Comparing Telework Locations and Traditional Work Arrangements: Differences in Work-Life Balance Support, Job Satisfaction, and Inclusion

Abstract

Purpose
The purpose of this paper is to examine differences in work‐life balance (WLB) support, job satisfaction, and inclusion as a function of work location.

Design/methodology/approach
Web‐based survey data were provided by 578 employees working at one of four locations (main office, client location, satellite office, and home). Multiple regression analyses were used to identify differences in WLB support, job satisfaction, and inclusion across employees working at the four locations.

Findings
Results showed that main office and home‐based workers had similar high levels of WLB support and job satisfaction. Main office workers reported higher levels of WLB support than satellite and client‐based workers. Additionally, main office workers reported the highest levels of workplace inclusion.

Research limitations/ implications
Data were originally gathered for practical purposes by the organization. The research design does not allow for manipulation or random assignment, therefore extraneous variables may have impacted the observed relationships.

Practical implications
Allowing employees flexibility in choosing their work locations is related to positive outcomes. The authors suggest several practices for the effective implementation of alternative work arrangements.

Originality/value
This paper is among the first to examine the outcomes of telework across locations. It uses a large single organization and a quasi‐experimental design, enhancing the validity of the findings.

Full text

Comparing telework locations
and traditional work
arrangements
Differences in work-life balance support, job
satisfaction, and inclusion
Valerie J. Morganson, Debra A. Major and Kurt L. Oborn
Old Dominion University, Norfolk, Virginia, USA
Jennifer M. Verive
White Rabbit Consulting, Carson City, Nevada, USA, and
Michelle P. Heelan
Telecommuting Advantage Group, San Francisco, California, USA
Abstract
Purpose – The purpose of this paper is to examine differences in work-life balance (WLB) support,
job satisfaction, and inclusion as a function of work location.
Design/methodology/approach – Web-based survey data were provided by 578 employees
working at one of four locations (main office, client location, satellite office, and home). Multiple
regression analyses were used to identify differences in WLB support, job satisfaction, and inclusion
across employees working at the four locations.
Findings – Results showed that main office and home-based workers had similar high levels of WLB
support and job satisfaction. Main office workers reported higher levels of WLB support than satellite
and client-based workers. Additionally, main office workers reported the highest levels of workplace
inclusion.
Research limitations/ implications – Data were originally gathered for practical purposes by the
organization. The research design does not allow for manipulation or random assignment, therefore
extraneous variables may have impacted the observed relationships.
Practical implications – Allowing employees flexibility in choosing their work locations is related
to positive outcomes. The authors suggest several practices for the effective implementation of
alternative work arrangements.
Originality/value – This paper is among the first to examine the outcomes of telework across
locations. It uses a large single organization and a quasi-experimental design, enhancing the validity of
the findings.
Keywords Teleworking, Conflict management, Job satisfaction
Paper type Research paper
Teleworking is defined broadly as “working from anywhere at anytime” (Kurland and
Bailey, 1999), or performing one’s work duties at a remote location. The term
“telework” is used interchangeably with “telecommuting” and “virtual work” (e.g.
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/0268-3946.htm
The authors thank Michelle L. Kelley for her helpful comments on previous drafts of this article.
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Received June 2008
Revised March 2009
December 2009
Accepted December 2009
Journal of Managerial Psychology
Vol. 25 No. 6, 2010
pp. 578-595
qEmerald Group Publishing Limited
0268-3946
DOI 10.1108/02683941011056941

Gajendran and Harrison, 2007; Siha and Monroe, 2006). As a practice, it is becoming
increasingly common internationally (Davis and Polonko, 2003). In fact, the mobile
worker population is expected to increase from 758.6 million in 2006 to over 1.0 billion
by 2011, representing 30 percent of the worldwide workforce (Sudan et al., 2007).
Telework is a widespread practical concern that merits research attention.
Work arrangements
Telework is a broad term used to describe a variety of arrangements that involve
working away from the employer’s main campus. For instance, Kurland and Bailey
(1999) described four types of telework: home-based, satellite office, neighborhood
work center, and mobile. In contrast, Garrett and Danziger (2007) define telework as:
(a) those whose remote work is from the home or in a satellite office, (b) those whose telework
is primarily in the field, and (c) those whose work is “networked” in such a way that they
regularly work in a combination of home, work and field contexts (p. 29).
The present study compared workers employed by a single organization, but with four
primary work locations: the employer’s main office, a satellite office, a client site, and
the employee’s home. While telework theorists (Garrett and Danziger, 2007; Kurland
and Bailey, 1999) differentiate between types of work arrangements, little research has
examined how work arrangements impact individual and organizational outcomes.
The purpose of the present study, therefore, is toward filling the void in the research.
Theoretical framework
Numerous telework researchers and theorists have pointed out that working away
from the central office changes the motivational qualities of work, as well as employee
attitudes and organizational perceptions. Feldman and Gainey (1997) considered the
impact of telework from a job design standpoint. Drawing from Hackman and
Oldham’s (1980) job characteristics model, Feldman and Gainey (1997) suggested
telework should have positive implications for employee motivation and attitudes;
working away from the traditional office permits higher autonomy because it allows
workers control over how and when work is performed. Indeed, telework is positively
associated with autonomy (Gajendran and Harrison, 2007) and flexibility (Hill et al.,
1998).
Other telework researchers (e.g. Sparrow, 2000; Verive et al., n.d.) have explained
how work location may impact employees’ psychological contract or underlying
cognitive schema of their employment relationships. Allowing employees to work
away from the office may be viewed as a gesture of kindness and trust, which in theory
should be reciprocated through employee loyalty and appreciation. According to
Sparrow (2000), teleworkers represent “privileged core employees, enjoying high trust
relationships, and given autonomy over work location and time, i.e. the re-emergence of
industrial guilds serviced by a small technical and commercial elite” (Sparrow, 2000, p.
214). Due in part to the autonomy and flexibility it provides, and the entrusted status it
may symbolize, telework is likely to impact employee perceptions of work-life balance
(WLB) support and job satisfaction.
Although telework has many benefits, virtual workers are removed from the central
office location; therefore their amount of face-to-face interaction with co-workers,
supervisors, and clients is limited. For this reason, Feldman and Gainey (1997) argued
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that telework reduces task interdependence, a motivational factor. In addition, they
identified social isolation as a drawback to working virtually and argued that telework
may impede fulfillment of an individual’s need for affiliation. Considerable support has
been found for this premise as teleworkers often appreciate the autonomy and
efficiency of working away from the main office; however, at times they miss the social
context of traditional work (e.g. Chevron and Primeau, 1996; Cooper and Kurland, 2002;
Gajendran and Harrison, 2007; Golden et al., 2008; Kurland and Cooper, 2002; Siha and
Monroe, 2006). The issue of workplace inclusion is highly relevant to virtual work
arrangements.
Examining the outcomes of work arrangements
WLB support
Although telework initially aimed to cut organizational costs associated with
maintaining and leasing property, telework is increasingly implemented to reduce
work pressures and facilitate WLB (Sparrow, 2000). Feldman and Gainey (1997)
theorized that workers pursue telework to balance competing roles of work and family;
they are attracted to organizations that offer telework technology and are likely to
leave organizations that do not allow them the capacity to balance their work and
personal life roles. The flexibility model views telework as a way of balancing the
demands of work and family (Huws et al., 1996; Sullivan and Lewis, 2001). In support
of the flexibility model, numerous studies have identified telework as a strategy for
workers to care for dependents (e.g. Hartig et al., 2007; Hilbrecht et al., 2008; Major et al.,
2008; Sullivan and Lewis, 2001). Given the high cost of childcare, working would not be
an option for some individuals if not for telework arrangements (Olson and Primps,
1984).
The results of numerous studies have shown that telework helps workers to
accommodate WLB demands. For example, in qualitative studies, teleworkers report
that telework enhances their WLB (Hilbrecht et al., 2008; Hill et al., 1998; Sullivan and
Lewis, 2001). Specifically, telework provides workers flexibility to balance the
competing roles of work and family, allowing them to fulfill their household
responsibilities, strengthing family relationships, and permitting optimization of time
management (Hilbrecht et al., 2008; Hill et al., 1998). Hill et al. (2003) compared
traditional office workers, mobile workers (“virtual workers”), and home-based
workers finding that home-based workers reported the highest levels of WLB and the
greatest amount of work/family success. Moreover, a meta-analytic review of the
results of 19 primary studies (n¼9,852) found a negative relationship with an effect
size of d ¼0.23 between telework and work-family conflict (Gajendran and Harrison,
2007).
Paradoxically, however, telework can be a source of work-life imbalance. Working
from home increases the permeability of work and personal life domains (e.g. Hartig
et al., 2007; Marsh and Musson, 2008). Especially in high stress jobs, working from
home may not allow workers to escape work, both mentally and physically (Russell
et al., 2009). In qualitative research, subjects reported a breakdown of the psychological
distinction between work and family (Hill et al., 1998; Sullivan and Lewis, 2001).
Telework enables workers to continue working for longer hours (Hill et al., 1998). As a
result, teleworkers may experience increased stress and overload (Hill et al., 1998;
Konradt et al., 2003; Russell et al., 2009; Towers et al., 2006).
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Research has sought to empirically examine the equivocal findings of telework’s
impact on work-family balance. According to the literature, the work-family interface
consists of two domains (i.e. work and family), each with their own boundary (e.g.
Netemeyer et al., 1996). Work may interfere with family (e.g. a parent needs to work
long hours and cannot attend a child’s recital) just as family may interfere with work
(e.g. a sick child requires a parent to miss work). Work interference with family and
family interference with work are distinct phenomena, each uniquely associated with
outcome variables (Mesmer-Magnus and Viswesvaran, 2005). In a large quantitative
study of working professionals (n¼454), Golden et al. (2006) identified a positive
relationship between the amount of time people telework and levels of work
interference with family. Conversely, they found a negative relationship between time
spent teleworking and family interference with work. In a study of employees from
multiple organizations (n¼230), Lapierre and Allen (2006) found telework was
negatively related to family interference with work and was unrelated to work
interference with family. The bidirectional nature of work-family conflict appears to be
an important distinction in understanding the relationship between telework and
work-life issues.
At present, the research on whether telework may benefit workers is equivocal.
Although numerous studies have considered work-life conflict and balance, whether
workers perceive greater organizational support is not well understood. WLB support
may be defined as individuals’ perceptions of the organization’s willingness to and
interest in supporting their family and personal life needs. WLB support is negatively
related to work interfering with family, and positively related to job and family
satisfaction (Ford et al., 2007; Michel and Hargis, 2008). Additionally, support is
positively related to organizational commitment and job satisfaction, and negatively
related to turnover intent and job search behaviors (Behson, 2002; Thompson et al.,
2004). To the extent that telework indicates organizational WLB support, telework may
have positive organizational implications.
As Sparrow (2000) points out, working from home is often a privileged work
arrangement awarded to facilitate WLB. Offering flexible work programs such as
telework signals the organization’s willingness to help employees address WLB needs
(Shockley and Allen, 2007). Thus, home-based teleworkers are likely to perceive their
work arrangements as a gesture of organizational WLB support. In contrast, other
remote work locations (satellite and client-based work) are more likely to be a function
of the organization or client’s needs. In terms of reducing work-life conflict, satellite
work may do little more than reduce the employee’s commute; it does not allow the
same level of integration of work and home life responsibilities as home-based
telework. Similarly, working at a client location separates the employee from the parent
organization which may increase isolation. For these reasons, we hypothesized the
following:
H1. Individuals working from home will report greater perceptions of WLB
support than those working from a (a) satellite location, (b) the main office, or
(c) a client location.
Job satisfaction
Working from home is associated with job satisfaction (e.g. Bailey and Kurland, 2003;
Belanger, 1999; Golden and Veiga, 2005). However, as Bailey and Kurland (2003)
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pointed out in their review of the telework literature, few studies have examined job
satisfaction as an outcome of telework. As discussed earlier, telework is likely to
predict job satisfaction because it provides individuals autonomy and flexibility to
meet their own needs and personal life demands (e.g. Baltes et al., 1999; Golden and
Veiga, 2005). In Sullivan and Lewis’s (2001) qualitative study of home-based workers,
increased independence and autonomy in scheduling work emerged as advantages of
teleworking. In other qualitative research (Hill et al., 1998), increased employee morale
was identified as an outcome of working from home. In an empirical study comparing
mobile and home-based workers, home-based workers reported higher levels of job
satisfaction (Hill et al., 2003). Recent meta-analytic findings revealed a positive
relationship between home-based telework and job satisfaction (Gajendran and
Harrison, 2007).
Whereas autonomy and flexibility may influence teleworkers to feel more satisfied
with their jobs, professional isolation may act as a countervailing force. For example,
Campione (2008) found a positive relationship between telework and depression; they
identified the decrease in face time with other employees and social isolation as the
likely explanation. In an attempt to resolve the ambiguous relationship between
telework and job satisfaction, Golden and Veiga (2005) examined the moderating role
of telework intensity (i.e. frequency of telework). They found that the relationship
between telework and job satisfaction was curvilinear (i.e. in the shape of an
inverted-U); people with moderate telework levels reported the highest satisfaction.
However, their study did not account for differences in work location, which
constitutes another explanation for the inconsistent findings regarding the relationship
between telework and job satisfaction.
To the extent that home-based telework is a privileged work arrangement,
home-based teleworkers should report higher job satisfaction than employees who are
less connected with the organization or experience reduced job autonomy (i.e. satellite
and client-based workers). Because the main office location is the central hub for
organizational life (see Bartel et al., 2007), it logically follows that working from the
main office location should yield relatively high levels of job satisfaction as well (i.e.
social isolation is not an issue for main office workers). Although main office-based
workers may have lower autonomy and flexibility than their home-based teleworking
counterparts, main office-based workers may be better able to compartmentalize their
work and personal life roles; furthermore, other family-friendly policies frequently may
provide some degree of flexibility. Thus, we propose the following:
H2a. Individuals working from home and from the main office will report similar
levels of job satisfaction.
Satellite-office workers may be able to compartmentalize their work and personal lives;
further, they are on the periphery of organizational life and therefore should experience
lower job satisfaction than main office workers. Due to the demanding schedule and
reduced flexibility associated with client-based work, and the isolation of client-based
workers from their fellow coworkers, client-based workers may be especially prone to
low job satisfaction.
H2b. Individuals working from home will report greater job satisfaction than those
working from (b
i
) a satellite office or (b
ii
) a client location.
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Workplace inclusion
Association with other people is a basic human need, fundamental to human motivation
(Baumeister and Leary, 1995). Workplace inclusion refers to one’s sense of belonging to
the organization. It involves feeling invited to participate and perceiving that one’s input
matters (Hayes et al., 2002). Workplace exclusion (or lack of inclusion) is associated with
adverse outcomes such as higher turnover, reduced organizational commitment, lower
job satisfaction, burnout, and disinterest in and rejection by co-workers (Baumeister and
Leary, 1995; Golden, 2006; Greenhaus et al., 1990). Likewise, professionally isolated
workers report anxiety, loneliness, and physiological health symptoms (Beaumeister and
Tice, 1990; DeWall and Baumeister, 2006; Jones, 1990).
Teleworkers may have inherent communication barriers with their organizations
due to temporal and physical distance (Dambrin, 2004; Hinds and Bailey, 2003).
Teleworkers may feel “out of the loop” because they do not as readily see how their
work fits in with larger team and organizational goals and may face jealousy from
non-teleworking counterparts (Gajendran and Harrison, 2007; Lombard and Ditton,
1997). Bartel et al.’s (2007) qualitative telework study provided strong evidence that
teleworkers often feel insecure about aspects of their organizational membership.
Teleworkers felt excluded, out of the loop, and not respected as workgroup members.
Additionally, they complained about missing formal and informal opportunities at the
office and were concerned about isolation and exclusion. Similarly, in other qualitative
research, social isolation has been cited as a telework drawback (Montreuil and Lippel,
2003). In a recent empirical study using a sample of teleworkers, Golden et al. (2008)
examined the impact of professional isolation, a parallel construct to inclusion,
referring to beliefs about the sufficiency of professional and social relationships.
Professional isolation was negatively associated with job performance. Furthermore,
there were significant interactions suggesting that the impact of professional isolation
on job performance is greater for those who spend extensive amounts of time
teleworking and for those who engage in limited face-to-face interactions. The authors
call for a quasi-experimental study comparing professional isolation in a matched
sample of teleworkers and non-teleworkers. The current study responds to this call. We
expect that all types of remote work involve communication barriers, and physical
distance from the organization, thus:
H3. Individuals working from (a) home, (b) a satellite office, or (c) a client location
will report lower workplace inclusion than individuals working from the main
office.
Method
Participants and procedure
Data for this study were originally collected as part of an organizational initiative to
understand existing remote work practices and to determine how to leverage them to
achieve business goals. The current study is a secondary analysis of the data. A total of
1,426 individuals from a division of a large, US-based, not-for-profit engineering and
technology research organization were invited by e-mail to participate in an online
study. Of these, 749 responded, yielding a response rate of 52.5 percent. The survey
was anonymous and confidential. The study underwent ethical review and was
granted exempt status from an institutional review board. Data examined in this study
have not been published elsewhere.
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Data from 164 participants were discarded because of missing information on the
variables of interest. Because the total amount of missing data was high (21.9 percent),
we checked for patterns to determine if data were missing systematically (Tabachnick
and Fidell, 2007). Missing data were dummy-coded and tested for relationships with
demographic variables including primary work location, gender, race, age, and tenure.
Results of these analyses did not reveal systematic patterns in missing data. Data from
seven other workers who indicated their primary location as “travel” were excluded.
Thus, the final sample included a total of 578 participants.
Participants were predominantly technical staff (75.9 percent) with some managers
(10.8 percent) and support personnel (e.g. administrative, non-technical, 11.0 percent).
Participants were eligible to telework regardless of their job title; thus, all four work
locations (main office, client location, satellite office, and home) represented all job
types. The majority were male (67.2 percent), white (75.9 percent), and between the
ages of 35 and 64 (78 percent). The vast majority (95.2 percent) indicated working at
least 40 hours per week.
Measures
Primary work location. Workers were asked to indicate their primary work location (i.e.
the location where they spend the most hours per week): the main office (n¼238), a
company-provided satellite location (n¼108), a client location (n¼150), or at home
(n¼82).
WLB support. A measure of WLB support was created for the current study.
Participants responded to two items using a five-point scale ranging from 1 (strongly
disagree) to 5 (strongly agree). Items included, “The work environment at [name of
organization] supports a balance between work and personal life,” and “The work
environment within my department/division supports balance between work and
personal life.” The items were correlated r(590) ¼0.81, p,0.001.
Job satisfaction. A job satisfaction scale was created for the current study (
a
¼0.79).
Participants responded to three items using a five-point scale ranging from 1 (strongly
disagree) to 5 (strongly agree). Items included, “Overall, I am satisfied with my job,” “I
recommend [name of organization] to others as a good place to work,” and “I am
satisfied with my current work schedule.”
Workplace inclusion. A four-item measure of workplace inclusion was created for
the current study (
a
¼0.89). Participants were asked to “Think of your primary work
location and indicate how much you feel about the following:” They responded to four
items using a five-point scale ranging from 1 (very little) to 5 (very much). Example
items included, “A sense of belonging to your department/division,” and “‘In the loop’
with what’s going on within your department/division.”
Demographic questions. Participants indicated their gender, whether they worked
part-time or full-time, age, and their tenure with the organization. Age was collected on
an interval scale in the following increments: 1 (18-24), 2 (25-24), 3 (35-44), 4 (45-54), 5
(55-65), and 6 (65 and over). Similarly, tenure was collected in five year increments 1
(less than 1 year), 2 (1-5), 3 (6-10), 4 (11-15), and 5 (more than 16 years). Participant also
indicated the extent to which having children or other dependents at home was a factor
in whether or not they would telework. Responses ranged from 1 to 3 (not a factor,
minor factor, major factor).
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Results
Because the measures used in this study have not been used in past research, we
performed a confirmatory factor analysis (CFA) using EQS 6.1. The CFA model
included a factor for WLB support, job satisfaction, and workplace inclusion with, two,
three and four items, respectively. Factors were allowed to correlate with one another
and the first factor loading of each factor was fixed to 1; all other paths were freely
estimated. The fit indices indicated a good fit
x
2
/df ratio of 2.71, comparative fit index
(CFI) of 0.99, root-mean square error of approximation (RMSEA) of 0.06, and
standardized root mean residual (SRMR) of 0.03. Hu and Bentler (1999) stated that an
RMSEA of 0.06 or below indicates good fit. The RMSEA in conjunction with the other
indices indicated very good measurement fit. Additionally, modification tests were
performed but no changes to the factor model significantly improved fit.
Prior to running hypotheses tests, control variables were examined to determine if they
should be included in the analyses. Gender (0¼woman, 1¼man) and work status
(0¼full-time, 1¼part-time) were dummy-coded. We examined demographics across the
four primary work locations (Table I). Additionally, we statistically tested whether
demographic variables were related to primary work location. Chi-square tests of
independence indicated that primary work location was significantly related to work
status (part-time, full-time) and marginally related to gender ( p¼0.07). Thus, we included
both as controls in our hypotheses tests. We also performed ANOVAs to determine if
work location was significantly related to continuous demographic variables (i.e. age,
tenure, impact of dependents). Only tenure was significantly related to primary work
location; therefore, we included it as a control variable. As shown in Table II,
full-time/part-time work status was the only demographic variable significantly related to
the outcome variables (i.e. WLB support and job satisfaction) used for hypothesis testing.
Table II presents descriptive statistics and zero-order correlations. Assumptions of
homogeneity of regression, homogeneity of variance, and normality of residuals were
supported. There were no univariate or multivariate outliers. Three hierarchical
multiple regression equations tested the three hypotheses. Primary work location was
transformed into two series of dummy-coded variables. The first series of codes were
created to test H1 and H2; home-based workers were coded zero to serve as the
reference group. The second set of codes was created to test H3; main office workers
were coded zero to serve as the reference group. Control variables (i.e. gender, full/part
time work status, and tenure) were entered in step 1 and dummy-coded work location
variables were entered in step 2.
Main office Satellite Client Home
MSDMSDMSDMSD
Gender 0.67 0.47 0.64 0.48 0.74 0.44 0.58 0.50
Full/part time 0.04 0.19 0.06 0.24 0.04 0.19 0.40 0.49
Age 3.81 1.28 3.69 1.54 3.96 1.15 3.97 1.22
Tenure 2.99 1.29 2.68 1.26 2.90 1.27 3.35 1.26
Impact of dependents 1.46 0.72 1.50 0.79 1.33 0.61 1.56 0.77
Notes: n¼578; gender and full/part time were dummy-coded (0 ¼female, 1 ¼male; 0 ¼full-time,
1¼part-time)
Table I.
Demographic information
by primary work location
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WLB support
H1 predicted that home-based workers would report higher WLB support than
workers at the other three primary work locations. The first step in the regression
equation was non-significant, F(3,565) ¼1.67, p¼0.17, R
2
¼0.01. The combination of
demographic variables did not significantly predict WLB support. However, work
status significantly predicted WLB support (
b
¼0.09, p,0.05); part-time workers
perceived greater support than full-time workers (see Table III). Primary work location
accounted for an additional 4 percent of the variance in WLB support beyond the
control variables, F(6,562) ¼4.81, p,0.001, DR
2
¼0.04. H1a was supported;
home-based workers reported significantly greater WLB support than satellite office
workers (
b
¼20.12, p,0.05). H1b was not supported; home-based and main office
workers reported similar levels of WLB support (
b
¼20.01, n.s.). H1c was supported;
home-based workers reported higher WLB support than client-based workers
(
b
¼20.20, p,20.01).
Job satisfaction
H2 predicted home-based workers would report similar levels of job satisfaction as
main office-based workers, and greater job satisfaction than satellite-based and
Variable M SD 1 2 3 4 5 6 7 8
1. Gender 0.67 0.47 –
2. Full/part time 0.09 0.28 20.20 *** –
3. Age 3.86 1.29 0.18 *** 0.04 –
4. Tenure 2.96 1.28 20.11 *0.17 *** 0.34 *** –
5. Impact of dependents 1.44 0.72 0.00 0.10 *20.15 *** 0.02 –
6. WLB support 4.17 0.95 20.02 0.10 *20.06 0.01 0.04 –
7. Job satisfaction 4.30 0.69 20.03 0.13 ** 20.01 0.05 0.06 0.68 ** –
8. Workplace inclusion 3.52 1.02 20.01 0.00 20.05 0.06 0.08 0.46 ** 0.52 ** –
Notes: n¼578; M ¼mean; SD ¼standard deviation; gender and full/part time were dummy-coded
(0 ¼female, 1 ¼male; 0 ¼full-time, 1 ¼part-time); *p,0.05; **
p,0.01; ***
p,0.001
BSEBB R
2
DR
2
Step 1 0.01
Gender 20.01 0.09 20.00
Work status 0.31 *0.14 0.09 *
Tenure 20.00 0.03 20.00
Step 2 0.05 *** 0.04 ***
Home (constant) 4.35 *** 0.17
Main office 0.02 0.12 0.01
Satellite office 20.28*0.14 20.12 *
Client location 20.41 ** 0.14 20.20 **
Notes: n¼578; gender and full/part time were dummy-coded (0 ¼female, 1 ¼male; 0 ¼full-time,
1¼part-time); work locations were dummy coded such that the home location ¼0; *p ,0:05,
**p ,0:01, ***p ,0:001
Table III.
Regression results for
predicting WLB support
Table II.
Means, standard
deviations, coefficient
alphas and
intercorrelations among
variables
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client-based workers. The first step in the regression equation was significant,
F(3,565) ¼3.14, p,0.05, R
2
¼0.02. The combination of demographic variables
significantly predicted job satisfaction. In the first step, only work status significantly
predicted job satisfaction (
b
¼0.12, p,0.01); part-time workers reported greater job
satisfaction than full-time workers (see Table IV). Primary work location accounted for
an additional 2 percent of the variance in job satisfaction beyond the control variables,
F(6,466) ¼2.86, p,0.01, DR
2
¼0.02, p,0.01. In support of H2a, home-based and
main office-based workers reported similar levels of job satisfaction (
b
¼20.06, n.s.).
H2b was partially supported. Home-based workers reported similar job satisfaction as
satellite-based workers (
b
¼0.80, n.s.). Home-based workers reported greater job
satisfaction than client-based workers (
b
¼20.16, p,0.05).
Inclusion
H3 predicted that main office workers would report greater inclusion than home-based,
satellite-based, and client-based workers. The first step of the regression equation was
non-significant, F(3,564) ¼0.844, n.s., R
2
¼0.00. None of the control variables
significantly predicted inclusion (see Table V). Primary work location accounted for an
additional 18 percent of the variance in inclusion beyond the demographic variables,
F(3,561) ¼20.19, p,0.001, DR
2
¼0.18. H3 was fully supported. Main office workers
reported higher inclusion than home (
b
¼20.10, p,0.05), satellite (
b
¼20.15,
p,0.001), and client-based workers (
b
¼20.47, p,0.001).
Additional analysis
As a follow up analysis, we considered whether WLB support and inclusion drive
differences in levels of job satisfaction across primary work location. As an exploratory
analysis, we entered WLB support and inclusion as control variables in step 1 and
re-ran the regression equation for H2. Inclusion (
b
¼0.27, p,0.001) and WLB
support (
b
¼0.55, p,0.001) significantly positively predicted job satisfaction. After
controlling for work status, tenure, gender, WLB support, and inclusion, work location
predicted incremental variance in job satisfaction (DR
2
¼0.02, p,0.001). Main office
workers reported significantly lower job satisfaction than home-based workers
BSEBB R
2
DR
2
Step 1 0.02 *
Gender 0.00 0.06 0.00
Work status 0.21 ** 0.11 0.12**
Tenure 0.02 0.02 0.04
Step 2 0.03 *0.01 *
Home (constant) 4.37 *** 0.12
Main office 20.09 0.10 20.06
Satellite office 20.14 0.11 20.08
Client location 20.24 *0.10 20.16 *
Notes: n¼578; gender and full/part time were dummy-coded (0 ¼female, 1 ¼male; 0 ¼full-time,
1¼part-time); work locations were dummy coded such that the home location ¼0; *p ,0:05;
**p ,0:01; ***p ,0:001
Table IV.
Regression results for
predicting job
satisfaction
Comparing
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locations
587

(
b
¼20.16, p,0.05). Satellite (
b
¼20.01, n.s.) and client-based workers (
b
¼0.06,
n.s.) reported similar levels of job satisfaction as home-based workers.
Discussion
This study examined differences in three affective outcomes across workers based at
four primary work locations. We examined three outcomes that are central to the issue
of telework: WLB support, job satisfaction, and inclusion. Our results generally
indicated that where workers spend the majority of their work day may alter their
relationship with their employer and explain the differences in outcomes. Research
tends to treat all types of telework similarly or to focus solely on home-based telework,
but these results suggest a need to recognize distinctions in the different types of
remote work. We discuss the findings of each of the hypothesized relationships below.
WLB support
Research has yielded mixed findings regarding the impact of telework on work-life
balance. The present study expanded on extant research by examining employee
perceptions of WLB support. As hypothesized, home-based workers reported higher
WLB support than satellite and client-based workers. Satellite and client-based work is
more likely to be a function of the organization’s or client’s needs. Furthermore, while
working at the satellite location is a form of telework, it may do little more than reduce
employee commute. Contrary to expectations, home-based workers reported similar
WLB support as main office-based workers. The finding that home-based employees
did not report greater WLB support may be because home-based work has benefits and
drawbacks, which may counteract one another.
Inclusion and job satisfaction
Drawing from Feldman and Gainey’s (1997) and Sparrow’s (2000) theoretical models,
we expected that telework status would be linked with differences in job satisfaction.
Whereas home-based teleworkers may experience the greatest amount of flexibility
and autonomy and appreciate the privileged status that telework symbolizes, they miss
the social context of work. In support of this notion, hypothesis tests revealed that
BSEBB R
2
DR
2
Step 1 0.00
Gender 20.01 0.09 20.00
Work status 20.05 0.16 20.01
Tenure 0.05 0.03 0.07
Step 2 0.18 *** 0.17 ***
Main office
(constant) 3.78 *** 0.13
Home 20.29 0.13 20.10 *
Satellite office 20.37 0.11 20.15 **
Client location 21.05 *** 0.10 20.47 ***
Notes: n¼578; gender and full/part time were dummy-coded (0 ¼female, 1 ¼male; 0 ¼full-time,
1¼part-time); work locations were dummy coded such that the main office location ¼0; *p,0.05;
**
p,0.01; ***
p,0.001
Table V.
Regression results for
predicting inclusion
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home-based and main office workers reported similar levels of job satisfaction;
home-based workers reported higher job satisfaction than client-based workers. Yet,
after controlling for differences in inclusion, the observed differences resembled our
original hypothesis: home-based workers reported higher job satisfaction than
main-office workers. Additional research is needed to understand the mechanisms
through which telework relates to job satisfaction. For example, research should
measure the relative importance of worker autonomy, flexibility, and inclusion on job
satisfaction and should determine if teleworkers do indeed regard their status as a
privilege. Personality is presumed to impact telework outcomes (Feldman and Gainey,
1997). Workers may differ to the extent that they value autonomy and flexibility and
require social interaction.
To our knowledge, the present study is the first to examine the issue of professional
isolation in a sample of both teleworkers and workers in traditional work
arrangements. The findings of this study support claims (e.g. Bartel et al., 2007;
Golden et al., 2008; Montreuil and Lippel, 2003) that social isolation is a drawback of
teleworking. Main office workers reported significantly higher inclusion than home,
satellite office, and client-based workers. Golden et al. (2008) found that the impact of
professional isolation is more severe as workers spend more time teleworking. Since
our focus was on primary work locations, we likely captured the telework-isolation
relationship at or near its highest point. Indeed, this may be why inclusion had a large
impact on the telework-job satisfaction relationship.
Strengths, limitations, and future directions
A strength of the present study is that it uses a large sample from a single
organization, providing the necessary preconditions for reliable results. Sampling
teleworkers from a single organization permits greater internal validity than
examining teleworkers across organizations because there are fewer
between-organization variables to act as confounding variables. Teleworkers often
work autonomously and typically only comprise a small segment within a single
organization; therefore, recruiting participants for telework research can be
challenging. Furthermore, the unique work setting of a teleworker and the
employee-organization relationship does not lend itself to replication in a contrived
research setting (e.g. a laboratory design). Although quasi-experimental designs do not
allow for control or manipulation as is required to rule out all extraneous variables,
quasi-experimental field studies such as this one may provide the most sound and
realistic method for making inferences about telework. Yet, extraneous variables
continue to be a concern. Therefore, additional research is needed to replicate the
findings and to examine other factors that may impact the relationship between work
location and outcome variables. For example, future research should examine if
workers based at different locations experience different leadership and performance
goals, perceived control and communication practices.
One of the merits of this research is that it identified a large effect between work
arrangement and workplace inclusion (18 percent). However, effect sizes for the impact
of work location on WLB support (4 percent) and job satisfaction (2 percent) were
relatively small (Cohen, 1977), especially given literature precedent suggesting WLB
issues and worker attitudes are central to telework (see Gajendran and Harrison, 2007).
The small observed effects may be the result of countervailing forces that drive WLB
Comparing
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589

support and job satisfaction counteract one another. Additionally, in the present study,
workers indicated their primary work location but were not asked how many hours per
week they spent at the primary location. Although this limitation is common to
telework research (Bailey and Kurland, 2003), it creates an issue of range restriction,
which likely attenuated the relationship between work location and outcome variables.
As Sparrow (2000, p. 203) suggests in his manuscript about the changing nature of
work designs and the changing nature of work, scaled survey items may be
“insensitive to the underlying changes in cognitive structures and the perceived
cause-and-effect reasoning of employees”. Sparrow’s logic suggests that qualitative
(versus quantitative) methods would better capture the expected relationships in our
study. The qualitative findings for WLB issues and job satisfaction discussed in the
introduction of this paper seem to support Sparrow’s (2000) conjecture. Furthermore,
employees adapt to their work conditions and report minor adjustments in work
attitudes and phenomena (Sparrow, 2000). Employees in various work conditions may
habituate to their work setting, attenuating the impact of work location on employee
attitudes and perceptions. Thus, future research should examine the impact of primary
work location over time, as it may yield larger observed effect sizes.
Practical implications
Our results suggest organizations must take action to improve the workplace inclusion
of employees who work away from the main office. For example, managers can setup
regular meetings with distant workers and keep them up to date on current issues and
involve them in decisions by telephone or e-mail. In addition, work teams should make
an effort to meet face-to-face on a regular basis. Organizations should also consider
implementing job location rotations for employees who report low workplace inclusion.
By switching work locations periodically, employees may benefit from changes to the
social atmosphere. When teleworkers are included, home-based telework may have
positive organizational implications through job satisfaction. Our exploratory analyses
suggest that when managers support employees’ work-life balance and foster
inclusion, teleworking from home may be a more advantageous work arrangement
than working from the main office in terms of job satisfaction.
Client-based workers reported lower WLB support, job satisfaction, and inclusion
than workers based at the main office and at home. In many cases, working from the
client location is a necessity. Therefore, managers may need to make special efforts to
engage client-based workers. Client-based workers may benefit from work-life balance
initiatives, stress management activities, and time away from the client location.
Conclusion
“Working from anywhere at any time,” as telework has been defined (Kurland and
Bailey, 1999) aggregates across multiple work arrangements. Using a large database
from a single organization, our findings suggest that work location explains significant
differences in WLB support, job satisfaction, and inclusion. WLB support and
inclusion impact differences in job satisfaction among workers at various locations.
Research needs to distinguish between different work arrangements rather than
broadly categorizing workers or focusing only on main office and home-based workers
as much of the literature has done.
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References
Bailey, D.E. and Kurland, N.B. (2003), “A review of telework research: findings, new directions,
and lessons for the study of modern work”, Journal of Organizational Behavior, Vol. 23,
pp. 383-400.
Baltes, B.B., Briggs, T.E., Huff, J.W., Wright, J.A. and Neuman, G.A. (1999), “Flexible and
compressed workweek schedules: a meta-analysis of their effects on work-related criteria”,
Journal of Applied Psychology, Vol. 84, pp. 496-513.
Bartel, C.A., Wrzesniewski, A. and Wiesenfeld, B. (2007), “The struggle to establish
organizational membership and identification in remote work contexts”, in Bartel, C.A.
(Ed.), Identity and the Modern Organization, Lawrence Erlbaum Associates, Mahwah, NJ,
pp. 253-72.
Baumeister, R.R. and Leary, M.R. (1995), “The need to belong: Desire for interpersonal
attachments as a fundamental human motivation”, Psychological Bulletin, Vol. 117,
pp. 497-529.
Beaumeister, R.F. and Tice, D.M. (1990), “Anxiety and social exclusion”, Journal of Social and
Clinical Psychology, Vol. 9, pp. 165-95.
Behson, S.J. (2002), “Which dominates: the relative importance of work-family organizational
support and general organizational context on employee outcomes”, Journal of Vocational
Behavior, Vol. 61, pp. 53-72.
Belanger, F. (1999), “Workers’ propensity to telecommute: an empirical study”, Information and
Management, Vol. 35, pp. 139-1153.
Campione, W. (2008), “Employed women’s well-being: the global and daily impact of work”,
Journal of Family and Economic Issues, Vol. 29, pp. 346-61.
Chevron, J. and Primeau, M. (1996), “The telecommuting innovation opportunity”, Journal of
Consumer Marketing, Vol. 13, pp. 40-8.
Cohen, J. (1977), Statistical Power Analysis for the Behavioral Sciences, Erlbaum, Hillsdale, NJ.
Cooper, C.D. and Kurland, N.B. (2002), “Telecommuting, professional isolation, and employee
development in public and private organizations”, Journal of Organizational Behavior,
Vol. 23, pp. 511-32.
Dambrin, C. (2004), “How does telework influence the manager-employee relationship?”,
International Journal of Human Resource Development & Management, Vol. 4, pp. 358-74.
Davis, D.D. and Polonko, K.A. (2003), “Distributed work in the virtual office: a national study of
telework and virtual outcomes”, paper presented at the meeting for the Society for
Industrial and Organizational Psychology, Orlando, FL, April.
DeWall, C.N. and Baumeister, R.F. (2006), “Alone but feeling no pain: effects of social exclusion
on pain tolerance and pain threshold, affective forecasting, and interpersonal empathy”,
Journal of Personality and Social Psychology, Vol. 91, pp. 1-15.
Feldman, D.C. and Gainey, T.W. (1997), “Patterns of telecommuting and their consequences:
framing the research agenda”, Human Resource Management Review, Vol. 7, pp. 369-88.
Ford, M.T., Heinen, B.A. and Langkamer, K.L. (2007), “Work and family satisfaction and conflict:
a meta-analysis of cross-domain relations”, Journal of Applied Psychology, Vol. 92,
pp. 57-80.
Gajendran, R.S. and Harrison, D.A. (2007), “The good, the bad, and the unknown about
telecommuting: a meta-analysis of the psychological mediators and individual
consequences”, Journal of Applied Psychology, Vol. 92, pp. 1524-41.
Comparing
telework
locations
591

Garrett, R.K. and Danziger, J.N. (2007), “Which telework? Defining and testing a taxonomy of
technology-mediated work at a distance”, Social Science Computer Review, Vol. 25,
pp. 27-47.
Golden, T.D. (2006), “The role of relationships in understanding telecommuter satisfaction”,
Journal of Organizational Behavior, Vol. 27, pp. 319-40.
Golden, T.D. and Veiga, J.F. (2005), “The impact of extent of telecommuting on job satisfaction:
resolving inconsistent findings”, Journal of Management, Vol. 31, pp. 301-18.
Golden, T.D., Veiga, J.F. and Dino, R.N. (2008), “The impact of professional isolation on
teleworker job performance and turnover intentions: does time spent teleworking,
interacting fact-to-face, or having access to communication-enhancing technology
matter?”, Journal of Applied Psychology, Vol. 93, pp. 1412-21.
Golden, T.D., Veiga, J.F. and Simsek, Z. (2006), “Telecommuting’s differential impact on
work-family conflict: is there no place like home?”, Journal of Applied Psychology, Vol. 91,
pp. 1340-50.
Greenhaus, J.H., Parasuraman, S. and Wormley, W.M. (1990), “Effects of race on organizational
experiences, job performance evaluations, and career outcomes”, Academy of Management
Journal, Vol. 33, pp. 64-86.
Hackman, J.R. and Oldham, G.R. (1980), Work Redesign, Addison-Wesley, Reading, MA.
Hartig, T., Kylin, C. and Johansson, G. (2007), “The telework tradeoff: stress mitigation versus
constrained restoration”, Applied Psychology: An International Review, Vol. 56, pp. 232-53.
Hayes, B.C., Bartle, S.A. and Major, D.A. (2002), “Climate for opportunity: a conceptual model”,
Human Resource Management Review, Vol. 12, pp. 445-68.
Hilbrecht, M., Shaw, S.M., Johnson, L.C. and Andrey, J. (2008), “‘I’m home for the kids’:
contradictory implications for work-life balance of teleworking mothers”, Gender, Work, &
Organization, Vol. 5, pp. 454-76.
Hill, E.J., Ferris, M. and Ma
¨rtinson, V. (2003), “Does it matter where you work? A comparison of
how three work venues (traditional office, virtual office, and home office) influence aspects
of work and personal/family life”, Journal of Vocational Behavior, Vol. 63, pp. 220-41.
Hill, E.J., Miller, B.C., Weiner, S.P. and Colihan, J. (1998), “Influences of virtual office on aspects of
work and work/life balance”, Personnel Psychology, Vol. 51, pp. 667-83.
Hinds, P.J. and Bailey, D.E. (2003), “Out of sight, out of sync: understanding conflict in
distributed teams”, Organization Science, Vol. 15, pp. 615-32.
Hu, L. and Bentler, P.M. (1999), “Cutoff criteria for fit indexes in covariance structure analysis:
conventional criteria versus new alternatives”, Structural Equation Modeling, Vol. 6,
pp. 1-55.
Huws, U., Podro, S., Gunnarsson, E., Weijers, T., Arvanitaki, K. and Trova, V. (1996),
Teleworking and Gender, Institute of Employment Studies, Brighton.
Jones, W.H. (1990), “Loneliness and social exclusion”, Journal of Social and Clinical Psychology,
Vol. 9, pp. 214-20.
Konradt, U., Hertel, G. and Schmook, R. (2003), “Quality of management by objectives,
task-related stressors, and non-task related stressors as predictors of stress and job
satisfaction”, European Journal of Work & Organizational Psychology, Vol. 12, pp. 61-80.
Kurland, N.B. and Bailey, D.E. (1999), “Telework: the advantages and challenges of working
here, there, anywhere, and anytime”, Organizational Dynamics, Vol. 28, pp. 53-68.
Kurland, N.B. and Cooper, C.D. (2002), “Manager control and employee isolation in
telecommuting environments”, Journal of High Technology Management Research,
Vol. 13, pp. 107-26.
JMP
25,6
592

Lapierre, L.M. and Allen, T.D. (2006), “Work-supportive family, family-supportive supervision,
use of organizational benefits, and problem-focused coping: implications for work-family
conflict and employee well-being”, Journal of Occupational Health Psychology, Vol. 11,
pp. 169-81.
Lombard, M. and Ditton, T. (1997), “At the heart of it all: the concept of presence”, Journal of
Computer Mediated Communication, Vol. 3, pp. 1-43.
Major, D.A., Verive, J.M. and Joice, W. (2008), “Telework as a dependent care solution: examining
current practice to improve telework management strategies”, The Psychologist-Manager
Journal, Vol. 11, pp. 65-91.
Marsh, K. and Musson, G. (2008), “Men at work and at home: managing emotion in telework”,
Gender, Work, & Organization, Vol. 15, pp. 31-48.
Mesmer-Magnus, J.R. and Viswesvaran, C. (2005), “Convergence between measures of
work-to-family and family-to-work conflict: a meta-analytic examination”, Journal of
Vocational Behavior, Vol. 67, pp. 215-32.
Michel, J.S. and Hargis, M.B. (2008), “Linking mechanisms of work-family conflict and
segmentation”, Journal of Vocational Behavior, Vol. 73, pp. 509-22.
Montreuil, S. and Lippel, K. (2003), “Telework and occupational health: a Quebec empirical study
and regulatory implications”, Safety Science, Vol. 41, pp. 339-59.
Netemeyer, R.G., Boles, J.S. and McMurrian, R. (1996), “Development and validation of
work-family conflict scales”, Journal of Applied Psychology, Vol. 81, pp. 400-10.
Olson, M.H. and Primps, S. (1984), “Working at home with computers: work and non-work
issues”, Journal of Social Issues, Vol. 40, pp. 97-112.
Russell, H., O’Connell, P.J. and McGinnity, F. (2009), “The impact of flexible working
arrangements on work-life conflict and work pressure in Ireland”, Gender, Work &
Organization, Vol. 16, pp. 73-97.
Shockley, K.M. and Allen, T.D. (2007), “When flexibility helps: another look at the availability of
flexible work arrangements and work-family conflict”, Journal of Vocational Behavior,
Vol. 71, pp. 476-93.
Siha, S.M. and Monroe, R.W. (2006), “Telecommuting’s past and future: a literature review and
research agenda”, Business Process Management Journal, Vol. 12, pp. 455-82.
Sparrow, P.R. (2000), “New employee behaviours, work designs and forms of work organization:
what is in store for the future of work?”, Journal of Managerial Psychology, Vol. 15,
pp. 202-18.
Sudan, S.K., Ryan, S., Drake, S.D., Sandler, M., Boggs, R. and Giusto, R. (2007), “Worldwide
Mobile Worker Population 2007-2011 Forecast (IDC No. 209813)”, International Data
Corporation, available at: www.idc.com/getdoc.jsp?containerId¼209813 (accessed 12 March
2008).
Sullivan, C. and Lewis, S. (2001), “Home-based telework, gender, and the synchronization of work
and family: perspectives of teleworkers and their co-residents”, Gender, Work and
Organization, Vol. 8, pp. 123-45.
Tabachnick, B. and Fidell, L. (2007), Using Multivariate Statistics, 5th ed., Allyn and Bacon,
Boston, MA.
Thompson, C.A., Jahn, E.W., Kopelman, R.E. and Prottas, D.J. (2004), “Perceived organizational
family support: a longitudinal and multi-level analysis”, Journal of Managerial Issues,
Vol. 16, pp. 465-565.
Comparing
telework
locations
593

Towers, I., Duxbury, L., Higgins, C. and Thomas, J. (2006), “Time thieves and space invaders:
technology, work and the organization”, Journal of Organizational Change Management,
Vol. 19, pp. 593-618.
Verive, J.M., Morganson, V.J. and Albiero, R. (n.d.), “Telework: a centuries-old idea with modern
value and appeal”, Trendlines, in press.
Further reading
Rubery, J., Cooke, F.L., Earnshaw, J. and Marchington, M. (2003), “Inter-organizational relations
and employment in a multi-employer environment”, British Journal of Industrial Relations,
Vol. 41, pp. 265-89.
About the authors
Valerie J. Morganson is a Doctoral Candidate in industrial-organizational psychology at Old
Dominion University. Her research centers on helping individuals and organizations to overcome
career development barriers. Within this theme, she studies interventions to achieve work-life
balance and the impact of gender on career development. Her research has appeared in The
Psychologist-Manager Journal,Career Development Quarterly,Workspan, and other edited
volumes. Additionally, she has presented her work at numerous national and international
conferences. As an applied professional, Ms Morganson has interned for the City of Norfolk and
has worked as a research fellow at ICF, International to provide statistical and management
consulting to private and public sector clients. Valerie J. Morganson is the corresponding author
and can be contacted at vmorgans@odu.edu
Debra A. Major is a Professor of Psychology at Old Dominion University. Her research
focuses on career development issues, including barriers faced by women and minorities,
developmental relationships at work, and the work-family interface. She is interested in how
inclusive workplace climates and supportive relationships with coworkers and supervisors
improve individual outcomes. Her work has appeared in scholarly journals, including Career
Development Quarterly, Human Resource Development Quarterly, Human Resource
Management, Human Resource Management Review, Journal of Applied Psychology, Journal
of Business and Psychology, Journal of Occupational Health Psychology, Psychologist-Manager
Journal and Journal of Organizational Behavior, as well as numerous edited volumes. Her
research has been funded by the Health Resources and Services Administration, NASA, and the
National Science Foundation. She presently serves on the editorial boards of Journal of
Organizational Behavior, Journal of Management and Journal of Business and Psychology.
Kurt L. Oborn is a Senior Analyst in Organization Development at Collective Brands
Incorporated and a PhD candidate in Industrial-organizational Psychology at Old Dominion
University. His research interests center on the development and maintenance of
leader-subordinate relationships and effective leader behaviors. He is focused on creating
work environments and systems that foster employee satisfaction and work-life balance while
maximizing the potential of both employees and organizations.
Jennifer M. Verive is a founder and CEO of White Rabbit Virtual, Inc., a woman-owned firm
that develops research-based surveys and training programs for remote and mobile workers, and
helps organizations implement all types of flexible work programs (telework, telecommuting,
compressed workweeks, etc.). A passionate telework educator and advocate, Jennifer focuses on
helping individuals and companies develop the knowledge, skills, and abilities needed to work
effectively in the virtual workplace. Dr Verive speaks and publishes in the flexible work arena
often, is a member of WorldatWork’s Telework Advisory Group, and is part-time faculty at
Western Nevada College in Carson City, Nevada.
Michelle P. Heelan, PhD is an Industrial/Organizational Psychologist with 15 years of
experience in organizational assessment and development. Dr Heelan helps her clients assess the
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bottom-line impact of various human resource initiatives, to improve both internal and external
effectiveness, and to maximize high performance. In her capacity as Telecommuting Advantage
Group’s East Coast Business Liaison, Dr Heelan has provided consulting support to both private
and public sector organizations. She has been a key contributor to the research, design, and
development of TAG’s assessment tools and on-line surveys. Dr Heelan has also created and
facilitated a wide range of action-based training courses and workshops, including a Flexwork
Metrics Worksession that helps clients design flexwork programs more likely to obtain
stakeholder buy-in and generate measurable results. Her clients include the Department of
Justice (including the Bureau of Alcohol, Tobacco & Firearms), Department of Agriculture,
National Institutes of Health, Department of Defense, MITRE, Marriott-International and
Northrop Grumman.
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