Journal of Occupational Health Psychology 2015, Vol. 20, No. 1, 82–92

© 2014 American Psychological Association 1076-8998/15/$12.00 http://dx.doi.org/10.1037/a0037890

Setting a Good Example: Supervisors as Work-Life-Friendly Role Models Within the Context of Boundary Management Anna R. Koch and Carmen Binnewies

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University of Muenster This multisource, multilevel study examined the importance of supervisors as work-life-friendly role models for employees’ boundary management. Particularly, we tested whether supervisors’ work-home segmentation behavior represents work-life-friendly role modeling for their employees. Furthermore, we tested whether work-life-friendly role modeling is positively related to employees’ work-home segmentation behavior. Also, we examined whether work-life-friendly role modeling is positively related to employees’ well-being in terms of feeling less exhausted and disengaged. In total, 237 employees and their 75 supervisors participated in our study. Results from hierarchical linear models revealed that supervisors who showed more segmentation behavior to separate work and home were more likely perceived as work-life-friendly role models. Employees with work-life-friendly role models were more likely to segment between work and home, and they felt less exhausted and disengaged. One may conclude that supervisors as work-life-friendly role models are highly important for employees’ workhome segmentation behavior and gatekeepers to implement a work-life-friendly organizational culture. Keywords: work-life-friendly role modeling, boundary management, work-home segmentation behavior, exhaustion, disengagement

typically cannot rely on formal systems of job descriptions to cultivate boundary management, there should be a strong influence of role models (Yaffe & Kark, 2011). Until now, knowledge about supervisors as role models for their employees’ work-home segmentation is scarce, although there have been calls for studies on the effect of supervisors as role models within the context of boundary management (Hammer, Kossek, Yragui, Bodner, & Hanson, 2009). In addition, research aimed to identify starting points for implementing a work-lifefriendly organizational culture (Thompson, Beauvais, & Lyness, 1999). Supervisors constitute promising starting points (O’Neill et al., 2009). Considering organizational work-life interventions, it would be highly important to know whether supervisors with high work-home segmentation behavior represent work-life-friendly role models within their work group. We address these calls and focus on supervisors as role models within the context of boundary management. Relying on social learning (Bandura, 1977) and recovery theories (Meijman & Mulder, 1998), we argue that supervisors with high work-home segmentation behavior who define clear respite from work when being at home represent work-lifefriendly role models. Although the work-home segmentation of supervisors is not behavior that is directly aimed at employees, it is visible and thus observable by employees (Nippert-Eng, 1996). Employees can observe supervisors giving an example of how to manage both life domains successfully in terms of defining workfree respites when at home. We propose that work-life-friendly role modeling is positively related to employees’ individual workhome segmentation behavior and well-being (low amounts of exhaustion and disengagement). Work-life-friendly role models should facilitate the work-home segmentation behavior of employees in terms of taking respites, during which recovery can occur. Moreover, work-life-friendly role models may give employees the feeling of being fairly treated because of an adequate amount of

Currently, work can be done anywhere and anytime. Boundaries between work and home domains are becoming increasingly blurred (Ashforth, Kreiner, & Fugate, 2000). For example, the rise of communication technology allows wireless Internet access and facilitates work being done at home (Kurland & Bailey, 1999). Employees must step up to the new challenge of successfully organizing the boundaries between their work and home domains. As most human learning occurs through observational learning (Bandura, 1977) employees often rely on their supervisors as role models for learning how to successfully organize their work-home boundaries (Kreiner, Hollensbe, & Sheep, 2009; Park, Fritz, & Jex, 2011). Supervisors are part of employees’ organizational environment, which boundary theory emphasizes as an influential antecedent for employees’ boundary management (Clark, 2000; Kossek & Lautsch, 2012). Supervisors embody organizational values (Powell & Mainiero, 1999; Scandura & Lankau, 1997) and allow employees to view them as positive examples of organizational boundary management norms. Particularly, because organizations

This article was published Online First September 8, 2014. Anna R. Koch and Carmen Binnewies, Institute of Psychology, University of Muenster. This study is part of Anna R. Koch’s dissertation. Preliminary results of this study were presented at the 16th Conference of the European Association of Work and Organizational Psychology in Muenster, Germany. We thank Wiebke Boess, Anna Sophie Herrmann, Ina Krueger and Astrid Wirth for their involvement in data collection. We thank Verena C. Hahn and Eva Brosch for helpful comments on earlier versions of this paper. Correspondence concerning this article should be addressed to Anna R. Koch, Institute of Psychology, University of Muenster, Fliednerstr. 21, 48149 Muenster, Germany. E-mail: [email protected] 82

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SETTING A GOOD EXAMPLE

segmentation from work when they are at home, and increase positive emotions and identification with the organization. By including the concept of supervisors’ work-life-friendly role modeling into boundary management research, our study contributes to the literature in two ways. First, our study captures the relationship between work-life-friendly role modeling and employees’ work-home segmentation behavior. Studying work-lifefriendly role modeling as one element and potential predictor from the organizational environment will enrich theory building around the construct of boundary management. Hence, our study contributes to boundary literature and helps to better understand the phenomenon of boundary management itself. Second, our study examines whether supervisors who show a high degree of segmentation behavior between the work domain and home domain are experienced as work-life-friendly role models within their work groups. Focusing on the relationship between supervisors’ own work-home segmentation behavior and work-life-friendly role modeling allows us to draw a more comprehensive picture of the potential consequences of boundary management. Our study thereby aims to identify new starting points for implementing a work-life-friendly organizational culture.

Boundary Management Boundary theory indicates that employees create and maintain boundaries between their life domains, such as work and home (Bulger, Matthews, & Hoffman, 2007; Clark, 2000; Nippert-Eng, 1996). Boundaries can be constructed along a continuum from weak ones (high integration between domains) to strong ones (high segmentation between domains). Employees differ in their behaviors and strategies for integrating and segmenting life domains (Hecht & Allen, 2009; Nippert-Eng, 1996). These behavioral strategies aimed at integrating and segmenting life domains have been defined as boundary management (Ashforth et al., 2000; Bulger et al., 2007; Clark, 2000; Nippert-Eng, 1996). Within the context of work-life-balance, boundary management (e.g., bringing elements of one domain into the other) comprises two typical behaviors, referring to the integration of home into work and work into home (Bulger et al., 2007; Hecht & Allen, 2009). Home-work segmentation behavior refers to the degree to which employees prevent various aspects of the home domain from entering the work domain. Second, work-home segmentation behavior refers to the degree to which employees prevent various aspects of work from entering the home domain. In our study, we focus on the second dimension: work-home segmentation behavior. Work-homesegmentation behavior refers to the extent that employees work out of office, write or receive work-related correspondence at home, and define clear respites (Hecht & Allen, 2009). Employees with high work-home segmentation behavior draw a line between work and home domains (Kreiner et al., 2009). For example, employees take respites during which they are not available for work issues while at home. In contrast, employees with low work-home segmentation behavior are likely to integrate work into the home domain, for example by doing work-related correspondence at home (Hecht & Allen, 2009). Boundary management is visible and thus observable by others (Nippert-Eng, 1996). Nippert-Eng (1996) states that boundary management “is first and foremost a mental activity, but it must be enacted and enhanced through a largely visible collection of essential, practical activities” (Nippert-

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Eng, 1996, p. 7). Thus, supervisors’ work-home segmentation behavior can be recognized by employees through direct and indirect indicators (Friedman & Lobel, 2003). Such indicators could be supervisors’ direct communication, observed work and nonwork hours, work results and received and written work-related correspondence during nonwork time.

Recovery Perspective on Work-Home Segmentation Behavior In general, there is not just one right way to manage boundaries. Research suggests that boundary management highly depends on employees’ preferences for segmentation (Park et al., 2011). However, we argue that from a recovery perspective at least a slight degree of segmentation between work and home domain is essential to release load reactions and secure well-being (Meijman & Mulder, 1998). According to the Effort-Recovery model (Meijman & Mulder, 1998), recovery occurs with the absence of work stressors. If an employee stops working and depleting resources, the functional system returns to the baseline level and recovery automatically occurs (Binnewies & Sonnentag, 2008; Meijman & Mulder, 1998). Therefore, according to the Effort-Recovery model (Meijman & Mulder, 1998) recovery is essential to segment life domains and find at least some respite from work when at home. Recovery research supports this assumption and shows that recovery during nonwork time is beneficial for well-being and health (Sonnentag & Bayer, 2005; Sonnentag & Fritz, 2007). However, if time for recovery is not sufficient, an employee’s functional system does not return to the baseline level and the performance of upcoming work tasks is impeded (Binnewies & Sonnentag, 2008; Meijman & Mulder, 1998). For example, job-related activities during nonwork time further draw on resources needed at work and inhibit recovery (Sonnentag, 2001). Consequently, an employee must invest compensatory effort in order to maintain the fulfillment of tasks and goals (Meijman & Mulder, 1998). Insufficient recovery and increased fatigue can accumulate, when recovery is lacking over longer periods of time (Meijman & Mulder, 1998). Over time, negative consequences, such as severe health complaints that cannot be easily reversed during the usual rest periods can result (Burke & Fiksenbaum, 2008). In conclusion, from a recovery perspective work-home segmentation in terms of finding respite from work is needed to recover from work stress (Park et al., 2011). High integration of work into the home domain without respite harms recovery (Park et al., 2011).

Supervisors as Work-Life-Friendly Role Models Social learning theory emphasizes the importance of role models for employees’ behaviors and attitudes within the organizational context (Bandura, 1977). Supervisors are emphasized as particularly important role models, for example by transformational leadership theories (Bass & Avolio, 1994; Judge & Bono, 2000). Supervisors’ behavior shapes organizational norms and embodies organizational values (Hammer et al., 2009; Powell & Mainiero, 1999; Scandura & Lankau, 1997). For example, supervisors embody organizational valued boundary management. Therefore, we argue that supervisors who segment more between work and home represent stronger work-life-friendly role models within their work groups.

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KOCH AND BINNEWIES

We define work-life-friendly role models as those who provide examples of strategies and behaviors that allow employees to recover from work stress. Supervisors who are perceived as worklife-friendly role models set a good example in terms of work-life balance, for example by taking respites during nonwork time and refraining from work-related activities. In our study, we conceptualize work-life-friendly role modeling as a shared group-level variable that reflects work group members’ perceptions of the extent to which their supervisor constitutes a work-life-friendly role model. This definition implies that employees working in the same work group are likely to experience similar supervisor boundary management. This definition is consistent with Chen and Bliese (2002) who conceptualized leadership behavior as shared group-level perception and implies that supervisors’ work-home segmentation behavior is visible within their work group. Work-life role modeling comprises supervisors’ modeling behaviors on the job (Hammer et al., 2009). We propose that supervisors’ work-home segmentation behavior is a particularly important modeling behavior. Supervisors who highly segment between work and home domains create work-free spaces in their private lives (e.g., engaging in leisure and family activities) during which they are not available for work-related issues. These supervisor behaviors provide employees with the impression that the organization values private life and that taking time off does not hinder organizational success (Friedman & Lobel, 2003). Supervisors who highly integrate work into the home domain with an ‘always-on’ mentality do not intentionally create work-free spaces in their private lives. These supervisors are likely to engage in work issues at any time (Hecht & Allen, 2009). Supervisors with high work-home integration behavior may therefore imply that the organization expects employees to be always available even during nonwork time, probably to the detriment of family obligations and leisure activities (Friedman & Lobel, 2003). Therefore, these supervisors may embody the perception that there is low organizational support for employees’ private lives and recovery from work stress. Empirical evidence supports our proposition: Kirby and Krone (2002) showed that other than what supervisors communicate, employees look at their supervisors’ behavior (e.g., hours worked overtime) regarding their use of alternative work arrangements (e.g., flextime). Also Hammer and colleagues (2009) found that supervisors are experienced as role models within the context of work-life-balance. Hypothesis 1: Supervisors with high work-home segmentation behavior represent work-life-friendly role models within their work group.

Work-Life-Friendly Role Modeling Is Related to Employees’ Work-Home Segmentation Behavior and Well-Being We argue that work-life-friendly role models constitute an important resource for employees in the organizational context (Hammer et al., 2009) and should be positively related to employees’ own work-home segmentation behavior. Moreover, work-life role modeling should be positively associated with employees’ well-being. Regarding employees’ well-being, we focused on two core dimensions: emotional exhaustion and disengagement (cf.

Demerouti, Bakker, Nachreiner, & Schaufeli, 2001). Exhaustion is a consequence of intense strain, and a long-term consequence of prolonged exposure to certain job demands (Demerouti et al., 2001). Disengagement refers to distancing oneself from one’s work in general, work tasks and work content (Demerouti et al., 2001). Low disengagement is associated with high identification with work and willingness to stay in the same occupation (Demerouti, Mostert, & Bakker, 2010). In general, employees rely on role models by forming expectations for themselves as well as guidelines for future behavior (Bandura, 1977), which in turn affects their well-being and behavior. A role model’s behavior is copied particularly at times when rewarding consequences are expected (Bandura, 1977). Supervisors represent organizational values (Powell & Mainiero, 1999; Scandura & Lankau, 1997), have high decisional power, and are often responsible for hiring, evaluating and promoting employees. As a consequence, they constitute role models whose behavior is likely to be imitated (Bandura, 1977; Weiss, 1978). Previous research has shown that work-home segmentation behavior depends not only on individual preferences for integration and segmentation but also on organizational norms (Park et al., 2011), as represented by the supervisor. We argue that employees should be more likely to intentionally define respites and believe that they do not have to be always available when working with a work-life-friendly role model. In order to be successful in the organization, employees are likely to adapt their behavior according to the work-life-friendly role model (Park et al., 2011) by segmenting stronger between work and home domains. Moreover, employees should feel fairly treated and experience support for their private lives, as organizations allow time for respites. Positive emotions and identification with the organization should thereby also be higher. Also, during work-free respites load reactions (e.g., fatigue) can be released and recovery can occur, which should benefit employees’ well-being (CohenCharash & Spector, 2001; Meijman & Mulder, 1998). In sum, we argue that work-life-friendly role modeling should be positively related to employees’ work-home segmentation behavior and wellbeing (low amounts of exhaustion and disengagement). A work-life-unfriendly role model makes it more likely that employees conclude that their organization expects an “alwayson” mentality. Therefore, it will be more likely that employees integrate work into their home domain, for example, by taking fewer work-free respites. These employees are more likely to feel unfairly treated by disproportionate expectations of work-home integration. Employees are more likely to feel distressed and less committed to their organization (Cohen-Charash & Spector, 2001). Moreover, if employees do not take work-free respites, they cannot recover from load reactions, which may result in impaired wellbeing (Meijman & Mulder, 1998). Therefore, we argue that worklife-unfriendly role models should be negatively related to employees’ work-home integration and reduce employees’ well-being (high amounts of exhaustion and disengagement). There is initial empirical evidence that supports our assumptions. Park and colleagues (2011) found that the organizational segmentation norm affects whether employees can refrain from work-related thoughts during nonwork time. Burke (2006) found that employees who experienced their organization (and supervisor) as valuing work-life-balance felt less forced to work extended hours.

SETTING A GOOD EXAMPLE

Hypothesis 2: Work-life-friendly role modeling will have a direct positive relationship with employees’ work-home segmentation behavior. Hypothesis 3: Work-life-friendly role modeling will have a direct negative relationship with employees’ exhaustion and disengagement.

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Method We used a multisource design with employees and their supervisors to test our hypotheses. Participants were white-collar employees and supervisors from various German organizations. To recruit participants we contacted and informed managers from various companies (e.g., mostly local and federal administrations, health insurance companies and care providers) about our study on “work-life balance and recovery.” After managers expressed interest in participation, we provided them with information leaflets that they used to inform employees. Employees could then register online for study participation. Upon registration we sent employees packages including instruction leaflets, paper-and-pencil questionnaires and postpaid return envelopes. Employees completed the predictor variable questionnaire immediately, whereas the outcome variable questionnaire was completed 2 days later. Employees also received questionnaires for their supervisors and were asked to invite their supervisors to participate in the study by giving them the questionnaires. Like employees, supervisors could then decide whether or not they wanted to participate in the study. All questionnaires were sent back via postpaid envelopes. Employees’ and supervisors’ questionnaires were matched with a code. In total, 403 employees and 81 supervisors participated in our study. A total of 149 employees1 had to be dropped from the analyses, as they could not be matched with supervisor data. For all study variables as well as for all demographic variables, we conducted t-tests in order to compare employees whose supervisors had participated with employees whose supervisors had not participated. T-tests showed that employees whose supervisors had participated did not significantly differ from those employees whose supervisors had not participated with respect to job involvement, work-life role modeling, work-home segmentation behavior and exhaustion. The only significant difference between the groups was that disengagement was higher for employees whose supervisors had not participated. One possible explanation for this finding is that less highly disengaged employees did invite their supervisors to participate. Another 17 employees and six supervisors had to be excluded because of missing data on study variables. Thus, our final sample consisted of 237 employees and 75 supervisors. The majority of employees was female (67.4%). Employees’ mean age was 41.93 years (SD ⫽ 13.15). On average, 31.6% of employees lived together with a partner and 37.6% lived together with a partner and children. The average number of children was 0.82 (SD ⫽ 0.98).2 On average, employees had worked 10 years (SD ⫽ 9.78) in their current company and 1.26% held a leadership position (SD ⫽ 0.99). With regard to supervisors, 45.5% were female and on average 49.25 years old (SD ⫽ 11.50). The average employment duration of supervisors within their current company was 15.81 years (SD ⫽ 9.86). On average, 12.57 employees per supervisor participated (SD ⫽ 12.53).

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Measures Supervisors completed one questionnaire, which comprised their work-home segmentation behavior and demographic data. Employee data was measured with two questionnaires: a predictor and an outcome variable questionnaire. In the predictor variable questionnaire, employees’ perception of their supervisors as worklife-friendly role models was measured. Furthermore, employees’ job involvement as a control variable and demographic data were collected. In the outcome variable questionnaire that was completed 2 days after the predictor variable questionnaire, employees’ work-home segmentation behavior as well as their exhaustion and disengagement were measured. We used two separate questionnaires for employees to reduce common method bias. As recommended by Podsakoff, MacKenzie, Lee, and Podsakoff (2003), we separated the measurement of the predictor (role modeling perception) from the outcomes (employees’ work-home segmentation behavior and well-being). Our research design is displayed in Figure 1. Supervisors’ questionnaire. Supervisors’ work-home segmentation behavior was assessed with Hecht and Allen’s (2009) eight-item boundary strength at home scale. A sample item is “I often do work at home” (reverse coded). Answering categories were “1 ⫽ strongly disagree” to “7 ⫽ strongly agree.” Cronbach’s alpha was .88. Employees’ predictor variable questionnaire. Work-lifefriendly role modeling was assessed with a subscale of Hammer and colleagues’ (2009) family supportive supervisor behavior (FSSB) scale. The subscale contains three items. A sample item is “My supervisor is a good role model for work and nonwork balance.” Answering categories were “1 ⫽ strongly disagree” to “5 ⫽ strongly agree.” Cronbach’s alpha was .88. Employees’ job involvement was measured as a control variable. Boundary theory and recent research findings (Ashforth et al., 2000; Hecht & Allen, 2009) suggest that strong involvement within the work domain makes integration of work into the home domain more likely. Employees who strongly identify themselves with their job seem to be particularly willing to put their private life on hold in favor of work issues. Job involvement was assessed with a five-item short scale of Kanungo’s job involvement questionnaire (1982). This scale measures the degree of psychological importance of one’s job using a five-point Likert scale from “1 ⫽ strongly disagree” to “5 ⫽ strongly agree.” A sample item is “I consider my job to be very central to my existence.” Cronbach’s alpha was .87. Supervisors’ emotional work-life support was measured as a further control variable. Work-life research (e.g., Hammer et al., 2009; Thompson et al., 1999) has shown that supervisors’ worklife support benefits their employees in terms of work-home issues. To rule out proposed relationships simply being because of supervisors’ expressed support we decided to control for supervisors’ 1 In our study, employees who participated received the supervisor’s questionnaire and were asked to forward it to their supervisor. Thus, the dropout of the 149 employees without matchable supervisor data could have been caused by both employees and supervisors. Because of this procedure and reasons of anonymity, the rate of nonresponding supervisors cannot be determined. 2 Neither employees’ living situation nor their number of children was significantly related to our study’s predictor and outcome variables.

KOCH AND BINNEWIES

86 Supervisors’ quesonnaire

Supervisors’ work-home segmentaon behavior

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Figure 1.

Employees’ predictor variable quesonnaire

Employees’ outcome variable questionnaire

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Work-life friendly rolemodeling

-

Employees’ work-home segmentaon behavior

-

Employees’ job involvement

-

Employees’ exhauson

-

Emoonal work-life support

-

Employees’ disengagement

Conceptual model and research design.

emotional work-life support within our analyses. Supervisors’ emotional work-life support was measured with a subscale of Hammer and colleagues’ (2009) family supportive supervisor behavior (FSSB) scale. The subscale measures supervisors’ care and verbalized support toward employees’ work-life balance with four items. A sample item is “My supervisor makes me feel comfortable talking to him or her about my conflicts between work and nonwork.” Answering categories were “1 ⫽ strongly disagree” to “5 ⫽ strongly agree.” Cronbach’s alpha was .92. Employees’ outcome variable questionnaire. Employees’ work-home segmentation behavior was assessed with Hecht and Allen’s (2009) eight-item boundary strength at home scale. A sample item is “I often do work at home” (reverse coded). Answering categories were “1 ⫽ strongly disagree” to “7 ⫽ strongly agree.” Cronbach’s alpha was .82. Exhaustion and disengagement were assessed with the Oldenburg Burnout Inventory (Demerouti, Bakker, Vardakou, & Kantas Aristotelis, 2003). Emotional exhaustion was measured with eight items. A sample item is “After my work, I usually feel worn out and weary.” Disengagement was also measured with eight items. An example item is “I usually talk about my work in a derogatory way.” Answering categories for both dimensions were “1 – totally disagree” to “4 – totally agree.” Cronbach’s alphas were .82 for exhaustion and .78 for disengagement.

Data Analysis We had data at two levels: the employee level (Level 1) and the supervisor level (Level 2). Employee-level data was nested within supervisors. In order not to overestimate statistical significance (Urbach & Austin, 2005) we applied hierarchical linear models to test our hypotheses (Snijders & Bosker, 1999). We used the HLM software (HLM Version 6; Raudenbush, Bryk, Cheong, & Congdon, 2004) to analyze the data with hierarchical linear modeling.

To test our hypotheses, all predictor variables were centered around the grand mean.

Results Means, standard deviations, Cronbach’s alphas, intraclass correlations and zero-order correlations are displayed in Table 1. To test for the relationship between supervisors’ work-home segmentation behavior and work-life-friendly role modeling (Hypothesis 1) we conducted HLM analyses. In the Null model, the intercept was the only predictor. In Model 1, we entered employees’ job involvement and supervisors’ emotional work-life support as control variables. In Model 2, we entered supervisors’ work-home segmentation behavior as Level 2 predictor variable. Supervisors’ emotional work-life support in Model 1 (b ⫽ 0.57, p ⬍ .01) and supervisors’ work-home segmentation in Model 2 (b ⫽ 0.29, p ⬍ .01) emerged as significant positive predictors of work-lifefriendly role modeling (see Table 2). Thus, supervisors who provided support and segmented work from the home domain were experienced as stronger work-life-friendly role models within their work groups, which supports Hypothesis 1. To test whether work-life-friendly role modeling is related to employees’ work-home segmentation behavior and well-being (Hypotheses 2–3) we also used HLM analyses. In the Null model, the intercept was the only predictor. In Model 1, we entered employees’ job involvement and supervisors’ emotional work-life support as control variables. In Model 2, we entered supervisors’ work-home segmentation behavior and work-life-friendly role modeling as predictor variables. Table 3 displays the results for employees’ work-home segmentation behavior as an outcome variable. In Model 1, job involvement was a significant negative (b ⫽ ⫺.22, p ⬍ .001) predictor of employees’ work-home segmentation behavior. In Model 2, worklife-friendly role modeling was a significant positive predictor

Table 1 Means, Standard Deviations (SDs), Cronbach’s Alphas, Intra Class Correlations (ICCs) and Correlations Between Study Variables Variables 1. 2. 3. 4. 5. 6. 7.

Employees’ job involvement Emotional work-life support Supervisors’ work-home segmentation behavior Work-life-friendly role modeling Employees’ work-home segmentation behavior Employees’ exhaustion Employees’ disengagement

Mean

SD

␣

ICC

4.12 3.56 3.15 3.25 3.85 2.14 1.89

1.16 0.97 0.82 0.98 0.85 0.55 0.53

0.87 0.92 0.88 0.88 0.82 0.82 0.78

0.10 0.08

Note. N at the employee level ⫽ 237. N at the supervisor level ⫽ 75. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01.

0.14 0.08 0.06 0.13

1

2

3

4

5

6

.18ⴱⴱ .06 .20ⴱⴱ ⫺.29ⴱⴱ ⫺.02 ⫺.27ⴱⴱ

⫺.05 .56ⴱⴱ .08 ⫺.15ⴱ ⫺.27ⴱⴱ

.24ⴱⴱ .04 ⫺.02 ⫺.04

.14ⴱ ⫺.23ⴱⴱ ⫺.27ⴱⴱ

⫺.15ⴱ .17ⴱ

⫺.36ⴱⴱ

SETTING A GOOD EXAMPLE

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Table 2 Multilevel Estimates for Models Predicting Work-Life-Friendly Role Modeling Nullmodel

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Estim. Intercept Employees’ job involvement Emotional work-life support Supervisors’ work-home segmentation behavior ⫺2ⴱlog (lh) ⌬⫺2ⴱlog ⌬ DF Level 1 Intercept Variance (SE) Level 2 Intercept Variance (SE)

3.24

Model 1

SE

t

0.08

38.90

650.25 0.82 (0.09) 0.13 (0.08)

Estim. 3.26 0.05 0.57ⴱⴱⴱ

Model 2

SE

t

Estim.

SE

t

0.08 0.05 0.08

42.18 1.05 7.02

3.27 0.06 0.58ⴱⴱⴱ 0.29ⴱⴱ 541.96 9.89ⴱⴱ 1 0.51 (0.05) 0.11 (0.05)

0.07 0.05 0.08 0.10

48.52 1.14 7.49 2.84

551.85 98.40ⴱⴱⴱ 2 0.50 (0.05) 0.18 (0.07)

Note. N at employee level ⫽ 237. N at supervisor level ⫽ 75. Unstandardized estimates are reported. p ⬍ .01. ⴱⴱⴱ p ⬍ .001.

ⴱⴱ

(b ⫽ 0.17, p ⬍ .05). Supervisors’ work-home segmentation behavior was not significantly related to employees’ work-home segmentation behavior. Consequently, Hypothesis 2 was supported: Work-life-friendly role modeling was positively related to employees’ work-home segmentation behavior. Table 4 displays the results for employees’ exhaustion as an outcome variable. In Model 1, supervisors’ emotional work-life support (b ⫽ ⫺.08, p ⬍ .05) and in Model 2, work-life-friendly role modeling emerged as significant negative predictors (b ⫽ ⫺.14, p ⬍ .01). Supervisors’ work-home segmentation behavior was not a significant predictor. Table 5 displays the results for employees’ disengagement as an outcome variable. In Model 1, job involvement (b ⫽ ⫺.10, p ⬍ .001) and supervisors’ emotional work-life support (b ⫽ ⫺.11, p ⬍ .01) emerged as negative predictors of employees’ disengagement. In Model 2, work-life-friendly role modeling (b ⫽ ⫺.09, p ⬍ .05) but not supervisors’ work-home segmentation behavior was a significant negative predictor. In sum, work-life-friendly role modeling was positively related to employees’ well-being, such that employees felt less exhausted and disengaged. Thus, Hypothesis 3 was confirmed.

Testing for Indirect Effects of Supervisors’ Work-Home Segmentation Behavior and Employees’ Work-Home Segmentation Behavior and Well-Being Because we found positive relationships between supervisors’ work-home segmentation behavior and work-life role modeling, as well as between work-life role modeling and employees’ outcome variables (work-home segmentation behavior, exhaustion, disengagement), the question arises whether work-life-friendly role modeling is the linking mechanism and functions as a mediator.3 Therefore, we tested for indirect effects of supervisors’ work-home segmentation behavior on employees’ work-home segmentation behavior and well-being, conducting Sobel tests (Sobel, 1982) and Multilevel SEM. Concerning employees’ work-home segmentation behavior as an outcome variable, Sobel tests revealed an indirect effect of supervisors’ work-home segmentation behavior (Sobel’s z ⫽ 2.04, p ⬍ .05). This finding indicates that work-life role modeling mediates the relationship of supervisors’ workhome segmentation and employees’ work-home segmentation be-

havior. Referring to exhaustion and disengagement as outcome variables, Sobel tests did not reveal significant indirect effects. In the context of two-level data, Multilevel SEM constitutes a more sophisticated way of testing multilevel mediation (Preacher, Zyphur, & Zhang, 2010; Preacher, Zhang, & Zyphur, 2011). To test for the indirect relationships between supervisors’ work-home segmentation behavior and employees’ outcomes via work-life role modeling we also conducted Multilevel SEM, using Mplus 7.0 (Muthén & Muthén, 1998 –2012). Specifically, we entered worklife role modeling as a latent variable. Concerning all three outcome variables, Multilevel SEM showed similar relationships as the Sobel tests. However, concerning employees’ work-home segmentation behavior as an outcome variable, the indirect effect of supervisors’ work-home segmentation behavior via work-life role modeling was only marginally significant (b ⫽ .04, SE ⫽ .02, p ⫽ .075). The slightly smaller effect may be because of the small sample size at Level 2 (75 supervisors), which limits statistical power. Nevertheless, Multilevel SEM supports the proposition that work-life role modeling functions as a mediator between supervisors’ and employees’ work-home segmentation behavior. We also tested the effects of supervisors’ and employees’ gender on our proposed relationships. We tested for main effects, cross-level interactions (supervisors’ gender and work-life role modeling) and effects of specific gender pairings but could not identify any significant gender effects.

Discussion This multisource, multilevel study examined the importance of supervisors as role models within the context of boundary management. Recent research highly emphasizes the importance of supervisors as role models for their employees’ boundary between work and home domains (Hammer et al., 2009; Kirby & Krone, 2002; Regan, 1994). However, to the best of our knowledge our study is the first to examine the relationship between supervisors’ actual work-home segmentation behavior and employees’ perception of work-life role modeling. By our study, we can enrich theory 3 Additional analyses showed that work-life role modeling was not a significant moderator between supervisors’ work-home segmentation and our three outcome variables.

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Table 3 Multilevel Estimates for Models Predicting Employees’ Work-Home Segmentation Behavior Nullmodel

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Estim. Intercept Employees’ job involvement Emotional work-life support Supervisors’ work-home segmentation behavior Work-life-friendly role modeling ⫺2ⴱlog (lh) ⌬ ⫺2ⴱlog ⌬ DF Level 1 Intercept Variance (SE) Level 2 Intercept Variance (SE)

3.85

Model 1

Model 2

SE

t

Estim.

SE

t

Estim.

SE

t

0.07

56.64

3.85 ⫺0.22ⴱⴱⴱ 0.14

0.06 0.05 0.07

63.63 ⫺4.76 1.95

3.86 ⫺0.23 0.06 0.12 0.17ⴱ 556.01 10.41ⴱⴱ 2 0.57 (0.06) 0.06 (0.04)

0.06 0.05 0.06 0.08 0.08

59.86 ⫺4.97 0.91 1.48 2.08

590.62

566.42 24.20ⴱⴱⴱ 2 0.62 (0.06) 0.03 (0.03)

0.67 (0.07) 0.06 (0.05)

Note. N at employee level ⫽ 237. N at supervisor level ⫽ 75. Unstandardized estimates are reported. p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.

ⴱ

building around the construct of boundary management and identify starting points for implementing a work-life-friendly organizational culture within organizations. As boundary theory suggests (Kossek & Lautsch, 2012), we found that work-life-friendly role modeling is positively related to employees’ individual workhome segmentation behavior and well-being. The perception of working with a work-life-friendly role model seems to give employees the feeling that it is socially accepted within the organization to take time away from work and that organizations require an appropriate amount of work-home integration. When working with a work-life-friendly role model, employees were more likely to segment between life domains in terms of taking respites. Also, these employees reported better well-being, in terms of feeling less exhausted and disengaged. Lockwood (2006) suggested that female employees may derive particular benefit from the example of a female supervisor with family duties as a role model. However, our findings do not support these assumptions, as we could not find any significant effects of gender on our study variables and proposed relationships. It may be concluded from our results that it is functionally strategic for organizations to stimulate supervisors’ work-lifefriendly role modeling to benefit their employees’ work-home segmentation behavior, well-being, and their work-life-balance in

a broader sense. Our results are consistent with findings from Hammer and colleagues (2009) who found that family-supportive supervisor behavior, from which role modeling is one subcomponent, decreases employees’ work-home conflict. Employees with a family-supportive role model reported less conflict from workrelated issues entering the home domain. However, Hammer and colleagues (2009) acknowledged that predictors of supervisors’ role modeling as well as underlying mechanisms between supervisors’ support and employees’ boundary management should be identified by further research. Our results show that supervisors’ work-home segmentation behavior is related to work-life role modeling. Supervisors with high work-home segmentation behavior draw a sharper line between life domains. Employees have the feeling that these supervisors are able to meet the needs from both life domains and balance both domains successfully. This finding is highly important, as supervisors’ work-home segmentation is not a behavior that is aimed at employees, compared with the leadership behaviors or emotional work-life support that we also identified as being significantly related to work-life role modeling. Many supervisors are probably not even aware that their work-home segmentation behavior is recognized and has an effect on employees. Our findings are in line with research suggesting that supervisors’ own

Table 4 Multilevel Estimates for Models Predicting Employees’ Exhaustion Nullmodel Estim. Intercept Employees’ job involvement Emotional work-life support Supervisors’ work-home segmentation behavior Work-life-friendly role modeling ⫺2ⴱlog (lh) ⌬ ⫺2ⴱlog ⌬ DF 1 Level 1 Intercept Variance (SE) Level 2 Intercept Variance (SE)

2.17

387.95 0.29 (0.03) 0.02 (0.02)

Model 1

Model 2

SE

t

Estim.

SE

t

Estim.

SE

t

0.04

51.17

2.17 ⫺0.01 ⫺0.08ⴱ

0.04 0.03 0.04

50.38 ⫺0.26 ⫺2.28

2.17 0.00 ⫺0.01 0.01 ⫺0.14ⴱⴱ 373.10 9.66ⴱⴱ 2 0.27 (0.03) 0.02 (0.02)

0.04 0.03 0.04 0.05 0.05

51.21 0.04 ⫺0.14 0.11 ⫺3.05

382.76 5.19 2 0.28 (0.03) 0.02 (0.02)

Note. N at employee level ⫽ 237. N at supervisor level ⫽ 75. Unstandardized estimates are reported. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01.

SETTING A GOOD EXAMPLE

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Table 5 Multilevel Estimates for Models Predicting Employees’ Disengagement Nullmodel

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Estim. Intercept Employees’ job involvement Emotional work-life support Supervisors’ work-home segmentation behavior Work-life-friendly role modeling ⫺2ⴱlog (lh) ⌬ ⫺2ⴱlog ⌬ DF 1 Level 1 Intercept Variance (SE) Level 2 Intercept Variance (SE)

1.89

Model 1

Model 2

SE

t

Estim.

SE

t

Estim.

SE

t

0.04

42.20

1.90 ⫺0.10ⴱⴱⴱ ⫺0.11ⴱⴱ

0.04 0.02 0.04

49.68 ⫺4.97 ⫺2.87

1.90 ⫺0.10ⴱⴱⴱ ⫺0.06 0.01 ⫺0.09ⴱ 329.50 4.31 2 0.22 (0.02) 0.02 (0.01)

0.04 0.02 0.05 0.04 0.04

49.14 ⫺4.34 ⫺1.32 0.31 ⫺2.09

360.71 0.24 (0.03) 0.04 (0.02)

333.82 26.89ⴱⴱⴱ 2 0.23 (0.02) 0.02 (0.01)

Note. N at employee level ⫽ 237. N at supervisor level ⫽ 75. Unstandardized estimates are reported. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.

behavior has an effect on employees, over and above what supervisors directly communicate to employees (Kirby & Krone, 2002). Friedman and Lobel (2003) suggest that “no matter what you say, people look at what you do. And if you’re working 15 hours a day and not taking any vacation, it will be believed that emulating that in the organization is a way to success” (p.88). Our study’s findings support these suggestions: although supervisors’ emotional work-life support also relates to work-life role modeling, supervisors’ work-home segmentation behavior was related to work-life role modeling above and beyond the expressed support. Supervisors’ work-home segmentation behavior was measured as a more distal construct than emotional work-life support, which yields common method variance with work-life role modeling as both constructs were measured in the same employee questionnaire. We also found a significant indirect relationship between supervisors’ work-home segmentation behavior and employees’ workhome segmentation behavior via work-life role modeling, and thus identified work-life role modeling as mediator according to the definition of Hayes (2009); Judd and Kenney (2010) and MacKinnon, Krull, and Lockwood (2000). We can conclude from this result that supervisors’ work-home segmentation behavior represents work-life-friendly role modeling within their work group, which in turn is positively related to their employees’ work-home segmentation behavior. Regarding the well-being of employees, no indirect relationships could be identified. In terms of our findings, it could be suggested that there is no direct relationship, as supervisors’ work-home segmentation behavior and employees’ well-being constitute distal constructs. We can conclude from this result that work-life-friendly role modeling is not the connecting mechanism between supervisors’ work-home segmentation behavior and employees’ well-being.

Theoretical Implications Our results suggest that social learning (Bandura, 1977) and recovery (Meijman & Mulder, 1998) theory can be useful frameworks to describe organizational influence on employees’ workhome segmentation behavior. Many organizations wish to implement a work-life-friendly organizational culture. Research suggests that only implementing organizational-work-life benefits

is not enough (Dikkers et al., 2007; Kirby & Krone, 2002; Lewis, 1997). Regan (1994) suggested that cultural change would only come about when supervisors also embrace work-life values, both in what they say and in what they do. Our study brings up initial evidence for this assumption, and shows that supervisors with high work-home segmentation behavior constitute work-life-friendly role models. Our study also contributes to boundary theory and shows that elements from the organizational environment, in terms of work-life role models, are related to employees’ work-home segmentation behavior. In line with previous research, our results show that individual predictors, such as employees’ own job involvement (Hecht & Allen, 2009), are also related to work-home segmentation behavior. Additionally, correlations show a significant positive correlation between employees’ disengagement and work-home segmentation behavior (r ⫽ .17). Disengaged employees experience negative attitudes toward their work (Demerouti et al., 2001) and could therefore be more likely to implement a high work-home boundary to minimize negative work-home spillover. However, this explanation should be further tested in future research. Furthermore, future studies should focus on examining individual and organizational predictors together and how they interact with each other. For example, Kossek and Lautsch (2012) suggested that the boundary management of employees might be a function of individual preferences in relation to the organizational context in which these styles are enacted. Referring to our study, employees’ individual preference for segmentation may be a moderator in the relationship between work-life-friendly role modeling and employees’ outcomes. Employees who prefer segmentation between life domains may particularly benefit from a work-life-friendly role model and experience a work-life-unfriendly role model as a source of stress (Kossek & Lautsch, 2012). Furthermore, based on our results regarding supervisors as role models in the context of boundary management, future research should further investigate the role of other domain members, such as the role of spouses from the home domain or the role of colleagues from the work domain (Park et al., 2011). Research also suggests that organizational climate that is supportive of employees’ work-life-balance affects employees’ workhome segmentation behavior. For example, Thompson and col-

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leagues (1999) showed that a work-life-friendly climate fosters employees’ use of work-life benefits (e.g., telework) and decreases work-life conflict. In terms of work-life role modeling, the importance of climate supporting employees to deal with work-life issues is promising. It could be suggested that employees’ particularly imitate a role model’s behavior when this is in line with the work-life climate. Whether supervisors feel affected by climate in terms of their own work-home segmentation behavior and which behaviors of organizational actors shape the climate would be important additional research questions within this context. In line with previous research, it can be suggested that work-life climate affects both supervisors’ and employees’ work-home segmentation behavior (Thompson et al., 1999).

Practical Implications Our findings are highly important with respect to practical implications. Organizations should keep in mind that because of their status supervisors can be powerful change agents in making workplaces more work-life-friendly. Supervisors can act as gatekeepers for the availability and implementation of organizational work-life benefits and as change agents for informal supportive organizational cultures. Therefore, organizations may wish to enable their supervisors to set a positive example in the context of boundary management. Organizations should make sure that supervisors are not expected to be always available, and have opportunities to switch off when at home. Supervisors’ high workhome segmentation behavior represents work-life-friendly role modeling, which in turn is positively related to employees’ workhome segmentation behavior. Also, work-life-friendly role modeling was positively related to employees’ well-being. Therefore, efforts to enhance supervisors’ work-home segmentation behavior would probably not only benefit supervisors themselves but also the system as a whole. For example, Burke (2001) emphasizes that it is important that organizations stop taking “pride in developing cultures where long work hours and sacrifices in nonwork lives are seen as requirements for success and advancement” (p. 639). Keeping a boundary between work and home allows switching off from work demands, recovery and continued motivation in the long run (Hecht & Allen, 2009; Park et al., 2011). However, responsibility for employees’ well-being and worklife balance in a broader sense should not be exclusively attributed to supervisors. Organizations should also take additional steps to foster their employees’ well-being and work-life balance, for example by avoiding negative career consequences in terms of private obligations and also by limiting organizational time demands (Thompson et al., 1999).

Limitations and Future Research Any study such as ours has some limitations, and this must be taken into account when considering the results. One limitation of our study is the use of a cross-sectional design in which causal interpretations are limited. For example, we cannot ensure from our study design whether there really is a downward process from supervisors on employees or whether the effect is vice versa. Although this study provides multilevel findings of supervisors’ behavior on work groups’ role modeling perception that are theoretically plausible (Weiss, 1978), we recommend the use of a

longitudinal design in future research to confirm the current finding in more detail. For example, the effect could be more precisely studied in a sample of job beginners who are having their first contact with organizational boundary management values. Second, we focused exclusively on the supervisor-employee relationship in our study, although there may be other social influences on employees within the organizational context. For example, Park and colleagues (2011) showed that a social norm within the work group that is also shaped by coworkers affects employees’ detachment at home. Still, in focusing on the supervisor-employee relationship it is neither suggested that the supervisor is the only potential role model nor that the influence process occurs only in a downward direction. However, if role modeling does occur in organizations, the supervisor-employee relationship is an interaction in which this is likely to be found and is therefore a good starting point (Weiss, 1978). Third, although we could confirm a positive relationship between supervisors’ work-home segmentation behavior and employees’ shared work-life role modeling perception, we cannot conclusively say which specific behaviors of supervisors’ workhome segmentation (e.g., working after hours, received correspondence) shape employees’ perception. As we controlled for supervisors’ emotional work-life support in our analyses, we ruled out one alternative influence on work-life role modeling. Our study is one first step to enhance the understanding of work-life role modeling in the context of work-home segmentation behavior and should stimulate further research in this field. Whereas our study focused on whether supervisors’ work-home segmentation behavior is related to employees’ work-life role modeling perception at all, future research should continue our effort by directly asking employees about crucial signals of supervisors’ work-home segmentation behavior. Also a comparison with supervisors’ own perspective on visible indicators would be interesting to find out how much awareness supervisors have concerning their role modeling effect. Furthermore, it has to be taken into account that supervisors’ work-home segmentation is one important but probably not the only modeling behavior that shapes employees’ perception of having a work-life-friendly role model. Therefore, further modeling behaviors on the job as well as further confounding variables above emotional work-life support should be examined. Thereby, the understanding of the relationship between supervisors’ work-home segmentation behavior and work-life role modeling can be expanded. In addition, our sample consisted of employees and supervisors from the health and service sector. Most of the employees who participated were female. Thus, there may be concerns about the generalizability of our study. However, additional analyses did not reveal relations between employees’ and supervisors’ gender and our study’s predictor and outcome variables. Furthermore, we had to drop 149 employees as they could not be matched with supervisor data that introduces the risk of a systematic sample bias. However, t-tests showed that employees whose supervisors had participated did not significantly differ from those employees whose supervisors had not participated (with the exception of disengagement). Also, our dropout is still in the range of what Nulty (2008) describes as being typically found in paper-based settings. Nevertheless, future research should replicate our findings in a more representative sample to validate our findings.

SETTING A GOOD EXAMPLE

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Received November 29, 2013 Revision received August 4, 2014 Accepted August 6, 2014 䡲

Showcase your work in APA’s newest database. Make your tests available to other researchers and students; get wider recognition for your work. “PsycTESTS is going to be an outstanding resource for psychology,” said Ronald F. Levant, PhD. “I was among the first to provide some of my tests and was happy to do so. They will be available for others to use—and will relieve me of the administrative tasks of providing them to individuals.”

Visit http://www.apa.org/pubs/databases/psyctests/call-for-tests.aspx to learn more about PsycTESTS and how you can participate. Questions? Call 1-800-374-2722 or write to [email protected].

Not since PsycARTICLES has a database been so eagerly anticipated!