationships between three pairs of antecedents (demand/control, autonomy/hours spent at both work and family domains and role overload/flexibility) and WFC. While COR theory argues that resource loss perceptions would generate much more influential impact on individuals comparing to that of resource gain, both favourable and unfavourable antecedents, representing resource gain and resource loss, respectively, are incorporated in each pair of antecedents. This inclusion of contrary antecedents allows the authors to investigate the comparison of the relationships between the favourable antecedents – WFC relationships and the unfavourable factors – WFC relationships. In addition, the authors analyse how and to what extent WFC influences employees’ attitudes (i.e. commitment), behaviours (i.e. performance) towards both work and family, and their career consequences.

Findings

The meta-analytical findings generally support the hypotheses. Work and family demands are found positively related to WFC, while having a control at either work or family would be negatively related to WFC. Perceiving a high level of autonomy at work is negatively related to WFC, and hours spend at work has a positive relation with WFC. Role overload at both work and family are associated with WFC, while having flexibility from work schedule would be negatively related to WFC. In addition, WFC is negatively related to employee career development outcomes.

Originality/value

First, the authors adopt a resource-based view to organise both favourable and unfavourable antecedents of WFC. Second, this paper aims at extending the investigation on WFC consequences to performance at both work and family, commitment to both work and family, and employee career outcomes, because all of them are critical consequences but not fully explored in previous meta-analyses. Third, this paper has incorporated newly explored correlates of WFC (e.g. employee career development-related outcomes) and quantitatively reviewed their relationships with WFC.

Keywords

Citation

Liao, E.Y., Lau, V.P., Hui, R.T.-y. and Kong, K.H. (2019), "A resource-based perspective on work–family conflict: meta-analytical findings", Career Development International, Vol. 24 No. 1, pp. 37-73. https://doi.org/10.1108/CDI-12-2017-0236

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited


Employees are facing unprecedented challenges and stress in coping with work and family interfaces. For example, job tasks are becoming more complicated such as multi-cultural communication has become a norm. Employees are often expected to work from home with tasks like dealing with instant messaging or video conferencing at night with overseas clients, which may sacrifice their time with family. Likewise, changes in family characteristics such as the increase in dual-earner couples or single parents may impede working life in the way that employees would find less energy and time reserved for work tasks. Accordingly, people may be experiencing work–family conflict (WFC) more than ever before (e.g. Pluut et al., 2018). WFC refers to employees’ perception of conflicts arising from the clashes and challenges of work and family issues, which may occur in two directions, with work interfering with family (WIF) or family interfering with work (FIW) (French et al., 2018). WFC has been examined in hundreds of empirical, experimental and review studies. In the literature, various antecedents and consequences of WFC have been identified (Frone et al., 1992). To our knowledge, there are 20 published meta-analyses related to WFC (Table I). Of these studies, the majority (15 out of 20) focussed on examining its antecedents, such as social supports (Byron, 2005; Ford et al., 2007; Kossek et al., 2011), contextual factors (Allen et al., 2013, 2015; Mesmer-Magnus and Viswesvaran, 2006), role stressors (Michel and Hargis, 2008; Michel et al., 2009, 2010) and personality traits (Allen et al., 2012; Michel, Clark and Jaramillo, 2011; Michel, Kotrba, Mitchelson, Clark and Baltes, 2011). Relatively fewer studies (9 out of 20) focussed on examining its consequences, such as job satisfaction, family satisfaction and life satisfaction (cf. Allen et al., 2000; Amstad et al., 2011; Kossek and Ozeki, 1998). Four of the studies included both antecedents and consequences in the same model, with three of these studies examining antecedents such as social supports and consequences such as family satisfaction (cf. Ford et al., 2007; Michel and Hargis, 2008; Michel et al., 2009) and one study examining strain as both an antecedent and consequence (Nohe et al., 2015). Furthermore, some meta-analyses have examined moderators, such as time spent at work (Amstad et al., 2011), or mediators, such as work/family hours (Shockley et al., 2017).

Different meta-analyses may draw on different theoretical perspectives. Informed by social support theory, French et al. (2018) dissected the effects of the different forms – behaviours and perceptions, sources – supervisor, co-worker and spouse and types – instrumental and emotional – of social support on WFC. Building upon personality theory, Michel, Clark and Jaramillo (2011) examined the effects of the Five Factor Model on work–non-work spillover. Using two competing theoretical perspectives, namely, segmentation theory and conflict theory, Michel et al. (2009, 2010) tested whether the same-domain or the cross-domain perspective is a more robust theoretical underpinning by comparing the effects of WIF and FIW on various forms of satisfactions. It is worth noting that several meta-analyses of WFC were interested in the comparisons of the same-domain and the cross-domain perspectives. Over two decades ago, based on the WFC model of Frone et al. (1992), Ford et al. (2007) quantitatively reviewed the permeability of the boundary between the work and family domains and found family satisfaction to be explained by work domain-specific variables (e.g. job involvement, job stress, work support and work hours), but job satisfaction to be explained by family domain-specific variables (e.g. family conflict, family stress, family support and family hours), suggesting cross-domain relations of the work–family interface. Several subsequent meta-analytic findings, however, have supported segmentation theory with direct effect links or same-domain satisfaction rather than conflict theory with indirect WFC links or cross-domain satisfaction. That is, WIF is a better predictor of job satisfaction, whereas FIW is a better predictor of family satisfaction (cf. Amstad et al., 2011; Michel and Hargis, 2008; Michel et al., 2009; Nohe et al., 2015; Shockley and Singla, 2011).

Despite these meta-analyses advancing our knowledge of WFC, three notable research gaps remain. First, an overarching theoretical underpinning that explains the logic across both the antecedents and consequences of WFC is lacking, with the exception of Nohe et al. (2015), who used conservation of resources (COR) theory (Hobfoll, 1989) as a theoretical lens to meta-analyse the reciprocal effects between WFC and strain, and Michel and Hargis (2008) and Michel et al. (2009), who compared whether the same-domain perspective or conflict theory (a cross-domain perspective) provides a better rationale behind the models. Most meta-analyses have either examined the antecedents (e.g. Allen et al., 2012, 2013; French et al., 2018; Shockley et al., 2017) or the consequences (Shockley and Singla, 2011). Also, most of them have only quantitatively reviewed the effect sizes without a clear overarching theoretical framework (e.g. Amstad et al., 2011; Kossek and Ozeki, 1998; Mesmer-Magnus and Viswesvaran, 2005, 2006). As such, two problems remain unsolved. One is the need for a sound overarching theoretical underpinning that supports the typologies of the antecedents and consequences of WFC. Another is the lack of differentiation between the favourable and unfavourable conditions of WFC, where favourable conditions are beneficial in reducing conflicts and unfavourable conditions may increase the perception of conflicts.

Second, the inclusion of WFC consequences in existing meta-analyses has been limited, with mainly satisfaction towards family/work/life and stress-related outcomes being included (e.g. Amstad et al., 2011; Michel and Hargis, 2008). Other critical outcomes, such as employee commitment in both the family and work domains and career consequences, have generally been overlooked, except by Allen et al. (2000) and Amstad et al. (2011). This may hinder researchers from developing more robust nomological networks of WFC in the future. Furthermore, although meta-analyses have investigated both work- and family-related outcomes, inclusions and comparisons of parallel antecedents from these two domains have often been ignored. For example, although Amstad et al. (2011) did include organisational commitment as an outcome of WFC, they did not examine the potentially negative influence of WFC on employees’ commitment to family functioning.

Third, an updated meta-analysis is warranted, as the new correlates of WFC (e.g. career consequences) from the latest empirical studies must be incorporated. Inconsistent findings of correlates from previous empirical research must also be incorporated to investigate the true effect sizes. For example, significant negative relationships between WFC and employee job performance have been found in some studies (e.g. Hoobler et al., 2009), whereas non-significant relationships have been indicated in others (e.g. Kossek et al., 2006). An integrative quantitative review (i.e. a meta-analysis) would help aggregate the empirical findings of individual studies and correct for different research artefacts in calculating more approximate effect sizes.

To address the above-mentioned research gaps, we have three objectives in conducting this study. First, we draw upon COR theory as an overarching theoretical underpinning to organise both the favourable and unfavourable antecedents of WFC. Specifically, we propose three pairs of WFC antecedents, each of which includes both favourable (e.g. perceived control at work) and unfavourable (e.g. perceived work demand) conditions. Second, we aim to extend the investigation on WFC consequences to both work performance and family performance, commitment to both work and family and employee career outcomes, all of which are critical consequences that have not been fully explored in previous meta-analyses. Specifically, individuals’ performances both at work and at home are the two most important functions to achieve work effectiveness and family harmony. Likewise, individuals’ commitment to both the work and family domains is important, as highly committed employees are more valued by their organisations and a high level of family commitment demonstrates loyalty and dedication to family roles. Employees’ career outcomes also help indicate the extent to which WFC may interfere with individuals’ career paths or become a critical obstacle to achieving career success. Despite their importance, these three types of outcomes have been discussed less in previous WFC meta-analytic reviews. Third, we aim to incorporate newly explored correlates of WFC such as employee career development-related outcomes and quantitatively review their relationships with WFC. Combining the results of this study and those of previous WFC meta-analyses, a more comprehensive nomological network of WFC is developed and investigated.

Theoretical underpinning and research model

We adopt COR theory to interpret the relationships between WFC and its correlates. COR theory argues that resources – conditions, personal characteristics, energy and objects – are instrumental for individuals to cope with stressful events and challenging situations (Hobfoll, 1989, 2001). Thus, people are inclined to develop and maintain important and critical resources across different situations to assist them in accomplishments and other expected outcomes. COR theory is an appropriate theoretical framework for this study for two reasons. First, COR theory provides arguments for the impact of resource gain vs resource loss on individuals’ perceptions and behaviours. WFC studies have largely focussed on either positive or negative antecedents of WFC or have not distinguished between the two types of antecedents. Thus, we contribute to the WFC literature by incorporating and comparing both types of WFC antecedents. To this end, the COR framework is helpful, as it clearly indicates how and to what extent individuals should be influenced by resource gain (i.e. favourable or positive antecedents) and resource loss (i.e. unfavourable or negative antecedents). Second, COR theory provides an overarching framework guiding the process through which individuals experience resource change (i.e. three groups of WFC antecedents), develop relevant perceptions (i.e. having high, medium or low levels of WFC perception) and in turn undergo attitudinal and behavioural consequences. We draw upon COR theory to develop the research model of this study (Figure 1).

To investigate the specific conditions of resource loss/gain related to WFC, we propose three pairs of antecedents (i.e. demand/control, hours spent/autonomy and role overload/flexibility). These three pairs of critical factors are related to employees’ perception of resource change. In each pair, both favourable conditions (e.g. perception of control at work) and unfavourable conditions (e.g. work demand) are proposed in a parallel and contrasting manner. For example, when employees face intense task demands at work, the more control they have, the better the performance and perception outcomes they may experience. To this end, the perception of control at work would be a contrasting force to the work demand. Consistent with COR theory, we argue that favourable conditions at work generate the perception of resource gain, whereas unfavourable conditions lead to negative perceptions, specifically the perception of resource loss (Hobfoll, 1989, 2011). For resource gain signals, we argue that having sufficient control over both work and family, acquiring independent decision-making latitude (i.e. job autonomy) and allowing flexible work arrangements (i.e. flexibility) are three critical situations that can help alleviate negative WFC perceptions. Of these three pairs of antecedents, except for autonomy and flexibility which only apply to work-related issues, all constructs pertain to both the family and work domains. Unfavourable conditions, such as facing intense work or family demands, spending long hours on various tasks (i.e. hours spent at work/with family) and being overburdened with tasks (i.e. work and family role overload), however imply resource loss to employees. As a result, employees are left with less power and energy to balance their work and family issues.

In terms of WFC consequences, from a COR perspective, WFC is stressful and challenging to employees because it implies more time, effort and energy needed to achieve the balance and compatibility between work and family issues. In turn, employees face potential and actual resource loss both at work and at home. Such resource loss is manifested in three ways. Employees’ positive attitudes are influenced such that they show less commitment to family and work. Furthermore, their functional behaviours (e.g. performance) at work and home decrease. Finally, their career development results are threatened. In the following section, we present our hypotheses.

Antecedents and WFC

According to Hobfoll’s (1989) COR theory, individuals seek to acquire, maintain and allocate resources (Hobfoll, 2001). Conditions are resources sought after particular situations such as employment, marriage and birth of children. They also represent the resource needs confined within or between such different roles at home and at work (Luk and Shaffer, 2005). Referring to Ahmad (2008), conditions are WFC predictors that can be classified into two types: job-related (e.g. work demand, work control, role overload, job autonomy and flexibility) and family-related (e.g. family demand, family control and family role overload). When individuals experience the fear of losing their job or family status due to insufficient or lack of resources to fulfil the needs of either their work or family roles, they may be forced to re-allocate their resources by drawing from one role to another (Grandey and Cropanzano, 1999). When individuals perceive their resources as insufficient to maintain the balance of resource needs (i.e. condition) between their work and family roles, they subsequently experience WFC.

Role demands and control

Work demand is defined as the resource commitment required to fulfil work responsibilities (McElwain et al., 2005), whereas family demand refers to the household maintenance and childcare responsibilities at home (McManus et al., 2002). Due to the limited nature of resources, higher demands in one role result in fewer resources for another role, which may be related to WFC. Research has provided strong empirical support for the negative impacts of work demand (e.g. Bhave et al., 2010; Boyar et al., 2007; Ilies et al., 2015; Pal and Saksvik, 2008; Westring and Ryan, 2011) and family demand (e.g. Bakker et al., 2008; Boyar et al., 2008; Choi, 2008) on WFC. As time and energy demands in the workplace or at home increase, the likelihood of those demands intruding upon the opposite domain increases, leading to WFC. For example, when employees are heavily occupied by family tasks like newborn baby care, home renovations or taking care of a sick family member, they experience a psychological burden and physical challenges that drain their time and energy from fully engaging in job tasks. Due to increasing demands either at home or at work interfering with their commitment to fulfil their responsibilities in another role, employees may experience negative perceptions of time and energy loss. This may lead to the perception of conflict arising from clashes in resource allocation to maintain a good balance between work and family. Thus, we propose the following hypotheses:

H1a.

Employees’ perceived work demand is positively related to WFC.

H1b.

Employees’ perceived family demand is positively related to WFC.

Despite work and family demands, the amount of control experienced by employees both at work and at home is also related to WFC (Kossek et al., 2006, 2012; Lapierre and Allen, 2012). Work control represents employees’ freedom to decide and self-manage the ways, the work goals and the arrangements of schedules to perform their work tasks by imposing their personal initiative and judgment. Family control represents employees’ degree of influence over home-related goals and responsibilities and over how and when to perform home-related tasks such as doing the laundry, purchasing groceries or planning a family outing on a given day. People may vary in the amount of control they have at work or at home. Greater control enables people to arrange and allocate their resources more easily to avoid interference between their work and family roles, reducing the potential for WFC. Thus, we propose the following hypotheses:

H2a.

Employees’ perceived work control is negatively related to WFC.

H2b.

Employees’ perceived family control is negatively related to WFC.

Time and autonomy

Time is an important resource that is exhaustible in nature. Individuals may spend and allocate their time to different roles in a mutually exclusive manner (Luk and Shaffer, 2005). In other words, once the time is spent on the tasks in one role, less time is available to spend on other tasks in another role. Therefore, when the average number of hours spent at work or home increases, the degree of WFC experienced by employees is likely to increase due to the increasing imbalance of the time allocation in performing well in both the work and family roles (Beham et al., 2011; Buonocore and Russo, 2013; Butts et al., 2015; Casper et al., 2011; Choi, 2008). Thus, we propose the following hypotheses:

H3a.

Employees’ work hours are positively related to WFC.

H3b.

Employees’ family hours are positively related to WFC.

Job autonomy is defined as the degree of control people have over when and how their work gets done (Behson, 2005). Job autonomy allows employees to use and allocate resources, such as time and energy, in more effective ways, which in turn may impact their ability to minimise their experience of WFC (e.g. Beham et al., 2012, 2014; Lambert and Haley-Lock, 2004). For example, employees can postpone less critical work tasks to handle family issues, such as taking sick children to see the doctor. Previous research has shown that perceived job autonomy may reduce WFC (Ahuja et al., 2007; DiRenzo et al., 2011; Hosking and Western, 2008; Lu et al., 2008). Thus, we propose the following hypothesis:

H4.

Employees’ perceived job autonomy is negatively related to WFC.

Overload and work flexibility

Overload is a state in which an individual’s capacity is not enough to handle and complete all of the demands they face at work (i.e. work role overload) or at home (i.e. family role overload; Aryee, Luk, Leung and Lo, 1999). When employees perceive that they have too many tasks to perform in a role but have insufficient time and energy to perform them, they are likely to experience overload (Caplan et al., 1975). Therefore, overload indicates a lack of resources to successfully perform work and family roles.

Based on Eckenrode and Gore’s (1990) spillover theory, Dierdorff and Ellington (2008) proposed that work/family overload caused by increased interdependence, responsibility for others and interpersonal conflict may lead to a significant resource drain in the work/family roles. The negative spillover effects between work and family boundaries refer to the reciprocal influence of individuals’ work and family roles (Grzywacz and Marks, 2000; Hanson et al., 2006). Such negative effects lead to employees’ emotional exhaustion and create the perception of losing critical resources, such as positive emotions (Wayne et al., 2017). The perceived deficiency of psychological and physiological resources needed to fulfil work/family role obligations may lead to employees’ increased fatigue and emotional exhaustion. Such exhaustion can subsequently increase the perceived conflict between work and family roles (Aryee et al., 2005). Studies have found both work role overload (Boyar et al., 2008; Dierdorff and Ellington, 2008; Reinardy, 2007) and family role overload (Aryee et al., 2005; Bakker et al., 2008; Matthews, Winkel and Wayne, 2014) to be related to WFC. Thus, we propose the following hypotheses:

H5a.

Employees’ work role overload is positively related to WFC.

H5b.

Employees’ family role overload is positively related to WFC.

In the WFC literature, flexibility at work is associated with a wide range of flexible work arrangements, such as flexible work hours, flexible workplaces, flexible work schedules and compressed workweeks (Allen, 2001; Shockley and Allen, 2007). Studies have also found that flexibility at work can help reduce WFC (Dierdorff and Ellington, 2008; Pal and Saksvik, 2008; Rimi, 2014; Shockley and Allen, 2007). For example, although five-day workweeks are not adopted worldwide, including many organisations in Hong Kong, such a workweek policy allows employees to spread their total work hours over five days or fewer and enjoy two-day weekends with family, resulting in a better work–family balance. Therefore, flexibility at work allows employees to use their resources such as time and energy more effectively to fulfil both their work and family roles, leading to the reduction of WFC. More importantly, flexible work arrangements also allow employees to handle unexpected, short-term increases in demands in their work or family roles, such as urgent projects or sick family members, with the flexible allocation of resources between different roles. For example, employees may be allowed to work at home so that they can take care of their children who are ill. Thus, we propose the following hypothesis:

H6.

Employees’ flexibility at work is negatively related to WFC.

WFC and outcomes

WFC represents an incompatibility between the demands of work and family roles (Kahn et al., 1964; Katz and Kahn, 1978). In accordance with a COR perspective, the incompatibility of time and energy needed to meet demands from both domains is perceived as stressful and challenging. Employees may face potential and actual psychological and behavioural resource loss when they have to meet different demands.

Work/family commitment

Employees’ commitment to work is defined as their desire to devote time and energy to work roles (Cinamon and Rich, 2002). Employees’ commitment to family is defined as the “degree of time and effort they spent in activities with their family/spouse” (Shaffer et al., 2001, p. 109). Both types of commitment require employees’ resources, namely, their time and energy for both physical and psychological conducts. In the case of WFC, the two domains are both salient and dependent on each other for resources (e.g. Greenhaus and Beutell, 1985). High demand on either the work or family domain requires employees’ resources to fulfil that demand, which in turn may drain resources from another domain (Shaffer et al., 2001). Inevitably, employees would need to reduce their engagement and expend less personal temporal and psychological resources on another domain (Mowday et al., 1982), thereby also reducing their commitment. Empirical findings also provide support for this prediction (e.g. Day and Chamberlain, 2006; Parasuraman et al., 1996; Shaffer et al., 2001; Van Steenbergen et al., 2007). Thus, we propose the following hypotheses:

H7a.

WFC is negatively related to employees’ commitment to work.

H7b.

WFC is negatively related to employees’ commitment to family.

Work/family performance

In addition, in accordance with the COR perspective, WFC is regarded as stressful and challenging, as it causes the threat of or an actual loss of resources. For instance, when faced with WFC, employees’ level of stress increases, as they may perceive that the resources they need to fulfil demands in a particular domain are lost because they have depleted their resources in the other domain. Inevitably, stressed employees may withdraw either psychologically or physically from their work/family tasks. More specifically, mutually incompatible demands from the work and family domains cause employees to have insufficient psychological and behavioural resources to be devoted to their work. As such, they may not be able to fully meet the requirements associated with their jobs. At the same time, employees’ family performance may also suffer, as they cannot devote enough resources to fulfilling their family responsibilities. Empirical evidence (e.g. Frone et al., 1997; Kossek et al., 2001; Van Steenbergen et al., 2007) also suggests that WFC leads to decreased performances in both domains. Thus, we propose the following hypotheses:

H8a.

WFC is negatively related to employees’ work performance.

H8b.

WFC is negatively related to employees’ family performance.

Employees’ career outcomes

Finally, WFC also affects employees’ career perceptions, in terms of both satisfaction and development opportunities. When individuals are faced with conflicts between their work and family, the stressors from both domains may lead to a negative evaluation of the satisfactoriness of their career progress and work life success. Past findings support this negative relationship between WFC and career satisfaction (e.g. Gordon et al., 2007; Greenhaus and Parasuraman, 1986; Parasuraman et al., 1996; Richardsen et al., 1997). Additionally, employees consider their jobs promising if they can see their career development opportunities and consequences. Anderson et al. (2002) defined this as employees’ perceived consequences related to future career or advancement opportunities. Employees would feel overwhelmed by competing work tasks and in fulfilling role requirements if they continuously struggled between two roles. In turn, they would experience fewer opportunities for future career advancement. Thus, we propose the following hypotheses:

H9a.

WFC is negatively related to career satisfaction.

H9b.

WFC is negatively related to career development consequences.

Method

Literature search and measures

A comprehensive search was conducted for field studies that examined the relationships between WFC and its correlates and that were published in or before 2017. Searches for relevant articles were conducted in the EBSCOhost and ProQuest databases, using keywords, such as “work–family conflict”, “work interfering with family”, “family interfering with work” and “work–family interference”. The reference lists of previous WFC meta-analyses were also considered to locate articles missed in previous processes. The inclusion criteria of this meta-analysis were as follows: whether any form of WFC (e.g. general WFC, WIF/FIW or time/strain-based WFC) was measured and whether the study reported sufficient information about effect sizes and measurements for analyses. The literature search yielded 1,074 empirical research papers. Overall, 228 research papers that included the constructs of our research model were included in our meta-analysis with 243 independent samples. Two of the authors and a trained research assistant were responsible for the coding process. The level of agreement among the three coders for this coding section was relatively high, with a κ value higher than 0.90. As such, they agreed on all of the literature included upon discussion. All of the coders used the same protocols to code the first ten research papers. They then discussed any discrepancies from their independent coding and agreed on consistent approaches in the coding process.

A variety of operationalisations, largely consistent with prior research, were used to measure WFC. Studies were limited to those concerning the relationships between general WFC and its correlates – the same relationship used in previous meta-analytical research (e.g. Allen et al., 2000). For WFC correlates, Table AI shows the WFC antecedents and consequences included in this meta-analysis.

Meta-analytical procedures

Comprehensive meta-analysis software version 3.0 developed by Borenstein, Hedges, Higgins and Rothstein was used to conduct meta-analytical tests. Random effects model was used to estimate the population parameters. To address the artefact issue and calculate the true effect sizes from individual studies, Hunter and Schmidt’s (2004) meta-analysis technique was adopted. First, an effect size corrected for measurement unreliability was calculated for each reported correlation between WFC and its correlates using the Cronbach’s α values reported in each study. Second, the disattenuated correlations were corrected for sampling error by calculating the corrected correlations weighted by sample size. For the cases requiring combined effect sizes, such as combining time-based WFC with strain-based WFC for an effect size of general WFC, the average of individual effect sizes was calculated. Two indices are reported to help estimate the variability of true correlation: confidence interval (CI) and credibility interval (CrI). A 95% CI is presented for each corrected correlation. A 90% CrI is also reported. If the 90% two-tailed CrI does not include zero, at least 95% of the individual correlations should also be nonzero (Judge and Ilies, 2002). In addition, the random effects variance component (REVC) value was reported, which estimates the variance of “infinite-sample effect sizes” (Lipsey and Wilson, 2001).

Moderation analysis

In investigating the distinct relationships between the WIF–correlate and FIW–correlate relationships, subgroup meta-analyses were performed. Specifically, the 80% CrI index was adopted as a moderator indicator, such that the subgroup tests were conducted with those effect sizes when 80% CrI included zero. For example, the studies that reported the correlation between WIF and work demand were organised into one group, whereas those that reported the correlation between FIW and work demand were classified into another group. This was followed by conducting separate meta-analyses for both groups.

Results

Table II shows the results of the meta-analysis. For each relationship, the total sample size accumulated across studies (n), the number of studies including an analysis of that relationship (k), the sample size weighted uncorrected correlation (r), the standard deviation of r (SD), the sample size weighted corrected correlation (rc), the standard deviation of rc (SDc), the 95% CI, the 90% CrI and REVC are reported. Q-statistics value was also incorporated in the moderation analysis. Regarding the interpretation of effect sizes, an absolute value of 0.10 to 0.23 is regarded as small, 0.24–0.36 as medium and 0.37 or higher as large (Cohen, 1988).

H1ab and H2ab, which argue that work demand and family demand are positively related to WFCm and that work control and family control are negatively related WFC, respectively, are fully supported. WFC is found to be positively related to work demand (rc=0.30) and family demand (rc=0.22) and negatively related to work control (rc=−0.12) and family control (rc=−0.24).

H3a3b and H4, which argue that work hours and family hours are positively related to WFC and that job autonomy is negatively related to WFC, respectively, are partially supported. WFC is found to be positively related to work hours (rc=0.18) and negatively related to job autonomy (rc=−0.14). The effect size between WFC and family hours is not prominent (rc=0.02).

H5a5b and H6, which argue that work role overload and family role overload are positively related to WFC and that flexibility at work is negatively related to WFC, respectively, are fully supported. WFC is found to be positively related to work role overload (rc=0.52) and family role overload (rc=0.31) and negatively related to flexibility at work (rc=−0.14).

H7a7b, H8a8b and H9a9b, which argue that WFC is negatively related to three types of consequences, are fully supported. WFC is found to be negatively related to commitment to work (rc=−0.15), commitment to family (rc=−0.11), work performance (rc=−0.13), family performance (rc=−0.23), career satisfaction (rc=−0.17) and career rewards and development (rc=−0.30).

Moderation results

Table III shows the moderation results, with one moderator (WIF vs FIW) analysed. Moderation analyses were conducted with those WFC–correlate relationships gathered sufficient number of empirical studies (i.e. at least two studies for each subgroup).

In terms of the moderating effects, Q statistic of family demand, family control, work hours, flexibility, and work performance show significant differences between WIF–correlate and FIW–correlate relationships. These results suggest that WIF has stronger relationships with family control (rc=−0.37) and work hours (rc=0.26); while FIW has stronger relationships with family demand (rc=0.26), flexibility at work (rc=0.10) and work performance (rc=−0.25).

Discussion

To date, more than a dozen meta-analytic studies of WFC have been conducted. Most of them have examined either the antecedents (e.g. Allen et al., 2012; Byron, 2005; Mesmer-Magnus and Viswesvaran, 2006; Michel, Clark and Jaramillo, 2011; Michel, Kotrba, Mitchelson, Clark and Baltes, 2011; Michel et al., 2010) or the consequences (e.g. Allen et al., 2000; Amstad et al., 2011; Kossek and Ozeki, 1998; Mesmer-Magnus and Viswesvaran, 2005; Nohe et al., 2015) of WFC. Although the rest have comprised both WFC antecedents and consequences, they have mainly examined the cross-domain (i.e. work antecedents affecting family consequences and vice versa) or match-domain (i.e. work antecedents affecting work consequences and vice versa) relations of WFC (e.g. Ford et al., 2007; Michel and Hargis, 2008; Michel et al., 2009). Despite these studies advancing our knowledge of WFC, theory-driven meta-analytic models of WFC comprising both antecedents and consequences have been limited.

To fill the knowledge gap, from a COR perspective, we extend the literature by developing a theory-driven meta-analytic model of WFC comprising both antecedents and consequences. More specifically, we identify three sets of WFC antecedents: demand of and control over work and family, hours spent at work and home and job autonomy and role overload at work and home and work flexibility. Likewise, we identify three sets of WFC consequences: employees’ commitment to work and family (work attitude), employees’ performance at work and home and employees’ career satisfaction and rewards such as favourable career appraisals.

Antecedents of WFC

There are three sets of WFC antecedents. First, we argue that work demand and family demand are two significantly positive predictors of WFC, whereas work control and family control are two significantly negative predictors of WFC. Our findings support that either work or family demand worsens WFC, as work and family obligations use up individuals’ resources, leading to the deterioration of WFC. When individuals perceive that they have control over their work or family obligations, they are in a better position to retain or protect their limited resources for their dual roles in the work and family domains, leading to the mitigation of WFC.

Second, in addition to the perceptions of work and family obligations, the actual hours spent in the work and family domains explicitly deplete personal resources. Our findings uphold that when individuals are substantially occupied by work, they tend to find it challenging to effectively cope with both work and family responsibilities, leading to the occurrence of WFC. On the other hand, hours spent in the family domain are not a significant predictor of WFC, probably because individuals’ psychological ownership in family issues is generally stronger than that in work issues and thus resource loss may be less noticeable. In contrast, individuals’ job autonomy affects their perceptions of their degree of control over when and how they complete their work tasks, which may help save their personal resources on both work and family responsibilities. The occurrence of WFC may thus decrease.

Third, our findings indicate that role overload from the work and family domains are two significantly positive predictors of WFC, whereas employees’ flexibility at work such as flexible work hours, flexible workplaces and flexible work schedules is a significantly negative predictor of WFC. Role overload is essentially a resource loss event that leads to a certain degree of depression (Hobfoll, 1989). Such resource loss weakens individuals’ capacity to deal with their work or family obligations, giving rise to WFC. In contrast, employees’ flexibility at work allows them to make better use of their personal resources and thus helps alleviate the impact of WFC.

Finally, the findings from the moderation test show that despite no significant differences between the effect sizes that WIF and FIW have with most of the correlates (9 out of 14), five correlates do suggest some distinct relationships. Employee work hours are indicated as more related to WIF than to FIW. This is consistent with the argument that when employees spend more time on work tasks, they are more likely to reserve less time and effort for family commitments. Thus, the perception of WIF would be stronger. Family demands are more associated with FIW, supporting the notion that with high family demands, employees would perceive family tasks interfering with their work. In addition, the subgroup analysis results show that having higher level of control over family issues and having more flexibility at work is more associated with FIW than WIF. Further empirical studies investigating the underlying mechanisms of these associations would help clarify the comparison.

Consequences of WFC

COR theory posits that WFC can result in resource loss because individuals need to use personal resources to deal with it (Kwan et al., 2012). As such, we expect WFC to lead to negative consequences. We also hypothesise three sets of WFC consequences. First, we argue that WFC has negative effects on work attitudes, such as employees’ commitment to both work and family domains. Our findings endorse these relationships. As individuals have to utilise their resources to cope with the conflict, they may suffer from resource drain and thus reduce their commitment to fulfilling their work and family roles.

Second, we believe that WFC also has negative effects on employees’ performance both at work and home. Employees who experience WFC may deplete their resources, leading to insufficient resources to be devoted to their work and family obligations, which in turn decrease their performance in the work and family domains.

Third, we expect WFC to hamper employees’ favourable career appraisals, including career satisfaction and career rewards and development. Similar to the effects of other negative consequences of WFC, when individuals experience WFC, their personal resources are drained, and the negative appraisals of such adverse situations may generate further negative outcomes and affect other domains, such as career appraisals. Our findings are consistent with our expectations, with those who experience WFC being likely to appraise their career satisfaction and career rewards and development more unfavourably.

Implications and limitations

There are several implications from this study. First, we adopt a COR perspective to understand how acquiring critical resources (i.e. perceptions of control, autonomy and flexibility) decreases the unfavourable experiences of WFC and how WFC as a signal of potential and actual resource loss influences employees’ positive attitudes and performance both at work and home. These findings are of valuable reference to management practitioners. Insofar as employees feel empowered by higher levels of control, autonomy and flexibility in their jobs, they are more likely to perceive a lower level of WFC. More importantly, in turn, these employees may have a better chance to experience positive outcomes at work, such as higher work commitment, better job performance and increased career satisfaction. These findings provide practical implication to support the importance of managerial support, such as coaching (Hui and Sue-Chan, 2018; Hui et al., 2013) and mentoring (Nielson et al., 2001), in enhancing employees’ attitude and performance through reducing their stress caused by conflicts between work and family. Second, we provide preliminary findings on the comparison of the strengths between the favourable and unfavourable antecedents of WFC. Our results are consistent with the arguments of COR theory such that compared to favourable antecedents, unfavourable/negative predictors demonstrate stronger relationships with individuals’ WFC. Empirical findings from other research have also supported this argument. Baumeister et al. (2001) asserted that compared to positive or neutral stimuli, negative events have a great power to generate stronger psychological, affective and behavioural reactions. Such negative asymmetry effects have gained support from various scholarly perspectives, such as discrepancy theories (Fiske, 1980). If unfavourable conditions have stronger impacts on employees’ WFC than favourable conditions, management practitioners should be more aware of getting rid of extremely high work demands or other constraining requirements, instead of focussing merely on building supportive work environments. Third, we incorporate the less discussed and newly developed correlates of WFC, such as the negative consequences of WFC on individuals’ favourable career appraisals. In addition, our subgroup tests show that most of the WFC correlates included (i.e. 11 out of 14) show similar effect sizes to WIF and FIW. The findings support our conceptualisation that from our research model, employees often react to their feelings of conflict in a general way, instead of having distinct reactions to WIF or FIW.

We are also aware of some potential limitations to this study. First, the effect sizes from our meta-analytical findings only suggest the binary relationship between WFC and its correlates. More empirical studies with appropriate research designs are needed to investigate the causal relationships. Although the research model developed in this meta-analysis is based on theoretical arguments, the nature of correlation-based meta-analyses does not support the examination of causality relationships. Furthermore, our meta-analytical results show the preliminary results of effect size comparison. More empirical studies are needed to simultaneously include both antecedents to provide more robust statistical comparison. In addition, although a moderation test was conducted using the types of WFC as moderators, some of the CrI intervals still contain the value of zero. This result indicates other moderators. Future research should examine whether other moderators such as job level and company industry can provide further information on the effect size findings. Second, we aim to develop a relatively parsimonious meta-analytic model of WFC comprising both favourable and unfavourable antecedents and consequences. Furthermore, the WFC studies incorporating both antecedents and consequences and testing the bidirectional conception of conflict between work and family are limited in the literature. The trade-off would be the loss of valuable information given by the two dimensions of WFC (i.e. WIF and FIW). Future research should consider including both the WIF and FIW dimensions provided that a relatively parsimonious model could be attained. In addition, such a methodological arrangement is consistent with our research purpose of investigating the impacts of resource gain/loss experiences on individual perceived levels of WFC. Although we do not focus on discovering whether work issues interfere with family issues more (i.e. WIF) or vice versa, having a general WFC construct is reasonable in our research model. Third, similar to other meta-analytic studies, one limitation is associated with the primary research aggregated in this study. As many primary studies are based on cross-sectional research designs or self-reported data, caution is needed regarding the inferences drawn (Allen et al., 2012). Future research may consider empirically testing both favourable and unfavourable conditions in the same sample, preferably with a longitudinal design. We also encourage researchers to include both work and family conditions in the same study and to compare the influence of each domain over employees’ WFC perceptions.

Conclusion

We provide an updated meta-analytic model of WFC comprising both antecedents and consequences. From a COR perspective, we develop and test three sets of WFC antecedents and three sets of WFC consequences. The hypotheses are generally supported. Our findings extend the WFC literature and lay the groundwork for future research in this area of study.

Figures

Proposed research model

Figure 1

Proposed research model

Summary of the antecedents and consequences in previous meta-analyses of work–family conflict

Article Theoretical underpinnings Antecedents Moderators Mediators Consequences Key findings
French et al. (2018) Social support theory Forms (behaviours and perceptions), sources (supervisor, co-worker and spouse) and types (instrumental and emotional) of social support Cultural values and economic factors Nil Nil All antecedents are significantly negative predictors of WIF and FIW (except for the relationships between work instrumental support and WIF, between family instrumental support and WIF, and between work instrumental support and FIW)
Shockley et al. (2017) Rational view
Sensitisation perspective
Boundary theory
Gender Full-time, same job, parental status and dual-earner status Work/family hours, work/family salience and work/family boundaries Nil Gender is a significant (but weak) predictor of WIF and FIW
Same job, parental and dual-earner status and type of WFC are significant moderators
Work/family hours and work/family boundaries are significant mediators
Allen et al. (2015) Nil National context Nil Nil Nil Collectivism, gender gap and non-US countries are significantly positive predictors of FIW
Nohe et al. (2015) Conservation of resources theory Strain Nil Nil Strain WIF and FIW are significantly positive predictors of strain
Strain is a significantly positive predictor of WIF and FIW
WIF has a stronger effect on work-related strain than FIW, supporting the matching hypothesis rather than the cross-domain perspective
Allen et al. (2013) Resource drain theory Flexible work arrangements Nil Nil Nil Flexible work arrangements are significantly negative predictors of WIF
Flextime is more negatively associated with WIF than with flexplaces
Flexplace use is more negatively associated with WIF than flexplace availability
Allen et al. (2012) Resource drain theory Dispositions Time-, strain- and behaviour-based WFC and demographics Nil Nil Most dispositions are significant predictors of WIF and FIW
Time-, strain- and behaviour-based WFC are significant moderators
Amstad et al. (2011) Nil Nil Parenthood and time spent at work Nil Work-related (e.g. work satisfaction and organisational commitment), family-related (e.g. family satisfaction and family performance) and domain-unspecific (e.g., life satisfaction, health and psychological strain) outcomes WIF and FIW are significant predictors of work-related, family-related and domain-unspecific outcomes
WIF is more strongly associated with work-related outcomes and FIW is more strongly associated with family-related outcomes, supporting the matching hypothesis rather than the cross-domain perspective
Time spent at work is a significant moderator between WIF and family-related outcomes and between FIW and domain-unspecific outcomes
Kossek et al. (2011) Perceived organisational support theory General and work–family-specific supervisory and organisational support Nil General and work–family-specific organisational support Nil Work–family-specific support (organisational and supervisory) is a stronger predictor of WIF than general support (organisational and supervisory)
Organisational support (general and work–family-specific) is a significant mediator of supervisory support (general and work–family-specific)
Michel, Clark and Jaramillo (2011) Personality theory “Big Five” personality traits Nil Nil Nil Extraversion, agreeableness, conscientiousness and neuroticism are significant predictors of work–non-work spillover (e.g. WFC)
Michel, Kotrba, Mitchelson, Clark and Baltes (2011) Work–family theories Work role stressors, family role stressors, work role involvement, family role involvement, work social support, family social support, work characteristics, family characteristics and personality Marital status, parental status and gender Nil Nil Work role stressors, work role involvement, work social support and work characteristics are significant predictors of WIF
Family role stressors, family role involvement, family social support and family characteristics are significant predictors of FIW
Locus of control and neuroticism are significant predictors of WIF and FIW
Marital status, parental status and gender are significant moderators of WIF and FIW
Shockley and Singla (2011) Domain specificity perspective
Source attribution perspective
Nil Gender Nil Family satisfaction and job satisfaction WIF is a stronger predictor of job satisfaction than of family satisfaction and FIW is a stronger predictor of family satisfaction than of job satisfaction, supporting the source attribution perspective rather than the domain specificity perspective
Gender is a significant moderator
Michel et al. (2010) Role theory Work/family role conflict, time demands, role ambiguity, social support and role involvement Nil Work/family social support, role involvement, role conflict, time demands and role ambiguity Nil Work/family social support and role involvement are significant predictors of WIF and FIW, mediated by work/family role conflict, time demands and role ambiguity
Michel et al. (2009) Conflict theory
Segmentation theory
Work/family social support, involvement, role conflict, time demands and role ambiguity Nil Nil Job satisfaction, family satisfaction and life satisfaction WIF and FIW are better predictors of same-domain than of cross-domain satisfaction (e.g., WIF is a better predictor of job satisfaction), supporting segmentation theory (direct effect links) rather than conflict theory (indirect WFC links)
Michel and Hargis (2008) Conflict theory
Segmentation theory
Work/family social support, involvement, role conflict, time demands and role ambiguity Nil Nil Job satisfaction and family satisfaction WIF and FIW are better predictors of same-domain than of cross-domain satisfaction, supporting direct effect links rather than indirect WFC links
Ford et al. (2007) Nil Job involvement, job stress, work support and work hours
Family conflict, family stress, family support and family hours
Nil Nil Job satisfaction and family satisfaction Job involvement, job stress, work support and work hours are significant predictors of WIF
Family conflict, family stress, family support and family hours are significant predictors of FIW
WIF and FIW are significant predictors of family satisfaction and job satisfaction, respectively, supporting cross-domain satisfaction
Mesmer-Magnus and Viswesvaran (2006) Nil Family-friendly work environment Nil Nil Nil Family-friendly work environment is a stronger predictor of global WFC and WIF than of FIW
Byron (2005) Conflict theory Work domain, non-work domain, demographic and individual variables Percentages of females and parents and coding of antecedents Nil Nil Work variables (job involvement, hours spent at work, work support, schedule flexibility and job stress) are stronger predictors of WIF than of FIW
Non-work variables (hours of non-work, family stress, number of children and marital status) are stronger predictors of FIW than of WIF
Job stress, family stress and family conflict are the strongest predictors of both WIF and FIW
Mesmer-Magnus and Viswesvaran (2005) Nil Nil Nil Nil Job stressors, non-work stressors, supportive work environment, organisational withdrawal, job satisfaction, life satisfaction and health WIF and FIW have similar but distinct correlations with the eight consequences
Allen et al. (2000) Nil Nil Nil Nil Work-related (e.g. job satisfaction and organisational commitment), non-work-related (e.g. life satisfaction and family satisfaction) and stress-related (e.g. depression and burnout) consequences Intention to turnover, life satisfaction and work-related stress are the strongest predictors of work-related, non-work-related and stress-related consequences, respectively
Kossek and Ozeki (1998) Nil Nil Nil Nil Job satisfaction and life satisfaction WFC, WIF and FIW are all significantly negative predictors of job satisfaction and life satisfaction

Meta-analytic results of the antecedents–WFC and WFC–consequences relationships

Correlate n k r SD rc SDc 95% CI 90% CrI REVC
Work demand 19,869 41 0.24 0.24 0.30 0.29 (0.22, 0.38) (−0.18, 0.78) 0.05
Family demand 15,803 25 0.18 0.13 0.22 0.17 (0.16, 0.28) (−0.06, 0.50) 0.01
Work control 11,929 32 −0.10 0.20 −0.12 0.26 (−0.19, −0.04) (−0.55, 0.31) 0.02
Family control 7,220 11 −0.20 0.20 −0.24 0.23 (−0.34, −0.13) (−0.62, 0.14) 0.02
Job autonomy 21,521 30 −0.11 0.13 −0.14 0.16 (−0.19, −0.10) (−0.40, 0.12) 0.01
Hours at work 56,318 106 0.17 0.14 0.18 0.16 (0.15, 0.20) (−0.08, 0.44) 0.01
Hours at home 8,851 14 0.02 0.08 0.02 0.09 (−0.04, 0.08) (−0.13, 0.17) 0.00
Role overload at work 16,898 38 0.40 0.12 0.52 0.15 (0.47, 0.57) (0.27, 0.77) 0.01
Role overload at home 1,300 5 0.27 0.12 0.31 0.14 (0.16, 0.44) (0.08, 0.54) 0.00
Flexibility (work time/schedule) 20,932 39 −0.11 0.17 −0.14 0.21 (−0.20, −0.08) (−0.49, 0.21) 0.02
Work commitment 8,228 22 −0.12 0.15 −0.15 0.14 (−0.22, −0.08) (−0.38, 0.08) −0.01
Family commitment 1,775 7 −0.09 0.07 −0.11 0.18 (−0.15, −0.06) (−0.41, 0.19) 0.01
Work performance 6,750 22 −0.10 0.11 −0.13 0.14 (−0.19, −0.07) (−0.36, 0.10) 0.00
Family performance 1,918 4 −0.20 0.12 −0.23 0.08 (−0.28, −0.19) (−0.36, −0.10) 0.01
Career satisfaction 2,697 10 −0.13 0.08 −0.17 0.10 (−0.24, −0.11) (−0.33, −0.01) 0.00
Career development consequences 4,172 6 −0.24 0.14 −0.30 0.17 (−0.42, −0.18) (−0.58, −0.02) 0.00

Notes: N, total sample size accumulated across studies; k, number of studies including an analysis of that relationship; r, sample size weighted uncorrected correlation; SD, standard deviation of r; rc, sample size weighted corrected correlation; SDc, standard deviation of rc; 95% CI, 95% confidence interval; 90% CrI, 90% credibility interval; REVC, random effects variance component

Moderation analyses

WFC correlate Subgroup n k r SD rc SDc 95% CI 90% CrI Q
Work demand WIF 13,802 32 0.23 0.32 0.29 0.39 (0.15, 0.42) (−0.41, 0.87) 2.74
FIW 9,027 21 0.12 0.17 0.15 0.20 (0.05, 0.25) (−0.18, 0.48)
Family demand WIF 12,975 22 0.11 0.14 0.14 0.18 (0.07, 0.21) (−0.16, 0.44) 5.21*
FIW 13,257 20 0.21 0.13 0.26 0.16 (0.19, 0.33) (0.00, 0.52)
Work control WIF 9,008 25 −0.12 0.23 −0.16 0.29 (−0.25, −0.06) (−0.64, 0.32) 0.68
FIW 4,737 14 −0.07 0.12 −0.10 0.16 (−0.20, −0.00) (−0.36, 0.16)
Family control WIF 6,560 8 −0.32 0.15 −0.37 0.17 (−0.45, −0.27) (−0.65, −0.09) 4.33*
FIW 6,560 8 −0.16 0.17 −0.20 0.21 (−0.33, −0.06) (−0.55, 0.15)
Job autonomy WIF 15,525 20 −0.11 0.12 −0.15 0.14 (−0.20, −0.10) (−0.38, 0.08) 1.56
FIW 7,290 9 −0.05 0.15 −0.07 0.19 (−0.18, 0.03) (−0.38, 0.24)
Hours at work WIF 38,469 80 0.24 0.13 0.26 0.15 (0.24, 0.29) (0.01, 0.51) 166.68**
FIW 25,867 52 0.01 0.11 0.03 0.12 (0.02, 0.05) (−0.17, 0.23)
Hours at home WIF 3,673 6 −0.08 0.11 −0.08 0.12 (−0.11, −0.05) (−0.23, 0.17) 0.89
FIW 4,175 6 0.01 0.06 0.01 0.07 (−0.04, 0.07) (−0.11, 0.13)
Role overload at work WIF 14,617 31 0.42 0.14 0.53 0.18 (0.45, 0.60) (0.23, 0.83) 3.31
FIW 10,723 18 0.33 0.15 0.43 0.20 (0.35, 0.50) (0.10, 0.76)
Role overload at home WIF 1,543 6 0.20 0.16 0.23 0.18 (0.05, 0.40) (−0.07, 0.53) 1.03
FIW 1,543 6 0.28 0.10 0.34 0.13 (0.21, 0.46) (0.13, 0.55)
Flexibility (work time/schedule) WIF 16,057 26 −0.06 0.18 −0.07 0.22 (−0.14, −0.01) (−0.43, 0.29) 10.10**
FIW 7,664 15 0.07 0.13 0.10 0.19 (0.02, 0.18) (−0.21, 0.41)
Career development consequences WIF 4,188 6 −0.27 0.19 −0.33 0.23 (−0.49, −0.16) (−0.71, 0.05) 1.09
FIW 3,930 5 −0.19 0.06 −0.23 0.08 (−0.30, −0.16) (−0.36, −0.10)
Work performance WIF 3,660 14 −0.06 0.12 −0.07 0.15 (−0.16, 0.02) (−0.32, 0.18) 7.12**
FIW 3,641 16 −0.19 0.13 −0.25 0.17 (−0.33, −0.16) (−0.53, 0.03)
Family commitment WIF 1,037 4 −0.13 0.11 −0.15 0.12 (−0.26, −0.04) (−0.35, 0.05) 1.94
FIW 683 3 −0.03 0.09 −0.02 0.12 (−0.16, 0.12) (−0.22, 0.18)
Work commitment WIF 4,398 13 −0.17 0.15 −0.20 0.18 (−0.29, −0.11) (−0.50, 0.10) 0.00
FIW 3,576 8 −0.16 0.15 −0.21 0.19 (−0.34, −0.06) (−0.52, 0.10)

Notes: N, total sample size accumulated across studies; k, number of studies including an analysis of that relationship; r, sample size weighted uncorrected correlation; SD, standard deviation of r; rc, sample size weighted corrected correlation; SDc, standard deviation of rc; 95% CI, 95% confidence interval; 90% CrI, 90% credibility interval; Q, value of Q-statistic. *p<0.05, **p<0.01

Definition or operationalisation of WFC correlates

Correlate Definition
Work demand General work roles, tasks and responsibilities, including time, effort and energy
Family demand Household maintenance tasks and childcare responsibilities (McManus et al., 2002, p. 1298)
Family control The amount of control experienced at family (Lapierre and Allen, 2012, p. 1501)
Work control The amount of control experienced at work (Lapierre and Allen, 2012, p. 1501)
Job autonomy The degree of control people has over when and how their work gets done (Behson, 2005)
Hours at work The average number of hours spent at work
Hours at home The average number of hours spent at home
Role overload at work When an individual’s capacity is not enough to handle and complete the amount of workload at work
Role overload at home When an individual’s capacity is not enough to handle and complete the amount of workload at home
Flexibility (work time/schedule) The ability to have discretion in one’s work schedule (Clark, 2001, p. 349)
Career satisfaction Level of satisfaction with career progress and success (Parasuraman and Simmers, 2001, p. 558)
Career development consequences The degree of internal promotion opportunity in an organisation (Lee and Hui, 1999)
Work performance The “fulfilment of the general responsibilities associated with a particular job or role (Frone et al., p. 153)
Family performance The fulfilment of family responsibilities
Family commitment The “degree of time and effort employees spend on activities with their family/spouse” (Shaffer et al., 2001, p. 109)
Work commitment The degree of time and effort employees spent on work activities

Coding summary

Study n Correlate (r/α) αWFC
Adams and Jex (1999) 522 WC (−0.25/0.57) 0.44
Ahuja et al. (2007) 171 JA (−0.20/0.63); GOC (−0.32, 0.76); WR (0.48/0.79) 0.79
Allard et al. (2007) 77 WH (0.20/1) 0.75
Allen (2001) 522 FL (−0.1/0.73) 0.89
Allen and Armstrong (2006) 246 WH (0.16/1) 0.88
Allis and O’Driscoll (2008) 938 FH (0.04/1); WH (0.16/1) 0.88
Anderson et al. (2002) 2,248 CDS (−0.23/0.75); FL (−0.03/0.73) 0.85
Anderson-Kulman and Paludi (1986) 204 FC (0.29/0.83); FL (−0.02/0.73) 0.83
Andreassi and Thompson (2007) 3,504 FD (0.11/0.79); WH (0.17/1) 0.83
Anwar et al. (2016) 281 JA (0.01/0.63); WR (0.46/0.78) 0.86
Aryee (1993) 95 FL (−0.07/0.83); WR (0.65/0.73) 0.75
Aryee (1993) 95 FL (−0.09/0.83); WR (0.12/0.73) 0.75
Aryee and Luk (1996) – wife sample 207 JA (−0.14/0.78); CS (−0.14/0.82) 0.84
Aryee and Luk (1996) – husband sample 207 JA (0.13/0.78); CS (0.01/0.82) 0.84
Aryee, Luk, Leung and Lo (1999) 320 WC (−0.20/1) 0.75
Aryee, Luk, Leung and Lo (1999) 320 WC (−0.20/1); CS (−0.10/0.83) 0.75
Aryee, Luk, Leung and Lo (1999) 243 WR (0.51/0.84); FR (0.13/0.89) 0.86
Aryee, Luk, Leung and Lo (1999) 243 WR (0.51/0.84); FR (0.11/0.85) 0.86
Aryee, Luk, Leung and Lo (2005) 267 WR (0.31/0.79); FR (0.20/0.89) 0.76
Aryee (1992) 354 JA (−0.28/0.78); FC (−0.07/0.89); FD (0.07/0.79); FL (−0.03/0.73); WR (0.10/0.79); WH (0.13/1) 0.76
Aycan and Eskin (2005) 197 WD (0.40/0.84) 0.90
Aycan and Eskin (2005) 237 WD (0.31/0.84) 0.90
Bacharach et al. (1991) 215 WR (0.24/0.60) 0.77
Bacharach et al. (1991) 430 WR (0.26/0.68) 0.87
Bakker et al. (2008) 168 FD (0.23/0.77); WD (0.46/0.81); WR (0.39/0.82); FR (0.17/0.83) 0.80
Bakker et al. (2011) 230 WD (0.22/0.78); JA (−0.16/0.71) 0.78
Balmforth and Gardner (2006) 75 WH (−0.11/1) 0.67
Batt and Valcour (2003) 557 JA (−0.01/0.68); FL (0.06/1); WC (0.06/1); WH (0.20/1) 0.54
Beauregard (2006) 208 FC (−0.30/0.90); WC (−0.32/0.67); WH (0.13/1) 0.84
Bedeian et al. (1988) – male sample 411 CS (0.29/0.92) 0.92
Bedeian et al. (1988) – female sample 321 CS (0.27/0.92) 0.92
Beham et al. (2011) 999 FL (−0.10/1); WD (0.52/0.75); WC (−0.08/0.75); WH (0.20/1) 0.76
Behson (2002) 141 WC (0.01/0.87) 0.81
Behson (2005) 2,248 JA (−0.16/0.68); FL (−0.08/1) 0.85
Beigi et al. (2016) 398 FH (0.01/1); WH (0.09/1) 0.81
Bhave et al. (2010) 1,547 WD (0.14/0.95); WH (0.40/1) 0.95
Bolino and Turnley (2005) 196 WR (0.59/0.84) 0.94
Boyar and Mosley (2007) 112 FD (0.23/0.74); WD (0.16/0.83); WR (0.43/0.77) 0.90
Boyar and Mosley (2007) 699 FD (0.31/0.79); WD (0.27/0.78); WR (0.39/0.79) 0.90
Boyar et al. (2008) 698 JA (−0.11/0.84); FD (0.31/0.77); WH (0.21/1) 0.90
Boyar et al. (2003) 432 WR (0.31/0.83) 0.90
Bragger et al. (2005) 203 OC (0.15/0.83) 0.80
Britt and Dawson (2005) 253 WC (−0.24/0.76); WH (0.15/1) 0.94
Britt and Dawson (2005) 493 WR (0.48/0.79) 0.83
Brough and Kelling (2002) 691 FC (−0.10/0.83); WC (−0.07/0.77) 0.88
Brough et al. (2005) 398 WH (0.21/1) 0.90
Brown and Pitt-Catsouphes (2016) 211 FH (0.01/1); FL (−0.45/0.64) 0.86
Bruck et al. (2002) 160 WH (−0.02/1) 0.84
Buonocore and Russo (2013) 171 OC (−0.14/0.78); WH (0.07/1) 0.89
Butler et al. (2005) 46 WD (0.48/not reported); WC (0.76/0.91) 0.76
Butts et al. (2013) 341 WH (0.11/1) 0.93
Carlson et al. (2011) 179 WC (−0.14/0.80) 0.88
Carlson and Kacmar (2000) 314 WD (0.29/0.60); FD (0.33/0.73) 0.85
Carr et al. (2008) 129 OC (−0.34/0.93) 0.96
Casper and Buffardi (2004) 371 FL (0.06/1); WH (0.12/1) 0.78
Casper et al. (2011) 168 FH (−0.10/1); WH (0.15/1) 0.80
Cho and Allen (2012) 201 WH (0.27/1) 0.90
Cho and Allen (2012) 230 WH (0.19/1) 0.85
Choi (2008) 239 FD (0.40/0.86); FH (0.13/1); WD (0.29/0.80); WH (0.08/1) 0.81
Cinamon and Rich (2002) 213 FL (−0.01/0.52); WH (−0.02/1) 0.80
Cinamon et al. (2007) 230 FL (0.16/0.52); WH (0/1) 0.80
Clark (2001) 179 FL (−0.18/84); WH (0.24/1) 0.86
Clark (2002) 151 FL (−0.18/0.73); WC (−0.25/0.76) 0.86
Cleveland et al. (2006) 81 WD (0.25/0.85) 0.89
Cohen et al. (2007) 195 OC (−0.11/0.89) 0.8
Cohen and Kirchmeyer (1995) 227 OC (0.11/0.71) 0.82
Cullen and Hammer (2007) 218 WR (0.31/0.80); WH (0.06/1) 0.90
Daalen et al. (2006) 444 WH (0.23/1) 0.82
Day and Chamberlain (2006) 436 FH (0.09/1); WC (−0.27/0.89); WH (0.10/1) 0.94
Demerouti et al. (2005) 382 WD (0.43/0.82) 0.76
Demerouti et al. (2007) 123 WP (−0.08/0.83) 0.77
Desrochers et al. (2005) 100 WH (0.27/1) 0.83
Dierdorff and Ellington (2008) 1,367 FL (−0.34/0.73); WR (0.27/0.79) 0.83
DiRenzo et al. (2011) 1,090 JA (−0.07/0.78); FD (−0.02/0.79); FH (−0.04/1); WD (0.40/0.78); WH (0.18/1) 0.84
Duxbury et al. (1994) 1,989 FC (−0.29/0.80); WR (0.48/0.79) 0.83
Duxbury et al. (1996) 307 JA (−0.02/0.58); WR (0.50/0.88) 0.71
Eagle et al. (1998) 318 FL (−0.23/0.73); OC (0/0.84); WH (0.22/1) 0.83
Eagle et al. (1997) 168 WH (0.04/1) 0.82
Eagle et al. (1997) 225 WH (0.14/1) 0.82
Fein and Skinner (2015) 328 WH (0.27/1) 0.82
Fein and Skinner (2015) 714 WH (0.20/1) 0.82
Ferguson et al. (2015) 503 FL (−0.42/0.87); OC (−0.35/0.86) 0.83
Foley et al. (2005) 877 WR (0.28/0.67) 0.89
Forret and de Janasz (2005) 418 CDS (−0.36/0.81); FL (0.12/0.73); WD (−0.43/0.84); WH (0.10/1) 0.87
Fox and Dwyer (1999) 113 WH (−0.04/1) 0.83
Frone (2000) 2,700 WH (0.12/1) 0.66
Frone et al. (1994) 366 WH (0.17/1) 0.69
Frone et al. (1993) 473 WH (0.17/1) 0.65
Frone and Yardley (1996) 496 WH (0.26/1) 0.67
Frone and Yardley (1996) 252 FL (0.13/0.73) 0.67
Frone et al. (1997) 372 FP (−0.38/0.84); WR (0.40/0.79); FR (0.32/0.72); WP (−0.27/0.77) 0.84
Frye and Breaugh (2004) 54 WH (0.15/1) 0.87
Fu and Shaffer (2001) 267 JA (−0.18/0.78); FD (0.12/0.79); FH (0.04/1); WR (0.35/0.77); WH (0.15/) 0.87
Golden et al. (2006) 454 JA (0.11/0.78); FL (0.15/0.91) 0.87
Gordon et al. (2007) 489 CS (−0.14/0.76) 0.80
Grandey et al. (2005) 174 JA (0.05/0.82) 0.77
Grandey et al. (2007) 228 WH (0.37/1); WP (−0.14/0.83) 0.92
Grandey et al. (2007) 228 WH (0.37/1) 0.92
Haar (2017) 203 WH (0.06/1) 0.80
Hart and Kelley (2006) 132 WH (0.27/1) 0.82
Hecht (2001) 279 FH (−0.06/1); FL (−0.15/0.73); WH (0.14/1) 0.83
Heponiemi et al. (2008) 713 WD (0.39/0.82); WC (−0.11/0.81) 0.76
Higgins et al. (1994) 3,616 WR (0.48/0.79) 0.63
Hill (2005) 1,314 FH (−0.01/1); FL (−0.07/0.73); OC (−0.10/0.84); WH (0.08/1) 0.88
Hill et al. (2004) 529 FL (−0.20/0.73); WP (0.05/0.83) 0.83
Hogan et al. (2006) 272 FL (−0.44/0.88) 0.79
Hoobler et al. (2009) 126 WP (−0.11/0.84) 0.83
Hosking and Western (2008) 1,142 JA (−0.03/0.78) 0.82
Hosking and Western (2008) 1,179 JA (−0.16/0.78) 0.85
Houkes et al. (2008) 261 WC (−0.34/0.64) 0.86
Hughes et al. (1992) 523 WC (0.04/0.75) 0.83
Hughes and Parkes (2007) 292 WD (0.43/0.75); WC (−0.12/0.83); WH (0.34/0.80) 0.89
Ilies et al. (2007) 106 WH (0.17/1) 0.73
de Janasz and Behson (2007) 157 OC (−0.21/0.88) 0.89
Janssen et al. (2004) 107 WD (0.36/0.74); WC (0.12/0.80) 0.90
Janssen et al. (2004) 249 WC (−0.06/0.79); WD (0.36/0.78) 0.87
Jex and Elacqua (1999) 525 WR (0.31/0.70); WC (0.25/0.55) 0.44
Jones and Butler (1980) 181 JA (−0.49/0.78) 0.80
Judge et al. (1994) 1,388 WH (0.16/10.00) 0.82
Karatepe and Bekteshi (2008) 107 WP (−0.06/0.87) 0.75
Karatepe and Tekinkus (2006) 363 WP (−0.01/0.73) 0.87
Katz and Piotrkowski (1983) 51 JA (−0.50/0.80); WD (0.45/0.78); WH (0.20/1.00) 0.92
Kelly and Dabul Marin (1998) 103 FL (−0.03/0.73) 0.83
Kinnunen et al. (2006) 202 WH (0.04/1.00) 0.83
Kossek et al. (2001) 490 FP (−0.11/0.90); WP (0.01/0.94) 0.70
Kossek et al. (2006) 90 WC (−0.14/0.74); WH (0.10/1.00); WP (−0.03/0.91) 0.73
Kossek et al. (2012) 278 FC (−0.37/0.85); WC (−0.25/0.80); 0.92
Kossek et al. (2012) 313 FC (−0.11/0.84) 0.91
Lambert et al. (2006) 95 GOC (−0.01/0.84) 0.83
Lapierre and Allen (2012) 205 FC (−0.27/0.85); WC (−0.11/0.86) 0.81
Laurence et al. (2016) 1,616 WR (0.39/0.89) 0.84
Laurence et al. (2016) 190 WR (0.20/0.89); WP (0.04/0.88) 0.93
Lee et al. (2018) 242 GOC (−0.15/0.80) 0.83
Lee and Hui (1999) 198 CDS (−0.10/0.86) 0.75
Leiter and Durup (1996) 151 WR (0.26/0.75) 0.75
Lenaghan et al. (2007) 205 WH (0.16/1.00) 0.89
Leslie et al. (2017) 1,311 FH (0.19/1.00); GOC (−0.08/0.86); WH (−0.12/1.00); WP (0.01/0.65) 0.80
Li et al. (2017) 113 WH (0.26/1.00); WP (−0.20/0.76) 0.84
Lingard and Francis (2005) 232 WH (0.44/1.00) 0.83
Lingard and Lin (2004) 109 CS (−0.09/0.80); GOC (−0.23/0.90) WH (−0.07/1.00) 0.75
Lu et al. (2006) 103 WH (0.16/1.00) 0.90
Lu et al. (2006) 220 WH (0.20/1.00) 0.84
Lu et al. (2008) 1,122 JA (0.07/0.78); GOC (−0.06/0.84); WH (0.14/1.00) 0.83
Luk and Shaffer (2005) 248 FMC (−0.04/0.89); FD (0.15/0.79) 0.70
Łukasz and Derbis (2012) 282 WH (0.29/1.00) 0.89
Lyness and Thompson (1997) 107 CS (−0.16/0.79); GOC (0.01/0.77); WR (0.65/0.81) 0.86
Mache et al. (2016) 564 WD (0.45/0.83); WC (−0.25/0.83) 0.81
Madsen (2006) 98 WH (0.18/1.00); 0.89
Madsen (2006) 123 WH (−0.02/1.00) 0.89
Major et al. (2002) 513 FD (0.07/0.79); FL (−0.48/0.96); WR (0.50/0.88) 0.91
Mallard and Lance (1998) 143 GOC (0.04/0.89) 0.87
Martins et al. (2002) 975 CS (−0.10/0.79) 0.64
Masuda et al. (2012) 220 WH (−0.04/1.00) 0.92
Matsui et al. (1995) 131 FD (0.08/0.79); FL (−0.05/0.73) 0.84
Matthews, Wayne and Ford (2014)/Matthews, Winkel and Wayne (2014) 250 WR (0.40/0.88); FR (0.46/0.89) 0.90
McElwain et al. (2005) 320 FD (0.08/0.85); WD (0.14/0.71) 0.87
McManus et al. (2002) 178 FD (0.04/0.79) 0.88
McManus et al. (2002) 342 WD (0.13/0.72) 0.75
Mellor et al. (2015) 126 WD (0.33/0.81); WR (0.55/0.61); WC (−0.43/0.84) 0.91
Montgomery et al. (2006) 162 WD (0.43/0.73); WH (0.19/1.00) 0.90
Muse and Pichler (2011) 209 WP (−0.06/0.94) 0.90
Netemeyer et al. (1996) 162 WH (0.15/1.00) 0.89
Netemeyer et al. (1996) 182 GOC (−0.23/0.89); WH (0.24/1.00) 0.88
Netemeyer et al. (1996) 186 WH (0.08/1.00); WP (−0.19/0.79) 0.88
Netemeyer et al. (2004) 125 WP (−0.35/0.62) 0.89
Netemeyer et al. (2004) 275 WP (−0.11/0.76) 0.90
Netemeyer et al. (2004) 284 WP (−0.20/0.72) 0.84
Ngo and Lau (1998) 461 FL (0.11/0.69); WH (0.18/1.00) 0.81
Nielson et al. (2001) 502 CDS (−0.03/0.86); WH (0.19/1.00) 0.88
Nohe and Sonntag (2014) 95 WH (−0.22/1.00); WP (−0.32/0.84) 0.82
Noor (2003) 147 WD (0.32/0.83); WC (0.02/0.88); WH (0.16/1.00) 0.84
Noor (2004) 147 WH (0.16/1.00) 0.84
Pal and Saksvik (2008) 247 FL (−0.19/0.61); WD (0.16/0.73); WC (0.12/0.81); WH (0.09/1.00) 0.74
Pal and Saksvik (2008) 455 FL (0.01/0.61); WC (−0.06/0.81); WH (0.13/1.00) 0.74
Parasuraman et al. (1996) 111 JA (−0.19/0.85); CS (−0.13/0.87); FMC (−0.09/0.89); FD (0.10/0.86); FL (−0.20/0.68); WR (0.35/0.77) 0.87
Parasuraman and Simmers (2001) 99 JA (−0.04/0.83); CS (−0.15/0.84); FMC (−0.26/0.89); FD (0.03/0.79); FL (−0.18/0.64) 0.84
Parasuraman and Simmers (2001) 287 JA (−0.13/0.83); FMC (−0.08/0.89); FL (−0.09/0.64) 0.84
Pleck et al. (1980) 940 FL (−0.08/0.73); WD (0.16/0.78); WC (0.06/0.75); WH (0.14/1.00) 0.83
Pleck et al. (1980) 1.012 WH (0.13/1.00) 0.83
Poposki (2011) 269 WH (−0.13/1.00) 0.87
Premeaux et al. (2007) 564 JA (−0.06/0.76); CDS (−0.29/0.72); WD (−0.17/0.71) 0.98
Promislo et al. (2010) 236 WR (0.30/0.92) 0.87
Prottas and Thompson (2006) 3,504 JA (−0.09/0.74); WH (0.18/1.00) 0.86
Rantanen et al. (2005) 155 FD (0.15/0.79); WH (0.22/1.00); 0.79
Reinardy (2011) 155 WR (0.44/0.58) 0.88
Reinardy (2011) 170 WH (0.26/1.00) 0.88
Richardsen et al. (1997) 191 CS (−0.32/0.82); WH (0.83/1.00) 0.66
Rowley et al. (2016) 202 CS (−0.16/0.91) 0.85
Russo and Waters (2006) 169 FL (−0.12/0.73) 0.73
Secret and Sprang (2001) 374 WD (0.32/0.78) 0.79
Senécal et al. (2001) 786 JA (−0.09/0.74) 0.73
Shaffer et al. (2001) 324 FMC (−0.12/0.82) 0.81
Shannon et al. (2001) 346 WD (0.25/0.69); WH (0.11/1.00) 0.64
Shockley and Allen (2007) 230 FL (−0.03/0.91); FL (−0.15/0.84); WH (0.10/1.00) 0.89
Simon et al. (2004) 3,565 WD (0.22/0.78); WH (0.08/1.00) 0.83
Smith and Gardner (2007) 153 WD (0.42/0.93) 0.90
Staines and Pleck (1986) 616 FH (−0.06/1.00) 0.83
Steinmetz et al. (2008) 130 WH (0.40/1.00) 0.88
Stevens et al. (2006) 156 FL (−0.53/0.73); WH (0.36/1.00) 0.89
Stevens et al. (2002) 156 WH (0.36/1.00) 0.89
Taylor et al. (2009) 1,156 WH (0.27/1.00) 0.85
Tepper (2000) 362 GOC (0.02/0.81) 0.93
Thomas and Ganster (1995) 398 FC (−0.45/0.75); FL (−0.09/0.73) 0.92
Thompson and Cavallaro (2007) 187 WH (0.22/1.00) 0.89
Thompson and Prottas (2005) 2,810 JA (−0.08/0.71); FC (−0.31/0.83); FD (0.11/0.79); WD (0.18/0.78) 0.92
Thompson et al. (1999) 242 CDS (−0.43/0.74); WD (−0.52/0.80) 0.86
Thompson et al. (1999) 258 WH (0.38/1.00) 0.86
Tucker et al. (2005) 1,489 WH (0.19/1.00) 0.92
Tuten and August (2006) 58 JA (−0.15/0.91); WD (−0.27/0.73); WH (0.44/1.00) 0.83
Van Daalen et al. (2006) 444 WH (0.23/1.00) 0.70
Van Steenbergen and Ellemers (2009) 1.134 WH (0.01/1.00) 0.80
Van Steenbergen et al. (2007) 352 FMC (−0.08/0.89); FP (−0.08/0.94); WP (−0.07/0.94) 0.77
Voydanoff (2005a) 2,109 FL (−0.08/0.73); WH (0.28/1.00) 0.87
Voydanoff (2005b) 1,567 FD (0.29/0.79); FD (0.13/0.70) 0.80
Voydanoff (2004) 1,938 JA (−0.16/0.68); WH (0.21/1.00) 0.86
Voydanoff (1988) 270 JA (−0.06/0.78); FH (−0.05/1.00); WD (−0.02/0.82); WC (−0.11/0.71); WH (0.26/1.00) 0.83
Voydanoff (1988) 757 WC (−0.07/0.71); WH (0.28/1.00) 0.83
Van Rijswijk et al. (2004) 189 FD (0.34/0.75); WD (0.33/0.83) 0.84
Wayne et al. (2017) 704 FP (−0.21/0.87); GOC (−0.07/0.81); WP (−0.07/0.90) 0.87
Wayne et al. (2013) 408 WH (0.33/1.00) 0.88
Wayne et al. (2004) 2.124 WH (0.19/1.00) 0.82
Weigel et al. (1995) 517 WR (0.48/0.83) 0.76
Westman et al. (2008) 66 FC (−0.10/0.81) 0.84
Westman et al. (2004) 58 FC (−0.03/0.87) 0.77
Westring and Ryan (2011) 357 WD (0.07/0.78); WC (−0.03/0.75) 0.79
Wiese and Salmela-Aro (2008) 131 WH (0.02/1.00) 0.76
Wiley (1987) 191 GOC (−0.17/0.71); WR (0.45/0.81) 0.78
Williams and Alliger (1994) 41 FD (0.06/0.79); WD (−0.05/0.78) 0.71
Williams et al. (2006) 168 WD (0.18/0.89); WH (−0.06/1.00) 0.76
Witt and Carlson (2006) 136 WP (−0.23/0.86) 0.85
Yang et al. (2000) 108 FD (0.53/0.78); WD (0.38/0.76) 0.83
Yavas et al. (2008) 342 WP (−0.04/0.83) 0.83

Notes: α, reported reliability number; r, reported correlation number. Scales: WD, work demand; FD, family demand; WC, work control; FC, family control; JA, job autonomy; WH, work hours; FH, family hours; WR, work role overload; FR, family role overload; FL, flexibility (work time/schedule); CS, career satisfaction; CDS, career development consequences; WP, work performance; FP, family performance; GOC, general organisational commitment; Multiple entries for one article refer to the different studies included in that article

Appendix

Table AI

Table AII

References

The studies included in the meta-analysis are marked by an asterisk.

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Further reading

Clive, F. and Bailey, C. (2002), “The impact of multiple source feedback on management development: findings from a longitudinal study”, Journal of Organizational Behavior, Vol. 23 No. 7, pp. 853-867.

Kossek, E.E. and Lautsch, B.A. (2012), “Work–family boundary management styles in organisations: a cross-level model”, Organisational Psychology Review, Vol. 2 No. 2, pp. 152-171.

Pam, A. and O’Driscoll, M. (2008), “Positive effects of nonwork-to-work facilitation on well-being in work, family and personal domains”, Journal of Managerial Psychology, Vol. 23 No. 3, pp. 273-291.

Acknowledgements

The work described in this paper was supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. UGC/FDS14/B09/17).

Corresponding author

Eko Yi Liao can be contacted at: ekoliao@hsu.edu.hk