New venture growth and personal networks

New venture growth and personal networks

ELSEVIER New Venture Growth and Personal Networks Tone A. Ostgaard THE MANAGEMENTSCHOOL,IMPERIALCOLLEGEOF SCIENCE,TECHNOLOGY,AND MEDICINE,LONDON Sue ...

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ELSEVIER

New Venture Growth and Personal Networks Tone A. Ostgaard THE MANAGEMENTSCHOOL,IMPERIALCOLLEGEOF SCIENCE,TECHNOLOGY,AND MEDICINE,LONDON Sue Birley THE MANAGEMENTSCHOOL,IMPEmALCOLLEGEOF SCIENCE,TECHNOLOGY,AND MEDICINE,LONDON

This articlepresents the results of a survey of 159 owner-managed companies in England. The research question explores the effectiveness of personal networks in terms of firm performance and growth. Multiple regression confirmed the importance of networksfor company performance and development, j BUSN RES 1 9 9 6 . 3 6 . 3 7 - - 5 0

he primary linkage between new venture success and the entrepreneur seems to involve the entrepreneur's behavioral characteristics (Hofer and Sandberg, 1987). Moreover, the increasing attention paid by academics to the use of social business networks illustrates that networking is being used as a surrogate measure for behavioral characteristics. Indeed, Starr and colleagues (1990) argue that the study of networking skills and strategies may give new insights as well as provide alternative factors for understanding venture success. This is particularly the case for new ventures where the absence of a track record, with the possible effect on the ability to raise working capital, is a major factor constraining both their creation and expansion (O'Farrell and Hitchens, 1988). Thus, the role of networks and networking is no longer limited to sociology (Granovetter, 1973), but has increasingly been adopted as a medium for understanding human behavior, both in the start-up phase of new enterprises (Birley, 1985; Aldrich and Zimmer, 1986), and in developing and growing both independent ventures and corporate ventures (Mueller, 1986; Nelson, 1989; Charan, 1991). Indeed, Johannisson (1986b) argues that applying the network paradigm to venture creation changes the focal aspect of the process in that the entrepreneur's networking behavior, as it relates to the use of personal social and professional networks, will highly influence the success potential of the venture (Birley, 1985; Aldrich and

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Address correspondence to Tone A. Ostgaard, The Management School, Imperial College of Science,Technology and Medicine, 53 PrincesGate, Exhibition Road,London SW7 2PG, England. Journal of Business Research 36, 37-50 (1996) © 1996 Elsevier Science Inc. 655 Avenue of the Americas, New York, NY 10010

Zimmer, 1986; Aldrich, Rosen, and Woodward 1987; Birley, Cromie, and Myers 1991).

Social Network Theory In relation to this study, social network theory relies upon two basic premises (Birley and Cromie, 1988). First, the entrepreneurial process involves the gathering of scarce resources from the environment, and second, resources are usually obtained through the entrepreneur's personal network. As Johannisson (1990a, p. 3) notes, "Some of these resources may provide direct solutions to operational problems while others increase the firm's legitimacy in the market-place and indirectly provide access to resources needed for the pursuit of economic goals." Thus, the underlying assumption of the theory is that, in the absence of a track record for the firm, the entrepreneur must rely upon personal credibility in asking individuals, whether they be customers, suppliers, employees, or investors, to take a risk by providing the necessary resource (MacMillan, 1983; Birley and Norburn, 1985; Johannisson, 1986). A network in this respect provides the entrepreneur with support, contact, and credibility.

Network

Dynamics

Clearly, by its very nature, the role of personal networks in relation to new venture development is likely to be dynamic. As Butler and Hansen (1988) argue, the functions for which networks are to be valued change with the development of the organization and whereas "... social networks are very important in initializing the entrepreneurial process.., different types of networks have to be developed in a more proactive manner as the functional and strategies needs of the organization develop." Here the social network includes all those family, friends, and acquaintances with whom the entrepreneur relates to primarily on a social level (Szarka, 1990) as distinct from the professional network that includes all those individuals with whom ISSN 0148-2963/96/$15.00 SSDI 0148-2963(95)00161-1

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the relationship is primarily concerned with business. Indeed, Birley and Cromie (1988) propose a model of network development that moves from the start-up network, where social relationships are presumed to predominate to the growing network where professional networks predominate. The emphasis here is on the primary relationship. Clearly, it is possible for family members to be professional advisers and for professional contacts to be friends (Aldrich, Rosen, and Woodward, 1986). However, empirical research on such a transition has been limited (Butler and Hansen, 1988; Johannisson, 1990a), although several studies confirm the multiplexity of networks (Boissevain, 1974; Falemo, 1989). Thus, despite the considerable attention that the role of networks in entrepreneurship has received in the literature-the ultimate question still does not seem to be answered-do they matter?

Personal Networks and New Firm Growth Aldrich, Rosen, and Woodward (1986) contend that little has come forth as to the relative merits and contributions of social and professional networks to the development and growth of new businesses. In fact, only a handful of empirical studies deliberately ask this question and even fewer have actually found an indication of the effectiveness of networks in terms of continuous development and growth of the new venture. So, for example, Van de Ven et al. (1984) found high performing entrepreneurs to be more externally oriented, involving a broader network of potential customers and professional consultants in the planning and development of market niche and specific products thus maintaining"...a richer, broader, and more complex network of ongoing relationships with people both within and outside the firm" (p. 101). Birley (1985) found the social network to provide the main sources of help in assembling the resources needed among start-ups in Indiana. However, no significant relationship was found between growth and no-growth firms. Similarly, Carsrud, Gaglio, and Olm (1987) found social networks to have only minimal impact on the development of new ventures owned by women in Texas. Indeed, mentoring relationships were found to have a negative impact on performance, implying that mentors were so influential that they stifled necessary initiative and creativity. However, this result must be treated with caution. Of the 197 subjects, 130 did not respond to the question on network contacts. Mugler (1988) found "surviving" entrepreneurs to be more active in social relations than unsuccessful entrepreneurs. Duchesneau and Gartner (1988) found lead entrepreneurs of successful firms to be more likely to spend more time communicating with parmers, customers, suppliers, and employees than the lead entrepreneur of unsuccessful firms. This is analogous to the finding of Ginn and Sexton (1989) who concluded that moderate-growth founders preferred a "here and now" orientation with regard to gathering information, whereas high-growth founders favored a future orientation that had a major impact on the founders' involvement in strategic planning. Johannisson (1990a) found

that resourceful networks, both with respect to size and accessibility, seemed to infuse "Swedish new entrepreneurs with belief in future venture growth" (p. 19). Cooper, Folta, and Woo (1991) concluded that high usage of professional sources of information related to a greater likelihood of survival, whereas low usage corresponded with more failures.

This Research The previous review of the few studies linking networks and networking behavior to performance have provided inconsistent results. Thus, little conclusive evidence has come forth as to the potential of personal networks in stimulating growth. This is not altogether surprising since there is a wide variation in context, in the measurement of networks, in sample frames, and in the measurement of performance. Overall, however, the findings would lead us to expect that time spent nurturing and developing a broad range of contacts in the evolution of the business to be positively related to performance. Therefore, this study seeks to answer the simple question: How is new venture growth affected by the networking characteristics of the entrepreneur?

Research Hypotheses Dubini and Aldrich (1991) argue for the necessity to specify the conditions under which networking contributes to business effectiveness, and to link them to the contingencies facing firms. Therefore, based on the previous research question, six hypotheses were formulated. HI: New venture growth is more likely when the en-

trepreneur has (a) a large social network and (b) a large professional network. Falemo (1989) found that managers of expansive firms (those in the upper quartile with regard to sales) iderltified more external persons who channeled resources for product development and marketing than managers of regressive firms (those in the lower quartile with regard to sales). Hansen (1991) confirmed that social structures and processes that occur during the preorganization stage of a business explain to some extent the large variation in initial new venture growth rates, as measured by dollar amounts of monthly payrolls after one year. Size (number of people who contributed in some way to creating the new venture), degree of interconnectivity within the preorganization, and frequency of communication between preorganization members were all found positively to relate to new venture growth, with frequency only marginally so. Aldrich, Rosen, and Woodward (1987) found network size to be the only variable that showed a significant relationship to performance. Cromie and Birley (1992) note that " . . . if the entrepreneur can expand his or her social network or gain a more central position in a network, additional resources and opportunities might be uncovered and this could facilitate business expansion" (p. 6), and further "... a narrow contact base

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is likely to constrain the entrepreneur's ability to seek new market opportunities" (p. 13).

sured by the percentage of strangers in the personal network and by the duration of the relationship.

H2: New venture growth is more likely when the en-

Reflecting on an earlier finding by Aldrich, Rosen, and Woodward (1987) that profit-makers have networks whose members are closely associated and whose members are interconnected, Dubini and Aldrich (1991 ) hypothesize that "... effective entrepreneurs are able to check network density, so as to avoid too many overlaps (because they affect network efficiency) while still attaining solidarity and cohesiveness" (p. 311). Larson (1990) shows how entrepreneurial organizations maintained a handful of dense interorganizational networks (mainly with customers and suppliers) during a period of high growth. Hansen (1991) found that interconnectivity-the extent to which people in entrepreneurial action sets know each other (and therefore are able to interact with each other)-was positively related to new venture performance. Therefore, contrary to the Dubini and Aldrich (1991) hypothesis, and based upon the empirical evidence, we hypothesize that:

trepreneur has a large "global" network as measured by time spent on traveling to maintain and develop contacts. Johannisson (1986) indicates that the entrepreneur, and his/her employees, both directly and indirectly build global networks through their local networks, networks that, combined with the internal resources of the organization, create a change capability vital to the operation and development of the business. Falemo (1989) found that external persons who channeled resources for marketing and product development were more important if they lived outside the firm's local region in that they channeled resources of greater importance to the firm. I-I3: New venture growth is more likely when entrepreneurs

(a) take the initiative in establishing their network and (b) devote considerable time to establish and maintain personal networks. Several studies have indicated that entrepreneurs often go to considerable effort to involve members of their network in both the start-up and the growth of their business (Birley, Cromie, and Myers, 1991; Falemo, 1989). Further, Dubini and Aldrich (1991) hypothesize that effective entrepreneurs are more likely than others to undertake action toward increasing their network density and diversity, and toward stabilizing and sustaining their networks. Therefore, this hypothesis builds upon the results of several studies that indicate the significant amount of energy and time many entrepreneurs spend on developing and maintaining contacts (Birley, Cromie, and Myers, 1991; Aldrich, Rosen, and Woodward, 1986, 1987).

H6: New venture growth is more likely when the entre-

preneur maintains a high frequency of communication with their contact personal network. Aldrich, Rosen, and Woodward (1987) reported a positive relationship between new venture foundation and the average number of times per week entrepreneurs had contacted the five members of their personal contact network-those people who they "particularly like to talk to about their business." (This is the phrase used in the questionnaire and all other related studies by Howard Aldrich.) Hansen (1991) found a negative correlation between frequency of interaction between preorganization members and new venture performance after one year, but a positive relationship between network size and degree of interaction.

H4" New venture growth is more likely when the en-

trepreneur delegates networking responsibility and activity to colleagues in the firm. Kamm and Aldrich (1991) found a venture team effect in their Swedish sample such that the larger the venture team, the more hours were likely to be spent on contacting new and existing customers and on traveling to make contacts. Assuming age to be a surrogate for growth, Birley, Cromie, and Myers (1988) note " . . . a diffusion of effort as the firm grows, as reflected in the percentage of the entrepreneur's contacts who also have contact with other people in the firm." Delegation of responsibility and authority are, clearly, necessary ingredients for any organization successfully to grow. That "delegation" should also apply to the external personal network of the entrepreneur would therefore not be unexpected. Whether delegation of this activity actually contributes to growth or is rather a necessary, and maybe painful, adjustment on behalf of the entrepreneur remains an unresolved issue. H5: New venture growth is more likely when the en-

trepreneur's network contains many strong ties as mea-

Research Design Sample The sample in this survey consists of owner-managed companies less than 10 years old operating in two English counties: Cambridgeshire and Avon. A bounded geographical stratification was chosen for the research as there is evidence of different growth rates among U.K. regions as well as different rates of business formation (Moyes and Westhead, 1990). The two counties were selected in order to control for this effect, because they have experienced relatively equal rates of new firm formation (Moyes and Westhead, 1990) and also possess similar characteristics in terms of, for example, size, the industrial composition, and the urban/rural structure. Further, whereas we believe that networking is a universal activity, we were collecting data on "time spent in travel," and our intuition was that we would expect different absolute results on this variable from an entrepreneur based in the remote highlands of Scotland compared to those from one based in the center of London. Indeed,

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most of the networking studies to which we refer are geographically bounded. Companies were selected from the 1991 County Councils Industrial directories according to the following criteria: • The firm was owner-operated, i.e., independent. • The firm had fewer than 50 employees. It was necessary to fix an upper size limit, as the research question is such that it would be increasingly difficult to acquire any understanding of one person's network as the firm became large. The limit chosen is one commonly used in small business research (Robinson et al., 1984; Hornaday and Wheatley, 1986; Hakim, 1989). • The firm was more than two and less than 10 years old. The lower limit was selected because this is the first point at which growth performance can sensibly be assessed. It is, however, unclear from the literature when a new venture can no longer be considered "new." As no theoretical direction can be found, guidance was taken from previous empirical studies (Kirchoff and Phillips, 1989; Covin and Slevin, 1990). • Manufacturing firms were the focus of the study because of their "... leading role in generating wealth and income" (Harris, 1987, p. 302). Within this, data were collected on the total number of firms in the nine largest four-digit SIC categories within the two counties as measured by the number of new ventures within the respective industries. All companies that appeared to fit the criteria were initially contacted by telephone when the purpose of the study was explained and they were asked for cooperation. Of those contacted, 181 entrepreneurs in Avon and 241 in Cambridgeshire agreed to participate and were mailed a prepiloted questionnaire. Two follow-up mailings were sent to nonrespondents. The mail survey was conducted in the period from June to December 1991. Total usable response rate in Avon was 61% (N z 110) and 45% in Cambridgeshire (N ~ 108). No significant differences were found between early and late respondents indicating a possible lack of response bias. Despite the screening of the firms from the data in the business directories, only 84.5% of the Avon companies (n = 93) and 61% of the Cambridgeshire companies (n = 66) fit the sampling criteria leaving a total sample of 159 companies. This difference between the counties was found to be mainly due to the more accurate information on start-up date in the Avon database.

Growth/Performance Based on a review of the literature pertinent to the measurement of performance, three objective measures of growth were included: sales growth, increase in number of employees, and increase in profitability over a three-year period. Firm size was measured by operating profit (1990), sales (1990), and fulltime employees (January 1991).

Networks The networking variables used. in this study originate primarily from Howard Aldrich and have been used in several national studies (Aldrich, Rosen, and Woodward, 1987; Aldrich, Reese, and Dubini, 1991; Birley, Cromie, and Myers, 1991). An attempt was also made to capture the content of network exchanges because "... the transactional content of a relation thus gives a crude measure of its quality" (Boissevain, 1974, p. 33). Guidance as to the particular variables was taken from Birley (1985), Mattsson and Noren (1988), Falemo (1989), and Nelson (1989). They are listed in Appendix 1 in relation to the six hypotheses.

Data Analysis In order to explore the research hypotheses, each of the variables was first entered into a correlation analysis. The significant correlation coefficients were examined together with scatter plots because the same coefficient can result from very different underlying relationships. The general research question was examined by means of multiple regression analysis. Due to the assumption of normal distribution, the employment data were logtransformed as they were highly skewed toward the lower end of the scale. The relationships among all independent variables were first examined by bivariate correlation analysis using the Pearson correlation coefficient. A "web" of intercorrelations was found between the independent variables, causing multicollinearity. Although multicollinearity does not violate any assumptions and does not affect predictions, it does make the estimates of the regressions coefficients unreliable (Lehmann, 1979). Therefore, in order to deal with the potential problems resulting from inclusion or exclusion of variables on the basis of multicollinearity, several multiple regressions were run. Three sets of procedures were followed, not with the objective of testing hypotheses relating to each individual variable, but rather to identify patterns. The first was to include all the variables, recognizing the presence of multicollinearity, but living with the consequences (Berry and Feldman, 1985); the second involved only the independent variables where the relationship with the dependent variables was significant at .10; and the third involved removing variables with strong intercorrelations. An adjusted R2 statistic was used as the basic measure of the model's explanatory power with the criterion level set at. 10, because the purpose of the analysis was not prediction but rather an exploratory analysis of the direction and strength of the relationships (Stearns, Carter, and Reynolds, 1993). In this sense, the results from all the analyses were similar. Therefore, the following analysis is based upon the second procedure. 1. Only independent variables whose relationship with the dependent variable was statistically significant (p <. 10) were chosen for further analysis. 2. Of these variables, any variable that was strongly correlated with any of the other independent variables was re-

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moved. Here we used Hair, Anderson, and Tatham's (1987) rule of thumb to determine the cutoff point for intercorrelation, i.e., no predictor variable was included that was more closely related to the best predictor than it was to the dependent variable. 3. Stepwise regression was chosen as the method for entering the variables in multiple regression. Stepwise regression reexamines the independent variables at each stage to identify any that have become superfluous following the introduction of subsequent items, and it permits use of previously rejected variables. In doing so, stepwise regression takes particular note of the problems of multicollinearity, but may exaggerate the problem of omitted variables. The F-ratio statistic, together with its level of significance (p < .10), was used as a measure of the model's overall significance. The SPSSPC+ statistical package for the social sciences was used to perform the statistical analyses. Cases with missing values for any of the variables included in the multivariate regressions were excluded.

Limitations The analysis of the data and interpretations of the findings of this research are subject to several limitations. First, there are inevitably limitations involved in the measurement of networking activity. The research design called for single respondents per organization. As the focus of this research was on the entrepreneur's networking activities, no attempt was made to capture the "total" networking activities going on in the firm as a whole. Nevertheless, in investigating the relationships between such activities and firm growth in particular, the use of only one respondent per firm is a source of measurement error for all constructs, and maybe particularly so for the network construct. Nearly 80% of the firms do in fact have more than one owner. Second, the networking activities of employees have been completely disregarded. Although there is no reason to believe this potential bias as being as serious as the former, the networks of employees are nevertheless an important factor (Hakansson, 1987), which has been disregarded. Third, despite the findings presented in this study, the measures of networking activity and network characteristics should not be overvalued as they are relatively crude measures of networking activity. An inherent problem with any statistical study, especially of such an, as yet, vague concept as networking, is that

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no set of variables can hope to capture all relevant aspects; that is, there will always be omitted variables, and their effect will be reflected in those included variables with which they are correlated (Keeley and Roure, 1990).

Analysis and Results Firm characteristics are given in Table 1. About 60% of the sample was incorporated, 20% partnerships, and 20% sole proprietorships. The entrepreneurs' ages ranged from 25 to 70 with a mean of 43.8 (SD - 8.93). About 92% were men, and 89% were married. Of the sample, 58% had at least advancedlevel school leaving qualifications and, of these, 11.4% had a postgraduate degree.

Correlation Analysis HI: Taking a 5% significance level, Table 2 shows a com-

plete lack of any significant relationship between the size of the network and sales or profit growth. However, there is some support for the hypothesis when absolute values of sales and profit are measured. Thus, those with the larger firms are more likely to have larger networks. Moreover, they are also likely to include people in their network who have a commercial relationship with their firm rather than a purely social relationship. With regard to network content, those from the larger sales firms are more likely to use their networks for competitor information and to obtain new contacts and less likely to use them for advertising by word of mouth. Those from the firms with the larger profits are likely to use their networks to obtain new contacts and less likely to use them for finding new product ideas. There is more support for the hypothesis when examining the results for employment. Thus, those employing the larger number of people in 1991 are likely to belong to the larger number of trade organizations and fewer social organizations. Consistent with this, entrepreneurs with the larger firms tend to have talked to those people in their network who have a commercial relationship with the firm. Moreover, they are more likely to use the network for obtaining competitor in-

Table 1. Firm Characteristics Characteristics

Mean

SD

Range

Year Started Full-time employment January 1991 Number of partners Percent sales growth 1990/1988 Percent profit growth 1990/1988

1985 9.7 2.6 113.0 115.8

2.54 14.2 2.7 190.1 221.0

1980-1988 0-75 1-30 (-50)-(1250) ( - 125)-(1000)

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Table 2, Correlations between Networks and Performance Measures Profit

Sales

Employment

1990

Growth

1990

Growth

Start

1991

Growth

Size of networks TRADE SOCIAL PROF NETWORK NETWCOMM

0.13 -0.17 a -0.07 0.146 0.32 a

0.04 -0.05 0.16 -0.03 0.07

0.11 -0.04 -0.03 0.18 b 0.23 a

-0.03 -0.10 0.03 -0.10 -0.09

0.12 -0.09 -0.05 0.11 0.26 a

0.17 a -0.19 ~ -0.05 0.08 0.27 ~

-0.43 ~ -0.01 -0.18 ~ 0.12 0.24 ~

Content of networks CUSTOMER MRKTINFO COMPINFO ACCESS CONTACTS WORDOFM ADVICE PRODIDEA INVESTOR

0.02 0.08 0.18 a 0.02 0.16 b -0.156 0.05 -0.13 0.11

0.176 -0.07 -0.00 0.10 0.05 0.00 0.03 0.05 0.08

0.14 0.05 0.05 0.07 0.17 ~ -0.08 0.00 -0.22 ~ -0.07

0.22 a -0.06 0.03 0.31 ~ 0.05 -0.04 0.17 0.2P 0.23 a

-0.03 0.11 0.12 0.02 0.08 -0.23 ~ 0.03 -0.10 0.10

-0.05 0.14 0.18 a -0.02 0.06 -0.20 ~ 0.05 -0.10 0.09

-0.16 0.08 0.14 0.07 0.01 -0.2P -0.03 -0.05 0.04

-0.02

0.03

0.01

0.01

0.12

-0.02

0.06 -0.06 -0.06 -0.12 0.02 -0.02 - 0.09

0.09 -0.03 0.13 -0.02 0.18 a -0.08 - 0.05

0.06 -0.15 0.10 -0.11 0.03 0.07 - 0.00

0.15 b 0.06 0.26 a 0.12 0.29 a 0.04 - 0.11

0.12 -0.08 0.21 a 0.10 0.24 a 0.06 - 0.10

0.06 -0.09 0.05 0.00 0.2P 0.09 - 0.08

0.06

0.02

0.27 a

0.38 a

-0.22 a -0.02

0.05 -0.38 a

-0.14 0.06

-0.14 0.15

-0.00 -0.01

0.22 a -0.03

-0.06 -0.19

0.196 -0.17

0.28 a -0.12

0.02 -0.08

Global network TRAVEL

0.11

Establishing and maintaining network NEWCUST 0.13 OLDCUST 0.08 NEWSUPPL 0.23 a OLDSUPPL 0.06 NE'v~VINVES 0.26 a OLDINVES 0.02 INITIATI - 0.08 Delegation of networking MONOPOLY

0.36 a

0.04

Diversity in personal contact network STRANGER NETW Intensity of relationship with PCN FREQUENC 0.18 b KNOWN - 0.12

0.01 -0,18

0.25 ~

a Significantat 05 level. b Significantat . 1 level. f o r m a t i o n a n d less likely to use it to a d v e r t i s e t h r o u g h w o r d of m o u t h . Interestingly, e n t r e p r e n e u r s w i t h the h i g h e r g r o w t h firms are less likely to b e m e m b e r s of e i t h e r t r a d e o r p r o f e s s i o n a l o r g a n i z a t i o n s , b u t still rely u p o n talking to p e o p l e w h o h a v e a c o m m e r c i a l relat i o n s h i p w i t h the firm.

H2:

T h e r e is n o s u p p o r t for this h y p o t h e s i s across a n y of the v a r i a b l e s studied.

H3:

T h e r e is s o m e s u p p o r t for this h y p o t h e s i s in relation to absolute size, b u t only o n e significant result in relation to g r o w t h rates. Thus, the e n t r e p r e n e u r s w i t h the larger firms are likely to use t h e i r n e t w o r k s to find n e w s u p p l i e r s a n d investors.

H4:

T h e r e is e v i d e n c e that t h o s e w i t h the larger firms in t e r m s of sales a n d e m p l o y m e n t a n d t h o s e w i t h g r o w -

ing e m p l o y m e n t t e n d to h a v e c o n t a c t s w h o also k n o w o t h e r s w i t h i n the firm.

H5:

T h e r e is e v i d e n c e that t h o s e w i t h larger firms are likely to h a v e a smaller p e r c e n t a g e of s t r a n g e r s in the p e r sonal contact n e t w o r k .

H6:

T h e r e is s o m e s u p p o r t for this h y p o t h e s i s in that t h e r e is a r e a s o n a b l y c o n s i s t e n t c o r r e l a t i o n b e t w e e n size a n d the n u m b e r of h o u r s p e r m o n t h that r e s p o n d e n t s s p e n d c o m m u n i c a t i n g w i t h t h e i r p e r s o n a l contact n e t w o r k .

Multivariate Regression Analysis T h e p r e v i o u s s i m p l e c o r r e l a t i o n analysis gives variable s u p p o r t to the six h y p o t h e s e s . H o w e v e r , as e x p e c t e d in v i e w of the holistic n a t u r e of n e t w o r k i n g , t h e r e w e r e also significant i n t e r c o r r e l a t i o n s . Therefore, in o r d e r to o b t a i n a m o r e realistic

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Table 3. Regression on Sales and Profit 1990 Profit

Sales BETA

Control variables LOGSTRT FIRMAGE EDUCATN IND2 IND3 IND8 IND9

0.53 0.10 0.02 -0.05 0.07 -5.63e-03 -0.08

Size of networks SOCIAL NETWORK NETWCOMM Content of networks WORDOFM COMPINFO CONTACTS PRODIDEA

Diversity in PCN STRANGER COLLEAG ENGINEER

df

F Sig. F

0.000

0.098 0.106 0.121 0.102 0.089 0.094 0.119

-

0.23 0.23 -0.47 0.23 -0.18 -0.20 0.25

-0.02 0.09 0.15

-

-0.16 0.84 1.43

0.876 0.403 0.159

NE 0.15 0.17

-0.18

0.096 -

- 1.89 0.62 0.86

0.063

0.538 0.392

NE NE 0.10 -0.48

0.09 - 0.08 0.17 -0.02

Intensity of relationship with PCN FREQUENC 0.04 Adjusted R2 N

BETA

0.293 0.867 0.621 0.479 0.954 0.454

0.06 0.09 NE

0.097 -

SIG t

SE BETA

5.48 1.06 0.17 -0.50 0.71 -0.06 -0.75

Establishing and maintaining networks NEWINVES 0.35 NEWSUPPL 0.09 Delegation of networking MONOPOLY

SE BETA

-

0.096 -

3.66 0.99

0.324

0.08 NE

-

0.89

0.379

NE

-0.85 1.75 -0.24

0.400 0.811

-0.36 0.17 -0.19

0.39

0.694

0.02

0.169 -

0.4166 122 6O 12.427 0.000

0.001

0.085

0.106

0.100 0.095 0.097

t

SIG t

2.37 3.00 -3.86 2.29 - 2.03 - 2.17 2.14

0.021

0.004 0.000 0.026 0.047 0.034 0.037

1.453 1.641

0.152 0.106

0.932 -4.525

0.356

0.813

0.419

- 3.589 1.760 - 1.992

0.001 0.084 0.051

0.203

0.840

0.000

0.4409 110 57 6.284 0.000

Abbreviation: NE, not entered

picture of the pattern of activities, and to examine the general research question, a n u m b e r of multivariate analyses were conducted. (See the data analysis section for a full outline of this procedure.) In addition to the explanatory networks variables, several control variables were entered into the analyses. Education has been found to increase network range and diversity in personal networks (Aldrich, Reese, arid Dubini, 1989, 1990) and was therefore included as a control variable together with industry (SIC categories), age of the firm, and start-up size. Industry and the occupation of the members of the personal contact network were entered as d u m m y variables. SALES. Table 3 shows that two variables in particular emerged as significant in explaining sales size. Most importantly, size at start-up in terms of employees (LOGSTRT) is the single most

important determinator of sales 1990. The "large start-up-later larger size" factor is not an unheard of p h e n o m e n o n as indicated by numerous studies (Cardozo et al., 1992). However, of more interest here is the single important contribution of one networking variable: time spent developing contacts with new investors. Not quite so unexpected is the importance of colleagues/parmers as members of the entrepreneurs' personal network for larger firms (Birley, Cromie, and Myers, 1991). Consistent with the need to delegate and to introduce more formal methods of marketing as the firm increases in size (El Rayyes and Birley, 1991 ), the extent to which personal networks contribute to advertising by word of mouth is negatively related to level of sales. As expected, sales growth between 1988 and 1990 (Table 4) is strongly related to the age of the firm: the younger the firm, the higher the growth rate. Operating in the office ma-

44

J Busn Res 1996:36:37-50

A. Ostgaard and S. Birley

Table 4. Regression on Growth in Salesa and Profit Sales BETA

Control variables LOGSTRT FIRMAGE EDUCATN IND3 IND9

-0.04 -0.34 -0.20 -0.28 0.08

Size of networks NETWCOMM

0.16

Content of networks WORDOFM CUSTOMER INVESTOR ACCESS PRODIDEA Diversity in PCN NETW

-0.52 0.38 NE NE NE

df

F Sig. F

t

SIG t

0.114 0.115 0.111 -

-0.37 - 2.99 - 1.74 -2.48 0.64

0.714

-0.03

-

0.005

- O. 15

-

0.089 0.524

1.2e-03 -0.02 0.41

1.35

0.183

NE

-4.15 3.03

0.000 0.004

0.125 0.126

0.017

NE

Intensity of relationship with PCN KNOWN -0.14 Adjusted R2 N

Profit

SE BETA

-

- 1.11

.4468 98 41 8.430 .000

0.273

BETA

SE BETA

t

SIG t

0.114

-0.23 - 1.28 0.01 -0.23 3.63

0.817 0.209 0.992 0.820

NE 0.28 0.47 1.1 e-03 - 0.10

0.111 0.109 -

2.50 4.32 0.01 -0.85

0.017 0.000

0.993 0.402

-0.46

0.118

- 3.93

0.000

0.001

NE .5415 47 37 13.105 .000

a Two further variableswere includedin this analysisafter the correlationswere rerun excludingtwo outliercases.Abbreviations:NE, not entered. chinery and data industry (SIC 3300) seems to have a negative impact on sales growth. Two network content variables appear to have an impact on sales growth: gaining contact with customers through personal network has a positive influence and, consistent with results in the previous section, advertising by word of l:nouth has a negative impact. Profit size (Table 3) would appear to be more influenced by the control variables of industry in which the firm operates, age of the firm, and education level of the entrepreneur than by the networking activities of the owners. Two of the industry categories have a positive relationship with profit (IND2, mechanical engineering; IND9, computer software), whereas manufacturers of paper and paper products (IND8) and of ofrice machinery (1ND3) show a negative relationship. Not surprisingly, start-up size has the same impact on profit as on s a l e s - t h e larger the start-up size, the higher the present profit size. Education was also positively related to operating profit. (Higher education was given a score of 1 leading to an expected negative sign). Whereas network activity seems to have little or no impact on profitability, this is not the case for diversity of the network composition. The significant negative sign for percentage of strangers in the personal network supports the hypothesis that entrepreneurs of more profitable firms have networks, the members of which are closely connected. Further, the occupation

of personal network members does seem to play a stronger role. In particular, entrepreneurs who include colleagues in their personal networks tend to have more profitable firms. Unfortunately, the same cannot be said for engineers! A negative relationship occurs between profitability and existence of engineers in personal network. This latter finding may be explained on the basis of firm size. W h e n controlling for the number of fulltime equivalent employees, the effect disappears, and unrelated occupations (UNREL) assumes a negative influence on profit. The negative sign of assistance with product and service development was unexpected and may suggest that the network content variable reflects a product innovation strategy. In other words, firms pursuing a product innovation strategy (and drawing on the entrepreneur's network for ideas and feedback) are less profitable due to the longer return on investment period for high-tech products. Firms operating in the software industry (INDg) have not only a higher profit per se, but they have also experienced a higher profit growth (Table 4). Similarly, whereas entrepreneurs who have a low percentage of strangers in their personal network tend to have achieved a higher profit level, growth in profit seems to be related to another network diversity variable: size of secondary networks (NETW). The negative sign is a further indication of the dense network surrounding entrepreneurs of profitable firms. Interestingly, entrepreneurs who gain contact

New Venture Growth and Personal Networks

J Busn Res

45

1996:36:37-50

Table 5. Regression on Employment in 1991 and Employment Growth Log Employment Growth

Log 1991 Employment BETA

SE BETA

t

SIG t

BETA

SE BETA

t

SIG t

Control variables LOGSTRT FIRMAGE EDUCATN IND4

0.60 -0.07 -0.01 -0.17

0.082 0.083

7.28 -0.78 -0.18 - 2.05

0.000 0.439 0.859 0.045

- 22e-0 -0.08 -0.13 - 5.7e-03

-

- 0.02 -0.87 - 1.49 - 0.07

0.981 0.384 0.140 0.948

Size of networks TRADE SOCIAL PROF NETWCOMM

0.05 - 0.11 NE 0.09

-

0.55 - 1.27

0.581 0.208

-

-0.41

0.679

-

1.04

0.303

-0.04 NE -3.7e-04 0.36

0.089

-0.00 4.05

0.997 0.000

Content of networks WORDOFM COMPINFO

-0.30 0.07

0.082 -

- 3.68 0.73

0.001 0.469

- 0.27 NE

0.088

- 3.05

0.003

0.082 0.083

4.82 2.52

0.000 0.015

0.24 NE

0.088

2.77

0.007

-

1.21

0.231

0.13

-

1.47

0.144

2.19 - 1.01 0.49

0.033 0.317 0.625

0.03 0.17 - 0.15

0.31 1.96 - 1.73

0.757 0.053 0.088

0.55

0.583

NE

Establishing and maintaining networks NEWlNVES 0.40 NEWSUPPL 0.21 Delegation of networking MONOPOLY 0.11 Diversity of relationship with PCN COLLEAG 0.18 PROFESS - 0.08 ENGINEER 0.04

0.083 -

Intensity of relationship with PCN FREQUENC 0.05

-

Adjusted R2 N df F Sig F

0.5661 120 60 15.353 0.000

0.099 0.089

0.2719 113 94 8.395 0.000

Abbreviation: NE, not entered.

with investors and customers through their personal n e t w o r k have e x p e r i e n c e d a higher profit growth. Table 5 s h o w s that start-up size (employment) continues to be related to present size, this time in terms of e m p l o y e e s (log of full-time equavalent e m p l o y e e s in January 1991). O n e industry, electrical and electronic engineering (IND4), appears to have a negative impact on firm size. Netw o r k i n g activity and n e t w o r k diversity s h o w a significant relationship with the dependent variable: entrepreneurs w h o spend a significant a m o u n t of their time d e v e l o p i n g contact with n e w investors and n e w suppliers have larger firms in terms of emp l o y m e n t size. These e n t r e p r e n e u r s also tend to have coll e a g u e s / p a r m e r s as m e m b e r s of their personal networks. Finally, advertising by w o r d of mouth continues to show a negative impact on the d e p e n d e n t variable. EMPLOYMENTSIZE.

EMPLOYMENT GROWTH. A large c o m m e r c i a l network, time spent developing n e w investors, and having professionals as

m e m b e r s of the personal contact network are all associated with higher e m p l o y m e n t growth since 1988. Advertising by w o r d of m o u t h is again negatively related to growth. Education has a positive effect as expected, although not significantly so for any of the two e m p l o y m e n t variables. Table 6 s u m m a r i z e s the variables that emerge in the previous regression analyses.

Discussion and Conclusions The u n d e r l y i n g a s s u m p t i o n of social n e t w o r k theory is that through their personal networks, e n t r e p r e n e u r s of a n e w venture gather access to critical resources which, for a variety of reasons, the new firm does not possess internally. Consequently, this research has argued that this resource base cannot be ign o r e d w h e n attempting to understand the relationship between the resources a new firm has at its disposal and the subsequent growth of the firm. Indeed, J o h a n n i s s o n (1990b) argues that

46

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A. Ostgaard and S. Birley

Table 6. Summary of Multivariate Regression Analysis

Direction of Relationship Control variables LOGSTRT Positive FIRMAGE EDUCATN Positive IND2 Positive IND3 Negative IND4 Negative IND8 Negative IND9 Positive Size of networks NETWCOMM Positive Content of networks PRODIDEA Negative WORDOFM Negative INVESTOR Positive CUSTOMER Positive Establishing and maintaining the network NEW INVES Positive NEW SUPPL Positive Diversity in PCN STRANGER Negative NETW Negative COLLEAG Positive ENGINEER Negative PROFESS Positive

Size

Growth

Profit

Sales

Employment

* * (+ve) * *

*

g*

Profit

Sales

Employment

* (-ve)

* *

*

the personal network of the entrepreneur is " . . . the strategically most significant resource of the firm" (p. 41). Interestingly, however, this analysis underlined two important points. The first is that networking involves a multiplicity of activities and so, not surprisingly, the important findings emerged from the multivariate analysis rather than from the univariate correlations. The second issue concerns the importance of incorporating the control variables. Thus, whereas not directly related to this study, start-up size was found to have a consistently strong positive relationship with present size, whether in terms of sales, profit or employees, a finding in accordance with numerous studies citing start-up size as having an effect both on survival (Birley, 1987; Kirchhoff and Phillips, 1989; Cooper, Dunkleburg, and Woo, 1988) and subsequent growth (Bannock and Gray, 1989; Cooper, Woo, and Dunkleburg, 1989). The industry in which the firm operates also exhibited a strong influence on firm performance, particularly so in the case of the profit measures. Not unexpectedly, firm age was positively related to present size (profit), and negatively related to firm growth. Reassuringly, higher education also appeared to have a positive impact! The research question was formulated on the basis of previous research, primarily from the fields of sociology and entrepreneurship. In sum, it was proposed that large networks, high levels of networking activity, a more diverse network, and

more communication with personal network members would be positively related to new venture growth. Overall, the findings are as follows. Network activity incorporates both the size of social and professional networks (H1) and the e x t e n t t o which the entrepreneur spends time establishing and maintaining the network (H3). Although both size of the commexiciat network and time spent developing supplier relationships were positively associated with performance, of particular interest is the apparent importance of developing investor relationships. Leontiades (1982) suggests that external "buy" strategies (e.g., acquisitions) require managers who can build contacts with the financial/brokerage community. The "physical" expansion often associated with employment growth may explain the positive association between time spent developing new investor relationships and this growth variable. Swift (1989) found that high-growth firms perceived a greater problem with the banker's understanding of their business than did other firms and seemed to shop around more for a new financial institution. In his literature review, Wetzel (1987) found that informal investors' decision to consider an investment was highly related to personal knowledge of the business field or the entrepreneur, or a high regard for the third party who brought the investment opporutunity to the investor for review. His review illustrates the dominant role of informal networks of trusted friends and business

New Venture Growth and Personal Networks

associates in the referral process. Moreover, Van de Ven, Hudson, and Schroeder (1984) found high performers to have more frequent communications with employees, customers, and financiers than low performers. Finally, Bruno and Tyebjee (1985) reveal the amount of time spent by entrepreneurs in search of financing, and also show that large capital infusions through relinquishment of most of the equity leads to higher performance as compared to firms in which the founders continue to maintain control. External search for financing is therefore not only associated with the start-up process of the new venture (Birley, 1985), but also the continued growth and development of the firm. This research has shown that entrepreneurs who devote some time to the development of contacts with new investors tend to manage high-growth firms. Employment growth appears to be significantly related to time spent developing contact with all the strategic interest groups included: customers, suppliers, and investors. This finding appears to support Aldrich, Rosen, and Woodward's (1987) findings that developing contacts are significant for business founding, but not for profitability. Apart from developing contacts with new investors, none of the other measures of developing contact was related to profitability. The findings may, therefore, reflect firm size and growth (in terms of sales and employees) as having a larger impact on the way entrepreneurs distribute their time, how they manage the firm in general and, specifically, how they conduct networking activities. The fact that these results relate to growth rather than profitability is not unexpected in view of the trade-offs between achieving growth and profitability in the literature. Profitability is greatly affected by amounts reinvested to build the business, and growth-oriented companies may invest heavily in product and market development, resulting in losses or low profits even when the firms are well-managed (Cooper, 1979; Cooper, Woo, and Dunkleburg, 1989). Therefore, these findings support and extend those of Aldrich et al. (1987) that developing contacts is not only important for business founding (this sample is per definition "successful" founders), but also to the continued development of the firm. Whereas time spent developing new suppliers and investors appears to be have a significant relation to performance, there is a complete lack of variables relating to the maintenance of contacts. A possible explanation may be found in the age distribution of this sample. Aldrich Rosen, and Woodward (1987) found that for businesses three years and younger, entrepreneurs who maintain high levels of contact with networks whose members were interconnected were more likely to make a profit. As the sample in this study consists of firms that are at least two years old, it is possible that maintaining contacts may be more important in the early stages of a ventures development when it is more vulnerable and when the potential impact of losing any of its relatively newly acquired contacts more damaging. Equally, time spent developing customer relationships, new or old, was not included in the analysis, due to lack of significant relations, a finding that may indicate that develop-

J Busn Res 1996:36:37-50

47

ing customer relationships is particularly important in the venture's early years, whereas its importance for further growth when the firm is more established in the marketplace may be limited. Alternatively, although dealing with customers is without doubt important, its activity may be of such a crucial character that all firms implicitly understand the importance of good customer relations. Indeed, the vast amount of the entrepreneur's time spent on developing and maintaining contacts is directed toward customers. Two network content variables showed a negative relationship with the performance and growth variables-assistance in product/service development and advertising by word of mouth. This suggests that high-growth firms have implemented more "formal" procedures for marketing and product development and perceive use of their network for such purposes as not being compatible with this "professional approach." What is also of particular interest are the variables not present. In particular, no relationship was found between new venture growth and time spent on travel in relation to the development and maintenance of contacts, taking the initiative for contact, and time spent maintaining contacts. In particular, a positive relationship was expected between time spent on travel and new venture growth (H2). Spatially weaker links (less proximity involved) were assumed to be informationally stronger (Rogers and Kincaid, 1981) and able to provide more improtant resources to the firm (Falemo, 1989). No support could be given to this hypothesis. There are two possible explanations for this finding. First, global networks may simply not have any association with growth, and second, travel is merely one way of communicating with a "global" network (Cromie, Birley, and Callaghan, 1992). Moreover, although taking the initiative for contact was positively related across all measures as expected, none were significant. Taking the initiative for contact may be a characteristic of high-performing entrepreneurs, or it may be a trait common to entrepreneurs in general. In fact, it may be a trait "responsible" for their coming into being as entrepreneurs in the first place. Although delegation of networking (H4) activities had a positive association with growth in the univariate correlation analysis, the variable failed to survive the multivariate analysis. Instead, the presence of colleagues/partners in the entrepreneurs' personal networks was found to be related to all performance size measures. Network diversity (H5) was concerned with the structure of entrepreneurs' personal contact network-the five individuals with whom they regularly discusses their business. Network diversity builds upon Granovetter's (1973) theory of weak ties, which assumes that networks that include people who are not personal friends are more likely to contain diverse information. Thus, the percentage of strangers in personal networks and the size of secondary networks have been argued to affect both the speed with which information circulates to network members and the diversity of this information (Granovetter, 1973; Aldrich, Reese, and Dubini 1989). Despite the sociologi-

48

J Busn Res 1996:36:37-50

cal hypothesis that less dense networks tend to possess a wide variety of information, thereby having a positive effect on network efficiency, the (albeit limited) empirical evidence actually contradicts this hypothesis. This research lends support to these previous empirical findings (Aldrich, Rosen, and Woodward, 1987; Larson, 1990; Hansen, 1991). In fact, not only do successful (i.e., more profitable) entrepreneurs tend to have a denser network in terms of "percentage of strangers," they also tend to have smaller secondary networks. It may be that profitoriented entrepreneurs are more concerned about the efficiency of internal operations, and (consciously) attempt to build a dense network in order to have the less diverse, but highly relevant information easily flow through this network. The density of networks in general and secondary networks in particular, may be more important in instances where the entrepreneur seeks to increase sales/market share, i.e., more market/competitiveoriented behavior. The presence of colleagues/parmers in the entrepreneurs' personal networks is strongly related to all performance measures. The results give support to Allen (1970) who found high performers (in R&D laboratories) to make far greater use of colleagues as a source of technical information. Entrepreneurship research seems to offer the same conclusion (Van de Ven, Hudson, and Schroeder, 1984; Storey, Watson, and Wynarczyk, 1989). The positive impact of professional advisors (bankers, accountants, lawyers, and consultants) in personal networks Should also not come as any great surprise. "Outsider-based" strategic planning has been found to have a positive impact upon small firm performance (Robinson, 1982) and, consistent with this, this study identified a positive association between new venture growth and network diversity in terms of the occupational roles of network members. Overall, this research lends support to previous studies arguing the particular informational value of business contacts (Birley and Cromie, 1988; Aldrich and Von Glinow, 1990). Although this study gathered data on the entrepreneur's relationship with the five personal network members in addition to their occupation, the results presented simply relate to their occupation. There is, in other words, no claim to be made that these people are not also personal friends or family of the entrepreneur. What can be claimed is that network members who merely have a friendship or family affiliation with the respondent do not appear to contribute greatly to the venture's growth. Two measures of network intensity (H6), which is the strength of interpersonal ties, have been argued to be the frequency of interaction with personal network members (Granovetter, 1973; Boissevain, 1984) and years knowing these members (Boissevain, 1974). New venture growth was proposed to be more likely when entrepreneurs maintain a high frequency of communication with their personal network. However, none of these variables emerged as significant in the multiple regression analysis, although frequency of communication did have a positive bivariate relationship with the dependent variables,

A. Ostgaard and S. Birley

suggesting that its explanatory effect was "replaced" by another variable in the multiple regression analyses. Notwithstanding the limitations of this study, this research has established a link between the entrepreneur's networking behavior and the growth of the firm. What, then, can explain some of the disparities between this study and previous studies investigating the actual impact of personal networks on new venture growth? First, this study included a wider variety of measures of personal networks than any other study. This larger number may, of course, increase the chances of significant relationships occurring, but also may incorporate important aspects of networks previously ignored. Moreover, this study included a wider range of growth and performance measures, and the results illustrate very clearly the importance of taking into account the different ways by which new ventures grow. Second, this sample of 159 entrepreneurs is larger than has been common in studies of this kind. Third, the interval scaled measures used provided for the use of more powerful parametric statistical tests. Overall, however, this research has tended to confirm the arguments put forward by others rather than to dispute them.

References Aldrich, H., and Zimmer, C., Entrepreneurship through Social Networks, in The Art and Science of Entrepreneurship, D.L. Sexton and R. Smilor, eds, Ballinger, Cambridge, MA. 1986, pp. 3-23. Aldrich, H., Rosen, B., and Woodward, W., The Impact of Social Networks on Business Founding and Profit: A longitudinal Study, in Frontiers of Entrepreneurship Research, Babson College, Wellesley, MA. 1987, pp. 154-168. Aldrich, H. E, Reese, P. R., and Dubini, P., The Go-Between: Broker's Roles in Entrepreneurial Networks, in N. C. Churchill, et al., eds. Frontiers of Entrepreneurship Research, Babson College, Wellesley, MA 1990, pp. 554-555. Aldrich, H. E., and Von Glinlow, M. A., Small World, Isn't It? Personal Networks and lnfrastructural Development. International Technopolis Conference, Linked Infrastructure-Smart Cities, Fast Systems, Global Networks, San Francisco, CA, May 20-22, 1990. Aldrich, H. E., Reese, P. R., and Dubini, P, Women on the Verge of a Breakthrough?: Networking among Entrepreneurs in the United States and Italy. Entrepreneurship and Regional Development (4) (1989): 339-356. Allen, T. J., Communications Networks in R&D Laboratories. R&D Management 1 (1) (1970): 14-21. Bannock, G., and Gray, C, The Growing Small Business in Great Britain: Trends in Quarterly Profiles of Growing Small Firms 1984-88. Piccola Impresa (1989) 3: 3-25. Berry, W. D., and Feldman, S., Multiple Regression in Practice,Sage Publications, Newbury Park, CA. 1985. Birley, S., and Norburn, D., Small Versus Large Companies: The Entrepreneurial Conundrum. Journal of Business Strategy (1) (Summer 1985): 81-87. Birley, S., New Ventures and Employment Growth.Journal oJBusiness Venturing 2 (1987): 155-165. Birley, S., Cromie, S., and Myers, A.. Entrepreneurial Networks: Their

New Venture Growth and Personal Networks

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49

Appendix 1. Network Variables in the Study Hypothesis 1: Size of Social and Professional Networks Size of Network TRADE SOCIAL PROF NETWORK NETWCOMM

Network Content CUSTOMER MRKTINFO COMPINFO ACCESS CONTACTS WORDOFM ADVICE PRODIDEA INVESTOR

Number of memberships in trade organizations Number of memberships in social organizations Number of memberships in professional organizations Entrepreneurs total network-"With approximately how many people have you discussed various aspects of your present company during the last six months?" Commercial relafionships-"How many of these people have a commercial relationship with your firm?" "To what extent have the people you talked to contributed to the following aspects of your business?a Contacts with new customers Market information Computer information Access to distribution channels New contacts Advertising by word of mouth General advice Product and service development Assistance in obtaining business loans or investors

Hypothesis 2: Size of "Global" Network TRAVEL

The approximate number of hours per month spent on journeys outside the country in relation to the development and maintenance of new and existing customers

Hypothesis 3: Establishing and Maintaining the Network NEWCUST/OLDCUST NEWSUPPL/OLDSUPPL NEWINVES/OLDINVES NEWTIME/TIMEOLD INITIATI

Hours per Hours per Hours per Hours per Percent of

week making contact with new/old customers week making contact with new/old suppliers week making contact with new/old investors week creating/maintaining other contacts new contacts taking initiative for contact

Hypothesis 4: Delegation of Networking MONOPOLY

Proportion of contacts knowing other people in firm

Hypothesis 5: Diversity in Personal Contact Network (PCN) STRANGER NETW

Percentage of PCN who do not know each other Composite measure of size of secondary networks

Hypothesis 6: Intensity of Relationships with PCN FREQUENC KNOWN

Composite measure of hours per month communicating with PCN Composite measure of years known PCN

Scale ranged from 1 (not at all) to 5 (to a very large extent).

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