ROLE OF SOCIAL NETWORKS ON THE PERFORMANCE OF WOMEN OWNED SMALL AND MEDIUM ENTERPRISES IN MIGORI COUNTY, KENYA

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ROLE OF SOCIAL NETWORKS ON THE PERFORMANCE OF WOMEN OWNED SMALL AND MEDIUM
ENTERPRISES IN MIGORI COUNTY, KENYA
Obiero, S. A., Njeru, E., & Muriithi, S.

- 253 - | The Strategic Journal of Business & Change Management. ISSN 2312-9492(Online) 2414-8970(Print). www.strategicjournals.com
Vol. 5, Iss. 3, pp 253 - 270, July 19, 2018. www.strategicjournals.com, ©strategic Journals
ROLE OF SOCIAL NETWORKS ON THE PERFORMANCE OF WOMEN OWNED SMALL AND MEDIUM
ENTERPRISES IN MIGORI COUNTY, KENYA
Obiero, S. A.,*1 Njeru, E.,2 & Muriithi, S.3
*1 MBA Candidate, Kenya Methodist University [KEMU], Nairobi, Kenya
2 Lecturer, Kenya Methodist University [KEMU], Nairobi, Kenya
3 Lecturer, Kenya Methodist University [KEMU], Nairobi, Kenya
Accepted: July 16, 2018
ABSTARCT
The general objective of the study was to establish the role of social networks on the performance of women
owned small and medium enterprises in Migori County. The study used descriptive survey design. The target
population for this study was 7,000 women who own SMEs in Migori County. The research adopted a sample
size of 1400 women owned SMEs. The study employed stratified random sampling techniques to obtain the
required sample sizes. The data collections instruments was structured questionnaires which were distributed
to the respondents and were later collected for further analysis. This study used the Cronbach's Alpha for the
five point Likert scale items. The study concluded that social network diversity is positively correlated with
Performance of Women Owned Small and Medium Enterprises in Migori County. The correlation was also
significance thus women running Small and Medium Enterprises in Migori County ought to lay more
emphasis on social network diversity. It was further concluded that social network diversity allowed for
consultation with members. The study concluded that women uses social network strength mostly for
strategy analysis, objectives analysis, and problem analysis. It was also concluded that member’s religiously
assist any of their own when they are in serious problems. From the study it was concluded that structure
describes level of closeness or ties existing within a social group among the members; which could be
assessed by the frequency of their meetings or interactions. The study recommended that the county
government supplement the effort of these women by organizing workshops and training where expertise
from different regions and government department would be brought to give a talk on women
empowerment. National government should also partner with these women goods so as to provide them
with loans from women development loans, uwezo funds as well as youth empowerment funds.
Keywords: Social Network Diversity, Size, Strength, Structure, Women Owned Enterprises, Migori County

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INTRODUCTION
Entrepreneurship involves the capacity and
willingness to develop, organize and manage a
business venture along with any of its risks in
order to make a profit such as starting a new
business with the aim of making a profit out of
the activities of the business. Entrepreneurs are
widely recognized as the prime movers of
economic development; the people who translate
ideas into action (Wachira, Ngugi & Otieno, 2017).
An interesting though not widely accepted
definition of an entrepreneur is a person who has
the ability to scan and identify opportunities in his
or her environment, gather the resources
necessary to take advantage of the opportunities
and implement successful action to utilize the
opportunities. This definition identifies an
entrepreneur by their behavior rather than the
specific occupation they are involved in. Those
who have studied entrepreneurial behavior have
noted certain characteristics such as
innovativeness, ability and willingness to take
calculated risks, determination, insight, total
involvement, independence, need for
achievement, leadership ability and so on. The
benefits of entrepreneurship for development
and economic growth have been widely
highlighted. Entrepreneurship is seen as a self-
development strategy for community
development.
Entrepreneurship has been claimed to be the
single most important pathway out of poverty.
Hence, international development agencies are
demanding for stronger tools for expanding
employment and entrepreneurial opportunities
(Pages, 2005). For example, it is demanded to
improve the access of small and micro-enterprises
to finance information and technology and
develop new sound business practices.
Performance involves women actively engaging as
full members in the process of economic
development by coming up with individual
programs to boost their economic power. Women
performance in entrepreneurship ventures are an
essential precondition to the development of the
nation as a whole. Entrepreneurship amongst
women has been a recent concern. Various
national, regional and international conventions
and documentation have emphasized that
enabling the population, regardless of gender to
actively participate in social and economic
wellbeing is critical for long-term and sustainable
social, political and economic development of any
society. Women entrepreneurs have become
important players in the entrepreneurial
landscape (Pages, 2005).
Although the number is still small as compared to
businesses owned by men, this is encouraging as
it shows that women no longer adhere to the
stereotype that only men can be wage earners in
the family. Besides numerous obligations assigned
to women including reproductive chores such as
childcare and doing house work, women can find
success through their own businesses.
Many scholars have argued that aside lack of loan
and training, inability to develop adequate stock
of social networks was another bane of women
entrepreneurs (Basargekar, 2011; Kelley ,Brush,
Greene, & Litovsky 2010; Tundui & Tundui, 2013).
This was due to much family, work and business
responsibilities handled by most women
entrepreneurs (Tundui &Tundui, 2013). Sappleton
(2009) also contended that the growth of women
enterprises is closely related to the stocks of their
social networks.
Women's entrepreneurship is a central aspect of
economic development and public policy concern
in most African countries, scholarly research
about their entrepreneurial activities is
comparatively scarce. Issues explored by women
entrepreneurs as listed in previous studies include
their socio-demographic and economic
background, the factors that facilitated or
inhibited their decisions to become entrepreneurs
and their experiences in entrepreneurship
(Hisrich, Micheal & Shepherd, 2005). The
increasing use of networks for SMEs has been

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reported as a factor influential in the
developmental process of entrepreneurial activity
(Baines & Wheelock, 1998).
Entrepreneurs have ideas to test, and some
knowledge and competence to run the business,
but they also need complementary resources to
produce and deliver their goods or services
(Xavier et al., 2013).Women get support,
knowledge, and access to distribution channels
through their social networks. Entrepreneurs are
also linked to people and organizations that
interact among themselves and these contacts
can widen the availability of resources that can
maintain a new firm (Xavier et al., 2013).
Networking is a way of introducing or exchanging
resources (knowledge, financial capital) and
information within the group, which may lead to
potential opportunities. Entering a network
should be a strategic choice for every
entrepreneur. Since networks are bound up with
social, cultural, political, and economic structures;
networks affect the identity of the entrepreneur
individually and also the group as a whole, and
because social reciprocity and the positioning of
comparable individuals are part of a network and
networks are about gender as well (Hanson &
Blake, 2009).
Business performance is measured from the
economic perspectives in terms of increase in
sales volume or turnover, employee strength and
profits. Due to the nature of women and the
circumstances surrounding their entrepreneurial
motivation, variables such as business net worth
and outcome may be used in measuring their
entrepreneurial performance. The measurement
of business performance is also subject to the
entrepreneurial motivational factors which might
be pull or push and intrinsic or extrinsic (Ahuja &
Lampert 2010). The motivation is pull, push,
intrinsic or extrinsic inclined, and the performance
effect can be internally and/or externally
measured. Women who start businesses because
of lack of opportunity to advance their career will
measure their business performance in terms of
the growth they experience in their business
profit and career life.
Statement of the Problem
Women are the backbone of economics in
developing countries and especially Kenya. The
major problems faced by competition from
marketing problem and also better quality
procedures. Some factors that inhibit credit
availability to women include, lack of networking
skills, lack of leadership capacity and negative
attitude towards gender equality.
Bula and Tiagha (2012) state that the women
enterprises in Kenya do not usually make business
networking which they can use to improve their
knowledge of operating successful business
enterprises and Omwenga, Mukulu and Kanali
(2013) urge that women entrepreneurs face a
shortage of peer support networks compared
with men. Most women group members in
women group associations such as Kenya
Association of Women business Owners (KAWBO)
in Kenya and Migori County in particular, feels
that women entrepreneurs are not likely to be
involved in the business networking activities due
to family commitments which are hindrances as
much as they are aware that business networks
are important in the survival and success of their
enterprises (Kariuki, 2015).
Lack of use of business social networks by SMEs
limits the acquisition of resources and knowledge
essential for enterprises survival and growth
(Schoonjans, Cauwenberge & Bauwhede, 2011).
Women SMEs who do not rely on business social
networks suffer from isolation in the current
globalized market where they can export their
products (Rutashobya & Jaensson, 2004). Local
scholars like Misango and Ongiti (2013) have
written on the role played by women
entrepreneurs in reducing poverty. The factors
which affect the uptake of mentorship services by
women entrepreneurs in Kenya through a case
study of the mentorship programme of KAWBO

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has been looked at by Kariuki (2015). Large social
networks enable entrepreneurs to assemble
diverse resources and information. These social
networks include the personal network which the
entrepreneur has with certain individuals, and the
cultural dimension with an overall inclusion of the
family and community.
Most studies reflect a consensus that
entrepreneurial networks are important because
they provide entrepreneurs with a diverse
information and access to large pool of resources,
business opportunities, and markets.
Nevertheless, there is still rarity in studies at the
present times dealing with the role of
entrepreneurial networks usage in the success of
a business in Migori County context. The
researcher analyzed the role of social networks on
the performance of women owned enterprises in
Migori County since there was a glaring gap
between the social networking and performance
of women owned SMES in Migori County. This
study intended to enrich literature on business
networks, knowledge on women
entrepreneurship and fill the knowledge gap.
Objective of the Study
The general objective was to establish the role of
social networks on the performance of women
owned small and medium enterprises in Migori
County. The specific objectives were:-
 To assess the effect of social network diversity
on the performance of women owned
enterprises in Migori County
 To establish the effect of social network size
on the performance of women owned
enterprises in Migori County
 To analyze the effect of social network
strength (bonding) on the performance of
women owned enterprises in Migori County
 To establish the effect of social network
structure on the performance of women
owned enterprises in Migori County
LITERATURE REVIEW
Theoretical Literature Review
The social network Approach Theory
Social network theory views social relationships in
terms of nodes and ties. Nodes are the individual
actors within the networks, and ties are the
relationships between the actors. There can be
many kinds of ties between the nodes. Aldrich
and Zimmer (1986) illustrate this as the reason
why certain entrepreneurs are more successful
than others in starting up and continuing their
businesses.
The networks approach to entrepreneurship is
mainly based on the ground that entrepreneurs
build relations with the external environment, and
thereby have access to different information, in
order to define potential business opportunities,
and obtain required resources to start-up and
continue their businesses successfully. They get
support, knowledge, and access to distribution
channels through their social networks.
Entrepreneurs are also linked to people and
organizations that interact among themselves and
these contacts will widen the availability of
resources that sustain a new firm (Madey, Freeh,
Tynan & 2002). To meet their enterprise needs,
entrepreneurs will bring both those that are
closer and distant to them into their business
    
contribute to their entrepreneurial goals, these
social contacts are their social capital (Musolesi, &
Mascolo, 2007). Entrepreneurial networks span
relations to organizations, clusters of firms, as
well as to other people that can help them set up
the firm (Latour, 2005).
Resource-Based Entrepreneurship Theories
The Resource-based theory of entrepreneurship
argues that access to resources by founders is an
important predictor of opportunity based
entrepreneurship and new venture growth
(Alvarez & Busenitz, 2001). This theory stresses

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the importance of financial, social and human
resources (Aldrich & Ruef, 2006). Thus, access to
     
detect and act upon discovered opportunities
(Clausen, 2006). Financial, social and human
capital will represent three classes of theories
under the resource  based entrepreneurship
theories.
Social Network Theory; -Entrepreneurs will be
embedded in a larger social network structure
that constitutes a significant proportion of their
opportunity structure (Clausen, 2006). Shane and
Eckhardt, (2003) argue that an individual may
have the ability to recognize that a given
entrepreneurial opportunity exist, but might lack
the social connections to transform the
opportunity into a business startup. It is thought
that access to a larger social network will help
overcome this problem.
In a similar vein, Reynolds (2011) mentioned
social network in his four stages in the sociological
theory. The literature on this theory shows that
stronger social ties to resource providers and
facilitate the acquisition of resources and enhance
the probability of opportunity exploitation
(Aldrich & Cliff, 2003).Other researchers have
suggested that it is important for nascent
founders to have access to entrepreneurs in their
social network, as the competence these people
represents a kind of cultural capital that nascent
ventures and can draw upon in order to detect
opportunities (Gartner ,Shaver, Carter &
Reynolds, 2004; Kim, Aldrich & Keister, 2003).
The Network Founding Hypothesis
The network founding hypothesis investigates
how social networks influence the business start-
up (Brüderl & Preisendörfer, 1998). It consists of
the discovery and exploitation of entrepreneurial
opportunities (Shane & Venkataraman, 2000).
This hypothesis assumes that social network
resources, networking activities, and network
support positively influence the process of
business start-up (Hite, 2005). With respect to the
impacts of social network structures on business
start-up, both strong and weak social network ties
affect business start-up by providing scarce but
necessary information (Brüderl & Preisendörfer,
1998; Davidsson, 2003; Wagner, 2004).
Weak ties stimulate entrepreneurship and
facilitate the discovery of opportunities by
exposing nascent entrepreneurs to new and
different ideas, worldviews, and advice (Aldrich &
Zimmer, 1986; Granovetter, 2005). Strong ties
also assist nascent entrepreneurs by providing
unpaid family work and emotional support (Hite,
2005). For example, inexperienced nascent
entrepreneurs are more likely to depend on the
advice of their close friends than someone
unknown or not trusted, and their friends may
offer opportunities or resources that influence the
nascent  
2007; Hite, 2005; Woolcock, 2001). Micro-
entrepreneurs rely on the advice of friends and
relatives in order to maintain confidentiality and
control of the business (Davidsson, 2003).
Social networks also provide nascent
entrepreneurs with resources to leverage critical
resources for establishing businesses, including
information, advice, and access to financial
Gender and Social Networks in Microenterprise
capital (Brüderl & Preisendörfer, 1998; Davidsson,
2003). For emerging firms, these social network
resources are critical because they might not
otherwise be available or affordable (Hite, 2005;
Littunen, 2000). Despite these theoretical
findings, only a few studies demonstrate positive
effects of social networks on business startup.
The Network Success Hypothesis
The network success hypothesis suggests that
weak ties are most likely to assist inexperienced
entrepreneurs by providing links to organizations
and people who have valuable information and
resources regarding the growth and survival of
businesses (Casson & Giusta, 2007; Woolcock,
2001). Similarly, Hite (2005) and Fischer and
Reuber (2003) argue that if the emerging firm

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depends heavily on close personal relationships
that do not have resources, early growth would
be at risk. However, research has produced
inconsistent results with respect to the
relationship between e 
networks and business growth and survival.
       
supports the network success hypothesis by
finding that more numerous weak network ties
increase the probability of business growth.
However, some findings contradict the network
success hypothesis. Brüderl and Preisendörfer
(1998) found that both weak and strong ties have
positive influence on sales growth in a randomly
selected sample of business founders. These
scholars also report more strong ties lead to
higher chances of business survival, whereas more
weak ties have little effect on survival. In terms of
the impact of network resources on business
performance, Aldrich, Rosen, and Woodward
(1987) found that accessibility of network
resources is also positively correlated with
business profit.
Littunen (2000) find no significant positive effect
of network size, activities, and resources on
business performance. In fact, Bates (1994) finds
that heavy use of social networks is more likely to
result in less profitable and failure-prone
businesses. Brüderl and Preisendörfer (1998)
propose two reasons for these findings. The first
reason is related to measurement error. They
contend that instead of measuring network
structures or accessible resources, research
should measure actual utilization or support from
networks because entrepreneurs can improve
success only if they use their social networks for
their business. The second reason is that
entrepreneurs are more likely to compensate for
their lack of financial and human capital by
utilizing their social networks. Despite
entrepreneur efforts to extract capital from social
networks, studies tend to show no or even
negative effects of social network on business
performance (Brüderl & Preisendörfer, 1998).
Empirical Review
Networking, Collaborations, partnerships, or
alliances will provide the entrepreneur with
      &
Benzel, 2007). This will lead to an expanded web
of contacts which will eventually result in
recognition of new opportunities and a larger
network of clients and customers.
Jiang, Zimmerman, and Guo, (2012) conducted a
study on the growth of women-owned
businesses, the effects of intangible resources and
social competence. The study is to examine the
relationship of intangible resources and the
growth of women owned businesses. They are
focused on four intangible resources; social,
human, and reputational capital, as well as social
competence. Using case studies of women
entrepreneurs, they found that a woman
    utational
capitals are related to the growth of her business.
They also found that social competence
moderates the social, human, and reputational
capital growth relationship in women
entrepreneurs.
Ekpe, Mat, and Ekpe (2015) study on social
networks and women micro-enterprise
performance used a cross-sectional survey design,
with stratified random sampling, to collect data
from women entrepreneurs in Malaysia
Peninsula. The study also used t-test to determine
whether the success or failure of women micro-
enterprises was due to availability or lack of social
networks. It sampled two groups made up of well-
established women clients and nascent women
clients of a microfinance bank. The study found
that women entrepreneurs do not only need
loans and skill acquisition training but also social
networks to provide access to information and
other resources such as professional advice and
avenue for customers.
Oke, (2013) conducted a study on the effect of
social network on women entrepreneurs in
Nigeria. The paper discussed the findings of

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research on the impact of social networks on
business growth of women entrepreneurs in
AdoEkiti, Ekiti State in Nigeria. The sample of
women entrepreneurs used for this paper
comprised those working in the Tailoring sector.
In-depth interviews and questionnaire were used
for the gathering of data. To test the hypothesis
and analyze the data, a non-parametric statistical
techniques Chi-square test for independence
analysis and descriptive statistics were used. The
result indicated significant relationships between
business growth and social network. The study
further showed that family /friends shared the
largest part of the social network of the group
studied.
Tundui & Tundui (2013) empirical analysis of
social capital and enterprise performance in
Tanzania results showed that social capital plays a
significant role in the performance of women
owned businesses. The results demonstrated that
business owners who received business support
and advice from informal networks were more
likely to experience profits increase in their
enterprises than otherwise. Results also showed
that the impact of bridging social capital on
enterprise performance was more important than
the bonding social capital. They suggested that for
women business owners to enhance performance
of their enterprises they needed not only financial
capital and human capital, business training and
management skills, but also needed to develop,
promote and use appropriate forms of social
capital. In particular, women business owners
could be facilitated to establish social capital
beyond their immediate neighborhoods, such as
joining heterogeneous networks both formal and
informal. Efforts could also include strengthening
      
their sources of resources and information for
them to unleash their business growth potentials.
Abel (2016) conducted a study on dynamics of
social networks and growth of women-owned
firms in Eritrea. Paired samples t-test on firms in
Eritrea showed that social networks are more
important in the early stages than in the later
stages. Regression analysis revealed that social
networks have an impact on the growth of the
firm. From the empirical study, they provided
evidence to the effect that the social networks
were importance along the business lifecycle.
They also found that social networks contribute to
growth.
Conceptual Framework
Independent Variables Dependent Variable
Figure 1: Conceptual Framework
Source: Researcher, 2018
METHODOLOGY
A research design is the strategy for a study and
the plan by which the strategy is to be carried out
(Cooper & Schindler, 2014). The research design
that was employed in this study was descriptive
research design. The target population was 7000
and the accessible population was 700. A multiple
regression model was used to link the
independent variables and the dependent
variable. This led to the model as shown below;
Y= β0+ β 1X1+ β 2X2+ β 3X3+ β 4X4+ e
Where:
Y = Performance of Women Owned Enterprises
X1 = Network Diversity
X2 = Network Size
X3 = Network Strength
X4 = Network Structure
e= error term
Network Diversity
Network size
Network Strength
(Bonding)
Network Structure
Performance of
Women Owned
Small and Medium
enterprises

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β0 represents the constant/intercept
β1, β 2, β 3, β 4 are regression coefficients
RESULTS
Network Diversity
The respondents were asked to rate using a scale
of 1= strongly disagree, 2= disagree, 3=neutral, 4
agree, 5= strongly agree. The findings are shown
in table 1      
      
statement affirmed to, as little extent, equivalent
to mean sco   
has been taken to represent a statement affirmed
to as moderate extent, equivalent to a mean
         
  d been taken to represent a
statement affirmed to as great extent, equivalent
to a mean score of 3.5 to 5.0.
Table 1: Rating Of Network Diversity
variables
Mean
Pearson correlation
P-Value
Difference in education level helps us learn from each
other for betterment of the enterprise.
4.3797
0.684
0.007
Our social grouping is educating in terms of new trends
in businesses.
4.2664
0.781
0.001
Age diversity helps us be aware of changes taste and
satisfaction of products.
3.9332
0.566
0.04
Differences in sub-culture allow us to learn on how to
reach the needs of everyone.
3.5163
0.641
0.002
Religious beliefs we learn from our social network
teaches us to be hardworking
3.5431
0.563
0.004
Overall
3.9277
0.541
0.002
A majority of the respondents indicated that to a
great extent; Difference in education level helps
them learn from each other for betterment of the
enterprise. (Mean = 4.3797), our social grouping
was educating in terms of new trends in
businesses (mean = 4.2664), Age diversity helps us
be aware of changes taste and satisfaction of
products (mean = 3.9332), Religious beliefs we
learn from our social network teaches us to be
hardworking (mean = 3.5431) and Differences in
sub-culture allow us to learn on how to reach the
needs of everyone. (Mean = 3.5263). There was a
moderate to strong positive correlation amongst
the variables of network diversity (r ranging from
0.563 to 0.781). The findings further indicated
that there exist a significant relationship between
network diversity and performance of women
owned enterprises (P-value<0.05).
Network Size
The respondents were asked to rate using a scale
of 1= strongly disagree, 2= disagree, 3=neutral, 4
agree, 5= strongly agree.    
   d been taken to
represent a statement affirmed to, as little extent,
equivalent to mean score of 0 to 2.5. The score of
     ent a
statement affirmed to as moderate extent,
equivalent to a mean score of 2.6 to 3.4. The
      d been
taken to represent a statement affirmed to as
great extent, equivalent to a mean score of 3.5 to
5.0.

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Table 2: Rating Of Network Size
Variables
Mean
Pearson correlation
P-Value
I have built a social network with fellow women in the region.
3.9415
0.589
0.001
We occasionally do meet as county women members doing
small and medium enterprises.
3.6457
0.645
0.000
The social network I am in has members from different
regions in the county.
3.8746
0.606
0.027
Large size of members helps learn from each other the
challenges we share.
3.9945
0.568
0.047
Overall
3.8641
0.552
0.001
Under network size to a great extent; large size of
members helps learn from each other the
challenges we share. (Mean = 3.9945), I have built
a social network with fellow women in the region
(mean = 3.9415), the social network I am in has
members from different regions in the county
(mean = 3.8746) and we occasionally do meet as
county women members doing small and medium
enterprises (mean = 3.6457). There was a
moderate positive correlation amongst the
variables of network size (r ranging from 0.568 to
0.645). The findings further indicated that there
exist a significant relationship between network
size and performance of women owned
enterprises (P-value<0.05).
Network Strength
The respondents were asked to rate using a scale
of 1= strongly disagree, 2= disagree, 3=neutral, 4
agree, 5= strongly agree.    
      
represent a statement affirmed to, as little extent,
equivalent to mean score of 0 to 2.5. The score of
      
statement affirmed to as moderate extent,
equivalent to a mean score of 2.6 to 3.4. The
       
taken to represent a statement affirmed to as
great extent, equivalent to a mean score of 3.5 to
5.0.
Table 3: Rating Of Network Strength
Variables
Mean
Pearson correlation
P-Value
My social network starts with the members of my family.
3.5417
0.666
0
My social network gives me helpful opinions that assist my
enterprise
4.1516
0.723
0.015
We do regular group meetings with the women in my area.
3.9457
0.668
0.018
Aside from meeting for businesses, we meet to discuss several life
challenges.
4.0145
0.767
0.003
We occasionally set special days to visit each member and their
family.
4.3156
0.556
0.001
We religiously assist any of our members when they are in serious
problems
4.3525
0.656
0.001
overall
4.0536
0.156
0.001
With grand mean of 4.0536, it was deduced that
network strength significantly influenced
performance of women owned enterprises in
Migori County. The study further confirmed that
individually as measures of network strength to a
great extent; We religiously assist any of our
members when they are in serious problems
(Mean = 4.3525), we occasionally set special days
to visit each member and their family (mean =
4.3125), my social network gives me helpful
opinions that assist my enterprise (mean =
4.1516), Aside from meeting for businesses, we

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meet to discuss several life challenges (mean =
4.0145), we do regular group meetings with the
women in my area (mean = 3.9457) and my social
network starts with the members of my family
(mean = 3.5417). There was a moderate strong
positive correlation amongst the variables of
network strength (r ranging from 0.556 to 0.767).
The findings further indicated that there existed a
significant relationship between network diversity
and performance of women owned enterprises
(P-value<0.05). The findings support those of, that
is
Network Structure
The respondents were asked to rate using a scale
of 1= strongly disagree, 2= disagree, 3=neutral, 4
agree, 5= strongly agree.    
were taken to represent a
statement affirmed to, as little extent, equivalent
  
has been taken to represent a statement affirmed
to as moderate extent, equivalent to a mean
         
       
statement affirmed to as great extent, equivalent
to a mean score of 3.5 to 5.0.
Table 4: Rating of Network Structure
Variables
Mean
Pearson correlation
P-Value
The group I am in is registered with the registrar of societies.
3.6457
0.268
0.018
The group keeps well-documented records of all activities and
transactions
4.0015
0.267
0.003
Some of the groupings I am in are not registered
3.4516
0.156
0.001
Informal groupings are a times set to solve arising problems.
3.8916
0.368
0.000
Some groups I am in are not registered but keep well-
documented records of all activities and transactions
3.7113
0.201
0.029
Overall
3.7403
0.156
0.001
Under network structure, most of the
respondents indicated that to a great extent; The
group keeps well-documented records of all
activities and transactions (Mean = 4.0015),
Informal groupings are a times set to solve arising
problems (mean = 3.8916), some groups I am in
are not registered but keep well-documented
records of all activities and transactions (mean =
3.7113) and The group I am in is registered with
the registrar of societies (mean = 3.6457). On the
other hand to a moderate extent the respondents
were of the opinion that some of the groupings
they are in are not registered (mean = 3.4516).
There was a weak positive correlation amongst
the variables of network structure (r ranging from
0.156 to 0.3.68). The findings further indicated
that there exist a significant relationship between
network diversity and performance of women
owned enterprises (P-value<0.05)
Performance of Women Owned Enterprises
The respondents were asked to rate using a scale
of 1= strongly disagree, 2= disagree, 3=neutral, 4
agree, 5= strongly agree.    
disaWere taken to represent a
statement affirmed to, as little extent, equivalent
  
has been taken to represent a statement affirmed
to as moderate extent, equivalent to a mean
score of 2.       
       
statement affirmed to as great extent, equivalent
to a mean score of 3.5 to 5.0.
Table 5: Rating of Performance of Women Owned Enterprises
Variables
Mean
Pearson correlation
P-Value

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The sales revenue of the enterprise has been on the increase over
the years.
3.8945
0.785
0.000
The enterprise has realized an increased customer base over years
3.8812
0.645
0.002
The number of assets of the enterprise has been on the increase
over the years
3.7856
0.555
0.004
The enterprise has increased ability to attract better employees
3.7461
0.564
0.004
The enterprise has decreased its operating costs
3.7563
0.667
0.005
Overall
3.8173
0.156
0.002
The respondents were of the opinion that the
performance of their enterprises had significantly
changed due to network. More so the
respondents indicated that sales revenue of the
enterprise had been on the increase over the
years (Mean = 3.8945 enterprise had realized an
increased customer base over years (mean =
3.8812), number of assets of the enterprise had
been on the increase over the years (mean =
3.7856), enterprise had decreased its operating
costs (mean = 3.7563) and enterprise had
increased ability to attract better employees
(mean = 3.7461. There was a moderate to strong
positive correlation amongst the variables of
network diversity (r ranging from 0.558 to 0.785).
The findings further indicated that there existed a
significant relationship between network diversity
and performance of women owned enterprises
(P-value<0.05)
Regression and Correlation Analysis
Table 6: Pearson Correlation
Social network
diversity
Social network
size
Social network
strength
Social network
structure
Social network diversity
1.000
Social network size
.065
1.000
Social network strength
-.051
.140
1.000
Social network structure
-.015
.011
.293
1.000
Table 7: Model Summary
R
R Square
Adjusted R
Square
Std. Error
of the
Estimate
Change Statistics
R Square
Change
F Change
df1
df2
Sig. F
Change
.922
.851
.725
1.15397
.709
2.539
4
113
.000
a. Predictors: (Constant), social network structure, social network size, social network diversity, social
network strength
Table 8: ANOVA
Sum of Squares
df
Mean Square
F
Sig.
Regression
13.523
4
.881
2.539
.000
Residual
150.477
113
1.332
Total
164.000
117
a. Predictors: (Constant), social network structure, social network size, social network diversity, social
network strength
b. Dependent Variable: performance

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Table 9: Coefficients
Unstandardized
Coefficients
Standardized
Coefficients
t
Sig.
Collinearity Statistics
B
Std.
Error
Beta
Tolerance
VIF
(Constant)
.227
.185
1.227
.061
Social network diversity
.358
.097
.322
3.691
.003
.992
1.008
Social network size
.255
.096
.241
2.656
.007
.974
1.026
Social network strength
.422
.091
.419
4.637
.006
.892
1.121
Social network
structure
.333
.092
.317
3.619
.000
.913
1.095
Dependent Variable: Performance
CONCLUSION AND RECOMMENDATIONS
The study showed that to a great extent social
network diversity influenced performance of
women owned small and medium enterprises in
Migori County. The study found that in
performance of women owned small and medium
enterprises in Migori County, network size was
useful tool for strategy analysis, objectives
analysis and problem analysis. More so; large size
of members helped learn from each other the
challenges they shared. The study also revealed
that all the aspects of social network strength to a
great extent influenced performance of women
owned small and medium enterprises in Migori
County. The study found that structure as a social
network to a great extent influenced performance
of women owned small and Medium Enterprises
in Migori County.
Conclusions
From the study it was concluded that social
network diversity is positively correlated with
Performance of Women Owned Small and
Medium Enterprises in Migori County. It was
further concluded that social network diversity
allowed for consultation with members from
different regions in the county. The study
concluded that women used social network
strength mostly for strategy analysis, objectives
analysis, and problem analysis. It was also
concluded that  ed any
of their own when they were in serious problems.
From the study it was concluded that members
were not in total agreement that their social
network starts with the members of their family.
The study concluded that structure describes level
of closeness or ties existing within a social group
among the members; which could be assessed by
the frequency of their meetings or interactions. It
was also concluded that group keeps well-
documented records of all activities and
transactions as well as informal groupings are a
times set to solve arising problems. Hence social
network structure was key in successful
Performance of Women Owned Small and
Medium Enterprises in Migori County. From the
study it was concluded that members appreciated
that large size of members helped them learn
from each other and the challenges were shared.
Recommendations
The study showed that most women owning and
running small and medium enterprises in Migori
County had not fully embraced the role of social
network in enhancing the performance of their
businesses. It was therefore recommended that
the county government supplement the effort of
these women by organizing workshops and
training where expertise from different regions
and government department would be brought to
give a talk on women empowerment. National
government should also partner with these
women goods so as to provide them with loans
from women development loans, uwezo funds as

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well as youth empowerment funds. The study also
recommended that women be trained on the
emerging issues entrepreneurship as well as
accounting and record keeping so as to facilitate
the ease of accessing loans when need be. There
was need for public/ beneficiaries involvement in
the women empowerment process so as to ally
fear of misappropriation of government or donor
funds.
Recommendations for Further Studies
The study considered only women in Migori
county, future researchers could consider carrying
out a similar study in different counties to assess
any variation in responses. It would be interesting
to explore how the results obtained when the
methods applied in this study are applied in other
contexts for example in   . It
would be worthwhile establishing the extent to
which the findings of this study were
generalizable to other counties or settings.
Future researchers could also introduce different
variables other than diversity, size, strength and
structure and test their effect on Performance of
Women Owned Small and Medium Enterprises.
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