7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 1/24

 http://isb.sagepub.com/ International Small Business Journal

 http://isb.sagepub.com/content/30/5/536The online version of this article can be found at:

 DOI: 10.1177/0266242610384888

 2012 30: 536 originally published online 14 February 2011nternational Small Business Journal 

John WatsonNetworking: Gender differences and the association with firm performance 

Published by:

 http://www.sagepublications.com

 can be found at:International Small Business Journal Additional services and information for

http://isb.sagepub.com/cgi/alertsEmail Alerts: 

http://isb.sagepub.com/subscriptionsSubscriptions:

http://www.sagepub.com/journalsReprints.navReprints: 

http://www.sagepub.com/journalsPermissions.navPermissions: 

http://isb.sagepub.com/content/30/5/536.refs.htmlCitations: 

What is This?  - Feb 14, 2011OnlineFirst Version of Record

 - Jul 24, 2012Version of Record>> 

at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 2/24

 Article

mall Firms

isb j

Networking: Gender differences

and the association with firmperformance

 John WatsonThe University of Western Australia, Australia

Abstract

This study had two primary objectives. First, to determine whether there are any systematicnetworking diffesrences between male and female SME owners. Second, to determine if there isan association between networking and firm performance, for both male- and female-controlled

SMEs. The results of examining 2,919 male- and 181 female-controlled SMEs (with at least oneemployee) over a three-year period suggest little difference in the networks accessed by male andfemale SME owners after controlling for education, experience, industry, age and size. The results

also indicate that several formal and informal networks are positively associated with firm survivalbut only formal networks appear to be associated with growth. In particular, accessing an externalaccountant is associated with survival and growth for both male- and female-controlled SMEs.

Keywords

networking, gender, survival, growth

Introduction

Given an increasing awareness in the broader community of the significant contribution that small

and medium-sized enterprises (SMEs) make to job and wealth creation, examining the antecedent

factors associated with successful SME performance has become an important focus for policy-

makers and researchers (Low and MacMillan, 1988; Rosa et al., 1996). While previous research

indicates a link between SME success and various owner characteristics (such as education, experi-ence, planning and hours dedicated to the business), only recently have researchers begun to exam-

ine the association between the owner-manager’s personal networks (social capital) and rates of

 business formation, survival and growth (Aldrich, 1989; Cromie and Birley, 1992; Donckels and 

Lambrecht, 1995; Reese and Aldrich, 1995; De Clercq and Voronov, 2009).

Social capital theory suggests that owners’ ability to gain access to resources not under their

control cost-effectively through networking can influence the success of their ventures (Zhao and 

Aram, 1995). Florin et al. (2003) note that networking provides value to members by allowing

them access to social resources embedded within a network: that is, networking can provide the

Corresponding author: John Watson, Department of Accounting and Finance, The University of Western Australia, 35 Stirling Highway, Crawley

WA 6009, Australia

Email: John.Watson@uwa.edu.au

International Small Business Journal

30(5) 536–558

© The Author(s) 2011

Reprints and permission:

sagepub.co.uk/journalsPermissions.navDOI: 10.1177/0266242610384888

isb.sagepub.com

 at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 3/24

Watson 537

means by which SME owners can tap into needed resources ‘external’ to the firm (Jarillo, 1989).

Julien observed that this form of cooperation can facilitate the achievement of economies of scale

in small firms ‘without producing the diseconomies caused by large size’ (1993: 161). Similarly,

innovation theory suggests that networks (particularly those comprised of many weak ties;

Granovetter, 1973) are important in diffusing innovations and, therefore, SMEs whose owners areheavily involved in networking should outperform SMEs whose owners make limited (or no) use

of networks (Havnes and Senneseth, 2001). In short, both social capital theory and innovation

theory suggest that networking can potentially lower a firm’s risk of ‘failure’ (increase a firm’s

chances of ‘success’).

In addition, it has been suggested there might be significant differences between males and

females in terms of their  network use (Hanson and Blake, 2009). For example, Cromie and Birley

(1992) argue that networks are the product of personal drive and historical experiences, and the

social structure and domestic duties of many women might result in female entrepreneurs having

(and therefore using) fewer networks than their male counterparts. Aldrich (1989) noted that these

differences in network use could have a significant impact on the rate at which women (comparedto men) start new ventures and the performance of those ventures.

However, although there has been considerable conjecture about the possible networking differ-

ences between men and women, few empirical studies exist that examine the gender differences in

networking and, more importantly, the association between networking and firm performance

(Hanson and Blake, 2009). Following Ibarra’s (1992) call for further empirical evidence to clarify

how men’s and women’s networks differ, the extent of these differences and the potential conse-

quences of any such differences, this study sought to identify any systematic networking differ-

ences between male and female SME owners and to determine whether there is an association

 between networking and firm performance (for both male and female-controlled SMEs).

It is hoped that the findings presented and discussed within this paper will assist SME advisersand policymakers to understand better the potential differences in the use of networks by male and

female SME owners, and the association between networking and firm performance. This article

 begins with a summary of the literature that was central to the development of the models exam-

ined in this study. Next, there is a discussion of the models proposed to test for gender differences

in networking, the relationship between networking and firm performance, and a description of

the methodology adopted. The results of the analysis and discussion of those results are given, and

the article concludes with the limitations of the study and suggestions for future research.

Literature review

Coleman (1988) notes that while information is important to decision-making, it is costly to obtain,

hence networks provide a means by which important information can be potentially acquired in a

cost-effective manner. Similarly, Hanson and Blake argue that networking can help SME owners

‘reduce transaction costs’ and ‘provide access to resources’ (2009: 144). Therefore, networking can

enhance an SME owner’s social capital by providing access to information and ‘[j]ust as physical

capital and human capital facilitate productive activity, social capital does as well’ (Coleman, 1988:

S101). Seibert et al. (2001) provide a useful summary and discussion of the three conceptualizations

of social capital found in the literature. First, there is the weak tie theory proposed by Granovetter  

(1973). Here, the focus is on the strength of social ties and it is argued that networks comprising

strong ties (such as family and friends) are more likely to be a source of redundant information thanwould be the case where networks comprise weak ties (such as acquaintances). Second, there is

Burt’s (1992) notion of structural holes. A structural hole is deemed to exist where two individuals

are not connected in any way. Here the focus is not on the direct ties between SME owners and

at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 4/24

538 International Small Business Journal 30(5)

individual members of their network, but rather on the relationships between the various members

in an SME owner’s network. An SME owner whose network comprises many structural holes (that

is, few of the other members of the network are connected) is likely to have ‘more unique and timely

access to information’ (Seibert et al., 2001: 221). Third, there is social resource theory (Lin et al., 

1981), which focuses on the nature of the resources embedded within a network rather than on thestrength of ties or the existence of structural holes. While weak tie theory and structural hole theory

examine the links between the members of a network, social resource theory is concerned with the

nature of information (i.e. the social resources) held by individual members of the network.

A variety of terms can be found in the network literature to describe the important properties of

 personal networks. For example, Munch et al. (1997) refer to network size, contact volume and

composition; Moore (1990) refers to network range, volume of contacts and diversity of alters;

Zhao and Aram (1995) refer to network range and intensity; and Ibarra (1992) refers to network

composition, homophily, tie strength, range, density and the distinction between formal and infor-

mal networks. The focus of this study is on the number of networks that SME owners use to access

advice, and the frequency (volume) of their use. In addition, network composition will be exam-ined using Ibarra’s (1992) classification of networks as either formal or informal, with formal

networks likely to comprise more weak ties and structural holes (and therefore to be more benefi-

cial) than informal networks. Littunen (2000) suggests that formal networks include the likes of

accountants, banks, lawyers and trade associations, while informal networks comprise groups such

as business contacts, family and personal relationships.

Turning to the possible differences between the networks of male and female SME owners,

Cromie and Birley (1992) argue that because the majority of women enter self-employment from

a domestic and/or non-managerial background, it is likely that their personal network contacts will

not be as extensive or well-developed as their male counterparts. As Munch et al. (1997) note,

housework and childrearing are extremely lonely forms of work, and this isolation results in manywomen having limited network contacts compared to men. Even where women move directly from

 paid employment into self-employment, it is likely that they will have fewer network contacts

 because females typically occupy lower level positions within the organizations that they leave,

compared to the typical male (Cromie and Birley, 1992).

Aldrich (1989) argues that past research indicates that female entrepreneurs might not only

have fewer networks than their male counterparts, but are likely to be embedded in different types

of networks. Similarly, Munch et al. (1997) suggest that as a result of their childrearing respon-

sibilities, women will typically rearrange their network composition to favour kin (family and

friends) over other forms of network contacts. Consistent with this argument, Orhan (2001) notes

that the first source of advice for male entrepreneurs is usually professional experts (such asaccountants and lawyers), and second is their spouse; whereas the first source of advice for female

entrepreneurs is their spouse, second, their friends, and third, professional experts. Similarly,

Moore (1990) found that women were more likely to include family members in their networks

than men. This suggests that male SME owners are more likely to access formal networks, while

female SME owners are more likely to access informal networks (particularly family and friends).

In summary, it would seem past research suggests that, compared to men, women are likely to

have fewer networks, less time available for networking and networks that favour family and

friends (strong ties with few structural holes) over professional advisers (weak ties with many

structural holes). This gives rise to the first four hypotheses examined in this study.

H1: Female SME owners will have a smaller number of networks than male SME owners.

H2: Female SME owners will make less frequent use of networks than male SME owners.

 at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 5/24

Watson 539

H3: Female SME owners will make less frequent use of formal networks than male SME owners.

H4: Female SME owners will make more frequent use of informal networks (particularly family and

friends) than male SME owners.

As discussed earlier, social capital theory predicts a positive association between networking and

firm performance, with formal networks (weak ties with more structural holes) likely to have a

greater impact than informal networks (strong ties with fewer structural holes). Support for this

 proposition can be found in Renzulli et al. (2000: 538), who report that ‘network heterogeneity

significantly increased the odds of starting a business’ (see also Burt, 2000: 357 for a detailed

review of the evidence supporting ‘the argument that social capital is a function of brokerage

across structural holes’). This gives rise to the last hypothesis examined in this study.

H5: For both female and male-owned SMEs, firm performance is positively associated with networking –

with formal networks having a greater impact than informal networks.

Method

 Model development

Much of the previous work on networking and firm performance has ignored important intervening

variables. For example, Hoang and Antoncic (2003) indicate that an owner’s age, experience and

level of education are all related to network use. Similarly, the liability of newness (adolescence)

literature (Bruderl and Schussler, 1990; Stuart and Sorenson, 2003) suggests that networking islikely to be particularly critical for young (adolescent) firms whose owners have limited experience

in, and knowledge of, the industry in which they are operating. As Brüderl and Preisendörfer (1998: 

216) note, entrepreneurs endowed ‘with lower stocks of human capital’ are likely to make more

effort to develop their social resources. Cooper et al. (1989) found that owners or managers of larger

ventures were more likely to access formal networks (such as professional advisers), while the own-

ers or managers of smaller ventures were more likely to access informal sources (such as family and

friends). In terms of firm performance, Lussier and Pfeifer (2001) reported that owner-managers of

successful firms were more educated than those of unsuccessful firms, Robinson and Sexton (1994) 

noted that education and experience were positively related to self-employment success, and

Becchetti and Trovato (2002) found that firm growth was significantly affected by the industry, sizeand age of the firm. Therefore, in order to assess properly the relationship between networking and

firm performance, it is important to control for such potentially confounding variables. For example

if, compared to older firms, younger firms are more likely to fail (Jovanovic, 1982) and their owners

are also more likely to have fewer networks, including the age of the firm in the analysis allows the

effects of networking on firm performance to be assessed separately from the effects of firm age.

Therefore, in order to test for gender differences in networking (number and frequency), the

following networking model is proposed:

 Networking = f(gender, education, experience, industry, age, size)

The dependent variable in this model will take a variety of forms, including the number of networks used

to access advice, frequency of network use, frequency of formal network use, and frequency of informal

network use. Given that the independent variables in this model include a mix of ordinal, nominal and

at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 6/24

540 International Small Business Journal 30(5)

numeric data, categorical regression will be used to test the model. How each of the variables is measured

will be discussed in the following section, which describes the data available for this study.

For a variety of reasons (such as access to information, new innovations and finance) social

capital theory implies that networking should have a significant influence on the success of SMEs

(Chell and Baines, 2000; Greene et al., 2001; Kristiansen et al., 2005; Madill et al., 2004; Renzulli et al., 2000). The belief that networking is positively associated with firm performance has been

supported by various empirical studies. For example, Florin et al. found that using social networks

could provide a venture with a ‘durable source of competitive advantage’ (2003: 374), and Brüderl

and Preisendörfer (1998) found that network support increased the probability of survival and

growth for new businesses. In terms of professional advisory services, Davidsson and Honig

(2003) found that being a member of a business network (such as Chambers of Commerce, Rotary

Clubs or Lions) had a significant positive effect on firm performance. Duchesneau and Gartner

(1990) found that successful firms were more likely to have used professional advice, and Larsson 

et al. (2003) found that a lack of contact with outside expert advisers was an obstacle to the expan-

sion of small businesses. Kent (1994) found that the financial performance of a group of small pharmacy businesses was positively related to using external management advisory services.

Finally, Zhao and Aram (1995) found that managers of three high-growth firms reported a greater

range and intensity of business networking than managers of three low-growth firms.

Therefore, in order to test the potential association between networking and firm performance,

the following firm performance model is proposed:

Firm performance = f(gender, education, experience, industry, age, size, networking)

Given that the two measures of firm performance used in this study are dichotomous (as discussed

in the following section), logistic regression is used to test this second model. Firm performancewill be examined separately for the male and female-controlled SMEs to specifically examine

gender differences in the possible association between networking and firm performance.

It should be noted that, consistent with most prior empirical studies on networking, this study

focuses on the personal networks of the SME owner rather than the organizational networks of the

 business (Brüderl and Preisendörfer, 1998). As argued by Bratkovic et al., the personal networks of

SME owners and their organization’s networks ‘are almost synonymous since network ties exist at

the interpersonal level’ (2009: 487).

Data

Low and MacMillan (1988) note that, despite significant resource implications, it is important for

SME researchers to have access to large-scale longitudinal data in order to improve confidence in

research outcomes and as a basis for theoretical model building. This view was echoed by Reese

and Aldrich (1995), specifically in relation to the association between networking and firm per-

formance. Therefore, a major strength of this study is its use of a large longitudinal database. The

construction of this database was funded by the Australian federal government and was designed

to provide information on the growth and performance of Australian employing businesses. The

Australian Bureau of Statistics’ (ABS) Business Register was used as the population frame for

the surveys. All employing businesses in the Australian economy were included in the scope of

the survey, except for businesses in the nature of:

• government enterprises;

• libraries;

at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 7/24

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 8/24

542 International Small Business Journal 30(5)

There are three reasons for the relatively low number of female-controlled SMEs in the dataset. First,

only 18 percent of Australian businesses are run by an individual female or predominantly by females

(Australian Bureau of Statistics, 2001). Second, non-employing businesses were not included in the

database, and this further reduced the proportion of female-controlled firms in the study because a rela-

tively greater percentage of predominantly female-run businesses do not employ staff (i.e. 70% of predominantly female-run businesses compared to only 59% of predominantly male-run businesses do

not employ staff). Third, there was a sampling bias in favour of large businesses and manufacturing con-

cerns, and these are sectors where females tend to be relatively underrepresented (Marlow et al. 2009).

 Measurement of variables

 Networking variables. Each of the 10 potential networks (seven formal and three informal) was

treated as a categorical variable: if a particular network had not been used (to access advice) during

the past year it was coded ‘0’; where a network had been used between one and three times during

the past year, it was coded ‘1’; and where a network had been used more than three times, it wascoded ‘2’. Therefore, in terms of the number of network used, an SME owner could score from 0

(if no networks had been used during the past year) to 10 (if all 10 networks had been used). In

terms of the frequency of network use, an SME owner could score from 0 (if no networks had been

used during the past year) to 20 (if all 10 networks had been used more than three times). Similarly,

for formal (informal) networks, the maximum score for the number and frequency of network use

during the past year is 7 (3) and 14 (6) respectively. Given that frequency of network use is a com-

 bination of the number of networks used and the frequency of use for each individual network,

most of the analysis and tables that follow will focus on frequency of network use.

 Performance variables. Brüderl and Preisendörfer (1998) argue that survival is the minimum

criterion for success. However, policymakers are also interested in firm growth, as growing firmsare likely to contribute the most to a country’s economy and job creation. Delmar et al. note there

‘seems to be an emerging consensus that if only one indicator is to be chosen as a measure of firm

growth, the most preferred measure should be sales’ (2001: 194). Therefore, in this study firm

 performance is measured in terms of both firm survival and sales growth (measured as the percent-

age increase in total income over the three-year period of this study). Surviving firms are coded ‘1’,

while discontinued firms are coded ‘0’. In terms of growth, this study focuses on those firms in the

top 25 percent (upper quartile, coded ‘1’) for sales growth compared to those in the bottom 25

 percent (lower quartile, coded ‘0’). Although it is unusual to discard data, if there is a relationship

 between networking and firm performance it will most likely be evident at the extreme ends of the

 performance spectrum. That being the case, focusing on those firms in the tails of the performancedistribution (rather than including all firms) is more likely to find such a relationship.3

Control variables. As noted earlier, prior research indicates that potentially significant associa-

tions exist between various owner or business characteristics (such as education, experience,

industry, age of business and size of business) and both networking and firm performance, with

these characteristics also likely to vary by gender. Therefore, as far as possible, these variables

need to be controlled in order to understand and assess properly gender differences in networking

and the relationship between networking and firm performance.

In this study, education, industry and age of business were treated as categorical variables with

four categories for education (school, trade, tertiary non-business degree and tertiary business

degree), 11 for industry (mining, manufacturing, construction, wholesale trade, retail trade, accom-modation, cafes and restaurants, transport and storage, finance and insurance, property and busi-

ness services, cultural and recreational services, and personal and other services) and five for age

(less than 2 years, 2 to less than 5 years, 5 to less than 10 years, 10 to less than 20 years, and 20 or

at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 9/24

Watson 543

more years old). The owner’s years of experience and the size of the business (measured in terms

of the number of employees) were treated as continuous variables.

Results

Before examining the results of the networking and performance models developed earlier, some

key descriptive and demographic details are presented in Tables 1, 2, 3 and 4. Table 1 shows thenumber of networks used during the past year (to obtain advice) by the male and female SME own-

ers. The results show that most of the SME owners (88% of males and 84% of females) used at least

one network during the past year, with approximately 50% of all SME owners (52% of males and

46% of females) using five or more networks. This finding is consistent with Cooper et al. (1989) 

and Robson and Bennett (2000), who reported that entrepreneurs sought information from a variety

of sources. However, the results also indicate no significant differences between the male and

female owners in terms of the number of networks used to access advice. This result is at odds with

H1 (and most of the literature on gender and networking), but supports Cromie and Birley’s (1992)

finding that the personal networks of women are just as diverse as those of men. A separate analysis

of the subset of SMEs which had used three or fewer networks also failed to find any gender differ-ence, and the same applied to the subset of SMEs which had used seven or more networks.

Table 2 provides a summary of the frequency with which the male and female SME owners used

a variety of individual formal and informal networks. Contrary to H2, there was no difference in

the overall frequency with which male and female owners used all networks (formal and informal).

This result, although inconsistent with the majority of the literature, again confirms Cromie and

Birley’s (1992) finding that women are just as active in their networking relationships as men.

Similarly, Diaz Garcia and Carter (2009) found that male and female business owners devoted a

similar amount of time to networking. As noted by Cromie and Birley (1992), once in business,

women might well recognize the need to have appropriate network contacts and ‘proceed to

develop them vigorously’. Alternatively, compared to men, women might have less entrepreneurialself-efficacy (Wilson et al., 2007) and might feel a stronger need to develop a range of network ties

from which they can access advice. As noted by Wilson et al.:

Table 1.  Number of Networks used by SME Owners

Number ofNetworks

All SME ownersN = 3100

MaleN = 2919

FemaleN = 181

% Cum % % Cum % % Cum %

10 3% 3% 3% 3% 2% 2%9 5% 8% 5% 8% 4% 6%8 8% 15% 8% 16% 5% 11%7 12% 27% 12% 28% 8% 19%6 12% 39% 11% 39% 14% 34%5 13% 52% 13% 52% 12% 46%4 12% 64% 12% 64% 12% 58%3 11% 75% 11% 75% 9% 67%2 8% 82% 7% 82% 11% 77%1 6% 88% 6% 88% 7% 84%0 12% 100% 12% 100% 16% 100%

Note: Chi-square test comparing males and females not significant at 5%.

 at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 10/24

544 International Small Business Journal 30(5)

given the complex tasks involved for an individual to locate an opportunity, assemble the resources, set up

a business, and build it into a successful entity, self-efficacy or the belief in one’s ability to succeed as an

entrepreneur would seem to be especially important. (2007: 390)

Although there was no difference between males and females in terms of the overall frequency oftheir network use, consistent with H3, the male SME owners made significantly more use of formal

networks, particularly with banks, business consultants, industry associations and solicitors.

However, contrary to H4, the female SME owners did not make significantly more use of informal

networks, although they did make significantly more use of family and friends. These findings are

consistent with Robson et al. (2008), who reported that male Scottish business owners were

significantly more likely to seek advice from consultants and Chambers of Commerce, while

female Scottish business owners were significantly more likely to turn to friends and relatives.

Shaw et al. (2008) also reported that female owners were significantly more likely (than male

owners) to identify a family member as their prime network contact.

Interestingly, Table 2 shows the network most often used (for accessing advice) by both male andfemale SME owners (with no significant difference between the two groups) is external accountants 

(a formal network): 47% of males and 44% of females sought advice from an external accountant

more than three times a year. This finding is consistent with Robson and Bennett (2000) who reported

that, from the private sector, accountants are the most widely used source of advice. The result is also

consistent with Robson et al. (2008), who found that accountants were the most widely used source of

advice for both male and female Scottish business owners (with no significant difference by gender).

Similarly, both male and female SME owners frequently used others in the industry, with 27%

of males and females using this informal network more than three times a year. In summary, unlike

Birley (1985), who found that entrepreneurs relied heavily on informal networks but seldom tapped

Table 2.  Frequency of Formal and Informal Network use for Male and Female SME Owners

Networks Frequency of use (per year)

Nil 1–3 times   >3 times

Male Female Male Female Male Female

Formal 

  External accountant 19% 20% 34% 36% 47% 44%  Bank 36% 44% 36% 39% 28% 18% **  Solicitor 41% 48% 35% 40% 24% 12% **  Industry association 57% 75% 23% 15% 20% 10% **  Business consultant 71% 82% 19% 13% 10% 5% **  Tax office 58% 65% 32% 30% 10% 6%  SBDC 84% 87% 13% 12% 3% 1%  Average formal networks 52% 60% 27% 26% 20% 13% *

Informal 

  Others in the industry 44% 48% 30% 26% 27% 27%  Family and friends 63% 52% 20% 23% 17% 25% **  Local businesses 73% 75% 17% 15% 10% 9%  Average informal networks 60% 58% 22% 21% 18% 20%

  Average all networks 55% 60% 26% 25% 20% 16%

*, ** Chi-square test significantly different for males and females at 5% and 1% respectively.

 at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 11/24

Watson 545

into formal networks, the results presented in Table 2 suggest that Australian SME owners (male

and female) make extensive use of both formal and informal networks.

Table 3 provides key demographic details for the male and female owners (education and expe-

rience) and their firms (industry, age and size). The results indicate significant gender differences

for all variables. Table 4 provides the same demographic details (plus gender) for surviving andnon-surviving firms and for high and low-growth firms. With the exception of the owner’s level of

education, all variables are again significantly associated with at least one performance measure

(survival or growth). For example, the owners of firms that discontinued prior to the final year of

the study typically had fewer years of experience than the owners of firms that survived. Similarly,

younger firms were less likely to survive and more likely to be in the high-growth group. The find-

ing that younger firms are both less likely to survive and more likely to grow is consistent with

Jovanovic’s argument that ‘[f]irms learn about their efficiency as they operate in the industry. The

efficient grow and survive; the inefficient decline and fail’ (1982: 649). The result is also consistent

with Evans (1987) and Glancey (1998), who found that younger firms grow faster than older firms.

The findings reported in Table 4 highlight the importance of controlling for potentially con-founding variables, particularly if – as expected – a significant relationship also exists between

Table 3.  Descriptive Statistics: Gender

  Male N = 2919 Female N = 181

Education of owner  **  School 35% 49%  Trade 24% 14%  Non-business degree 20% 27%  Business degree 21% 10%

Experience of owner  **  Number of years (median) 13 8

Industry  **  Mining 1% 1%  Manufacturing 40% 24%  Construction 7% 1%  Wholesale trade 15% 10%  Retail trade 10% 18%  Accommodation, cafes and restaurants 2% 6%  Transport and storage 4% 6%  Finance and insurance 4% 2%  Property and business services 14% 19%  Cultural and recreational services 2% 4%  Personal and other services 1% 10%

 Age of business **  Less than 2 years old 13% 22%  2 years to less than 5 15% 19%  5 years to less than 10 24% 28%  10 years to less than 20 27% 22%  20 or more years old 22% 10%

Size of business **  Number of employees (median) 10 4

*, ** Significantly different at 5% and 1%, respectively, using the Chi-square test for categorical variables and the Mann-Whitney U test for continuous variables.

 at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 12/24

546 International Small Business Journal 30(5)

these variables and an SME owner’s level of networking. The importance of this issue is high-

lighted in Table 5, which provides the results of the networking model proposed earlier. Table 5

reports the results where the dependent variable is the overall number of networks used to access

advice, overall frequency of network use, frequency of formal network use and frequency of infor-

mal network use. Consistent with the findings reported in Tables 1 and 2, there is no significant

gender difference in terms of number of networks, frequency of use and frequency of informal

network use. With respect to the frequency of formal network use, the significant gender difference

reported in Table 2 disappears when other owner and firm characteristics are controlled.Apart from the last dependent variable (frequency of informal network use, where the adjusted

 R2 is extremely low), the results reported in Table 5 are very consistent, with education, industry,

age and size all being significantly associated with networking. The results suggest a positive

Table 4.  Descriptive Statistics: Survival and Growth

Variables Survived Growth

Yes

N = 2653

No

N = 447

High

N = 663

Low

N = 663

Education of owner  School 85% 15% 51% 49%

  Trade 88% 12% 51% 49%

  Non-business degree 85% 15% 48% 52%

  Business degree 85% 15% 49% 51%

Experience of owner  *  No. of years (median) 13 10 12 13

Industry  ** **  Mining 80% 20% 50% 50%

  Manufacturing86% 14% 46% 54%

  Construction 87% 13% 66% 34%

  Wholesale trade 89% 11% 52% 48%

  Retail trade 85% 15% 49% 51%

  Accommodation, cafes and restaurants 77% 23% 36% 64%

  Transport and storage 88% 12% 40% 60%

  Finance and insurance 78% 22% 52% 48%

  Property and bus services 86% 14% 52% 48%

  Cultural and recreational services 79% 21% 52% 48%

  Personal and other services 84% 16% 62% 38%

 Age of business * *

  Less than 2 years old41% 59% 67% 33%

  2 years to less than 5 90% 10% 51% 49%

  5 years to less than 10 92% 8% 51% 49%

  10 years to less than 20 94% 6% 49% 51%

  20 or more years old 93% 7% 43% 57%

Size of business *  No. of employees (median) 13 7 11 10

Gender of owner  **  Male 86% 14% 50% 50%

  Female 80% 20% 48% 52%

*, ** Significantly different at 5% and 1%, respectively, using the Chi-Square test for categorical variables and the Mann-

Whitney U test for continuous variables.

 at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 13/24

Watson 547

association between the level of education and networking, which is consistent with Shaw et al. 

(2008), who noted that individuals with high levels of human capital (such as education) are also

likely to possess high levels of social capital (such as network contacts). Similarly, owners of older

and larger firms appear to be more involved in networking: a finding consistent with Robson et al.,

who report that size of the business ‘is the main variable that explains the use of formal external

advice’ (2008: 305). With respect to industry, it appears (from further examination of the data, not

reported) that the manufacturing and wholesale trade sectors are associated with higher levels of

networking, while networking is less prevalent in the service sectors. Interestingly, there appearsto be no relationship between experience and networking.

The results for modelling the frequency of network use with each of the individual formal and

informal networks are not presented; however, two notable findings from the individual network

Table 5.  Modelling Network Use: Number and Frequency

Model Standardized Coefficients

B SE d.f. F Sig.

Number of networks used (H1)

  Gender   -0.01 0.02 1 0.51 0.47  Education 0.06 0.02 3 10.04   0.00

  Experience   -0.03 0.02 1 2.03 0.15  Industry   -0.09 0.02 10 20.51   0.00

  Age 0.05 0.02 4 5.99   0.00

  Size 0.28 0.02 1 196.28   0.00

  Adj R2 0.10

Frequency of network use (H2)

  Gender   -0.01 0.02 1 0.28 0.60

  Education 0.04 0.02 3 5.31   0.01  Experience   -0.03 0.02 1 1.85 0.17  Industry   -0.06 0.02 10 8.45   0.00

  Age 0.07 0.02 4 11.06   0.00

  Size 0.33 0.02 1 289.13   0.00

  Adj R2  0.14

Frequency of formal network use (H3)

  Gender   -0.03 0.02 1 1.89 0.17  Education 0.05 0.02 3 7.24   0.01

  Experience   -0.01 0.02 1 0.19 0.66  Industry   -0.08 0.02 10 18.56   0.00

  Age 0.08 0.02 4 15.95   0.00  Size 0.39 0.02 1 419.10   0.00

  Adj R2 0.19

Frequency of informal network use (H4)

  Gender 0.02 0.02 1 0.72 0.40  Education   -0.01 0.02 3 0.22 0.81  Experience   -0.04 0.03 1 2.01 0.16  Industry   -0.09 0.02 10 13.34   0.00

  Age 0.04 0.03 4 2.59   0.08

  Size 0.07 0.02 1 7.88   0.01

  Adj R2 0.01

at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 14/24

548 International Small Business Journal 30(5)

analysis are worth noting. First, although not associated with networking at the aggregate level,

experience was found to be negatively associated with frequency of network use for some individ-

ual formal and informal networks (business consultants, tax office, SBDC, others in the industry

and local businesses). It seems that as SME owners gain more experience they feel less inclined (i.e.

have less need) to access advice from such groups. Second, and contrary to the findings reported inTable 2, the results of a separate analysis of the use of family and friends as a source of advice found

no gender difference, but instead it appears that owners of smaller businesses (where women are

typically overrepresented) make greater use of this source of advice. This again highlights the

importance of controlling for potentially confounding variables when looking at gender differences.

Interestingly, Robson et al. (2008) also reported that while women appeared more likely than men

to use family and friends as a source of advice (based on a bivariate analysis), this difference disap-

 peared when owner and firm characteristics were included in a multivariate analysis.

Table 6 presents the results of modelling the relationship between network frequency and firm

survival and growth, incorporating gender and the various control variables from Table 4.

Table 6.  Modelling Firm Survival and Growth against Frequency of Network use

Variables in the final models Survival Growth

Wald Sig. Exp(B) Wald Sig. Exp(B)

Gender  0.00 0.97 1.01 0.11 0.74 1.09Education 0.49 0.92 0.80 0.85  School 0.03 0.87 0.97 0.29 0.59 1.09  Trade 0.19 0.67 1.09 0.45 0.50 1.13

  Non-business degree 0.02 0.90 0.98 0.00 0.98 1.00Experience 0.10 0.76 1.00 0.15 0.70 1.00Industry  14.67 0.14 19.42   0.04

  Mining 0.53 0.47 1.79 0.62 0.43 0.54  Manufacturing 0.38 0.54 0.76 2.23 0.14 0.50  Construction 0.01 0.92 1.05 0.05 0.82 1.12  Wholesale trade 0.26 0.61 1.26 0.84 0.36 0.64  Retail trade 0.01 0.94 1.04 1.80 0.18 0.52  Accommodation, cafes and restaurants 0.44 0.51 0.70 3.37   0.07 0.32  Transport and storage 0.03 0.87 1.09 2.72 0.10 0.41  Finance and insurance 1.81 0.18 0.51 0.72 0.40 0.65

  Property and business services 0.00 0.98 1.01 0.80 0.37 0.65  Cultural and recreational services 0.16 0.69 0.79 0.41 0.52 0.67

 Age 483.34   0.00 16.05   0.00

  Less than 2 years old 219.28   0.00 0.05 15.81   0.00 2.79  2 years to less than 5 2.80   0.09 0.67 3.29   0.07 1.43  5 years to less than 10 0.27 0.60 0.89 4.02   0.05 1.43  10 years to less than 20 0.91 0.34 1.24 2.25 0.13 1.29

Size 0.88 0.35 1.00 0.00 0.97 1.00Frequency of network use 100.85   0.00 1.18 5.96   0.02 1.03Constant 12.36   0.00 6.14 0.09 0.76 0.85  Percentage predicted correctly

  Survived/discontinued/overall 42.7 96 88.4  Low growth/high growth/overall 63.2 48.3 55.7

Nagelkerke R2 0.36 0.04

at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 15/24

Watson 549

Consistent with H5, the results in Table 6 indicate a significant positive relationship betweenfrequency of network use and firm survival (and a negative relationship between age of business

and firm survival). Similarly, the results in Table 6 indicate a significant positive relationship

 between frequency of network use and firm growth (with younger businesses also more likely to

achieve high growth), although the explanatory power of this model is low. Note that, consistent

with previous studies which have incorporated appropriate controls (see for example, Watson, 

2003), there is no relationship between gender and firm performance. In addition, note that when

firms were classified as high or low growth based on whether their growth rate was above or

 below the median result (rather than being based on the upper and lower quartiles), the findings

were qualitatively the same as those reported in Table 6; however, the explanatory power of the

model was substantially reduced.Finally, Tables 7 and 8 present the results of modelling (separately for male and female-controlled

SMEs) the relationship between an owner’s use of specific formal and informal networks (together

Table 7.  Modelling Firm Survival and Frequency of Individual Network use for Male and Female-controlledSMEsa

Variables in the final models Male-controlled SMEs Female-controlled SMEs

Wald Sig. Exp(B) Wald Sig. Exp(B)

 Age 434.74   0.00 37.84 0.00  Less than 2 years old 212.94   0.00 0.05 14.55   0.00 0.01  2 years to less than 5 3.10   0.08 0.66 0.15 0.70 0.59  5 years to less than 10 0.07 0.80 0.95 0.48 0.49 0.44  10 years to less than 20 0.69 0.41 1.21 0.33 0.56 2.37Formal networks

External accountant 77.07   0.00 10.18 0.01  Never 68.23   0.00 0.24 9.40   0.00 0.09  1–3 times 2.77 0.10 0.76 0.78 0.38 0.53

Industry association 13.27   0.00  Never 10.86   0.00 0.50  1–3 times 1.49 0.22 0.74Informal networksOthers in the industry  9.48   0.01

  Never 0.06 0.81 0.96  1–3 times 5.42   0.02 1.58

Family and friends 5.52 0.06  Never 0.47 0.49 0.60  1–3 times 2.91   0.09 4.87Constant 201.84   0.00 32.25 11.24   0.00 77.25

Percentage predicted correctlySurvived/discontinued/overall 96.6 39.4 88.5 94.5 66.7 89.0Chi-square significance 0.00 0.00-2 Log likelihood 1716 91Nagelkerke R2   0.36 0.62Cox and Snell R2 0.20 0.39

a Note that the variables reported in this table are those that were significant, and therefore ‘in the equation’ as reportedby SPSS using the forward stepwise (conditional) logistic regression method. Variables that were not significant, andtherefore ‘not in the equation’, are not reported.

at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 16/24

550 International Small Business Journal 30(5)

with the control variables discussed previously), and both firm survival and growth, respectively.

Given the relatively large number of control variables and networks that could be used to access

advice, the forward stepwise (conditional) logistic regression method was used, adopting the SPSS

default cut-off of 5 percent for variables entering the model and 10 percent for removal. To check

the robustness of the results, the stepwise logistic regressions were run backwards, with no signifi-cant differences found. Note that when using stepwise logistic regression, SPSS highlights those

variables that are significant and ‘in the equation’. Given space limitations, those variables that are

not significant and, therefore, ‘not in the equation’ are excluded from the tables and discussion.

Table 7 shows that the only network significantly related to the survival of both male and

female-controlled SMEs is external accountants (a formal network). Firms which had never

accessed advice from an external accountant during the past year were significantly less likely to

survive compared to firms that accessed advice from this source more than three times. Interestingly,

there was no advantage to accessing an external accountant more than three times a year compared

to accessing this source one to three times a year. This finding suggests that there might be some

optimal level of networking with external accountants beyond which no additional benefit is gained(however, there is no evidence that more frequent contact does any harm). The only other formal

network that showed up in the model was industry associations, although only for male-controlled

SMEs. As was the case with external accountants, it seems that provided male SME owners access

industry associations for advice between one and three times a year, there is no additional benefit

to accessing this network more frequently.

The results with respect to the use of informal networks were also quite interesting, with the

males apparently benefiting from networking with others in the industry and the females from fam-

ily and friends. However, in this case the results strongly suggest that excessive networking might

 be counterproductive. For male- (female-)controlled SMEs it appears that accessing advice from

others in the industry (family and friends) between one and three times a year is significantly morelikely to be associated with firm survival than accessing advice from such networks more fre-

quently (or not at all). This finding suggests that the association between firm survival and access-

ing informal networks for advice might resemble an inverted U-shaped function (Watson, 2007)

for both male and female-controlled SMEs.

In summary, the final model for predicting survival for male-controlled SMEs incorporates,

along with the age of the business, both formal (external accountants and industry associations)

and informal (others in the industry) networks. Accessing other networks (Australian tax office,

 banks, business consultants, family and friends, local businesses, the SBDC and solicitors) does

not add significantly to the explanatory power of the model. Similarly, the final model for predict-

ing survival for female-controlled SMEs incorporates, along with the age of the business, bothformal (external accountants) and informal (family and friends) networks.

Consistent with Granovetter’s (1973) weak tie theory and Burt’s (1992) notion of structural

holes (and H5), for both the male and female-controlled SMEs there was a stronger relationship

 between survival and formal networks than between survival and informal networks; although

clearly both types of networks were important. This result is contrary to Brüderl and Preisendörfer’s

(1998) finding that strong ties are more important than weak ties in explaining firm survival.

However, the results support the suggestion by Uzzi (1996) that networks consisting of a balance

of both weak and strong ties ultimately might be more valuable than networks focused on only

weak (or only strong) ties.

Table 8 provides the results of undertaking a similar analysis using sales growth (rather thanfirm survival) as the dependent variable. In terms of formal networks, male-controlled high-growth

SMEs appeared to gain some advantage from accessing advice from both external accountants and

at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 17/24

Watson 551

industry associations. However, the results again indicate with respect to external accountants that

there is an optimum level of networking beyond which no further benefit is gained and, in the case

of industry associations, excessive networking (more than three times a year) might be counterpro-

ductive. That is, there is no difference (in terms of firm growth) in accessing advice from an exter-

nal accountant between one and three times a year and accessing this network more often. However  , accessing advice from an industry association between one and three times a year appears to be

significantly more beneficial than accessing this network more often (or not at all). This suggests

that for high-growth male-controlled SMEs, obtaining advice from both external accountants and

industry associations up to three times a year might be an optimal strategy; any further interaction

with these formal networks is likely to be counterproductive (particularly with respect to network-

ing with industry associations).

Table 8.  Modelling firm Growth and Frequency of Individual Network use for Male and Female-controlled

SMEsa

Variables in the final models Male-controlled SMEs Female-controlled SMEs

Wald Sig. Exp(B) Wald Sig. Exp(B)

 Age 17.06   0.00  Less than 2 years old 15.71   0.00 2.78

  2 years to less than 5 2.92   0.09 1.39  5 years to less than 10 5.03   0.03 1.49  10 years to less than 20 1.49 0.22 1.23

Industry  21.65   0.02  

Mining 0.93 0.33 0.44  Manufacturing 2.47 0.12 0.42  Construction 0.00 0.97 0.98  Wholesale trade 1.55 0.21 0.49  Retail trade 2.62 0.11 0.39  Accommodation, cafes and restaurants 4.03   0.05 0.22  Transport and storage 3.26   0.07 0.32  Finance and insurance 1.16 0.28 0.52  Property and business services 1.22 0.27 0.53  Cultural and recreational services 0.60 0.44 0.57

External accountant 6.71   0.04   8.10   0.02  

Never 6.36   0.01 0.64 3.02   0.08 0.25  1–3 times 0.08 0.78 0.96 7.25   0.01 0.24

Industry Association 6.46   0.04  Never 0.09 0.76 0.95

  1–3 times 3.07   0.08 1.37Constant 0.69 0.41 1.62 3.52   0.06 2.00Percentage predicted correctlyHigh/low/overall 53.2 63.0 58.1 62.9 71.1 67.1Chi-square significance 0.00 0.01-2 Log likelihood 1683 92Nagelkerke R2   0.06 0.15

a Note that the variables reported in this table are those that were significant and, therefore, ‘in the equation’ asreported by SPSS using the forward stepwise (conditional) logistic regression method. Variables that were not significantand, therefore, ‘not in the equation’ are not reported.

 at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 18/24

552 International Small Business Journal 30(5)

For the female-controlled SMEs, the results presented in Table 8 indicate that using an external

accountant for advice more than three times a year is significantly more likely to be associated with

high growth compared to never using this network, or only using this network one to three times a

year. Beyond noting that using an external accountant for advice more than three times a year

appears beneficial, it is not possible (due to data limitations) to indicate what the optimum level ofcontact with external accountants might be for high-growth female-controlled SMEs. These results

suggest that while male SME owners make effective use of both external accountants and industry

associations, female SME owners tend to rely more heavily on external accountants (possibly

 because of problems associated with accessing industry associations which typically meet after

hours). Interestingly, no informal networks (which typically consist of stronger ties and fewer

structural holes) appear to be related to firm growth for either the male or female-controlled SMEs.

This result is consistent with Bratkovic et al.’s (2009) finding that strong ties can negatively affect

firm growth.

In summary, the final model for predicting high-growth male-controlled SMEs incorporates,

along with the age and industry of the business, two formal networks (external accountants andindustry associations) but no informal networks. The final model for predicting high-growth

female-controlled SMEs incorporates only one formal network (external accountants) and no

informal networks. This finding is consistent with Granovetter’s (1973) weak tie theory and Burt’s

(1992) notion of structural holes, because both theories suggest that SME owners are likely to

derive more benefit in terms of accessing new products and markets from formal rather than infor-

mal networks. The results are also consistent with Brüderl and Preisendörfer’s (1998) finding that

strong ties are more important to firm survival than to firm growth.

Discussion

Several interesting observations arise from the results presented in the previous section. First,

while male and female SME owners appear to use a similar number of networks, male SME own-

ers appear to make more frequent use of formal networks (in particular banks, solicitors, industry

associations and business consultants). However, once appropriate controls are introduced only

one gender difference remains: men appear to make more use of industry associations. Further,

with the exception of the relationship between industry associations and survival,  the formal net-

works used significantly more frequently by male (compared to female) SME owners (banks,

solicitors and business consultants) have no apparent association with firm performance. Therefore,

it would appear that female-controlled SMEs are not disadvantaged by their owners devoting fewer

resources to networking with these groups.Second, external accountants are the only formal network source significantly related to firm

survival and growth for both male and female-controlled SMEs. Therefore, given limited time for

networking, it would seem that SME owners would be well advised to ensure they maintain regular

contact with an external accountant; this would appear to be particularly relevant for female SME

owners. While this finding is consistent with Potts, who found that ‘successful companies rely

more heavily on accountants’ information and advice than do unsuccessful companies’ (1977: 93),

it contrasts with the results of Robson and Bennett (2000) and Cooper et al. (1994). Robson and 

Bennett (2000) found no statistically significant relationship between accessing advice from

accountants and any of their measures of firm performance. Similarly, Cooper et al. (1994) found

that the use of professional advisers had no significant effect on firm performance.Third, with respect to informal networks, there does not appear to be any significant difference

in the overall frequency with which male and female SME owners sought advice from these groups,

although female owners appear to make significantly more use of family and friends. However,

at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 19/24

Watson 553

this apparent gender difference with respect to accessing family and friends for advice disappears

when appropriate controls are introduced. Further, while SME owners appear to make frequent use

of a variety of informal networks, none of these networks appear to be related to firm growth, and

only two appear to be related to firm survival (others in the industry for male-controlled SMEs, and

family and friends for female-controlled SMEs). The finding that no informal networks wererelated to firm growth (for either the male or female-controlled SMEs) is contrary to Fischer and

Reuber’s (2003) observation, that owners of high-growth firms see the owners of other high-

growth firms as an invaluable source of relevant and useful advice. However, this finding supports

 Nelson’s (1989) argument, that owners who want to grow their firms are best advised to make more

frequent use of a limited number of networks where they can access the particular expertise (i.e.

advice) that they require. The finding also supports the argument that weak ties are more important

than strong ties for business growth and development (Granovetter, 1973).

Fourth, there were fewer networks associated with firm growth than was the case for firm sur-

vival. This, again, suggests that owners seeking rapid growth for their firms might be best advised

to access more frequent help from a smaller number of networks that have the specific expertiserequired (Nelson, 1989; Zhao and Aram, 1995). This result might also help to explain the finding

 by Bates that heavy use of social support networks typified ‘the less profitable, more failure-prone

 businesses’ (1994: 671). Therefore, it might be important for SME owners to regularly assess their

networking activities, in order to ensure that they are accessing appropriate networks without

devoting too many resources to networking relative to the benefits they receive. Through a process

of expanding and culling their networks, SME owners can identify those relationships that merit

‘continued development and future investment’ (Larson and Starr, 1993: 6).

Fifth, while there are some notable differences between the male and female-controlled SMEs

in terms of the network sources that were significant in the models developed to predict firm

 performance, these differences do not appear to impact negatively the performances of female-controlled SMEs relative to their male counterparts. Indeed, there was no significant gender

difference in the performances (survival or growth) of the male and female-controlled SMEs in

this study. This result is consistent with a social feminist theory perspective (Fischer et al., 

1993), in that although there might be differences in the networks accessed by male and female

SME owners, both groups appear equally effective in terms of the overall economic benefits that

they derive from their networking activities. Finally, for the relatively few networks that are

significantly related to firm performance, there is some evidence to suggest that excessive net-

working (more than three times a year) might be counter-productive. This was particularly true

of the association between firm survival and the use of certain informal networks (others in the

industry for male-controlled SMEs and family and friends for female-controlled SMEs).In summary, although SME owners appear to use a number of different networks, few of

these networks appear to be associated with firm performance (survival or growth). The only

networks to show up as being significantly associated with firm performance are: external

accountants (for firm survival and growth, for both male and female-controlled SMEs); industry

associations (for the survival and growth of male-controlled SMEs); others in the industry

(for the survival of male-controlled SMEs); and family and friends (for the survival of female-

controlled SMEs).

Conclusion

The key findings from this study indicate that SME owners make extensive use of both formal and

informal networks, with females making more frequent use of family and friends, and males

at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 20/24

554 International Small Business Journal 30(5)

making more frequent use of banks, solicitors, industry associations and business consultants.

However, although the types of networks used by men and women appear to differ, most differ-

ences disappear when appropriate controls are included in the analysis.

Further, despite the extensive use made by SME owners (male and female) of formal and infor-

mal networks, the majority of these networks – with the exception of external accountants, industryassociations, others in the industry and family and friends – do not appear to be associated with

firm performance (i.e. survival or growth). Zhao and Aram (1995) note that broad-ranging net-

works cost more financially, and in terms of the owner’s time and effort to develop and maintain;

Starr and MacMillan argue that individuals ‘invest their time and energy in social transactions

 based on their expectations of future profits and rewards’(1990: 80); and Uzzi suggests that an

‘organization’s network position, network structure, and distribution of embedded exchange rela-

tionships shape performance such that performance reaches a threshold as embeddedness in a

network increases’ (1996: 675). Consistent with these comments, and the notion of ‘parsimony’,

the results in this study suggest that too many resources devoted to networking might not be helpful

to SME performance. This finding provides support for Lerner et al. (1997) and Bates (1994), whofound that participation in multiple networks was negatively related to firm performance. As noted

 by Low and MacMillan: ‘Aspiring entrepreneurs are advised to evaluate and map their current

networks. Doing so is the first step toward building an effective network, an activity that is too

important to be left to chance’ (1988: 155).

In summary, the results from this study suggest that, given limited time for networking, SME

owners should ensure, at a minimum, that they maintain regular contact with an external account-

ant. This might be particularly important for female SME owners with family commitments and

limited time available for networking (particularly after hours). The results also suggest that, in

terms of firm survival, accessing advice from a mix of formal and informal networks is likely to be

 preferable to only accessing either formal or informal networks. However, this does not apply tofirm growth where only formal networks appear to have a positive impact. Finally, and contrary to

the findings of some prior research, the results suggest that female-controlled SMEs are not failing

to make appropriate use of networks.

Limitations of the study 

This study has a number of potential limitations that should be acknowledged. First, the SME own-

ers were asked to indicate, within three categories, how often they accessed advice from a variety

of sources. As this question only relates to accessing advice, it might not provide a true indication

of the total networking involvement by SME owners. Further, the question did not ask respondentsto indicate the nature of their network contact: that is, a simple phone call or a more in-depth meet-

ing. It has been argued that, due to its dynamic and fluid nature, it is difficult to fully appreciate

networking behaviour based simply on a count of the number of contacts made (Chell and Baines, 

2000). Second, another potential limitation of the study (as noted in the data section) is the rela-

tively low number of female compared to male-controlled SMEs in the sample. Third, a further

 potential limitation relates to the classification of firms as being either female or male-controlled.

Where there was more than one owner of the business, this classification was based on the major

decision-maker. If the major decision-maker was male (or female), the firm was classified as a

male (or female)-controlled firm for the purposes of this study, even though the major decision-

maker might not have been a majority owner. Fourth, this study was conducted at a time when theuse of social media networks (such as Facebook and Twitter) was limited and, therefore, this is an

area that future research could usefully explore.

at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 21/24

Watson 555

Finally, it should be noted that it is not possible to conclude causality from a study such as this; all

we can do is draw inferences based on an apparent association between networking and firm perform-

ance. For example, it might be that rapidly growing firms have a greater need to consult with external

accountants, rather than regular contact with external accountants necessarily leading to rapid growth.

This limitation is not as critical when firm survival is the dependent variable under consideration.The reader should be cautioned against interpreting the results of this study as indicating that

networking with those groups not featured in the various models has no benefit. SME owners

might receive other benefits from networking beyond the purely economic benefits that were the

focus of this study. For example, through networking owners might draw more comfort (i.e. reas-

surance) from their future plans, and might gain the reassurance needed to continue in difficult

times (Birley, 1985). In addition, networks can help SME owners integrate into the social life of a

community (Donckels and Lambrecht, 1995). Further, the benefits from some networking sources

might be firm and/or situation-specific and might not show up in a large-scale study looking at

average outcomes. For example, using management consultants might be of substantial benefit in

a few very specific cases. An analysis of a large data set might mask, or make it difficult to detect,these benefits. This is an area that future research could investigate further.

From a government policy perspective, it should be noted that while the lack of association

 between accessing the SBDC and firm performance could be viewed as disappointing, the SBDC’s

main objective is to help with new firm formations rather than to provide assistance to established

firms (which were the focus of this study). This is reflected in Table 2, which shows that the SBDC

was the least used network for the SMEs in this study. Therefore, the results should not be seen as

conflicting with the findings of Chrisman and McMullan (2004), who reported a positive associa-

tion between survival and an outsider assistance programme.

So, while the results indicate that a variety of formal and informal networks are associated with

SME performance (particularly external accountants and, to a lesser extent, industry associations,others in the industry and family and friends), they also indicate that SME owners need to monitor

the resources that they devote to networking in order to ensure that the benefits they receive from

networking exceed the costs. That is, the results do not support the widespread involvement of

SME owners in multiple networks. This finding appears to be consistent for male and female-

controlled SMEs. Finally, it should be noted that the results from this study indicate that women do

not appear to be disadvantaged (relative to men) by potential differences in their networking activi-

ties, calling into question the suggestion by Aldrich (1989)  that female entrepreneurs should

attempt to break into the ‘Old Boys’ network whenever possible.

Notes

1. To maintain a representative sample, businesses that ceased operations were replaced with similar

 businesses.

2. Copies of the questionnaires can be obtained from the ABS. Also note that the Australian tax year runs

from July 1 to June 30.

3. Note that the findings were not improved by examining firms above and below the median.

References

Aldrich H (1989) Networking among women entrepreneurs. In: Hagan O, Rivchun C and Sexton D (eds)  Women-owned Businesses. New York: Praeger, 103–132.

Australian Bureau of Statistics (2001) Characteristics of Small Business, Australia (8127.0). Canberra:

Australian Bureau of Statistics.

 at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 22/24

556 International Small Business Journal 30(5)

Bates T (1994) Social resources generated by group support networks may not be beneficial to Asian  

immigrant-owned small businesses. Social Forces 72(3): 671–689.

Becchetti L and Trovato G (2002) The determinants of growth for small and medium-sized firms. The role of  

the availability of external finance. Small Business Economics 19(4): 291–306.

Birley S (1985) The role of networks in the entrepreneurial process.  Journal of Business Venturing   1(1): 107–117.

Bratkovic T, Antoncic B and Ruzzier M (2009) Strategic utilization of entrepreneur’s resource-based social 

capital and small firm growth. Journal of Management and Organization 15(4): 486–499.

Brüderl J and Preisendörfer P (1998) Network support and the success of newly-founded business. Small  

 Business Economics 10(3): 213–225.

Bruderl J and Schussler R (1990) Organizational mortality: The liability of newness and adolescence.  

 Administrative Science Quarterly 35: 530–547.

Burt RS (1992) Structural Holes. Cambridge, MA: Harvard University Press.

Burt RS (2000) The network structure of social capital.  Research in Organizational Behavior   22(1): 

345–423.Chell E and Baines S (2000) Networking, entrepreneurship and microbusiness behaviour. Entrepreneurship & 

 Regional Development  12(3): 195–215.

Chrisman JJ and McMullan EW (2004) Outsider assistance as a knowledge resource for new venture survival. 

 Journal of Small Business Management  42(3): 229–244.

Coleman JS (1988) Social capital in the creation of human capital. American Journal of Sociology 94(supp.): 

S95–S120.

Cooper AC, Gimeno–Gascon JF and Woo C (1994) Initial human and financial capital as predictors of new

venture performance. Journal of Business Venturing  9(5): 371–395.

Cooper AC, Woo CY and Dunkelberg WC (1989) Entrepreneurship and the initial size of firms.  Journal of  

 Business Venturing  4(5): 317–332.Cromie S and Birley S (1992) Networking by female business owners in Northern Ireland. Journal of Business 

Venturing  7(3): 237–251.

Davidsson P and Honig B (2003) The role of social and human capital among nascent entrepreneurs.  Journal  

of Business Venturing  18(3): 301–331.

De Clercq D and Voronov M (2009) Towards a practice perspective of entrepreneurship: Entrepreneurial 

legitimacy as habitus. International Small Business Journal , 27(4) 395–419.

Diaz Garcia CM and Carter S (2009) Resource mobilization through business owners’ networks: Is gender an 

issue? International Journal of Gender and Entrepreneurship 1(3): 226–252.

Donckels R and Lambrecht J (1995) Networks and small business growth: An explanatory model. Small  

 Business Economics 7(4): 273–289.Duchesneau DA and Gartner WB (1990) A profile of new venture success and failure in an emerging industry. 

 Journal of Business Venturing  5(5): 297–312.

Evans DS (1987) Tests of alternative theories of firm growth. Journal of Political Economy 95(4): 657–674.

Fischer E and Reuber RA (2003) Support for rapid-growth firms: A comparison of the views of founders, 

government policymakers, and private sector resource providers. Journal of Small Business Management  

41(4): 346–365.

Fischer EM, Reuber RA and Dyke LS (1993) A theoretical overview and extension of research on sex, gender, 

and entrepreneurship. Journal of Business Venturing  8(2): 151–168.

Florin J, Lubatkin M and Schulze W (2003) A social capital model of high-growth ventures.  Academy of  

 Management Journal  46(3): 374–384.Glancey K (1998) Determinants of growth and profitability in small entrepreneurial firms.  International  

 Journal of Entrepreneurial Behaviour & Research 4(1): 18–27.

Granovetter MS (1973) The strength of weak ties. American Journal of Sociology 78(6): 1360–1380.

 at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 23/24

Watson 557

Greene PG, Brush CG, Hart MM, et al. (2001) Patterns of venture capital funding: Is gender a factor? Venture 

Capital  3(1): 63–83.

Hanson S and Blake M (2009) Gender and entrepreneurial networks. Regional Studies 43(1): 135–149.

Havnes P and Senneseth K (2001) A panel study of firm growth among SMEs in networks. Small Business 

 Economics 16(4): 293–302.Hoang H and Antoncic B (2003) Network-based research in entrepreneurship. Journal of Business Venturing  

18(2): 165–187.

Ibarra H (1992) Homophily and differential returns: Sex differences in network structure and access in an 

advertising firm. Administrative Science Quarterly 37(3): 422–447.

Jarillo CJ (1989) Entrepreneurship and growth: The strategic use of external resources.  Journal of Business 

Venturing  4(2): 133–147.

Jovanovic B (1982) Selection and the evolution of industry. Econometrica 50(3): 649–670.

Julien PA (1993) Small business as a research subject: Some reflections on knowledge of small businesses and 

its effects on economic theory. Small Business Economics 5(2): 157–166.

Kent P (1994) Management advisory services and the financial performance of clients.  International Small   Business Journal  12(4): 45–58

Kristiansen S, Kimeme J, Mbwambo A, et al. (2005) Information flows and adaptation in tanzanian cottage  

industries. Entrepreneurship & Regional Development, 17(5): 365–388.

Larson A and Starr JA (1993) A network model of organization formation.  Entrepreneurship Theory and

 Practice 17(2): 5–15.

Larsson E, Hedelin L and Garling T (2003) Influence of expert advice on expansion goals of small businesses 

in rural Sweden. Journal of Small Business Management  41(2): 205–212.

Lerner M, Brush C and Hisrich R (1997) Israeli women entrepreneurs: An examination of factors affecting  

 performance. Journal of Business Venturing  12(4): 315–339.

Lin N, Ensel WM and Vaughn JC (1981) Social resources and strength of ties: Structural factors in occupa-tional status attainment. American Sociological Review 46(4): 393–405.

Littunen H (2000) Networks and local environmental characteristics in the survival of new firms. Small  

 Business Economics 15(1): 59–71.

Low MB and MacMillan IC (1988) Entrepreneurship: Past research and future challenges.  Journal of  

 Management  14(2): 139–162.

Lussier RN and Pfeifer S (2001) A cross-national prediction model for business success.  Journal of Small  

 Business Management  39(3): 228–239.

Madill JJ, Haines GH and Riding AL (2004) Networks and linkages among firms and organizations in the 

Ottawa region technology cluster. Entrepreneurship & Regional Development  16(5): 351–368.

Marlow S, Henry C and Carter S (2009) Exploring the impact of gender upon women’s business ownership. International Small Business Journal , 27(2) 139–149.

Moore G (1990) Structural determinants of men’s and women’s personal networks.  American Sociological  

 Review 55(5): 726–735.

Munch A, McPherson JM and Smith-Lovin L (1997) Gender, children, and social contact: The effects of  

childrearing for men and women. American Sociological Review 62(4): 509–520.

 Nelson GW (1989) Factors of friendship: Relevance of significant others to female business owners.

 Entrepreneurship Theory and Practice 13(4): 7–18.

Orhan M (2001) Women business owners in France: The issue of financing discrimination. Journal of Small  

 Business Management  39(1): 95–102.

Potts AJ (1977) A study of the success and failure rates of small businesses and the use or non-use of account-ing information. Doctoral thesis, George Washington University, Washington, DC.

 at University of Western Australia on July 25, 2012isb.sagepub.comDownloaded from 

7/25/2019 3. Networking - Gender Differences and the Association With Firm Performance

http://slidepdf.com/reader/full/3-networking-gender-differences-and-the-association-with-firm-performance 24/24

558 International Small Business Journal 30(5)

Reese PR and Aldrich HE (1995) Entrepreneurial networks and business performance: A panel study of

small and medium-sized firms in the research triangle. In: Birley S and MacMillan IC (eds) International

 Entrepreneurship. London: Routledge, 124–144.

Renzulli LA, Aldrich H and Moody J (2000) Family matters: Gender, networks, and entrepreneurial out-

comes. Social Forces 79(2): 523–546.Robinson PB and Sexton EA (1994) The effect of education and experience on self-employment success. 

 Journal of Business Venturing  9(2): 141–156.

Robson P, Jack SL and Freel MS (2008) Gender and the use of business advice: Evidence from firms in the  

scottish service sector. Environment and Planning C: Government and Policy 26(2): 292–314.

Robson PJA and Bennett RJ (2000) SME growth: The relationship with business advice and external collabo-

ration. Small Business Economics 15(3): 193–208.

Rosa P, Carter S and Hamilton D (1996) Gender as a determinant of small business performance: Insights  

from a British study. Small Business Economics 8(4): 463–478.

Seibert SE, Kraimer ML and Liden RC (2001) A social capital theory of career success.  Academy of  

 Management Journal  44(2): 219–237.Shaw E, Lam W and Carter S (2008) The role of entrepreneurial capital in building service reputation. Service 

 Industries Journal  28(7): 899–917.

Starr JA and MacMillan IC (1990) Resource cooptation via social contracting: Resource acquisition strategies 

for new ventures. Strategic Management Journal  11(5): 79–92.

Stuart T and Sorenson O (2003) The geography of opportunity: Spatial heterogeneity in founding rates and  

the performance of biotechnology firms. Research Policy 32(2): 229–253.

Uzzi B (1996) The sources and consequences of embeddedness for the economic performance of organiza-

tions: The network effect. American Sociological Review 61(4): 674–698.

Watson J (2003) Failure rates for female controlled businesses: Are they any different?  Journal of Small  

 Business Management  41(3): 262–277.Watson J (2007) Modeling the relationship between networking and firm performance.  Journal of Business 

Venturing  22(6): 852–874.

Wilson F, Kickul J and Marlino D (2007) Gender, entrepreneurial self-efficacy, and entrepreneurial career  

intentions: Implications for entrepreneurship education.  Entrepreneurship: Theory and Practice  31(3): 

387–406.

Zhao L and Aram JD (1995) Networking and growth of young technology-intensive ventures in China. 

 Journal of Business Venturing  10(5): 349–370.

 John Watson is a professor in the Department of Accounting and Finance, The University of Western

Australia. His research interests lie in performance evaluation and measurement, and particularly the defini-tion of SME failure, SME failure rates, the effect of macro-economic variables on failure rates and comparing

the performances of male and female-controlled SMEs.