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. Author manuscript; available in PMC: 2014 Jun 1.
Published in final edited form as: Int J Hosp Manag. 2012 Oct 11;33:273–281. doi: 10.1016/j.ijhm.2012.09.003

Understanding Work-Family Spillover in Hotel Managers

Katie M Lawson 1, Kelly D Davis 1, Ann C Crouter 1, John W O’Neill 2
PMCID: PMC3718488  NIHMSID: NIHMS411505  PMID: 23888092

Abstract

The present study examined the experience of work-family spillover among 586 hotel managers (HMs) working in 50 full-service hotels throughout the U.S. Work-family spillover occurs when behaviors, moods, stresses, and emotions from work spill over into family. We first investigated which hotel managers were more likely to experience spillover and stressful work conditions based on their life circumstances (gender, parental status, age, decision-making latitude at work). Second, we investigated which work conditions (hours worked per week, organizational time expectations, emotional labor, and permeable boundaries) predicted more work-family spillover. Women, employees without children at home, and younger adults experienced the highest levels of negative work-family spillover. Work conditions, particularly organizational time expectations, put HMs at risk for experiencing more negative and less positive work-family spillover. The results provide evidence that modifying certain work conditions in the hotel industry may be helpful in improving the quality of HMs’ jobs and retention.

Keywords: work-family spillover, organizational time expectations, emotional labor, permeable boundaries

1. Introduction

In 2011, the leisure and hotel industry experienced the highest voluntary turnover rate among U.S. industries, with 449,000 employees (3.4%) quitting during the month of August alone (Bureau of Labor Statistics, 2011). Turnover costs (e.g., advertising for open positions, training new employees) are estimated to cost the hotel industry approximately $10,000 per lost manager (Tracey & Hinkin, 2008). The higher turnover rate is likely due in part to the stressful work conditions of businesses open 24 hours per day, 7 days per week (e.g., long hours, on-call hours). Because of these conditions, hotel managers are susceptible to elevated and prolonged stress both at work and at home. In fact, research suggests that stress and emotions at work can “spill over” into home life, and that this “spillover” may be associated with relatively high turnover rates in the hotel industry (O’Neill et al., 2009). Thus, research is needed to better understand which subgroups of hotel managers (HMs) experience work to family spillover, along with the work conditions and life circumstances that are associated with spillover.

The present research had three goals. First, the present study sought to identify who experiences stressful work conditions and the spillover of stress and enjoyment from work into home life among HMs by examining their association with the following life circumstances: age, decision-making latitude at work, gender, and parental status. Second, the present study investigated which stressful work conditions common among HMs (i.e., hours worked/week, organizational time expectations, emotional labor, and permeable boundaries) predict negative or positive spillover from work into home life, controlling for life circumstances. Third, the study identified potential subgroups for whom these stressful work conditions may be particularly problematic by examining gender, parental status, and the combination of gender and parental status (i.e., being a mother, father, childless male, or childless female) as potential moderators of the linkages between work conditions and spillover.

2. Literature review

2.1 Work-Family Spillover

Work-family spillover occurs when behaviors, moods, stress, and emotions from work are transferred to the family domain (Mennino, Rubin, & Brayfield, 2005). Conceptualizations of spillover theory hold that there are no boundaries between work and family life. Rather, people often bring their attitudes, behaviors, and emotions from one domain into the other (Zedeck & Mosier, 1990). Grzywacz and Marks (2000b) indicate that there are four distinct work-family spillover experiences: negative and positive spillover from work to family and family to work.

Most research on the work-family interface has focused on negative spillover between the two domains. This type of research takes a conflict perspective which assumes that individuals in multiple roles often experience stress due to a lack of time and energy to fulfill the obligations in all of the roles (Zedeck & Mosier, 1990). Past research indicates that negative work-family spillover is associated with poorer mental and physical health (e.g., Grzywacz, 2000). However, more recently scholars have begun to focus on positive spillover that can occur between work and family. This perspective is based on the expansionist hypothesis, which argues that the advantages of multiple roles outweigh the disadvantages (e.g., Greenhaus & Powell, 2006). Greenhaus and Powell (2006) argue that there are three ways in which multiple roles can produce positive outcomes: 1) multiple roles can have additive effects on well-being; 2) roles can buffer the individual from stress from other roles; and 3) experiences in one role can lead to positive outcomes and experiences in another role. Based on recommendations in several recent reviews (e.g., Frone, 2003), the present study investigated both positive and negative spillover from work to family.

2.2 Life Circumstances

2.2.1 Age/Decision-Making Latitude

Research indicates that as people age, negative work-family spillover decreases and positive work-family spillover increases (Grzywacz, Almeida, & MacDonald, 2002). As demonstrated by Martinengo, Jacob, and Hill (2010), age is likely associated with work-family spillover in part due to the changing role demands associated with different ages (e.g., younger ages are associated with younger children at home). Increased age is also associated with more decision-making latitude at work, which refers to the discretion an employee has to make job-related decisions or apply skills to the job (e.g., Zacher & Frese, 2009). Job demands and decision-making latitude interact to predict health and well-being. For example, when job demands are high and decision-making latitude is low (i.e., workers are unable to adequately deal with the job demands), health and well-being are at risk (Karasek et al., 1988).

2.2.2 Parental Status/Gender

Mulvaney and colleagues’ (2007) model of work-family dynamics of hotel managers asserts that family factors influence work-family issues for hotel managers. Gender and parental status are two background characteristics commonly researched in regard to work-family spillover. Findings on gender differences in work-family spillover (e.g., Grzywacz et al., 2002; Grzywacz & Marks 2000b; Williams & Alliger, 1994) and differences in work-family spillover between parents versus non-parents (e.g., Grzywacz et al., 2002; Keene & Quadagno, 2004; Kinnunen, Feldt, Geurts, & Pulkkinen, 2006) are inconclusive.

The mixed results may be due to the fact that gender and parental status matter in combination; that is, mothers, fathers, females without children, and males without children likely experience work and family differently. Although a majority of men and women with children under the age of 18 participate in the labor force (U.S. Bureau of Labor Statistics, 2007), women are typically responsible for more household work and childcare responsibilities (including taking care of child-related emergencies such as sick children; Bianchi & Milkie, 2010; Coltrane, 2000; Hochschild, 1989), whereas fathers typically work longer hours for pay than mothers (Bianchi, Robinson, & Milkie, 2006). Research investigating the combination of gender and parental status on work-family conflict (a related construct to spillover) found that working mothers reported more work-family conflict than working fathers, despite the fact that working mothers also reported working fewer hours and working in a culture more supportive of family life (Hill, 2005).

2.3 Work Conditions

2.3.1 Work Hours per Week

The more hours employees work per week, the more they report experiencing work-family conflict (e.g., Frone, Yardley, & Markel, 1997; Gutek, Searle, & Klepa, 1991; Major, Klein, & Ehrhart, 2002; Maume & Houston, 2001; Thompson, Beauvais, & Lyness, 1999; Van der Hulst & Geurts, 2001). Using data from the National Survey of Midlife Development in the United States (MIDUS), Grzywacz and Marks (2000b) found that working less than 20 hours per week was associated with less negative work-family spillover, whereas working 45 or more hours per week was associated with more negative work-family spillover. In addition, Grzywacz and Marks (2000b) found that longer work hours were associated with more positive work-family spillover. Hours worked per week was included in the present study not only because evidence suggests it is related to work-family spillover, but also because hotel managers have reported that working long hours is one of the most stressful aspects of working in the hotel industry (Cleveland et al., 2007). In fact, working long hours (and thus not having enough time to spend with family) may result in hotel management turnover (Stalcup and Pearson, 2001).

2.3.2 Organizational Time Expectations

Organizational time expectations refer to employees’ beliefs about the time organizations expect their employees to put in on the job. High organizational time expectations are associated with more work-family conflict, less affective commitment to an organization, and higher turnover intentions for employees (Ahmad & Omar, 2010; Major et al., 2002; Thompson et al., 1999). Organizational time expectations are related to the idea of “paying your dues,” which is a common concept in the hotel industry (Mulvaney et al., 2007). Because of this, it was included in the study as a predictor of work-family spillover.

2.3.3 Emotional Labor

Hocschild (1983) defines emotional labor as the “management of feeling to create a publicly observable facial and bodily display” (p. 7). Emotional labor, which is common in service industry occupations, is comprised of two components: deep and surface acting. Deep acting refers to the modification of actual feelings, whereas surface acting refers to the modification of the expression of feelings (e.g., smiling when unhappy while interacting with a hotel guest). Higher levels of emotional labor on the job is related to more health problems (e.g., Panagopoulou, Kersbergen, & Maes, 2002), burnout, and work-family interference/conflict (e.g., Montgomery, Panagopolou, Wildt, & Meenks, 2006; Seery, Corrigall, & Harpel, 2008). Surface-acting emotional labor is more relevant to the work environment, especially among workers in the service industry who often must modify emotions around customers. In addition, surface-acting emotional labor was reported in a qualitative study of hotel managers as a common complaint (Cleveland et al., 2007).

2.3.4 Permeable Boundaries

Permeable boundaries refer to the lack of segmentation or the degree of fluidity between the domains of work and family. Boundary theory indicates that boundaries between life domains (e.g., work and family) can range from highly segmented to highly integrated (Ashforth, Kreiner, & Fugate, 2000). Highly integrated roles can often lead to the blurring of roles, making boundary creation and/or maintenance quite difficult. The concept of permeable boundaries is relatively new in hospitality research. During the pilot study for the present study, hotel managers discussed how new technology (e.g., cell phones, pagers) has led to increased availability of employees, even when at home (Cleveland et al., 2007). The managers commented on the frustrations that arise due to interruptions at home and having to be available at all times for hotel needs. Because this was a common complaint among hotel managers, the present study investigated this work condition as a possible predictor of work-family spillover.

3. Hypotheses

In sum, the present study had three main research questions: 1) Who experiences stressful work conditions (hours worked/week, organizational time expectations, emotional labor, and permeable boundaries) and negative and positive work-family spillover among HMs? 2) How are HMs’ work conditions associated with their perceptions of both negative and positive work-family spillover? 3) Do gender and/or parental status moderate the association between work conditions and spillover? We addressed these questions using data from HMs from 50 hotels across the United States. Based on the past research described previously, we propose the following hypotheses:

  • Hypothesis 1a. Older age will be associated with less negative spillover, more positive spillover, and fewer stressful work conditions.

  • Hypothesis 1b. More decision-making latitude will be associated with less negative spillover, more positive spillover, and fewer stressful work conditions.

  • Hypothesis 1c. Due to the inconsistent research investigating the links between gender and parental status with work-family spillover, no specific predictions were made about the relationship between gender and parental status with negative and positive spillover. However, the analyses will examine the associations between gender/parental status with work-family spillover by examining gender and parental status both separately and in combination (i.e., being a mother, father, childless female, and childless male).

  • Hypothesis 1d. It is predicted that mothers will experience fewer stressful work conditions than fathers, childless females, and childless males.

  • Hypothesis 2a: Working longer hours will be associated with more negative and more positive work-family spillover.

  • Hypothesis 2b. Higher organizational time expectations will be related to more negative work-family spillover. No prediction was made about the relationship between organizational time expectations and positive work-family spillover because previous research has not been conducted on which to base a prediction.

  • Hypothesis 2c. Higher levels of surface emotional labor will be associated with more negative work-family spillover. No prediction was made regarding the relationship between positive spillover and surface emotional labor due to the lack of past research on the topic.

  • Hypothesis 2d. Higher boundary permeability will be associated with more negative work-family spillover. No prediction was made regarding the relationship between positive spillover and permeable boundaries due to a lack of previous research.

  • Hypothesis 3. Because of the increased demands at home for parents and women, it is predicted that gender and parental status may moderate the associations between work conditions and spillover.

4. Methods

4.1 Procedures/Participants

Data was originally collected to explore work-family issues among workers in the U.S. hotel industry. We undertook all possible efforts to make sure that hotels were included from all U.S. regions and to include properties representing major chains as well as independents. In addition, full-service hotels were recruited in order to obtain numerous departmental managers within a hotel. Initial contact with the President of the American Hotel & Lodging Association and representatives with municipal hotel associations in San Francisco, Los Angeles, Denver, Kansas City, Saint Louis, Chicago, Orlando, Atlanta, Washington, DC, and New York led to the initial identification of hotels. Based on these referrals, 65 out of the 121 hotel general managers (GMs) that were telephoned (53.7%) agreed to participate. After the GMs completed an in-person interview, permission was obtained from the GM for the research team to contact hotel managers (HMs).

A total of 869 randomly selected departmental HMs were telephoned. 588 (67.7%) HMs completed the survey, 139 (16.0%) HMs could not be reached or did not call back, 12 (1.4%) could not be reached because the wrong telephone number had been provided and the correct number could not be found, 81 (9.3%) refused to participate, 45 (5.2%) were no longer a manager, 2 (.2%) did not speak English, and 2 (.2%) never completed the full interview. Partial interviews were not included in the analyses. The final sample consisted of 588 HMs (288 females, 300 males) from 50 full-service hotels across the United States, including hotels from Pennsylvania (4% of the sample), New Jersey (8%), Washington, D.C. (4%), Virginia (6%), Missouri (14%), Kansas (2%), Illinois (4%), California (18%), Florida (16%), Georgia (8%), and Colorado (16%). On average, these hotels had a mean of 530 rooms (range: 152 to 1,908 rooms), 388 employees (range: 105 to 1,000 employees), and 52 hotel managers (range: 6 to 200 managers). Two participants were removed from the dataset because they reported working 10 hours or less per week, leaving a total of 586 participants (288 females, 298 males). Trained survey research personnel conducted telephone surveys with the HMs using computer-assisted telephone interviewing (CATI) procedures. The telephone survey was reviewed by graduate students/faculty (in and outside hospitality) and a full-time research director for the project who previously had experience as a hotel GM. In addition, the survey was created based on advice from experts outside the university. After completing the structured interview, HMs received $20 for their participation.

Participants ranged in age from 21 to 64 years old, with an average age of 37.9 years (SD= 9.2). The majority were Caucasian (67.1%), had at least a college degree (63.6%) and were currently married or living with a romantic partner (76.9%). Approximately 43.9% currently had children living at home. The HMs worked in various departments, including rooms (20.3%), food and beverage (32.1%), marketing (22.6%), accounting (9.2%), engineering (3.9%), human resources (5.8%), recreation (1.9%), and other (4.1%).

4.2 Measures

4.2.1 Work-Family Spillover

The work-family spillover scale (consisting of 8 items) from the National Survey of Midlife Development in the United States (MIDUS; Grzywacz & Marks, 2000b) was used to assess work-family spillover. Four items (e.g., “Stress at work makes you irritable at home”) were used to assess negative work-family spillover and four items (e.g., “The skills you use on your job are useful for things you have to do at home”) were used to assess positive work-family spillover. Participants responded to items using a 5-point numerical rating scale (1= Never, 5= All the Time). Item responses were summed to create total scores. One item was removed from the positive work-family spillover scale due to low correlations with the other three items. Cronbach’s alpha for the present study was .80 for negative work-family spillover and .61 for positive work-family spillover.

4.2.2 Life Circumstances

Four life circumstances were assessed in the current study: age, decision-making latitude at work, gender, and parental status. Participants indicated their age at the time of the survey. To assess decision-making latitude, participants rated their agreement with seven items (Karasek, 1979; e.g. “You have control over what happens on your job”) using a 4-point numerical rating scale (1=Strongly Disagree, 4=Strongly Agree). One of Karasek’s original 8 items was dropped due to low inter-item correlations. Items were averaged to create a total decision-making latitude score, with higher scores indicating greater decision-making authority (Cronbach’s alpha= .69). Gender was coded a 0 for female and 1 for male. For the current analyses, participants were considered a parent if they had children currently living at home because home demands are likely the greatest for this group (0= No children at home, 1= Children at home).

4.2.3 Stressful Work Conditions

Four items selected from Thompson et al.’s (1999) work and family culture scale were used to assess organizational time expectations (e.g., “Managers in your hotel are often expected to take work home at night and/or on weekends”). The four items were chosen because they were believed to be pertinent to the hotel industry. Participants rated their agreement with items using a 5-point Likert rating scale (1=Strongly Disagree, 5=Strongly Agree). Item responses were averaged to create an overall score. For the present study, the scale was found to be internally consistent (Cronbach’s alpha= .81).

Surface-acting emotional labor was assessed using Brotheridge & Lee’s (1998) Emotional Labor Scale (the surface-acting subscale). This subscale consists of three items (e.g., “On an average day at work, how frequently do you resist expressing your true feelings?”). Participants responded to items using a 5-point numerical rating scale (1=Never, 5=Always). Items were averaged to create a total emotional labor (surface acting) score. Previous studies suggest that it is a reliable and valid scale (Brotheridge & Lee, 2003), and with Cronbach’s alpha of .72, it is in this sample as well.

Four items were created (based on the results of a pilot study) to assess the permeability of the boundaries between work and home life. Items assessed whether participants are called into work at unexpected times, receive pages or calls from work at home, and never feel completely “off work.” Items were averaged to create an overall score (Cronbach’s alpha= .80).

4.3 Analyses

To describe who experiences stressful work conditions (hours worked per week, organizational time expectations, emotional labor, and permeable boundaries) and work-family spillover (Aim 1), two separate analyses were conducted. First, correlations between age, decision-making latitude at work, gender, and parental status with work conditions and spillover were examined. Second, two-way ANOVAS were used to assess whether work conditions and spillover differed as a function of the combination of gender and parental status.

For Aim 2, to assess the associations between work conditions and spillover, data were analyzed using MLM (i.e., Proc Mixed) in SAS. This approach takes into account the “nested” structure of the data (i.e., 586 managers were nested within 50 hotels). Our design included two levels: individual level (Level 1) and hotel-level (Level 2). Because raw variable scores contain both individual-level (Level 1) and hotel-level (Level 2) components, scores were recoded to separate these components (Hox, 2010). For example, if an individual reports working 60 hours per week, we do not know if it is because the individual works a lot of hours (relative to other individuals) or if all people at that hotel work a lot of hours. To assess Level 1 effects, continuous variables (hours worked per week, organizational time expectations, surface emotional labor, and permeable boundaries) were first grand-mean centered to create meaningful zeroes, then hotel-mean centered (i.e., the hotel mean for each variable was subtracted from each participant’s score for each variable). This centered variable represents the individual level component (Level 1) because it removes the hotel-level component (Level 2) by subtracting the hotel mean from each individual score. In addition, a hotel proportion was created for both dummy coded variables (gender and parental status) to separate individual level and hotel-level components. For each participant, this hotel proportion was subtracted from the dummy variables to create a variable that included only individual-level (Level 1) effects. Thus, the newly created hotel stressor, gender, and parental status variables only included between-person (Level 1) effects.

Model 1 (the main effects model) was used to assess the associations between work conditions and negative work-family spillover (Aim 2). For Model 1, work conditions (i.e., hours worked per week, organizational time expectations, emotional labor, and permeable boundaries) and life circumstances (i.e., age, decision-making latitude at work, gender, parental status, and the interaction between gender and parental status) were entered as predictors of negative spillover.

Models 2–5 were used to address Aim 3 (the moderation analyses). For Models 2–5, in addition to the main effects (entered as predictors in Model 1), interactions between each work condition and life circumstances (gender, parental status, and combined gender and parental status) were added to predict negative spillover. More specifically, Model 2 included interactions between life circumstances with hours worked per week, Model 3 included interactions between life circumstances with organizational time expectations, Model 4 included interactions between life circumstances with emotional labor, and Model 5 included interactions between life circumstances with permeable boundaries. Models were duplicated for positive work-family spillover (Models 6–10). In other words, Model 6 investigated the associations between work conditions and positive work-family spillover (the main effects model), whereas Models 7–10 included the moderation analyses.

5. Results

5.1 Who is Experiencing Stressful Work Conditions and Work-Family Spillover?

Table 1 provides descriptive statistics for life circumstances (age, decision-making latitude, gender, and parental status), work conditions, and spillover for the total sample and Table 2 provides correlations among these variables. Results of two-way ANOVAS can be seen in Table 3. Compared to men, women reported significantly fewer hours worked per week (F(1, 584)= 17.90, p < .001), less emotional labor (F(1, 584)= 6.77, p = .01), less permeable boundaries (F(1, 584)= 28.30, p < .001), and more negative work-family spillover (F(1, 584)= 4.56, p < .05). Compared to individuals without children living at home, parents with children living at home reported significantly fewer hours worked per week (F(1, 584)= 4.59, p < .05), fewer organizational time expectations (F(1, 583)= 7.35, p < .01), less emotional labor (F(1, 584)= 10.22, p < .001), less permeable boundaries (F(1, 584)= 5.57, p < .05), more decision-making latitude (F(1, 584)= 3.96, p < .01), and less negative work-family spillover (F(1, 584)= 10.29, p = .001). A significant interaction between gender and parental status emerged only for hours worked per week (F(1, 584)= 4.54, p < .05. Tukey-Kramer follow-up tests revealed that mothers reported working significantly fewer hours per week (M= 53.2, SD =7.4) compared to fathers (M= 57.9, SD = 9.4, p < .001), childless women (M= 56.4, SD = 8.1, p < .05), and childless men (M= 57.9, SD = 9.9, p < .001). There were no significant differences among the latter three groups.

Table 1.

Descriptive Statistics

Mean (SD)
or N(%)		 Minimum Maximum Range
Work-Family Spillover
Positive Spillover     8.59 (2.36)   3.00   15.00 12.00
Negative Spillover   12.19 (3.22)   4.00   20.00 16.00
Work Conditions
Hours/Week   56.56 (8.97) 32.00 110.00 78.00
Time Expectations     2.89 (1.08)   1.00     5.00   4.00
Emotional Labor     2.52 (.82)   1.00     5.00   4.00
Permeable Boundaries     2.68 (1.16)   1.00     5.00   4.00
Life Circumstances
Age   37.86 (9.18) 21.00   64.00 43.00
Decision-Making Latitude     3.28 (.43)   1.57     4.00   2.43
Number (and %) Male 298 (50.85%)  N/A    N/A  N/A
Number (and %) Parents 257 (43.86%)  N/A    N/A  N/A
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Table 2.

Correlations between spillover, work conditions, and life circumstances

1 2 3 4 5 6 7 8 9 10
1 Negative Spillover 1.00
2 Positive Spillover −.19** 1.00
3 Hours/Week .23** .02 1.00
4 Time Expectations .51** −.17** .27** 1.00
5 Emotional Labor .38** −.25** .06 .36** 1.00
6 Permeable Boundaries .40** −.07 .32** .49** .26** 1.00
7 Gender −.10* .04 .15** .04 .10* .21** 1.00
8 Parental Status −.14** .06 −.07 −.11* −.15** −.07 .11* 1.00
9 Age −.26** .03 −.02 −.11* −.16** −.08 .09* .27** 1.00
10 Decision-Making Latitude −.14** .26** .12* −.13* −.23** .04 .04 .13* .19** 1.00
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Note.

*

p< .05,

**

p< .001

Table 3.

Mean work-family spillover, work conditions, and decision-making latitude by gender and parental status

Men Women Parents Non-Parents
Negative Spilloverab 11.87 12.44 11.73 12.58
Positive Spillover   8.69   8.55   8.74   8.49
Hours/Weekabc 57.92 54.79 55.56 57.15
Time Expectationsb   2.94   2.82   2.76   3.00
Emotional Laborab   2.59   2.42   2.37   2.64
Permeable Boundariesab   2.92   2.41   2.55   2.77
Decision-Making Latitudeb   3.29   3.27   3.34   3.23
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Note.

a

Significant gender differences,

b

Significant differences between parents and non-parents,

c

Significant interaction between gender and parental status

5.2 Do Work Conditions Predict Work-Family Spillover?

To estimate the proportion of variance in work-family spillover attributable to between-hotel versus within-hotel effects, we calculated intraclass correlation coefficients (ICCs). The ICC is used to identify the proportion of the variability that exists at the hotel-level relative to the total variability in the data (Hoop, 2010). The ICCs were .015 and .021 for positive and negative work-family spillover, respectively, indicating that between-hotel variance accounted for only between 1.5% and 2.1% of the variance in work-family spillover.

5.2.1 Negative Work-Family Spillover

Table 4 provides the estimates for the models investigating negative work-family spillover. Gender, age, and all of the work conditions were significant predictors of negative work-family spillover (Model 1). Younger ages (β= −.05, p < .001), working more hours per week (β= .04, p < .01), higher organizational time expectations (β= .97, p < .001), higher emotional labor (β= .74, p < .001), and more permeable boundaries (β= .55, p < .001) were associated with greater negative work-family spillover. In addition, women experienced significantly more negative work-family spillover than men (β= −1.00, p < .001), whereas individuals with children living at home did not differ significantly in reports of negative work-family spillover, relative to individuals without children living at home (β= .04, ns).

Table 4.

Results of the multilevel models (Models 1 and 6) examining work conditions and life circumstances as predictors of spillover

Model 1:
Negative Spillover 		Model 6:
Positive Spillover
B (SE) B (SE)
Intercept 12.27 (.17)** 8.61 (.11)**
Life Circumstances
Age     −.05 (.01)**   .00 (.01)
Decision-Making Latitude     −.21 (.28) 1.03 (.25)**
Gender   −1.00 (.23)**   .16 (.20)
Parental Status       .04 (.24) −.01 (.21)
Gender X Parental Status     −.34 (.49) −.44 (.42)
Work Stressors
Hours/Week       .04 (.01)* −.00 (.01)
Time Expectations       .97 (.13)** −.24 (.11)*
Emotional Labor       .74 (.15)** −.47 (.14)**
Permeable Boundaries       .55 (.12)**   .09 (.10)
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Note.

*

p< .05,

**

p< .001

We ran separate analyses to assess life circumstances as moderators of the association between each work condition with negative work-family spillover (Models 2–5). The results indicated that parental status moderated the association between work hours and negative spillover (β= .06, p < .05). For individuals with children at home, longer work hours were associated with significantly more negative work-family spillover (β= .10, p = .001). In contrast, for individuals without children at home, there was no association between work hours and negative work-family spillover (β= −.01, ns). In addition, parental status moderated the association between emotional labor and negative spillover (β= −.61, p < .05). For individuals with children at home, emotional labor was not significantly associated with negative spillover (β= .13, ns). However, for individuals without children at home, emotional labor was associated with more negative spillover (β= 1.18, p < .001). Results of Models 2–5 can be seen in Appendix 2.

5.2.2 Positive Work-Family Spillover

Table 4 also summarizes the estimates for the model investigating the correlates of positive work-family spillover. Fewer variables predicted positive work-family spillover, as compared to negative work-family spillover (Model 6). Greater control over work (β= 1.03, p < .001), lower organizational time expectations (β= −.24, p < .05), and less emotional labor (β= −.47, p = .001) were associated with higher levels of positive work-family spillover. There was no evidence that the interaction between gender and parental status moderated the links between the work conditions and positive work-family spillover (Models 7–10). Results of Models 7–10 can be seen in Appendix 2.

5.3 Follow-Up Analyses

Results of the analyses indicated that women and HMs with children at home reported fewer stressful work conditions. It is possible that these groups, which typically have more family responsibilities (Bianchi & Milkie, 2010), may be choosing to work in jobs with fewer demands in an effort to balance work and family. To explore this possibility, follow-up chisquare analyses were conducted assessing the distribution of parents and women in different types of departments. Department positions were grouped in two ways. First, participants were classified as working in line (e.g., sales, restaurant and beverage, event management) or staff positions (e.g., human resource, financing, director of engineering) because individuals working in staff positions are more likely to have a traditionally “normal” schedule. Thus, the chi-square analyses allowed us to determine if parents and/or women cluster in jobs with more “normal” schedules (possibly in an effort to better balance work and family). Second, participants were classified as working in either back-of-the-house (e.g., sales, human resources) or front-of-the house positions (e.g., guest services, director of operations, restaurant) because front-of-the-house positions require more interactions with customers (and thus more emotional labor) than back-of-the-house positions. This allowed us to explore whether parents and/or women were clustered into occupations requiring less emotional labor.

Results of the follow-up analyses suggest that women and parents may be choosing jobs with fewer demands. Women were more likely to work in back-of-the-house occupations than men (59.1% of women v. 38.7% of men; χ2(1, N = 578) = 24.05 p < .001). However, there were not significant differences in the gender distribution among staff versus line positions. Parents were more likely than non-parents to work in staff positions (19.2% of parents v. 12.4% of nonparents; χ2(1, N = 578) = 5.11 p < .05), but were equally likely to work in back-of-the-house versus front-of-the-house positions.

6. Discussion

The present study investigated the experience of negative and positive work-family spillover among HMs. More specifically, the study investigated subgroups of HMs most likely to experience work-family spillover, in addition to stressful work conditions as predictors of spillover. Results indicated that stressful work conditions put HMs at risk for experiencing more negative and less positive work-family spillover, and that certain subgroups of HMs experienced higher levels of negative spillover. These findings, along with strengths, weaknesses, and implications of the research, are discussed in more detail below.

6.1 Who is Experiencing Work-Family Spillover and Stressful Work Conditions?

The present study found that women and HMs with children at home reported fewer stressful work conditions, suggesting that groups with more demands outside of work (e.g., Bianchi and Milkie, 2010) may be choosing jobs with fewer demands, perhaps in an effort to balance work and non-work roles. These results are partially supported by our follow-up analyses, which indicated that parents with children at home were more likely to work in departments with more traditionally “normal” work schedules and women were more likely to work in departments requiring less contact with customers (and thus less emotional labor).

Although HMs with children reported less negative work-family spillover than HMs without children (possibly due in part to fewer job demands), women still reported more negative work-family spillover than men. This result is consistent with past studies indicating that women report more negative work-family spillover, despite working in occupations with work characteristics that are relatively family-friendly (e.g., Grzywacz, Almeida, & McDonald, 2002; Hill, 2005). It is interesting to note that mothers did not report more negative or less positive work-family spillover than fathers, childless females, or childless males. There are a number of possible reasons why mothers did not report more negative work-family spillover, despite the fact that mothers often experience the greatest family demands (Bianchi & Milkie, 2010). Mothers in this sample reported working significantly fewer hours than other workers (although they still reported working on average over 50 hours per week). It is also possible that the mothers in our sample had many skills necessary to accommodate both work-family demands (e.g., multi-tasking abilities, organization skills). Mothers with these abilities and skills may “self-select” into high demand jobs based on these skills, mothers without these skills may opt out of stressful jobs over time, or mothers may develop coping skills over time, in response to the high work and family demands.

Younger adults also reported more negative work-family spillover than older adults. It is possible this finding is a result of the fact that age may be associated with both job characteristics (e.g., older adults may be more likely to work in better jobs) and home characteristics (e.g., children of older HMs may be older, and thus require less time). Older adults may have also developed better coping skills over time to deal with the job demands and balance work and family. In addition, selection effects may be playing a role. It is possible that people who handle job demands well continue working as HMs, whereas others may opt out to less stressful jobs.

6.2 Do Work Conditions Predict Spillover?

The present study found that work conditions common to hotel managers put HMs at risk for experiencing negative work-family spillover. Working longer hours for hotels with higher organizational time expectations, having to engage in more emotional labor, and experiencing permeable boundaries were associated with higher levels of negative work-family spillover, even controlling for some of the personal circumstances associated with these work stressors. Compared to negative work-family spillover, fewer correlates of positive spillover emerged from the analyses. However, higher levels of organizational time expectations and emotional labor were associated with less positive work-family spillover. It is interesting to note that these work conditions contributed uniquely to spillover, because all work conditions were entered simultaneously into the models.

Overall, the moderation analyses suggest that working conditions do not put women or parents at increased risk for negative spillover. In fact, emotional labor appears to decrease the risk of negative spillover among parents, relative to employees without children living at home. There are a number of possibilities for this finding. First, parents report experiencing less emotional labor at work, suggesting that this work condition may not influence negative spillover because it is less of a problem for this group. Second, it could be that parents have become adept at handling emotional labor due to common use of emotional labor at home. In contrast, working long hours may put parents at increased risk for negative spillover. This condition may be due to an increased number of time obligations required of parents at home, compared to employees without children at home.

Although an experimental design is necessary to determine a cause and effect relationship between stressors and spillover, these results suggest that modification of work conditions may lead to better work-family integration among HMs. Future experimental studies investigating the association between organizational time expectations and spillover may be of particular importance for three main reasons. First, this work condition was found to be associated with both positive and negative spillover, indicating that modification of this work condition may be particularly beneficial to managers’ well-being and satisfaction with work. Second, this work condition, which is a part of organizational culture in many hotel organizations, may be more easily modified than other work stressors. Third, modifying organizational time expectations may not only lead to better work-family integration among hotel managers, but past research suggests that it is also linked to other positive outcomes such as higher organizational commitment and lower turnover intent (O’Neill et al., 2009).

6.3 Strengths/Limitations

The present study focused on a large sample of 586 HMs employed in full-service hotels across the country. In addition, analyses included both negative and positive work-family spillover. Past research has focused mainly on negative spillover, which ignores the fact that engaging in multiple roles may have positive benefits. Another strength of the study is that the work conditions examined were chosen based on the results of prior research in the hotel industry. Focus groups of hotel managers indicated that long hours worked per week and high organizational time expectations, emotional labor, and permeable boundaries are particularly problematic for both managers and their spouses (Cleveland et al., 2007).

Despite these strengths, there are several limitations to be noted about the current study. First, department type (e.g., Food & Beverage, Rooms) was not taken into account. Analyses grouped all HMs together to increase the sample size (and thus the power) of the study. However, it is possible that some of the work stressors (e.g., emotional labor) are more problematic and/or common among HMs working in different departments, such as managing the front desk. Future research should compare the correlates of work-family spillover among hotel managers in a variety of different departments. Second, the cross-sectional design of the study limits the ability to assess cause and effect relationships between work conditions and spillover. Future longitudinal research with experimental designs are needed to better understand the association between work stressors and spillover. Third, the present study relied solely on self-reports of the HMs. Future research is needed using other forms of data, such as reports of spillover and work conditions from other sources (e.g., spouse reports, work records). Fourth, some of the measures had weak internal reliability (e.g., positive work-family spillover). Therefore, the associations among variables may be weaker due to measurement error.

6.4 Conclusion

The hotel industry experiences high turnover rates relative to other industries in the U.S. (Bureau of Labor Statistics, 2011). These high turnover rates likely in part stem from stressful work conditions associated with the nature of the hotel industry (e.g., long hours). The present study provides insight on the experience of work-family spillover among HMs working in the hotel industry. This information is important to the hotel industry because workers today put a premium on balance and having a life outside of employment (Becker & Moen, 1999). Without understanding work-family spillover among HMs, the hotel industry may lose the opportunity to improve the quality of HM jobs and, presumably, by understanding these issues, the industry may increase retention.

Acknowledgments

We would like to thank the Alfred P. Sloan Foundation (2004-12-4) and the NICHD (U01 HD051217-03) for providing support for this research. This research was conducted as part of the Work, Family and Health Network, which is funded by a cooperative agreement through the National Institutes of Health and the Centers for Disease Control and Prevention: National Institute of Child Health and Human Development (Grant # U01HD051217, U01HD051218, U01HD051256, U01HD051276), National Institute on Aging (Grant # U01AG027669), Office of Behavioral and Science Sciences Research, and National Institute for Occupational Safety and Health (Grant # U010H008788). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of these institutes and offices. Special acknowledgement goes to Extramural Staff Science Collaborator, Rosalind Berkowitz King, Ph.D. (NICHD) and Lynne Casper, Ph.D. (now of the University of Southern California) for design of the original Workplace, Family, Health and Well-Being Network Initiative. Persons interested in learning more about the Network should go to https:/www.kpchr.org/workplacenetwork.

Appendix 1

Results of the multilevel models examining life circumstances as moderators of the associations between work conditions and negative spillover (Models 2–5)

Model 2 Model 3 Model 4 Model 5
Intercept    12.27  12.29    12.21  12.29
Life Circumstances
Age   −.05 (.01)**   −.05 (.01)**   −.05 (.01)** −.05 (.01)**
Decision-Making Latitude   −.17 (.28)   −.19 (.28)   −.20 (.28) −.23 (.28)
Gender −1.02 (.23)** −1.00 (.23)** −1.01 (.23)** −.99 (.23)**
Parental Status      .06 (.24)     .05 (.24)     .03 (.24) −.004 (.25)
Gender X Parental Status   −.49 (.50)   −.29 (.49)   −.11 (.49) −.39 (.50)
Work Stressors
Hours/Week      .04 (.01)*     .04 (.01)*     .04 (.01)*   .04 (.01)*
Time Expectations      .98 (.13)**   1.00 (.13)**     .97 (.13)**   .97 (.13)**
Emotional Labor      .75 (.15)**     .73 (.15)**     .69 (.16)**   .74 (.15)**
Permeable Boundaries      .54 (.12)**     .54 (.12)**     .56 (.12)**   .55 (.12)**
Interactions
Hours/Week X Gender      .03 (.03)       --      --     --
Hours/Week X Parental Status      .06 (.03)*       --      --     --
Hours/Week X Gender X Parental Status    −.03 (.06)       --      --     --
Time Expectations X Gender       --     .31 (.23)      --     --
Time Expectations X Parental Status       --     .33 (.23)      --     --
Time Expectations X Gender X Parental Status       --   −.01 (.49)      --     --
Emotional Labor X Gender       --       --     .56 (.30)     --
Emotional Labor X Parental Status       --       --   −.61 (.31)*     --
Emotional Labor X Gender X Parental Status       --       --     .15 (.63)     --
Permeable Boundaries X Gender       --       --      -- −.22 (.21)
Permeable Boundaries X Parental Status       --       --      --   .08 (.22)
Permeable Boundaries X Gender X Parental Status       --       --      --   .39 (.47)
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*

Note. p < .05,

**

p < .001

Appendix 2

Results of the multilevel models examining life circumstances as moderators of the associations between work conditions and positive spillover (Models 7–10)

Model 7 Model 8 Model 9 Model 10
Intercept    8.62   8.62    8.63 (.11)    8.62
Life Circumstances
Age   .003 (.01)   .004 (.01)   .002 (.01)   .006 (.01)
Decision-Making Latitude 1.02 (.25)** 1.04 (.25)** 1.04 (.25)** 1.01 (.25)**
Gender   .16 (.21)   .18 (.20)   .13 (.21)   .18 (.20)
Parental Status −.01 (.21) −.005 (.21)   .05 (.21) −.08 (.22)
Gender X Parental Status −.42 (.43) −.40 (.42) −.53 (.43) −.53 (.43)
Work Stressors
Hours/Week −.001 (.01) −.003 (.01) −.002 (.01) −.002 (.01)
Time Expectations −.25 (.11)* −.22 (.11)* −.25 (.11)* −.24 (.11)*
Emotional Labor −.47 (.14)** −.47 (.13)** −.43 (.14)* −.46 (.14)**
Permeable Boundaries   .10 (.11)   .09 (.11)   .09 (.10)   .08 (.11)
Interactions
Hours/Week X Gender −.01 (.02)     --     --    --
Hours/Week X Parental Status −.01 (.03)     --     --    --
Hours/Week X Gender X Parental Status   .02 (.05)     --     --    --
Time Expectations X Gender    --   .27 (.11)     --    --
Time Expectations X Parental Status    --   .22 (.20)     --    --
Time Expectations X Gender X Parental Status    --   .54 (.43)     --    --
Emotional Labor X Gender    --     -- −.06 (.26)    --
Emotional Labor X Parental Status    --     --   .34 (.27)    --
Emotional Labor X Gender X Parental Status    --     -- −.76 (.55)    --
Permeable Boundaries X Gender    --     --     --   .04 (.19)
Permeable Boundaries X Parental Status    --     --     --   .25 (.20)
Permeable Boundaries X Gender X Parental Status    --     --     --   .60 (.41)
Open in a new tab
*

Note. p < .05,

**

p < .001

Footnotes

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