Individual differences: Factors affecting employee utilization of flexible work arrangements

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Journal of Vocational Behavior 73 (2008) 107–117

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Individual differences: Factors affecting employee utilizationof flexible work arrangements

Alysa D. Lambert a,*, Janet H. Marler b,1, Hal G. Gueutal b,1

a School of Business – HH214, Indiana University Southeast, 4201 Grant Line Road, New Albany, IN 47150, USAb Department of Management, School of Business, University at Albany, SUNY, 1400 Washington Avenue, Albany, NY 12222, USA

Received 17 July 2007Available online 4 March 2008

Abstract

This study investigated individual and organizational factors that predict an individual’s choice to use flexible workarrangements (FWAs). Survey data was collected from 144 employees in two different organizations. The results revealedseveral significant predictors of FWAs: tenure, hours worked per week, supervisory responsibilities, perceptions of work-group use and personal lifestyle. Individuals with longer tenure in the organization, who had supervisory responsibilities,had coworkers in their immediate workgroup who used FWAs or had personal lifestyle preferences were more likely to usethe programs than those with less tenure, who did not have supervisory responsibilities, did not perceive their workgroupused FWAs or did not have personal lifestyle preferences.� 2008 Elsevier Inc. All rights reserved.

Keywords: Work and family; Flextime; Compressed workweeks; Work-life programs; Logistic regression

1. Introduction

Research has shown that lack of balance in one’s life is related to higher stress, less life satisfaction, andlower work effectiveness (Kofodimos, 1993). Not surprisingly, a large percentage (30%) of employees say theyare willing to reduce pay or even change employers in order to achieve better work–family balance (Galinsky,Bond, & Friedman, 1993). In fact, work-life programs that increase an employee’s options for flexibility on thejob or allow alternate work schedules are becoming more popular (Bond, Thompson, Galinsky, & Prottas,2002). These programs are known as flexible work arrangements.

Flexible work arrangements (FWAs) are defined as employer provided benefits that permit employees somelevel of control over when and where they work outside of the standard workday (Hill, Hawkins, Ferris, &Weitzman, 2001). Research on FWAs suggest they have positive outcomes for individuals such as lowerwork–family conflict (Anderson, Coffey, & Byerly, 2002) and increased work–family balance (Eby, Casper,

0001-8791/$ - see front matter � 2008 Elsevier Inc. All rights reserved.doi:10.1016/j.jvb.2008.02.004

* Corresponding author. Fax: +1 812 941 2672.E-mail addresses: [email protected] (A.D. Lambert), [email protected] (J.H. Marler).

1 Fax: +1 518 442 4765.

mailto:[email protected]

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108 A.D. Lambert et al. / Journal of Vocational Behavior 73 (2008) 107–117

Lockwood, Bordeaux, & Brinley, 2005), and positive outcomes for organizations. For example, a meta-anal-ysis revealed FWAs were related to higher employee productivity, overall job satisfaction, and lower absen-teeism (Baltes, Briggs, Huff, Wright, & Neuman, 1999).

Despite research on positive outcomes for both individuals and organizations, there is little research on theantecedents of employees’ choice to participate in FWAs. Only one study could be found that directly studiedemployees’ use of FWAs. Kossek, Barber, and Winters (1999) looked at managers and their use of flexiblework options, and found that managers whose peers used the programs were also more likely to use FWAs.Most research on antecedents of use pertains to work-life programs (WLPs) more broadly, rather than FWAsspecifically (e.g. Allen, 2001; Thompson, Beauvais, & Lyness, 1999). While such studies provide a basis foridentifying possible predictors of FWA use, more research specific to FWAs is needed.

This study investigated both individual and organizational factors that increase the likelihood of using flex-time and compressed workweeks, two of the most popular forms of FWAs (Bond et al., 2002). The Theory ofHuman Ecology is used as the framework for deriving these characteristics and predictions concerning howthey are related to the probability of using FWAs.

1.1. Theoretical foundation and hypotheses

Human Ecology Theory (HET) posits that individuals’ behavioral choices are focused on achieving envi-ronmental adaptation (Bronfenbrenner, 1979). The goal is to become attuned to cues in the environment inorder to operate more efficiently within it. These environmental cues may include, but are not limited to, sup-port from others, imitation of others’ behavior, and learning from observing others. Using these cues, individ-uals develop patterns of behaviors that are efficient and routine and this results in a sense of equilibrium, timeto deal with unexpected changes, and the development of new skills. Achieving this balanced state (known asintegrity of functioning) occurs when the environment is molded to meet the specific requirements of the per-son’s needs, abilities, knowledge, and skills.

HET has been applied in the work–family context; Lee, MacDermid, and Buck (2002) found that the mainreasons individuals chose a reduced workload were to spend more time with children, family, or to creatework–family balance. Individuals were able to mold their environment to meet personal needs. Another studyused this theory to assess the success rate of managers and professionals working flexible schedules (Lee,MacDermid, Williams, Buck, & Leiba-O’Sullivan, 2002). Individuals using FWAs were able to adjust theirenvironment to fit the needs of both their professional and personal lives. Over 90% reported they were sat-isfied with their ability to maintain balance between work and family using FWAs.

According to HET, people sense the pressures and subtle nuances within their environments and use thatinformation to adapt to and mold their environment to better fit their needs (Lee, MacDermid, et al., 2002;Schabracq, Cooper, & Winnubst, 1994). In the case of the current study, individuals extract information fromseveral environmental sources to assess the effectiveness of FWAs as an adaptive choice. Environmental cuesused to achieve integrity of functioning are grouped into work factors (supervisory support, coworker supportand workgroup use) and non-work factors (spousal support, primary care responsibilities, and personal life-style). The factors studied here represent an initial list of factors based on current theoretical and empiricalsupport.

1.1.1. Perceived supervisory support of family and personal needsAccording to HET, an individual’s attempts to stabilize their environment are enhanced when people sup-

port their activities (Bronfenbrenner, 1979). Supervisors provide support by suggesting solutions that reducestressful situations (Cohen & Willis, 1985), offering emotional support or in creating greater control over one’sresponsibilities or work schedule (Anderson et al., 2002). Given the likely positive outcomes of supervisorysupport, employees are more likely to make choices supported by supervisors. Using a HET framework,Lee, MacDermid, Williams, et al. (2002) found supervisory support was related to individual perceptionsof FWA success in balancing work and family. Several studies found similar results with other WLPs (Allen,2001; Thompson et al., 1999). Thus the following is proposed:

A.D. Lambert et al. / Journal of Vocational Behavior 73 (2008) 107–117 109

Hypothesis 1. Employees who perceive their supervisor as supportive of the use of FWAs will be more likelyto use them than employees who believe their supervisor is not supportive.

1.1.2. Perceived coworker support of family and personal needs

In addition to supervisory support, support may also come from coworkers. Employees who had strongsupportive ties with coworkers had higher positive affect and job satisfaction (Ducharme & Martin, 2000).The authors believed that this support acted as a buffer which helped individuals cope with work stressors.If employees have coworkers who support and share their concerns, they have more assurance that their workand family issues will be taken into consideration (Clark, 2002). Thus, perceiving coworker support is likely toresult in adaptive choices such as using FWAs.

Hypothesis 2. Employees who perceive their coworkers as supportive of the use of FWAs will be more likelyto use them than employees who do not perceive their coworkers as supportive.

1.1.3. Perceptions of workgroup use

A principle tenet of HET states a major determinant of behavior is whether or not those around us areengaging in the same or similar behavior (Bronfenbrenner, 1979). Thoits (1986) suggested people learn fromthe experiences of others within the social network or workgroup. For instance, by observing others, individ-uals may try the same techniques in order to cope with the everyday stresses. Kossek et al. (1999) found thatpeer use significantly predicted employee use above and beyond factors like gender and age. In this case, byseeing people within the workgroup successfully use FWAs, individuals also observed that it was possible to besuccessful using FWAs themselves.

Hypothesis 3. Employees who perceive that their workgroup uses FWAs will be more likely to use them thanemployees who perceive their workgroup does not use FWAs.

1.1.4. Perceived spousal/partner support

Friedman and Greenhaus (2000) state there are two ways partners provide support: for stress preventionand for overall well-being. Specifically, they discuss a partner’s ability to explore stress relieving options thatmay be available to the employee, such as FWAs. Also, partners or spouses may be able to help individualsfeel better about their work or family situation by increasing the level of self-confidence and esteem the personfeels. This can help the individual feel more satisfied and more fulfilled at work.

Several empirical studies suggest spousal support may affect an individual’s sense of equilibrium (Galinsky& Stein, 1990; Repetti, 1987). Specifically, Galinsky and Stein (1990) followed women returning from mater-nity leave. These women reported that spousal support was as crucial to reducing the stress of returning towork as supervisory support. Based on empirical results and HET, we expect that spousal support also affectsFWA use.

Hypothesis 4. Individuals with higher levels of spousal/domestic partner support will be more likely to useFWAs than individuals with less spousal/domestic partner support.

1.1.5. Extent of primary care responsibilitiesMany researchers have assumed parental status explains why individuals use WLPs because much research

supports that parents, mothers especially, value family-friendly benefits. Grover (1991) found that people withchild care responsibilities had more positive attitudes toward parental leave than those who did not have childcare responsibilities. Also, people with child care needs were more likely to use WLPs than those without(Thompson et al., 1999).

Research has also reported that women believe WLPs are more important than men (Frone & Yardley,1996; Kossek & Nichol, 1992), are more likely to leave one organization for another with better benefits thanmen (Greenberger, Goldberg, Hamill, O’Neil, & Payne, 1989) and are more inclined to use WLPs than men(Butler, Gasser, & Smart, 2004). This leads many to believe gender differences exist for decisions about work


and family requirements. However, when gender differences are explored in organizational settings no varia-tions are found (Parker & Allen, 2001).

Much of the preceding research also suggests parental status and gender may be mediated by more prox-imal factors such as degree of primary care responsibilities. The extent of a person’s primary care responsibil-ities, both child and elder care, are important variables that affect an individual’s perceived need to makeadaptive choices. HET predicts individuals with more demands on their time have a greater need to engagein the adaptation process to achieve integrity of functioning. Individuals with these time constraints or, in thiscase, greater levels of primary care responsibilities, need to adapt more efficiently to their environment in orderto achieve integrity of functioning. Further, because women are socialized to feel the responsibility for primarycare is more important for their functioning than men, we assert:

Hypothesis 5a. Employees with high levels of primary care responsibilities will be more likely to use FWAsthan employees with low levels of primary care responsibilities.

Hypothesis 5b. Females with high levels of primary care responsibilities will be more likely to use FWAs thanmales with high levels of primary care responsibilities.

1.1.6. Personal lifestyle

According to HET, FWAs are used to help people adapt their environment to their own needs (Lee,MacDermid, et al., 2002). Thus, individuals with various lifestyle needs will be more likely to use FWAs toincrease control over their environment. Up to this point much of the literature has focused only on workand family, however not everything people do outside of work is related to the family. Golden (2001) pointedout that workers value FWAs greatly because they lower conflicts between work and non-work responsibili-ties. Golden also argued that the amount of time an employee wanted or needed to work was determined by anumber of economic, social and cultural issues, not just family-related issues. It is reasonable to assume thatindividuals who use FWAs may do so for reasons other than to meet parenting responsibilities. Personal life-style preferences, therefore, should also be related to use of FWAs.

Hypothesis 6. Employees with high levels of personal lifestyle preferences other than parenting responsibilitieswill be more likely to use FWAs than those with low levels of lifestyle preferences.

2. Methods

2.1. Sample and procedure

2.1.1. Sample

The sample consisted of 211 employees from two separate organizations: a financial institution and aninsurance company. Each of the companies offered employees flextime and/or compressed workweeks (noother types of FWAs were offered). The organizations were selected because they had full-time jobs that, inthe past, required their employees to work the traditional 8am to 5pm, Monday through Friday schedulebut were now offering these new alternatives. In this study, only individuals working full-time (35 h or moreper week) were included.

Of the 211 employees contacted, 166 took the survey. Twenty-two cases had missing data, resulting in afinal sample of 144 and a response rate of 63%. A total of 102 (75.6%) participants were female, betweenthe ages of 31–35 (25.8%) and were Caucasian (88.9%).

2.1.2. Survey collection

A three-stage pilot study was conducted to develop measures for this study and to assess previouslydesigned measures’ reliability. All the measures were included in at least one stage of the pilot study. Forthe current study, the authors followed Podsakoff, MacKenzie, Lee, and Podsakoff’s (2003) procedural rem-edies within the study design to minimize single-source bias. Employees received an email from a representative


within their company inviting them to participate in a two-part online survey. The employees’ confidentialityand anonymity were guaranteed.

The first survey collected information on the independent variables. Two weeks later employees were askedto provide data on the dependent variable and demographic information. Participant responses were matchedusing a participant selected identifying code.

2.2. Measures

2.2.1. Use of FWAs

Use was measured by asking the employee whether they currently used flextime and whether they used com-pressed workweeks. The answers to these two questions were combined into one categorical variable where thevariable took the value of 1 if the respondent answered ‘‘yes” to either question or the value 0 if answering‘‘no” to both questions.

Perceived supervisory support of family and personal needs was measured using a scale developed by Shinn,Wong, Simko, and Ortiz-Torres (1989), as used by Allen (2001). The pilot study revealed that a higher reli-ability could be achieved by dropping two of the original items. The 9-item measure (a = .91) asked partici-pants to rate how often their supervisor engages in supportive behaviors (i.e. ‘‘My supervisor rearranges orallows me to rearrange my schedule (hours, overtime hours, vacation) to accommodate my life/personalresponsibilities”). Ratings were on a Likert Scale ranging from 1 (strongly disagree) to 5 (strongly agree).

Perceived coworker support of family and personal needs was assessed using the measure of perceived super-visory support and adapted by replacing the word ‘‘supervisor” with ‘‘immediate coworkers.” One item couldnot be translated because it was not applicable to coworkers. An example from the 8-item measure (a = .84)included was ‘‘My immediate coworkers listen to my concerns about balancing work and life/personalresponsibilities.”

2.2.2. Perceptions of workgroup use

Participants answered whether their supervisor currently used (FWAs) and also if their coworkers currentlyused FWAs. Responses were combined into one categorical variable with the value of 1 for a ‘‘yes” and 0 ifneither coworker nor supervisor used FWAs.

2.2.3. Perceived spousal/partner support

The measure of spousal support was created specifically for use in this study and was designed during thepilot study. The scale consisted of 6 items (using the 5-point Likert scale described earlier) asking employees,for example, to rate to what extent ‘‘My spouse/domestic partner encourages me to use flexible work arrange-ments” (a = .86). Only individuals who were married or had been living with a domestic partner for a year orlonger responded to these statements. Because only 101 of the 144 participants were married or had a partner,this lead to 43 cases that had non-random missing data. Cohen and Cohen (1983) recommend a procedurewhere by a missing data dichotomous variable is created from the variable that has non-random missing dataand included in the regression equation as a control for the missing data in the original variable. This proce-dure was used here and the new variable was labeled marital status.

2.2.4. Extent of primary carePrimary care was calculated by summing several items that included number of children under the age of

18, number of elderly relatives or parents that the individual had primary responsibility for, whether or not theperson had a spouse or partner, and whether or not that spouse/partner was employed (3 points = no spouse,2 points = spouse, working full-time, 1 point = spouse, working part-time and 0 points = spouse, not work-ing); the higher the score the more primary care responsibilities. We used a process similar to Kossek et al.(1999) except points were not added for complexity of the individual’s responsibilities.

2.2.5. Personal lifestyle

This measure was developed during the three-stage pilot study. The final Lifestyle scale consisted of 12 rea-sons people might use FWAs including having preferred work times (e.g. the preference to work in the

Table 1Means, standard deviations, reliability estimates, and inter-correlations

a M SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14

1 Used 0.33 0.472 Supervisor supportb .91 3.67 0.78 .1453 Coworker supportb .84 3.46 0.62 .018 .311**

4 Spousal supportb .86 3.97 0.76 .113 �.001 .0395 Lifestyle determinantsa 2.58 0.80 �.047 �.032 .078 .279**

6 Workgroup used 0.36 0.48 .648** .153 .128 .091 �.0767 Extent of primary carea 3.04 2.08 .029 �.101 .081 .300** .045 �.1348 Genderc 0.76 0.43 .019 .057 .008 �.210* �.140 �.001 .0339 Race/ethnicity 1.30 0.98 �.001 �.137 �.037 .078 .015 �.061 .177* �.051

10 Education level 4.02 1.35 .130 .006 .002 .067 .032 .102 �.052 �.221* .08511 Age 4.62 1.81 .193* �.072 .100 �.132 �.025 .173* .366** .098 .061 �.08712 Tenure 3.78 2.63 .328** .035 .083 �.259* �.106 .224** .079 .212* �.072 �.179* .359**

13 Hours per week 40.56 5.93 �.243** �.267** �.204* .037 .010 �.244** .088 �.023 .081 �.081 .107 .06614 Supervisory responsibilitiesd 1.21 0.41 .187* .038 �.045 �.099 �.272** .021 .150 �.122 �.015 �.009 .093 .142 .204*

15 Marital statusd 0.70 0.46 .131 �.021 �.095 .944** .047 .048 .270** �.096 �.153 .107 .098 .196* .028 .052

a Higher values reflect a greater degree of the variable.b Higher values reflect greater levels of support.c Gender was coded 0 (male) and 1 (female).d Coded 0 (no) and 1 (yes).* p < .05.

** p < .01.

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Table 2Logistic regression analysis predicting use of FWAs (N = 144)

Variable Model A Model B Model C Model D Model E

b SE b SE b SE b SE b SE

Intercept 0.89 2.72 �6.78 4.55 �0.58 2.89 �4.77 4.65 �7.02 5.76Demographic variables

Gender �0.10 0.54 0.08 0.72 0.14 0.56 0.14 0.74 1.09 1.52Ethnicity 0.15 0.22 0.34 0.26 0.27 0.23 0.39 0.29 0.35 0.30Education 0.28 0.18 0.26 0.21 0.26 0.18 0.24 0.12 0.24 0.21Age 0.18 0.14 0.09 0.17 0.27* 0.15 0.07 0.18 0.07 0.18Tenure 0.31*** 0.10 0.34*** 0.13 0.34*** 0.10 0.34** 0.14 0.35** 0.14Hours worked �0.16*** 0.05 �0.11*** 0.06 �0.18*** 0.06 �0.14** 0.07 �0.13** 0.07Supervisory responsibilities 1.27*** 0.55 1.72*** 0.76 1.96*** 0.66 2.01** 0.85 1.93** 0.87Marital status 0.23 0.56 0.60 0.75 �1.56 1.69 1.53 2.22 1.65 2.24

Work environmentSupervisor support 0.38 0.43 0.35 0.45 0.38 0.45Coworker support �0.55 0.53 �0.58 0.55 �0.51 0.56Workgroup use 3.46*** 0.67 3.73*** 0.78 3.70*** 0.78

Non-work environmentSpousal/partner support 0.55 0.40 �0.29 0.54 �0.28 0.54Extent of primary care �0.28 0.15 0.08 0.20 0.59 0.73Lifestyle 0.04 0.03 0.07* 0.04 0.07* 0.04Gender � primary care �0.29 0.40

Log-likelihood 124.53 82.44 117.87 79.07 78.51Degree of freedom 8 11 11 14 15v2 35.21*** 77.31*** 41.87*** 80.67*** 81.23***

Dv2 42.09*** 6.66* 45.46*** 46.02***

Pseudo R2 0.24 0.45 0.28 0.47 0.47

* p < .10.** p < .05.

*** p < .01.


morning) and having more time for other activities (e.g. a second job or longer vacations). Respondentsreported how much each factor affected their willingness to use FWAs. Possible responses ranged from 1(has no affect) to 5 (highly affects). Because each item represents an independent reason why individualsmay use FWAs, the items were summed. Thus individuals with higher scores had a greater willingness touse FWAs.

3. Results

Table 1 provides means, standard deviations, reliabilities and correlations for all variables. Table 2 showsthe results of a stepwise logistic regression in which control variables (gender, race, education, age, tenure,work hours, supervisory responsibilities, and marital status) are reported in Model A, work environmentalvariables are added as a group in Model B, non-work environmental variables are entered as a group in ModelC, both groups of variables are entered together in Model D and finally Model E contains all variables plus theinteraction between gender and primary care.

Model A includes only the control variables. This model compared with the constant only model was sta-tistically significant, v2 (df = 8) = 35.21, p < .01. An employee’s tenure with the company (b = 0.31, p < .01),average number of weekly work hours (b = �0.16, p < .01) and supervisory responsibility (b = 1.27, p < .01)were significant predictors of use of FWAs. The probability of using FWAs was 1.4 times more likely for everyone year increase in tenure indicating the odds increased by almost 50% for every year increase in tenure. Forfull-time employees, those working 35 h or more per week, for every 1 h increase in hours worked per week the


probability of using FWAs decreased by .87 or 13%. Results also revealed employees with supervisory respon-sibility were over 8 times more likely to use FWAs than those with no supervisory responsibility.

Model B added the work environmental variables to the first model. When entered as a group, the workenvironmental variables improved model fit significantly (Dv2 = 42.09, p < .01) suggesting these variables,as a group, contributed to the increased likelihood of FWA use. However, no support was found for Hypoth-esis 1 (supervisory support) or Hypothesis 2 (coworker support). Only perceptions of workgroup use had asignificant parameter estimate (b = 3.46, p < .01), supporting Hypothesis 3. Employees who believed theirimmediate workgroup used FWAs were 44 times more likely to use FWAs themselves than those who per-ceived their workgroup did not use FWAs.

Model C included the control and non-work environmental variables. The model itself was significant (v2

(df = 11) = 41.87, p < .01) but the non-environmental factors as a group improved model fit only at a margin-ally significant level (Dv2 = 6.66, p < .10). These results indicate non-work variables are not as influential aswork variables in predicting likelihood of FWA use. Spousal/partner support, primary care responsibilitiesand lifestyle did not significantly predict use of FWAs; therefore, Hypotheses 4, 5a, and 6 were not supported.

Model D included all the predictors entered together and was significant (v2 (df = 14) = 80.67, p < .01). Inthis model all the variables added as a group contributed to improved model fit (Dv2 = 45.46, p < .001). Aswith Model B, support was found for Hypothesis 3; if the perception was that the employee’s immediate work-group used FWAs then the employee was more likely to use FWAs (b = 3.73, p < .01). However, unlike ModelC, the parameter estimate for the likelihood that lifestyle preferences contributed to the probability of FWAuse was significant (b = .07, p < .10), thus supporting Hypothesis 6.

A closer look at these results suggested the possibility of a reciprocal suppression effect (Tzelgov & Henik,1991), given that lifestyle and FWA use were not significantly correlated as shown in Table 1 (r = �.047).A t-test revealed a statistically significant difference between the means on the lifestyle measure for supervisors(25.89) and non-supervisors (32.00) suggesting supervisory responsibility could be a suppressor variable. Fur-thermore, logistic regression results using a subsample that excluded respondents with supervisory responsi-bilities indicated lifestyle was significant in both Model C and Model D.

Model E included all the variables from Model D and the interaction term of gender and primary careresponsibilities. While the model itself was significant (v2 (df = 15) = 81.23, p < .01) there was no significantinteraction effect and thus no support was found for Hypothesis 5b.

4. Discussion

HET asserts that an individual’s overarching goal is to become aware of the subtleties of the environment inorder to function efficiently within it. People assess factors within their environment to determine if FWAs willcontribute to their ability to function optimally. The results of this study revealed that all but one of the sig-nificant predictors of FWA usage were work related: tenure, hours worked, supervisory responsibility, andperceptions of workgroup use. The one non-work variable that predicted FWA use after variance in the workenvironment was controlled was personal lifestyle.

Perceived workgroup use was the strongest predictor of employees’ use of FWAs. Seeing one’s peers suc-cessfully engaging in a certain behavior encourages and inspires people to actively engage in the same or sim-ilar behavior (Bronfenbrenner, 1979). Previous research has confirmed this theoretical principle. Kossek et al.(1999) found workgroup use to be the strongest predictor of use of WLPs above other organizational factors.

Although neither supervisory support nor coworker support significantly increased the likelihood of usingFWAs, other work related demographic variables showed strong predictive effects. An individual’s job tenure,hours worked and supervisory responsibilities all contributed to the likelihood of FWA use. Tenure was a sig-nificant predictor of use suggesting that the longer one has been at an organization the more likely they are touse FWAs. An explanation for this may be that people with longer tenure feel more comfortable within theirenvironment and probably have more seniority and therefore, can ask for greater flexibility. Our data alsoindicated that employees who worked more hours per week were less likely to use FWAs. Previous researchhas found that employees who work an average of 40 hours per week used FWAs less than those who aver-aged less than 40 hours per week (Golden, 2001). An explanation for this is individuals who work on averagemore than 40 hours per week already have to work overtime to meet the demands of their responsibilities, and


therefore, would not see flexing their schedule as an aid in completing their work. It is also possible that indi-viduals who use FWAs, just by the nature of flexing their schedule work less hours; meaning they are able toaccomplish more in less time because they have more control over when and where they work. There isresearch to support the idea that individuals who use FWAs are more productive (Baltes et al., 1999).

Personal lifestyle preference was the only non-work factor that significantly predicted the probability of FWAuse. Based on HET, it was hypothesized that employees with greater personal lifestyle determinants would bemore likely to use FWAs and the results of this study support this, particularly for those in jobs without super-visory responsibilities. Because supervisors scored significantly lower on the lifestyle measure compared to thosewithout supervisory responsibilities when this negative correlation was controlled, the relationship betweenFWA use and lifestyle was enhanced. When supervisors were excluded from the sample, lifestyle preferences sig-nificantly predicted the probability of FWA use. An explanation for this result is that individuals with variouslifestyle preferences are more likely to use FWAs in order to have more control over their environment partic-ularly when they are not in supervisory positions because they have less autonomy over their time.

We also noted when supervisors were excluded from the sample the primary care variable also became sig-nificant, although opposite to the hypothesized direction. These results suggest that supervisors and non-supervisors appear to behave differently with respect to use of FWAs. Further, the unexpected negativeand significant relationship between FWA use and primary responsibilities for non-supervisors raises interest-ing questions for future research and employment policy. For example, it could be that individuals who haveprimary care responsibilities cannot flex their schedules because other support services such as daycare andsenior centers typically operate during normal business hours. One of the advantages of offering flexible workschedules is that they can be used more widely and therefore contribute less to feelings of unfairness amongemployees (Parker & Allen, 2001). Our results suggest fruitful avenues for future research that include a moreexpansive definition of non-work-life domains.

4.1. Limitations

As with all research there were limitations to this study. The first was the use of a self-reported survey data,which may contribute to inflation of relationships between variables. However, we followed the recommenda-tions of Podsakoff et al. (2003) to counteract mono-method bias in the initial design of the study. For example,the independent and dependent variables were collected at two different times (2 weeks apart) and we useddifferent scale endpoints to measure our variables.

Another limitation was the population used. Even though the participants were from two organizations,they all worked in service oriented jobs in a bank and an insurance company, and the majority of the samplewas Caucasian and female. It is plausible that cultural norms in our sample of service organizations affectedthe likelihood of FWA use. The fact that workgroup use was such a robust predictor of FWA use in this studysuggests normative influences might play an important role. It is also plausible that results would differ inother industries or in professions that are traditionally male dominated. An area for future research is toexamine the effect of cultural norms on FWA use across different organizational and professional contexts.

One last issue that should be addressed is the fact that this study combined flextime and compressed work-weeks into one variable. Although there is little theory to suggest that variations in type of FWAs wouldimpact the likelihood of use, and exploratory analyses of small subsamples of this data suggest there areno significant differences, this remains a question for future research. For example, the incidence of com-pressed workweek use appeared to be lower than use of flextime. This difference might vary across organiza-tional and job-level contexts.

4.2. Implications and conclusions

The results of this study suggest that many people imitate the behavior of others as a way to better balancework and family. If an employee believes their workgroup uses FWAs then the employee is more likely to usethe program. This result confirms past research and highlights the importance of the normative influences ofthe workgroup on individual employee behavior.


Up to this point much of the research on individual characteristics has focused on gender (Butler et al.,2004; Frone & Yardley, 1996; Grover, 1991; Kossek & Nichol, 1992), parental status (Thompson et al.,1999), or primary care responsibilities (Kossek et al., 1999; Thompson et al., 1999) as the main determinantsof an employee’s use of WLPs. This study, which included gender and extent of primary care responsibilities(parental status was part of this factor) and personal lifestyle, found that of all of them, personal lifestyle wasthe strongest predictor an individual’s choice to use FWAs, particularly amongst those without supervisoryresponsibilities.

This study, in conclusion, has contributed to the research on work and family, particularly in the area ofFWAs by introducing new factors that have not been assessed previously. Our results indicate that work-related variables are more predictive of FWA use than non-work factors, and that personal lifestyle prefer-ences have more impact than family-care related factors particularly for those without supervisoryresponsibilities.

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Individual differences: Factors affecting employee utilization of flexible work arrangements