New ways of working does flexibility in time and location o.docx

New ways of working: does flexibility in
time and location of work change work
behavior and affect business outcomes?
Merle M. Bloka,*, Liesbeth Groenesteijna,b, Roos Schelvisa
and Peter Vinka,b
a, TNO, P.O. Box 718, 2130 AS Hoofddorp, The Netherlands.
b Faculty of Industrial Design Engineering, Delft University of
Technology, Landbergstraat 15, 2628 CE Delft,
The Netherlands.
Abstract. In the changing modern economy some new factors
have been addressed that are of importance for productivity and
economic growth, such as human skills, workplace organization,
information and communication technologies (ICT) and
knowledge sharing. An increasing number of companies and
organizations are implementing measures to better address these
factors, often referred to as ‘the New Ways of Working
(NWW)’. This consists of a large variety of measures that
enable flexi-
bility in the time and location of work. Expectations of these
measures are often high, such as a reduction in operating costs
and an increase of productivity. However, scientific proof is
still lacking, and it is worth asking whether al these
implementa-
tions actually cause a change in work behavior and effect
business outcomes positively. This article describes a case study
of
three departments (total of 73 employees) that changed from a
traditional way of working towards a new way of working.
Questionnaires and a new developed objective measurement
system called ‘[email protected]’ were used to measure changes
in work

behavior (i.e. increased variation in work location, work times
and a change towards NWW management style) and the effect
on business objectives such as knowledge sharing, employees
satisfaction, and collaboration.
Keywords: new ways of working, task facilitating office,
knowledge worker, work behavior, business objectives
*Corresponding author: Merle Blok. E-mail: [email protected]
1. Introduction
The modern economy is changing from agriculture
and industrial manufacturing to a service and knowl-
edge driven economy. Knowledge is recognized as
the driver of productivity and economic growth, and
statistics form the OECD studies show that the num-
ber of employees working for knowledge- intensive
service sector is increasing [6]. Knowledge work is
supported by a revolution in new ICT applications
and communication networks. These innovations has
changed our perceptions on work and made it possi-
ble to work at any location at any time [5]. The pro-
liferating use of information has long been seen as
‘the’ aspect that would bring us higher productivity
and better business outcomes. However aspects such
as human talent can be seen of even greater impor-
tance, since that makes it possible to share knowledge,
adapt and innovate [1]. It is therefore argued that em-
ployees, especially knowledge workers, should be
more empowered to work more efficiently and effec-
tively [4]. This empowerment implies offering the
employees more self control and freedom by intro-
ducing flexible work arrangements. This transforma-
tion is often referred to as ‘the New Ways of Work-

ing’ (NWW) and consist of changes that take place at
four aspects:1) the physical workspace, 2) (ICT)
technology, 3) organization & management and 4)
work culture. The physical workspaces refers to
NWW measures that increasing the flexibility where
and when to work by introducing flexible work hours,
telework and creating flexible workplaces at the of-
fice that better suits the work task. Introducing ICT
technologies implies that employees are supported
with technologies that allows them to be connected
and able to collaboration always and everywhere. The
1051-9815/12/$27.50 © 2012 – IOS Press and the authors. All
rights reserved
5075Work 41 (2012) 5075-5080
DOI: 10.3233/WOR-2012-0800-5075
IOS Press
third NWW aspect: ‘organization and management’
is important since managing employees might be-
come a big challenge when it is not longer visible
were, when and what employees are working on. It is
therefor important that managers have trust in there
employees, focus more on output instead of presence
at the office, and provide them with more autonomy
by stimulating own initiative. Changes in work cul-
ture implies that an open culture, with focus on in-
formation sharing and collaboration in networks is
created.
Many organizations see potential opportunities in
the transition to the NWW and the number of organi-
zations that have implemented a form of NWW is

rapidly increasing. This is not only in order to en-
hance productivity growth, but is also seen as a nec-
essary preparation for the upcoming societal issues.
Attracting skilled professionals will get more difficult,
since we are facing a demographic shift in aging
populations. And there is an increase in road traffic,
causing serious traffic infarcts and a loss in produc-
tive work time. The NWW measures not only offer
differentiation in starting and ending time of work, it
also offers the possibility to work from any other
remote location. The Telework Trendlines 2009 [7]
reported that the number of U.S. employees who
worked remotely at least one day per month increased
39% in two years from approximately 12.4 million in
2006 to 17.2 million in 2008.
Working from remote locations affect the purpose
of the office building, making it less important for the
performance of individual work tasks, and more im-
portant for work activities such as collaboration, face-
to-face meetings and knowledge sharing [2]. To bet-
ter suit these work activities, a growing number of
organization lower the total amount of office building
space, and task facilitating offices. This often consists
of transparent offices including a large variety of
shared workplaces, such as meeting rooms, project
places, lounge corners and concentration arias [3].
Although the expectations of the NWW measures
are often high, scientific proof is still lacking. It is
important to know more about the effects to provide
organizations with a better understanding and (at
forehand) insight in the effects of their NWW in-
vestment or policy decisions regarding the implemen-
tation. It is still unknown how implementations of
NWW measures affect work behavior, in means of

where and when the employees work, and how this
relates to business objectives such as increased pro-
ductivity by improvements in collaboration, knowl-
edge sharing and employee satisfaction.
In this paper a case study is presented of a Dutch
organization with a pilot group consisting of three
departments that changed from a traditional way of
working towards a new way of working. The changes
includes a new flexible office layout were workplaces
are shared, introduction of social ICT and the ability
to work from home or any other remote location at
flexible work hours. Their objective was to increase
collaboration, knowledge sharing and employees sat-
isfaction, and thereby enhance the productivity of the
employees, while at the same time reducing cost by
decreasing the amount of total office space used. The
effects on work behavior and on the aimed business
objectives are monitored every half year for four
times in total. A questionnaire and a new developed
objective measuring method called ‘[email protected]’ to
monitor changes in work location are used. The re-
sults from the first two measures will be presented in
this paper. This article is aimed to provide an answer
to the research question: “What are the effects of new
ways of working in a task facilitating office on work
behavior, and does this positively effect collaboration,
employee satisfaction and knowledge sharing?
2. Method
A group of 73 employees from three different de-
partments participated in this study. All participants
moved from a traditional work environment where
each department had his own work space, to one

shared work area consisting of a large variety of dif-
ferent shared workspaces such as brainstorm area’s,
meeting rooms, silent open workspaces and project
places. Digital smart boards were introduced to sup-
port project work, as well as laptops, cellphones, and
access to the business network in order to enable em-
ployees to work everywhere throughout the depart-
ment.
2.1. Questionnaire
A web based internet questionnaire was developed
and carried out twice, once while implementing the
new ways of working (M1), and one six months later
in the new office environment (M2). All employees
of the three different departments participated in the
study. The questionnaire was conducted in order to
measure NWW awareness, change in work behavior
and the effects on business outcomes. Questions on
change in behavior consisted of questions on flexibil-
ity in work location and workplace, and if a NWW
M.M. Blok et al. / Does Flexibility in Time and Location of
Work Change Work Behavior and Affect Business
Outcomes?5076
management style was created in the new work envi-
ronment. Since the first measure (M1) was conducted
while at the same time the implementation of the new
way of work was implemented, the questionnaire
consisted of some questions to retrieved information
of the actual stage of the three differed departments,
such as habitation to the new flexible work environ-
ment.

Questions on NWW management style consisted
of items measuring the degree to which managers
behaved as a NWW role model, if they listened and
showing interest in the work of the employees, and
questions on the focus and agreements on results, the
feasibility of the results and whether the employees
perceived enough autonomy
2.2. [email protected]
In the new work environment the participant had
greater flexibility in the timing and location of work.
It was therefore assumed that employees would more
frequently change workplaces and work location (at
the office, at home, while traveling or at the client
office). In order to measure actual behavioral changes
in work place and location a ‘[email protected]’ system
was developed and tested. The method consists of an
automatic short message services, were texts mas-
sages were send to the business cellphones of sixty
employees five times a day at standardized moments
in time for a period of two weeks. The employees
were asked to respond immediately to each text mes-
sage with a message code that described their work-
place, work location and the task they were perform-
ing. In order to make the response as less time con-
suming as possible, response codes were formulated
and profited to the employees at small pocketsize
plastic cards (see figure 1) and the workplaces at the
office were labeled with code numbers. The
[email protected] measurement was conducted in the new
office situation only and corresponded in time with
the second questionnaire measure (M2).
2.3. Statistics

Descriptive statistics were used to describe the re-
sults from the questionnaire and [email protected] Within-
subject t-test analysis (p<0.05) was used on the ques-
tionnaire data of participants that participated in both
the M1 and M2 questionnaire only, in order to detect
significant effects of NWW on collaboration, em-
ployees satisfaction and knowledge sharing.
[email protected] Codes for short message service
For example O1IC
Location
O# = Office + workplace number
OD = Office, working at a different de-
partment
OL = Working at a different office loca-
tion
H = Home
T = Traveling
WE = Working extern (at client office)
How?
I = individual
T1 = working together at one location
T2 = working together at two locations
G1 = group work at one location
G2 = group work at two or more loca-
tions
What?
C = concentration task

R = routine task
F = formal meeting
IF = informal meeting
P = Phone call
B = Break
N = Not working
Figure [email protected] codes that were used in the short
massage service.
3. Results
All 73 employees of the three departments received
the first online questionnaire (M1) and half a year
later 60 of them received the second questionnaire
(M2). In total 58 participants (average age 45; 59%
male) filled out the first questionnaire, while 52 em-
ployees (average age 44; 53% male) responded to the
second questionnaire. A total of 39 participants filled
out both questionnaires. The job functions of the sub-
jects existed of either manager, project manager, pro-
ject support or advisor.
3.1. Implementation awareness of NWW measures
Questionnaire data on the status of implementation of
the new ways of working and the habituation to the
new flexible work layout showed that none of the
participants were fully habituated to the new flexible
work layout, and a part of the participants (28%)
were still working at the traditional office at the time
the first questionnaire was filled out (M1). Half year
later, at the time the second questionnaire (M2) was
Work Change Work Behavior and Affect Business Outcomes?

5077
filled out all participants were working at the flexible
work layout. More than half (54%) of the participants
were entirely habituated and 30% was habituated
somewhat. A total of 16% stated that they were not
yet habituated to the new flexible work layout.
In figure 2 the results are shown for differed state-
ments that were addressed in the questionnaire on the
possibility to work flexible. The results show an in-
crease over time between M1 and M2 in the experi-
enced possibility to work at flexible work hours at the
office, the availability of sufficient ICT facilities and
access to business networks from home or other re-
mote work locations. These results indicate that the
participant were aware of the new possibilities that
were created by introducing the new way of working.
Figure 2. The ability to work flexible in time and the
accessibility
and sufficient ICT facilities to work from remote locations at
measurement M1 (n= 57) and M2 (n=50)
Besides changes in physical workspace and (ICT)
technology, implementations of the NWW also im-
plies changes in organization & management and a
change towards a suitable work culture. The results
on NWW management style items of M1 and M2
(see figure 3) show that the overall score on NWW
role model and the focus on results improved over-
time, although there is still a large percentage of em-
ployees that did not experience the manager as a

NWW role model (31%) with forces on results (15%).
The other aspects of the NWW management style
aspect show a decrease over time.
Figure 3. The average score on question items measuring NWW
management style M1n=48, M2n =48.
3.2. Changes in flexible work behavior
In order to investigate whether the actual implemen-
tation of NWW measures actually caused a change in
work behavior the participants were asked where they
performed their work tasks. The results in figure 4
show that there were no big changes in amount of
working hours spend on different work locations.
Working at home increased from 4.5 hours per week
at M1 to 5.5 hours at M2, which was not as much as
was expected, since at M2 working from home was
officially enabled. The biggest increase was seen for
working at the client office which increased from 5.8
hours per week to 7.4 hours per week.
Figure 4. The number of hours per week worked at different
loca-
tions, at measurement M1 (n= 57) and M2 (n=50).
The results from [email protected] (see figure 5) show that
60% of the work time was spend at the office build-
ing, of which 40% of the working time was spend at
the flexible work layout. A total of 18% of the work-
ing time was spend at home, an another 13% was
spend teleworking extern at the client office.

Outcomes?5078
Figure 5. The number of hours per week worked at different
loca-
tions, at measurement M1 (n= 57) and M2 (n=50)
At the traditional office the employees had owned
workstations, and did not have a variety of different
workplaces except for meeting rooms and coffee cor-
ners. The new flexible office layout did offer a wide
variety of different workspaces (M2). In the
[email protected] measurement the percentage of work
time spend at each workplace was measured for M2
(see figure 6). The workplaces at the open area (a
total of 31 workplaces), were used for 61% or the
time. The three meeting rooms and team rooms were
used 13% of the time, followed by meeting/lounge
rooms. The phone booths were only used 1% of the
time.
Figure 6. The average number of hours spend at different work-
places at the office for M2 (n=49), # number of workspaces.
3.3. Effect on business outcomes
So far, the results have shown that the employees did
experience an increase in possibilities to work flexi-

ble in time and location and a small change in behav-
ior caused by these increased flexibilities was visible.
Results on the business objectives were measured on
a scale from 1 ‘very low’ to 7 ‘very high’. Results did
not show any change between M1 and M2 for col-
laboration and employees’ satisfaction and the suit-
ability of the environment to perform the work tasks,
while knowledge sharing was decreased significantly
(see Fig. 7).
Figure 7. Average scores for M1 and M2 on scale from 1 to 7 (1
=
very low, 7 = very high).
4. Discussion
In this research study it was investigated whether the
introduction of new way of working measures caused
changes in work behavior, leading to positive effects
on business objectives. The results of this study
showed that the participants were aware of the in-
creased possibility to work at different locations, and
they experienced an increase in availability of ICT
facilities and better remote access to business net-
works. It is interesting to see that even after halve a
year still not all of the employees were habituated.
Results on the implementation of a NWW
management style did not show overall positive re-
sults. Four out of six questionnaire items on NWW
management style showed a decrease over time. This
is a interesting result, since it was expected that the

NWW management style was implemented and
therefor the experienced NWW management style
would improve. It was certainly not expected that it
would decrease. This result might indicate that when
NWW is introduced the importance of a NWW man-
agement style is of greater importance, which might
created increased awareness of the absence of NWW
management style resulting in lower scores.
As mentioned before, NWW consist of changes that
Work Change Work Behavior and Affect Business Outcomes?
5079
take place at four aspects, the physical workspace,
(ICT) technology, organization & management and
work culture. From the results we might conclude
that at least two out of four NWW aspects (i.e. phys-
ical workspace and ICT technologies) were success-
fully implemented. The implementation of manage-
ment style was not conducted successfully yet, and
should be given more priority. Changing the organ-
izational culture might be of greater effort and take
up more time. It will be interesting to see if im-
provements are seen at a later stage in the third or
fourth measure.
Studying the results on change in behavior,
some indications are found for the hypothesis that
implementing NWW measures changes the work
behavior. For instance, more different work locations
and workplaces throughout the office were used. It is
expected that there will be a greater change in work
behavior when all four NWW aspects are imple-

mented successfully.
Not finding any improvements in the busi-
ness objectives can have at least two important rea-
sons. First of all it can be explained by the fact that
not all four aspects of NWW are implemented well
enough to cause a significant change in work behav-
ior, and therefore the business objective are not af-
fected. Second of all it is possible that although ex-
pected by NWW believers, the NWW measures do
not affect of improve the selected business objectives.
The NWW might increase ad hoc interaction and
communication of colleagues, but this does not imply
improvements in knowledge sharing or collaboration
Even if knowledge sharing and collaboration at the
office itself improves, this might be counteracted by
the fact that more time is spend working at home or
at other remote locations where less ad hoc interac-
tion and communication has takes place.
This case study provides us with some inter-
esting insights in some of the effects of the NWW
measures. It is difficulty to set up a good research
study to measure the effects of the NWW since in
reality it is difficult to isolate the effects of NWW in
organizations, and other changes that might affect the
results as well are often taking place as well. In order
to gain good inside in the effect of NWW interven-
tion it is important to measure the situation some time
before the implementation takes place and a period of
time after, when al the short term effects caused by
the change toward the NWW measures has disap-
peared. Unfortunately in this study at the moment of
the M1 measure the implementation was already part-
ly started and some of the employees had already
moved to the new flexible office layout a few days

prior to the measure. Even so, it was not expected
that the recent movement did cause an immediate
change in business objectives and it is expected that
when employees get more habituated to the flexible
work environment it will have a positive effect on
knowledge sharing, collaboration, satisfaction and
experienced suitability of the work environment.
Further research on this topic will be done,
since two other measures will be performed. It will be
interesting to see whether all four NWW aspects will
be further implemented successfully. And if the be-
havior of the employees will change towards a more
flexible work behavior such as a further increase in
hours worked at home or remote, changes in work
time and more flexibility in the use of different
workplaces at the office. It will then be possible to
see if a further increase in work behavior will signifi-
cantly improve the business objectives.
References
[1] S. Aravaniti and E.N. Loukis, ICT, human capital,
workplace
organization and labour productivity: A comparative study
based on firm-level data for Greece and Switzerland, Informa-
tion, Economics and Policy 21, 2009, pp. 43-61.
[2] M. Blok, E. de Korte., L. Groenesteijn, M. Formanoy, P.
Vink,
The effects of a task facilitating working environment on of-
fice space use, communication, concentration, collaboration,
privacy and distraction. Proceedings of the 17th World Con-
gress on Ergonomics, Bejing, 2009.
[3] E.M. de Croon, J.K. Sluiter, P.P.F.M. Kuijer, and M.H.W.

Frings-Dresen, The effect of office concepts on worker health
and performance: a systematic review of the literature, Ergo-
nomics, 48: 2, 2005, pp. 119-34.
[4] C. Ichniowski, T.A. Kochan, D.I. Levine, C. Olson, G.
Strauss,
What works at work: overview and assessment. In: Ichniowski,
C., Levine, D.I., Olson, C., Strauss, G. (Eds.), The American
Workplace. Skills compensation and Employee Involvement.
Cambridge University Press, Cambridge, 2000 pp. 1–37.
[5] S.Y. Lee, J.L. Brand, Effects of control over office
workspace
on perceptions of the work environment and work outcomes,
Journal of Environmental Psychology, 25, 2005, pp.323–333.
[6] OECD, Organization for economic co-operation and
develop-
ment.. The knowledge-based economy. General distribution
OCDE//GD(96)102, 1996.
[7] WorldatWork Research. Flexible Work Arrangements for
Nonexempt Employees, 2009. WorldatWork Telework trend-
lines (2009),
http://www.workingfromanywhere.org/news/Trendlines_2009.
pdf.
Outcomes?5080
Copyright of Work is the property of IOS Press and its content
may not be copied or emailed to multiple sites or

posted to a listserv without the copyright holder's express
written permission. However, users may print,
download, or email articles for individual use.
O R I G I N A L P A P E R
Gender Differences in Perceived Business Success and Profit
Growth Among Family Business Managers
Yoon G. Lee • Cynthia R. Jasper •
Margaret A. Fitzgerald
Published online: 25 September 2010
� Springer Science+Business Media, LLC 2010
Abstract Using data from the 1997–2000 National
Family Business Surveys (NFBS), this study investigated
the effect of gender on business success and profit growth
among family businesses. The Ordinary Least Squares
(OLS) results indicate that all else being equal, female
managers perceived their businesses as more successful
than male managers, and they reported more profit growth
between 1996 and 1999 than male managers. The results of

the dummy variable interaction approach also show that a
differential response existed in profit growth over time
between female and male managers in relation to health
status, business liabilities, business size, and whether the
business was home-based. This study concludes that there
are many distinct differences between male and female
managers in business performance.
Keywords Business success � Family businesses � Female
manager � Gender differences � Profit growth
Introduction
According to the Small Business Administration (2002),
between 1997 and 2002, the number of women-owned
businesses grew at a faster rate than the number of U. S.
businesses overall. In 2002, women owned 6.5 million
nonfarm businesses in the United States and generated
$939.5 billion in business revenues (U.S. Census Bureau
2002). Nearly 85% of all businesses owned by women are
sole proprietorships (SCORE 2009). Consequently, more

and more women have become managers of their family
businesses and women managers play an important role in
the economy and industry of the United States. Therefore,
to better understand this recent change in management, the
purpose of this study is to provide a comparison of the
characteristics of the family businesses run by female
managers to those owned by male managers, to examine
the effect of gender on business success and profit growth,
and to investigate what factors are associated with business
performance in terms of perceptions of business success
and business profits.
The analyses of this study are based on panel data from
the National Family Business Survey in the United States
collected in 1997 and its consequent survey data set
obtained in 2000. By using panel data, this study allows
This paper reports results from the Cooperative Regional
Research
Project, NE-167 ‘‘Family Business Viability in Economically
Vulnerable Communities’’, partially supported by the

Cooperative
States Research, Education, and Extension Service (CSREES);
U.S.
Department of Agriculture; Baruch College, the experiment
stations
at the University of Arkansas, University of Hawaii at Manoa,
University of Illinois, Purdue University (Indiana), Iowa State
University, University of Minnesota, Cornell University (New
York),
North Dakota State University, The Ohio State University,
Oklahoma
State University, Utah State University, and University of
Wisconsin-
Madison.
Y. G. Lee (&)
Department of Family, Consumer, and Human Development,
Utah State University, 218 Family Life,
2905 Old Main Hill, Logan, UT 84322-2905, USA
e-mail: [email protected]
C. R. Jasper
Department of Consumer Science, School of Human Ecology,
University of Wisconsin-Madison, 1305 Linden Drive,

Madison, WI 53706, USA
M. A. Fitzgerald
Department of Human Development and Family Science,
North Dakota State University, P. O. Box 6060, Dept. 2615,
Fargo, ND 58108-6050, USA
123
J Fam Econ Iss (2010) 31:458–474
DOI 10.1007/s10834-010-9226-z
one to measure the percentage change in business profit
growth over time in family businesses. The study is
informed by Sustainable Family Business Theory (Danes
et al. 2008a; Stafford et al. 1999) with emphasis on human,
social, and financial capital to explain similarities and
differences in performance outcomes between male and
female run businesses. This descriptive study focuses on
the variables such as human capital, financial and social

capital of managers, business activities of managers, and
business demographics that could influence performance
outcomes of family businesses. The unique contribution of
this study will be to fill the gap in the literature about
gender differences in profit growth over time in family
businesses.
Literature Review
Comparison of Female and Male Business Managers
Many studies focus on the comparison between female and
male owned businesses. The findings of these studies offer
conflicting information about the degree and extent of
differences between female and male run businesses. In a
recent 2007 study, Coleman examines human capital as
well as financial capital variables to explain differences in
business profitability between male- and female-owned
business. Coleman’s (2007) findings indicate that human
capital variables such as education and experience are more
likely to contribute to the profitability of female-owned

businesses and that financial capital has a greater impact on
the success and profitability of male-owned businesses.
These findings reinforce the work of Lansberg (1983),
Marion (1988), and Davis (1983).
By looking at the family and the business as two over-
lapping systems, Lansberg (1983) points out that when the
founder of the business makes decisions, the main problem
is how to balance the benefits of the family and the busi-
ness. The founders ‘‘frequently experience a great deal of
stress from ‘internalizing’ the contradictions that are built
into their jobs as heads of the family firm’’ (Lansberg 1983
p. 41). Marion (1988) acknowledges that sometimes the
goals of the family and the business are not complementary
and thus contributed to conflict within the family business.
Davis (1983) presents a theoretical model and contends
that a family business is a joint system in which behavior
depends both on the family part and the business part. The
vitality of a family business needs the commitment of the

family as well as non-family employees in meeting their
family business goals. Thus, both men and women are
impacted by the intertwining of the family and the business
in terms of human and financial capital. Lee et al. (2006)
note when married women in business-owning families
experience tensions over resource constraints between
family and business systems, they report lower levels of
well-being. Fitzgerald and Winter (2001) also find the roles
of managing a family and managing a business are in
conflict, but find that the adjustment strategies in coping
with these demands do not vary by gender and instead
depend on the number of roles one takes on. Kirkwood
(2009), in studying spousal roles among entrepreneurs in
New Zealand, finds that women are more likely to seek
unambiguous support of their business endeavors, while
men are likely to assume spousal support exists without
seeking explicit statement of it.
Haynes et al. (2000) show that the financial statement of

the household is a good indicator of the performance of the
family business only if the manager is male, but it does not
indicate success if the business is managed by a woman.
They also find that women-owned businesses are more
likely to be in the retail and transportation service indus-
tries and have fewer employees than those managed by
men. It is noted that, ‘‘on average, women-owned busi-
nesses have lower levels of total business assets, liabilities,
equity, and income than men-owned businesses’’ (p. 221).
Haynes et al. (2007) report, on the contrary, that the suc-
cess of small businesses is not necessarily tied to family
prosperity; however, women-owned businesses are more
likely to realize ‘‘an increase in the transfer of money from
the business to the household’’ (p.403, 407) compared to
businesses owned by men. Loscocco et al. (1991) report
that most (64.9%) of the female-owned businesses are in
the business service industry, while fewer of the male
owned businesses are in the business service industry

(35.4%) and manufacturing industry (36.3%).
Likewise, other studies point out that women-owned
businesses are more likely to be smaller in terms of size
and income. Loscocco et al. (1991) claim the average
levels of income and sales of female-managed businesses
are substantially lower than those of male-managed busi-
nesses. They find that the average income and sales of
female-managed businesses are $51,340 and $1,346,900,
respectively; and those of male-managed businesses are
$95,240 and $3,414,300, respectively. In another study,
Cliff (1998) finds that female-managed businesses have
significantly smaller annual sales, employment growth, and
return on assets. Cuba et al. (1983) contend that there are
two reasons why the survival rate of female-managed
businesses is low: First, the majority of women are not
adequately prepared before they become an owner; second,
women managers are reluctant to delegate detailed work to
other people so that they do not distribute their time

efficiently.
On the other hand, in a more recent study, Collins-Dodd
et al. (2004) point out that gender is not a significant var-
iable to explain the difference in financial performance
J Fam Econ Iss (2010) 31:458–474 459
123
between male- and female-managed businesses if the
effects of some other factors (for example, number of
employees, home-based or not, control of work situation)
and personal characteristics (for example, age, education,
number of children) are considered in the model. The
results of a study by Kalleberg and Leicht (1991) also
indicate that women-owned businesses are less likely to
fail than men-owned businesses; they report that success
levels are similar across genders. Other researchers point
out that women might measure business success differently
than men, in part because they tend to focus on balancing

work and family (Anna et al. 1999) preferring to adapt their
businesses to manage personal, family, and professional
demands (Fitzgerald and Folker 2005). Masuo et al. (2001)
also conclude that perceived business success varies by
gender, with females perceiving higher levels of success.
Kepler and Shane (2007) examine the characteristics of
male and female entrepreneurs when they establish a new
business. Kepler and Shane indicate that females are more
likely to purchase their firms instead of establishing them;
firms managed by females are more likely to earn positive
revenue; males are more likely to take risky strategies for
their new venture; and males spend more time searching
new business opportunities. Furthermore, businesses star-
ted by female managers are less likely to have technolog-
ically intensive features, and more likely to be founded on
a local customer base than those founded by males.
Demographic and Managerial Differences Between
Female- and Male-Owned Businesses

Other researchers look at demographic differences between
male and female business owners. Boden and Nucci (2000)
show that compared to their male counterparts, female
business managers are more likely to have higher levels of
education and less prior employment experience. Human
capital of managers such as higher levels of education and
employment experience can improve the survival rate of
the businesses in their first few years. Loscocco et al.
(1991) show that male managers stay in the industry for a
longer time than female managers; consequently, they have
more managerial experience than their female counterparts.
Carter and Marlow (2003) point out the differences in
the prior occupational and professional experience of male
and female managers in waged jobs which impacts busi-
nesses ownership. They claim that this explains why
female-managed firms are smaller and have lower perfor-
mance. However, Fischer et al’s (1993) findings do not
support this point; their results suggest that the reason for

the size and performance difference is that women man-
agers have ‘‘less experience in managing employees, in
working in similar firms, or in helping to start-up new
businesses’’ (p. 151).
In a study of female and male managers, Loscocco and
Leicht (1993) focus on the link between the family and the
business. They compare the work-family connections
among small businesses managers. They find that female
managers are more likely to be single and spend more time
on their work; they operate younger and smaller businesses
than male managers do. A recent study by Philbrick and
Fitzgerald (2007) further supports these results. In a
demographic summary of women-owned family busi-
nesses, Lowrey (2006) shows that 28.2% of the nonfarm
firms in the U.S. are owned by women who hire 6.5% of
the employees; on the other hand, men owned 57.4% of the
nonfarm firms and hire 38.4% of the employees.
Many female managers establish home-based firms so

they can simultaneously care for their children; they are
willing to sacrifice their income at times to accomplish this
goal. In comparing this with males, Hundley (2001) simi-
larly finds that self-employed males ‘‘work the most hours
per week in the market and the female self-employed work
the fewest’’ (p.128), indicating that females may sacrifice
business priorities for family priorities. Regarding the
division of labor by gender, Hundley also states that
‘‘women do more housework, and the amounts by which
female hours on chores and childcare exceed male hours are
much greater among the self-employed’’ (p.131). Other
scholars also point out that women put more effort into their
family goals such as spending time with family members,
and put less effort into accomplishing business goals (His-
rich and Brush 1987; Kaplan 1988; Kepler and Shane 2007);
however, Fischer et al. (1993) report an opposite result.
Similarly, Tuttle and Garr (2009) report limited support for
the hypothesis that self-employed women have better work-

family fit, concluding that the higher job satisfaction and
autonomy available to the self-employed may have an
indirect influence. In 2010, Schieman and Young
acknowledge greater levels of family-work conflict in
association with economic hardship, especially among men.
A study of Canadian households with home-based
businesses reports that self-employed workers use con-
ceptual and physical barriers to create boundaries between
their homes and business spaces, allowing them to manage
both work and family (Myrie and Daly 2009). However,
Zody et al. (2006) find that, contrary to the pervasive belief
that a lack of boundaries causes problems in family firms,
success acts as a mediating factor; in essence, the interplay
of family and business may change based on perceptions of
success and the boundaries between the two ‘‘are dynamic
and complex’’ (p.204). Masuo et al. (2001) find that while
family success positively impacts business success, the
reverse is not true.

Kalleberg and Leicht (1991) point out that female man-
agers place a greater emphasis on the quality of the business
in competition; they contend that there is no significant
460 J Fam Econ Iss (2010) 31:458–474
123
innovation gap between male and female-managed busi-
nesses. Cliff (1998) finds that there is no significant differ-
ence between the desires of female and male managers to
expand their businesses. However, Cliff describes female
managers as being more careful and conservative, when
they expand their firms, while male managers are more
likely to undertake risky strategies. Cliff also notes that male
managers are both more aggressive and more at ease in
competitive business situations.
In another study, Orser and Hogarth-Scott (2002) show
that the plurality of the female managers (40%) engage in
business strategies to improve the quality and offer better

price, but limit the quantity and the variety of the products;
and 20% of the female managers take ‘‘analyzer and
prospector’’ strategies. That means that female managers
do not act as a leader of their industries; instead, they
analyze their competitors’ behavior carefully and learn
from their mistakes. Orser and Hogarth-Scott also report
that there is no significant difference in the processes and
weights that the two different genders put into the devel-
opment of the firm, but female managers are more likely to
be influenced by their spouse’s opinions and perspectives
when they make business decisions.
Danes et al. (2007) find differences in the gross revenue
between female- and male-owned family firms after con-
trolling for family business management and innovation
practices. The introduction of new production methods has
positive effects on the gross revenue for both female- and
male-owned businesses, but personnel management has a
larger effect on gross revenue for females. They also note

that gender has a moderating effect on business manage-
ment practices, but gender does not moderate the effects of
innovations on gross revenue.
In terms of the motivation of establishing a firm, Fielden
et al. (2003) point out four possible reasons why a woman
starts a business as the following: (1) she is not satisfied
with her previous job; (2) she has redundancy in energy,
time or money; (3) she is unable to find suitable employ-
ment; and (4) she wants to be her own boss. Moreover, as
previously mentioned, many female managers start their
firms because they want to have flexible schedules to
enable child and family care (Loscocco 1997).
Studies within the International Perspective on Male
and Female Managers
In a study specific to family businesses conducted in the
United Kingdom, researchers explain the difference
between male-managed and female-managed businesses by
the barriers posed by a lack of financial support for women

(Schmidt and Parker 2003). The contention is that women
have significantly less wealth and business experience; as a
result, it is difficult for women business managers to get
loans to begin a business. Thus, it is more difficult for
women to establish or expand the business. Fielden et al.
(2003) use this fact to explain the reduction of female-
owned business in North West England in the early 2000 s.
In regard to business strategies and financial decisions,
Watson (2002) focuses on the small- and medium-sized
businesses in Australia and points out that male business
managers invest more heavily than female managers do,
and female managers incorporate fewer resources for their
new ventures. Watson provides two reasonable explana-
tions to this phenomenon: One is that female managers
have fewer resources in their businesses on average which
limit their strategies; the other was that female managers
are more risk averse.
In a study of gender issues, Sonfield and Lussier (2009)

investigate family businesses in six countries. Their find-
ings indicate that when the gender of the business manager
is female, it is not an indicator of a success of the family
business. Other factors do influence business success (e.g.,
leadership style and family conflicts have a direct influence
on the success of the family business). Sonfield and Lussier
also find that business strategies and management planning,
using outside advisors, long-term planning, financial
management tools, founder influence, going public, and
formal management style are more important factors
regarding the success of the family business than whether
the manager was male or female.
In a study of small-to-medium size family businesses in
Australia, Romano et al. (2000) investigate the factors that
could influence the finances of businesses. Their significant
results include that the larger the family business, the more
debt the business has, and the lower the family loan, the
higher the equity. Romano et al. (2000) also find that the

age of the family business and the age of the business
owners positively affect the equity of the business.
Conceptual Framework and Hypotheses
Sustainable Family Business Theory
To guide this study, Sustainable Family Business Theory
(SFBT) is used to inform the selection of variables and
interpretation of results (Danes et al. 2008a; Stafford et al.
1999). In SFBT, the family is viewed as a rational social
system and the sustainability of a family business is a
function of both the success of the business and family
functionality (Stafford et al. 1999). An individual in either
system may affect parts of both systems (Heck and Trent
1999). SFBT gives equal recognition to the family system
and the business system in family-owned businesses and
how the interplay between the two systems influences the
achievement of sustainability for both. In the framework of
J Fam Econ Iss (2010) 31:458–474 461
123

SFBT, this study investigates resources and business suc-
cess at the firm level. Figure 1 depicts the framework of
SFBT (Werbel and Danes 2010).
Resources: Human, Social and Financial Capital
Using the SFBT, this study estimates the influence of
human, social, and financial capital on family business
outcomes. Considered as resources in SFBT, human capital
and financial capital have been identified as necessary
components for small business success and survival
(Coleman 2007). Human capital is viewed as the stock of
resources existing in people. These resources include their
acquired skills, experience, and knowledge gained through
formal schooling, market work, and on-the-job training
(Becker 1993). Bryant (1992) also notes human capital as
the skills, abilities, attitudes, and work ethic of individuals.
Previous studies indicate that among the self-employed,
the most important factor influencing a business’s success

is education (Carter et al. 2003; Kangasharju and Pekkala
2002). Coleman (2007) operationalizes human capital as
education, prior business experience, age and maturity, the
presence of partners who can provide additional expertise,
and a family history of firm ownership, employment,
industry or other kinds of experience in her comparison of
male- and female-owned businesses.
Danes et al. (2010) believe that gender of the business
owner implies a set of human capital characteristics that
differ by gender such as management ability and resource
use. They find that gender of the business manager and
family resource exchanges with the business affect family
firm performance (Danes et al. 2007). Age of the business
owner can be a proxy of experience. The most widely used
measure of human capital is formal education. Increased
schooling increases an individual’s productivity (Bryant
1992). Health of the owner is another form of human capital
because having good health allows individuals to be more

productive (Cutler and Richardson 1999) and thus good
health can help individuals be more productive at work
activities in operating their businesses. Additionally,
investments in health have long been viewed as a way to
improve human capital (Hammermesh and Rees 1993;
Masuo et al. 2001). In this study, human capital is measured
by education, age, and health of the business manager.
Social capital, another form of resource, is ‘‘goodwill that
is engendered by the fabric of social relations that can be
mobilized to facilitate action’’ (Adler and Kwon 2002,
p. 17). As explained by Danes et al. (2008)a, ‘‘it is embodied
in relationships among people and formal social institu-
tions’’ (p. 239) and can be used to benefit the business. Our
regression model looked at managers’ satisfaction with
community support as one of the constructs related to social
Fig. 1 Sustainable family business theory. Source Werbel and
Danes (2010)
462 J Fam Econ Iss (2010) 31:458–474

123
capital to measure a sense of community as perceived by the
business managers (Brown et al. 2003; McMillan and
Chavis 1986).
Financial capital pertains to available funds which may
come from the family in business, extended networks and
formal financial institutions (Danes et al. 2007) or debt
and/or equity infusions from external sources (Coleman
2007). Business income, business liabilities, and cash-flow
problems are used to measure financial capital of the
business. While human capital and financial capital have
been shown to explain success in the short term, social
capital contributes more to long-term success (Danes et al.
2010).
Processes: Business Activities
SFBT illustrates that families and businesses have the
ability to transform available resources and constraints

via interpersonal and resource transactions into achieve-
ments. Resources and interpersonal transactions from
either the business or the family system can facilitate or
hinder the sustainability of either system at various
points in time. Achievements can be objective or sub-
jective (Olson et al. 2003) and the two systems (family
and firm) are affected by environmental and structural
change (Danes 2006), described in the theory as nor-
mative and non-normative disruption. Similar to Danes
et al. (2008b), in this study, business management and
innovation practices represent managerial processes and
are illustrated as interpersonal and resource transactions
in the SFB model (Fig. 1).
Business Demographics
In addition to measures of human, social and financial
capital, and business management activities, the empirical
models include characteristics of the business as control-
ling variables. They are business size, business age, and

whether or not it is home-based. Walch and Merante (2007)
indicate that a minimum number of employees are needed
to provide resiliency in times of business turmoil. Busi-
nesses with more employees are larger businesses, and they
have many more resources available than smaller busi-
nesses. Kale and Arditi (1998) explain that the age of the
business is related to the failure of business, and they
conclude that the risk of business failure is the highest in
the first few years of business age, and then the risk of
failure decreases as the business gets older. Soldressen
et al. (1998) also note that home-based family businesses
are smaller than other businesses in terms of employees
and many home-based family businesses are less profitable
than non-home based family businesses.
Hypotheses
The review of literature indicates that female managers
may have lower levels of human capital in the form of
employment and managerial experience than their male

counterparts (Boden and Nucci 2000; Carter and Marlow
2003; Loscocco et al. 1991). Female managers may also
have lower levels of financial capital in the forms of
business assets and equity (Haynes et al. 2000), income,
and sales than male managers (Cliff 1998; Loscocco et al.
1991). Women’s priorities for business goals and operation
may differ from men’s due to family considerations (Los-
cocco and Leicht 1993). There is also evidence that their
approaches to business management and innovation differ
as do the impact these strategies have on performance as
compared to men (Cliff 1998; Danes et al. 2007; Orser and
Hograth-Scott 2002). Clearly, there is a need to discern the
effects of gender on business success and profit growth.
Additionally, the influence of gender on business man-
agement strategies and innovation is estimated.
Although SFBT does not specify differences between
male and female managers, the literature presented above
indicates that male and female managers may have different

levels of resources such as human, social, and financial cap-
ital, and they are different in the use of managerial processes
such as business management and innovation; therefore,
differences in firm performance outcomes between male and
female business managers are expected (Anna et al. 1999;
Cliff 1998; Cuba et al. 1983; Haynes et al. 2000; Kalleberg
and Leicht 1991; Watson 2002). Thus, based on the findings
in the literature, this study hypothesizes that female managers
will experience more perceived business success than male
managers (H1-a); but female managers will experience less
profit growth than male managers (H1-b).
As shown in the review of literature, numerous factors
impact the success of male and female operated firms
including financial support, industry, business size, and
work-family connections. Therefore, while the overall
hypothesis tested in this study is that male and female busi-
ness managers will differ in their perceptions in business
success and profit grow over time, this study also considers

the influence of factors within the SFBT such as human,
social, and financial capital to predict perceptions of business
success and revenue change over time for family firms.
Accordingly, based on the SFBT and literature on human,
social and financial capital, business activities, and business
demographics, this study tests five other hypotheses.
Human capital of business managers will influence
business success and profit growth. This study measures
human capital by education, age, and health of business
managers. Based on the findings of previous studies
(Bryant 1992; Carter et al. 2003; Coleman 2007; Cutler
and Richardson 1999; Hammermesh and Rees 1993;
J Fam Econ Iss (2010) 31:458–474 463
123
Kangasharju and Pekkala 2002), it is hypothesized that
older managers, managers with higher levels of education,
and managers who are in good health will experience more

business success and profit growth than managers who are
younger, have lower levels of education, and those who are
in poor health (H2-a, H2-b, and H2-c, respectively).
Social capital will influence business success and profit
growth (Adler and Kwon 2002; Brown et al. 2003; Danes
et al. 2008a; McMillian and Chavis 1986); thus, this study
hypothesizes that managers who express more satisfaction
with community support will experience more business
success and profit growth than those with less satisfaction
with community support (H3). Moreover, according to the
findings of previous studies (Coleman 2007; Danes et al.
2008a; Haynes et al. 2000), the financial experiences of
business managers will influence business success and
profit growth. Specifically, managers with greater amounts
of business income (H4-a) will experience greater business
success and profit growth than those with lower amounts of
business income, while those business managers with
greater amounts of business liabilities (H4-b) and those

with business cash-flow problems (H4-c) will experience
less business success and profit growth than those with
lower levels of business liabilities and without cash-flow
problems.
Managerial processes including management activities
and innovation practices will affect business success and
profit growth (Danes 2006; Danes et al. 2008b; Olson et al.
2003). Thus, this study hypothesizes that managers who
report a greater use of business managerial activities (H5-a)
and innovative practices (H5-b) will experience more
business success and profit growth than those using fewer
managerial activities and innovation strategies (Danes et al.
2007, 2008b; Sonfield and Lussier 2009).
Demographic characteristics of the business will influ-
ence business success and profit growth (Kale and Arditi
1998; Soldressen et al. 1998; Walch and Merante 2007).
Therefore, this study hypothesizes that managers with more
total employees (H6-a) and those managing older busi-

nesses (H6-b) will experience more business success and
profit growth than those with fewer employees and younger
businesses (Romano et al. 2000), while managers in home-
based businesses (H6-c) will experience less business
success and profit growth than managers in businesses
based from another location (Davis 1983; Lansberg 1983).
Methods
Data and Sample
Data for this study are from the 1997 and 2000 panels of the
National Family Business Survey (NFBS). Details of the
sampling frame and methods of data collection for the 1997
wave of the NFBS can be found in Winter et al. (1998), but a
brief description is provided here. The 1997 data are from a
nationally representative sample of family businesses.
Telephone interviews were used to screen over 14,000
households in the U.S. to identify family-owned businesses.
Subsequent interviews were conducted with both the busi-
ness manager, or the person most involved in the day-to-day

management of the business, the household manager defined
as the person responsible for most of the meal preparation,
laundry, and cleaning, as well as the scheduling of family
activities and the overseeing of child care, or a combined
interview schedule if one person was primarily responsible
for the business and the household. Of the 1,116 eligible
households, interviews were completed with 794 family
businesses for a response rate of 71%.
In 2000, researchers attempted to contact the 1997
respondents to conduct additional interviews (Winter et al.
2004). Because the interest was on tracking family busi-
nesses over time, 86 households in which the business
manager had not been interviewed in 1997 were omitted
from the 2000 sample, reducing the sample size from
794–708. Additionally, 63 households could not be reached
in 2000, and 92 refused to participate in the follow-up
interviews. Thus, data were gathered from the remaining
553 households, again by interviewing business or house-

hold managers or by completing a combined interview
schedule if one person served in both roles.
Among the 553 family-owned firms, 132 managers/
owners were not involved, but 421 business managers/
owners were still involved in their family businesses. The
subsample selected for analysis consisted of 421 business
managers who participated in both 1997 and 2000 surveys.
For the data analyses, observations with missing values were
dropped and this procedure resulted in a study sample of 365
business managers. The sub-samples of this study consisted
of male (n = 275) and female managers (n = 90).
Statistical Analyses
Frequencies and means were performed to obtain the
descriptive information on all variables in the multivariate
analyses. Cross-tabulations and t-tests were conducted to
determine differences between male and female-managed
family businesses. To examine the effect of gender on
business success and profit growth over time, this study

employed Ordinary Least Squares (OLS) regression anal-
yses. If the dummy variable for gender (Dfem) was statis-
tically significant in the regression models for the business
success and profit growth, then the dummy variable inter-
action technique was applicable.
In methodology, the OLS regression with dummy vari-
able interaction approach is examined to demonstrate
464 J Fam Econ Iss (2010) 31:458–474
123
whether the regressions for female managers and male
managers are totally different, and identify which variables
differently affect the business success and profit growth of
female managers as compared to male managers. The
dummy variable interaction approach allows a single
regression equation to be estimated. As outlined in Gujarati
(1988, p. 446), a dummy variable (e.g., FEM, female
manager = 1; 0 if not) is interacted with the entire vector

of independent variables. The dummy variable interaction
approach explicitly identifies which coefficients, intercepts,
or slopes are different or whether both are the same
between subgroups of the sample (Gujarati 1988).
The dummy variable interaction approach estimates the
following regression:
y ¼ a þ b0Dfemi þ b1x1i þ b2x2i þ : :þ bkxki þ Dfem
� b1femix1i þ b2femix2i þ : :þ bkfemixkið Þþ ui
In this equation, y is the dependent variable, a is the
regression intercept, and x1i… xki are the independent
variables. The i represents the individual family business
identifier and k is the number of independent variables (xk).
b0 is the differential intercept and b1i, b2i… ? bki are the
regression coefficients indicating the direction and strength
of the relationship between the independent variables and
each dependent variable. Dfem is the dummy variable for
family business which takes on the value of 1 (if a female-
managed business) or 0 (if not) and b1femi, b2femi… bkfemi
represent the differential coefficients. The differential
coefficients indicate how much the coefficients of female-
managed businesses differ from the coefficients of male-

managed businesses. The significant bkfem identify the
variables for which the responses of female and male-
managed businesses differ.
The dummy variable interaction technique does more
than identify whether there exist differences in business
success and business performance between the two groups.
This method also pinpoints which explanatory variables
account for the differences in business success and profit
growth between female and male-managed businesses.
Moreover, it provides insights as to whether differences in
business success are due to different effects of the set of
independent variables across the two family business types
(Jang 1995).
Variables
Dependent Variables
It is important to use both objective and subjective mea-
sures in examining business success (Jones 2003; Walker
and Brown 2004). In this study, business success is mea-

sured subjectively by the business managers’ rating of how
successful they perceive their business to be in 1999.
Business manager’s responses to overall business success
to date range from 1 (not at all) to 5 (very successful). To
measure business success objectively, the profit growth
between 1996 and 1999 is utilized, while measuring the
percentage change in business profit over the two periods.
Thus, perceived business success and profit growth are
included as dependent variables in the OLS regression
models.
Independent Variables
The independent variables are categorized by human cap-
ital or personal demographics of the manager, social, and
financial capital of the business, managerial activities, and
demographic characteristics of the business. All indepen-
dent variables are from the second wave data set. As noted
previously, this study analyzes the data to understand
resources at the firm level in the forms of human, social

and financial capital and their influence on the levels of
business success. Human capital of the business manager
includes age, education, and health status. Both age and
education are included as continuous variables, whereas the
heath status represents categorical variables [poor (refer-
ence group), good, and excellent].
Manager’s satisfaction with community support is
included as a proxy of social capital. In the survey, business
managers are asked: ‘‘How satisfied are you with the amount
of support you get from your community.’’ Community
support reflects the quality of community infrastructure such
as the quality of the local schools, transportation, health
care, telecommunications, recreation facilities, or public
safety services. Responses range from 1 to 5, where ‘‘1’’
represents ‘‘very dissatisfied’’ and ‘‘5’’ represents very sat-
isfied. For financial capital, business income, business total
liabilities, and presence of business cash-flow problems are
included in the regression analyses. While both business

income and business liabilities are included as continuous
variables, the business cash-flow problem represents cate-
gorical variables [having problem, no cash-flow problem
(reference group)].
In terms of processes, managerial activity is a scale that
measures the extent the business managers practice a set of
ten business management activities (see Table 3 for a list
of items). Each management activity is rated from 1 to 5,
where ‘‘1’’ represents that the activity is not being done at
all, and ‘‘5’’ represents that the activity is being done to the
great extent. Additionally, the manager’s innovative prac-
tice is included to measure process in SFBT. In the survey,
business managers are asked about whether they have done
any of the five items (see Table 3 for a list of items). Each
innovative practice is rated from 0 to 1, where ‘‘0’’ rep-
resents ‘‘no’’ if managers have not engaged in the business
practice and ‘‘1’’ represents that they have.
J Fam Econ Iss (2010) 31:458–474 465

123
Business size, age of the business, and type of business
are included as business characteristics in the empirical
models. Both business size and age of the business are
continuous variables, whereas the type of business is coded
as a categorical variable [home-based, non-home based
(reference group)]. The measurements of variables inclu-
ded in the regression analyses are presented in Table 1.
Findings
A Profile of Family Businesses by Gender
Table 2 provides descriptive information on business and
manager characteristics by gender. The t-tests indicate sig-
nificant mean differences in the levels of perceived business
success, 1996 business profit, and the percentage change in
business profit between 1996 and 1999 between male and
female managers. The average levels of perceived business
success and the percentage change in business profit are

higher for female managers than for male managers. How-
ever, the levels of business profit in both 1996 and 1999 are
much higher for male managers than for female managers.
The table shows that female managers are younger,
more highly educated, and healthier than male managers.
However, the levels of involvement in managerial and
innovative practices are lower for female managers than
male managers. While male managers report higher levels
of satisfaction with community support, they have more
cash-flow problems and larger amounts of debt than female
managers. The average number of total employees is lower
for female managers than male managers. It is obvious that
female managers operate smaller-sized companies than
male managers. A relatively higher portion of the female
Table 1 Measurement of
dependent and independent
variables
Note Reference categories are in
parentheses

Variables Measurement
Gender
FEM 1 if female manager, 0 otherwise
(Male) 1 if male manager, 0 otherwise
Resources
Human capital
Age of manager Continuous, age of business manager (# of
years)
Education of manager Continuous, educational attainment (# of
years)
Perceived health condition
(Poor) 1 if perceived health is poor, 0 otherwise
Good 1 if perceived health is good, 0 otherwise
Excellent 1 if perceived health is excellent, 0 otherwise
Social and financial capital
Community support Satisfied with community support(response
range 1–5:
1 very dissatisfied, 5 very satisfied)
Business income Continuous, Imputed gross business income
Business liabilities Continuous, Imputed total liabilities

Cash-flow problems 1 if having business cash-flow problem, 0
otherwise
Processes
Management practices Continuous, Sum of 10 items of
managerial activities (response range 1–5: 1
not done at all, 5 very great extent)
Innovative practices Continuous, Sum of 5 items including new
product development, product &
service development, marketing development, market
establishment,
customer service improvement(response range 0–1: 0 not done,
5: have
done)
Business demographics
Business size Continuous, # of non-family employees
Age of business Continuous, 1999-established year
Home-based business
Yes 1 if operate business at home, 0 otherwise
(No) 1 if operate business outside of home, 0 otherwise
Dependent variables

Business success Perceived overall business success to date (1
not at all, 5 very successful)
Profit growth Continuous, [(1999 profit–1996 profit)/1996
profit] 9 100
466 J Fam Econ Iss (2010) 31:458–474
123
managers report their businesses as home-based than do
male managers.
Business Management and Innovative Practices
of Male and Female Managers
Table 3 shows the extent to which male and female man-
agers are involved in managerial and innovative activities.
The ten items of management practices assessed are pre-
sented, indicating that the higher the score, the greater the
management activity level performed by the managers.
Female managers are more likely to be involved in analyzing
customer satisfaction, evaluating product quality, and plan-
ning advertisement than male managers. Five items of

innovative practices are also presented in Table 3. Except for
the category of improving customer service, female man-
agers are more likely to practice all the other four categories,
such as developing new products/services, improving
methods, developing new marketing strategies, and estab-
lishing markets. It is evident in Table 3 that there are gender
difference in how managers engage in business management
through managerial activities and innovative practices.
OLS Results
Table 4 presents significant factors that determine the levels
of business success and profit growth over time. The main
purpose of this study is to explore the influence of gender on
business success and profit growth. The coefficients associ-
ated with gender have a statistically significant effect on both
business success and the profit growth models. The results
show that all else being equal, female managers have higher
levels of business success than male managers, and they
experience 381% more profit growth between 1996 and 1999

than male managers; thus, H1-a is supported. However, H1-b
is supported but in a different direction.
Table 2 A Profile of male and
female managers among family
owned businesses
� p 0.10, * p 0.05,
** p 0.01, *** p 0.001
Male manager
(n = 275)
Female manager
(n = 90)
Test statistics
t test
v2-test
Business success and profit growth
Perceived business success 3.9 4.1 t = -2.41*
1996 business profit $122,010 $20,112 t = 3.70***
1999 business profit $179,160 $61,853 t = 1.40
% D in business profit 118% 459% t = -1.75�
Resources
Human capital

Age 49.8 48.4 t = 1.10
Education 14.3 14.9 t = -1.77�
Health status
Poor 10.1% 15.6% v2 = 6.15*
Good 49.2% 34.4%
Excellent 40.7% 50.0%
Community support 3.7 3.6 t = 1.36
Business income $714,516 $509,111 t = 0.80
Business liabilities $192,816 $131,247 t = 0.78
Business cash-flow problem
No problem 39.3% 52.2% v2 = 4.65*
Have problem 60.7% 47.8%
Processes
Management practices 31.8 29.2 t = 2.65**
Innovative practices 2.9 2.7 t = 1.30
Business size 6.6 5.3 t = 0.49

Age of business 26 17 t = 3.67***
Home-based type
Home-based 52.7% 62.2% v2 = 2.47
Non-home based 47.3% 37.8%
J Fam Econ Iss (2010) 31:458–474 467
123
Perceived Business Success
As the predictors of business success, gender (H1-a), age
(H2-a), health (H2-c), satisfaction with community support
(H3), business cash-flow problems (H4-c), and the business
being home-based (H6-c) are statistically significant. Not
surprisingly, the age variable shows a significant and neg-
ative effect on the levels of perceived business success,
indicating that the levels of business success decrease as the
age of the manager increases. The findings also suggest that
managers with excellent health report greater levels of
business success than those with poor health status sup-

porting H2-c. The results for social capital show a signifi-
cant and positive effect, indicating that as a manager’s
satisfaction with community support increases, the levels of
business success increase as well. Thus, H3 is supported.
The coefficient associated with cash-flow problems
shows a significant and negative effect on the perceived
levels of business success, indicating that as managers have
business cash-flow problems, the perceived levels of
business success decrease, thus supporting H4-c. The
results also show that the business being home-based or not
have a significant effect on the perceived level of business
success, indicating that as managers run their business at
home, the perceived levels of business success decrease
over those that operate their businesses outside of home,
confirming H6-c.
Profit Growth
As the predictors of profit growth, gender, health, satis-
faction with community support, business size, and home-

based business are statistically significant. The results show
that managers with good health experience 333% more
profit growth between 1996 and 1999 than do those with
poor health, supporting H2-c. A manager’s satisfaction
with community support has a significant and positive
effect on the percentage change in business growth over
time (H3). That is, as the level of satisfaction with com-
munity support increases, the level of percentage change in
business profit increases by about 123%. As the number of
employees increases, the level of percentage change in
Table 3 A comparison of
management practice and
innovative practices between
male and female manager
* p 0.05, ** p 0.01,
*** p 0.001
Variables Male manager
(n = 275)
Female manager

(n = 90)
Test statistic
t test
v2-test
Management Practice
Analyze customer satisfaction 3.7 3.9 t = -0.96
Evaluate quality of services/product 4.1 4.2 t = -0.22
Plan advertising/promotions 2.6 2.7 t = -0.37
Estimate costs and expense figures 3.8 3.4 t = 2.61**
Prepare financial records 3.3 3.0 t = 2.26*
Deal with personnel issues 3.0 2.2 t = 4.51***
Evaluate employee performance 2.9 2.3 t = 3.19***
Motivate workers to be better employee 3.0 2.3 t = 3.48***
Determine numerical objectives 3.2 2.9 t = 1.51
Develop a written strategic plan 2.2 2.2 t = 0.06
Innovative Practice
Have developed new products/services
Yes 58.1% 60.0% v2 = 0.11
No 41.9% 40.0%

Have improved method of products/services
Yes 21.4% 36.7% v2 = 8.14***
No 78.6% 63.3%
Have developed new marketing strategies
Yes 57.7% 58.9% v2 = 0.04
No 42.3% 41.1%
Have established markets
Yes 43.9% 50.0% v2 = 0.97
No 56.1% 50.0%
Have improved customer services
Yes 30.7% 28.9% v2 = 0.10
No 69.3% 71.1%
468 J Fam Econ Iss (2010) 31:458–474
123
business profit also increases (H6-b). Managers who run
business at home experience 236% less profit growth
between 1996 and 1999 than those who run businesses

outside the home.
OLS Results of Dummy Variable Interaction Approach
The OLS regression with dummy variable interaction
approach identifies which variables differentially affect the
business success and profit growth of these two types of
business managers. The first section of Table 5 reports the
OLS coefficients on variables for male managers. Using a
dummy variable interaction approach, thirteen variables
are interacted with the dummy variable for female manager
(Dfemi). If any of these thirteen interaction terms display
statistical significance, it means that the female manager’s
responses to a change in those interaction variables are
statistically different from the male manager’s responses to
a change in the same variables.
Perceived Business Success
In the first part of the business success model, it is evident
that excellent health (H2-c), satisfaction with community
support (H3), having cash-flow problems (H4-b), and being

a home-based business (H6-c) are all statistically signifi-
cant. The findings of this study suggest that male managers
with excellent health status and higher levels of satisfaction
with community support indicate higher levels of perceived
business success. However, male managers with business
cash-flow problems (H4-c) and those who operate business
at home (H6-c) report lower levels of perceived business
success than other managers. When all independent vari-
ables (x1i x2i,….xki) are interacted with the dummy variable
for gender (Dfemi), none of the coefficients is statistically
significant in accounting for differences in perceived
business success between female and male managers. This
means that the difference in perceived business success
between male and female managers is not due to different
response to change in any characteristics of managers and
family businesses.
Profit Growth
The first section of Table 5 shows that none of the vari-
ables for male managers is statistically significant. How-

ever, when the Dfemi variable is interacted with thirteen
variables, four out of the thirteen coefficients are statisti-
cally significant. The findings suggest that FEM 9 good
health, FEM 9 liabilities, FEM 9 business size, and
FEM 9 home-based play a significant role in explaining
factors that create differences in profit growth between
female and male managers. Based upon the results of the
significant parameters, it can be said that differences in
profit growth over time between the two groups are partly
due to different responses to changes in the health status of
the manager, business total debt, business size, and home-
based business type. Therefore, H2-c, H4-b, H6-a, and
H6-c are supported. It is worth noting that female managers
with good health have greater increases in percentage
change in business profit than male owners with good
health. It is also important to note that female managers
that run businesses at home have a greater decrease in
percentage change in business profit than male managers

who operate businesses at home.
Table 4 OLS results: determinants of business success and
profit
growth
Business success Profit growth
coefficients (SE) coefficients (SE)
Intercept 3.842 (0.436) -467(618)
Gender
(Male)
FEM 0.209(0.095)* 381(137)**
Resources
Human capital
Age of manager -0.009(0.004)* -3.09(5.79)
Education of manager -6.1E-5(0.019) 10.56(27.37)
Health status
(Poor)
Good 0.159(0.137) 333(196)
�
Excellent 0.270(0.141)* 114(202)

Community support 0.156(0.051)*** 123(71.99)
�
Business income 1.59E-8(2.62E-8) 2.92E-5(3.5E-5)
Business liabilities 6.32E-8(8.18E-8) -1.35E-4(1.1E-4)
Business cash-flow problem
(No)
Have cash-flow problem -0.238(0.083)*** 35.07(116)
Processes
Management practices 0.005(0.005) -0.31(7.23)
Innovation practices -0.015(0.031) -2.36(45.35)
Business size -8.61E-4(0.003) 7.63(3.70)*
Age of business -0.003(0.002) 0.28(2.61)
Home-based type
(Non-home based)
Home-based -0.274(0.089)*** -236(125)*
F-value 4.01*** 2.26**
Adj R

2
0.11 0.06
� p 0.10, * p 0.05, ** p 0.01, *** p 0.001
Note Reference categories are in parentheses
J Fam Econ Iss (2010) 31:458–474 469
123
Summary, Discussion, and Conclusions
In previous studies, gender is not a significant variable to
explain the difference in financial performance between
male and female managers (Collins-Dodd et al. 2004) and
the levels of business success are similar across genders
(Kalleberg and Leicht 1991). Using data from the 1997 and
2000 panels of the NFBS, this descriptive study attempts to
present information on the differences found in male- and
female-managed family businesses. The findings of this
study suggest that female managers perceive their busi-
nesses as more successful than male managers. The find-
ings related to perceived business success are consistent

with the findings of Danes et al. (2010). Female managers
also experience 381% more profit growth between 1996
and 1999 than do male managers. It might be possible that
female managers have such a high growth rate because
they start from a very low base; thus, female-managed
firms, despite their small size, do show great potential for
growth. Such growth has implications for the larger society
Table 5 OLS results of
interaction approach for
business success and profit
growth
�
p 0.10, * p 0.05,
** p 0.01, *** p 0.001
Note Reference categories are in
parentheses
Business success Profit growth
coefficients (SE) coefficients (SE)
Male manager vector of coefficients
Intercept 3.428(0.453)*** -186(624)

Age of manager -0.007(0.005) 0.79(6.38)
Education of manager -0.002(0.022) -10.41(28.71)
Health condition
(Poor)
Good 0.224(0.165) 227(228)
Excellent 0.398(0.172)* 148(236)
Community support 0.207(0.058)***
Business income 1.60E-8(2.78E-8) 99.3(79.84)
Business liabilities 8.77E-8(8.9E-8) 4.9E-5(3.5E-5)
Cash-flow problem -4.2E-5(1.2E-4)
(No problem)
Have problem -0.301(0.097)*** 10.05(127)
Management practice 0.007(0.006) -6.10(7.69)
Innovation practice 0.005(0.038) 32.85(50.68)
Business size -0.002(0.003) -1.39(4.19)
Age of business -0.003(0.002)
�
0.43(2.64)

Business type
(Non-home based)
Home-based -0.255(0.102)** -118(136)
Female manager vector of interaction coefficients
FEM 1.270(0.337)*** -106.30(432)
FEM 9 Age of manager -0.009(0.009) -16.51(13.33)
FEM 9 Education 0.015(0.349) 26.87(53.15)
FEM 9 Good health -0.145(0.305) 732(440)*
FEM 9 Excellent health -0.337(0.312) 37.78(456)
FEM 9 Satisfaction with com. support -0.146(0.109) 186(149)
FEM 9 Business income 3.7E-8(8.7E-8) -6.0E-5(1.1E-4)
FEM 9 Business liabilities -2.3E-7(2.4E-7) -5.4E-4(3.1E-4)
�
FEM 9 Cash-flow problems 0.158(0.191) 57.38(272)
FEM 9 Management practice -0.004(0.011) 14.23(16.87)
FEM 9 Innovation practice -0.053(0.072) -90.59(109)
FEM 9 Business size 2.3E-4(6.5E-3) 34.07(8.24)***
FEM 9 Age of business 0.003(0.006) -1.14(9.41)
FEM 9 Home-based -0.006(0.203) -575(277)*

F-value 2.78*** 2.75***
Adj R
2
0.13 0.14
470 J Fam Econ Iss (2010) 31:458–474
123
in their ability to generate tax revenue through property,
income, and sales tax, and to potentially hire additional
employees if the owner decides to expand the operation.
Yet, small female operated firms also represent a mecha-
nism for successfully balancing work and family, while
achieving a desired level of business success.
Using the dummy variable interaction approach, vari-
ables such as good health status, business liabilities, busi-
ness size, and the business being home-based are all found
to have coefficients that are statistically significant, sug-
gesting that these four factors differently affect these two

types of business managers for their profit growth over
time. Based on this result, this study concludes that a dif-
ferential response exists in profit growth over time between
female and male managers in relation to health status,
business liabilities, business size, and whether the business
is home-based. Understanding how the health of the man-
ager, business debt, business size, and home-based factors
differently affect firm performance for male and female-
managed businesses can be useful for policy makers,
business consultants, and even for business managers or
owners to survive during economic downturns.
While the SFBT provides a useful framework that
identifies resource inputs, managerial processes, and the
relationship between the business and the larger commu-
nity through community support, additional research to
understand resources and processes at the family level and
their influence on firm outcomes is warranted. The findings
of this study are consistent with the review of literature that

female business managers may have lower levels of human
and financial capital than male managers (Boden and Nucci
2000; Carter and Marlow 2003; Haynes et al. 2000; Los-
cocco et al. 1991; Schmidt and Parker 2003).
The study concludes that the human capital of the man-
ager is an important determinant of business success. Health
is significantly associated with the level of business success;
age is also a significant predictor. It is evident that as the level
of health increases, business managers report higher levels of
business success as well as profit growth which is especially
true for female managers. To enhance the human capital of
managers in the form of health, it is important for community
decision makers to be aware of the role of health on business
success and to launch a diverse set of health-enhancing
efforts such as physical activity programs or the provision of
recreational facilities within a community. Educational
efforts related to nutrition, hygiene, immunization, and dis-
ease prevention may also facilitate wellness. Business

managers should make a concerted effort to monitor, and
possibly improve their health through diet, exercise, and
maintaining a healthy life style.
There is also great potential in understanding social
capital, particularly as it pertains to the long-term sustain-
ability of the business (Danes et al. 2010). As social capital,
manager’s satisfaction with community support is signifi-
cant in both business success and profit growth regression
models, implying that providing small business managers or
owners with a variety of support programs is critical for firm
outcomes. Decision makers might need to consider policies
that could support family firms, while developing regula-
tions or laws to reduce barriers to business success within
the community. However, in terms of limitations, this study
utilizes a single-item indicator to measure community sup-
port, a form of social capital; thus, improved measures could
add insight into the relationship between social capital and
firm performance. As suggested by Danes et al. (2010),

human and social capital may sustain small firms during
financially difficult times when other forms of capital, such
as financial capital, are less available.
Regarding financial capital, the presence of cash-flow
problems negatively affects the levels of business success.
Therefore, a consultant working with small business man-
agers might need to focus on equipping those managers
with financial knowledge and providing information on a
various funding opportunities. On the other hand, small
business managers might need to become more financially
literate in handling their debts through education and
business supporting programs.
Using SFBT, management activity represents a process
through which business managers transform resources. The
findings of this study describe that differences exist in
management activities between male and female managers.
Professionals who work with female business managers
need to recognize gender differences in management

practices. For example, female managers are less likely to
be involved in dealing with employees and business
finance than male managers. Thus, it might be necessary
for educators to assist female managers by providing
business finance seminars or relationship skill training
programs to help them deal with their employees, and
educators can further assist female managers by providing
enhancement programs to strengthen business skills
(Weigel and Ballard-Reisch 1997). Assisting female-
owned business in estimating costs and expenses, preparing
or managing business finance, and dealing with personnel
or employee issues would be important to help this grow-
ing segment of family business owners.
In SFBT, business innovative practice also represents a
process through which business managers transform
resources to meet demands. In the literature, it is noted that
there is no significant innovation gap between male- and
female-managed businesses (Kalleberg and Leicht 1991);

however, this study finds gender differences in use of
innovative practices. It is important for female business
managers to strengthen their skills in innovative practices,
while seeking help to improve the areas of innovative
practices that they lack.
J Fam Econ Iss (2010) 31:458–474 471
123
This study finds that businesses operated at home report
lower levels of business success and profit growth. Previ-
ous studies indicate that female managers operate their
businesses at home so that they can take care of their
children, while generating income; however, it might be
difficult for female managers to operate businesses at home
while putting lots of effort toward the business goals
(Hirsch and Brush 1987; Kaplan 1988; Kepler and Shane
2007). Involvement in home-based work can lead to
additional demands on both the family and the business

system (Fitzgerald and Winter 2001). Using the dummy
variable interaction approach, the results also show that the
home-based factor differently affects female and male
business managers for their profit growth over time. The
results imply that female managers who operate their
businesses at home could encounter more difficulties than
their male counterparts. This is consistent with Fitzgerald
and Winter (2001) who find that men and women
encounter different kinds of intrusions in their home-based
businesses based on occupation. Consultants may need to
work with male and female managers to develop unique
strategies that help them overcome the challenges of
operating a home-based business.
This study makes several contributions to the literature
on the performance of male- and female-managed family
businesses. First, both financial and non-financial measures
of firm success are included in the analyses. Firm success is
a multidimensional concept (Danes et al. 2008b) and while

financial performance is commonly used to measure firm
success, subjective measures have been shown to provide
insight into other dimensions of success such as commit-
ment and passion for the firm (Stanforth and Muske 2001).
Second, Danes et al. (2007) suggest that it is no longer
sufficient to investigate gender differences in management
practices with a dummy variable. The main and moderating
effects of gender need to be assessed through the use of
interaction terms as they were in this study. The results of
this study indicate that health has a differential effect on
perceived business success for male and female managers.
Health, liabilities, business size, and whether the business
is based in the home also have a differential impact on
profit growth for male and female managers. Third, the
study adds to the understanding of the performance of
family-owned businesses within the community context by
including a measure of social capital, although additional
work in this area is certainly warranted. Lastly, the findings

clarify the complex interplay between resources, manage-
ment practices, and other characteristics in understanding
perceptions of business success and profit increase over
time.
A better understanding of the factors that influence firm
performance in general, and the differential effects for men
and women can help business managers, consultants, and
policy makers tailor efforts to strengthen family firms to
become more profitable and successful for the owners and
employees. Gender-based public policy programs have
been created to increase the number of women entrepre-
neurs in the marketplace (Walker and Joyner 1999). In
addition, many colleges and universities in the United
States have added courses focusing on entrepreneurship
and business management, with significant support from
the entrepreneurship community. For example, the Ewing
Marion Kauffman Foundation’s Kauffman Campuses Pro-
gram began distributing $5 million grants in 2006 to help

universities to create entrepreneurial training programs
(Ewing Marion Kauffman Foundation 2010). Fostering the
success of family firms, whether they are male or female
owned, is important to family, business, and community
viability. Financially successful small firms not only pro-
vide adequate income to their owners, they also will likely
make larger contributions to their communities (Fitzgerald
et al. 2005).
References
Adler, P., & Kwon, S.-W. (2002). Social capital: Prospects for a
new
concept. Academy of Management Review, 27(1), 17–40.
Anna, A. L., Chandler, G. N., Jansen, E., & Mero, N. P. (1999).
Women business owners in traditional and non-traditional
industries. Journal of Business Venturing, 15, 279–303.
Becker, G. S. (1993). The economic approach to human
behavior.
Chicago, IL: The University of Chicago Press.
Boden, R. J., Jr., & Nucci, A. (2000). On the survival prospects
of
men’s and women’s new business ventures. Journal of Business

Venturing, 15(4), 347–362.
Brown, B. B., Perkins, D. D., & Brown, G. (2003). Place
attachment
in a revitalizing neighborhood: Individual and block levels of
analysis. Journal of Environmental Psychology, 23(3), 259–271.
Bryant, W. K. (1992). Human capital, time use, and other family
behavior. Journal of Family and Economic Issues, 13(4),
395–406.
Carter, N., Brush, C., Greene, P., Gatewood, E., & Hart, M.
(2003).
Women entrepreneurs who break through to equity financing:
The influence of human, social, and financial capital. Venture
Capital, 5(1), 1–28.
Carter, S., & Marlow, S. (2003, June). Professional attainment
as a
challenge to gender disadvantage in entrepreneurship. Paper
presented at the 48th International Small Business Conference,
Belfast, Germany.
U.S. Census Bureau (2002). Survey of business owners –
Women –
owned firms – 2002. Retrieved on October 7, 2009 from
http://www.sba.gov/ADVO/reserach/ rs280tot.pdf.
Cliff, J. (1998). Does one size fit all? Exploring the relationship
between attitudes towards growth, gender, and business size.

Journal of Business Venturing, 13, 523–542.
Coleman, S. (2007). The role of human and financial capital in
the
profitability and growth of women-owned small firms. Journal
of
Small Business Management, 45(3), 303–319.
Collins-Dodd, C., Gordon, I. M., & Smart, C. (2004). Further
evidence on the role of gender in financial performance. Journal
of Small Business Management, 42(4), 395–417.
472 J Fam Econ Iss (2010) 31:458–474
123
http://www.sba.gov/ADVO/reserach/
Cuba, R., DeCenzo, D., & Anish, A. (1983). Management
practices of
successful female business owners. American Journal of Small
Business, 8, 40–45.
Cutler, D., & Richardson, E. (1999). Your money and your life:
The
value of health and what affects it. Frontiers in Health Policy
Research, 3(1), 99–132.
Danes, S. M. (2006). Tensions within family business-owning
couples

over time. Stress. Trauma and Crisis, 9(3–4), 227–246.
Danes, S. M., Lee, J., Stafford, K., & Heck, R. (2008a). The
effects of
ethnicity, families and culture, on entrepreneurial experience:
An
extension of sustainable family business theory. Journal of
Developmental Entrepreneurship, 13(3), 229–268.
Danes, S. M., Loy, J. T., & Stafford, K. (2008b). Management
practices of small private firms within a quality framework.
Journal of Small Business Management, 46, 395–421.
Danes, S. M., Stafford, K., Haynes, G., & Amarapurkar, S. S.
(2010).
Family capital of family firms: Bridging human, social, and
financial capital. Family Business Review, 22(3), 199–215.
Danes, S. M., Stafford, K., & Loy, J. T. C. (2007). Family
business
performance: The effects of gender and management. Journal of
Business Research, 60(10), 1058–1069.
Davis, P. (1983). Realizing the potential of family businesses.
Organizational Dynamics, 12(1), 47–56.
Ewing Marion Kauffman Foundation (2010). Kauffman
campuses
initiative: Entrepreneurship across college campuses. Retrieved
June 27, 2010, from http://www.kauffman.org/entrepreneur

ship/kauffman-campuses.aspx.
Fielden, S., Davidson, M., Dawe, A., & Makin, P. (2003).
Factors
inhibiting the economic growth of female owned small busi-
nesses in North West England. Journal of Small Business and
Enterprise Development, 10(2), 152–166.
Fischer, E., Reuber, A. R., & Dyke, L. S. (1993). A theoretical
overview and extension of research on sex, gender, and
entrepreneurship. Journal of Business Venturing, 8, 151–168.
Fitzgerald, M. A., & Folker, C. A. (2005). Exploring new
frontiers in
women’s family business leadership: The impact of women’s
motivations on family and business measures of success.
International Journal of Family Business, 2, 1–11.
Fitzgerald, M. A., Haynes, G. W., Schrank, H., & Danes, S. M.
(2005,
September). For-profit family firms as socially responsible
organizations: Evidence from the U.S. National Business
Survey.
Paper presented at the F.B.N.-IFERA World Academic Research
Forum, Brussels.
Fitzgerald, M. A., & Winter, M. (2001). The intrusiveness of
home

based work on family life. Journal of Family and Economic
Issues, 22(1), 75–92.
Gujarati, D. N. (1988). Basic Econometrics (Second Edition
ed.).
New York: McGraw-Hill Publishing company.
Hammermesh, D. S., & Rees, A. (1993). The economics of work
and
pay. New York, NY: HarperCollins College Publishers.
Haynes, G. W., Onochie, J. I., & Muske, G. (2007). Is what’s
good for
the business, good for the family: A financial assessment.
Journal of Family and Economic Issues, 28(3), 395–409.
Haynes, G. W., Rowe, B. R., Walker, R., & Hong, G. (2000).
The
differences in financial structure between women-and men-
owned family businesses. Journal of Family and Economic
Issues, 21(3), 209–226.
Heck, R. K. Z., & Trent, E. S. (1999). The prevalence of family
business from a household sample. Family Business Review, 12,
209–224.
Hisrich, R. D., & Brush, C. G. (1987). Women entrepreneurs: A
longitudinal study. In frontiers of entrepreneurship research (pp.
187–189). Wellesley, MA: Babson College.
Hundley, G. (2001). Domestic division of labor and
self/organiza-

tionally employed differences in job attitudes and earnings.
Jang, Y. L. (1995). Human Capital-Enhancing Expenditures: A
Comparison of Female-headed and Married Couple Households.
(Doctoral dissertation, University of Missouri, Columbia).
Jones, C. T. (2003). Predicting the financial success and
occupational
wellbeing of micro-business owners: An integrated model of
personality and the work-family interface. Australian Journal of
Psychology, Supplement, 131.
Kale, S., & Arditi, D. (1998). Business failures: Liabilities of
newness, adolescence and smallness. Journal of Construction
Engineering and Management, 124(6), 458–464.
Kalleberg, A., & Leicht, K. T. (1991). Gender and
organizational
performance. Determinants of small business survival and
success. Academy of Management Journal, 34, 136–161.
Kangasharju, A., & Pekkala, S. (2002). The role of education
and
self-employment success in Finland. Growth and Change, 33,
216–237.
Kaplan, E. (1988). Women entrepreneurs: Constructing a
framework

to examine venture success and business failures. In Frontiers
of
entrepreneurship research pp. 625–637. Wellesley, MA: Babson
College.
Kepler, E., & Shane, S. (2007). Are male and female
entrepreneurs
really that different? Contract report for the office of advocacy,
U.S. small business administration. Retrieved on April 20, 2008
from http://www.sba.gov/advo.
Kirkwood, J. (2009). Spousal roles on motivations for
entrepreneur-
ship: A qualitative study in New Zealand. Journal of Family and
Economic Issues, 30(4), 372–385.
Lansberg, I. (1983). Managing human resources in family firms:
The
problem of institutional overlap. Organizational Dynamics,
12(1), 39–46.
Lee, Y., Danes, S., & Shelley, M. (2006). Work roles,
management and
perceived well-being for married women within family busi-
nesses. Journal of Family and Economic Issues, 27(3), 523–541.
Loscocco, K. A. (1997). Work-family linkages among self-
employed
women and men. Journal of Vocational Behavior, 50, 204–226.
Loscocco, K. A., & Leicht, K. T. (1993). Gender, work-family

linkages, and economic success among small business owners.
Journal of Marriage and the Family, 55(4), 875–877.
Loscocco, K. A., Robinson, J., Hall, R. H., & Allen, J. K.
(1991).
Gender and small business: An inquiry into women’s relative
disadvantage. Social Forces, 70, 65–85.
Lowrey, Y. (2006). Women in business: A demographic review
of
women’s business ownership. Office of advocacy, U. S. small
business administration. Retrieved on April 20, 2008 from
http://www.sba.gov/advo.
Marion, R. M. (1988). Integration in the family firm: When the
family
system replaces controls and culture? Family Business Review,
1(4), 399–417.
Masuo, D., Fong, G., Yanagida, J., & Cabal, C. (2001). Factors
associated with business and family success: A comparison of
single manager and dual manager family business households.
McMillan, D. W., & Chavis, D. M. (1986). Sense of community:
A
definition and theory. Journal of Community Psychology, 14(1),
6–23.

Myrie, J., & Daly, K. (2009). The use of boundaries by self-
employed, home-based workers to manage work and family: A
qualitative study in Canada. Journal of Family and Economic
Issues, 30(4), 386–398.
Olson, P. D., Zuiker, V. S., Danes, S. M., Stafford, K., Heck, R.
K. Z.,
& Duncan, K. A. (2003). The impact of family and business on
family business sustainability. Journal of Business Venturing,
18, 639–666.
Orser, B., & Hogarth-Scott, S. (2002). Opting for growth:
Gender
dimensions of choosing enterprise development. Canadian
Journal of Administrative Sciences, 19(3), 284–301.
J Fam Econ Iss (2010) 31:458–474 473
123
http://www.kauffman.org/entrepreneurship/kauffman-
campuses.aspx
http://www.kauffman.org/entrepreneurship/kauffman-
campuses.aspx
http://www.sba.gov/advo
http://www.sba.gov/advo
Philbrick, C., & Fitzgerald, M. (2007). Women in business-
owning

families: A comparison of roles, responsibilities, and predictors
of family functionality. Journal of Family and Economic Issues,
28(4), 618–634.
Romano, C. A., Tanewski, G. A., & Smyrnios, K. X. (2000).
Capital
structure decision making: A model for family business. Journal
of Business Venturing, 16, 285–310.
Schieman, S., & Young, M. (2010). Economic hardship and
family-
to-work conflict: The importance of gender and work
conditions.
Journal of Family and Economic Issues, Online first, doi:
10.1007/s10834-010-9206-3.
Schmidt, R. A., & Parker, C. (2003). Diversity in independent
retailing: Barriers and benefits—the impact of gender. Interna-
tional Journal of Retail & Distribution Management, 31(8/9),
428–439.
SCORE Women Entrepreneurs Web Site Retrieved on October
8,
2009 from http://www.score.org/women/site.html.
Small Business Administration. (2002). Programs and services
to
help you start, grow and succeed. Retrieved on April 24, 2008
from http://www.sba.gov.

Soldressen, L. S., Fiorito, S. S., & He, Y. (1998). An
exploration into
home-based businesses: Data from textile artists. Journal of
Small Business Management, 36, 33–44.
Sonfield, M. C., & Lussier, R. N. (2009). Gender in family
business
ownership and management: A six-country analysis. Interna-
tional Journal of Gender and Entrepreneurship, 1, 96–117.
Stafford, K., Duncan, K., Danes, S., & Winter, M. (1999). A
research
model for sustainable family businesses. Family Business
Review, 12, 197–208.
Stanforth, N., & Muske, G. (2001). An exploration of
entrepreneur-
ship. Stillwater: Department of Design, Housing & Merchandis-
ing, Oklahoma State University.
Tuttle, R., & Garr, M. (2009). Self-employment, work-family
fit, and
mental health among female workers. Journal of Family and
Economic Issues, 30(3), 282–292.
Walch, D., & Merante, J. (2007). What is the appropriate
business
continuity management staff size? Journal of Business Continu-
ity and Emergency Planning, 2(3), 240–250.
Walker, E., & Brown, A. (2004). What success factors are

important
to small business owners? International Small Business Journal,
22(6), 577–594.
Walker, D., & Joyner, B. E. (1999). Female entrepreneurship
and the
market process: Gender-based public policy considerations.
Journal of Developmental Entrepreneurship, 4(2), 95–116.
Watson, J. (2002). Comparing the performance of male and
female
controlled businesses: Relating outputs to inputs. Entrepreneur-
ship Theory and Practice, 26(3), 91–100.
Werbel, J. D., & Danes, S. M. (2010). Work family conflict in
new
business ventures: The moderating effects of spousal commit-
ment to the new business venture. Journal of Small Business
Management, 48(3), 421–440.
Weigel, D. J., & Ballard-Reisch, D. S. (1997). Merging family
and
firm: An integrated systems approach to process and change.
Winter, M., Danes, S. M., Koh, S., Fredericks, K., & Paul, J. J.
(2004). Tracking family businesses and their owners over time:
panel attrition, manager departure and business demise. Journal

of Business Venturing, 19, 535–559.
Winter, M., Fitzgerald, M. A., Heck, R. K. Z., Haynes, G. W., &
Danes, S. M. (1998). Revisiting the study of family businesses:
Methodological challenges, dilemmas, and altermative
approaches. Family Business Review, 11(3), 239–252.
Zody, Z., Sprenkle, D., MacDermid, S., & Schrank, H. (2006).
Boundaries and the functioning of family and business systems.
Author Biographies
Yoon G. Lee, PhD is an Associate Professor in the Department
of
Family, Consumer, and Human Development at Utah State
Univer-
sity. She received her PhD from University of Missouri-
Columbia.
Dr. Lee’s research interests include household financial
behavior,
with an emphasis on women, elderly, and baby boomers. Her
current
topics deal with consumer and mortgage debts among near-
retirees,
retirement savings of older minorities, and business success &

management issues in family businesses.
Cynthia R. Jasper, PhD is a Professor in the Department of
Consumer Science at the University of Wisconsin–Madison. Her
doctoral degree is from the University of Wisconsin–Madison.
She
also serves as the Chair of the Department of Interdisciplinary
Studies
in Human Ecology. Dr. Jasper has been named the Vaughn
Bascom
Professor of Women and Philanthropy. Dr. Jasper’s research
interests
include consumer behavior and management within the retailing
settings, women and philanthropy, and succession and
management
issues in family businesses.
Margaret A. Fitzgerald, PhD is an Associate Professor in the
Department of Human Development and Family Science at
North
Dakota State University in Fargo. Her PhD is from Iowa State
University. Dr. Fitzgerald’s research interests include
copreneurial
couples, gender and management issues, and business social
respon-

sibility in family businesses.
474 J Fam Econ Iss (2010) 31:458–474
123
http://dx.doi.org/10.1007/s10834-010-9206-3
http://www.score.org/women/site.html
http://www.sba.gov
Copyright of Journal of Family & Economic Issues is the
property of Springer Science & Business Media B.V.
and its content may not be copied or emailed to multiple sites or
posted to a listserv without the copyright
holder's express written permission. However, users may print,
Continuing Education Mitigates the Negative Consequences
of Adolescent Childbearing
Kate Sullivan • Jamie Clark • Brian Castrucci •
Rachel Samsel • Vincent Fonseca • Imelda Garcia
Published online: 5 March 2010
� Springer Science+Business Media, LLC 2010
Abstract Beginning childbearing during adolescence is

consistently linked with negative outcomes for both chil-
dren and parents. Many have attributed this association to
maternal background characteristics which are often diffi-
cult to change through policy. Though maternal educa-
tional attainment is often a side effect of adolescent
childbearing, it also represents a potential avenue through
which we can help young mothers overcome the obstacles
associated with an early birth. The data for this study come
from the 1997 Child Development Supplement of the Panel
Study of Income Dynamics, a nationally representative
sample of mothers and their children (N = 3,193). Data are
used to explore the cognitive stimulation and emotional
support in the home, measured using the HOME Scale
(Caldwell and Bradley in Home observation for measure-
ment of the environment. University of Arkansas at Little
Rock, Little Rock, 1984). OLS regression models how
maternal education moderates the association between age
at first birth and quality of children’s home environment.

Adolescent mothers scored significantly lower on the
indicator of home environment than older mothers. How-
ever, when continuing education was considered, maternal
age at first birth was no longer significantly associated with
the home environment. The negative consequences of early
births were mediated by adolescent mothers’ continuing
education efforts. While interventions are needed to reduce
adolescent childbearing, these results highlight the need to
ensure that adolescent mothers are provided support to
continue their education following delivery. The negative
consequences of adolescent births are not inevitable.
Encouraging school retention may help young mothers
form a safe, healthy, nurturing, and developmentally
appropriate home environment.
Keywords Adolescent childbearing � Education �
Child development � Home environment
Introduction
After over a decade of declining adolescent birth rates,
recent data indicate an increase in the rate of adolescent

births [2]. For women aged 15–19 years, the birth rate in
2006 was 41.9 births per 1,000 females, a three to four
percent increase compared to previous years. Nearly half a
million infants are born to adolescent mothers every year in
the United States.
For most adolescents, these births are unexpected and
have long reaching implications for both mothers and
children [3, 4]. Children born to adolescent mothers are at a
greater risk for a variety of negative behavioral and
developmental outcomes across the life course. Children
born to adolescent mothers are more likely to have both
internalizing and externalizing behavior problems [5–14].
Children with adolescent mothers also have lower reading
and math scores during childhood and poorer academic
trajectories through adolescence [15–17].
Compared to children born to adult mothers, children
born to adolescent mothers are also at greater risk for
growing up in home environments marked by lower emo-

tional and cognitive support [18, 19]. Adolescent mothers
fare less well in evaluations and observations of their home
environments than older mothers. Early childbearing is
K. Sullivan (&) � J. Clark � B. Castrucci � R. Samsel �
V. Fonseca � I. Garcia
Office of Program Decision Support, Texas Department of State
Health Services, MC1922, PO Box 149347, Austin,
TX 78714-9347, USA
e-mail: [email protected]; [email protected]
123
Matern Child Health J (2011) 15:360–366
DOI 10.1007/s10995-010-0585-8
linked with difficulties in constructing a safe and devel-
opmentally appropriate home environment for children.
New research has indicated that many of these disad-
vantages in children’s home environment and development
may be attributed to mothers’ family background and so-
ciodemographic characteristics rather than to the timing of

first birth. Adolescent mothers are more likely to come
from families with fewer resources, poorer neighborhoods,
and more family instability [5, 10, 14, 17, 20, 21, 22].
Research also suggests that young mothers have lower
levels of educational attainment and aspirations than
women who delay childbearing [23–25]. Adolescent
mothers are more likely to drop out of school and receive
no postsecondary education [26–29].
In previous studies, mothers’ educational attainment has
been grouped into the broad range of family of origin and
sociodemographic factors that increase the likelihood that
women will have an adolescent birth and thus lead to neg-
ative outcomes for their children. This range of variables,
like annual household income or family structure, are often
defined as static variables and not easily changed through
policy or interventions. However, a mother’s educational
attainment may be better understood as a dynamic variable
that can change over the course of her child’s life.

Maternal educational attainment can and often does
change after first birth. Over the course of young adult-
hood, many adolescent mothers are able to catch up to their
counterparts and achieve comparable rates of high school
completion [18, 30, 31]. The rebound in educational
attainment that some adolescent mothers experience by
later adulthood may also be paralleled by higher quality
home environments mothers are able to establish for their
children. Continuing education after an adolescent birth
may hold promise for mitigating the negative consequences
of early childbearing on child development.
Taking advantage of the longitudinal and intergenera-
tional nature of the Panel Study of Income Dynamics and
the Child Development Supplement, we investigate how
maternal age at first birth and educational attainment
impacts children’s home environments. We examine
whether continuing education mitigates the negative rela-
tionship between adolescent childbearing and home envi-

ronments. Though lower educational attainment is often a
side effect of adolescent childbearing, encouraging
continuing educational efforts represents a potential avenue
through which we can help young parents overcome the
obstacles associated with an early birth.
Data and Methods
The data for this study come from the Panel Study of
Income Dynamics (PSID). This survey was started in 1968
with 4,800 families, a national probability sample of
households in 1967, and was supplemented with a Latino/
Hispanic sample added in 1990. The survey was repeated
on an annual basis until 1997 when assessments took place
every other year. In 1997, a sample of PSID families with
children younger than 13 was selected for the Child
Development Supplement (CDS-I). This sample consisted
of one or two children from selected families (N = 3,563)
and included an oversample of low-income and minority
families. This supplement to the PSID original survey was

intended to provide an in depth look at child development.
This study uses an analysis sample of CDS-I families with
complete data on maternal education, marital history, and
the focal child development outcome (n = 3,193).
The primary outcome measure for this study was an
observational measure of cognitive stimulation and emo-
tional support parents provide children, known as the
Home Observation for Measurement of the Environment
Scale (HOME) [1]. The HOME Scale is based on obser-
vations and interviews conducted at the family’s home and
is widely used [32–35]. Depending on the child’s age, the
home environment was assessed for specific conditions,
facilities, and the social and emotional tone of mother–
child interactions. Higher scores indicate better, more
supportive home environments, the score ranging from 7 to
24. One of four comparable versions of the HOME Scale
was administered depending on the child’s age at assess-
ment: infant/toddler, early childhood, middle childhood, or

early adolescence.
Mothers of these children were classified into one of
three categories depending on age at first birth. The three
groups included women who were younger than 18 at first
birth, 18–19 years old, and 20 years or older. These cate-
gories were created based on previous literature while also
ensuring adequate cell sizes for each category [3, 17].
The PSID collected information annually on the edu-
cational attainment of all members of participating
households. To capture a dynamic indicator of maternal
education attainment, mothers’ education level was based
on two measurements: women’s grade level at the time
their first child was born and highest grade achieved when
their children participated in the CDS-I in 1997. A three
level variable was constructed to represent education prior
to first birth: not a high school graduate, a high school
graduate, and had attended some college. Continuing
education efforts were determined by changes in educa-

tional attainment by 1997. Changes were based on
improvements in education defined as graduating from
high school or attending at least some college.
Several control variables were also constructed based on
factors determined to be influential on children’s home
environment in previous work. Demographic variables
included child’s age and gender, maternal race/ethnicity,
Matern Child Health J (2011) 15:360–366 361
123
and family structure. Maternal race/ethnicity was catego-
rized as non-Hispanic White, non-Hispanic Black/African
American, Hispanic, and Other. Family structure was
measured by mother’s marital status at birth, the presence
of a father figure in 1997, and presence of siblings. The
indicator of socioeconomic well being was computed from
reports of Aid to Families with Dependent Children
(AFDC) receipt from 1994 through 1997 to determine

exposure to poverty during childhood. AFDC was awarded
to families with children and low or no income.
Plan of Analysis
The goal of the analyses is to examine variance in home
environments by timing of first birth and maternal educa-
tional attainment. We focus on first births that occurred
while women were younger than 18 years old to determine
if continuing education can make up for the disparity
in these families home environments. Analyses explore
whether educational attainment after first birth helps
mothers rebound from early births, thereby mitigating the
negative consequences of having an early birth. The first
step of the analysis includes bivariate analyses of home
environment by maternal age at first birth and educational
attainment. The second step of the analysis involves mul-
tivariate regression analyses to isolate the association
between continuing education and age at first birth on
home environment. As the HOME score is a continuous

variable, Ordinary Least Squares (OLS) regression will be
used to model the linear association between the home
environment and timing of first birth and maternal educa-
tion. Coefficients from OLS regression models can be used
to predict HOME scores, adjusted for variables in the
model. Model 1 provides a baseline examination of the
association between timing of first birth and home envi-
ronment. Model 2 examines whether continuing education
efforts moderate the relationship between age at first birth
and home environment. Given the complex sampling nat-
ure of the PSID and CDS, complex survey techniques and
1997 sampling weights were used in all analyses.
Results
Sample Description
Half of the children in the sample were female. The
average age of children was 7 years. Most mothers iden-
tified as non-Hispanic white (67%) while the remaining
families were non-Hispanic black (17%), Hispanic (14%),

or Other race/ethnicity (3%).
On average, mothers were 34 years old at the 1997
assessment. At first birth, most women were at least
20 years old (76%), 15% of women were 18–19 years old,
and 9% were less than 18 years old. Most women (71%)
were married at first birth. Two-thirds of households
reported a father figure was present in the 1997. Over 90%
of women reported having more than one child. 13% of
families reported receiving AFDC assistance between 1994
and 1997.
Forty-one percent of women had not graduated from
high school prior to first birth, 22% graduated from high
school, and 35% of women had attended at least some
college. Measurement of continuing education efforts after
first birth revealed that 25% of mothers graduated from
high school and 15% of mothers had attended at least some
college by 1997.
Bivariate Analyses

Nearly one out of ten children were born to mothers who
were 17 years or younger at first birth. None of these young
mothers were able to graduate from high school prior to
first birth and over half never graduated from high school.
The second group, mothers who were 18-19 years old at
first birth, had moderately better educational attainment.
Less than 30% of these mothers never graduated from high
school. Eighteen percent graduated from high school prior
to first birth and 3% attended college prior to first birth.
Older mothers, those at least 20 years old at first birth,
reported better educational attainment than younger
mothers. Only 8% of these women never graduated from
high school. Nearly half of the women attended at least
some college before first birth.
The mean HOME score was 19.4 though HOME scores
evidenced significant variation across maternal age at first
birth and educational attainment (Table 1). Women who
were at least 20 years at first birth received the highest

Table 1 Mean HOME scores by independent and control
variables
N HOME scores
Mean 95% Confidence
interval
Overall 3,193 19.44 19.28–19.60
Maternal age at first birth
18 Years 425 17.41 16.94–17.87
18–19 Years 615 18.11 17.75–18.47
20? Years 2,153 19.95 19.77–20.13
Educational attainment at first birth
No high school graduation 1,539 18.30 18.08–18.53
High school graduate 704 19.53 19.18–19.87
Attended at least some college 950 20.67 20.41–20.93
Note: Categories with non-overlapping confidence intervals are
significant different
362 Matern Child Health J (2011) 15:360–366
123
mean HOME score at 19.9 (95% CI 19.8–20.1). Adolescent

mothers have the lowest mean score at 17.4 (95% CI 19.6–
17.9) though not significantly different than 18 and 19 year
old mothers (M = 18.1, 95% CI 17.7–18.5).
Mothers who attended at least some college before first
birth have the highest mean scores (M = 20.7, 95% CI
20.4–20.9). Mothers who had not graduated from high
school had the lowest mean HOME scores (M = 18.3, 95%
CI 18.1–18.5). Mothers who had graduated from high
school had HOME scores that fell between more and less
educated women (M = 19.5, 95% CI 19.2–19.9). These
results are likely confounded by maternal age. Independent
effects will be explored in the following multivariate
analyses and will also explore how continuing education
moderates this association.
Multivariate Analyses
The multivariate analyses explore how maternal educational
attainment may moderate the effect of maternal age and
education at first birth (Table 2). That is, can continuing

education following an adolescent birth mitigate the nega-
tive consequences associated with being an adolescent at first
birth? Even with child, maternal, and family characteristics
as well as maternal education at first birth as control vari-
ables, younger mothers received lower HOME scores than
households with older mothers. Young mothers received
HOME scores that were 3% lower than older mothers.
When indicators of continuing education after first birth
were included in the model, maternal age at first birth was
no longer significantly associated with HOME scores. The
negative consequences of an early birth were mediated by
women’s continuing education efforts among adolescent
mothers and mothers aged 18–19 years. Model 2 demon-
strates that there was no significant difference in HOME
scores by age. Differences in the home environment are
due to variation across categories of educational attainment
and continuing education efforts. Regardless of age,
mothers who never graduated high school had the lowest

HOME scores. These mothers were at the greatest risk for
negative home environments while more educated mothers,
young and old alike, received higher scores on home
environment.
In both models, disparity in children’s HOME scores
persisted by family structure and race/ethnicity. Even after
accounting for education and the other control variables,
Hispanic and black children received significantly lower
HOME scores than their white counterparts. Similarly,
children without a father figure in the household in 1997
scored significantly lower than children living with a father
figure.
For the adolescent mothers, continuing education efforts
generally included returning to and graduating from high
school. At first birth, none of these adolescent mothers had
graduated from high school. Among those who had not
graduated from high school, 46% of the women returned to
school to graduate from high school. Very few of the

youngest mothers (9%) who had not graduated from high
school before first birth went onto attend college by the
1997 assessment. Model 2 indicates that for the youngest
mothers, returning to high school or attending some college
was associated with significant increases in HOME scores.
Young mothers who returned to school had up to 5%
higher HOME scores than young mothers who did not
return to school. Continuing education for adolescent
mothers was associated with more positive home envi-
ronments for their children.
Table 2 OLS regression models for HOME scores
Model 1 Model 2
Coefficient SE Coefficient SE
Intercept 13.96*** 0.44 13.21*** 0.44
Child characteristics
Age in years 0.45*** 0.02 0.45*** 0.02
Gender
(Male)

Female 0.27* 0.11 0.30** 0.11
Family characteristics
Mother’s marital status at first
birth
-0.19 0.17 -0.15 0.17
Father figure present (1997) 1.87*** 0.14 1.90*** 0.14
Mother had more than 1 child -0.15 0.20 -0.11 0.20
AFDC receipt (1994-1997) -0.11 0.19 0.03 0.19
Maternal characteristics
Maternal age (1997) 0.04*** 0.01 0.04** 0.01
Race/ethnicity
(White)
Black, African American -1.37*** 0.17 -1.39*** 0.17
Hispanic -1.50*** 0.22 -1.23*** 0.21
Other 0.02 0.32 -0.06 0.35
Maternal age at first birth
(Older than 20 years)
17 Years and younger -0.51* 0.24 -0.13 0.24

18–19 Years -0.47* 0.20 -0.31 0.20
Maternal education at first birth
(Less than HS graduation)
HS graduate 0.18 0.19 0.86*** 0.23
Attended at least some
college
1.11*** 0.18 1.96*** 0.22
Continuing education efforts by 1997
HS graduate 0.60** 0.20
Attended at least some
college
0.92*** 0.19
Note: * P 0.05, ** P 0.01, *** P 0.001
123
Among the 18 and 19 year old mothers, nearly three out
of four of these women had not graduated from high school

before first birth. Even for these slightly older mothers, the
most common continuing education efforts included grad-
uating from high school. Among mothers who had not
graduated from high school prior to first birth, 45% of these
women returned to finish high school and 12% attended at
least some college by 1997. Mothers who returned to
school after first birth at age18 or 19 received significantly
higher HOME scores, even after controlling for educational
attainment at first birth, family structure, and SES indica-
tors among other controls. Among mothers who were
18–19 years old at first birth, continuing education efforts
were associated with a 4–10% higher HOME score, a sig-
nificant increase in the quality of their home environments.
Discussion
The goal of this study was to explore ways that the negative
consequences of adolescent childbearing for child well
being can be mitigated by maternal education. Using a
nationally representative sample of women and their chil-

dren, we examined whether continuing education could
help adolescent mothers overcome the challenges of an
early birth. The results from this study suggest that
maternal educational attainment has more lasting effects on
children’s well being and development than her age at first
birth.
Baseline models of the relationship between timing of first
birth and home environments revealed that early births are
associated with disadvantages in children’s home environ-
ments. Adolescent mothers were less likely to construct
emotionally and cognitively supportive and engaging envi-
ronments for their children. Women who delayed child-
bearing until their adult years provided better home
environments. However, this link disappeared when mater-
nal continuing education was considered. Rather, children’s
home environments depended more on mothers’ educational
attainment and continuing education efforts than the timing
of first birth. Continuing education following an adolescent

birth was associated with significant improvements in the
home environment, increasing the emotional and cognitive
support available to children. Mothers who went back to
school following early births provided substantially better
family environments for their children.
The data support previous findings that women are able
to overcome the hardships associated with an early birth if
they return to school. Many children born to young mothers
actually fare quite well suggesting that early childbearing
does not ‘‘inevitably or irreversibly’’ lead to lifelong
hardships for young mothers and their children [36]. The
results from this study suggest that educational attainment
is an important factor for helping young mothers improve
the long term outcomes for their children, even when
mothers return to school after the birth of their first child.
These results suggest that encouraging continued educa-
tional efforts may be fruitful in helping young mothers
overcome the obstacles associated with early births.

Studies have also highlighted the importance of making
comparisons of maternal age at first birth beyond a dichot-
omous variable of younger than versus older than 19 years.
Researchers and public health officials have specified addi-
tional categories such as 15–17 and 18–19 years old at first
birth compared to women aged 20–21 and 22 years and older
[3, 17]. The data from this study are consistent with this in
finding that none of the youngest mothers had graduated
from high school prior to first birth and some of the
18–19 year old mothers had already graduated. Though the
regression models suggested returning to high school yielded
similar benefits for both groups of young mothers, programs
developed to help young mothers should consider the dis-
parate barriers to continuing education that very young
mothers may face. Programs aimed at 18 year old mothers
can have a shorter duration as these adolescents are closer to
graduating. Helping a 15 year old mother graduate or com-
plete her GED requires longer interventions as these ado-

lescents may have more ground to cover in order to graduate
from high school or receive a GED.
Though young mothers who returned to school fared
better on the HOME Scale, continuing education efforts did
not erase all disparity in home environments. Even after
educational attainment and age at first birth were consid-
ered, racial/ethnic minority families and single parent
families scored considerably lower than their counterparts.
Children who were white and lived with a father figure
lived in significantly better home environments. Additional
research and intervention is required to help minority and
single parent families improve their home environments.
Additional limitations in this study included the diffi-
culty controlling for any inherent and confounding differ-
ences that may exist between adolescent and adult mothers.
It is unknown if adolescent mothers differ from older
mothers in meaningful ways that could account for dif-
ferences in the home environment (e.g., IQ, mental health,

neighborhood characteristics, history of abuse, family
size). Though these factors are important to consider, they
are often not available in the data, as is the case with PSID
and CDS data. Data quality issues are common when using
prospective, intergenerational data.
Conclusion
The costs of adolescent childbearing exceed nine billion
dollars annually [3, 4]. Several strategies are needed to
123
reduce these costs. A significant portion of these costs are
attributed to the behaviors, needs, and actions of the chil-
dren of adolescent mothers. While funding and interven-
tions are needed to reduce primary and secondary
adolescent childbearing, these results highlight the need to
ensure that adolescent mothers are provided support to
ensure educational achievement following delivery. Ado-

lescent mothers provide an identifiable target for intensive
case management or other interventions that can mediate
outcomes through encouraging educational achievement.
Investments in the educational attainment of adolescent
mothers can be measured in the improved success and
reduced costs associated with children of adolescent
mothers, as evidenced here.
Reducing the costs of adolescent births requires multi-
dimensional strategies. Prevention should be a priority to
ensure that adolescent births are avoided. However, when
an adolescent birth occurs, it is important to ensure that
young mothers have opportunities to continue education.
The findings in this study are consistent with the call from
others to consider schooling a public health priority, given
the benefits associated with educational attainment [37].
Strategies that ensure pregnant and postpartum adolescent
mothers can continue to attend school, online educational
solutions, and cooperatives with local community colleges

to facilitate high school and post-secondary educational
attainment are examples of policy and program strategies
needed to ensure that one undesired outcome is not allowed
to have additional and long lasting negative impacts for the
adolescent mothers, their children, and society.
This study provides evidence that encouraging school
retention and returning to school among adolescent may
yield direct benefits for children. Mothers who have greater
educational attainment are more likely to provide healthy
and supportive home environments for their children.
Helping adolescent mothers form a safe, healthy, nurturing,
and developmentally appropriate home and family envi-
ronment for children may depend on educational
attainment.
References
1. Caldwell, B. M., & Bradley, R. H. (1984). Home observation
for
measurement of the environment. Little Rock: University of
Arkansas at Little Rock.

2. Martin, J. A., Hamilton, B. E., Sutton, P. D., Ventura, S. J.,
Menacker, F., & Kirmeyer, S. (2009). Births: Final data for
2006.
National Vital Statistics Reports, 55(1), 1–26.
3. Hoffman, S. D., & Maynard, R. A. (2008). Kids having kids:
The
economic and social consequences of teenage childbearing.
Washington, DC: Urban Institute Press.
4. Maynard, R. A. (1997). Kids having kids. Washington, DC:
Urban Institute.
5. Pogarsky, G., Thornberry, T. P., & Lizotte, A. J. (2006).
Devel-
opmental outcomes for children of young mothers. Journal of
Marriage and Family, 68, 332–344.
6. Pogarsky, G., Lizotte, A. J., & Thornberry, T. P. (2003). The
delinquency of children born to young mothers: Results from
the
Rochester youth development study. Criminology, 41(4), 1249–
1286.
7. Hofferth, S. L., & Reid, L. (2002). Early childbearing and
chil-
dren’s achievement and behavior over time. Perspectives on
Sexual and Reproductive Health, 34(1), 41–49.
8. Barber, J. S. (2001). Ideational influences on the transition to

parenthood: Attitudes toward childbearing and competing alter-
natives. Social Psychology Quarterly, 64(2), 101–127.
9. Geronimus, A. T., Korenman, S., & Hillemeier, M. M.
(1994).
Does young maternal age adversely affect child development?
Evidence from cousin comparisons in the United States. Popu-
lation and Development Review, 20(3), 585–609.
10. Turley, R. N. L. (2003). Are children of young mothers
disad-
vantaged because of their mother’s age or family background?
Child Development, 74(2), 465–474.
11. Jaffee, S., Caspi, A., Moffitt, T., Belsky, J., & Silva, P.
(2001).
Why are children born to teen mothers at risk for adverse out-
comes in young adulthood? Results from a 20-year longitudinal
study. Development and Psychopathology, 13(02), 377–397.
12. Cooksey, E. C. (1997). Consequences of young mothers’
marital
histories for children’s cognitive development. Journal of Mar-
riage and the Family, 59(2), 245–261.
13. Fergusson, D. M., & Woodward, L. J. (1999). Maternal age
and
educational and psychosocial outcomes in early adulthood. The

Journal of Child Psychology and Psychiatry and Allied Disci-
plines, 40(03), 479–489.
14. Nagin, D. S., Pogarsky, G., & Farrington, D. P. (1997).
Adoles-
cent mothers and the criminal behavior of their children. Law &
Society Review, 31(1), 137–162.
15. Hardy, J. B., Shapiro, S., Astone, N. M., Miller, T. L.,
Brooks-
Gunn, J., & Hilton, S. C. (1997). Adolescent childbearing
revisited: The age of inner-city mothers at delivery is a deter-
minant of their children’s self-sufficiency at age 27 to 33. Pedi-
atrics, 100(5), 802–809.
16. Hardy, J. B., Astone, N. M., Brooks-Gunn, J., Shapiro, S., &
Miller, T. L. (1998). Like mother, like child: Intergenerational
patterns of age at first birth and associations with childhood and
adolescent characteristics and adult outcomes in the second
generation. Developmental Psychology, 34, 1220–1232.
17. Levine, J. A., Pollack, H., & Comfort, M. E. (2001).
Academic
and behavioral outcomes among the children of young mothers.
Journal of Marriage and the Family, 63(2), 355–369.
18. Hoffman, S. D. (2008). Updated estimtaes of the
consequences of

teen childbearing for mothers. In Kids having kids: Economic
costs and social consequences of teen pregnancy (pp. 74–118).
Washington, DC: The Urban Institute Press.
19. Garcia Coll, C. T., Hoffman, J., & Oh, W. (1987). The
social
ecology and early parenting of Caucasian adolescent mothers.
Child Development, 58(4), 955–963.
20. Cherlin, A. J. (1999). Going to extremes: Family structure,
children’s well-being, and social science. Demography, 36(4),
421–428.
21. Hoffman, S. D. (1998). Teenage childbearing is not so bad
after
all…Or is it? A review of the new literature. Family Planning
Perspectives, 30(5), 236–243.
22. Levine, J. A., Emery, C. R., & Pollack, H. (2007). The well-
being
of children born to teen mothers. Journal of Marriage and
Family, 69(1), 105–122.
23. Glick, J. E., Ruf, S. D., White, M. J., & Goldscheider, F.
(2006).
Educational engagement and early family formation. Social
Forces, 84, 1391–1415.

123
24. Beutel, A. M. (2000). The relationship between adolescent
non-
marital childbearing and educational expectations: A cohort and
period comparison. The Sociological Quarterly, 41(2), 297–314.
25. Ribar, D. C. (1994). Teenage fertility and high school
comple-
tion. The Review of Economics and Statistics, 76(3), 413–424.
26. Hotz, V. J., McElroy, S. W., & Sanders, S. G. (1997). The
costs
and consequences of teenage childbearing for the mothers and
the
government. In Kids having kids (pp. 55–94). Washington, DC:
The Urban Institute Press.
27. Hoffman, S. D., Foster, E. M., & Furstenberg, F., Jr. (1993).
Reevaluating the costs of teenage childbearing. Demography,
30(1), 1–13.
28. Manlove, J. (1998). The influence of high school dropout
and
school disengagement on the risk of school-age pregnancy.
Journal of Research on Adolescence, 8(2), 187–220.
29. Kirby, D. (2002). The impact of schools and school
programs

upon adolescent sexual behavior. The Journal of Sex Research,
39(1), 27–33.
30. Furstenberg, F. F., Morgan, S. P., Moore, K. A., & Peterson,
J. L.
(1987). Race differences in the timing of adolescent intercourse.
American Sociological Review, 52(4), 511–518.
31. Furstenberg, F. F. (2003). Teenage childbearing as a public
issue
and private concern. Annual Review of Sociology, 29, 23–39.
32. Canfield, R. L., Henderson, C. R., Cory-Slechta, D. A., Cox,
C.,
Jusko, T. A., & Lanphear, B. P. (2003). Intellectual impairment
in
children with blood lead concentrations below 10 {micro}g per
deciliter. New England Journal of Medicine, 348(16), 1517–
1526.
33. Lumeng, J. C., Appugliese, D., Cabral, H. J., Bradley, R. H.,
&
Zuckerman, B. (2006). Neighborhood safety and overweight
status in children. Archives of Pediatrics and Adolescent Medi-
cine, 160(1), 25–31.
34. Olds, D. L., Robinson, J., Pettitt, L., Luckey, D. W.,
Holmberg,

J., Ng, R. K., et al. (2004). Effects of home visits by parapro-
fessionals and by nurses: Age 4 follow-up results of a
randomized
trial. Pediatrics, 114(6), 1560–1568.
35. Walkowiak, J., Wiener, J., Fastabend, A., Heinzow, B.,
Kramer,
U., Schmidt, E., et al. (2001). Environmental exposure to poly-
chlorinated biphenyls and quality of the home environment:
Effects on psychodevelopment in early childhood. The Lancet,
358(9293), 1602–1607.
36. Furstenberg, F. F. (2003). Teenage childbearing as a public
issue
and private concern. Annual Review of Sociology, 29(1), 23–39.
37. Freudenberg, N., & Ruglis, J. (2007). Reframing school
dropout
as a public health issue. Preventing Chronic Disease, 4(4),
A107.
123
Copyright of Maternal & Child Health Journal is the property of
Springer Science & Business Media B.V. and

its content may not be copied or emailed to multiple sites or
posted to a listserv without the copyright holder's
express written permission. However, users may print,

New ways of working does flexibility in time and location o.docx

More Related Content

Similar to New ways of working does flexibility in time and location o.docx (20)

More from henrymartin15260 (20)

Recently uploaded (20)

New ways of working does flexibility in time and location o.docx