Organizational Support Factors and Work–Family Outcomes: Exploring Gender Differences

Organizational Support Factors and Work–Family Outcomes

Organizations may offer a variety of supports for families, composed of both informal and formal practices and policies. In the present study, we use the categorization by Hammer, Kossek, Zimmerman, and Daniels (2007) and examine how gender moderates the relationship between: (a) family-supportive organization perceptions (FSOP), which refer to the employees’ perception that the organization is family-supportive; (b) supervisor work–family support, or the employees’ perception that their supervisor is family-supportive; and (c) organizational policies (i.e., flextime, telecommuting, compressed workweeks); on both negative and positive work–family outcomes.

On a broad level, the relationship between each of these organizational support factors and work–family outcomes can be explained through conservation of resources (COR; Hobfoll, 1989) and the principles of fixed resources and resource drain (Edwards & Rothbard, 2000). According to COR, individuals have a finite amount of resources (time, energy, attention), and if resources are spent in one role (e.g., work), there is a decrease in resources available for use in another role (e.g., family). Thus, COR theory serves to explain how people respond to stressors in their environment and how managing those stressors influence outcomes such as negative work–family spillover and intent to quit (Ten Brummelhuis & Bakker, 2012). The COR model proposes that people try to prevent resource loss and seek to attain and sustain resources that are important to them. By offering employees support for their work–family needs, the organization might mitigate the amount of resource drain felt by employees. For example, allowing employees to work flexible hours may reduce time demands attributable to conflicting work and family schedules. Similarly, a supervisor who is family-supportive may provide employees emotional (e.g., serve as a sounding board) or instrumental (e.g., offer suggestions for assistance) support, which can help employees cope more effectively with work or family demands. Empirical research supports the notion that organizational support factors decrease employees’ negative work–family spillover and intent to quit (Clark, 2002; Thompson, Beauvais, & Lyness,1999).

Organizational support factors should be related to positive work–family spillover and job satisfaction, as these resources can be an important source of developmental, affective, and capital gains. Working in a family-friendly environment may engender feelings of positive affect or confidence that carries over and enhances functioning of the family (Wayne, Grzywacz, Carlson, & Kacmar, 2007). COR theory and the concept of resource gain spiral would suggest these individuals are more likely to acquire new resources to help them perform in their family role because resource acquisition is additive (Hobfoll, 1989). Furthermore, a supportive work environment can enhance flexibility, which better enables individuals to integrate their work and family roles (Greenhaus & Parasuraman, 1999). Research has also shown links between organizational support factors and the related concept of work–family facilitation (Aryee et al., 2005), as well as with job satisfaction and organizational commitment (Baltes, Briggs, Huff, Wright, & Heuman, 1999; Casper & Harris, 2008). In sum, both theory and research support the idea that employees can benefit when their organization is supportive of their work–family needs. However, little attention has been paid to the role of gender in these relationships.

Examining the Role of Gender

Although there is evidence that a growing number of men espouse egalitarian values (particularly those with a spouse who is also employed; Parasuraman & Greenhaus, 2002), societal norms and traditional gender role expectations that men should be more invested in the work domain, whereas women should be more invested in the family domain still greatly influence behavior and attitudes toward managing work and family roles (Bagger, Li, & Gutek,2008; Blair-Loy, 2003). For example, based on gendered expectations related to parenting and household duties, women on average continue to take on more child care and household responsibilities than men (Coltrane, 2000; Galinsky, Aumann, & Bond,2011). Given the greater family role demands, working women may experience greater resource drain than working men (Hobfoll, 1989), and as a result may experience greater benefits from organizational support factors. Furthermore, social identity theory (Ashforth & Mael, 1989) suggests that individuals are especially concerned with factors that benefit or threaten their most central identity (e.g., work, family). To the extent that women view their family identity as more central to their self-perceptions than their work identity, women will benefit more than men from informal and formal support factors that allow them to better attend to family needs and responsibilities. This focus on family is also consistent with sex role theory and gender role prescriptions that women should be more concerned with family than with work (Blair-Loy, 2003; Pleck, 1977). Indeed, research has shown that women generally invest more into their family role than their work role (Gutek, Searle, & Klepa,1991), and women with children were more likely than men with children to report they were family-centric (Families and Work Institute, 2004).

Women, more so than men, may also place a greater value on informal forms of organizational support that are of a social nature (e.g., supervisor support; Friedman & Greenhaus, 2000; Wayneet al., 2007), due to differences in socialization regarding relationships (Gilligan, 1980). Specifically, women are socialized to be more dependent on social attachments for their identity, whereas men are socialized to be more dependent on work and professional accomplishments (Gallos, 1989). Research has supported this idea, showing that women tend to utilize social networks at work to increase their pool of useful information and advice more so than men (Friedman & Greenhaus, 2000). There is empirical evidence to support the idea of gender as a moderator of the relationship between informal organizational support (e.g., FSOP, supervisor support) and outcomes. For example, Hill (2005) found that the relationship between a supportive organizational culture and work–family facilitation was positive for working mothers and negative for working fathers. Additionally, Batt and Valcour (2003) found that supervisor work–family support was related to lower work–family conflict for women but not men, and Raghuram,Luksyte, Avery, and Macoukji (2012) found that men’s overall stress levels remained constant regardless of the level of general supervisor support, but women had significantly lower levels of stress when supervisor support was high. For ease of presentation, we have organized our study hypotheses by valence: negatively valenced work–family outcomes include negative spillover and intent to quit, whereas positively valenced work–family outcomes include positive spillover and job satisfaction.

We also predict that the relationship between use of formal policies (e.g., flextime, telecommuting) and work–family outcomes may differ for men and women. Specifically, based on the aforementioned theoretical rationale, we hypothesize that women will experience greater positive outcomes through the utilization of formal organizational policies including flextime, telecommuting, and compressed workweeks. Empirical evidence also supports the idea that men and women react to and benefit from various organizational support policies differently. For example, research has shown that women are more likely than men to highly value flexible work options (Catalyst, 2001), which may at least partially explain why flextime has been shown to reduce work–family conflict (Casper & Harris, 2008) and enhance commitment (Carlson et al., 2010) and job satisfaction (Scandura & Lankau, 1997) more effectively for women than for men. Additionally, using percentage of women employed at a given company as a proxy for gender, Konrad and Mangel (2000) found that the larger the percentage of women employed at a company, the stronger the relationship between the organization’s formal work–life programs and firm productivity. Overall, we hypothesize that women will be more likely to benefit from formal organizational support factors than men.

Although not a main focus of the present study, we also examined the potential differential relationships between negative and positive spillover and the outcomes of job satisfaction and intention to quit. Researchers have speculated that work and family variables are more strongly related to each other for women than men because men are more likely to mentally separate work and family roles than women (Andrews & Bailyn, 1993; Rothbard, 2001). There is some empirical evidence to support this idea. For example, in Kossek and Ozeki’s (1998) meta-analysis, work–family conflict was more strongly related to job and life satisfaction for women than men. Duxbury and Higgins (1991) found a stronger relationship between work–family conflict and quality of work life for women than for men, but the relationship between work–family conflict and quality of family life was stronger for men than for women. Ergeneli, Ilsev, and Karapinar(2010) found that work–family conflict was more strongly related to women’s job satisfaction than men’s, but this also depended on employees’ stress-resilient interpretive habits. Due to the lack of a clear theoretical explanation for these differences, we study these relationships in an exploratory manner.

Method

Results

As a first step, the pattern of missing data were examined. Excluding items clearly not relevant to some participants (e.g., items asking about child care); there was an average of less than 5% missing data at the item level. Little’s (1988) missing completely at random test was conducted, and the chi-square value for this test was nonsignificant (χ² = 626.93, df = 598, ns), which indicates that no identifiable pattern exists to the missing data. Thus, missing data were handled via multiple imputations based on the expectation maximization algorithm. Table 1 presents the means, standard deviations, and correlations for study variables separately for men and women. There were significant gender differences in telecommuting usage (t = −2.26, p < .05), with men reporting significantly higher usage (M = 0.30) than women (M = 0.17). No other gender differences were found for the other study variables. Multiple regression analyses were run to test our hypotheses.

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Table 1.

Study Means, Standard Deviations, and Intercorrelations.

	Men		Women		Intercorrelations
	M	SD	M	SD	1	2	3	4	5	6	7	8	9
1. FSOP	5.59	1.74	5.05	2.12	—	.52**	.15	.11	.06	−.23*	.31**	.45**	−.37**
2. Supervisor work–family support	3.79	0.99	3.56	1.14	.67**	—	.06	.15	.04	−.02	.32**	.47**	−.26*
3. Flextime use	0.45	0.50	0.36	0.48	.23**	.16	—	.42**	.46**	.10	.19	.02	−.15
4. Telecommuting use	0.30	0.46	0.16	0.37	.22*	.12	.41**	—	.22*	.12	.08	−.03	−.27*
5. Compressed workweek use	0.24	0.43	0.19	0.39	−.03	.06	.37**	.21*	—	.10	.11	−.05	−.10
6. Negative work–family spillover	2.41	0.61	2.57	0.73	−.41**	−.42**	−.13	−.08	−.11	—	.03	−.26*	.27*
7. Positive work–family spillover	2.85	0.81	2.85	0.92	.22*	.26**	.17	.17	.02	−.13	—	.26*	−.28**
8. Job satisfaction	5.77	1.47	5.66	1.40	.58**	.46**	.14	.15	.08	−.41**	.32**	—	−.57**
9. Intent to quit	2.29	1.47	2.65	1.70	−.56**	−.56**	−.11	−.13	.01	.38**	−.34**	−.58**	—

Note. FSOP =family-supportive organization perceptions. n (men) = 87, n (women) = 131 due to listwise deletion. Intercorrelations for women are below the diagonal and intercorrelations for men are above the diagonal.

*

p < .05. **p < .01.

Turning next to the multiple regression analyses, prior to entering the interaction terms to investigate the moderating role of gender in the relationship between organizational support factors and work–family outcomes, we first entered all control variables and each predictor variable. As shown in Table 2, at this first step, the variables cumulatively explained a significant amount of variance in negative work–family spillover (R²= .18, p < .001), positive work–family spillover (R²= .11, p < .01), job satisfaction (R²= .37, p < .01), and intent to quit (R²= .44, p < .001). FSOP was a significant predictor of negative work–family spillover (β= −.30, p < .001). Supervisor work–family support was a significant predictor of positive work–family spillover (β= .21, p < .05). FSOP (β= .33, p < .001), supervisor work–family support (β= .18, p < .05), negative work–family spillover (β= −.18, p < .01) and positive work–family spillover (β= .15, p < .05) were significant predictors of job satisfaction. FSOP (β= −.15, p < .05), telecommuting use (β= −.13, p < .05), negative work–family spillover (β= .14, p < .05), positive work–family spillover (β= −.12, p < .05), and job satisfaction (β= −.35, p < .001) were significant predictors of intent to quit.

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Table 2.

Hierarchical Regression Results for Covariates, Main Effects, and Moderator Analyses.

	Negative work–family spillover		Positive work–family spillover		Job satisfaction		Intent to quit
	Step 1	Step 2	Step 1	Step 2	Step 1	Step 2	Step 1	Step 2
Marital status	0.07	0.09	0.06	0.08	0.11	0.13*	−0.05	−0.02
Parental status	−0.16*	−0.16*	−0.02	−0.01	0.03	0.04	0.03	0.04
Gender	−0.09	−0.09	−0.06	−0.07	−0.07	−0.07	−0.02	−0.03
FSOP	−0.30***	−0.27**	0.09	0.07	0.33***	0.36***	−0.15*	−0.13
Supervisor work–family support	−0.12	−0.13	0.21*	0.23**	0.18*	0.17*	−0.12	−0.12
Flextime use	0.01	0.01	0.12	0.12	−0.03	−0.01	0.03	0.03
Telecommuting use	0.07	0.06	0.04	0.05	−0.01	−0.02	−0.13*	−0.14*
Compressed workweek use	−0.04	−0.04	−0.01	−0.01	0.02	0.03	0.01	0.00
Negative work–family spillover	—	—	—	—	−0.18**	−0.19**	0.14*	0.11
Positive work–family spillover	—	—	—	—	0.15*	0.15*	−0.12*	−0.13*
Job satisfaction	—	—	—	—	—	—	−0.35***	−0.39***
Gender * FSOP	—	−0.03	—	0.09	—	−0.06	—	0.03
Gender * Supervisor work–family support	—	0.17*	—	0.01	—	0.17*	—	0.18**
Gender *Flextime use	—	0.04	—	0.02	—	0.07	—	0.00
Gender *Telecommuting use	—	0.03	—	−0.09	—	−0.08	—	−0.12*
Gender *Compressed workweeks use	—	0.07	—	0.04	—	−0.07	—	−0.06
Gender *Negative work–family spillover	—	—	—	—	—	−0.03	—	0.04
Gender * Positive work–family spillover	—	—	—	—	—	−0.05	—	0.00
df	(8, 209)	(13, 204)	(8, 209)	(13, 204)	(10, 207)	(17, 200)	(11, 206)	(19, 198)
F	5.59***	4.27***	3.23**	2.21*	12.34***	7.89***	14.94***	9.76**
R 2	.18	.21	.11	.12	.37	.40	.44	.48

Note. FSOP =family-supportive organization perceptions; df = degrees of freedom. N = 229. Gender, 1 = women and 2 = men.

*

p < .05. **p < .01. ***p < .001.

Moderating Role of Gender

In Step 2, the interaction terms were entered into the regression equation (see Table 2). Significant interaction effects were examined graphically (see Figures 1 through 4) and simple slopes are presented in Table 3. The overall regressions were significant, as the control variables, antecedent variables, and interaction terms cumulatively explained a significant amount of variance in negative work–family spillover (R²= .21, p < .001), positive work–family spillover (R²= .12, p < .05), job satisfaction (R²= .40, p < .001), and intent to quit (R²= .48, p < .01).

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Table 3.

Simple Slopes for Significant Interactions.

Variable	Outcome	Simple slope	Standard error	t Value	p Value
Supervisor work–familysupport	Negative work–family spillover (df = 204)
	Women	−0.10*	0.05	−1.96	0.05
	Men	0.12	0.10	1.18	0.24
	Job satisfaction (df = 200)
	Women	0.18	0.10	1.74	0.08
	Men	0.66***	0.19	3.48	0.00
Telecommuting use	Intent to quit (df = 198)
	Women	−0.46	0.23	−1.95	0.05
	Men	−1.37**	0.47	−2.91	0.00
Supervisor work–family support	Intent to quit (df = 198)
	Women	−0.23*	0.11	−2.15	0.03
	Men	0.32	0.21	1.50	0.13

Note.df = degrees of freedom.

*

p < .05. **p < .01. ***p < .001.

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Figure 1.

Gender as a moderator of the relationship between supervisor work–family support and negative work–family spillover.

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Figure 2.

Gender as a moderator of the relationship between supervisor work–family support and intent to quit.

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Figure 3.

Gender as a moderator of the relationship between supervisor work–family support and job satisfaction.

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Figure 4.

Gender as a moderator of the relationship between telecommuting use and intention to quit.

Hypotheses 1 and 2 predicted that gender would moderate the relationship between FSOP and work–family outcomes; however,none of the interactions were significant. In support of Hypothesis 3, gender significantly moderated the relationship between supervisor work–family support and negative work–family outcomes (see Figures 1 and 2). The relationship between supervisor work–family support and intent to quit was negative and significant for women (b = −0.23, SE = 0.11, p < .05) but not for men. Additionally, the relationship between supervisor work–family support and negative work–family spillover was negative and significant for women (b = −0.10, SE = 0.05, p < .05) but not for men. Our Hypothesis 4, which predicted that gender would moderate the relationship between supervisor work–family support and positive work–family outcomes, was not supported. Although gender significantly moderated the relationship between supervisor work–family support and job satisfaction (see Figure 3), findings were contrary to our hypothesis. Specifically, the relationship between supervisor work–family support and job satisfaction was positive and significant for men (b = 0.66, SE = 0.19, p < .001) but not for women. Gender did not moderate the relationship between supervisor work–family support and positive spillover. Hypotheses 5 to 10 predicted that gender would moderate the relationship between policy use (flextime, telecommuting, and compressed workweek) and the positive and negative outcome variables. These analyses revealed one significant interaction (Hypothesis 7), but it was in the opposite direction as hypothesized. Specifically, the effect of use of telecommuting on intent to quit was negative and significant for men (b = −1.37, SE = 0.47, p < .01) but not for women. Figure 4 depicts this relationship in terms of conditional mean-levels of intent to quit. Finally, no gender differences were found relating to our research question. Specifically, the relationships between negative and positive work–family spillover and the outcome variables of job satisfaction and intent to quit were not significantly moderated by gender (see Table 2). Thus, the research question was not supported.

Discussion

The goal of this study was to develop a better understanding of how various organizational support factors influence work–family outcomes and the role of gender in these experiences. Results obtained from a random sample of Michigan residents who worked full-time revealed four key findings: (a) some organizational support factors (e.g., FSOP) appear to be beneficial for both men and women; (b) some organizational support factors, particularly supervisor work–family support, may benefit men and women through different underlying mechanisms; (c) supervisor work–family support was the only significant predictor of positive work–family spillover; and (d) contrary to predictions, men appear to use and benefit more than women from telecommuting use. Below, we discuss the implications of these findings on theory and practice and suggestions for future research.

In the present study, we examined three forms of organizational support using Hammer et al.’s(2007) categorization: (a) FSOP, (b) supervisor work–family support, and (c) organizational policies (i.e., flextime, telecommuting, and compressed workweeks). Our results suggest that employees’ perception that their organization is family supportive was the most consistent predictor of work–family outcomes. Specifically, FSOP were related to lower negative work–family spillover and intent to quit, and higher job satisfaction. Gender did not emerge as a significant moderator of the FSOP—outcomes relationships. It appears that both men and women benefit when they perceive their organization as supportive of their desires to balance work and family.

Supervisor work–family support also emerged as an important predictor of work–family outcomes, as it was significantly related to higher positive work–family spillover and job satisfaction. Interestingly, though, men and women appear to benefit in different ways from this form of support. Specifically, at least in our sample, having a supportive work–family supervisor was related to reduced negative outcomes for women (e.g., decreased intent to quit), but enhanced positive outcomes (e.g., increased job satisfaction) for men. As Hammer and colleagues point out, supervisors can show their support for employees’ work and family needs in many different ways: (a) emotional support, (b) instrumental support, (c) role-modeling behaviors, and (d) creative work–family management (Hammer, Kossek, Anger, Bodner, & Zimmerman, 2011; Hammer, Kossek, Yragui, Bodner, & Hanson, 2009). Perhaps, men and women may respond differently to each of these specific forms of supervisor work–family support behaviors. To date, no known studies have examined the mechanisms through which supervisor work–family support may influence outcomes separately for men and women, but based on the results from the present study, this appears to be an area in need of greater research.

Turning next to organizational policies, we found that not only were men more likely to utilize telecommuting than women, but the use of telecommuting was significantly related to less intent to quit for men but not for women. One possible explanation for the gender difference in usage is that many companies have a policy of “formalized discretion” in which the manager decides whether or not to offer family-friendly policies to a particular employee (Kelly & Kalev, 2006). Research has shown that women are less likely than men to negotiate for themselves (Babcock & Laschever, 2003), so it is possible that when organizations have a “formalized discretion” approach to work–family policies, women are less likely than men to ask to use these work–family benefits. In order to examine this possibility, we performed some post hoc analyses to further examine our telecommuting variable. The option of using telecommuting was made available to 31% of our participants. However, when breaking this down by gender, we see that indeed telecommuting was available to a greater percentage of men (39%) than women (26%) in the present sample (and this difference was statistically significant). Furthermore, more men (76%) than women (65%) actually used telecommuting when it was made available to them. Though this difference in usage was not statistically significant in the present sample, these trends provide initial support to the idea of a gender difference in either formalized discretion or in the extent to which women and men ask or negotiate to use such policies.

Another possible explanation for these findings is that women may work in less family-friendly industries, and this is influencing the extent to which women choose to use family-friendly policies. To explore this, we examined the number of policies available (examined as an aggregate) among respondents from the top-eight sectors represented in our data (i.e., Administrative & Support; Professional, Scientific, & Technical Services; Health & Social Assistance; Education Services; Retail Trade; Management of Companies & Enterprises; Transportation & Warehousing; Public Administration). A 2 (men vs. women) × 8 (top-eight NAICS Codes) analysis of variance was run, F(15, 173) = 1.39, ns; neither main effect nor the gender × industry interaction was significant. Analyses specific to telecommuting availability (as opposed to an aggregate policy variable) were also nonsignificant. Thus, our additional analyses suggest these findings are not attributable to the type of industry sectors participants were employed in.

It is possible that telecommuting may be considered more acceptable for men to use than other types of work–family policies such as flextime or compressed workweeks, and that may explain the significant negative relationship between telecommuting use and intent to quit for men. Further examination of the data revealed that in our sample, this does not appear to be the case; 83% of men who were offered flextime used it, compared with 76% for telecommuting, and 65% for compressed workweeks. Interestingly, women were most likely to take advantage of flextime when it was offered to them (80%), were slightly less likely to take advantage of compressed workweeks (71%), and the least likely to take advantage of telecommuting when it was offered (65%). Given these trends, we recommend that future research investigate the possible reasons women may be less likely to take advantage of telecommuting over other workplace policies when made available.

One key finding of the present study is that, with one exception, the use of family-friendly policies was not related to work–family outcomes for men or women in our sample. The current findings support the claim that the use of organizational policies may be a necessary, but insufficient condition to help employees balance the demands of work and family (Allen, 2001). We propose that both men and women may be hesitant to utilize such formal policies, but for different reasons. On the one hand, men may not take advantage of policies as much as women due to fears of social stigmatization (Kossek, Lautsch, & Eaton,2006). Such negative ramifications have been shown in a laboratory study by Butler and Skattebo (2004), who found evidence that men who admitted to experiencing family conflicts received lower performance ratings. On the other hand, women who take advantage of family-friendly policies may be subject to the stereotype that working mothers are less committed to work than men (Konrad & Yang, 2012). Both men and women may desire to take advantage of such work–life policies, but fear that using them may hurt their careers (Blair-Loy & Wharton, 2002). Additionally, many other contextual constraints may influence all employees’ (not just women’s) use of these policies, such as the number of women in one’s work group, opinions, and beliefs from powerful others in the organization, characteristics of one’s supervisor (Blair-Loy & Wharton, 2002, 2004), as well as one’s organizational tenure.

This study also advances our understanding of how organizational support factors relate to positive, in addition to negative, work–family spillover. Our results support the notion that positive and negative forms of work–family spillover are unique constructs that operate in different ways (Grzywacz & Butler, 2005). Thus, if organizations wish to both reduce employees’ negative work–family spillover and increase their positive work–family spillover, the organization may want to ensure that they are offering employees several different forms of support (e.g., ensuring the organization is committed to endorsing a strong family-friendly culture and also offering formal family-friendly policies). Future research should examine the mechanisms through which some of the support factors are related to one form of spillover and not the other.

Conclusion

The present study contributes to our understanding of how various formal and informal organizational support factors affect employee work–family outcomes, and it also highlights how these relationships may sometimes differ for men and women. Although some forms of support appear to be beneficial for men and women alike (e.g., FSOP), other forms of support appear to have more complex relationships with outcomes depending on one’s gender. These findings suggest that researchers should further examine how these forms of support benefit different groups of employees (e.g., men vs. women, parents vs. nonparents). In the present study, informal support factors were generally more impactful than formal organizational support factors such as flextime and telecommuting. This suggests that even if an organization cannot offer formal work–family policies, they may be able to improve employee well-being through a strategic focus on creating and fostering a supportive work–family culture or by encouraging supervisors to be supportive of employee’s work–family concerns.

Our findings regarding gender differences illustrate the positive effects one’s supervisor can have on work–family outcomes, though supervisor support may be important in different ways for men and women. For women, having a supportive work–family supervisor was related to less negative work–family spillover and lower intent to quit, and for men, having a supportive work–family supervisor was related to greater job satisfaction. Additionally, telecommuting use was particularly beneficial for men, resulting in lower intent to quit. Post hoc analyses revealed that women were less likely than men to have telecommuting offered as an option, and when it was offered, they were also less likely than men to use it. These findings have implications for both research and practice, and highlight the fact that gender cannot be ignored when considering the effects of various organizational support factors on employee well-being.