social capital2.pdf

The Impact of Human and Social Capitalon Entrepreneurs’ Knowledge ofFinance Alternativesjsbm_344 63..86

by Arnout Seghers, Sophie Manigart, and Tom Vanacker

Building upon prior research that demonstrates how the limited knowledge offinance alternatives of entrepreneurs may cause suboptimal finance decisions, thispaper examines how entrepreneurs’ human and social capital influence their know-ledge of finance alternatives. For this purpose, we use survey data from 103 Belgianstart-ups. Results demonstrate that entrepreneurs with a business education andentrepreneurs with experience in accountancy or finance have a broader knowledgeof finance alternatives. Having a strong network in the financial community isfurther positively associated with the knowledge of finance alternatives. However,generic human capital, including higher education, industry experience, and man-agement experience, is almost not related with the knowledge of finance alternatives.

IntroductionFinance is one of the necessary

resources required for new ventures toform and subsequently operate (Ang1992; Gilbert, McDougall, and Audretsch2006; Van Auken 2001). Finance deci-sions are hence key decisions made byentrepreneurs, which bear significantimplications for the operations, risk offailure, performance, and future growthpotential of ventures (Cassar 2004; VanAuken 2001). Traditional finance theory

resorts to the framework of perfectcapital markets (Modigliani and Miller1958). This framework assumes thatinformation is free and directly availableto all entrepreneurs, which allows entre-preneurs to make comprehensive financedecisions with wealth maximization astheir ultimate goal (Brealey and Myers2000). Moreover, in this perspective, thesupply and demand for finance are inequilibrium, which implies that all value-creating projects will find sufficientfinance. Contrary to this image portrayed

Arnout Seghers is Research and Teaching Assistant in the Department of Accounting andCorporate Finance at Ghent University, Gent, Belgium.

Sophie Manigart is Full Professor at Vlerick Leuven Gent Management School and at GhentUniversity, Gent, Belgium.

Tom Vanacker is Assistant Professor at Ghent University, Gent, Belgium.Address correspondence to: Sophie Manigart, Accounting and Corporate Finance, Ghent

University, Kuiperskaai 55 E, Gent 9000, Belgium. E-mail: [email protected].

Journal of Small Business Management 2012 50(1), pp. 63–86

SEGHERS, MANIGART, AND VANACKER 63

in traditional finance theory, entrepre-neurial ventures are often confrontedwith finance constraints and are not ableto raise sufficient outside finance neces-sary to conduct all their value-creatinginvestment projects (Heshmati 2001;Himmelberg and Petersen 1994;Hubbard 1998; Ullah and Taylor 2007).As a result, the growth of entrepreneurialventures is often constrained by internalfinance (Carpenter and Petersen 2002;Heshmati 2001).

Scholars studying finance constraintswithin ventures have largely stressedsupply-side arguments, thereby puttingthe decision-making process of investorsin the foreground (Mason and Harrison2002; Wright and Robbie 1998). Withinthis perspective, prior research mainlyfocused on the role of information asym-metries and transaction costs in explain-ing why investors may refrain frominvesting in value-creating entrepreneur-ial ventures (Berger and Udell 1998).Nevertheless, finance decisions may alsobe driven by demand-side factors, andmore specifically by the characteristics ofentrepreneurs. Research on demand-sidearguments, which puts the decision-making process of entrepreneurs in theforeground, is more limited but growingrapidly (Bates 1997; Cassar 2004;Coleman 2000; Scherr, Sugrue, and Ward1993; Van Auken 2005). Entrepreneursare the driving force of important deci-sions, and entrepreneurial characteristicsmay hence play a key role in explainingfinance decisions (Cassar 2004). Forexample, though traditional financeresearch assumes that value maximiza-tion is the overarching firm objective,entrepreneurs may want to pursue othergoals (Kotey and Meredith 1997;LeCornu et al. 1996; Sadler-Smith et al.2003) that may affect their financechoices. An important goal for manyentrepreneurs, for instance, is to retainfull control over their ventures, whichmight preclude them from raising equityfrom new shareholders such as venture

capital investors or business angels (Ang1992; Manigart and Struyf 1997; Norton1991; Sapienza, Korsgaard, and Forbes2003). Furthermore, some entrepreneurswith conservative personal values adoptreactive strategies emphasizing riskavoidance (Kotey and Meredith 1997),and hence such entrepreneurs mayrefrain from the use of financial debt.

This paper focuses on another entre-preneurial characteristic that may impactthe finance decisions of entrepreneurs,namely their knowledge of finance alter-natives. Traditional finance theoriesassume that all parties have full informa-tion, hence that entrepreneurs are fullyaware of the existence of all potentialfinance alternatives and their respectiveadvantages and disadvantages (Brealeyand Myers 2000). However, the assump-tion that information is free and widelyavailable may not hold in the context ofnew and small ventures (Gibson 1992;Holmes and Kent 1991; Van Auken2005). Indeed, entrepreneurs in thesenew and small ventures may havelimited access to information and skillsthat are necessary to understand theprocess of finance acquisition (Gibson1992; Van Auken 2005). This is empiri-cally supported by Van Auken (2001),who shows that entrepreneurs generallyhave a limited knowledge of financealternatives that hamper their ability toprice and negotiate investments. More-over, learning theory posits that indi-viduals who are not knowledgeable of acertain topic will not actively search toexpand their knowledge (Cohen andLevinthal 1990). Though information onfinance alternatives may be abundant forindividuals actively searching for it, aninitial knowledge gap will lead to arestricted set of finance alternatives con-sidered (Van Auken 2001). Overall, agood knowledge of finance alternativesis the basis for making good financialdecisions (Gibson 1992). Hence, evenfor entrepreneurs who do not need orwould be unable to raise certain finance

JOURNAL OF SMALL BUSINESS MANAGEMENT64

alternatives given the characteristics oftheir ventures, it may be important tobe knowledgeable about all financealternatives in order to make well-informed choices. After all, how canentrepreneurs know that they will beunable to raise particular finance alter-natives when they are not knowledge-able about these alternatives or aremisinformed about the characteristics ofthese alternatives?

The goal of this study is to expand thisstream of research by exploring whysome entrepreneurs have a higherknowledge of finance alternatives com-pared with others. This is relevant, giventhat a limited understanding of financealternatives is likely to be an obstacle tothe development of successful capitalacquisition strategies (Gibson 1992; VanAuken 2001, 2005). In this study, wefocus on the association between entre-preneurs’ human and social capital andtheir knowledge of finance alternatives.We propose and show that higher levelsof specific human and social capital—that is, more experience in accountancyor finance, business education, andknowledgeable networks in the financialcommunity—are associated with abroader knowledge of finance alterna-tives. However, more generic humancapital is almost not related to the know-ledge of finance alternatives. This offersan explanation as to why some entrepre-neurs are confronted with a strongerknowledge gap, potentially leading tosuboptimal finance decisions.

In the following section, the theoreti-cal arguments and hypotheses on theimpact of human and social capital on anentrepreneur’s knowledge of financealternatives will be developed. Next, theempirical strategy used to test thehypotheses will be explained; the dataand variables employed in this study arefurther described. Thereafter, the empiri-cal findings will be presented, followedby concluding remarks and avenues forfuture research.

Theoretical DevelopmentNumerous scholars have highlighted

the importance of taking entrepreneurialcharacteristics into account to more fullyunderstand finance decisions in youngand small ventures (Ang 1991, 1992;LeCornu et al. 1996; McMahon et al.1993). We focus on the relation betweenentrepreneurs’ human and social capitaland their knowledge of finance alterna-tives. This is important as prior researchdemonstrates how entrepreneurs’ knowl-edge of finance alternatives influencestheir finance behavior (Van Auken 2001).Though traditional finance theories gen-erally assume that decision-makers arefully aware of all finance alternatives andtheir characteristics, entrepreneurshipscholars argue that not all entrepreneurshave an equally broad understanding ofthe finance options that are available,which leads to a knowledge gap (Gibson1992; Holmes and Kent 1991; Van Auken2001). Entrepreneurs often lack detailedknowledge on finance alternatives,thereby limiting the set of financeoptions that they consider (Van Auken2001). This limited knowledge of financealternatives further hampers entrepre-neurs when negotiating and pricinginvestments and may result in entrepre-neurs being unsuccessful in raisingcapital or raising inappropriate levelsand combinations of capital (Van Auken2001, 2005). We draw upon human andsocial capital theory to theorize about therelationship between entrepreneurs’characteristics and their knowledge offinance alternatives. The conceptualframework behind the hypotheses issummarized in Figure 1.

Prior research demonstrates how anentrepreneur’s human capital andfinance strategies are linked. First,human capital is positively related withthe wealth of entrepreneurs. Hence,entrepreneurs with more human capitalcan use more of their personal fundsto mitigate their venture’s finance


constraints (Holtz-Eakin, Joulfaian, andRosen 1994; Lindh and Ohlsson 1996).Second, the human capital of entrepre-neurs serves as a quality signal to exter-nal investors. This is especially valuablein an environment with high levels ofinformation asymmetry, as it increasesthe probability that investors will providefinancial resources to uncertain entrepre-neurial ventures (Hallen 2008). Botheffects explain why ventures establishedby entrepreneurs with higher humancapital generally have less bindingcapital constraints (Astebro and Bern-hardt 2005; Hsu 2007). We argue that thehuman capital of entrepreneurs may notonly be associated with their personalwealth or quality signals but also withtheir knowledge of finance alternatives.

Human capital theory states thatentrepreneurs with a greater humancapital stock will outperform their lessendowed counterparts (Becker 1975).The accumulated knowledge of entrepre-neurs is likely to provide them withsuperior cognitive abilities that makethem more productive and efficient in a

range of start-up activities includ-ing financial decision-making (Alsosand Kolvereid 1998; Van Auken 2005;Westhead, Ucbasaran, and Wright 2005).Entrepreneurs with more human capitalare therefore expected to be moreknowledgeable about finance alterna-tives and as such generate financestrategies that are more elaborated andfine-tuned to their business and personalneeds (Van Auken 2005).

Following prior studies, we distin-guish between generic and specifichuman capital (Becker 1975; Colomboand Grilli 2005; Dimov and Shepherd2005; Gimeno et al. 1997). The distinc-tion between generic and specific humancapital is context specific and as suchmay differ from prior studies that do notfocus on financial decision-making(Dimov and Shepherd 2005). In thecurrent research context, generic humancapital refers to the general knowledgeacquired by entrepreneurs through bothformal education and professional expe-rience, which is broad in application andnot directly related to the acquisition of

Figure 1Conceptual Framework

Van Auken(2001)

H3

H2

H1

HUMAN CAPITAL

Generic humancapital

Specific humancapital

SOCIAL CAPITAL

KNOWLEDGE OFFINANCE

ALTERNATIVES

FINANCEBEHAVIOR


financial resources. In our context, spe-cific human capital relates to educationand experience, which is directly appli-cable to financial decision-making(Dimov and Shepherd 2005).

We propose that entrepreneurs withhigher levels of generic human capitalwill experience a lower knowledge gapof finance alternatives compared withtheir peers with lower levels of generichuman capital. More specifically, weexpect a positive association between thelevel of education of entrepreneurs andtheir knowledge of finance alternatives.Higher education contributes to theability of entrepreneurs to analyze infor-mation, to develop skills to acquireknowledge independently, and to useknowledge in order to solve unforeseenproblems (Dochy, Segers, and Sluijsmans1999). Although higher education is gen-erally broad in its application and maynot directly provide knowledge relatedto financial decision-making, the argu-ments that were just given may explainwhy we expect educational attainment tobe positively related with higher knowl-edge of finance alternatives. This wouldprovide an additional explanation for therelation between education and theamount of finance raised (Robinson andSexton 1994).

Next to education, we propose a posi-tive association between entrepreneurialexperience and knowledge of financealternatives. There is a considerableamount of evidence that novice entrepre-

neurs differ from entrepreneurs withprior founding experience in manyimportant ways (Westhead and Wright1998; Wright, Robbie, and Ennew 1997).Entrepreneurs with higher levels of priorfounding experience and prior workexperience may have learned from theirexperience and as such may exhibit moreelaborate strategies for starting new ven-tures related to business planning,financing of the venture, and interactionswith external environments amongothers (Alsos and Kolvereid 1998; Mac-Millan 1986). Prior research further indi-cates how less experienced or noviceentrepreneurs conduct search routinesthat are narrower in terms of the amountof information collected compared withexperienced entrepreneurs that maydraw upon their previous business own-ership experience (Westhead, Ucbasaran,and Wright 2005). This implies thatentrepreneurs with more previous workand founding experience may search formore information on finance alternativesand their characteristics. The expertiseand broader search process, which maylead to a broader knowledge of financealternatives, may explain why experi-enced entrepreneurs raise start-upfinance more easily and in largeramounts (Starr and Bygrave 1991).1 Thisleads to our first hypothesis:

H1: Entrepreneurs with higher levels ofgeneric human capital have a greaterknowledge of finance alternatives

1The literature on experienced founders segments experienced founders into “portfolio”founders, that is, those who start ventures in a parallel fashion, and “serial” founders who startventures sequentially (Alsos and Kolvereid 1998; Westhead, Ucbasaran, and Wright 2005;Westhead and Wright 1998; Wright, Robbie, and Ennew 1997). Though these authors documentdifferences between types of experienced founders, following Hsu (2007), we do not focus onthe distinction between both types of entrepreneurs, as we are interested in contrastingexperienced entrepreneurs with novice entrepreneurs. Furthermore, 30 percent of our respon-dents are experienced entrepreneurs, with the vast majority (90 percent) of them beingportfolio entrepreneurs and only 10 percent of the experienced entrepreneurs being serialentrepreneurs. The limited number of serial entrepreneurs prevents us further from doing morerefined statistical analyses.


than entrepreneurs with lower levelsof generic human capital.

Arguments related to absorptivecapacity indicate that entrepreneurs willbe more likely to learn when theyperform tasks that are more related totheir prior experience and knowledgebase (Cohen and Levinthal 1990). Hence,the specific human capital of entrepre-neurs may turn out to be more valuablethan their generic human capital. Davids-son and Honig (2003), for instance, showhow specific human capital, which is ofimmediate relevance to the task at hand,is positively associated with entrepre-neurial discovery and the successfulexploitation of such discoveries. Thesame authors also show how the effect ofmore generic human capital indicatorswas weaker and less consistent.

Entrepreneurs with a business educa-tion may not only have developedgeneral problem-solving skills (Dochy,Segers, and Sluijsmans 1999) but maypossess more relevant knowledge withinthe finance domain compared with entre-preneurs with higher nonbusiness edu-cation or compared with entrepreneurswith less education (Dimov and Shep-herd 2005). Even if the knowledge onfinance alternatives acquired during theirbusiness studies might be outdated whenneeded, their specific knowledge maytrigger them to actively search for up-to-date information and enable them tomore easily acquire other finance-relatedknowledge (Cohen and Levinthal 1990).The knowledge of finance alternativesmay also benefit from specific experi-ence accumulated by entrepreneurs inthe accountancy or finance domain. It isexpected that individuals, who possessmore finance-related experience, will bemore aware about the value that differ-ent types of finance providers may bringto their ventures (Dimov and Shepherd2005). Direct experience with capitalacquisition is expected to further provideentrepreneurs with deeper knowledge of

multiple finance alternatives and theircharacteristics (Van Auken 2005). Thisleads to our second hypothesis:

H2: Entrepreneurs with higher levels ofspecific human capital have a greaterknowledge of finance alternativesthan entrepreneurs with lower levelsof specific human capital.

The above hypotheses are nontrivial,however. When entrepreneurs accumu-late experience in only one particulararea, this may increase the risk of enter-ing competency traps (Levinthal andMarch 1993). More experienced entre-preneurs may, for instance, becomeincreasingly trapped in current modes ofthought, thereby not recognizing thatsituations have changed and that thesechanging situations require newapproaches (Shepherd, Zacharakis, andBaron 2003; Starr and Bygrave 1991).Moreover, transferring routines fromprior experiences to new ones may besimilar to transferring old lessons to newenvironments where they do not fit(Haleblian and Finkelstein 1999). Assuch, experienced entrepreneurs may failto develop a more elaborate knowledgeof a broad range of finance alternatives.

Next to human capital, entrepreneurscan also learn about finance alternativesthrough their social capital (Hsu 2007).The central proposition in social capitaltheory refers to the ability of actors toextract benefits, for example, informa-tion, from their social structures, net-works, and memberships (Granovetter1985; Lin, Ensel, and Vaughn 1981). Ahigh level of social capital of the entre-preneur in the form of relationshipsbetween individuals is useful in obtain-ing information that would otherwise beunavailable or costly to locate (Granovet-ter 1985). Relationships with relevantindividuals and organizations provide anadvantage to entrepreneurs throughaccess to private information (Podolny1994). We claim that knowledgeable


relationships in the financial community,established before start-up, may alsoreduce information problems experi-enced by entrepreneurs, as they enableinformation transfer to entrepreneursabout potential finance alternatives andinvestor characteristics (Van Auken2005). For example, entrepreneurs thathave relationships with bankers are ableto discuss their specific financial needswith them (Ang 1992; Wright, Robbie,and Ennew 1997), allowing entrepre-neurs to gain a deeper understanding offinance alternatives. Relationships hencereduce information asymmetries on thedemand side of the market (Behr andGüttler 2007). This leads to our finalhypothesis:

H3: Entrepreneurs with more ties in thefinancial community have a greaterknowledge of finance alternativesthan entrepreneurs with fewer ties inthe financial community.

Research MethodData Collection Strategy

A random sample of 450 Flemish ven-tures founded between April 2008 andSeptember 2008 were selected from therecords of business incorporation as pro-vided by the Flemish government.2 Giventhe homogeneous sample frame, non-measured variance in terms of geo-graphical location and venture age isreduced. Moreover, survivorship and rec-ollection biases are limited by samplingventures close to the period of formation(Cassar 2004).

Between mid-November 2008 andmid-January 2009, all ventures were tele-phoned in order to identify whether ornot they fulfilled the conditions of ourresearch. Following Chandler and Hanks(1998), we exclude 118 subsidiaries orcompanies that merely changed theirlegal form from further study, as the

focus of this research is on real start-ups.Furthermore, 44 start-ups indicated theywere not interested in participating toour research. This resulted in a sample of288 independent start-ups, which weremailed a questionnaire. Several possibili-ties to complete and return the question-naire were offered, including e-mail, fax,post, and web survey. A total of 125questionnaires were returned after tele-phone recalls (response rate of 43percent). Comparing characteristics ofearly and late respondents, includingmanagement experience, experience inthe same industry and level of education,with Mann–Whitney tests, showed nosignificant differences between the twogroups. This indicates that the sample isunlikely to suffer from a nonresponsebias. The majority of respondents (84percent) completed the questionnaireusing the web survey. Since some ques-tionnaires were incomplete, the numberof responses used throughout this studyfurther decreases to 103. Some basiccharacteristics of our sample firms aresummarized in Table 1.

Almost all ventures (100 out of 103)are independent companies set up underthe initiative of the founding entrepre-neur. Three ventures are spin-outs of acorporate company. Almost one-third ofall ventures are active in professional,scientific, and technical activities (32.0percent) and another third in the whole-sale and retail trade industry (31.1percent). Other important industries arehotels and restaurants (8.7 percent), con-struction (7.8 percent), and informationand communication companies (7.8percent). Almost half of the ventures(44.7 percent) were founded with lessthan €20,000 start-up capital, whereas 11percent of the ventures were foundedwith more than €250,000 start-up capital.This shows that the initial size of theventures in the sample varies widely.

2Flanders is a region in Belgium.


The questionnaire was developedbased on previous research (Van Auken2001) and pretested through personalinterviews with entrepreneurs. Thesepretests allowed us to optimize the ques-tionnaire by including finance alterna-tives specific to the Flemish researchsetting and to make the questionnairecomprehensible for entrepreneurs. Thequestionnaire was organized in threemain sections. The first section collectedinformation about the venture, includingthe amount of start-up finance raised andthe industry in which the venture oper-ates. The second section asked respon-dents to what degree they are familiarwith various finance alternatives. Thefinal section of the questionnaire askeddetails on entrepreneurs’ education,prior experiences, and ties with financeexperts.

VariablesDependent Variables. A list of financealternatives was composed based on the

finance sources listed by Van Auken(2001) and government programs aimedat start-ups specific for the Flemishregion. The knowledge of the respon-dent with respect to the different financealternatives was measured on a seven-point Likert scale ranging from-3 = unaware of the existence of a par-ticular finance alternative to 3 = veryextensive knowledge, with 0 indicatingaverage knowledge. Hence, negativevalues on the scale represent below-average knowledge, and positive valuesrepresent above-average knowledge offinance alternatives. The disadvantage ofself-reported data is that entrepreneurscould be influenced by their perceptionsof what seems to be a desirable responserather than indicating their actual knowl-edge of finance alternatives. Neverthe-less, if this would be the case, we wouldexpect the average entrepreneur to indi-cate that he or she is more knowledge-able than average. This was not the case.On the contrary, as described further,

Table 1Characteristics of Sample Firms (n = 103)

Characteristic Frequency Percent

Origin of the companyIndependent company 100 97.1Corporate spin out 3 2.9

IndustryProfessional, scientific, and technical activities 33 32.0Wholesale and retail trade 32 31.1Hotels and restaurants 9 8.7Construction 8 7.8Information and communication 8 7.8Other 13 12.6

Amount of start-up capitalLess than €20,000 46 44.7€20,000–€50,000 21 20.4€50,001–€100,000 13 12.6€100,001–€250,000 12 11.6Greater than €250,000 11 10.7


many entrepreneurs even indicated thatthey are unaware of the existence ofparticular finance alternatives. To furthermotivate our respondents to give accu-rate data, we also promised strictconfidentiality.

Consistent with prior studies in entre-preneurial finance (Carter and VanAuken 2005; Winborg and Landström2001), we conducted an exploratoryfactor analysis to identify groups offinance alternatives. Factor analysis is adata reduction technique that reduces alist of measures to their essence, that is,a smaller set of factors that capture pat-terns in the data (Hair et al. 1998). Thishas two major advantages. First, factoranalysis enabled us to identify groups offinance alternatives that are highlyrelated to each other. This allows us todraw conclusions that are more general-izable. Second, if we would study theknowledge of entrepreneurs on eachindividual finance alternative, we wouldhave to test specific models for each ofthe 14 finance alternatives studied.Testing a large number of models onrelated dependent variables increases theprobability of finding significant relation-ships that are merely due to chance.3

Table 2 presents the results of thefactor analysis. The Kaiser–Meyer–Olkinmeasure is 0.868 and Bartlett’s test is0.000, implying that a factor analysis ismeaningful (Hair et al. 1998). Onlyfactors with an eigenvalue larger than 1are included in further analyses. Thisprocedure yields three factors, capturing69 percent of the total variance aftervarimax rotation. The factors are broadlyconsistent with those identified by Van

Auken (2001). Factor one captures theknowledge of five traditional and com-monly used finance alternatives: loans,credit lines, trade credit, leasing, andfriends and family financing (Cronbach’salpha = 0.875). Factor two (advancedfinance alternatives for the start-upphase) captures the knowledge of fourspecific finance alternatives targetedtoward start-ups (Cronbach’salpha = 0.742). Besides Business Angelsfinancing, three specific governmentmeasures (IWT-subsidy, Vinnof, andARKimedes) are included. Factor threecaptures the knowledge of five advancedfinance alternatives targeted towardgrowth-oriented ventures: public andprivate equity, bonds, factoring, andventure capital (Cronbach’salpha = 0.887). Given the high Cron-bach’s alpha reliability coefficients of thethree factors, these factors are used asvariables in the multivariate analyses.The variables were calculated bysumming the values for the items thatcompose the respective factors anddividing it by the number of items.

The knowledge of finance alternativesis limited to very limited: the three aggre-gated variables, as well as many of theindividual finance alternatives, havenegative mean values. Unsurprisingly,the best known finance methods arecommon finance alternatives (-0.10).Within the group of common financealternatives, some finance options evenhave a positive average knowledgeincluding bank loans (0.14) and leasing(0.11). The knowledge of advancedfinance alternatives for the start-up phase(-2.41) and growth phase (-1.31) is

3We thank one of our reviewers for pointing out that the use of factor analysis may also havelimitations. For instance, we lose more fine-grained information on the individual financealternatives. In order to test for the robustness of our findings, we also ran regressions usingeach individual finance alternative as a dependent variable. These additional regressions largelyconfirm the main conclusions drawn from using the broader groups of finance alternatives asidentified by the factor analysis. These more fine-grained analyses are available from theauthors upon request.


lower. The advanced finance alternativesfor the start-up phase are the leastknown by the entrepreneurs. Theaverage knowledge of finance alterna-tives like Vinnof and ARKimedes are allbelow -2.50, where -3 indicates thatentrepreneurs are unaware of the exist-ence of these finance alternatives.

Independent Variables. Descriptive sta-tistics and correlations between depen-dent, independent, and control variablesare presented in Table 3. The key inde-pendent variables measure the humanand social capital of the founding entre-preneur. Scholars generally distinguishbetween specific and generic humancapital on the basis of whether education

and experience in a particular domainprovide skills that are directly relevantfor carrying out specific activities(Becker 1975; Dimov and Shepherd2005; Gimeno et al. 1997). In this study,the generic human capital of the found-ing entrepreneur relates to overall edu-cation and practical experience with ascope of application that is typicallybroader and not limited to financialdecision-making, whereas specifichuman capital relates to education andexperience that is directly relevant forfinance decisions in the entrepreneurialventures. Higher education can be con-sidered more general in its contributionto human capital (Dimov and Shepherd2005). Higher education in humanities or

Table 2Descriptive Statistics and Rotated Orthogonal Factor

Analysis for Knowledge of Finance Alternatives (n = 103)

Finance alternatives Mean StandardDeviation

Factor

1 2 3

Common finance alternatives -0.10 1.00Loans 0.14 1.09 0.89 0.03 0.18Credit lines -0.15 1.33 0.88 0.11 0.17Trade credit -0.37 1.38 0.68 0.17 0.43Leasing 0.11 1.04 0.72 0.13 0.24Friends and familyfinancing

-0.39 1.26 0.64 0.10 0.28

Advanced finance alternativesfor the start-up phase

-2.41 0.83

Vinnof -2.76 0.79 -0.03 0.82 0.15IWT-subsidy -2.43 1.23 0.12 0.78 -0.01ARKimedes -2.59 0.91 0.13 0.76 0.21Business angels -1.99 1.37 0.36 0.58 0.39

Advanced finance alternativesfor the growth phase

-1.31 1.13

Public stock -1.35 1.24 0.22 0.12 0.88Private stock -1.05 1.36 0.19 0.10 0.85Bonds -0.93 1.21 0.31 0.17 0.68Factoring -1.65 1.58 0.46 0.22 0.61Venture capital -1.68 1.47 0.44 0.44 0.60


Tab

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Des

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Tab

le3

Con

tin

ued

Var

iable

sA

bbre

viat

ion

Min

Max

Mea

nSta

ndar

dD

evia

tion

Corr

elat

ion

12

34

56

78

9

Spec

ific

Hum

anCap

ital

10B

usi

nes

sEduca

tion

(Dum

my)

Busi

nes

sEduca

tion

0.00

1.00

0.35

0.48

0.39

50.

200

0.47

40.

219

-0.2

280.

057

0.03

30.

162

0.15

711

Num

ber

of

Yea

rsof

Work

Exp

erie

nce

Gai

ned

by

Founder

sin

the

Indust

ryof

Acc

ounta

ncy

or

Finan

ce

Exp

erie

nce

inA

ccounta

ncy

or

Finan

ce

0.00

40.0

01.

274.

820.

327

0.18

80.

338

0.06

6-0

.107

0.07

2-0

.044

-0.0

110.

066

Soci

alCap

ital

12Rel

atio

nsh

ips

inth

eFi

nan

cial

Com

munity

Rel

atio

nsh

ips

inFi

nan

cial

Com

munity

-1.0

01.

000.

340.

450.

248

0.20

40.

190

0.04

40.

036

-0.1

39-0

.123

0.13

20.

044

Contr

ol

Var

iable

s13

Tar

gete

dN

um

ber

of

Em

plo

yees

afte

r5

Yea

rsN

um

ber

of

Em

plo

yees

0.00

90.0

05.

1613

.14

0.14

90.

145

0.21

60.

086

0.12

6-0

.152

0.17

00.

024

0.04

3

14Fi

nan

cial

Pla

nnin

g(D

um

my)

Finan

cial

Pla

nnin

g0.

001.

000.

920.

270.

153

-0.0

130.

204

0.14

90.

003

0.06

80.

147

-0.0

220.

026

15Sh

ares

100%

Ret

ained

by

the

Entr

epre

neu

rial

Tea

m(D

um

my)

Ext

ernal

Shar

ehold

ers

0.00

1.00

0.90

0.30

0.10

50.

074

0.16

60.

242

0.08

8-0

.117

-0.1

600.

097

0.06

6

16Ln

(Lev

elof

Star

t-U

pCap

ital

)St

art-U

pCap

ital

2.56

15.4

210

.14

2.28

0.36

6-0

.001

0.14

40.

058

-0.1

21-0

.078

-0.2

470.

106

0.09

317

Indust

ry:

Whole

sale

and

Ret

ail

(Dum

my)

Indust

rySa

les

0.00

1.00

0.31

0.47

-0.1

11-0

.204

-0.2

10-0

.108

-0.1

170.

114

-0.1

83-0

.039

-0.0

1518

Indust

ry:

Pro

fess

ional

,Sc

ientific

and

Tec

hnic

alA

ctiv

itie

s(D

um

my)

Indust

ryA

ctiv

itie

s0.

001.

000.

320.

470.

217

0.35

50.

272

0.23

20.

168

-0.0

070.

324

-0.0

53-0

.211


Tab

le3

Con

tin

ued

Var

iable

sA

bbre

viat

ion

Min

Max

Mea

nSta

ndar

dD

evia

tion

Corr

elat

ion

10

11

12

13

14

15

16

17

18

Spec

ific

Hum

anCap

ital

10B

usi

nes

sEduca

tion

(Dum

my)

Busi

nes

sEduca

tion

0.00

1.00

0.35

0.48

1.00

011

Num

ber

of

Yea

rsof

Work

Exp

erie

nce

Gai

ned

by

Founder

sin

the

Indust

ryof

Acc

ounta

ncy

or

Finan

ce

Exp

erie

nce

inA

ccounta

ncy

or

Finan

ce

0.00

40.0

01.

274.

820.

264

1.00

0

Soci

alCap

ital

12Rel

atio

nsh

ips

inth

eFi

nan

cial

Com

munity

Rel

atio

nsh

ips

inFi

nan

cial

Com

munity

-1.0

01.

000.

340.

450.

059

0.02

21.

000

Contr

ol

Var

iable

s13

Tar

gete

dN

um

ber

of

Em

plo

yees

afte

r5

Yea

rsN

um

ber

of

Em

plo

yees

0.00

90.0

05.

1613

.14

0.03

30.

038

-0.0

641.

000

14Fi

nan

cial

Pla

nnin

g(D

um

my)

Finan

cial

Pla

nnin

g0.

001.

000.

920.

270.

137

0.06

2-0

.064

0.06

41.

000

15Sh

ares

100%

Ret

ained

by

the

Entr

epre

neu

rial

Tea

m(D

um

my)

Ext

ernal

Shar

ehold

ers

0.00

1.00

0.90

0.30

0.03

40.

032

0.17

6-0

.212

0.15

01.

000

16Ln

(Lev

elof

Star

t-U

pCap

ital

)St

art-up

Cap

ital

2.56

15.4

210

.14

2.28

0.22

30.

231

0.06

50.

104

0.08

80.

059

1.00

017

Indust

ry:

Whole

sale

and

Ret

ail

(Dum

my)

Indust

rySa

les

0.00

1.00

0.31

0.47

-0.0

52-0

.015

0.07

4-0

.097

0.19

50.

078

0.12

21.

000

18In

dust

ry:

Pro

fess

ional

,Sc

ientific

and

Tec

hnic

alA

ctiv

itie

s(D

um

my)

Indust

ryA

ctiv

itie

s0.

001.

000.

320.

470.

151

0.09

10.

174

-0.0

58-0

.034

0.01

4-0

.062

-0.4

611.

000

a Corr

elat

ion

coef

fici

ents

sign

ifica

nt

atp

<.0

5ar

esh

ow

nin

bold

.


science for instance generally does notprovide skills directly related to financialdecision-making by entrepreneurs. Weinclude a dummy variable higher educa-tion, which is equal to 1 if the entrepre-neur has a university-level or equivalentdegree and 0 otherwise. Almost three-quarters of the entrepreneurs have auniversity-level or equivalent education.

Similarly, prior work experience isvery broad and includes multiple tasksthat may not directly relate to financialdecision-making but may neverthelessenhance an entrepreneur’s informationprocessing and decision-making skills.The number of years of work experi-ence by the entrepreneur in the sameindustry and the number of years ofwork experience in other industriesproxy for entrepreneurs’ general humancapital. Before starting their venture,entrepreneurs have on average nineyears of work experience in the sameindustry as their start-up venture andsix years in another industry. Wefurther include management experience,which is measured by a dummy vari-able equal to 1 if the entrepreneur pre-viously held a management position ina company employing more than 100people and 0 otherwise. About one infive entrepreneurs have previous man-agement experience. Self-employmentexperience is measured by a dummyvariable equal to 1 if the entrepreneurhas prior self-employment experienceand 0 otherwise. One-third of the entre-preneurs have prior self-employmentexperience. Finally, start-up experienceis measured by a dummy variable equalto 1 if the entrepreneur has priorstart-up experience and 0 otherwise.Although entrepreneurs that have priorstart-up experience may have searchedfor finance in the past, prior start-upexperience is much broader in its appli-cation during new business formation(Alsos and Kolvereid 1998). Moreover,it is not necessarily the case thatentrepreneurs with prior start-up expe-

rience have experience directly relatedto financial decision-making, sinceentrepreneurs may have restrictedthemselves to personal sources offinance in the past (Van Auken andNeeley 1996) or cofounders may havefocused on the finance aspect in previ-ous businesses due to functional spe-cialization (Maurer and Ebers 2006).Hence, previous start-up experience isconsidered to contribute to an entrepre-neur’s generic human capital but not tothe specific human capital. Close to 30percent of the entrepreneurs havestart-up experience, which is in linewith findings from other studies (Birleyand Westhead 1993; Hsu 2007).

Contrary to generic human capital,which is broad in its application, specifichuman capital relates to the entrepre-neur’s education and experience that isdirectly valuable for financial decision-making. Business education is likely toequip entrepreneurs with a toolset forfinancial decision-making and hence con-tributes more to specific human capital asopposed to general human capital(Dimov and Shepherd 2005). It is mea-sured by a dummy variable, which equals1 if the entrepreneur has a degree inbusiness and 0 otherwise. Approximately35 percent of all entrepreneurs have adegree in the field of business. Moreover,prior experience in accountancy orfinance domains is likely to be particu-larly relevant for financial decision-making. We therefore include the numberof years of work experience in accoun-tancy and/or finance as another measureof specific human capital. About 16percent of the entrepreneurs have previ-ous work experience in the field ofaccountancy or finance. These entrepre-neurs have on average eight years ofexperience in the field of accountancy orfinance.

The social capital variable is measuredwith a six-item five-point Likert scaleranging from -2 = strongly disagree to+2 = strongly agree, about network ties


between the entrepreneur and financeexperts, adapted from the items of Shaneand Cable (2002). A finance expert isdefined as an individual with correct andreliable information about finance alter-natives. The items are: “Prior to the com-pany’s start-up, I had a professionalrelationship with at least one financeexpert”; “Prior to the company’s start-up,at least one finance expert was someonewith whom I had engaged in informalsocial activity (for example, playingtennis, going to the movies)”; “Prior to thecompany’s start-up, at least one financeexpert was a personal friend”; “Someonewhom I trust to discuss important confi-dential matters knew at least one financeexpert”; “A third party whose judgment Itrust can bring me in contact with afinance expert”; and “Through mynetwork of contacts, I could obtain infor-mation from a finance expert.”

An exploratory factor analysis is under-taken in order to identify whether allitems were measuring the same construct.The Kaiser–Meyer–Olkin measure is0.819 and Bartlett’s test is 0.000, implyingthat a factor analysis is meaningful (Hairet al. 1998). Only one factor with aneigenvalue larger than 1 was extracted. Asa result, the six items that were just givenare measures for the same construct(Cronbach’s alpha = 0.863). The socialcapital variable is calculated by taking theaverage of the values for the six items.Entrepreneurs report an average level ofsocial capital of 0.34.

Control Variables. Entrepreneurs withgrowth ambitions may have more thor-oughly prepared the start-up of theirventure and hence have acquired abetter knowledge of finance alternatives.

We therefore control for the expectedgrowth rate, which is measured as thetarget number of employees (in full timeequivalents) five years after start-up.The average employment target equalsapproximately five employees with amaximum of 90 employees.4 In order tofurther control for preparation, adummy variable measures whether ornot the entrepreneur performed formalfinancial planning before start-up.Almost all entrepreneurs (92 percent)indicate that they performed formalfinancial planning before start-up. Wealso distinguish between start-ups withand without external shareholders, witha dummy variable equal to 1 if there areexternal shareholders and 0 otherwise.If external shareholders are involved,the knowledge base is likely to bebroader. Only 10 percent of the start-ups have external shareholders. In orderto account for the initial size of theventure, we include the natural loga-rithm of start-up capital as a control.Entrepreneurs setting up larger start-upsmay have a higher knowledge offinance alternatives. Finally, we controlfor industry effects. We created twoindustry dummy variables, “Wholesaleand retail” and “Professional, scientificand technical activities.” More than 60percent of the start-ups are active inthese two industries.

Correlations across explanatory vari-ables are generally low and do not indi-cate the existence of multicollinearityproblems.

ResultsMain Findings

As the dependent variables are cen-sored, the multivariate relationships

4We used targeted turnover after five years as an alternative proxy for the expected growth rate.Unfortunately, only 78 respondents filled in the targeted turnover after five years. Thecorrelation between the targeted number of employees and the targeted turnover after fiveyears is 0.348. Using this variable rather than the targeted number of employees leads toqualitatively similar results.


between the dependent variables andindependent variables are analyzed withTobit regressions. Table 4 panel“Common” contains the regressionmodels with the knowledge of commonfinance methods as dependent variable,panel “Start-up Advanced” contains themodels with the knowledge ofadvanced finance methods for thestart-up phase as dependent variable,and panel “Growth Advanced” containsthe models with the knowledge ofadvanced finance methods for thegrowth phase as dependent variable.Three models are reported in eachpanel. The first model in each panelonly includes the control variables. Thesecond model includes the humancapital variables next to the controlvariables from the first model. The thirdmodel in each panel is the full model,including control variables, humancapital, and social capital variables. Asthe significance and the sign of thecoefficients are broadly consistent inthe three models within each panel, thediscussion of the results will focus onthe full models. Adding human capitalvariables significantly improves allmodel fits, whereas adding the socialcapital variable significantly improvesthe models explaining the knowledgeof common finance methods and ofadvanced finance methods for thegrowth phase.

The coefficients of the control vari-ables show that entrepreneurs withhigher growth aspirations have a signifi-cantly higher knowledge of all financealternatives. A higher level of start-upcapital is associated with a higher know-ledge of common finance techniques(p < 0.01). Interestingly, entrepreneurs ofcompanies active in the industry of“Wholesale and retail” have a signifi-cantly lower knowledge of commonfinance methods (p < .05) and advancedfinance methods for the growth phase(p < .05). Entrepreneurs of companiesactive in the industry of “Professional,

scientific and technical activities” have asignificantly higher knowledge ofadvanced finance methods for thestart-up phase (p < 0.1).

In order to test the first hypothesis,we examine the impact of generichuman capital variables on the know-ledge of finance alternatives. Neitherhigher education nor experience in thesame industry has an impact on theknowledge of finance alternatives.Experience in other industries has apositive impact on the knowledge ofcommon finance alternatives (p < 0.01)and advanced finance alternatives forthe growth phase (p < 0.1). Entrepre-neurs with previous start-up experience,however, have a lower knowledge ofcommon finance alternatives (p < .05).Experience as a self-employed andoverall management experience have noimpact on an entrepreneur’s knowledgeof finance alternatives. Overall, supportfor H1 is weak.

The impact of specific human capitalon the knowledge of finance alternativesis more pronounced. Specific humancapital leads to a significantly higherknowledge of finance alternatives, espe-cially of common finance alternativesand of advanced finance alternatives forthe growth phase. More specifically, bothbusiness education and experience inaccountancy or finance lead to signifi-cantly higher knowledge of commonfinance alternatives (p < .05) andadvanced finance alternatives for thegrowth phase (p < 0.01). Overall, theseresults strongly support H2.

The social capital of entrepreneurs issignificantly associated with their knowl-edge of finance alternatives in severalmodel specifications. Specifically, entre-preneurs who have network ties withfinance experts have a greater knowl-edge of common finance alternatives(p < 0.001) and advanced finance alterna-tives for the growth phase (p < .05).These findings provide strong supportfor H3.


Tab

le4

Mult

ivar

iate

Tobit

Reg

ress

ion

Model

s(n

=103)

Com

mon

Sta

rt-U

pA

dva

nce

dG

row

thA

dva

nce

d

Model

1M

odel

2M

odel

3M

odel

1M

odel

2M

odel

3M

odel

1M

odel

2M

odel

3

Const

ant

-2.6

57**

*-2

.480

***

-2.6

08**

*-3

.556

***

-3.0

82**

*-3

.177

***

-3.4

99**

*-3

.315

***

-3.4

31**

*C

ontr

ol

Var

iable

sN

um

ber

of

Em

plo

yees

0.01

10.

013†

0.01

3*0.

020*

0.01

7†0.

018†

0.02

2*0.

019*

*0.

019*

*Fi

nan

cial

Pla

nnin

g(D

um

my)

0.44

10.

251

0.35

7-0

.002

-0.0

630.

010

0.76

8†0.

427

0.51

0Ext

ernal

Shar

ehold

ers

(Dum

my)

0.33

60.

415

0.30

00.

535

0.24

80.

184

0.71

9*0.

663†

0.57

3†St

art-up

Cap

ital

0.16

6***

0.12

8**

0.12

9**

-0.0

07-0

.077

-0.0

740.

062

0.01

20.

013

Indust

rySa

les

(Dum

my)

-0.1

49-0

.273

-0.4

36*

-0.1

88-0

.129

-0.1

89-0

.373

-0.3

90†

-0.5

15*

Indust

ryA

ctiv

itie

s(D

um

my)

0.49

9*0.

234

0.03

00.

868*

*0.

748*

0.66

5†0.

601*

0.22

10.

053

Indep

enden

tV

aria

ble

sH

um

anCap

ital

Gen

eric

Hum

anCap

ital

Hig

her

Educa

tion

(dum

my)

0.15

90.

143

0.38

10.

371

0.23

70.

225

Exp

erie

nce

Sam

eIn

dust

ry-0

.003

-0.0

03-0

.007

-0.0

060.

015

0.01

6Exp

erie

nce

Oth

erIn

dust

ry0.

032*

0.03

9**

-0.0

07-0

.003

0.02

00.

027†

Man

agem

ent

Exp

erie

nce

(Dum

my)

-0.0

570.

025

-0.0

30-0

.015

0.14

50.

204

Exp

erie

nce

Self-E

mplo

ymen

t(D

um

my)

0.14

10.

079

0.63

5†0.

584

0.11

70.

061

Exp

erie

nce

Star

t-U

p(D

um

my)

-0.4

44†

-0.4

93*

-0.0

61-0

.065

-0.1

43-0

.174

Spec

ific

Hum

anCap

ital

Busi

nes

sEduca

tion

(Dum

my)

0.48

0*0.

462*

0.42

00.

402

0.86

2***

0.85

7***

Exp

erie

nce

inA

ccounta

ncy

or

Finan

ce0.

054*

0.06

5*0.

040

0.04

00.

051*

0.05

1**

Soci

alCap

ital

Rel

atio

nsh

ips

inFi

nan

cial

Com

munity

0.67

0***

0.29

90.

539*

McF

adden

’sPse

udo

R2

0.09

50.

192

0.23

60.

062

0.11

40.

118

0.08

20.

177

0.19

7Pro

b>

[chi

sym

bol]2

0.00

00.

000

0.00

00.

012

0.00

70.

009

0.00

00.

000

0.00

0Lo

glikel

ihood

-134

.300

-120

.000

-113

.400

-123

.400

-116

.500

-116

.000

-148

.700

-133

.200

-130

.000

Wher

e†p

<.1

;*p

<.0

5;**

p<

.01;

***p

<.0

01(c

onse

rvat

ive

two-tai

led

test

s).


Robustness TestsAdditional models were tested in

order to provide evidence with respect tothe robustness of our main findings.5

First, many entrepreneurs may not needthe wide range of finance alternativesincluded in our study. Hence, one couldargue that the existence of a knowledgegap is likely to be less problematic forentrepreneurs who do not require largeamounts of finance. Entrepreneurs withhigher growth aspirations are known torealize higher growth rates (Wiklund andShepherd 2003) and hence are morelikely to need multiple sources of financebesides owner funds (Vanacker andManigart 2010). Nonparametric testscomparing entrepreneurs with highversus low growth aspirations (mediansplit) show no significant differences inthe knowledge of finance alternativesbetween these two types of entrepre-neurs: the knowledge of finance alterna-tives of entrepreneurs with high growthaspirations is equally limited comparedwith that of entrepreneurs with limitedgrowth aspirations. Hence, entrepre-neurs who will likely need to raise morefinance from more diverse sources tofulfill their growth aspirations start withan equally low knowledge of financealternatives. Furthermore, in the sub-sample of entrepreneurs with highgrowth ambitions, specific human capitalin the form of business education andyears of experience in accountancy orfinance is associated with an enhancedknowledge of common finance alterna-tives and advanced finance alternativesfor the growth phase. Relationships inthe financial community are also posi-tively associated with the knowledge ofadvanced finance alternatives for thegrowth phase. This indicates that theresults from a subsample of entrepre-neurs with high growth aspirations are

broadly similar to those provided for theentire sample including all entrepre-neurs. Specific human capital and socialcapital of entrepreneurs with highgrowth aspirations are associated withhigher knowledge of finance alterna-tives, providing support for H2 and H3.High growth-oriented entrepreneurswith high levels of generic human capitaldo not necessarily report higher knowl-edge of finance alternatives, hence pro-viding only weak support for H1.

Second, additional control variableswere added to the regression models,including the gender of the foundingentrepreneur, number of founders, andfounder’s age. The main results remainqualitatively similar when these addi-tional control variables are included, butthis reduces the sample size. Femaleentrepreneurs exhibit different financebehaviors compared with their malecounterparts (Coleman 2000; Greeneet al. 2001; Neeley and Van Auken 2010).Our findings show that female entrepre-neurs are less knowledgeable ofadvanced finance alternatives for thegrowth phase, potentially partly explain-ing the difference in finance behavior.The larger the number of founders, thegreater the tangible and knowledge-based resources they will have available(Colombo and Grilli 2005). Nevertheless,the number of founders is negativelyassociated with the knowledge ofadvanced finance alternatives for thegrowth phase. Finally, the age of thefounding entrepreneur is added. Thoughthe age of the entrepreneur may serve asa proxy for generic human capital, weincluded more detailed measures (includ-ing their educational background andwork experiences) in our regressions,which, when combined, should reflectthe age of entrepreneurs. The age ofthe founding entrepreneur is negatively

5These additional tests are not reported due to space considerations but available from theauthors upon simple request.


associated with the knowledge ofadvanced finance alternatives for thestart-up phase.

Finally, we implicitly assumedthroughout this paper that the know-ledge of finance alternatives will influ-ence finance behavior. Van Auken (2001)indeed demonstrates that limited know-ledge of finance alternatives hampers theability of entrepreneurs to price andnegotiate investments. We study newventures, and no data are available yeton the finance decisions in these ven-tures after start-up. Nevertheless, non-parametric tests (further supported withthe regressions in Table 4) indicate thatentrepreneurs who raise more start-upfinance have a higher knowledge ofcommon finance alternatives. This pro-vides at least some explicit evidence thatwithin our research context the amountof start-up capital raised is positivelyassociated with the knowledge of financealternatives, which is of significant inter-est given the evidence on the undercapi-talization of many private ventures(Holtz-Eakin, Joulfaian, and Rosen 1994).

Discussion andConclusion

It is widely acknowledged that finan-cial resource acquisition is a key processin the start-up and growth of new busi-nesses. Traditional finance theories gen-erally emphasize wealth maximization asan overarching goal, rational behavior ofall actors, and prefect information(Brealey and Myers 2000). In such a theo-retical setting, financial decision-makingis straightforward: all value creatinginvestment projects will find sufficientfinance, and finance decisions will notinfluence firm value (Modigliani andMiller 1958). In practice, however, theprocess of acquiring sufficient andadequate finance is fraught with difficul-ties, especially for small and new ven-tures. Scholars have argued thatinformation asymmetries between inves-tors and entrepreneurs may constrain the

supply of finance toward young and smallentrepreneurial ventures (Berger andUdell 1998). Theories building on theexistence of information asymmetriestypically assume that (potential) investorsare informationally constrained, which isexpected to influence their investmentdecisions (Wright and Robbie 1998). Thispaper highlights a second informationasymmetry problem, namely the fact thatentrepreneurs do not have full informa-tion of finance alternatives. This knowl-edge gap may lead entrepreneurs to selectonly these finance alternatives they arefamiliar with, potentially leading to sub-optimal finance structures (Gibson 1992;Van Auken 2001, 2005).

The main contribution of this paperlies in the finding that entrepreneurs withhigher levels of specific human capitaland higher levels of social capital experi-ence lower knowledge gaps. Consistentwith prior research, we find that specifichuman capital is more valuable thangeneric human capital (Davidsson andHonig 2003). Specific human capital, thatis, business education and previous expe-rience in accountancy or finance,increases an entrepreneur’s knowledge offinance alternatives. Generic humancapital in the form of higher education orgeneral experience has a more modestand less consistent impact. The socialcapital of entrepreneurs at start-up, andmore specifically their ties to financeexperts, is positively associated with theirknowledge of finance alternatives.Overall, we contribute to a further socia-lizing of the finance acquisition process inentrepreneurial ventures (Shane andCable 2002) by demonstrating the keyrole of entrepreneurial characteristics onentrepreneurs’ knowledge of financealternatives in start-ups. This is critical asa good knowledge of finance alternativesis the basis for making good financialdecisions (Gibson 1992).

We have shown that entrepreneurs’knowledge of finance alternatives ingeneral is rather limited. Even the know-


ledge of commonly used finance methodsis limited. More complex finance options,specifically targeted toward growth-oriented ventures, are even less known.The advanced finance methods targetedat start-ups is the least known category.Though the specific human capital andsocial capital of entrepreneurs explaindifferences in their knowledge ofcommon finance alternatives and ofadvanced finance alternatives for thegrowth phase, these entrepreneurial char-acteristics are not associated with theirknowledge of advanced finance alterna-tives for the start-up phase. This may bedriven by the fact that there is little varia-tion in the knowledge of the latter, aswitnessed by the low standard deviationof this variable. Almost all entrepreneursreported that they either are unaware ofthese finance alternatives, or that theirknowledge thereof is very limited. Hence,the government programs specifically tar-geted toward start-ups are badly knownby all entrepreneurs, even those with highlevels of human and social capital.

This finding is broadly consistent withprevious findings of Van Auken (2001)for U.S. entrepreneurs and Audet,Berger-Douce, and St-Jean (2007) forCanadian entrepreneurs. Two potentialexplanations have been advanced forthis general lack of knowledge of gov-ernment programs (Audet, Berger-Douce, and St-Jean 2007; Stevenson andLundström 2002). First, many entrepre-neurs do not seem to understand theutility or relevance of the governmentprograms. Second, entrepreneurs maynot need or may not be eligible forseveral of these government programs.We demonstrate how some entrepre-neurs are simply unaware of the exist-ence of government programs targetedspecifically toward start-ups. Whenentrepreneurs are unaware of govern-ment programs, they are both unable tojudge their utility and unable to judgewhether or not their ventures are eligiblefor such programs.

A methodological strength of thisstudy is that all social and human capitalvariables are measured at start-up, henceeliminating survival and recall biases. Itwould be interesting to add a longitudi-nal dimension to the current research.This would allow understanding how theinitial knowledge gap influences subse-quent finance and growth processes. Isthe knowledge gap of an entrepreneur atstart-up a major hindrance in the devel-opment of the start-up, or is the entre-preneur able to overcome this liabilitythrough subsequent learning and experi-ence? Moreover, the importance of aknowledge gap may be more or less criti-cal depending upon the growth ambi-tions of entrepreneurs and theirintention to remain independent. Forinstance, it might well be that a limitedknowledge of finance alternatives willconstrain high growth-oriented entrepre-neurs more than low growth-orientedentrepreneurs who have a lower needfor resources. These are importantavenues for future research.

The study suggests implications forpolicymakers and for entrepreneurs. Therole of business education is highlighted.Strengthening lifelong education forentrepreneurs on business in general andon financial matters in particular is war-ranted. Furthermore, when new policyinitiatives are developed, frequent andclear communication with the targetgroup and their advisors is key. Thisstudy suggests that well-designed initia-tives often fail to capture the attention oftheir target group.

Entrepreneurs should understand thatfinance is a key resource for their busi-ness; failure to understand the financealternatives and their characteristics mayseriously hamper the development oftheir ventures. Most entrepreneurs,however, have a limited knowledge offinance options, even if they have abroad business experience. They mayenhance their understanding of financethrough training. Furthermore, they


should understand that links to financialexperts are valuable in reducing theknowledge gap. If they do not have tieswith finance experts yet, they shouldactively seek to establish them. More-over, when entrepreneurs already havelinks to experts, they should actively taptheir knowledge.

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