Social networks across theSME organizational lifecycle

James W. Peltier and G.M. NaiduDepartment of Marketing, University of Wisconsin-Whitewater, Whitewater,

Wisconsin, USA

Abstract

Purpose – The purpose of this paper is to investigate how social networks evolve as small businessenterprises transition across the organizational lifecycle. It aims to give attention to how socialidentities of small business owners impact social networks and whether social networks improveorganizational performance in small firms.

Design/methodology/approach – A sample of small to medium-sized enterprise (SME) ownersemploying less than 500 employees was drawn from the local directory of businesses in two Indiancities. A total of 297 SME owners participated in the study, for a response rate of 85.6 percent.

Findings – The findings show that social networks for small businesses change as firms transitionfrom startup to growth and beyond. Personal networks were most important during startup, withother social networks growing in contact frequency and importance over time. The findings also showthat small business owners can be classified along network preferences and that social networks leadsuperior performance.

Research limitations/implications – The study focused on a limited set of performance indices.Future research should assess a wider set of organizational metrics and should investigate granularaspects of transitional networks.

Practical implications – The findings suggest that small business owners cannot adhere to thestatus quo and must instead be willing to change business practices as their organizations evolveacross the organizational lifecycle.

Originality/value – The study provides evidence that small business owners use different types ofsocial networks and that the range and value of the strategic advice that they receive differ as theirorganization unfolds over time. The research contributes to the literature by showing that socialnetworks and entrepreneurial learning practices are not static, and instead must be viewed in terms ofdynamic decision making needs and processes.

Keywords Social networks, Social identities, Entrepreneurs, Small business owners,Organizational lifecycle, Performance, Small to medium-sized enterprises

Paper type Research paper

IntroductionThere is a growing consensus that forming, nurturing, and managing internal andexternal relational networks are critical to the success of innovative and small businessventures ( Jones and Holt, 2008; Ngugi et al., 2010; Street and Cameron, 2007). Broadlydefined, relational networks represent the aggregation of all interactions throughmembership in formal organizations and relational encounters entrepreneurs createand nurture with suppliers, distributors, consultants and customers, or any of a widerange of other social contacts, including friends, family, and acquaintances (Dodd andPatra, 2002). Through cooperative interactions with varied types of social networkmembers, small businesses place themselves in a better position to develop effectivestrategies and tactics needed for thriving in an ever-changing global landscape (Leeand Jones, 2008; Molina-Morales and Martınez-Fernandez, 2010). Combined, social

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Journal of Small Business andEnterprise DevelopmentVol. 19 No. 1, 2012pp. 56-73q Emerald Group Publishing Limited1462-6004DOI 10.1108/14626001211196406

networks are valuable components of entrepreneurial learning and can enhance thesuccess of small businesses through the creation of organizational assets in the form ofhuman, market, financial, and technological capital (Fuller-Love and Thomas, 2004;Jack et al., 2008)

Although social networking is receiving increased attention in the small businessand entrepreneurship literature, major shortcomings exist with regard to thetransitional nature of entrepreneurial learning networks over time (Hampton et al.,2009; Littunen and Niittykangas, 2010; Zhang et al., 2008). Virtually silent is researchthat examines the evolutionary nature of social networks in terms of their importanceand contact frequency across the organization lifecycle, and specifically from start-upand/or acquisition through growth (Elfring and Hulsink, 2007; Klyver, 2008; Xu et al.,2008). A greater understanding of these networking needs will extend the literature byhighlighting how effective small business are at transitioning from launch to growth,and how social networks may benefit this transition (Hampton et al., 2009; Hite, 2005;Lechner and Dowling, 2003).

Also of significance, research is increasingly questioning whether entrepreneurshave “social identities” (Watson, 2009) and whether these social orientations impact thefrequency and effectiveness of different types of social network relationships (Shaw,2006). Although a steady stream of research has emerged on the personalitycharacteristics of entrepreneurs, relatively unexplored is the extent to which anentrepreneur’s social orientation moderates the degree of information sharing thatexists within and across SMEs (Bowey and Easton, 2007) and the extent to which smallbusinesses seek input from associates within and external to their organization(MacDonald et al., 2007; Molina-Morales and Martınez-Fernandez, 2010). Given thegaps in the social networking and entrepreneurship literature, four research questionshave emerged:

(1) How do social networks and entrepreneurial learning mechanisms evolve assmall business enterprises transition from start-up/acquisition to growth?

(2) Do small business owners differ in their configurations of social identities?

(3) How do the social identities of small business owners impact social networks?

(4) Do social networks improve profitability and organizational performance insmall firms?

Research framework: social network theoryThe social network approach to asset creation is founded on the principle that therelationships entrepreneurs have with others is a key resource for creating andbuilding business ventures (Aldrich et al., 1987; Carsrud and Johnson, 1989). Structuralsocial capital helps entrepreneurs access information, knowledge, resources andfinancing by participating in networks rich in structural holes (Casson and DellaGiusta, 2007). Although not meant to be exhaustive, social networks have beendescribed in terms of three types of relational interactions (see Johannisson, 1995). Thefirst are exchange networks, made up of an organization’s set of commercialrelationships, most notably associated with vendors and customers. Communicationnetworks encompass the set of organizations and individuals from which theentrepreneur could receive support in terms of business contacts and knowledgeneeded for making sound business and financial decisions and could include

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consulting firms, financial advisors, trade associations, and other sources of expertise(Klyver, 2008; Palakshappa and Gordon, 2007). Lastly, personal networks may exist inthe form of ongoing communications with family members, relatives, friends andacquaintances. Exchange and communication relationships can be viewed asformal/external networks, while family and personal relationships can beconceptualized as informal/internal networks (Mackinnon et al., 2004; Sequeira et al.,2007). Although in the current research we conceptualize social assets in terms ofexchange, communication and personal networks, social networks often have fuzzyand overlapping boundaries with varying degrees of multi-plexity, leading tocontinuous rather than a finite number of relationships, all of which could run inmultiple directions and encompass different qualities and values (Mitchell, 1969).

Traditionally, social network theory has been applied to entrepreneurialorganizations in two ways – to illustrate that an entrepreneur’s social network ofcontacts allows access to resources that are not possessed internally, and todemonstrate that relational networks enhance economic exchange (Anderson and Jack,2002). When a network relationship is entrenched within a social relationship anddirectly impacts an entrepreneur’s decision making process, the linkage is deemed tobe “relationally embedded” (Uzzi, 1996). As Staber and Aldrich (1995) state,“sociologists now take as axiomatic the proposition that economic action, includingentrepreneurial behaviour, is embedded in interpersonal social networks” (p. 442).Granovetter (1985) argues that all relationships are socially embedded and that thedegree of embeddedness has a direct and positive impact on economic actions andperformance.

Research hypothesesSocial network theory and business transitionsResearch on the transitional and temporal nature of relational networks is scarce ( Jacket al., 2008). Transitional networking can be framed in part on the notion of “networkculling” (Larson and Starr, 1993), which has been conceptualized as an iterative processinvolving the exploration, evaluation and selection of network partners. This cullingprocess underscores the dynamic nature of social networks, and particularly withregard to the evolution of one’s network over time as new relationships are added, assome are dropped, and some modified (Bowey and Easton, 2007). This temporalevolution of networks and network ties has important ramifications for understandinginnovative decision making involving opportunity assessment, resource utilization,and the governance of launching, growing, and maintaining small firms (Miller et al.,2007). In some instances, network relationships create organizational assets oftenreferred to as social capital (Burt, 1992). Social capital is amassed when entities in thenetwork establish relationships, relationships that build trust and expectations offairness and reciprocity (Grabher, 1993; Granovetter, 1985). The empirical andtheoretical treatment of business networking has paid little attention to understandinghow complex sociological ties or attachments develop among small businesses orwithin small communities where an increasing number of businesses fail (Cope et al.,2007).

The creation, modification, and elimination of social networks over time areimportant areas of inquiry (Bowey and Easton, 2007). Hite and Hesterly (2001) contendthat emerging firms might rely more heavily on close, relationally embedded ties

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(personal networks) early on in their organizational lifecycle. This reliance on closelyembedded relational networks might be traced in part to higher levels of trustassociated with these informational exchange partners (Mackinnon et al., 2004). Familyand friends might thus have their most important impact during the planning stages ofa potential venture (Greve and Salaff, 2003). Later, as the business transitions into agrowth mode and beyond, the entrepreneur might be more inclined to extend the rangeand depth of its relational linkages in the form of exchange (vendor and customerresearch) and communication (consultants, financial advisors, trade associations, etc.)networks (see Hite and Hesterly, 2001). As a consequence, the characteristics ofnetwork ties may change and these changes may affect opportunity discovery,resource access and mobilization (e.g. Hite, 2003; Uzzi and Gillespie, 2002). Forexample, Larson and Starr (1993) examined the evolution of network ties in emergingfirms and suggested that even newly established work related ties may evolve tobecome more relationally-embedded over time as social exchanges are layered over thebusiness relationship, thus increasing the influence of the tie on the firm (Granovetter,1985; Uzzi, 1996; Uzzi and Gillespie, 2002). Likewise, Lechner and Dowling (2003) foundthat the mix of networks evolve as firms develop, with the relative importance of morepersonal social networks decreasing over time in favor of more external relationships.

Logically, the preceding discussion suggests that a small business owner’s socialidentity is not necessarily static and might evolve as the organization proceeds throughthe organizational life-cycle. This is consistent with Hall’s (2002) identity-changeprocess model that implies that an entrepreneur’s social identity might be altered overtime as organizational goals change along with the effort needed to succeed in dynamicand competitive markets. As such, as the decision situation changes so too can anindividual’s social identity in response to the changing context in which these decisionsare made (Tajfel and Turner, 1986). There is some expectation that although relativeimportance might deviate over time, entrepreneurs with a greater family- and/orpersonally-based orientation will utilize personal and family-oriented networks moreacross all stages of the organizational life-cycle and those with a more externalorientation will always form relationships with exchange and communication socialnetworks (Greve and Salaff, 2003).

Based on this review, we posit the following:

H1. Advice from personal networks (family and friends) will be the most usedsocial network during the start-up stage of the organizational lifecycle.

H2. Advice from personal networks (family and friends) will have the highestperceived value during the start-up stage of the organizational cycle.

H3. The frequency advantage of advice received from personal networks (familyand friends) over other types of social networks will decrease from thestart-up to the on-going stage of the organizational life-cycle.

H4. The value advantage of advice received from personal networks (family andfriends) over other types of social networks will decrease from the start-up tothe on-going stage of the organizational life-cycle.

H5. The frequency of advice and value of advice received from exchangenetworks (customers and suppliers) will increase from the start-up to theon-going stage of the organizational life-cycle.

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H6. The frequency of advice and value of advice received from communicationnetworks (consultants, financial advisors, competitors) will increase from thestart-up to the on-going stage of the organizational life-cycle.

H7. The frequency and value of advice received from personal networks(family/friends) will decrease from the start-up to the on-going stage of theorganizational life-cycle.

Social network theory and social identitiesConsistent with emerging research by Down (2006), and Peltier et al. (2009, 2012),entrepreneurs’ “self-identity” is expected to play a role in the internal and externalorientation that they take in making business decisions. Hite (2003) contends that thenature, scope and importance of relationally embedded linkages for solving businessproblems may differ based on the interpersonal characteristics of an entrepreneur andthe social setting in which the interactions take place. In this way, the type of “socialidentity” employed by an entrepreneur may play a major role in impacting opportunitydiscovery and resource mobilization (Hite, 2005; Larson and Starr, 1993). Moreover, theinterdependence of individuals and groups in the social network and that these socialmembers share common goals are expected to be key aspects of external socialidentities (Ellemers and Bos, 1998).

Watson (2009) contends that an entrepreneur’s social identity will impact the degreeand value of information seeking and sharing (MacDonald et al., 2007). Pertinent tosocial networks, information access comes from multiple sources, including pastexperience, customers and competitors, and other players in the social environment.Information accessibility and fit thus determine which social groups (if any) becomesalient and thus influence the frequency and value of that information and the extent towhich one’s social identity is impacted (Ullrich et al., 2007). As such, a key ingredientfor capturing social identities is the ability to categorize small business owners withregard to their preferences for varied network relationships, and specifically, exchangenetworks, communication networks, and personal networks (Sequeira et al., 2007).Importantly, the information access process undertaken is thus a function of whethersmall business owners define themselves in terms of a more personal or social identity,and when an external social identity is prevalent, which type of social network servesto guide behaviour (Haslam et al., 2003).

H8. A family/personal-oriented social identity will result in greater use andperceived value of personal networks at all stages of the life-cycle; and anexternal-focused social identity will result in greater use and perceived valueof exchange and communication networks at all stages of the life-cycle.

Social identities, entrepreneurial learning and economic performanceDespite the increasing consensus that entrepreneurs and small businesses must formnetworks to survive, relatively few empirical studies have investigated the linkbetween an entrepreneur’s social identity and firm performance (Watson, 2009).Granovetter (1992) argues that socially embedded relations are also closely linked toproductivity and economic performance vis-a-vis the ability to make better decisionsthrough information sharing and tactic knowledge exchange, and particularly indecision environments containing high levels of task complexity and uncertainty. We

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argue that regardless of the social identity type in which entrepreneurs fall, “social”entrepreneurs will outperform “non-social” entrepreneurs. Linking back to the notionof “social capital”, Casson and Della Giusta (2007) contend that the “capitalized value”of social networks contribute to future economic performance, a view supported byMolina-Morales and Martınez-Fernandez (2010) and Zhang and Fung (2006).

(1) H9.Firms operated by small business owners characterized as having astronger internal or external social identity will outperform firms operated byindividuals with a weaker social identity.

MethodsSampleRespondents were selected from the local directory of businesses and chosen toparticipate by a systematic random sample of firms employing less than 500employees (most were much smaller than 500). Some completed the survey while theinterviewer awaited but the majority of the respondents asked the surveyor to comeand pick it up one or two days later. The interviewers were female faculty from localeducational institutions, which had a great impact on the willingness to participate inthe study. A total of 312 questionnaires were returned. Given this face-to-face datacollection approach and that the sponsoring universities were identified, nearly all ofthe surveys had complete data. Of the 312 returns, 15 were removed because of missingdata pertaining to the performance measures, for a final response rate of 85.6 percent.The profile of respondents is provided in Table I.

MeasurementsTo generate insight into social network usage, we asked the small business owners toindicate their level of Contact Frequency (five-point scale: never, once in a while,sometimes, frequently, very frequently) and Value of Information Received from thesecontacts (five-point scale: no value, slightly valuable, some value, valuable, veryvaluable) for the three types of Social Networks (personal network – family/friends;exchange network – current/potential customers, suppliers; and communicationnetwork – business/financial consultants, non-competing businesses, competingbusinesses) at two points in time along the organizational life-cycle (start-up/planningstage and current/ongoing strategic planning stage).

To assess social identity, respondents indicated their level of agreement (five-pointscale: strongly disagree to strongly agree) with 28 statements, which were then used tocluster respondents to serve as independent variables for H8 and H9 (see Table II).Using a five-point comparative scale (inferior to competition, below average, average,above average, superior to competition), four Comparative Firm PerformanceMeasures were also collected (sales growth, market share growth, profit growth, andoverall success of business).

Cluster analysisWe were also interested in determining whether the social identity of the respondentsimpacted the frequency and value of the advice they receive from personal, exchange,and communication networks (H8). To test H8 we first conducted a K-means clusteranalysis utilizing the 28 question instrument measuring respondents’ perceptions ofdifferent types of social networks and how they apply to their business/themselves.

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Two, three, and four cluster models were conducted, with the three-clustersegmentation model providing the cleanest separation in the segments. Table IIshows our three-segment solution and the mean scores for each of the social identitystatements (all significant at p , 0:01). The three clusters that emerged were namedFamily/Personal Social Identity, External Social Identity and Weak Social Identity.What is first evident from Table II is that entrepreneurs with an External SocialIdentity (n ¼ 146) make up the majority of the respondents, followed byFamily/Personal Social Identity (n ¼ 85); and Weak Social Identity was the smallestgroup of entrepreneurs (n ¼ 66). In this regard, 78 percent of the respondents seem toseek some type of relational networking partners, either family/personal networks orexternal networks.

Findings and discussionPrior to conducting tests of our hypotheses, and to determine whether the variousfirmographics could confound our tests, for H1, H2, H3, H4, H5, H6 and H7 wecompared the frequency/value of advice received from social networks based on

Characteristic Profile (%)

How business startedStart-up 72.3Acquired from family 22.7Acquired externally 5.0

When business was startedWithin ten years 51.611-15 years 25.815 þ years 22.6

Family involvement in businessSpouse 22.6Parent 25.6Children 15.8

Age, 34 20.235 35.445-54 30.655 þ 12.8

EducationHigh school or less 4.1Some college/tech 11.5Graduated college 47.2Post graduate 37.2

Company sales (Euros), 73,000 26.373,000-217,999 27.0218,000-364,999 11.5365,000-730,000 18.4. 730,000 16.8

Table I.Profile of respondents

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Social identity statements

Family/personalidentity(n ¼ 85)

Weak socialidentity(n ¼ 66)

Externalidentity

(n ¼ 146)

I seek business advice from many differentpeople

3.24 2.61 3.71

My family/friends play a large role in mybusiness decisions

4.14 2.91 3.42

My family/friends are important supportgroups

4.38 3.48 3.79

My family agrees with my businessdecisions

4.04 3.55 3.82

My family really cares about the success ofmy business

4.48 3.74 4.08

My parents have been a major influence inmy business life

3.96 2.59 3.13

I am often in conflict with my familyregarding my business

1.89 2.36 2.49

I don’t trust the advice that I receive fromnon-family members

2.35 2.88 2.36

I am very secretive so competitors won’tknow my strategies

3.01 3.24 3.49

My friends have often given me bad advice 2.15 2.53 2.49I have a strong network of businessacquaintances

3.35 2.91 3.92

I have a strong network of suppliers whohelp me make decisions

3.28 2.61 3.88

I have a strong network of experts who helpme make decisions

3.04 2.45 3.85

I spend a lot of time developing a strongrelationship network

3.55 2.95 3.87

Advice from non-family members is betterthan from family

2.20 2.64 3.16

I share my business advice with others 3.22 2.68 3.66Business organizations are important forsharing ideas

3.76 3.08 3.97

I have a high tolerance for risk 3.48 3.03 3.90Others would describe me as a team player 3.67 3.29 3.90I have open communications with externalbusiness members

3.71 3.21 4.08

I am often in conflict with members of myrelationship network

2.16 2.36 2.66

I don’t like to work in teams 1.96 2.77 2.16I am a competitive person 3.80 3.41 4.07Others like to work with me 3.91 3.52 4.15Many people seek my advice 3.88 3.68 4.21I don’t look to other businesses to see how Ican improve mine

1.97 2.50 2.01

My family is an important part of thesuccess of my business

4.36 3.71 3.62

I trust the advice that my family gives me 4.19 3.65 3.65

Table II.Social identity segments:

cluster centers andone-way ANOVAS of Sig

means ( p , 0.05)

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whether the firm was started vs. acquired (independent sample t-test) and the numberof employees, firm revenue, and when started/acquired the firm (one-way anova). ForH8-H9 we compared social identity segments across these same groups as well. Fewsignificant differences existed across the groups, increasing confidence thatfirmographics will not confound our hypothesis testing procedures.

Specific to H1, Table III provides the mean frequency scores for each type ofstrategic advice sought during the start-up/planning stage of the organizationallifecycle. A one-tailed paired t-test was conducted to test H1 that family/friends wouldbe most frequently sought for strategic advice during the start-up/planning than allsources of advice. As expected, the frequency of strategic advice received fromfamily/friends (mean ¼ 2:93) during the start-up/planning stage of the organizationallifecycle was significantly higher than all of the other networks types, providing strongsupport for H1.

Table III also presents the “value scores” of the advice received during thestart-up/planning stage of the organizational life-cycle. A one-tailed paired t-test wasconducted to test H2 that family/friends would provide the most valuable adviceduring start-up/planning. As shown in Table II, the mean value score of the strategicadvice provided by family/friends (mean ¼ 2:23) was significantly higher than all ofthe other network types except current/potential customers (all other relationshipssignificant at p , 0:01), showing strong support for H2.

H3 investigated the frequency of strategic advice sought from network memberswhen transitioning from start-up to current/on-going operations of the organizationallife-cycle. Specifically, it was hypothesized that the frequency advantage of strategicadvice received from personal networks (family/friends) relative to other types of advicewould decrease as organizations transitioned out of the start-up stage to on-goingoperations. As shown in Table IV, as expected, no statistical difference was found for thefrequency of advice received from personal networks and that received fromcurrent/potential customers, business/financial consultants, and suppliers (becausedirectional hypotheses were not made, a one-tailed paired t-test was used in theanalysis). However, significantly more frequent strategic advice was received from allfour networks than from competing and non-competing businesses (p , 0:001).

H4 examined the value of strategic advice across the organizational lifecycle.Specifically, H4 hypothesized that the value advantage of strategic advice given by

FrequencyStart-up/planning

ValueStart-up/planning

Family/friends 2.93 * 3.23 * *

Current/potential customers 2.68 3.13Business/financial consultants 2.71 3.01Suppliers 2.70 2.92Competing businesses 2.20 2.52Non-competing businesses 2.02 2.16

Notes: All comparisons were tested using one-tailed paired sample t-tests. *Family/friendssignificantly more frequent than the other network types (all significant at p , 0.05 or better).* *Family/friends significantly more valuable than all network types except current/potentialcustomers ( p , 0.01)

Table III.Frequency and value ofstrategic advice (H1 andH2): one-tailed pairedt-tests of start-up/planning stage oforganizational life-cyclerank-ordered by valueof advice

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personal networks (family/friends) relative to other network members would decreaseas organizations moved from the start-up to on-going stage of the organizationallife-cycle. Using one-tailed paired t-tests, Table IV provides support for H4 in twoways. First, the value of strategic advice received from current/potential customersduring the current/on-going stage of the organizational lifecycle was significantlygreater (p , 0:01) than for personal networks, suggesting a transition away from thevalue of personal sources to critical information sought from target markets. Second,the fact that no significant difference was found between the value of advice receivedfrom family/friends and business/financial consultants, and between family/friendsand suppliers, further highlights the decreasing importance of personal sources ofinformation as organizations transition out of the start-up stage. However, advice frompersonal networks continues to be more valuable during the current/on-going stages ofthe organizational lifecycle than that received from competitors (p , 0:01).

H5 and H6 hypothesized that the frequency and value of strategic advice receivedfrom exchange networks (H5) (suppliers and customers) and communication networks(H6 (consultants, financial advisors, and competitors) will increase from thestart-up/planning stage to current/on-going operations. H7 predicted a drop in the(a) frequency and value of strategic advice received from personal networks(family/friends) when moving from start-up/planning to current/on-going operations.To test these hypotheses, one-tailed paired t-tests compared the mean frequency andvalue scores for each of the network members during the start-up/planning stage wascompared to those found for the current/on-going stage of operations.

Table V shows general support for H5 regarding exchange networks. Specifically,both the frequency and value of strategic advice received from current and potentialcustomers increased from start-up to current/ongoing operations. Although thefrequency of advice received from suppliers increased across the organizationallifecycle, its value did not.

H6, which involved the transitional nature of advice received from communicationnetworks, received moderate support. Specifically, both the frequency and value ofadvice increased for business/financial consultants. Although the frequency of advice

FrequencyCurrent/on-going

ValueCurrent/on-going

Current/potential customers 2.95 * 3.26 * *

Business/financial consultants 2.98 3.12Family/friends 2.83 3.02Suppliers 2.89 2.96Competing businesses 2.35 2.55Non-competing businesses 2.10 2.21

Notes: All comparisons were tested using one-tailed paired sample t-tests. *(a) No significantdifference between Family/Friends and Current/Potential Customers, Business/Financial Consultants,and Suppliers. (b) All four are significantly more frequent than Competing and Non-CompetingBusinesses. * *(a) Current/Potential Customers are now significantly more valuable than Friends/Family ( p , 0.05). (b) Except for Business/Financial Consults (n.s.), Current/Potential Customersprovide significantly more value than the remaining network types ( p , 0.01). (c) No significantdifference between the value of Family/Friends and Business/Financial Consultants, and Suppliers. (d)Family/Friends continue to be more value than Competing Businesses and Non-Competing Businesses

Table IV.Frequency and value of

strategic advice (H3 andH4): one-tailed paired

t-tests of current/on-goingstrategic planning stage

of organizationallife-cycle rank-ordered by

value of advice

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65

Fre

qu

ency

Sta

rt-u

pF

req

uen

cyC

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ent

Ch

ang

eS

ig.

Val

ue

Sta

rt-U

pV

alu

eC

urr

ent

Ch

ang

eS

ig.

Exchange

networks

(H5

)C

urr

ent/

pot

enti

alcu

stom

ers

2.68

2.95

0.27

0.00

13.

133.

260.

130.

05S

up

pli

ers

2.70

2.89

0.19

0.00

12.

922.

960.

04n

.s.

Com

munication

networks

(H6

)C

omp

etin

gb

usi

nes

ses

2.20

2.35

0.15

0.05

2.52

2.55

0.03

n.s

Non

-com

pet

ing

bu

sin

esse

s2.

022.

100.

008

n.s

2.16

2.21

0.05

n.s

Bu

sin

ess/

fin

anci

alco

nsu

ltan

ts2.

712.

980.

270.

001

3.01

3.12

0.11

0.05

Personalnetworks

(H7

)F

amil

y/f

rien

ds

2.93

2.83

20.

10.

053.

233.

022

0.21

0.00

1

Table V.Network type changescores: one-tailed pairedt-tests of frequency andvalue of strategic advice

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received from competing businesses increased from start-up to current/ongoingoperations, no significant difference was found for the value of this advice. Lastly, thefrequency and value of advice from non-competing businesses remained unchangedand little used across the organizational lifecycle.

The transitional nature of strategic advice from family/friends was alsoinvestigated (H7). As shown in Table V, the frequency and value of strategic advicereceived from family and friends decreased as the organization moved from thestart-up to the current/ongoing stage of the organizational lifecycle; providing strongsupport for H7.

H1, H2, H3, H4, H5, H6 and H7 all investigated various social networkrelationships and the transitioning of the frequency and value of these social networksacross the organizational life-cycle. Individually each hypothesis was supported,combined they help validate the premise that social networks evolve over time (Boweyand Easton, 2007; Granovetter, 1985; Larson and Starr, 1993; Uzzi, 1996; Uzzi andGillespie, 2002). Beyond the broad notion of evolving networks, the findings alsosupport Hite and Hesterly (2001), Greve and Salaff (2003), and Lechner and Dowling(2003) that the mix of networks shift away from personal social networks during earlystages of the organizational life-cycle to include a wider range of external relationshipsas the company expands over time.

As would be expected, Table VI provides general support for H8 thatFamily/Personal social networkers utilize and place the greatest value on personalnetworks across the organizational lifecycle than the other segments (seeitalicized/means). Similarly, External social networkers utilize and value exchangeand communication networks more than Family and Non-Networkers (Weak SocialIdentity) (see italicized/means). Of interest, both Family/Personal and Externalnetworkers have similar usage and value perceptions for advice provided by currentand potential customers during the on-going stage of the life-cycle, suggesting thatFamily/Personal Networkers shift some of their focus to customers as they movebeyond the start-up stage.

H8 provides support for the contention that small business owners can be classifiedinto social identify segments based on their need for and the use of personal andexternal network partners (MacDonald et al., 2007; Tajfel and Turner, 1986; Watson,2009), and particularly with regard to the frequency and value of information soughtfrom these network partners (Ullrich et al., 2007). Moreover, the findings suggest thatsmall business owners can be grouped by their preferences for exchange,communication, and personal networks (Sequeira et al., 2007) and that these specificnetworks guide their decision-making behaviour (Haslam et al., 2003).

Lastly, H9 predicts that firms operated by entrepreneurs with an internal(family/personal) or external social identity will outperform firms operated byentrepreneurs with weaker social identities. To test H9, one-tailed independent samplet-tests were conducted to compare entrepreneurs with stronger family/personal socialidentities to those with weak social identities, and entrepreneurs with stronger externalsocial identities to those with weak social identities. As shown in Table VII, H9 wassupported for three of the four firm performance measures, including market sharegrowth, profitability growth, and overall success of the business. These tests providedstrong support that as compared to having a weak social identity, having either afamily/personal social identity or an external identity contributes to firm performance.

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Our findings for H9 support and extend the recent work of Watson (2009) andHomburg et al. (2009) which suggest that having a social identity, whether personal orexternal, leads to superior performance as compared to small business owners withweak social identities. Superior performance associated with having a social identity

Organizational life-cyclestage

Family/personalidentity

Weak socialidentity

Externalidentity Sig.

Frequency of advice: start-up/planningFamily/friends 3.66 2.51 2.68 0.001Current/potential customers 2.58 2.40 2.86 0.05Non-competing businesses 1.85 1.85 2.19 0.05Competing businesses 2.18 1.90 2.34 n.s.Suppliers 2.64 2.20 2.94 0.001Business/financialconsultants

2.55 2.26 3.01 0.001

Value of advice: start-up/planningFamily/friends 3.94 2.83 3.00 0.001Current/potential customers 3.27 2.85 3.17 n.s.Non-competing businesses 1.99 1.86 2.38 0.01Competing businesses 2.58 2.04 2.68 0.01Suppliers 2.95 2.53 3.07 0.05Business/financialconsultants

2.85 2.64 3.25 0.01

Frequency of advice: current/ongoingFamily/friends 3.43 2.52 2.62 0.01Current/potential customers 3.10 2.53 3.04 0.01Non-competing businesses 1.96 1.86 2.29 0.01Competing businesses 2.41 1.90 2.50 0.001Suppliers 2.93 2.30 3.12 0.001Business/financialconsultants

2.98 2.45 3.21 0.01

Value of advice: current/ongoingFamily/friends 3.84 2.33 2.86 0.000Current/potential customers 3.35 3.02 3.31 n.s.Non-competing businesses 2.15 1.98 2.34 n.s.Competing businesses 2.71 2.27 2.58 n.s.Suppliers 3.05 2.18 3.24 0.001Business/financialconsultants

3.12 2.43 3.41 0.001

Table VI.One-way ANOVAS offrequency and value ofadvice across socialidentity segments

Performance measureFamily/personal

identityWeak social

identity Sig.Externalidentity

Weak socialidentity Sig.

Sales growth 3.75 3.67 ns 3.73 3.67 nsMarket share growth 3.64 3.38 0.05 3.63 3.38 0.05Profitability growth 3.72 3.42 0.05 3.70 3.42 0.01Overall success ofbusiness

3.99 3.59 0.001 3.86 3.59 0.01

Table VII.One-way ANOVAS ofmean firm performanceindices

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regardless of its internal-external orientation is in line with Casson and Della Giusta’s(2007) contention that social networks are organizational assets. These assets are likelythe result of better decision-making through the acquisition of tactic knowledge notpresently possessed by the small business owner (Granovetter, 1992). In agreementwith (Mackinnon et al., 2004), the fact there was a clear delineation in terms of the socialidentity segments for categorizing small business owners contributed to the ability todetect performance effects.

ConclusionWe reported the findings from a study of 297 Indian entrepreneurs regarding theextent and value of strategic advice they received from personal, exchange andcommunication networks as they move along the organizational lifecycle and how theuse/importance of entrepreneurial learning networks change as the organizationtransitions along the organizational lifecycle. Each of our transitional hypothesesreceived support, suggesting that it is important to understand not only the types ofsocial networks that entrepreneurs use, but that the range and value of the strategicadvice that they receive differ as their organization unfolds over time. In this regard weprovide clear evidence that social networks and entrepreneurial learning practices arenot static, and instead must be viewed in terms of dynamic decision making needs andprocesses.

Given that our study was motivated by the need to better understand the nature andscope of social networks as the goals, needs and actions of a small business aretransformed over time (see Hampton et al., 2009), we extend the literature by providingempirical evidence that social networks and social identities are evolutionaryconstructs. Dating back to the early work of Mitchell (1969), we also contribute togrowing literature attempting to develop insight into the fuzzy nature of socialboundaries and how small business owners extend their networks to acquire theneeded knowledge to successful move their business along the organizational lifecycle.

Because our study focused primarily on the frequency and value of various networkrelationships, future research should investigate more granular aspects of transitionalnetworks across all types of social and non-social relationships, including personal andbusiness relationships. Research is particularly needed to assess network andorganization transitions based on evolving goal structures (Ullrich et al., 2007),opportunity discovery and assessment (Miller et al., 2007), financial and human capitalaccess and mobilization (e.g. Hite, 2003; Uzzi and Gillespie, 2002), and any in a widevariety of specific marketing (Frazier and Huddleston, 2009) or other function-basedproblem solving strategies and tactics (Cope et al., 2007). Although our study focusedprimarily on for-profit organizations, it would be interesting to investigate whether theneed for and transition of social networks differ for non-profit and/or socialentrepreneurs. This line of research would help to further our understanding of the useand importance of exchange, communication and personal networks across differenttypes of organizations and different sets of organizational objectives.

We also added to the literature by showing that entrepreneurs have social identities,ones that form with priority given to family and personal network relationships ortoward more external relational contacts. Importantly, we also provided evidence thatboth types of social identities contribute equally to firm performance and that having asocial identity leads to greater economic success over those organizations that fall

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outside of these two internal/external orientations. Given that a limitation of our studyis that we focused on a limited set of performance indices, future research shouldinvestigate a wider set of organizational metrics (Watson, 2009). Especially importantis research that examines the relationship between social networks and performanceindices at various stages of the organizational and entrepreneurial lifecycle (Uhlaneret al., 2007). As with the needed focus on more granular network orientations,performance effects also need to be expanded through the inclusion of more advancedstatistical models that parse out the impact that varied social networks and networkrelationships have on wide-ranging organization success indices (Homburg et al.,2009).

The fact that entrepreneurs differ in their entrepreneurial and network orientationand that these differences impact network utilization confirms the need to explore theseissues in greater detail. Research is especially needed to further our understanding ofhow social networks evolve over time, how the use of these social networks are affectedby varied organizational and situational factors, whether additional network segmentsexist, and any in a wide range of other areas that investigate profitability metrics andorganizational firmographics. We acknowledge that although quantitativetechniques/measures and large scale samples generalizing benefits, he findings tobroader populations, future research should incorporate deep probing techniques likecritical incident interviewing to develop a richer understanding of what actually takesplace as business transition across various stages of the organization life cycle(Watson, 2009).

From a strategic perspective, our findings contribute to the managerial literature byunderscoring the importance for small business owners to reach out fordecision-making information to any in a wide range of social network partners. Ourfindings suggest that small business owners cannot adhere to the status quo and mustinstead be willing to change business practices as their organizations evolve across theorganizational lifecycle. Research involving critical incidence interviewing is needed toprovide a richer framework for understanding the strategic evolution process.

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About the authorsDr James W. Peltier is a Professor of Marketing at the University of Wisconsin-Whitewater andprevious holder of the Irvin L. Young Chair of Entrepreneurship at UW-Whitewater. In additionto directing the creation of the entrepreneurship major at UW-Whitewater, Dr Peltier haspublished over 80 refereed articles, many on small to medium-sized enterprises and smallbusiness owners. James W. Peltier is the corresponding author and can be contacted at:Peltierj@uww.edu

Dr G.M. Naidu is Professor of Marketing (Emeritus) at the University ofWisconsin-Whitewater. In addition to publishing a extensive array of refereed journal articles,Dr Naidu was the founder of the Global Business Resource Center at UW-Whitewater. A centerdesigned to assist SMEs and entrepreneurs.

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